Merge pull request #5338 from freqtrade/new_release

New release 2021.7

.devcontainer/devcontainer.json

@@ -1,11 +1,20 @@
 {
     "name": "freqtrade Develop",
-
-    "dockerComposeFile": [
-        "docker-compose.yml"
+    "build": {
+        "dockerfile": "Dockerfile",
+        "context": ".."
+    },
+    // Use 'forwardPorts' to make a list of ports inside the container available locally.
+    "forwardPorts": [
+        8080
     ],
+    "mounts": [
+        "source=freqtrade-bashhistory,target=/home/ftuser/commandhistory,type=volume"
+    ],
+    // Uncomment to connect as a non-root user if you've added one. See https://aka.ms/vscode-remote/containers/non-root.
+    "remoteUser": "ftuser",
 
-    "service": "ft_vscode",
+    "postCreateCommand": "freqtrade create-userdir --userdir user_data/",
 
     "workspaceFolder": "/freqtrade/",
 
@@ -25,20 +34,6 @@
         "ms-python.vscode-pylance",
         "davidanson.vscode-markdownlint",
         "ms-azuretools.vscode-docker",
+        "vscode-icons-team.vscode-icons",
     ],
-
-    // Use 'forwardPorts' to make a list of ports inside the container available locally.
-    // "forwardPorts": [],
-
-    // Uncomment the next line if you want start specific services in your Docker Compose config.
-    // "runServices": [],
-
-    // Uncomment the next line if you want to keep your containers running after VS Code shuts down.
-    // "shutdownAction": "none",
-
-    // Uncomment the next line to run commands after the container is created - for example installing curl.
-    // "postCreateCommand": "sudo apt-get update && apt-get install -y git",
-
-    // Uncomment to connect as a non-root user if you've added one. See https://aka.ms/vscode-remote/containers/non-root.
-    "remoteUser": "ftuser"
 }

.devcontainer/docker-compose.yml

@@ -1,24 +0,0 @@
----
-version: '3'
-services:
-  ft_vscode:
-    build:
-      context: ..
-      dockerfile: ".devcontainer/Dockerfile"
-    volumes:
-      # Allow git usage within container
-      - "${HOME}/.ssh:/home/ftuser/.ssh:ro"
-      - "${HOME}/.gitconfig:/home/ftuser/.gitconfig:ro"
-      - ..:/freqtrade:cached
-      # Persist bash-history
-      - freqtrade-vscode-server:/home/ftuser/.vscode-server
-      - freqtrade-bashhistory:/home/ftuser/commandhistory
-    # Expose API port
-    ports:
-      - "127.0.0.1:8080:8080"
-    command: /bin/sh -c "while sleep 1000; do :; done"
-
-
-volumes:
-  freqtrade-vscode-server:
-  freqtrade-bashhistory:

.github/workflows/ci.yml

@@ -79,13 +79,13 @@ jobs:
 
     - name: Backtesting
       run: |
-        cp config_bittrex.json.example config.json
+        cp config_examples/config_bittrex.example.json config.json
         freqtrade create-userdir --userdir user_data
         freqtrade backtesting --datadir tests/testdata --strategy SampleStrategy
 
     - name: Hyperopt
       run: |
-        cp config_bittrex.json.example config.json
+        cp config_examples/config_bittrex.example.json config.json
         freqtrade create-userdir --userdir user_data
         freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt --hyperopt-loss SharpeHyperOptLossDaily --print-all
 
@@ -172,13 +172,13 @@ jobs:
 
     - name: Backtesting
       run: |
-        cp config_bittrex.json.example config.json
+        cp config_examples/config_bittrex.example.json config.json
         freqtrade create-userdir --userdir user_data
         freqtrade backtesting --datadir tests/testdata --strategy SampleStrategy
 
     - name: Hyperopt
       run: |
-        cp config_bittrex.json.example config.json
+        cp config_examples/config_bittrex.example.json config.json
         freqtrade create-userdir --userdir user_data
         freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt --hyperopt-loss SharpeHyperOptLossDaily --print-all
 
@@ -239,13 +239,13 @@ jobs:
 
     - name: Backtesting
       run: |
-        cp config_bittrex.json.example config.json
+        cp config_examples/config_bittrex.example.json config.json
         freqtrade create-userdir --userdir user_data
         freqtrade backtesting --datadir tests/testdata --strategy SampleStrategy
 
     - name: Hyperopt
       run: |
-        cp config_bittrex.json.example config.json
+        cp config_examples/config_bittrex.example.json config.json
         freqtrade create-userdir --userdir user_data
         freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt --hyperopt-loss SharpeHyperOptLossDaily --print-all
 
@@ -334,6 +334,7 @@ jobs:
     runs-on: ubuntu-20.04
 
     if: (github.event_name == 'push' || github.event_name == 'schedule' || github.event_name == 'release') && github.repository == 'freqtrade/freqtrade'
+
     steps:
     - uses: actions/checkout@v2
 
@@ -411,3 +412,31 @@ jobs:
         channel: '#notifications'
         url: ${{ secrets.SLACK_WEBHOOK }}
 
+
+  deploy_arm:
+    needs: [ deploy ]
+    # Only run on 64bit machines
+    runs-on: [self-hosted, linux, ARM64]
+    if: (github.event_name == 'push' || github.event_name == 'schedule' || github.event_name == 'release') && github.repository == 'freqtrade/freqtrade'
+
+    steps:
+    - uses: actions/checkout@v2
+
+    - name: Extract branch name
+      shell: bash
+      run: echo "##[set-output name=branch;]$(echo ${GITHUB_REF##*/})"
+      id: extract_branch
+
+    - name: Dockerhub login
+      env:
+        DOCKER_PASSWORD: ${{ secrets.DOCKER_PASSWORD }}
+        DOCKER_USERNAME: ${{ secrets.DOCKER_USERNAME }}
+      run: |
+        echo "${DOCKER_PASSWORD}" | docker login --username ${DOCKER_USERNAME} --password-stdin
+
+    - name: Build and test and push docker images
+      env:
+        IMAGE_NAME: freqtradeorg/freqtrade
+        BRANCH_NAME: ${{ steps.extract_branch.outputs.branch }}
+      run: |
+        build_helpers/publish_docker_arm64.sh

.gitignore

@@ -95,3 +95,8 @@ target/
 
 #exceptions
 !*.gitkeep
+!config_examples/config_binance.example.json
+!config_examples/config_bittrex.example.json
+!config_examples/config_ftx.example.json
+!config_examples/config_full.example.json
+!config_examples/config_kraken.example.json

.travis.yml

@@ -26,12 +26,12 @@ jobs:
       # - coveralls || true
       name: pytest
     - script:
-      - cp config_bittrex.json.example config.json
+      - cp config_examples/config_bittrex.example.json config.json
       - freqtrade create-userdir --userdir user_data
       - freqtrade backtesting --datadir tests/testdata --strategy SampleStrategy
       name: backtest
     - script:
-      - cp config_bittrex.json.example config.json
+      - cp config_examples/config_bittrex.example.json config.json
       - freqtrade create-userdir --userdir user_data
       - freqtrade hyperopt --datadir tests/testdata -e 5 --strategy SampleStrategy --hyperopt SampleHyperOpt --hyperopt-loss SharpeHyperOptLossDaily
       name: hyperopt

CONTRIBUTING.md

@@ -12,7 +12,7 @@ Few pointers for contributions:
 - New features need to contain unit tests, must conform to PEP8 (max-line-length = 100) and should be documented with the introduction PR.
 - PR's can be declared as `[WIP]` - which signify Work in Progress Pull Requests (which are not finished).
 
-If you are unsure, discuss the feature on our [discord server](https://discord.gg/p7nuUNVfP7), on [Slack](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw) or in a [issue](https://github.com/freqtrade/freqtrade/issues) before a PR.
+If you are unsure, discuss the feature on our [discord server](https://discord.gg/p7nuUNVfP7) or in a [issue](https://github.com/freqtrade/freqtrade/issues) before a Pull Request.
 
 ## Getting started
 

Dockerfile

@@ -1,4 +1,4 @@
-FROM python:3.9.5-slim-buster as base
+FROM python:3.9.6-slim-buster as base
 
 # Setup env
 ENV LANG C.UTF-8

README.md

@@ -37,6 +37,7 @@ Please read the [exchange specific notes](docs/exchanges.md) to learn about even
 Exchanges confirmed working by the community:
 
 - [X] [Bitvavo](https://bitvavo.com/)
+- [X] [Kukoin](https://www.kucoin.com/)
 
 ## Documentation
 
@@ -141,13 +142,9 @@ The project is currently setup in two main branches:
 
 ## Support
 
-### Help / Discord / Slack
+### Help / Discord
 
-For any questions not covered by the documentation or for further information about the bot, or to simply engage with like-minded individuals, we encourage you to join our slack channel.
-
-Please check out our [discord server](https://discord.gg/p7nuUNVfP7).
-
-You can also join our [Slack channel](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw).
+For any questions not covered by the documentation or for further information about the bot, or to simply engage with like-minded individuals, we encourage you to join the Freqtrade [discord server](https://discord.gg/p7nuUNVfP7).
 
 ### [Bugs / Issues](https://github.com/freqtrade/freqtrade/issues?q=is%3Aissue)
 
@@ -178,7 +175,7 @@ to understand the requirements before sending your pull-requests.
 Coding is not a necessity to contribute - maybe start with improving our documentation?
 Issues labeled [good first issue](https://github.com/freqtrade/freqtrade/labels/good%20first%20issue) can be good first contributions, and will help get you familiar with the codebase.
 
-**Note** before starting any major new feature work, *please open an issue describing what you are planning to do* or talk to us on [discord](https://discord.gg/p7nuUNVfP7) or [Slack](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw). This will ensure that interested parties can give valuable feedback on the feature, and let others know that you are working on it.
+**Note** before starting any major new feature work, *please open an issue describing what you are planning to do* or talk to us on [discord](https://discord.gg/p7nuUNVfP7) (please use the #dev channel for this). This will ensure that interested parties can give valuable feedback on the feature, and let others know that you are working on it.
 
 **Important:** Always create your PR against the `develop` branch, not `stable`.
 

build_helpers/install_windows.ps1

@@ -6,10 +6,13 @@ python -m pip install --upgrade pip
 $pyv = python -c "import sys; print(f'{sys.version_info.major}.{sys.version_info.minor}')"
 
 if ($pyv -eq '3.7') {
-    pip install build_helpers\TA_Lib-0.4.20-cp37-cp37m-win_amd64.whl
+    pip install build_helpers\TA_Lib-0.4.21-cp37-cp37m-win_amd64.whl
 }
 if ($pyv -eq '3.8') {
-    pip install build_helpers\TA_Lib-0.4.20-cp38-cp38-win_amd64.whl
+    pip install build_helpers\TA_Lib-0.4.21-cp38-cp38-win_amd64.whl
+}
+if ($pyv -eq '3.9') {
+    pip install build_helpers\TA_Lib-0.4.21-cp39-cp39-win_amd64.whl
 }
 
 pip install -r requirements-dev.txt

build_helpers/publish_docker_arm64.sh

@@ -0,0 +1,80 @@
+#!/bin/sh
+
+# Use BuildKit, otherwise building on ARM fails
+export DOCKER_BUILDKIT=1
+
+# Replace / with _ to create a valid tag
+TAG=$(echo "${BRANCH_NAME}" | sed -e "s/\//_/g")
+TAG_PLOT=${TAG}_plot
+TAG_PI="${TAG}_pi"
+
+TAG_ARM=${TAG}_arm
+TAG_PLOT_ARM=${TAG_PLOT}_arm
+CACHE_IMAGE=freqtradeorg/freqtrade_cache
+
+echo "Running for ${TAG}"
+
+# Add commit and commit_message to docker container
+echo "${GITHUB_SHA}" > freqtrade_commit
+
+if [ "${GITHUB_EVENT_NAME}" = "schedule" ]; then
+    echo "event ${GITHUB_EVENT_NAME}: full rebuild - skipping cache"
+    # Build regular image
+    docker build -t freqtrade:${TAG_ARM} .
+
+else
+    echo "event ${GITHUB_EVENT_NAME}: building with cache"
+    # Build regular image
+    docker pull ${IMAGE_NAME}:${TAG_ARM}
+    docker build --cache-from ${IMAGE_NAME}:${TAG_ARM} -t freqtrade:${TAG_ARM} .
+
+fi
+
+if [ $? -ne 0 ]; then
+    echo "failed building multiarch images"
+    return 1
+fi
+# Tag image for upload and next build step
+docker tag freqtrade:$TAG_ARM ${CACHE_IMAGE}:$TAG_ARM
+
+docker build --cache-from freqtrade:${TAG_ARM} --build-arg sourceimage=${TAG_ARM} -t freqtrade:${TAG_PLOT_ARM} -f docker/Dockerfile.plot .
+
+docker tag freqtrade:$TAG_PLOT_ARM ${CACHE_IMAGE}:$TAG_PLOT_ARM
+
+# Run backtest
+docker run --rm -v $(pwd)/config_examples/config_bittrex.example.json:/freqtrade/config.json:ro -v $(pwd)/tests:/tests freqtrade:${TAG_ARM} backtesting --datadir /tests/testdata --strategy-path /tests/strategy/strats/ --strategy DefaultStrategy
+
+if [ $? -ne 0 ]; then
+    echo "failed running backtest"
+    return 1
+fi
+
+docker images
+
+# docker push ${IMAGE_NAME}
+docker push ${CACHE_IMAGE}:$TAG_PLOT_ARM
+docker push ${CACHE_IMAGE}:$TAG_ARM
+
+# Create multi-arch image
+# Make sure that all images contained here are pushed to github first.
+# Otherwise installation might fail.
+echo "create manifests"
+
+docker manifest create --amend ${IMAGE_NAME}:${TAG} ${CACHE_IMAGE}:${TAG_ARM} ${IMAGE_NAME}:${TAG_PI} ${CACHE_IMAGE}:${TAG}
+docker manifest push -p ${IMAGE_NAME}:${TAG}
+
+docker manifest create --amend ${IMAGE_NAME}:${TAG_PLOT} ${CACHE_IMAGE}:${TAG_PLOT_ARM} ${CACHE_IMAGE}:${TAG_PLOT}
+docker manifest push -p ${IMAGE_NAME}:${TAG_PLOT}
+
+Tag as latest for develop builds
+if [ "${TAG}" = "develop" ]; then
+    docker tag ${IMAGE_NAME}:develop ${IMAGE_NAME}:latest
+    docker push ${IMAGE_NAME}:latest
+fi
+
+docker images
+
+if [ $? -ne 0 ]; then
+    echo "failed building image"
+    return 1
+fi

build_helpers/publish_docker_multi.sh

@@ -9,7 +9,8 @@ TAG_PI="${TAG}_pi"
 
 PI_PLATFORM="linux/arm/v7"
 echo "Running for ${TAG}"
-CACHE_TAG=freqtradeorg/freqtrade_cache:${TAG}_cache
+CACHE_IMAGE=freqtradeorg/freqtrade_cache
+CACHE_TAG=${CACHE_IMAGE}:${TAG_PI}_cache
 
 # Add commit and commit_message to docker container
 echo "${GITHUB_SHA}" > freqtrade_commit
@@ -45,14 +46,14 @@ if [ $? -ne 0 ]; then
     return 1
 fi
 # Tag image for upload and next build step
-docker tag freqtrade:$TAG ${IMAGE_NAME}:$TAG
+docker tag freqtrade:$TAG ${CACHE_IMAGE}:$TAG
 
 docker build --cache-from freqtrade:${TAG} --build-arg sourceimage=${TAG} -t freqtrade:${TAG_PLOT} -f docker/Dockerfile.plot .
 
-docker tag freqtrade:$TAG_PLOT ${IMAGE_NAME}:$TAG_PLOT
+docker tag freqtrade:$TAG_PLOT ${CACHE_IMAGE}:$TAG_PLOT
 
 # Run backtest
-docker run --rm -v $(pwd)/config_bittrex.json.example:/freqtrade/config.json:ro -v $(pwd)/tests:/tests freqtrade:${TAG} backtesting --datadir /tests/testdata --strategy-path /tests/strategy/strats/ --strategy DefaultStrategy
+docker run --rm -v $(pwd)/config_examples/config_bittrex.example.json:/freqtrade/config.json:ro -v $(pwd)/tests:/tests freqtrade:${TAG} backtesting --datadir /tests/testdata --strategy-path /tests/strategy/strats/ --strategy DefaultStrategy
 
 if [ $? -ne 0 ]; then
     echo "failed running backtest"
@@ -61,22 +62,9 @@ fi
 
 docker images
 
-docker push ${IMAGE_NAME}
-docker push ${IMAGE_NAME}:$TAG_PLOT
-docker push ${IMAGE_NAME}:$TAG
-
-# Create multiarch image
-# Make sure that all images contained here are pushed to github first.
-# Otherwise installation might fail.
-
-docker manifest create freqtradeorg/freqtrade:${TAG} ${IMAGE_NAME}:${TAG} ${IMAGE_NAME}:${TAG_PI}
-docker manifest push freqtradeorg/freqtrade:${TAG}
-
-# Tag as latest for develop builds
-if [ "${TAG}" = "develop" ]; then
-    docker manifest create freqtradeorg/freqtrade:latest ${IMAGE_NAME}:${TAG} ${IMAGE_NAME}:${TAG_PI}
-    docker manifest push freqtradeorg/freqtrade:latest
-fi
+docker push ${CACHE_IMAGE}
+docker push ${CACHE_IMAGE}:$TAG_PLOT
+docker push ${CACHE_IMAGE}:$TAG
 
 
 docker images

config_examples/config_binance.example.json

@@ -13,7 +13,7 @@
     },
     "bid_strategy": {
         "ask_last_balance": 0.0,
-        "use_order_book": false,
+        "use_order_book": true,
         "order_book_top": 1,
         "check_depth_of_market": {
             "enabled": false,
@@ -21,12 +21,8 @@
         }
     },
     "ask_strategy": {
-        "use_order_book": false,
-        "order_book_min": 1,
-        "order_book_max": 1,
-        "use_sell_signal": true,
-        "sell_profit_only": false,
-        "ignore_roi_if_buy_signal": false
+        "use_order_book": true,
+        "order_book_top": 1
     },
     "exchange": {
         "name": "binance",

config_examples/config_bittrex.example.json

@@ -12,7 +12,7 @@
         "sell": 30
     },
     "bid_strategy": {
-        "use_order_book": false,
+        "use_order_book": true,
         "ask_last_balance": 0.0,
         "order_book_top": 1,
         "check_depth_of_market": {
@@ -21,12 +21,8 @@
         }
     },
     "ask_strategy":{
-        "use_order_book": false,
-        "order_book_min": 1,
-        "order_book_max": 1,
-        "use_sell_signal": true,
-        "sell_profit_only": false,
-        "ignore_roi_if_buy_signal": false
+        "use_order_book": true,
+        "order_book_top": 1
     },
     "exchange": {
         "name": "bittrex",

config_examples/config_ftx.example.json

@@ -13,7 +13,7 @@
     },
     "bid_strategy": {
         "ask_last_balance": 0.0,
-        "use_order_book": false,
+        "use_order_book": true,
         "order_book_top": 1,
         "check_depth_of_market": {
             "enabled": false,
@@ -21,12 +21,8 @@
         }
     },
     "ask_strategy": {
-        "use_order_book": false,
-        "order_book_min": 1,
-        "order_book_max": 1,
-        "use_sell_signal": true,
-        "sell_profit_only": false,
-        "ignore_roi_if_buy_signal": false
+        "use_order_book": true,
+        "order_book_top": 1
     },
     "exchange": {
         "name": "ftx",

config_examples/config_full.example.json

@@ -14,6 +14,10 @@
     "trailing_stop_positive": 0.005,
     "trailing_stop_positive_offset": 0.0051,
     "trailing_only_offset_is_reached": false,
+    "use_sell_signal": true,
+    "sell_profit_only": false,
+    "sell_profit_offset": 0.0,
+    "ignore_roi_if_buy_signal": false,
     "minimal_roi": {
         "40":  0.0,
         "30":  0.01,
@@ -28,7 +32,7 @@
     },
     "bid_strategy": {
         "price_side": "bid",
-        "use_order_book": false,
+        "use_order_book": true,
         "ask_last_balance": 0.0,
         "order_book_top": 1,
         "check_depth_of_market": {
@@ -38,13 +42,8 @@
     },
     "ask_strategy":{
         "price_side": "ask",
-        "use_order_book": false,
-        "order_book_min": 1,
-        "order_book_max": 1,
-        "use_sell_signal": true,
-        "sell_profit_only": false,
-        "sell_profit_offset": 0.0,
-        "ignore_roi_if_buy_signal": false
+        "use_order_book": true,
+        "order_book_top": 1
     },
     "order_types": {
         "buy": "limit",

config_examples/config_kraken.example.json

@@ -12,7 +12,7 @@
         "sell": 30
     },
     "bid_strategy": {
-        "use_order_book": false,
+        "use_order_book": true,
         "ask_last_balance": 0.0,
         "order_book_top": 1,
         "check_depth_of_market": {
@@ -21,12 +21,8 @@
         }
     },
     "ask_strategy":{
-        "use_order_book": false,
-        "order_book_min": 1,
-        "order_book_max": 1,
-        "use_sell_signal": true,
-        "sell_profit_only": false,
-        "ignore_roi_if_buy_signal": false
+        "use_order_book": true,
+        "order_book_top": 1
     },
     "exchange": {
         "name": "kraken",

docs/advanced-hyperopt.md

@@ -32,6 +32,7 @@ class SuperDuperHyperOptLoss(IHyperOptLoss):
     def hyperopt_loss_function(results: DataFrame, trade_count: int,
                                min_date: datetime, max_date: datetime,
                                config: Dict, processed: Dict[str, DataFrame],
+                               backtest_stats: Dict[str, Any],
                                *args, **kwargs) -> float:
         """
         Objective function, returns smaller number for better results
@@ -53,7 +54,7 @@ class SuperDuperHyperOptLoss(IHyperOptLoss):
 
 Currently, the arguments are:
 
-* `results`: DataFrame containing the result  
+* `results`: DataFrame containing the resulting trades.
     The following columns are available in results (corresponds to the output-file of backtesting when used with `--export trades`):  
     `pair, profit_ratio, profit_abs, open_date, open_rate, fee_open, close_date, close_rate, fee_close, amount, trade_duration, is_open, sell_reason, stake_amount, min_rate, max_rate, stop_loss_ratio, stop_loss_abs`
 * `trade_count`: Amount of trades (identical to `len(results)`)
@@ -61,6 +62,7 @@ Currently, the arguments are:
 * `min_date`: End date of the timerange used
 * `config`: Config object used (Note: Not all strategy-related parameters will be updated here if they are part of a hyperopt space).
 * `processed`: Dict of Dataframes with the pair as keys containing the data used for backtesting.
+* `backtest_stats`: Backtesting statistics using the same format as the backtesting file "strategy" substructure. Available fields can be seen in `generate_strategy_stats()` in `optimize_reports.py`.
 
 This function needs to return a floating point number (`float`). Smaller numbers will be interpreted as better results. The parameters and balancing for this is up to you.
 

docs/backtesting.md

@@ -302,7 +302,6 @@ A backtesting result will look like that:
 | Days win/draw/lose    | 12 / 82 / 25        |
 | Avg. Duration Winners | 4:23:00             |
 | Avg. Duration Loser   | 6:55:00             |
-| Zero Duration Trades  | 4.6% (20)           |
 | Rejected Buy signals  | 3089                |
 |                       |                     |
 | Min balance           | 0.00945123 BTC      |
@@ -390,7 +389,6 @@ It contains some useful key metrics about performance of your strategy on backte
 | Days win/draw/lose    | 12 / 82 / 25        |
 | Avg. Duration Winners | 4:23:00             |
 | Avg. Duration Loser   | 6:55:00             |
-| Zero Duration Trades  | 4.6% (20)           |
 | Rejected Buy signals  | 3089                |
 |                       |                     |
 | Min balance           | 0.00945123 BTC      |
@@ -420,7 +418,6 @@ It contains some useful key metrics about performance of your strategy on backte
 - `Best day` / `Worst day`: Best and worst day based on daily profit.
 - `Days win/draw/lose`: Winning / Losing days (draws are usually days without closed trade).
 - `Avg. Duration Winners` / `Avg. Duration Loser`: Average durations for winning and losing trades.
-- `Zero Duration Trades`: A number of trades that completed within same candle as they opened and had `trailing_stop_loss` sell reason. A significant amount of such trades may indicate that strategy is exploiting trailing stoploss behavior in backtesting and produces unrealistic results.
 - `Rejected Buy signals`: Buy signals that could not be acted upon due to max_open_trades being reached.
 - `Min balance` / `Max balance`: Lowest and Highest Wallet balance during the backtest period.
 - `Drawdown`: Maximum drawdown experienced. For example, the value of 50% means that from highest to subsequent lowest point, a 50% drop was experienced).

docs/configuration.md

@@ -5,11 +5,11 @@ By default, these settings are configured via the configuration file (see below)
 
 ## The Freqtrade configuration file
 
-The bot uses a set of configuration parameters during its operation that all together conform the bot configuration. It normally reads its configuration from a file (Freqtrade configuration file).
+The bot uses a set of configuration parameters during its operation that all together conform to the bot configuration. It normally reads its configuration from a file (Freqtrade configuration file).
 
 Per default, the bot loads the configuration from the `config.json` file, located in the current working directory.
 
-You can specify a different configuration file used by the bot with the `-c/--config` command line option.
+You can specify a different configuration file used by the bot with the `-c/--config` command-line option.
 
 Multiple configuration files can be specified and used by the bot or the bot can read its configuration parameters from the process standard input stream.
 
@@ -25,33 +25,34 @@ Multiple configuration files can be specified and used by the bot or the bot can
 If you used the [Quick start](installation.md/#quick-start) method for installing 
 the bot, the installation script should have already created the default configuration file (`config.json`) for you.
 
-If default configuration file is not created we recommend you to use `freqtrade new-config --config config.json` to generate a basic configuration file.
+If the default configuration file is not created we recommend you to use `freqtrade new-config --config config.json` to generate a basic configuration file.
 
-The Freqtrade configuration file is to be written in the JSON format.
+The Freqtrade configuration file is to be written in JSON format.
 
 Additionally to the standard JSON syntax, you may use one-line `// ...` and multi-line `/* ... */` comments in your configuration files and trailing commas in the lists of parameters.
 
-Do not worry if you are not familiar with JSON format -- simply open the configuration file with an editor of your choice, make some changes to the parameters you need, save your changes and, finally, restart the bot or, if it was previously stopped, run it again with the changes you made to the configuration. The bot validates syntax of the configuration file at startup and will warn you if you made any errors editing it, pointing out problematic lines.
+Do not worry if you are not familiar with JSON format -- simply open the configuration file with an editor of your choice, make some changes to the parameters you need, save your changes and, finally, restart the bot or, if it was previously stopped, run it again with the changes you made to the configuration. The bot validates the syntax of the configuration file at startup and will warn you if you made any errors editing it, pointing out problematic lines.
 
 ## Configuration parameters
 
 The table below will list all configuration parameters available.
 
 Freqtrade can also load many options via command line (CLI) arguments (check out the commands `--help` output for details).
-The prevelance for all Options is as follows:
+The prevalence for all Options is as follows:
 
 - CLI arguments override any other option
-- Configuration files are used in sequence (last file wins), and override Strategy configurations.
-- Strategy configurations are only used if they are not set via configuration or via command line arguments. These options are marked with [Strategy Override](#parameters-in-the-strategy) in the below table.
+- Configuration files are used in sequence (the last file wins) and override Strategy configurations.
+- Strategy configurations are only used if they are not set via configuration or command-line arguments. These options are marked with [Strategy Override](#parameters-in-the-strategy) in the below table.
 
 Mandatory parameters are marked as **Required**, which means that they are required to be set in one of the possible ways.
 
 |  Parameter | Description |
 |------------|-------------|
-| `max_open_trades` | **Required.** Number of open trades your bot is allowed to have. Only one open trade per pair is possible, so the length of your pairlist is another limitation which can apply. If -1 then it is ignored (i.e. potentially unlimited open trades, limited by the pairlist). [More information below](#configuring-amount-per-trade).<br> **Datatype:** Positive integer or -1.
+| `max_open_trades` | **Required.** Number of open trades your bot is allowed to have. Only one open trade per pair is possible, so the length of your pairlist is another limitation that can apply. If -1 then it is ignored (i.e. potentially unlimited open trades, limited by the pairlist). [More information below](#configuring-amount-per-trade).<br> **Datatype:** Positive integer or -1.
 | `stake_currency` | **Required.** Crypto-currency used for trading. <br> **Datatype:** String
 | `stake_amount` | **Required.** Amount of crypto-currency your bot will use for each trade. Set it to `"unlimited"` to allow the bot to use all available balance. [More information below](#configuring-amount-per-trade). <br> **Datatype:** Positive float or `"unlimited"`.
 | `tradable_balance_ratio` | Ratio of the total account balance the bot is allowed to trade. [More information below](#configuring-amount-per-trade). <br>*Defaults to `0.99` 99%).*<br> **Datatype:** Positive float between `0.1` and `1.0`.
+| `available_capital` | Available starting capital for the bot. Useful when running multiple bots on the same exchange account.[More information below](#configuring-amount-per-trade). <br> **Datatype:** Positive float.
 | `amend_last_stake_amount` | Use reduced last stake amount if necessary. [More information below](#configuring-amount-per-trade). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
 | `last_stake_amount_min_ratio` | Defines minimum stake amount that has to be left and executed. Applies only to the last stake amount when it's amended to a reduced value (i.e. if `amend_last_stake_amount` is set to `true`). [More information below](#configuring-amount-per-trade). <br>*Defaults to `0.5`.* <br> **Datatype:** Float (as ratio)
 | `amount_reserve_percent` | Reserve some amount in min pair stake amount. The bot will reserve `amount_reserve_percent` + stoploss value when calculating min pair stake amount in order to avoid possible trade refusals. <br>*Defaults to `0.05` (5%).* <br> **Datatype:** Positive Float as ratio.
@@ -74,19 +75,18 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 | `bid_strategy.price_side` | Select the side of the spread the bot should look at to get the buy rate. [More information below](#buy-price-side).<br> *Defaults to `bid`.* <br> **Datatype:** String (either `ask` or `bid`).
 | `bid_strategy.ask_last_balance` | **Required.** Interpolate the bidding price. More information [below](#buy-price-without-orderbook-enabled).
 | `bid_strategy.use_order_book` | Enable buying using the rates in [Order Book Bids](#buy-price-with-orderbook-enabled). <br> **Datatype:** Boolean
-| `bid_strategy.order_book_top` | Bot will use the top N rate in Order Book Bids to buy. I.e. a value of 2 will allow the bot to pick the 2nd bid rate in [Order Book Bids](#buy-price-with-orderbook-enabled). <br>*Defaults to `1`.*  <br> **Datatype:** Positive Integer
+| `bid_strategy.order_book_top` | Bot will use the top N rate in Order Book "price_side" to buy. I.e. a value of 2 will allow the bot to pick the 2nd bid rate in [Order Book Bids](#buy-price-with-orderbook-enabled). <br>*Defaults to `1`.*  <br> **Datatype:** Positive Integer
 | `bid_strategy. check_depth_of_market.enabled` | Do not buy if the difference of buy orders and sell orders is met in Order Book. [Check market depth](#check-depth-of-market). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
 | `bid_strategy. check_depth_of_market.bids_to_ask_delta` | The difference ratio of buy orders and sell orders found in Order Book. A value below 1 means sell order size is greater, while value greater than 1 means buy order size is higher. [Check market depth](#check-depth-of-market) <br> *Defaults to `0`.*  <br> **Datatype:** Float (as ratio)
 | `ask_strategy.price_side` | Select the side of the spread the bot should look at to get the sell rate. [More information below](#sell-price-side).<br> *Defaults to `ask`.* <br> **Datatype:** String (either `ask` or `bid`).
 | `ask_strategy.bid_last_balance` | Interpolate the selling price. More information [below](#sell-price-without-orderbook-enabled).
 | `ask_strategy.use_order_book` | Enable selling of open trades using [Order Book Asks](#sell-price-with-orderbook-enabled). <br> **Datatype:** Boolean
-| `ask_strategy.order_book_min` | Bot will scan from the top min to max Order Book Asks searching for a profitable rate. <br>*Defaults to `1`.* <br> **Datatype:** Positive Integer
-| `ask_strategy.order_book_max` | Bot will scan from the top min to max Order Book Asks searching for a profitable rate. <br>*Defaults to `1`.* <br> **Datatype:** Positive Integer
-| `ask_strategy.use_sell_signal` | Use sell signals produced by the strategy in addition to the `minimal_roi`. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `true`.* <br> **Datatype:** Boolean
-| `ask_strategy.sell_profit_only` | Wait until the bot reaches `ask_strategy.sell_profit_offset` before taking a sell decision. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
-| `ask_strategy.sell_profit_offset` | Sell-signal is only active above this value. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `0.0`.* <br> **Datatype:** Float (as ratio)
-| `ask_strategy.ignore_roi_if_buy_signal` | Do not sell if the buy signal is still active. This setting takes preference over `minimal_roi` and `use_sell_signal`. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
-| `ask_strategy.ignore_buying_expired_candle_after` | Specifies the number of seconds until a buy signal is no longer used. <br> **Datatype:** Integer
+| `ask_strategy.order_book_top` | Bot will use the top N rate in Order Book "price_side" to sell. I.e. a value of 2 will allow the bot to pick the 2nd ask rate in [Order Book Asks](#sell-price-with-orderbook-enabled)<br>*Defaults to `1`.* <br> **Datatype:** Positive Integer
+| `use_sell_signal` | Use sell signals produced by the strategy in addition to the `minimal_roi`. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `true`.* <br> **Datatype:** Boolean
+| `sell_profit_only` | Wait until the bot reaches `sell_profit_offset` before taking a sell decision. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
+| `sell_profit_offset` | Sell-signal is only active above this value. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `0.0`.* <br> **Datatype:** Float (as ratio)
+| `ignore_roi_if_buy_signal` | Do not sell if the buy signal is still active. This setting takes preference over `minimal_roi` and `use_sell_signal`. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
+| `ignore_buying_expired_candle_after` | Specifies the number of seconds until a buy signal is no longer used. <br> **Datatype:** Integer
 | `order_types` | Configure order-types depending on the action (`"buy"`, `"sell"`, `"stoploss"`, `"stoploss_on_exchange"`). [More information below](#understand-order_types). [Strategy Override](#parameters-in-the-strategy).<br> **Datatype:** Dict
 | `order_time_in_force` | Configure time in force for buy and sell orders. [More information below](#understand-order_time_in_force). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Dict
 | `exchange.name` | **Required.** Name of the exchange class to use. [List below](#user-content-what-values-for-exchangename). <br> **Datatype:** String
@@ -141,7 +141,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
 
 ### Parameters in the strategy
 
-The following parameters can be set in configuration file or strategy.
+The following parameters can be set in the configuration file or strategy.
 Values set in the configuration file always overwrite values set in the strategy.
 
 * `minimal_roi`
@@ -157,51 +157,67 @@ Values set in the configuration file always overwrite values set in the strategy
 * `order_time_in_force`
 * `unfilledtimeout`
 * `disable_dataframe_checks`
-* `use_sell_signal` (ask_strategy)
-* `sell_profit_only` (ask_strategy)
-* `sell_profit_offset` (ask_strategy)
-* `ignore_roi_if_buy_signal` (ask_strategy)
-* `ignore_buying_expired_candle_after` (ask_strategy)
+* `use_sell_signal`
+* `sell_profit_only`
+* `sell_profit_offset`
+* `ignore_roi_if_buy_signal`
+* `ignore_buying_expired_candle_after`
 
 ### Configuring amount per trade
 
-There are several methods to configure how much of the stake currency the bot will use to enter a trade. All methods respect the [available balance configuration](#available-balance) as explained below.
+There are several methods to configure how much of the stake currency the bot will use to enter a trade. All methods respect the [available balance configuration](#tradable-balance) as explained below.
 
 #### Minimum trade stake
 
-The minimum stake amount will depend by exchange and pair, and is usually listed in the exchange support pages.
+The minimum stake amount will depend on exchange and pair and is usually listed in the exchange support pages.
 Assuming the minimum tradable amount for XRP/USD is 20 XRP (given by the exchange), and the price is 0.6$.
 
-The minimum stake amount to buy this pair is therefore `20 * 0.6 ~= 12`.
+The minimum stake amount to buy this pair is, therefore, `20 * 0.6 ~= 12`.
 This exchange has also a limit on USD - where all orders must be > 10$ - which however does not apply in this case.
 
 To guarantee safe execution, freqtrade will not allow buying with a stake-amount of 10.1$, instead, it'll make sure that there's enough space to place a stoploss below the pair (+ an offset, defined by `amount_reserve_percent`, which defaults to 5%).
 
-With a reserve of 5%, the minimum stake amount would be ~12.6$ (`12 * (1 + 0.05)`). If we take in account a stoploss of 10% on top of that - we'd end up with a value of ~14$ (`12.6 / (1 - 0.1)`).
+With a reserve of 5%, the minimum stake amount would be ~12.6$ (`12 * (1 + 0.05)`). If we take into account a stoploss of 10% on top of that - we'd end up with a value of ~14$ (`12.6 / (1 - 0.1)`).
 
 To limit this calculation in case of large stoploss values, the calculated minimum stake-limit will never be more than 50% above the real limit.
 
 !!! Warning
     Since the limits on exchanges are usually stable and are not updated often, some pairs can show pretty high minimum limits, simply because the price increased a lot since the last limit adjustment by the exchange.
 
-#### Available balance
+#### Tradable balance
 
 By default, the bot assumes that the `complete amount - 1%` is at it's disposal, and when using [dynamic stake amount](#dynamic-stake-amount), it will split the complete balance into `max_open_trades` buckets per trade.
 Freqtrade will reserve 1% for eventual fees when entering a trade and will therefore not touch that by default.
 
 You can configure the "untouched" amount by using the `tradable_balance_ratio` setting.
 
-For example, if you have 10 ETH available in your wallet on the exchange and `tradable_balance_ratio=0.5` (which is 50%), then the bot will use a maximum amount of 5 ETH for trading and considers this as available balance. The rest of the wallet is untouched by the trades.
+For example, if you have 10 ETH available in your wallet on the exchange and `tradable_balance_ratio=0.5` (which is 50%), then the bot will use a maximum amount of 5 ETH for trading and considers this as an available balance. The rest of the wallet is untouched by the trades.
+
+!!! Danger
+    This setting should **not** be used when running multiple bots on the same account. Please look at [Available Capital to the bot](#assign-available-capital) instead.
 
 !!! Warning
-    The `tradable_balance_ratio` setting applies to the current balance (free balance + tied up in trades). Therefore, assuming the starting balance of 1000, a configuration with `tradable_balance_ratio=0.99` will not guarantee that 10 currency units will always remain available on the exchange. For example, the free amount may reduce to 5 units if the total balance is reduced to 500 (either by a losing streak, or by withdrawing balance).
+    The `tradable_balance_ratio` setting applies to the current balance (free balance + tied up in trades). Therefore, assuming the starting balance of 1000, a configuration with `tradable_balance_ratio=0.99` will not guarantee that 10 currency units will always remain available on the exchange. For example, the free amount may reduce to 5 units if the total balance is reduced to 500 (either by a losing streak or by withdrawing balance).
+
+#### Assign available Capital
+
+To fully utilize compounding profits when using multiple bots on the same exchange account, you'll want to limit each bot to a certain starting balance.
+This can be accomplished by setting `available_capital` to the desired starting balance.
+
+Assuming your account has 10.000 USDT and you want to run 2 different strategies on this exchange.
+You'd set `available_capital=5000` - granting each bot an initial capital of 5000 USDT.
+The bot will then split this starting balance equally into `max_open_trades` buckets.
+Profitable trades will result in increased stake-sizes for this bot - without affecting the stake-sizes of the other bot.
+
+!!! Warning "Incompatible with `tradable_balance_ratio`"
+    Setting this option will replace any configuration of `tradable_balance_ratio`.
 
 #### Amend last stake amount
 
 Assuming we have the tradable balance of 1000 USDT, `stake_amount=400`, and `max_open_trades=3`.
-The bot would open 2 trades, and will be unable to fill the last trading slot, since the requested 400 USDT are no longer available, since 800 USDT are already tied in other trades.
+The bot would open 2 trades and will be unable to fill the last trading slot, since the requested 400 USDT are no longer available since 800 USDT are already tied in other trades.
 
-To overcome this, the option `amend_last_stake_amount` can be set to `True`, which will enable the bot to reduce stake_amount to the available balance in order to fill the last trade slot.
+To overcome this, the option `amend_last_stake_amount` can be set to `True`, which will enable the bot to reduce stake_amount to the available balance to fill the last trade slot.
 
 In the example above this would mean:
 
@@ -229,7 +245,7 @@ For example, the bot will at most use (0.05 BTC x 3) = 0.15 BTC, assuming a conf
 
 #### Dynamic stake amount
 
-Alternatively, you can use a dynamic stake amount, which will use the available balance on the exchange, and divide that equally by the amount of allowed trades (`max_open_trades`).
+Alternatively, you can use a dynamic stake amount, which will use the available balance on the exchange, and divide that equally by the number of allowed trades (`max_open_trades`).
 
 To configure this, set `stake_amount="unlimited"`. We also recommend to set `tradable_balance_ratio=0.99` (99%) - to keep a minimum balance for eventual fees.
 
@@ -247,18 +263,18 @@ To allow the bot to trade all the available `stake_currency` in your account (mi
 ```
 
 !!! Tip "Compounding profits"
-    This configuration will allow increasing / decreasing stakes depending on the performance of the bot (lower stake if bot is loosing, higher stakes if the bot has a winning record, since higher balances are available), and will result in profit compounding.
+    This configuration will allow increasing/decreasing stakes depending on the performance of the bot (lower stake if the bot is losing, higher stakes if the bot has a winning record since higher balances are available), and will result in profit compounding.
 
 !!! Note "When using Dry-Run Mode"
-    When using `"stake_amount" : "unlimited",` in combination with Dry-Run, Backtesting or Hyperopt, the balance will be simulated starting with a stake of `dry_run_wallet` which will evolve over time.  
-    It is therefore important to set `dry_run_wallet` to a sensible value (like 0.05 or 0.01 for BTC and 1000 or 100 for USDT, for example), otherwise it may simulate trades with 100 BTC (or more) or 0.05 USDT (or less) at once - which may not correspond to your real available balance or is less than the exchange minimal limit for the order amount for the stake currency.
+    When using `"stake_amount" : "unlimited",` in combination with Dry-Run, Backtesting or Hyperopt, the balance will be simulated starting with a stake of `dry_run_wallet` which will evolve.
+    It is therefore important to set `dry_run_wallet` to a sensible value (like 0.05 or 0.01 for BTC and 1000 or 100 for USDT, for example), otherwise, it may simulate trades with 100 BTC (or more) or 0.05 USDT (or less) at once - which may not correspond to your real available balance or is less than the exchange minimal limit for the order amount for the stake currency.
 
 --8<-- "includes/pricing.md"
 
 ### Understand minimal_roi
 
 The `minimal_roi` configuration parameter is a JSON object where the key is a duration
-in minutes and the value is the minimum ROI as ratio.
+in minutes and the value is the minimum ROI as a ratio.
 See the example below:
 
 ```json
@@ -273,7 +289,7 @@ See the example below:
 Most of the strategy files already include the optimal `minimal_roi` value.
 This parameter can be set in either Strategy or Configuration file. If you use it in the configuration file, it will override the
 `minimal_roi` value from the strategy file.
-If it is not set in either Strategy or Configuration, a default of 1000% `{"0": 10}` is used, and minimal roi is disabled unless your trade generates 1000% profit.
+If it is not set in either Strategy or Configuration, a default of 1000% `{"0": 10}` is used, and minimal ROI is disabled unless your trade generates 1000% profit.
 
 !!! Note "Special case to forcesell after a specific time"
     A special case presents using `"<N>": -1` as ROI. This forces the bot to sell a trade after N Minutes, no matter if it's positive or negative, so represents a time-limited force-sell.
@@ -292,16 +308,16 @@ See [the telegram documentation](telegram-usage.md) for details on usage.
 
 When working with larger timeframes (for example 1h or more) and using a low `max_open_trades` value, the last candle can be processed as soon as a trade slot becomes available. When processing the last candle, this can lead to a situation where it may not be desirable to use the buy signal on that candle. For example, when using a condition in your strategy where you use a cross-over, that point may have passed too long ago for you to start a trade on it.
 
-In these situations, you can enable the functionality to ignore candles that are beyond a specified period by setting `ask_strategy.ignore_buying_expired_candle_after` to a positive number, indicating the number of seconds after which the buy signal becomes expired.
+In these situations, you can enable the functionality to ignore candles that are beyond a specified period by setting `ignore_buying_expired_candle_after` to a positive number, indicating the number of seconds after which the buy signal becomes expired.
 
 For example, if your strategy is using a 1h timeframe, and you only want to buy within the first 5 minutes when a new candle comes in, you can add the following configuration to your strategy:
 
 ``` json
-  "ask_strategy":{
+  {
+    //...
     "ignore_buying_expired_candle_after": 300,
-    "price_side": "bid",
     // ...
-  },
+  }
 ```
 
 !!! Note
@@ -319,7 +335,7 @@ the buy order is fulfilled.
 `order_types` set in the configuration file overwrites values set in the strategy as a whole, so you need to configure the whole `order_types` dictionary in one place.
 
 If this is configured, the following 4 values (`buy`, `sell`, `stoploss` and
-`stoploss_on_exchange`) need to be present, otherwise the bot will fail to start.
+`stoploss_on_exchange`) need to be present, otherwise, the bot will fail to start.
 
 For information on (`emergencysell`,`forcesell`, `forcebuy`, `stoploss_on_exchange`,`stoploss_on_exchange_interval`,`stoploss_on_exchange_limit_ratio`) please see stop loss documentation [stop loss on exchange](stoploss.md)
 
@@ -370,7 +386,7 @@ Configuration:
     If `stoploss_on_exchange` is enabled and the stoploss is cancelled manually on the exchange, then the bot will create a new stoploss order.
 
 !!! Warning "Warning: stoploss_on_exchange failures"
-    If stoploss on exchange creation fails for some reason, then an "emergency sell" is initiated. By default, this will sell the asset using a market order. The order-type for the emergency-sell can be changed by setting the `emergencysell` value in the `order_types` dictionary - however this is not advised.
+    If stoploss on exchange creation fails for some reason, then an "emergency sell" is initiated. By default, this will sell the asset using a market order. The order-type for the emergency-sell can be changed by setting the `emergencysell` value in the `order_types` dictionary - however, this is not advised.
 
 ### Understand order_time_in_force
 
@@ -380,12 +396,12 @@ is executed on the exchange. Three commonly used time in force are:
 **GTC (Good Till Canceled):**
 
 This is most of the time the default time in force. It means the order will remain
-on exchange till it is canceled by user. It can be fully or partially fulfilled.
+on exchange till it is cancelled by the user. It can be fully or partially fulfilled.
 If partially fulfilled, the remaining will stay on the exchange till cancelled.
 
 **FOK (Fill Or Kill):**
 
-It means if the order is not executed immediately AND fully then it is canceled by the exchange.
+It means if the order is not executed immediately AND fully then it is cancelled by the exchange.
 
 **IOC (Immediate Or Canceled):**
 
@@ -406,7 +422,7 @@ The possible values are: `gtc` (default), `fok` or `ioc`.
 ```
 
 !!! Warning
-    This is an ongoing work. For now it is supported only for binance.
+    This is ongoing work. For now, it is supported only for binance.
     Please don't change the default value unless you know what you are doing and have researched the impact of using different values.
 
 ### Exchange configuration
@@ -415,7 +431,7 @@ Freqtrade is based on [CCXT library](https://github.com/ccxt/ccxt) that supports
 exchange markets and trading APIs. The complete up-to-date list can be found in the
 [CCXT repo homepage](https://github.com/ccxt/ccxt/tree/master/python).
  However, the bot was tested by the development team with only Bittrex, Binance and Kraken,
- so the these are the only officially supported exchanges:
+ so these are the only officially supported exchanges:
 
 - [Bittrex](https://bittrex.com/): "bittrex"
 - [Binance](https://www.binance.com/): "binance"
@@ -441,11 +457,11 @@ A exchange configuration for "binance" would look as follows:
     },
 ```
 
-This configuration enables binance, as well as rate limiting to avoid bans from the exchange.
+This configuration enables binance, as well as rate-limiting to avoid bans from the exchange.
 `"rateLimit": 200` defines a wait-event of 0.2s between each call. This can also be completely disabled by setting `"enableRateLimit"` to false.
 
 !!! Note
-    Optimal settings for rate limiting depend on the exchange and the size of the whitelist, so an ideal parameter will vary on many other settings.
+    Optimal settings for rate-limiting depend on the exchange and the size of the whitelist, so an ideal parameter will vary on many other settings.
     We try to provide sensible defaults per exchange where possible, if you encounter bans please make sure that `"enableRateLimit"` is enabled and increase the `"rateLimit"` parameter step by step.
 
 ### What values can be used for fiat_display_currency?
@@ -459,7 +475,7 @@ The valid values are:
 "AUD", "BRL", "CAD", "CHF", "CLP", "CNY", "CZK", "DKK", "EUR", "GBP", "HKD", "HUF", "IDR", "ILS", "INR", "JPY", "KRW", "MXN", "MYR", "NOK", "NZD", "PHP", "PKR", "PLN", "RUB", "SEK", "SGD", "THB", "TRY", "TWD", "ZAR", "USD"
 ```
 
-In addition to fiat currencies, a range of cryto currencies are supported.
+In addition to fiat currencies, a range of crypto currencies is supported.
 
 The valid values are:
 
@@ -470,7 +486,7 @@ The valid values are:
 ## Using Dry-run mode
 
 We recommend starting the bot in the Dry-run mode to see how your bot will
-behave and what is the performance of your strategy. In the Dry-run mode the
+behave and what is the performance of your strategy. In the Dry-run mode, the
 bot does not engage your money. It only runs a live simulation without
 creating trades on the exchange.
 
@@ -496,7 +512,7 @@ creating trades on the exchange.
 Once you will be happy with your bot performance running in the Dry-run mode, you can switch it to production mode.
 
 !!! Note
-    A simulated wallet is available during dry-run mode, and will assume a starting capital of `dry_run_wallet` (defaults to 1000).
+    A simulated wallet is available during dry-run mode and will assume a starting capital of `dry_run_wallet` (defaults to 1000).
 
 ### Considerations for dry-run
 
@@ -504,7 +520,7 @@ Once you will be happy with your bot performance running in the Dry-run mode, yo
 * Wallets (`/balance`) are simulated based on `dry_run_wallet`.
 * Orders are simulated, and will not be posted to the exchange.
 * Market orders fill based on orderbook volume the moment the order is placed.
-* Limit orders fill once price reaches the defined level - or time out based on `unfilledtimeout` settings.
+* Limit orders fill once the price reaches the defined level - or time out based on `unfilledtimeout` settings.
 * In combination with `stoploss_on_exchange`, the stop_loss price is assumed to be filled.
 * Open orders (not trades, which are stored in the database) are reset on bot restart.
 
@@ -517,7 +533,7 @@ you run it in production mode.
 ### Setup your exchange account
 
 You will need to create API Keys (usually you get `key` and `secret`, some exchanges require an additional `password`) from the Exchange website and you'll need to insert this into the appropriate fields in the configuration or when asked by the `freqtrade new-config` command.
-API Keys are usually only required for live trading (trading for real money, bot running in "production mode", executing real orders on the exchange) and are not required for the bot running in dry-run (trade simulation) mode. When you setup the bot in dry-run mode, you may fill these fields with empty values.
+API Keys are usually only required for live trading (trading for real money, bot running in "production mode", executing real orders on the exchange) and are not required for the bot running in dry-run (trade simulation) mode. When you set up the bot in dry-run mode, you may fill these fields with empty values.
 
 ### To switch your bot in production mode
 
@@ -529,7 +545,7 @@ API Keys are usually only required for live trading (trading for real money, bot
 "dry_run": false,
 ```
 
-**Insert your Exchange API key (change them by fake api keys):**
+**Insert your Exchange API key (change them by fake API keys):**
 
 ```json
 {
@@ -547,7 +563,7 @@ API Keys are usually only required for live trading (trading for real money, bot
 You should also make sure to read the [Exchanges](exchanges.md) section of the documentation to be aware of potential configuration details specific to your exchange.
 
 !!! Hint "Keep your secrets secret"
-    To keep your secrets secret, we recommend to use a 2nd configuration for your API keys.
+    To keep your secrets secret, we recommend using a 2nd configuration for your API keys.
     Simply use the above snippet in a new configuration file (e.g. `config-private.json`) and keep your settings in this file.
     You can then start the bot with `freqtrade trade --config user_data/config.json --config user_data/config-private.json <...>` to have your keys loaded.
 
@@ -557,7 +573,7 @@ You should also make sure to read the [Exchanges](exchanges.md) section of the d
 
 To use a proxy with freqtrade, add the kwarg `"aiohttp_trust_env"=true` to the `"ccxt_async_kwargs"` dict in the exchange section of the configuration.
 
-An example for this can be found in `config_full.json.example`
+An example for this can be found in `config_examples/config_full.example.json`
 
 ``` json
 "ccxt_async_config": {

docs/data-download.md

@@ -271,7 +271,7 @@ mkdir -p user_data/data/binance
 cp tests/testdata/pairs.json user_data/data/binance
 ```
 
-If you your configuration directory `user_data` was made by docker, you may get the following error:
+If your configuration directory `user_data` was made by docker, you may get the following error:
 
 ```
 cp: cannot create regular file 'user_data/data/binance/pairs.json': Permission denied

docs/deprecated.md

@@ -33,3 +33,8 @@ The old section of configuration parameters (`"pairlist"`) has been deprecated i
 ### deprecation of bidVolume and askVolume from volume-pairlist
 
 Since only quoteVolume can be compared between assets, the other options (bidVolume, askVolume) have been deprecated in 2020.4, and have been removed in 2020.9.
+
+### Using order book steps for sell price
+
+Using `order_book_min` and `order_book_max` used to allow stepping the orderbook and trying to find the next ROI slot - trying to place sell-orders early.
+As this does however increase risk and provides no benefit, it's been removed for maintainability purposes in 2021.7.

docs/developer.md

@@ -2,7 +2,7 @@
 
 This page is intended for developers of Freqtrade, people who want to contribute to the Freqtrade codebase or documentation, or people who want to understand the source code of the application they're running.
 
-All contributions, bug reports, bug fixes, documentation improvements, enhancements and ideas are welcome. We [track issues](https://github.com/freqtrade/freqtrade/issues) on [GitHub](https://github.com) and also have a dev channel on [discord](https://discord.gg/p7nuUNVfP7) or [slack](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw) where you can ask questions.
+All contributions, bug reports, bug fixes, documentation improvements, enhancements and ideas are welcome. We [track issues](https://github.com/freqtrade/freqtrade/issues) on [GitHub](https://github.com) and also have a dev channel on [discord](https://discord.gg/p7nuUNVfP7) where you can ask questions.
 
 ## Documentation
 

docs/docker_quickstart.md

@@ -24,82 +24,21 @@ Freqtrade provides an official Docker image on [Dockerhub](https://hub.docker.co
 
 Create a new directory and place the [docker-compose file](https://raw.githubusercontent.com/freqtrade/freqtrade/stable/docker-compose.yml) in this directory.
 
-=== "PC/MAC/Linux"
-    ``` bash
-    mkdir ft_userdata
-    cd ft_userdata/
-    # Download the docker-compose file from the repository
-    curl https://raw.githubusercontent.com/freqtrade/freqtrade/stable/docker-compose.yml -o docker-compose.yml
+``` bash
+mkdir ft_userdata
+cd ft_userdata/
+# Download the docker-compose file from the repository
+curl https://raw.githubusercontent.com/freqtrade/freqtrade/stable/docker-compose.yml -o docker-compose.yml
 
-    # Pull the freqtrade image
-    docker-compose pull
+# Pull the freqtrade image
+docker-compose pull
 
-    # Create user directory structure
-    docker-compose run --rm freqtrade create-userdir --userdir user_data
+# Create user directory structure
+docker-compose run --rm freqtrade create-userdir --userdir user_data
 
-    # Create configuration - Requires answering interactive questions
-    docker-compose run --rm freqtrade new-config --config user_data/config.json
-    ```
-
-=== "RaspberryPi"
-    ``` bash
-    mkdir ft_userdata
-    cd ft_userdata/
-    # Download the docker-compose file from the repository
-    curl https://raw.githubusercontent.com/freqtrade/freqtrade/stable/docker-compose.yml -o docker-compose.yml
-
-    # Edit the compose file to use an image named `*_pi` (stable_pi or develop_pi)
-
-    # Pull the freqtrade image
-    docker-compose pull
-
-    # Create user directory structure
-    docker-compose run --rm freqtrade create-userdir --userdir user_data
-
-    # Create configuration - Requires answering interactive questions
-    docker-compose run --rm freqtrade new-config --config user_data/config.json
-    ```
-
-    !!! Note "Change your docker Image"
-        You have to change the docker image in the docker-compose file for your Raspberry build to work properly.
-        ``` yml
-        image: freqtradeorg/freqtrade:stable_pi
-        # image: freqtradeorg/freqtrade:develop_pi
-        ```
-
-=== "ARM 64 Systenms (Mac M1, Raspberry Pi 4, Jetson Nano)"
-    In case of a Mac M1, make sure that your docker installation is running in native mode
-    Arm64 images are not yet provided via Docker Hub and need to be build locally first.
-    Depending on the device, this may take a few minutes (Apple M1) or multiple hours (Raspberry Pi)
-
-    ``` bash
-    # Clone Freqtrade repository
-    git clone  https://github.com/freqtrade/freqtrade.git
-    cd freqtrade
-    # Optionally switch to the stable version
-    git checkout stable   
-
-    # Modify your docker-compose file to enable building and change the image name 
-    # (see the Note Box below for necessary changes)
-
-    # Build image
-    docker-compose build
-    
-    # Create user directory structure
-    docker-compose run --rm freqtrade create-userdir --userdir user_data
-
-    # Create configuration - Requires answering interactive questions
-    docker-compose run --rm freqtrade new-config --config user_data/config.json
-    ```
-
-    !!! Note "Change your docker Image"
-        You have to change the docker image in the docker-compose file for your arm64 build to work properly.
-        ``` yml
-        image: freqtradeorg/freqtrade:custom_arm64
-        build:
-          context: .
-          dockerfile: "Dockerfile"
-        ```
+# Create configuration - Requires answering interactive questions
+docker-compose run --rm freqtrade new-config --config user_data/config.json
+```
 
 The above snippet creates a new directory called `ft_userdata`, downloads the latest compose file and pulls the freqtrade image.
 The last 2 steps in the snippet create the directory with `user_data`, as well as (interactively) the default configuration based on your selections.
@@ -117,7 +56,7 @@ The last 2 steps in the snippet create the directory with `user_data`, as well a
 
 The `SampleStrategy` is run by default.
 
-!!! Warning "`SampleStrategy` is just a demo!"
+!!! Danger "`SampleStrategy` is just a demo!"
     The `SampleStrategy` is there for your reference and give you ideas for your own strategy.
     Please always backtest your strategy and use dry-run for some time before risking real money!
     You will find more information about Strategy development in the [Strategy documentation](strategy-customization.md).
@@ -167,6 +106,10 @@ Advanced users may edit the docker-compose file further to include all possible
 
 All freqtrade arguments will be available by running `docker-compose run --rm freqtrade <command> <optional arguments>`.
 
+!!! Warning "`docker-compose` for trade commands"
+    Trade commands (`freqtrade trade <...>`) should not be ran via `docker-compose run` - but should use `docker-compose up -d` instead.
+    This makes sure that the container is properly started (including port forwardings) and will make sure that the container will restart after a system reboot.
+
 !!! Note "`docker-compose run --rm`"
     Including `--rm` will remove the container after completion, and is highly recommended for all modes except trading mode (running with `freqtrade trade` command).
 

docs/exchanges.md

@@ -77,8 +77,9 @@ You can get a list of restricted markets by using the following snippet:
 ``` python
 import ccxt
 ct = ccxt.bittrex()
-_ = ct.load_markets()
-res = [ f"{x['MarketCurrency']}/{x['BaseCurrency']}" for x in ct.publicGetMarkets()['result'] if x['IsRestricted']]
+lm = ct.load_markets()
+
+res = [p for p, x in lm.items() if 'US' in x['info']['prohibitedIn']]
 print(res)
 ```
 

docs/faq.md

@@ -172,7 +172,7 @@ freqtrade hyperopt --hyperopt SampleHyperopt --hyperopt-loss SharpeHyperOptLossD
 
 ### Why does it take a long time to run hyperopt?
 
-* Discovering a great strategy with Hyperopt takes time. Study www.freqtrade.io, the Freqtrade Documentation page, join the Freqtrade [Slack community](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw) - or the Freqtrade [discord community](https://discord.gg/p7nuUNVfP7). While you patiently wait for the most advanced, free crypto bot in the world, to hand you a possible golden strategy specially designed just for you.
+* Discovering a great strategy with Hyperopt takes time. Study www.freqtrade.io, the Freqtrade Documentation page, join the Freqtrade [discord community](https://discord.gg/p7nuUNVfP7). While you patiently wait for the most advanced, free crypto bot in the world, to hand you a possible golden strategy specially designed just for you.
 
 * If you wonder why it can take from 20 minutes to days to do 1000 epochs here are some answers:
 

docs/hyperopt.md

@@ -51,7 +51,7 @@ usage: freqtrade hyperopt [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
                           [--spaces {all,buy,sell,roi,stoploss,trailing,default} [{all,buy,sell,roi,stoploss,trailing,default} ...]]
                           [--print-all] [--no-color] [--print-json] [-j JOBS]
                           [--random-state INT] [--min-trades INT]
-                          [--hyperopt-loss NAME]
+                          [--hyperopt-loss NAME] [--disable-param-export]
 
 optional arguments:
   -h, --help            show this help message and exit
@@ -118,6 +118,8 @@ optional arguments:
                         ShortTradeDurHyperOptLoss, OnlyProfitHyperOptLoss,
                         SharpeHyperOptLoss, SharpeHyperOptLossDaily,
                         SortinoHyperOptLoss, SortinoHyperOptLossDaily
+  --disable-param-export
+                        Disable automatic hyperopt parameter export.
 
 Common arguments:
   -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
@@ -403,6 +405,9 @@ While this strategy is most likely too simple to provide consistent profit, it s
 !!! Note
     `self.buy_ema_short.range` will act differently between hyperopt and other modes. For hyperopt, the above example may generate 48 new columns, however for all other modes (backtesting, dry/live), it will only generate the column for the selected value. You should therefore avoid using the resulting column with explicit values (values other than `self.buy_ema_short.value`).
 
+!!! Note
+    `range` property may also be used with `DecimalParameter` and `CategoricalParameter`. `RealParameter` does not provide this property due to infinite search space.
+
 ??? Hint "Performance tip"
     By doing the calculation of all possible indicators in `populate_indicators()`, the calculation of the indicator happens only once for every parameter.  
     While this may slow down the hyperopt startup speed, the overall performance will increase as the Hyperopt execution itself may pick the same value for multiple epochs (changing other values).
@@ -509,7 +514,13 @@ You should understand this result like:
 * You should not use ADX because `'buy_adx_enabled': False`.
 * You should **consider** using the RSI indicator (`'buy_rsi_enabled': True`) and the best value is `29.0` (`'buy_rsi': 29.0`)
 
-Your strategy class can immediately take advantage of these results. Simply copy hyperopt results block and paste them at class level, replacing old parameters (if any). New parameters will automatically be loaded next time strategy is executed.
+### Automatic parameter application to the strategy
+
+When using Hyperoptable parameters, the result of your hyperopt-run will be written to a json file next to your strategy (so for `MyAwesomeStrategy.py`, the file would be `MyAwesomeStrategy.json`).  
+This file is also updated when using the `hyperopt-show` sub-command, unless `--disable-param-export` is provided to either of the 2 commands.
+
+
+Your strategy class can also contain these results explicitly. Simply copy hyperopt results block and paste them at class level, replacing old parameters (if any). New parameters will automatically be loaded next time strategy is executed.
 
 Transferring your whole hyperopt result to your strategy would then look like:
 
@@ -525,6 +536,10 @@ class MyAwesomeStrategy(IStrategy):
     }
 ```
 
+!!! Note
+    Values in the configuration file will overwrite Parameter-file level parameters - and both will overwrite parameters within the strategy.
+    The prevalence is therefore: config > parameter file > strategy
+
 ### Understand Hyperopt ROI results
 
 If you are optimizing ROI (i.e. if optimization search-space contains 'all', 'default' or 'roi'), your result will look as follows and include a ROI table:

docs/includes/pairlists.md

@@ -23,6 +23,7 @@ You may also use something like `.*DOWN/BTC` or `.*UP/BTC` to exclude leveraged
 * [`StaticPairList`](#static-pair-list) (default, if not configured differently)
 * [`VolumePairList`](#volume-pair-list)
 * [`AgeFilter`](#agefilter)
+* [`OffsetFilter`](#offsetfilter)
 * [`PerformanceFilter`](#performancefilter)
 * [`PrecisionFilter`](#precisionfilter)
 * [`PriceFilter`](#pricefilter)
@@ -63,17 +64,56 @@ The `refresh_period` setting allows to define the period (in seconds), at which
 The pairlist cache (`refresh_period`) on `VolumePairList` is only applicable to generating pairlists.
 Filtering instances (not the first position in the list) will not apply any cache and will always use up-to-date data.
 
-`VolumePairList` is based on the ticker data from exchange, as reported by the ccxt library:
+`VolumePairList` is per default based on the ticker data from exchange, as reported by the ccxt library:
 
 * The `quoteVolume` is the amount of quote (stake) currency traded (bought or sold) in last 24 hours.
 
 ```json
-"pairlists": [{
+"pairlists": [
+    {
         "method": "VolumePairList",
         "number_assets": 20,
         "sort_key": "quoteVolume",
         "refresh_period": 1800
-}],
+    }
+],
+```
+
+`VolumePairList` can also operate in an advanced mode to build volume over a given timerange of specified candle size. It utilizes exchange historical candle data, builds a typical price (calculated by (open+high+low)/3) and multiplies the typical price with every candle's volume. The sum is the `quoteVolume` over the given range. This allows different scenarios, for a  more smoothened volume, when using longer ranges with larger candle sizes, or the opposite when using a short range with small candles.
+
+For convenience `lookback_days` can be specified, which will imply that 1d candles will be used for the lookback. In the example below the pairlist would be created based on the last 7 days:
+
+```json
+"pairlists": [
+    {
+        "method": "VolumePairList",
+        "number_assets": 20,
+        "sort_key": "quoteVolume",
+        "refresh_period": 86400,
+        "lookback_days": 7
+    }
+],
+```
+
+!!! Warning "Range look back and refresh period"
+    When used in conjunction with `lookback_days` and `lookback_timeframe` the `refresh_period` can not be smaller than the candle size in seconds. As this will result in unnecessary requests to the exchanges API.
+
+!!! Warning "Performance implications when using lookback range"
+    If used in first position in combination with lookback, the computation of the range based volume can be time and resource consuming, as it downloads candles for all tradable pairs. Hence it's highly advised to use the standard approach with `VolumeFilter` to narrow the pairlist down for further range volume calculation.
+
+More sophisticated approach can be used, by using `lookback_timeframe` for candle size and `lookback_period` which specifies the amount of candles. This example will build the volume pairs based on a rolling period of 3 days of 1h candles:
+
+```json
+"pairlists": [
+    {
+        "method": "VolumePairList",
+        "number_assets": 20,
+        "sort_key": "quoteVolume",
+        "refresh_period": 3600,
+        "lookback_timeframe": "1h",
+        "lookback_period": 72
+    }
+],
 ```
 
 !!! Note
@@ -81,13 +121,39 @@ Filtering instances (not the first position in the list) will not apply any cach
 
 #### AgeFilter
 
-Removes pairs that have been listed on the exchange for less than `min_days_listed` days (defaults to `10`).
+Removes pairs that have been listed on the exchange for less than `min_days_listed` days (defaults to `10`) or more than `max_days_listed` days (defaults `None` mean infinity).
 
 When pairs are first listed on an exchange they can suffer huge price drops and volatility
 in the first few days while the pair goes through its price-discovery period. Bots can often
 be caught out buying before the pair has finished dropping in price.
 
-This filter allows freqtrade to ignore pairs until they have been listed for at least `min_days_listed` days.
+This filter allows freqtrade to ignore pairs until they have been listed for at least `min_days_listed` days and listed before `max_days_listed`.
+
+#### OffsetFilter
+
+Offsets an incoming pairlist by a given `offset` value.
+
+As an example it can be used in conjunction with `VolumeFilter` to remove the top X volume pairs. Or to split
+a larger pairlist on two bot instances.
+
+Example to remove the first 10 pairs from the pairlist:
+
+```json
+"pairlists": [
+    {
+        "method": "OffsetFilter",
+        "offset": 10
+    }
+],
+```
+
+!!! Warning
+    When `OffsetFilter` is used to split a larger pairlist among multiple bots in combination with `VolumeFilter` 
+    it can not be guaranteed that pairs won't overlap due to slightly different refresh intervals for the
+    `VolumeFilter`.
+
+!!! Note
+    An offset larger then the total length of the incoming pairlist will result in an empty pairlist.
 
 #### PerformanceFilter
 

docs/includes/pricing.md

@@ -47,7 +47,7 @@ Also, prices at the "ask" side of the spread are higher than prices at the "bid"
 
 #### Buy price with Orderbook enabled
 
-When buying with the orderbook enabled (`bid_strategy.use_order_book=True`), Freqtrade fetches the `bid_strategy.order_book_top` entries from the orderbook and then uses the entry specified as `bid_strategy.order_book_top` on the configured side (`bid_strategy.price_side`) of the orderbook. 1 specifies the topmost entry in the orderbook, while 2 would use the 2nd entry in the orderbook, and so on.
+When buying with the orderbook enabled (`bid_strategy.use_order_book=True`), Freqtrade fetches the `bid_strategy.order_book_top` entries from the orderbook and uses the entry specified as `bid_strategy.order_book_top` on the configured side (`bid_strategy.price_side`) of the orderbook. 1 specifies the topmost entry in the orderbook, while 2 would use the 2nd entry in the orderbook, and so on.
 
 #### Buy price without Orderbook enabled
 
@@ -82,22 +82,9 @@ In line with that, if `ask_strategy.price_side` is set to `"bid"`, then the bot
 
 #### Sell price with Orderbook enabled
 
-When selling with the orderbook enabled (`ask_strategy.use_order_book=True`), Freqtrade fetches the `ask_strategy.order_book_max` entries in the orderbook. Then each of the orderbook steps between `ask_strategy.order_book_min` and `ask_strategy.order_book_max` on the configured orderbook side are validated for a profitable sell-possibility based on the strategy configuration (`minimal_roi` conditions) and the sell order is placed at the first profitable spot.
+When selling with the orderbook enabled (`ask_strategy.use_order_book=True`), Freqtrade fetches the `ask_strategy.order_book_top` entries in the orderbook and uses the entry specified as `ask_strategy.order_book_top` from the configured side (`ask_strategy.price_side`) as selling price.
 
-!!! Note
-    Using `order_book_max` higher than `order_book_min` only makes sense when ask_strategy.price_side is set to `"ask"`.
-
-The idea here is to place the sell order early, to be ahead in the queue.
-
-A fixed slot (mirroring `bid_strategy.order_book_top`) can be defined by setting `ask_strategy.order_book_min` and `ask_strategy.order_book_max` to the same number.
-
-!!! Warning "Order_book_max > 1 - increased risks for stoplosses!"
-    Using `ask_strategy.order_book_max` higher than 1 will increase the risk the stoploss on exchange is cancelled too early, since an eventual [stoploss on exchange](#understand-order_types) will be cancelled as soon as the order is placed.
-    Also, the sell order will remain on the exchange for `unfilledtimeout.sell` (or until it's filled) - which can lead to missed stoplosses (with or without using stoploss on exchange).
-
-!!! Warning "Order_book_max > 1 in dry-run"
-    Using `ask_strategy.order_book_max` higher than 1 will result in improper dry-run results (significantly better than real orders executed on exchange), since dry-run assumes orders to be filled almost instantly.
-    It is therefore advised to not use this setting for dry-runs.
+1 specifies the topmost entry in the orderbook, while 2 would use the 2nd entry in the orderbook, and so on.
 
 #### Sell price without Orderbook enabled
 

docs/includes/protections.md

@@ -1,7 +1,7 @@
 ## Protections
 
 !!! Warning "Beta feature"
-    This feature is still in it's testing phase. Should you notice something you think is wrong please let us know via Discord, Slack or via Github Issue.
+    This feature is still in it's testing phase. Should you notice something you think is wrong please let us know via Discord or via Github Issue.
 
 Protections will protect your strategy from unexpected events and market conditions by temporarily stop trading for either one pair, or for all pairs.
 All protection end times are rounded up to the next candle to avoid sudden, unexpected intra-candle buys.

docs/index.md

@@ -47,6 +47,7 @@ Please read the [exchange specific notes](exchanges.md) to learn about eventual,
 Exchanges confirmed working by the community:
 
 - [X] [Bitvavo](https://bitvavo.com/)
+- [X] [Kukoin](https://www.kucoin.com/)
 
 ## Requirements
 
@@ -72,13 +73,9 @@ Alternatively
 
 ## Support
 
-### Help / Discord / Slack
+### Help / Discord
 
-For any questions not covered by the documentation or for further information about the bot, or to simply engage with like-minded individuals, we encourage you to join our slack channel.
-
-Please check out our [discord server](https://discord.gg/p7nuUNVfP7).
-
-You can also join our [Slack channel](https://join.slack.com/t/highfrequencybot/shared_invite/zt-mm786y93-Fxo37glxMY9g8OQC5AoOIw).
+For any questions not covered by the documentation or for further information about the bot, or to simply engage with like-minded individuals, we encourage you to join the Freqtrade [discord server](https://discord.gg/p7nuUNVfP7).
 
 ## Ready to try?
 

docs/installation.md

@@ -203,6 +203,8 @@ sed -i.bak "s|0.00000001|0.000000000000000001 |g" src/ta_func/ta_utility.h
 ./configure --prefix=/usr/local
 make
 sudo make install
+# On debian based systems (debian, ubuntu, ...) - updating ldconfig might be necessary.
+sudo ldconfig  
 cd ..
 rm -rf ./ta-lib*
 ```

docs/requirements-docs.txt

@@ -1,4 +1,4 @@
-mkdocs==1.2.1
-mkdocs-material==7.1.8
+mkdocs==1.2.2
+mkdocs-material==7.2.1
 mdx_truly_sane_lists==1.2
 pymdown-extensions==8.2

docs/strategy-advanced.md

@@ -55,7 +55,7 @@ class AwesomeStrategy(IStrategy):
         dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
 
         # Obtain last available candle. Do not use current_time to look up latest candle, because 
-        # current_time points to curret incomplete candle whose data is not available.
+        # current_time points to current incomplete candle whose data is not available.
         last_candle = dataframe.iloc[-1].squeeze()
         # <...>
 
@@ -83,7 +83,7 @@ It is possible to define custom sell signals, indicating that specified position
 
 For example you could implement a 1:2 risk-reward ROI with `custom_sell()`.
 
-Using custom_sell() signals in place of stoplosses though *is not recommended*. It is a inferior method to using `custom_stoploss()` in this regard - which also allows you to keep the stoploss on exchange.
+Using custom_sell() signals in place of stoploss though *is not recommended*. It is a inferior method to using `custom_stoploss()` in this regard - which also allows you to keep the stoploss on exchange.
 
 !!! Note
     Returning a `string` or `True` from this method is equal to setting sell signal on a candle at specified time. This method is not called when sell signal is set already, or if sell signals are disabled (`use_sell_signal=False` or `sell_profit_only=True` while profit is below `sell_profit_offset`). `string` max length is 64 characters. Exceeding this limit will cause the message to be truncated to 64 characters.
@@ -243,7 +243,7 @@ class AwesomeStrategy(IStrategy):
                         current_rate: float, current_profit: float, **kwargs) -> float:
 
         if current_profit < 0.04:
-            return -1 # return a value bigger than the inital stoploss to keep using the inital stoploss
+            return -1 # return a value bigger than the initial stoploss to keep using the initial stoploss
 
         # After reaching the desired offset, allow the stoploss to trail by half the profit
         desired_stoploss = current_profit / 2
@@ -454,7 +454,7 @@ class AwesomeStrategy(IStrategy):
     # ... populate_* methods
 
     def confirm_trade_entry(self, pair: str, order_type: str, amount: float, rate: float,
-                            time_in_force: str, **kwargs) -> bool:
+                            time_in_force: str, current_time: datetime, **kwargs) -> bool:
         """
         Called right before placing a buy order.
         Timing for this function is critical, so avoid doing heavy computations or
@@ -469,6 +469,7 @@ class AwesomeStrategy(IStrategy):
         :param amount: Amount in target (quote) currency that's going to be traded.
         :param rate: Rate that's going to be used when using limit orders
         :param time_in_force: Time in force. Defaults to GTC (Good-til-cancelled).
+        :param current_time: datetime object, containing the current datetime
         :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
         :return bool: When True is returned, then the buy-order is placed on the exchange.
             False aborts the process
@@ -490,7 +491,8 @@ class AwesomeStrategy(IStrategy):
     # ... populate_* methods
 
     def confirm_trade_exit(self, pair: str, trade: Trade, order_type: str, amount: float,
-                           rate: float, time_in_force: str, sell_reason: str, **kwargs) -> bool:
+                           rate: float, time_in_force: str, sell_reason: str,
+                           current_time: datetime, **kwargs) -> bool:
         """
         Called right before placing a regular sell order.
         Timing for this function is critical, so avoid doing heavy computations or
@@ -508,6 +510,7 @@ class AwesomeStrategy(IStrategy):
         :param sell_reason: Sell reason.
             Can be any of ['roi', 'stop_loss', 'stoploss_on_exchange', 'trailing_stop_loss',
                            'sell_signal', 'force_sell', 'emergency_sell']
+        :param current_time: datetime object, containing the current datetime
         :param **kwargs: Ensure to keep this here so updates to this won't break your strategy.
         :return bool: When True is returned, then the sell-order is placed on the exchange.
             False aborts the process
@@ -521,6 +524,39 @@ class AwesomeStrategy(IStrategy):
 
 ```
 
+### Stake size management
+
+It is possible to manage your risk by reducing or increasing stake amount when placing a new trade.
+
+```python
+class AwesomeStrategy(IStrategy):
+    def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
+                            proposed_stake: float, min_stake: float, max_stake: float,
+                            **kwargs) -> float:
+
+        dataframe, _ = self.dp.get_analyzed_dataframe(pair=pair, timeframe=self.timeframe)
+        current_candle = dataframe.iloc[-1].squeeze()
+
+        if current_candle['fastk_rsi_1h'] > current_candle['fastd_rsi_1h']:
+            if self.config['stake_amount'] == 'unlimited':
+                # Use entire available wallet during favorable conditions when in compounding mode.
+                return max_stake
+            else:
+                # Compound profits during favorable conditions instead of using a static stake.
+                return self.wallets.get_total_stake_amount() / self.config['max_open_trades']
+
+        # Use default stake amount.
+        return proposed_stake
+```
+
+Freqtrade will fall back to the `proposed_stake` value should your code raise an exception. The exception itself will be logged.
+
+!!! Tip
+    You do not _have_ to ensure that `min_stake <= returned_value <= max_stake`. Trades will succeed as the returned value will be clamped to supported range and this acton will be logged.
+
+!!! Tip
+    Returning `0` or `None` will prevent trades from being placed.
+
 ---
 
 ## Derived strategies

docs/strategy_analysis_example.md

@@ -130,6 +130,44 @@ trades = load_backtest_data(backtest_dir)
 trades.groupby("pair")["sell_reason"].value_counts()
 ```
 
+## Plotting daily profit / equity line
+
+
+```python
+# Plotting equity line (starting with 0 on day 1 and adding daily profit for each backtested day)
+
+from freqtrade.configuration import Configuration
+from freqtrade.data.btanalysis import load_backtest_data, load_backtest_stats
+import plotly.express as px
+import pandas as pd
+
+# strategy = 'SampleStrategy'
+# config = Configuration.from_files(["user_data/config.json"])
+# backtest_dir = config["user_data_dir"] / "backtest_results"
+
+stats = load_backtest_stats(backtest_dir)
+strategy_stats = stats['strategy'][strategy]
+
+dates = []
+profits = []
+for date_profit in strategy_stats['daily_profit']:
+    dates.append(date_profit[0])
+    profits.append(date_profit[1])
+
+equity = 0
+equity_daily = []
+for daily_profit in profits:
+    equity_daily.append(equity)
+    equity += float(daily_profit)
+
+
+df = pd.DataFrame({'dates': dates,'equity_daily': equity_daily})
+
+fig = px.line(df, x="dates", y="equity_daily")
+fig.show()
+
+```
+
 ### Load live trading results into a pandas dataframe
 
 In case you did already some trading and want to analyze your performance

docs/telegram-usage.md

@@ -245,10 +245,10 @@ current    max
 Return a summary of your profit/loss and performance.
 
 > **ROI:** Close trades  
->   ∙ `0.00485701 BTC (258.45%)`  
+>   ∙ `0.00485701 BTC (2.2%) (15.2 Σ%)`  
 >   ∙ `62.968 USD`  
 > **ROI:** All trades  
->   ∙ `0.00255280 BTC (143.43%)`  
+>   ∙ `0.00255280 BTC (1.5%) (6.43 Σ%)`  
 >   ∙ `33.095 EUR`  
 >  
 > **Total Trade Count:** `138`  
@@ -257,6 +257,10 @@ Return a summary of your profit/loss and performance.
 > **Avg. Duration:** `2:33:45`  
 > **Best Performing:** `PAY/BTC: 50.23%`  
 
+The relative profit of `1.2%` is the average profit per trade.  
+The relative profit of `15.2 Σ%` is be based on the starting capital - so in this case, the starting capital was `0.00485701 * 1.152 = 0.00738 BTC`.
+Starting capital is either taken from the `available_capital` setting, or calculated by using current wallet size - profits.
+
 ### /forcesell <trade_id>
 
 > **BITTREX:** Selling BTC/LTC with limit `0.01650000 (profit: ~-4.07%, -0.00008168)`

docs/utils.md

@@ -614,6 +614,48 @@ Show whitelist when using a [dynamic pairlist](plugins.md#pairlists).
 freqtrade test-pairlist --config config.json --quote USDT BTC
 ```
 
+## Webserver mode
+
+!!! Warning "Experimental"
+    Webserver mode is an experimental mode to increase backesting and strategy development productivity.
+    There may still be bugs - so if you happen to stumble across these, please report them as github issues, thanks.
+
+Run freqtrade in webserver mode.
+Freqtrade will start the webserver and allow FreqUI to start and control backtesting processes.
+This has the advantage that data will not be reloaded between backtesting runs (as long as timeframe and timerange remain identical).
+FreqUI will also show the backtesting results.
+
+```
+usage: freqtrade webserver [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
+                           [--userdir PATH] [-s NAME] [--strategy-path PATH]
+
+optional arguments:
+  -h, --help            show this help message and exit
+
+Common arguments:
+  -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).
+  --logfile FILE        Log to the file specified. Special values are:
+                        'syslog', 'journald'. See the documentation for more
+                        details.
+  -V, --version         show program's version number and exit
+  -c PATH, --config PATH
+                        Specify configuration file (default:
+                        `userdir/config.json` or `config.json` whichever
+                        exists). Multiple --config options may be used. Can be
+                        set to `-` to read config from stdin.
+  -d PATH, --datadir PATH
+                        Path to directory with historical backtesting data.
+  --userdir PATH, --user-data-dir PATH
+                        Path to userdata directory.
+
+Strategy arguments:
+  -s NAME, --strategy NAME
+                        Specify strategy class name which will be used by the
+                        bot.
+  --strategy-path PATH  Specify additional strategy lookup path.
+
+```
+
 ## List Hyperopt results
 
 You can list the hyperoptimization epochs the Hyperopt module evaluated previously with the `hyperopt-list` sub-command.
@@ -702,7 +744,8 @@ You can show the details of any hyperoptimization epoch previously evaluated by
 usage: freqtrade hyperopt-show [-h] [-v] [--logfile FILE] [-V] [-c PATH]
                                [-d PATH] [--userdir PATH] [--best]
                                [--profitable] [-n INT] [--print-json]
-                               [--hyperopt-filename PATH] [--no-header]
+                               [--hyperopt-filename FILENAME] [--no-header]
+                               [--disable-param-export]
 
 optional arguments:
   -h, --help            show this help message and exit
@@ -714,6 +757,8 @@ optional arguments:
                         Hyperopt result filename.Example: `--hyperopt-
                         filename=hyperopt_results_2020-09-27_16-20-48.pickle`
   --no-header           Do not print epoch details header.
+  --disable-param-export
+                        Disable automatic hyperopt parameter export.
 
 Common arguments:
   -v, --verbose         Verbose mode (-vv for more, -vvv to get all messages).

docs/windows_installation.md

@@ -23,7 +23,7 @@ git clone https://github.com/freqtrade/freqtrade.git
 
 Install ta-lib according to the [ta-lib documentation](https://github.com/mrjbq7/ta-lib#windows).
 
-As compiling from source on windows has heavy dependencies (requires a partial visual studio installation), there is also a repository of unofficial pre-compiled windows Wheels [here](https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib), which needs to be downloaded and installed using `pip install TA_Lib‑0.4.20‑cp38‑cp38‑win_amd64.whl` (make sure to use the version matching your python version).
+As compiling from source on windows has heavy dependencies (requires a partial visual studio installation), there is also a repository of unofficial pre-compiled windows Wheels [here](https://www.lfd.uci.edu/~gohlke/pythonlibs/#ta-lib), which need to be downloaded and installed using `pip install TA_Lib-0.4.21-cp38-cp38-win_amd64.whl` (make sure to use the version matching your python version).
 
 Freqtrade provides these dependencies for the latest 2 Python versions (3.7 and 3.8) and for 64bit Windows.
 Other versions must be downloaded from the above link.

freqtrade/__init__.py

@@ -1,5 +1,5 @@
 """ Freqtrade bot """
-__version__ = '2021.6'
+__version__ = '2021.7'
 
 if __version__ == 'develop':
 

freqtrade/commands/__init__.py

@@ -20,3 +20,4 @@ from freqtrade.commands.optimize_commands import start_backtesting, start_edge,
 from freqtrade.commands.pairlist_commands import start_test_pairlist
 from freqtrade.commands.plot_commands import start_plot_dataframe, start_plot_profit
 from freqtrade.commands.trade_commands import start_trading
+from freqtrade.commands.webserver_commands import start_webserver

freqtrade/commands/arguments.py

@@ -16,6 +16,8 @@ ARGS_STRATEGY = ["strategy", "strategy_path"]
 
 ARGS_TRADE = ["db_url", "sd_notify", "dry_run", "dry_run_wallet", "fee"]
 
+ARGS_WEBSERVER: List[str] = []
+
 ARGS_COMMON_OPTIMIZE = ["timeframe", "timerange", "dataformat_ohlcv",
                         "max_open_trades", "stake_amount", "fee", "pairs"]
 
@@ -29,7 +31,7 @@ ARGS_HYPEROPT = ARGS_COMMON_OPTIMIZE + ["hyperopt", "hyperopt_path",
                                         "epochs", "spaces", "print_all",
                                         "print_colorized", "print_json", "hyperopt_jobs",
                                         "hyperopt_random_state", "hyperopt_min_trades",
-                                        "hyperopt_loss"]
+                                        "hyperopt_loss", "disableparamexport"]
 
 ARGS_EDGE = ARGS_COMMON_OPTIMIZE + ["stoploss_range"]
 
@@ -85,7 +87,8 @@ ARGS_HYPEROPT_LIST = ["hyperopt_list_best", "hyperopt_list_profitable",
                       "hyperoptexportfilename", "export_csv"]
 
 ARGS_HYPEROPT_SHOW = ["hyperopt_list_best", "hyperopt_list_profitable", "hyperopt_show_index",
-                      "print_json", "hyperoptexportfilename", "hyperopt_show_no_header"]
+                      "print_json", "hyperoptexportfilename", "hyperopt_show_no_header",
+                      "disableparamexport"]
 
 NO_CONF_REQURIED = ["convert-data", "convert-trade-data", "download-data", "list-timeframes",
                     "list-markets", "list-pairs", "list-strategies", "list-data",
@@ -175,7 +178,8 @@ class Arguments:
                                         start_list_markets, start_list_strategies,
                                         start_list_timeframes, start_new_config, start_new_hyperopt,
                                         start_new_strategy, start_plot_dataframe, start_plot_profit,
-                                        start_show_trades, start_test_pairlist, start_trading)
+                                        start_show_trades, start_test_pairlist, start_trading,
+                                        start_webserver)
 
         subparsers = self.parser.add_subparsers(dest='command',
                                                 # Use custom message when no subhandler is added
@@ -383,3 +387,9 @@ class Arguments:
         )
         plot_profit_cmd.set_defaults(func=start_plot_profit)
         self._build_args(optionlist=ARGS_PLOT_PROFIT, parser=plot_profit_cmd)
+
+        # Add webserver subcommand
+        webserver_cmd = subparsers.add_parser('webserver', help='Webserver module.',
+                                              parents=[_common_parser])
+        webserver_cmd.set_defaults(func=start_webserver)
+        self._build_args(optionlist=ARGS_WEBSERVER, parser=webserver_cmd)

freqtrade/commands/cli_options.py

@@ -178,6 +178,11 @@ AVAILABLE_CLI_OPTIONS = {
         'Example: `--export-filename=user_data/backtest_results/backtest_today.json`',
         metavar='PATH',
     ),
+    "disableparamexport": Arg(
+        '--disable-param-export',
+        help="Disable automatic hyperopt parameter export.",
+        action='store_true',
+    ),
     "fee": Arg(
         '--fee',
         help='Specify fee ratio. Will be applied twice (on trade entry and exit).',

freqtrade/commands/data_commands.py

@@ -48,7 +48,8 @@ def start_download_data(args: Dict[str, Any]) -> None:
     # Init exchange
     exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config, validate=False)
     # Manual validations of relevant settings
-    exchange.validate_pairs(config['pairs'])
+    if not config['exchange'].get('skip_pair_validation', False):
+        exchange.validate_pairs(config['pairs'])
     expanded_pairs = expand_pairlist(config['pairs'], list(exchange.markets))
 
     logger.info(f"About to download pairs: {expanded_pairs}, "

freqtrade/commands/hyperopt_commands.py

@@ -129,9 +129,12 @@ def start_hyperopt_show(args: Dict[str, Any]) -> None:
 
         metrics = val['results_metrics']
         if 'strategy_name' in metrics:
-            show_backtest_result(metrics['strategy_name'], metrics,
+            strategy_name = metrics['strategy_name']
+            show_backtest_result(strategy_name, metrics,
                                  metrics['stake_currency'])
 
+            HyperoptTools.try_export_params(config, strategy_name, val)
+
         HyperoptTools.show_epoch_details(val, total_epochs, print_json, no_header,
                                          header_str="Epoch details")
 

freqtrade/commands/list_commands.py

@@ -14,7 +14,7 @@ from freqtrade.constants import USERPATH_HYPEROPTS, USERPATH_STRATEGIES
 from freqtrade.enums import RunMode
 from freqtrade.exceptions import OperationalException
 from freqtrade.exchange import market_is_active, validate_exchanges
-from freqtrade.misc import plural
+from freqtrade.misc import parse_db_uri_for_logging, plural
 from freqtrade.resolvers import ExchangeResolver, StrategyResolver
 
 
@@ -225,7 +225,7 @@ def start_show_trades(args: Dict[str, Any]) -> None:
     if 'db_url' not in config:
         raise OperationalException("--db-url is required for this command.")
 
-    logger.info(f'Using DB: "{config["db_url"]}"')
+    logger.info(f'Using DB: "{parse_db_uri_for_logging(config["db_url"])}"')
     init_db(config['db_url'], clean_open_orders=False)
     tfilter = []
 

freqtrade/commands/webserver_commands.py

@@ -0,0 +1,15 @@
+from typing import Any, Dict
+
+from freqtrade.enums import RunMode
+
+
+def start_webserver(args: Dict[str, Any]) -> None:
+    """
+    Main entry point for webserver mode
+    """
+    from freqtrade.configuration import Configuration
+    from freqtrade.rpc.api_server import ApiServer
+
+    # Initialize configuration
+    config = Configuration(args, RunMode.WEBSERVER).get_config()
+    ApiServer(config, standalone=True)

freqtrade/configuration/config_validation.py

@@ -79,6 +79,7 @@ def validate_config_consistency(conf: Dict[str, Any]) -> None:
     _validate_whitelist(conf)
     _validate_protections(conf)
     _validate_unlimited_amount(conf)
+    _validate_ask_orderbook(conf)
 
     # validate configuration before returning
     logger.info('Validating configuration ...')
@@ -149,7 +150,7 @@ def _validate_edge(conf: Dict[str, Any]) -> None:
     if not conf.get('edge', {}).get('enabled'):
         return
 
-    if not conf.get('ask_strategy', {}).get('use_sell_signal', True):
+    if not conf.get('use_sell_signal', True):
         raise OperationalException(
             "Edge requires `use_sell_signal` to be True, otherwise no sells will happen."
         )
@@ -186,3 +187,23 @@ def _validate_protections(conf: Dict[str, Any]) -> None:
                 "Protections must specify either `lookback_period` or `lookback_period_candles`.\n"
                 f"Please fix the protection {prot.get('method')}"
             )
+
+
+def _validate_ask_orderbook(conf: Dict[str, Any]) -> None:
+    ask_strategy = conf.get('ask_strategy', {})
+    ob_min = ask_strategy.get('order_book_min')
+    ob_max = ask_strategy.get('order_book_max')
+    if ob_min is not None and ob_max is not None and ask_strategy.get('use_order_book'):
+        if ob_min != ob_max:
+            raise OperationalException(
+                "Using order_book_max != order_book_min in ask_strategy is no longer supported."
+                "Please pick one value and use `order_book_top` in the future."
+            )
+        else:
+            # Move value to order_book_top
+            ask_strategy['order_book_top'] = ob_min
+            logger.warning(
+                "DEPRECATED: "
+                "Please use `order_book_top` instead of `order_book_min` and `order_book_max` "
+                "for your `ask_strategy` configuration."
+            )

freqtrade/configuration/configuration.py

@@ -15,7 +15,7 @@ from freqtrade.configuration.load_config import load_config_file, load_file
 from freqtrade.enums import NON_UTIL_MODES, TRADING_MODES, RunMode
 from freqtrade.exceptions import OperationalException
 from freqtrade.loggers import setup_logging
-from freqtrade.misc import deep_merge_dicts
+from freqtrade.misc import deep_merge_dicts, parse_db_uri_for_logging
 
 
 logger = logging.getLogger(__name__)
@@ -71,7 +71,7 @@ class Configuration:
 
             # Merge config options, overwriting old values
             config = deep_merge_dicts(load_config_file(path), config)
-
+        config['config_files'] = files
         # Normalize config
         if 'internals' not in config:
             config['internals'] = {}
@@ -144,7 +144,7 @@ class Configuration:
                 config['db_url'] = constants.DEFAULT_DB_PROD_URL
             logger.info('Dry run is disabled')
 
-        logger.info(f'Using DB: "{config["db_url"]}"')
+        logger.info(f'Using DB: "{parse_db_uri_for_logging(config["db_url"])}"')
 
     def _process_common_options(self, config: Dict[str, Any]) -> None:
 
@@ -260,6 +260,8 @@ class Configuration:
         self._args_to_config(config, argname='export',
                              logstring='Parameter --export detected: {} ...')
 
+        self._args_to_config(config, argname='disableparamexport',
+                             logstring='Parameter --disableparamexport detected: {} ...')
         # Edge section:
         if 'stoploss_range' in self.args and self.args["stoploss_range"]:
             txt_range = eval(self.args["stoploss_range"])

freqtrade/configuration/deprecated_settings.py

@@ -3,7 +3,7 @@ Functions to handle deprecated settings
 """
 
 import logging
-from typing import Any, Dict
+from typing import Any, Dict, Optional
 
 from freqtrade.exceptions import OperationalException
 
@@ -12,23 +12,24 @@ logger = logging.getLogger(__name__)
 
 
 def check_conflicting_settings(config: Dict[str, Any],
-                               section1: str, name1: str,
-                               section2: str, name2: str) -> None:
-    section1_config = config.get(section1, {})
-    section2_config = config.get(section2, {})
-    if name1 in section1_config and name2 in section2_config:
+                               section_old: str, name_old: str,
+                               section_new: Optional[str], name_new: str) -> None:
+    section_new_config = config.get(section_new, {}) if section_new else config
+    section_old_config = config.get(section_old, {})
+    if name_new in section_new_config and name_old in section_old_config:
+        new_name = f"{section_new}.{name_new}" if section_new else f"{name_new}"
         raise OperationalException(
-            f"Conflicting settings `{section1}.{name1}` and `{section2}.{name2}` "
+            f"Conflicting settings `{new_name}` and `{section_old}.{name_old}` "
             "(DEPRECATED) detected in the configuration file. "
             "This deprecated setting will be removed in the next versions of Freqtrade. "
-            f"Please delete it from your configuration and use the `{section1}.{name1}` "
+            f"Please delete it from your configuration and use the `{new_name}` "
             "setting instead."
         )
 
 
 def process_removed_setting(config: Dict[str, Any],
                             section1: str, name1: str,
-                            section2: str, name2: str) -> None:
+                            section2: Optional[str], name2: str) -> None:
     """
     :param section1: Removed section
     :param name1: Removed setting name
@@ -37,27 +38,32 @@ def process_removed_setting(config: Dict[str, Any],
     """
     section1_config = config.get(section1, {})
     if name1 in section1_config:
+        section_2 = f"{section2}.{name2}" if section2 else f"{name2}"
         raise OperationalException(
-            f"Setting `{section1}.{name1}` has been moved to `{section2}.{name2}. "
-            f"Please delete it from your configuration and use the `{section2}.{name2}` "
+            f"Setting `{section1}.{name1}` has been moved to `{section_2}. "
+            f"Please delete it from your configuration and use the `{section_2}` "
             "setting instead."
         )
 
 
 def process_deprecated_setting(config: Dict[str, Any],
-                               section1: str, name1: str,
-                               section2: str, name2: str) -> None:
-    section2_config = config.get(section2, {})
+                               section_old: str, name_old: str,
+                               section_new: Optional[str], name_new: str
+                               ) -> None:
+    check_conflicting_settings(config, section_old, name_old, section_new, name_new)
+    section_old_config = config.get(section_old, {})
 
-    if name2 in section2_config:
+    if name_old in section_old_config:
+        section_2 = f"{section_new}.{name_new}" if section_new else f"{name_new}"
         logger.warning(
             "DEPRECATED: "
-            f"The `{section2}.{name2}` setting is deprecated and "
+            f"The `{section_old}.{name_old}` setting is deprecated and "
             "will be removed in the next versions of Freqtrade. "
-            f"Please use the `{section1}.{name1}` setting in your configuration instead."
+            f"Please use the `{section_2}` setting in your configuration instead."
         )
-        section1_config = config.get(section1, {})
-        section1_config[name1] = section2_config[name2]
+
+        section_new_config = config.get(section_new, {}) if section_new else config
+        section_new_config[name_new] = section_old_config[name_old]
 
 
 def process_temporary_deprecated_settings(config: Dict[str, Any]) -> None:
@@ -65,15 +71,24 @@ def process_temporary_deprecated_settings(config: Dict[str, Any]) -> None:
     # Kept for future deprecated / moved settings
     # check_conflicting_settings(config, 'ask_strategy', 'use_sell_signal',
     #                            'experimental', 'use_sell_signal')
-    # process_deprecated_setting(config, 'ask_strategy', 'use_sell_signal',
-    #                            'experimental', 'use_sell_signal')
+    process_deprecated_setting(config, 'ask_strategy', 'use_sell_signal',
+                               None, 'use_sell_signal')
+    process_deprecated_setting(config, 'ask_strategy', 'sell_profit_only',
+                               None, 'sell_profit_only')
+    process_deprecated_setting(config, 'ask_strategy', 'sell_profit_offset',
+                               None, 'sell_profit_offset')
+    process_deprecated_setting(config, 'ask_strategy', 'ignore_roi_if_buy_signal',
+                               None, 'ignore_roi_if_buy_signal')
+    process_deprecated_setting(config, 'ask_strategy', 'ignore_buying_expired_candle_after',
+                               None, 'ignore_buying_expired_candle_after')
 
+    # Legacy way - having them in experimental ...
     process_removed_setting(config, 'experimental', 'use_sell_signal',
-                            'ask_strategy', 'use_sell_signal')
+                            None, 'use_sell_signal')
     process_removed_setting(config, 'experimental', 'sell_profit_only',
-                            'ask_strategy', 'sell_profit_only')
+                            None, 'sell_profit_only')
     process_removed_setting(config, 'experimental', 'ignore_roi_if_buy_signal',
-                            'ask_strategy', 'ignore_roi_if_buy_signal')
+                            None, 'ignore_roi_if_buy_signal')
 
     if (config.get('edge', {}).get('enabled', False)
        and 'capital_available_percentage' in config.get('edge', {})):

freqtrade/constants.py

@@ -26,9 +26,9 @@ HYPEROPT_LOSS_BUILTIN = ['ShortTradeDurHyperOptLoss', 'OnlyProfitHyperOptLoss',
                          'SharpeHyperOptLoss', 'SharpeHyperOptLossDaily',
                          'SortinoHyperOptLoss', 'SortinoHyperOptLossDaily']
 AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList',
-                       'AgeFilter', 'PerformanceFilter', 'PrecisionFilter',
-                       'PriceFilter', 'RangeStabilityFilter', 'ShuffleFilter',
-                       'SpreadFilter', 'VolatilityFilter']
+                       'AgeFilter', 'OffsetFilter', 'PerformanceFilter',
+                       'PrecisionFilter', 'PriceFilter', 'RangeStabilityFilter',
+                       'ShuffleFilter', 'SpreadFilter', 'VolatilityFilter']
 AVAILABLE_PROTECTIONS = ['CooldownPeriod', 'LowProfitPairs', 'MaxDrawdown', 'StoplossGuard']
 AVAILABLE_DATAHANDLERS = ['json', 'jsongz', 'hdf5']
 DRY_RUN_WALLET = 1000
@@ -40,6 +40,7 @@ DEFAULT_DATAFRAME_COLUMNS = ['date', 'open', 'high', 'low', 'close', 'volume']
 DEFAULT_TRADES_COLUMNS = ['timestamp', 'id', 'type', 'side', 'price', 'amount', 'cost']
 
 LAST_BT_RESULT_FN = '.last_result.json'
+FTHYPT_FILEVERSION = 'fthypt_fileversion'
 
 USERPATH_HYPEROPTS = 'hyperopts'
 USERPATH_STRATEGIES = 'strategies'
@@ -112,6 +113,10 @@ CONF_SCHEMA = {
             'maximum': 1,
             'default': 0.99
         },
+        'available_capital': {
+            'type': 'number',
+            'minimum': 0,
+        },
         'amend_last_stake_amount': {'type': 'boolean', 'default': False},
         'last_stake_amount_min_ratio': {
             'type': 'number', 'minimum': 0.0, 'maximum': 1.0, 'default': 0.5
@@ -134,6 +139,11 @@ CONF_SCHEMA = {
         'trailing_stop_positive': {'type': 'number', 'minimum': 0, 'maximum': 1},
         'trailing_stop_positive_offset': {'type': 'number', 'minimum': 0, 'maximum': 1},
         'trailing_only_offset_is_reached': {'type': 'boolean'},
+        'use_sell_signal': {'type': 'boolean'},
+        'sell_profit_only': {'type': 'boolean'},
+        'sell_profit_offset': {'type': 'number'},
+        'ignore_roi_if_buy_signal': {'type': 'boolean'},
+        'ignore_buying_expired_candle_after': {'type': 'number'},
         'bot_name': {'type': 'string'},
         'unfilledtimeout': {
             'type': 'object',
@@ -154,7 +164,7 @@ CONF_SCHEMA = {
                 },
                 'price_side': {'type': 'string', 'enum': ORDERBOOK_SIDES, 'default': 'bid'},
                 'use_order_book': {'type': 'boolean'},
-                'order_book_top': {'type': 'integer', 'maximum': 20, 'minimum': 1},
+                'order_book_top': {'type': 'integer', 'minimum': 1, 'maximum': 50, },
                 'check_depth_of_market': {
                     'type': 'object',
                     'properties': {
@@ -163,7 +173,7 @@ CONF_SCHEMA = {
                     }
                 },
             },
-            'required': ['ask_last_balance']
+            'required': ['price_side']
         },
         'ask_strategy': {
             'type': 'object',
@@ -176,13 +186,9 @@ CONF_SCHEMA = {
                     'exclusiveMaximum': False,
                 },
                 'use_order_book': {'type': 'boolean'},
-                'order_book_min': {'type': 'integer', 'minimum': 1},
-                'order_book_max': {'type': 'integer', 'minimum': 1, 'maximum': 50},
-                'use_sell_signal': {'type': 'boolean'},
-                'sell_profit_only': {'type': 'boolean'},
-                'sell_profit_offset': {'type': 'number'},
-                'ignore_roi_if_buy_signal': {'type': 'boolean'}
-            }
+                'order_book_top': {'type': 'integer', 'minimum': 1, 'maximum': 50, },
+            },
+            'required': ['price_side']
         },
         'order_types': {
             'type': 'object',
@@ -311,6 +317,7 @@ CONF_SCHEMA = {
         },
         'db_url': {'type': 'string'},
         'export': {'type': 'string', 'enum': EXPORT_OPTIONS, 'default': 'trades'},
+        'disableparamexport': {'type': 'boolean'},
         'initial_state': {'type': 'string', 'enum': ['running', 'stopped']},
         'forcebuy_enable': {'type': 'boolean'},
         'disable_dataframe_checks': {'type': 'boolean'},

freqtrade/data/history/history_utils.py

@@ -194,8 +194,8 @@ def _download_pair_history(datadir: Path,
         new_data = exchange.get_historic_ohlcv(pair=pair,
                                                timeframe=timeframe,
                                                since_ms=since_ms if since_ms else
-                                               int(arrow.utcnow().shift(
-                                                   days=-new_pairs_days).float_timestamp) * 1000
+                                               arrow.utcnow().shift(
+                                                   days=-new_pairs_days).int_timestamp * 1000
                                                )
         # TODO: Maybe move parsing to exchange class (?)
         new_dataframe = ohlcv_to_dataframe(new_data, timeframe, pair,
@@ -272,7 +272,7 @@ def _download_trades_history(exchange: Exchange,
             if timerange.stoptype == 'date':
                 until = timerange.stopts * 1000
         else:
-            since = int(arrow.utcnow().shift(days=-new_pairs_days).float_timestamp) * 1000
+            since = arrow.utcnow().shift(days=-new_pairs_days).int_timestamp * 1000
 
         trades = data_handler.trades_load(pair)
 

freqtrade/enums/__init__.py

@@ -1,4 +1,5 @@
 # flake8: noqa: F401
+from freqtrade.enums.backteststate import BacktestState
 from freqtrade.enums.rpcmessagetype import RPCMessageType
 from freqtrade.enums.runmode import NON_UTIL_MODES, OPTIMIZE_MODES, TRADING_MODES, RunMode
 from freqtrade.enums.selltype import SellType

freqtrade/enums/backteststate.py

@@ -0,0 +1,15 @@
+from enum import Enum
+
+
+class BacktestState(Enum):
+    """
+    Bot application states
+    """
+    STARTUP = 1
+    DATALOAD = 2
+    ANALYZE = 3
+    CONVERT = 4
+    BACKTEST = 5
+
+    def __str__(self):
+        return f"{self.name.lower()}"

freqtrade/enums/runmode.py

@@ -14,6 +14,7 @@ class RunMode(Enum):
     UTIL_EXCHANGE = "util_exchange"
     UTIL_NO_EXCHANGE = "util_no_exchange"
     PLOT = "plot"
+    WEBSERVER = "webserver"
     OTHER = "other"
 
 

freqtrade/exchange/exchange.py

@@ -387,7 +387,7 @@ class Exchange:
                 # its contents depend on the exchange.
                 # It can also be a string or similar ... so we need to verify that first.
             elif (isinstance(self.markets[pair].get('info', None), dict)
-                  and self.markets[pair].get('info', {}).get('IsRestricted', False)):
+                  and self.markets[pair].get('info', {}).get('prohibitedIn', False)):
                 # Warn users about restricted pairs in whitelist.
                 # We cannot determine reliably if Users are affected.
                 logger.warning(f"Pair {pair} is restricted for some users on this exchange."
@@ -551,7 +551,7 @@ class Exchange:
         amount_reserve_percent = 1.0 + self._config.get('amount_reserve_percent',
                                                         DEFAULT_AMOUNT_RESERVE_PERCENT)
         amount_reserve_percent = (
-          amount_reserve_percent / (1 - abs(stoploss)) if abs(stoploss) != 1 else 1.5
+            amount_reserve_percent / (1 - abs(stoploss)) if abs(stoploss) != 1 else 1.5
         )
         # it should not be more than 50%
         amount_reserve_percent = max(min(amount_reserve_percent, 1.5), 1)
@@ -578,7 +578,7 @@ class Exchange:
             'side': side,
             'remaining': _amount,
             'datetime': arrow.utcnow().isoformat(),
-            'timestamp': int(arrow.utcnow().int_timestamp * 1000),
+            'timestamp': arrow.utcnow().int_timestamp * 1000,
             'status': "closed" if ordertype == "market" else "open",
             'fee': None,
             'info': {}
@@ -999,99 +999,64 @@ class Exchange:
         except ccxt.BaseError as e:
             raise OperationalException(e) from e
 
-    def _order_book_gen(self, pair: str, side: str, order_book_max: int = 1,
-                        order_book_min: int = 1):
+    def get_rate(self, pair: str, refresh: bool, side: str) -> float:
         """
-        Helper generator to query orderbook in loop (used for early sell-order placing)
-        """
-        order_book = self.fetch_l2_order_book(pair, order_book_max)
-        for i in range(order_book_min, order_book_max + 1):
-            yield order_book[side][i - 1][0]
-
-    def get_buy_rate(self, pair: str, refresh: bool) -> float:
-        """
-        Calculates bid target between current ask price and last price
+        Calculates bid/ask target
+        bid rate - between current ask price and last price
+        ask rate - either using ticker bid or first bid based on orderbook
+        or remain static in any other case since it's not updating.
         :param pair: Pair to get rate for
         :param refresh: allow cached data
+        :param side: "buy" or "sell"
         :return: float: Price
         :raises PricingError if orderbook price could not be determined.
         """
+        cache_rate: TTLCache = self._buy_rate_cache if side == "buy" else self._sell_rate_cache
+        [strat_name, name] = ['bid_strategy', 'Buy'] if side == "buy" else ['ask_strategy', 'Sell']
+
         if not refresh:
-            rate = self._buy_rate_cache.get(pair)
+            rate = cache_rate.get(pair)
             # Check if cache has been invalidated
             if rate:
-                logger.debug(f"Using cached buy rate for {pair}.")
+                logger.debug(f"Using cached {side} rate for {pair}.")
                 return rate
 
-        bid_strategy = self._config.get('bid_strategy', {})
-        if 'use_order_book' in bid_strategy and bid_strategy.get('use_order_book', False):
+        conf_strategy = self._config.get(strat_name, {})
 
-            order_book_top = bid_strategy.get('order_book_top', 1)
+        if conf_strategy.get('use_order_book', False) and ('use_order_book' in conf_strategy):
+
+            order_book_top = conf_strategy.get('order_book_top', 1)
             order_book = self.fetch_l2_order_book(pair, order_book_top)
             logger.debug('order_book %s', order_book)
             # top 1 = index 0
             try:
-                rate_from_l2 = order_book[f"{bid_strategy['price_side']}s"][order_book_top - 1][0]
+                rate = order_book[f"{conf_strategy['price_side']}s"][order_book_top - 1][0]
             except (IndexError, KeyError) as e:
                 logger.warning(
-                    "Buy Price from orderbook could not be determined."
-                    f"Orderbook: {order_book}"
-                 )
+                    f"{name} Price at location {order_book_top} from orderbook could not be "
+                    f"determined. Orderbook: {order_book}"
+                )
                 raise PricingError from e
-            logger.info(f"Buy price from orderbook {bid_strategy['price_side'].capitalize()} side "
-                        f"- top {order_book_top} order book buy rate {rate_from_l2:.8f}")
-            used_rate = rate_from_l2
+            price_side = {conf_strategy['price_side'].capitalize()}
+            logger.debug(f"{name} price from orderbook {price_side}"
+                         f"side - top {order_book_top} order book {side} rate {rate:.8f}")
         else:
-            logger.info(f"Using Last {bid_strategy['price_side'].capitalize()} / Last Price")
+            logger.debug(f"Using Last {conf_strategy['price_side'].capitalize()} / Last Price")
             ticker = self.fetch_ticker(pair)
-            ticker_rate = ticker[bid_strategy['price_side']]
-            if ticker['last'] and ticker_rate > ticker['last']:
-                balance = bid_strategy['ask_last_balance']
-                ticker_rate = ticker_rate + balance * (ticker['last'] - ticker_rate)
-            used_rate = ticker_rate
-
-        self._buy_rate_cache[pair] = used_rate
-
-        return used_rate
-
-    def get_sell_rate(self, pair: str, refresh: bool) -> float:
-        """
-        Get sell rate - either using ticker bid or first bid based on orderbook
-        or remain static in any other case since it's not updating.
-        :param pair: Pair to get rate for
-        :param refresh: allow cached data
-        :return: Bid rate
-        :raises PricingError if price could not be determined.
-        """
-        if not refresh:
-            rate = self._sell_rate_cache.get(pair)
-            # Check if cache has been invalidated
-            if rate:
-                logger.debug(f"Using cached sell rate for {pair}.")
-                return rate
-
-        ask_strategy = self._config.get('ask_strategy', {})
-        if ask_strategy.get('use_order_book', False):
-            # This code is only used for notifications, selling uses the generator directly
-            logger.info(
-                f"Getting price from order book {ask_strategy['price_side'].capitalize()} side."
-            )
-            try:
-                rate = next(self._order_book_gen(pair, f"{ask_strategy['price_side']}s"))
-            except (IndexError, KeyError) as e:
-                logger.warning("Sell Price at location from orderbook could not be determined.")
-                raise PricingError from e
-        else:
-            ticker = self.fetch_ticker(pair)
-            ticker_rate = ticker[ask_strategy['price_side']]
-            if ticker['last'] and ticker_rate < ticker['last']:
-                balance = ask_strategy.get('bid_last_balance', 0.0)
-                ticker_rate = ticker_rate - balance * (ticker_rate - ticker['last'])
+            ticker_rate = ticker[conf_strategy['price_side']]
+            if ticker['last']:
+                if side == 'buy' and ticker_rate > ticker['last']:
+                    balance = conf_strategy['ask_last_balance']
+                    ticker_rate = ticker_rate + balance * (ticker['last'] - ticker_rate)
+                elif side == 'sell' and ticker_rate < ticker['last']:
+                    balance = conf_strategy.get('bid_last_balance', 0.0)
+                    ticker_rate = ticker_rate - balance * (ticker_rate - ticker['last'])
             rate = ticker_rate
 
         if rate is None:
-            raise PricingError(f"Sell-Rate for {pair} was empty.")
-        self._sell_rate_cache[pair] = rate
+            raise PricingError(f"{name}-Rate for {pair} was empty.")
+        cache_rate[pair] = rate
+
         return rate
 
     # Fee handling
@@ -1323,8 +1288,8 @@ class Exchange:
                 self._pairs_last_refresh_time[(pair, timeframe)] = ticks[-1][0] // 1000
             # keeping parsed dataframe in cache
             ohlcv_df = ohlcv_to_dataframe(
-                    ticks, timeframe, pair=pair, fill_missing=True,
-                    drop_incomplete=self._ohlcv_partial_candle)
+                ticks, timeframe, pair=pair, fill_missing=True,
+                drop_incomplete=self._ohlcv_partial_candle)
             results_df[(pair, timeframe)] = ohlcv_df
             if cache:
                 self._klines[(pair, timeframe)] = ohlcv_df

freqtrade/freqtradebot.py

@@ -424,16 +424,10 @@ class FreqtradeBot(LoggingMixin):
 
         if buy and not sell:
             stake_amount = self.wallets.get_trade_stake_amount(pair, self.edge)
-            if not stake_amount:
-                logger.debug(f"Stake amount is 0, ignoring possible trade for {pair}.")
-                return False
-
-            logger.info(f"Buy signal found: about create a new trade for {pair} with stake_amount: "
-                        f"{stake_amount} ...")
 
             bid_check_dom = self.config.get('bid_strategy', {}).get('check_depth_of_market', {})
             if ((bid_check_dom.get('enabled', False)) and
-                    (bid_check_dom.get('bids_to_ask_delta', 0) > 0)):
+               (bid_check_dom.get('bids_to_ask_delta', 0) > 0)):
                 if self._check_depth_of_market_buy(pair, bid_check_dom):
                     return self.execute_buy(pair, stake_amount)
                 else:
@@ -481,20 +475,29 @@ class FreqtradeBot(LoggingMixin):
             buy_limit_requested = price
         else:
             # Calculate price
-            buy_limit_requested = self.exchange.get_buy_rate(pair, True)
+            buy_limit_requested = self.exchange.get_rate(pair, refresh=True, side="buy")
 
         if not buy_limit_requested:
             raise PricingError('Could not determine buy price.')
 
         min_stake_amount = self.exchange.get_min_pair_stake_amount(pair, buy_limit_requested,
                                                                    self.strategy.stoploss)
-        if min_stake_amount is not None and min_stake_amount > stake_amount:
-            logger.warning(
-                f"Can't open a new trade for {pair}: stake amount "
-                f"is too small ({stake_amount} < {min_stake_amount})"
-            )
+
+        if not self.edge:
+            max_stake_amount = self.wallets.get_available_stake_amount()
+            stake_amount = strategy_safe_wrapper(self.strategy.custom_stake_amount,
+                                                 default_retval=stake_amount)(
+                pair=pair, current_time=datetime.now(timezone.utc),
+                current_rate=buy_limit_requested, proposed_stake=stake_amount,
+                min_stake=min_stake_amount, max_stake=max_stake_amount)
+        stake_amount = self.wallets._validate_stake_amount(pair, stake_amount, min_stake_amount)
+
+        if not stake_amount:
             return False
 
+        logger.info(f"Buy signal found: about create a new trade for {pair} with stake_amount: "
+                    f"{stake_amount} ...")
+
         amount = stake_amount / buy_limit_requested
         order_type = self.strategy.order_types['buy']
         if forcebuy:
@@ -606,7 +609,7 @@ class FreqtradeBot(LoggingMixin):
         """
         Sends rpc notification when a buy cancel occurred.
         """
-        current_rate = self.exchange.get_buy_rate(trade.pair, False)
+        current_rate = self.exchange.get_rate(trade.pair, refresh=False, side="buy")
 
         msg = {
             'trade_id': trade.id,
@@ -684,46 +687,17 @@ class FreqtradeBot(LoggingMixin):
 
         (buy, sell) = (False, False)
 
-        config_ask_strategy = self.config.get('ask_strategy', {})
-
-        if (config_ask_strategy.get('use_sell_signal', True) or
-                config_ask_strategy.get('ignore_roi_if_buy_signal', False)):
+        if (self.config.get('use_sell_signal', True) or
+                self.config.get('ignore_roi_if_buy_signal', False)):
             analyzed_df, _ = self.dataprovider.get_analyzed_dataframe(trade.pair,
                                                                       self.strategy.timeframe)
 
             (buy, sell) = self.strategy.get_signal(trade.pair, self.strategy.timeframe, analyzed_df)
 
-        if config_ask_strategy.get('use_order_book', False):
-            order_book_min = config_ask_strategy.get('order_book_min', 1)
-            order_book_max = config_ask_strategy.get('order_book_max', 1)
-            logger.debug(f'Using order book between {order_book_min} and {order_book_max} '
-                         f'for selling {trade.pair}...')
-
-            order_book = self.exchange._order_book_gen(
-                trade.pair, f"{config_ask_strategy['price_side']}s",
-                order_book_min=order_book_min, order_book_max=order_book_max)
-            for i in range(order_book_min, order_book_max + 1):
-                try:
-                    sell_rate = next(order_book)
-                except (IndexError, KeyError) as e:
-                    logger.warning(
-                        f"Sell Price at location {i} from orderbook could not be determined."
-                    )
-                    raise PricingError from e
-                logger.debug(f"  order book {config_ask_strategy['price_side']} top {i}: "
-                             f"{sell_rate:0.8f}")
-                # Assign sell-rate to cache - otherwise sell-rate is never updated in the cache,
-                # resulting in outdated RPC messages
-                self.exchange._sell_rate_cache[trade.pair] = sell_rate
-
-                if self._check_and_execute_sell(trade, sell_rate, buy, sell):
-                    return True
-
-        else:
-            logger.debug('checking sell')
-            sell_rate = self.exchange.get_sell_rate(trade.pair, True)
-            if self._check_and_execute_sell(trade, sell_rate, buy, sell):
-                return True
+        logger.debug('checking sell')
+        sell_rate = self.exchange.get_rate(trade.pair, refresh=True, side="sell")
+        if self._check_and_execute_sell(trade, sell_rate, buy, sell):
+            return True
 
         logger.debug('Found no sell signal for %s.', trade)
         return False
@@ -1158,7 +1132,8 @@ class FreqtradeBot(LoggingMixin):
         profit_rate = trade.close_rate if trade.close_rate else trade.close_rate_requested
         profit_trade = trade.calc_profit(rate=profit_rate)
         # Use cached rates here - it was updated seconds ago.
-        current_rate = self.exchange.get_sell_rate(trade.pair, False) if not fill else None
+        current_rate = self.exchange.get_rate(
+            trade.pair, refresh=False, side="sell") if not fill else None
         profit_ratio = trade.calc_profit_ratio(profit_rate)
         gain = "profit" if profit_ratio > 0 else "loss"
 
@@ -1203,7 +1178,7 @@ class FreqtradeBot(LoggingMixin):
 
         profit_rate = trade.close_rate if trade.close_rate else trade.close_rate_requested
         profit_trade = trade.calc_profit(rate=profit_rate)
-        current_rate = self.exchange.get_sell_rate(trade.pair, False)
+        current_rate = self.exchange.get_rate(trade.pair, refresh=False, side="sell")
         profit_ratio = trade.calc_profit_ratio(profit_rate)
         gain = "profit" if profit_ratio > 0 else "loss"
 

freqtrade/misc.py

@@ -8,6 +8,7 @@ from datetime import datetime
 from pathlib import Path
 from typing import Any, Iterator, List
 from typing.io import IO
+from urllib.parse import urlparse
 
 import rapidjson
 
@@ -214,3 +215,16 @@ def chunks(lst: List[Any], n: int) -> Iterator[List[Any]]:
     """
     for chunk in range(0, len(lst), n):
         yield (lst[chunk:chunk + n])
+
+
+def parse_db_uri_for_logging(uri: str):
+    """
+    Helper method to parse the DB URI and return the same DB URI with the password censored
+    if it contains it. Otherwise, return the DB URI unchanged
+    :param uri: DB URI to parse for logging
+    """
+    parsed_db_uri = urlparse(uri)
+    if not parsed_db_uri.netloc:  # No need for censoring as no password was provided
+        return uri
+    pwd = parsed_db_uri.netloc.split(':')[1].split('@')[0]
+    return parsed_db_uri.geturl().replace(f':{pwd}@', ':*****@')

freqtrade/optimize/backtesting.py

@@ -17,10 +17,11 @@ from freqtrade.data import history
 from freqtrade.data.btanalysis import trade_list_to_dataframe
 from freqtrade.data.converter import trim_dataframes
 from freqtrade.data.dataprovider import DataProvider
-from freqtrade.enums import SellType
+from freqtrade.enums import BacktestState, SellType
 from freqtrade.exceptions import DependencyException, OperationalException
 from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
 from freqtrade.mixins import LoggingMixin
+from freqtrade.optimize.bt_progress import BTProgress
 from freqtrade.optimize.optimize_reports import (generate_backtest_stats, show_backtest_results,
                                                  store_backtest_stats)
 from freqtrade.persistence import LocalTrade, PairLocks, Trade
@@ -57,6 +58,7 @@ class Backtesting:
 
         LoggingMixin.show_output = False
         self.config = config
+        self.results: Optional[Dict[str, Any]] = None
 
         # Reset keys for backtesting
         remove_credentials(self.config)
@@ -116,6 +118,10 @@ class Backtesting:
 
         # Get maximum required startup period
         self.required_startup = max([strat.startup_candle_count for strat in self.strategylist])
+        self.exchange.validate_required_startup_candles(self.required_startup, self.timeframe)
+
+        self.progress = BTProgress()
+        self.abort = False
 
     def __del__(self):
         LoggingMixin.show_output = True
@@ -128,6 +134,8 @@ class Backtesting:
         """
         self.strategy: IStrategy = strategy
         strategy.dp = self.dataprovider
+        # Attach Wallets to Strategy baseclass
+        IStrategy.wallets = self.wallets
         # Set stoploss_on_exchange to false for backtesting,
         # since a "perfect" stoploss-sell is assumed anyway
         # And the regular "stoploss" function would not apply to that case
@@ -144,6 +152,8 @@ class Backtesting:
         Loads backtest data and returns the data combined with the timerange
         as tuple.
         """
+        self.progress.init_step(BacktestState.DATALOAD, 1)
+
         timerange = TimeRange.parse_timerange(None if self.config.get(
             'timerange') is None else str(self.config.get('timerange')))
 
@@ -167,6 +177,7 @@ class Backtesting:
         timerange.adjust_start_if_necessary(timeframe_to_seconds(self.timeframe),
                                             self.required_startup, min_date)
 
+        self.progress.set_new_value(1)
         return data, timerange
 
     def prepare_backtest(self, enable_protections):
@@ -181,6 +192,15 @@ class Backtesting:
         self.rejected_trades = 0
         self.dataprovider.clear_cache()
 
+    def check_abort(self):
+        """
+        Check if abort was requested, raise DependencyException if that's the case
+        Only applies to Interactive backtest mode (webserver mode)
+        """
+        if self.abort:
+            self.abort = False
+            raise DependencyException("Stop requested")
+
     def _get_ohlcv_as_lists(self, processed: Dict[str, DataFrame]) -> Dict[str, Tuple]:
         """
         Helper function to convert a processed dataframes into lists for performance reasons.
@@ -191,8 +211,12 @@ class Backtesting:
         # and eventually change the constants for indexes at the top
         headers = ['date', 'buy', 'open', 'close', 'sell', 'low', 'high']
         data: Dict = {}
+        self.progress.init_step(BacktestState.CONVERT, len(processed))
+
         # Create dict with data
         for pair, pair_data in processed.items():
+            self.check_abort()
+            self.progress.increment()
             if not pair_data.empty:
                 pair_data.loc[:, 'buy'] = 0  # cleanup if buy_signal is exist
                 pair_data.loc[:, 'sell'] = 0  # cleanup if sell_signal is exist
@@ -228,16 +252,20 @@ class Backtesting:
             # Special case: trailing triggers within same candle as trade opened. Assume most
             # pessimistic price movement, which is moving just enough to arm stoploss and
             # immediately going down to stop price.
-            if (sell.sell_type == SellType.TRAILING_STOP_LOSS and trade_dur == 0
-                    and self.strategy.trailing_stop_positive):
-                if self.strategy.trailing_only_offset_is_reached:
+            if sell.sell_type == SellType.TRAILING_STOP_LOSS and trade_dur == 0:
+                if (
+                    not self.strategy.use_custom_stoploss and self.strategy.trailing_stop
+                    and self.strategy.trailing_only_offset_is_reached
+                    and self.strategy.trailing_stop_positive_offset is not None
+                    and self.strategy.trailing_stop_positive
+                ):
                     # Worst case: price reaches stop_positive_offset and dives down.
                     stop_rate = (sell_row[OPEN_IDX] *
                                  (1 + abs(self.strategy.trailing_stop_positive_offset) -
                                  abs(self.strategy.trailing_stop_positive)))
                 else:
                     # Worst case: price ticks tiny bit above open and dives down.
-                    stop_rate = sell_row[OPEN_IDX] * (1 - abs(self.strategy.trailing_stop_positive))
+                    stop_rate = sell_row[OPEN_IDX] * (1 - abs(trade.stop_loss_pct))
                     assert stop_rate < sell_row[HIGH_IDX]
                 return stop_rate
 
@@ -307,7 +335,18 @@ class Backtesting:
             stake_amount = self.wallets.get_trade_stake_amount(pair, None)
         except DependencyException:
             return None
-        min_stake_amount = self.exchange.get_min_pair_stake_amount(pair, row[OPEN_IDX], -0.05)
+
+        min_stake_amount = self.exchange.get_min_pair_stake_amount(pair, row[OPEN_IDX], -0.05) or 0
+        max_stake_amount = self.wallets.get_available_stake_amount()
+
+        stake_amount = strategy_safe_wrapper(self.strategy.custom_stake_amount,
+                                             default_retval=stake_amount)(
+            pair=pair, current_time=row[DATE_IDX].to_pydatetime(), current_rate=row[OPEN_IDX],
+            proposed_stake=stake_amount, min_stake=min_stake_amount, max_stake=max_stake_amount)
+        stake_amount = self.wallets._validate_stake_amount(pair, stake_amount, min_stake_amount)
+
+        if not stake_amount:
+            return None
 
         order_type = self.strategy.order_types['buy']
         time_in_force = self.strategy.order_time_in_force['sell']
@@ -399,10 +438,13 @@ class Backtesting:
         open_trades: Dict[str, List[LocalTrade]] = defaultdict(list)
         open_trade_count = 0
 
+        self.progress.init_step(BacktestState.BACKTEST, int(
+            (end_date - start_date) / timedelta(minutes=self.timeframe_min)))
+
         # Loop timerange and get candle for each pair at that point in time
         while tmp <= end_date:
             open_trade_count_start = open_trade_count
-
+            self.check_abort()
             for i, pair in enumerate(data):
                 row_index = indexes[pair]
                 try:
@@ -458,6 +500,7 @@ class Backtesting:
                             self.protections.global_stop(tmp)
 
             # Move time one configured time_interval ahead.
+            self.progress.increment()
             tmp += timedelta(minutes=self.timeframe_min)
 
         trades += self.handle_left_open(open_trades, data=data)
@@ -473,6 +516,8 @@ class Backtesting:
         }
 
     def backtest_one_strategy(self, strat: IStrategy, data: Dict[str, Any], timerange: TimeRange):
+        self.progress.init_step(BacktestState.ANALYZE, 0)
+
         logger.info("Running backtesting for Strategy %s", strat.get_strategy_name())
         backtest_start_time = datetime.now(timezone.utc)
         self._set_strategy(strat)
@@ -499,6 +544,7 @@ class Backtesting:
                 "No data left after adjusting for startup candles.")
 
         min_date, max_date = history.get_timerange(preprocessed)
+
         logger.info(f'Backtesting with data from {min_date.strftime(DATETIME_PRINT_FORMAT)} '
                     f'up to {max_date.strftime(DATETIME_PRINT_FORMAT)} '
                     f'({(max_date - min_date).days} days).')
@@ -533,11 +579,12 @@ class Backtesting:
         for strat in self.strategylist:
             min_date, max_date = self.backtest_one_strategy(strat, data, timerange)
         if len(self.strategylist) > 0:
-            stats = generate_backtest_stats(data, self.all_results,
-                                            min_date=min_date, max_date=max_date)
+
+            self.results = generate_backtest_stats(data, self.all_results,
+                                                   min_date=min_date, max_date=max_date)
 
             if self.config.get('export', 'none') == 'trades':
-                store_backtest_stats(self.config['exportfilename'], stats)
+                store_backtest_stats(self.config['exportfilename'], self.results)
 
             # Show backtest results
-            show_backtest_results(self.config, stats)
+            show_backtest_results(self.config, self.results)

freqtrade/optimize/bt_progress.py

@@ -0,0 +1,33 @@
+from freqtrade.enums import BacktestState
+
+
+class BTProgress:
+    _action: BacktestState = BacktestState.STARTUP
+    _progress: float = 0
+    _max_steps: float = 0
+
+    def __init__(self):
+        pass
+
+    def init_step(self, action: BacktestState, max_steps: float):
+        self._action = action
+        self._max_steps = max_steps
+        self._proress = 0
+
+    def set_new_value(self, new_value: float):
+        self._progress = new_value
+
+    def increment(self):
+        self._progress += 1
+
+    @property
+    def progress(self):
+        """
+        Get progress as ratio, capped to be between 0 and 1 (to avoid small calculation errors).
+        """
+        return max(min(round(self._progress / self._max_steps, 5)
+                       if self._max_steps > 0 else 0, 1), 0)
+
+    @property
+    def action(self):
+        return str(self._action)

freqtrade/optimize/hyperopt.py

@@ -12,7 +12,6 @@ from math import ceil
 from pathlib import Path
 from typing import Any, Dict, List, Optional
 
-import numpy as np
 import progressbar
 import rapidjson
 from colorama import Fore, Style
@@ -20,16 +19,16 @@ from colorama import init as colorama_init
 from joblib import Parallel, cpu_count, delayed, dump, load, wrap_non_picklable_objects
 from pandas import DataFrame
 
-from freqtrade.constants import DATETIME_PRINT_FORMAT, LAST_BT_RESULT_FN
+from freqtrade.constants import DATETIME_PRINT_FORMAT, FTHYPT_FILEVERSION, LAST_BT_RESULT_FN
 from freqtrade.data.converter import trim_dataframes
 from freqtrade.data.history import get_timerange
-from freqtrade.misc import file_dump_json, plural
+from freqtrade.misc import deep_merge_dicts, file_dump_json, plural
 from freqtrade.optimize.backtesting import Backtesting
 # Import IHyperOpt and IHyperOptLoss to allow unpickling classes from these modules
 from freqtrade.optimize.hyperopt_auto import HyperOptAuto
 from freqtrade.optimize.hyperopt_interface import IHyperOpt  # noqa: F401
 from freqtrade.optimize.hyperopt_loss_interface import IHyperOptLoss  # noqa: F401
-from freqtrade.optimize.hyperopt_tools import HyperoptTools
+from freqtrade.optimize.hyperopt_tools import HyperoptTools, hyperopt_serializer
 from freqtrade.optimize.optimize_reports import generate_strategy_stats
 from freqtrade.resolvers.hyperopt_resolver import HyperOptLossResolver, HyperOptResolver
 
@@ -78,8 +77,11 @@ class Hyperopt:
 
         if not self.config.get('hyperopt'):
             self.custom_hyperopt = HyperOptAuto(self.config)
+            self.auto_hyperopt = True
         else:
             self.custom_hyperopt = HyperOptResolver.load_hyperopt(self.config)
+            self.auto_hyperopt = False
+
         self.backtesting._set_strategy(self.backtesting.strategylist[0])
         self.custom_hyperopt.strategy = self.backtesting.strategy
 
@@ -163,13 +165,9 @@ class Hyperopt:
         While not a valid json object - this allows appending easily.
         :param epoch: result dictionary for this epoch.
         """
-        def default_parser(x):
-            if isinstance(x, np.integer):
-                return int(x)
-            return str(x)
-
+        epoch[FTHYPT_FILEVERSION] = 2
         with self.results_file.open('a') as f:
-            rapidjson.dump(epoch, f, default=default_parser,
+            rapidjson.dump(epoch, f, default=hyperopt_serializer,
                            number_mode=rapidjson.NM_NATIVE | rapidjson.NM_NAN)
             f.write("\n")
 
@@ -201,6 +199,25 @@ class Hyperopt:
 
         return result
 
+    def _get_no_optimize_details(self) -> Dict[str, Any]:
+        """
+        Get non-optimized parameters
+        """
+        result: Dict[str, Any] = {}
+        strategy = self.backtesting.strategy
+        if not HyperoptTools.has_space(self.config, 'roi'):
+            result['roi'] = {str(k): v for k, v in strategy.minimal_roi.items()}
+        if not HyperoptTools.has_space(self.config, 'stoploss'):
+            result['stoploss'] = {'stoploss': strategy.stoploss}
+        if not HyperoptTools.has_space(self.config, 'trailing'):
+            result['trailing'] = {
+                'trailing_stop': strategy.trailing_stop,
+                'trailing_stop_positive': strategy.trailing_stop_positive,
+                'trailing_stop_positive_offset': strategy.trailing_stop_positive_offset,
+                'trailing_only_offset_is_reached': strategy.trailing_only_offset_is_reached,
+            }
+        return result
+
     def print_results(self, results) -> None:
         """
         Log results if it is better than any previous evaluation
@@ -310,7 +327,8 @@ class Hyperopt:
         results_explanation = HyperoptTools.format_results_explanation_string(
             strat_stats, self.config['stake_currency'])
 
-        not_optimized = self.backtesting.strategy.get_params_dict()
+        not_optimized = self.backtesting.strategy.get_no_optimize_params()
+        not_optimized = deep_merge_dicts(not_optimized, self._get_no_optimize_details())
 
         trade_count = strat_stats['total_trades']
         total_profit = strat_stats['profit_total']
@@ -324,7 +342,8 @@ class Hyperopt:
             loss = self.calculate_loss(results=backtesting_results['results'],
                                        trade_count=trade_count,
                                        min_date=min_date, max_date=max_date,
-                                       config=self.config, processed=processed)
+                                       config=self.config, processed=processed,
+                                       backtest_stats=strat_stats)
         return {
             'loss': loss,
             'params_dict': params_dict,
@@ -469,6 +488,12 @@ class Hyperopt:
                     f"saved to '{self.results_file}'.")
 
         if self.current_best_epoch:
+            if self.auto_hyperopt:
+                HyperoptTools.try_export_params(
+                    self.config,
+                    self.backtesting.strategy.get_strategy_name(),
+                    self.current_best_epoch)
+
             HyperoptTools.show_epoch_details(self.current_best_epoch, self.total_epochs,
                                              self.print_json)
         else:

freqtrade/optimize/hyperopt_loss_interface.py

@@ -5,7 +5,7 @@ This module defines the interface for the loss-function for hyperopt
 
 from abc import ABC, abstractmethod
 from datetime import datetime
-from typing import Dict
+from typing import Any, Dict
 
 from pandas import DataFrame
 
@@ -22,6 +22,7 @@ class IHyperOptLoss(ABC):
     def hyperopt_loss_function(results: DataFrame, trade_count: int,
                                min_date: datetime, max_date: datetime,
                                config: Dict, processed: Dict[str, DataFrame],
+                               backtest_stats: Dict[str, Any],
                                *args, **kwargs) -> float:
         """
         Objective function, returns smaller number for better results

freqtrade/optimize/hyperopt_tools.py

@@ -1,23 +1,82 @@
 
 import io
 import logging
+from copy import deepcopy
+from datetime import datetime, timezone
 from pathlib import Path
-from typing import Any, Dict, List
+from typing import Any, Dict, List, Optional
 
+import numpy as np
 import rapidjson
 import tabulate
 from colorama import Fore, Style
 from pandas import isna, json_normalize
 
+from freqtrade.constants import FTHYPT_FILEVERSION, USERPATH_STRATEGIES
 from freqtrade.exceptions import OperationalException
-from freqtrade.misc import round_coin_value, round_dict
+from freqtrade.misc import deep_merge_dicts, round_coin_value, round_dict, safe_value_fallback2
 
 
 logger = logging.getLogger(__name__)
 
+NON_OPT_PARAM_APPENDIX = "  # value loaded from strategy"
+
+
+def hyperopt_serializer(x):
+    if isinstance(x, np.integer):
+        return int(x)
+    if isinstance(x, np.bool_):
+        return bool(x)
+
+    return str(x)
+
 
 class HyperoptTools():
 
+    @staticmethod
+    def get_strategy_filename(config: Dict, strategy_name: str) -> Optional[Path]:
+        """
+        Get Strategy-location (filename) from strategy_name
+        """
+        from freqtrade.resolvers.strategy_resolver import StrategyResolver
+        directory = Path(config.get('strategy_path', config['user_data_dir'] / USERPATH_STRATEGIES))
+        strategy_objs = StrategyResolver.search_all_objects(directory, False)
+        strategies = [s for s in strategy_objs if s['name'] == strategy_name]
+        if strategies:
+            strategy = strategies[0]
+
+            return Path(strategy['location'])
+        return None
+
+    @staticmethod
+    def export_params(params, strategy_name: str, filename: Path):
+        """
+        Generate files
+        """
+        final_params = deepcopy(params['params_not_optimized'])
+        final_params = deep_merge_dicts(params['params_details'], final_params)
+        final_params = {
+            'strategy_name': strategy_name,
+            'params': final_params,
+            'ft_stratparam_v': 1,
+            'export_time': datetime.now(timezone.utc),
+        }
+        logger.info(f"Dumping parameters to {filename}")
+        rapidjson.dump(final_params, filename.open('w'), indent=2,
+                       default=hyperopt_serializer,
+                       number_mode=rapidjson.NM_NATIVE | rapidjson.NM_NAN
+                       )
+
+    @staticmethod
+    def try_export_params(config: Dict[str, Any], strategy_name: str, params: Dict):
+        if params.get(FTHYPT_FILEVERSION, 1) >= 2 and not config.get('disableparamexport', False):
+            # Export parameters ...
+            fn = HyperoptTools.get_strategy_filename(config, strategy_name)
+            if fn:
+                HyperoptTools.export_params(params, strategy_name, fn.with_suffix('.json'))
+            else:
+                logger.warning("Strategy not found, not exporting parameter file.")
+
     @staticmethod
     def has_space(config: Dict[str, Any], space: str) -> bool:
         """
@@ -99,9 +158,9 @@ class HyperoptTools():
                                                non_optimized)
             HyperoptTools._params_pretty_print(params, 'sell', "Sell hyperspace params:",
                                                non_optimized)
-            HyperoptTools._params_pretty_print(params, 'roi', "ROI table:")
-            HyperoptTools._params_pretty_print(params, 'stoploss', "Stoploss:")
-            HyperoptTools._params_pretty_print(params, 'trailing', "Trailing stop:")
+            HyperoptTools._params_pretty_print(params, 'roi', "ROI table:", non_optimized)
+            HyperoptTools._params_pretty_print(params, 'stoploss', "Stoploss:", non_optimized)
+            HyperoptTools._params_pretty_print(params, 'trailing', "Trailing stop:", non_optimized)
 
     @staticmethod
     def _params_update_for_json(result_dict, params, non_optimized, space: str) -> None:
@@ -127,23 +186,34 @@ class HyperoptTools():
     def _params_pretty_print(params, space: str, header: str, non_optimized={}) -> None:
         if space in params or space in non_optimized:
             space_params = HyperoptTools._space_params(params, space, 5)
+            no_params = HyperoptTools._space_params(non_optimized, space, 5)
+            appendix = ''
+            if not space_params and not no_params:
+                # No parameters - don't print
+                return
+            if not space_params:
+                # Not optimized parameters - append string
+                appendix = NON_OPT_PARAM_APPENDIX
+
             result = f"\n# {header}\n"
-            if space == 'stoploss':
-                result += f"stoploss = {space_params.get('stoploss')}"
-            elif space == 'roi':
+            if space == "stoploss":
+                stoploss = safe_value_fallback2(space_params, no_params, space, space)
+                result += (f"stoploss = {stoploss}{appendix}")
+
+            elif space == "roi":
+                result = result[:-1] + f'{appendix}\n'
                 minimal_roi_result = rapidjson.dumps({
-                        str(k): v for k, v in space_params.items()
+                        str(k): v for k, v in (space_params or no_params).items()
                 }, default=str, indent=4, number_mode=rapidjson.NM_NATIVE)
                 result += f"minimal_roi = {minimal_roi_result}"
-            elif space == 'trailing':
-
-                for k, v in space_params.items():
-                    result += f'{k} = {v}\n'
+            elif space == "trailing":
+                for k, v in (space_params or no_params).items():
+                    result += f"{k} = {v}{appendix}\n"
 
             else:
-                no_params = HyperoptTools._space_params(non_optimized, space, 5)
+                # Buy / sell parameters
 
-                result += f"{space}_params = {HyperoptTools._pprint(space_params, no_params)}"
+                result += f"{space}_params = {HyperoptTools._pprint_dict(space_params, no_params)}"
 
             result = result.replace("\n", "\n    ")
             print(result)
@@ -157,7 +227,7 @@ class HyperoptTools():
         return {}
 
     @staticmethod
-    def _pprint(params, non_optimized, indent: int = 4):
+    def _pprint_dict(params, non_optimized, indent: int = 4):
         """
         Pretty-print hyperopt results (based on 2 dicts - with add. comment)
         """
@@ -169,7 +239,7 @@ class HyperoptTools():
             result += " " * indent + f'"{k}": '
             result += f'"{param}",' if isinstance(param, str) else f'{param},'
             if k in non_optimized:
-                result += "  # value loaded from strategy"
+                result += NON_OPT_PARAM_APPENDIX
             result += "\n"
         result += '}'
         return result

freqtrade/optimize/optimize_reports.py

@@ -229,8 +229,6 @@ def generate_trading_stats(results: DataFrame) -> Dict[str, Any]:
     winning_trades = results.loc[results['profit_ratio'] > 0]
     draw_trades = results.loc[results['profit_ratio'] == 0]
     losing_trades = results.loc[results['profit_ratio'] < 0]
-    zero_duration_trades = len(results.loc[(results['trade_duration'] == 0) &
-                                           (results['sell_reason'] == 'trailing_stop_loss')])
 
     holding_avg = (timedelta(minutes=round(results['trade_duration'].mean()))
                    if not results.empty else timedelta())
@@ -249,7 +247,6 @@ def generate_trading_stats(results: DataFrame) -> Dict[str, Any]:
         'winner_holding_avg_s': winner_holding_avg.total_seconds(),
         'loser_holding_avg': loser_holding_avg,
         'loser_holding_avg_s': loser_holding_avg.total_seconds(),
-        'zero_duration_trades': zero_duration_trades,
     }
 
 
@@ -264,6 +261,7 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]:
             'winning_days': 0,
             'draw_days': 0,
             'losing_days': 0,
+            'daily_profit_list': [],
         }
     daily_profit_rel = results.resample('1d', on='close_date')['profit_ratio'].sum()
     daily_profit = results.resample('1d', on='close_date')['profit_abs'].sum().round(10)
@@ -274,6 +272,7 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]:
     winning_days = sum(daily_profit > 0)
     draw_days = sum(daily_profit == 0)
     losing_days = sum(daily_profit < 0)
+    daily_profit_list = [(str(idx.date()), val) for idx, val in daily_profit.iteritems()]
 
     return {
         'backtest_best_day': best_rel,
@@ -283,6 +282,7 @@ def generate_daily_stats(results: DataFrame) -> Dict[str, Any]:
         'winning_days': winning_days,
         'draw_days': draw_days,
         'losing_days': losing_days,
+        'daily_profit': daily_profit_list,
     }
 
 
@@ -325,8 +325,9 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
                     key=lambda x: x['profit_sum']) if len(pair_results) > 1 else None
     worst_pair = min([pair for pair in pair_results if pair['key'] != 'TOTAL'],
                      key=lambda x: x['profit_sum']) if len(pair_results) > 1 else None
-    results['open_timestamp'] = results['open_date'].astype(int64) // 1e6
-    results['close_timestamp'] = results['close_date'].astype(int64) // 1e6
+    if not results.empty:
+        results['open_timestamp'] = results['open_date'].view(int64) // 1e6
+        results['close_timestamp'] = results['close_date'].view(int64) // 1e6
 
     backtest_days = (max_date - min_date).days
     strat_stats = {
@@ -378,10 +379,10 @@ def generate_strategy_stats(btdata: Dict[str, DataFrame],
         'trailing_only_offset_is_reached': config.get('trailing_only_offset_is_reached', False),
         'use_custom_stoploss': config.get('use_custom_stoploss', False),
         'minimal_roi': config['minimal_roi'],
-        'use_sell_signal': config['ask_strategy']['use_sell_signal'],
-        'sell_profit_only': config['ask_strategy']['sell_profit_only'],
-        'sell_profit_offset': config['ask_strategy']['sell_profit_offset'],
-        'ignore_roi_if_buy_signal': config['ask_strategy']['ignore_roi_if_buy_signal'],
+        'use_sell_signal': config['use_sell_signal'],
+        'sell_profit_only': config['sell_profit_only'],
+        'sell_profit_offset': config['sell_profit_offset'],
+        'ignore_roi_if_buy_signal': config['ignore_roi_if_buy_signal'],
         **daily_stats,
         **trade_stats
     }
@@ -542,14 +543,6 @@ def text_table_add_metrics(strat_results: Dict) -> str:
         # Newly added fields should be ignored if they are missing in strat_results. hyperopt-show
         # command stores these results and newer version of freqtrade must be able to handle old
         # results with missing new fields.
-        zero_duration_trades = '--'
-
-        if 'zero_duration_trades' in strat_results:
-            zero_duration_trades_per = \
-                100.0 / strat_results['total_trades'] * strat_results['zero_duration_trades']
-            zero_duration_trades = f'{zero_duration_trades_per:.2f}% ' \
-                                   f'({strat_results["zero_duration_trades"]})'
-
         metrics = [
             ('Backtesting from', strat_results['backtest_start']),
             ('Backtesting to', strat_results['backtest_end']),
@@ -585,7 +578,6 @@ def text_table_add_metrics(strat_results: Dict) -> str:
                 f"{strat_results['draw_days']} / {strat_results['losing_days']}"),
             ('Avg. Duration Winners', f"{strat_results['winner_holding_avg']}"),
             ('Avg. Duration Loser', f"{strat_results['loser_holding_avg']}"),
-            ('Zero Duration Trades', zero_duration_trades),
             ('Rejected Buy signals', strat_results.get('rejected_signals', 'N/A')),
             ('', ''),  # Empty line to improve readability
 
@@ -663,6 +655,8 @@ def show_backtest_results(config: Dict, backtest_stats: Dict):
         # Print Strategy summary table
 
         table = text_table_strategy(backtest_stats['strategy_comparison'], stake_currency)
+        print(f"{results['backtest_start']} -> {results['backtest_end']} |"
+              f" Max open trades : {results['max_open_trades']}")
         print(' STRATEGY SUMMARY '.center(len(table.splitlines()[0]), '='))
         print(table)
         print('=' * len(table.splitlines()[0]))

freqtrade/persistence/models.py

@@ -801,6 +801,19 @@ class Trade(_DECL_BASE, LocalTrade):
                                  Trade.is_open.is_(False),
                                  ]).all()
 
+    @staticmethod
+    def get_total_closed_profit() -> float:
+        """
+        Retrieves total realized profit
+        """
+        if Trade.use_db:
+            total_profit = Trade.query.with_entities(
+                func.sum(Trade.close_profit_abs)).filter(Trade.is_open.is_(False)).scalar()
+        else:
+            total_profit = sum(
+                t.close_profit_abs for t in LocalTrade.get_trades_proxy(is_open=False))
+        return total_profit or 0
+
     @staticmethod
     def total_open_trades_stakes() -> float:
         """
@@ -841,7 +854,7 @@ class Trade(_DECL_BASE, LocalTrade):
         ]
 
     @staticmethod
-    def get_best_pair():
+    def get_best_pair(start_date: datetime = datetime.fromtimestamp(0)):
         """
         Get best pair with closed trade.
         NOTE: Not supported in Backtesting.
@@ -849,7 +862,7 @@ class Trade(_DECL_BASE, LocalTrade):
         """
         best_pair = Trade.query.with_entities(
             Trade.pair, func.sum(Trade.close_profit).label('profit_sum')
-        ).filter(Trade.is_open.is_(False)) \
+        ).filter(Trade.is_open.is_(False) & (Trade.close_date >= start_date)) \
             .group_by(Trade.pair) \
             .order_by(desc('profit_sum')).first()
         return best_pair

freqtrade/plot/plotting.py

@@ -373,6 +373,7 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
     for i, name in enumerate(plot_config['subplots']):
         fig['layout'][f'yaxis{3 + i}'].update(title=name)
     fig['layout']['xaxis']['rangeslider'].update(visible=False)
+    fig.update_layout(modebar_add=["v1hovermode", "toggleSpikeLines"])
 
     # Common information
     candles = go.Candlestick(
@@ -452,6 +453,7 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
                              data=data)
         # fill area between indicators ( 'fill_to': 'other_indicator')
         fig = add_areas(fig, row, data, sub_config)
+
     return fig
 
 
@@ -484,6 +486,7 @@ def generate_profit_graph(pairs: str, data: Dict[str, pd.DataFrame],
     fig['layout']['yaxis2'].update(title=f'Profit {stake_currency}')
     fig['layout']['yaxis3'].update(title=f'Profit {stake_currency}')
     fig['layout']['xaxis']['rangeslider'].update(visible=False)
+    fig.update_layout(modebar_add=["v1hovermode", "toggleSpikeLines"])
 
     fig.add_trace(avgclose, 1, 1)
     fig = add_profit(fig, 2, df_comb, 'cum_profit', 'Profit')
@@ -497,7 +500,6 @@ def generate_profit_graph(pairs: str, data: Dict[str, pd.DataFrame],
             fig = add_profit(fig, 3, df_comb, profit_col, f"Profit {pair}")
         except ValueError:
             pass
-
     return fig
 
 

freqtrade/plugins/pairlist/AgeFilter.py

@@ -27,6 +27,7 @@ class AgeFilter(IPairList):
         super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
 
         self._min_days_listed = pairlistconfig.get('min_days_listed', 10)
+        self._max_days_listed = pairlistconfig.get('max_days_listed', None)
 
         if self._min_days_listed < 1:
             raise OperationalException("AgeFilter requires min_days_listed to be >= 1")
@@ -34,6 +35,12 @@ class AgeFilter(IPairList):
             raise OperationalException("AgeFilter requires min_days_listed to not exceed "
                                        "exchange max request size "
                                        f"({exchange.ohlcv_candle_limit('1d')})")
+        if self._max_days_listed and self._max_days_listed <= self._min_days_listed:
+            raise OperationalException("AgeFilter max_days_listed <= min_days_listed not permitted")
+        if self._max_days_listed and self._max_days_listed > exchange.ohlcv_candle_limit('1d'):
+            raise OperationalException("AgeFilter requires max_days_listed to not exceed "
+                                       "exchange max request size "
+                                       f"({exchange.ohlcv_candle_limit('1d')})")
 
     @property
     def needstickers(self) -> bool:
@@ -48,8 +55,13 @@ class AgeFilter(IPairList):
         """
         Short whitelist method description - used for startup-messages
         """
-        return (f"{self.name} - Filtering pairs with age less than "
-                f"{self._min_days_listed} {plural(self._min_days_listed, 'day')}.")
+        return (
+            f"{self.name} - Filtering pairs with age less than "
+            f"{self._min_days_listed} {plural(self._min_days_listed, 'day')}"
+        ) + ((
+            " or more than "
+            f"{self._max_days_listed} {plural(self._max_days_listed, 'day')}"
+        ) if self._max_days_listed else '')
 
     def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
         """
@@ -61,9 +73,12 @@ class AgeFilter(IPairList):
         if not needed_pairs:
             return pairlist
 
+        since_days = -(
+            self._max_days_listed if self._max_days_listed else self._min_days_listed
+        ) - 1
         since_ms = int(arrow.utcnow()
                        .floor('day')
-                       .shift(days=-self._min_days_listed - 1)
+                       .shift(days=since_days)
                        .float_timestamp) * 1000
         candles = self._exchange.refresh_latest_ohlcv(needed_pairs, since_ms=since_ms, cache=False)
         if self._enabled:
@@ -86,14 +101,22 @@ class AgeFilter(IPairList):
             return True
 
         if daily_candles is not None:
-            if len(daily_candles) >= self._min_days_listed:
+            if (
+                len(daily_candles) >= self._min_days_listed
+                and (not self._max_days_listed or len(daily_candles) <= self._max_days_listed)
+            ):
                 # We have fetched at least the minimum required number of daily candles
                 # Add to cache, store the time we last checked this symbol
-                self._symbolsChecked[pair] = int(arrow.utcnow().float_timestamp) * 1000
+                self._symbolsChecked[pair] = arrow.utcnow().int_timestamp * 1000
                 return True
             else:
-                self.log_once(f"Removed {pair} from whitelist, because age "
-                              f"{len(daily_candles)} is less than {self._min_days_listed} "
-                              f"{plural(self._min_days_listed, 'day')}", logger.info)
+                self.log_once((
+                    f"Removed {pair} from whitelist, because age "
+                    f"{len(daily_candles)} is less than {self._min_days_listed} "
+                    f"{plural(self._min_days_listed, 'day')}"
+                ) + ((
+                    " or more than "
+                    f"{self._max_days_listed} {plural(self._max_days_listed, 'day')}"
+                ) if self._max_days_listed else ''), logger.info)
                 return False
         return False

freqtrade/plugins/pairlist/OffsetFilter.py

@@ -0,0 +1,54 @@
+"""
+Offset pair list filter
+"""
+import logging
+from typing import Any, Dict, List
+
+from freqtrade.exceptions import OperationalException
+from freqtrade.plugins.pairlist.IPairList import IPairList
+
+
+logger = logging.getLogger(__name__)
+
+
+class OffsetFilter(IPairList):
+
+    def __init__(self, exchange, pairlistmanager,
+                 config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+                 pairlist_pos: int) -> None:
+        super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
+
+        self._offset = pairlistconfig.get('offset', 0)
+
+        if self._offset < 0:
+            raise OperationalException("OffsetFilter requires offset to be >= 0")
+
+    @property
+    def needstickers(self) -> bool:
+        """
+        Boolean property defining if tickers are necessary.
+        If no Pairlist requires tickers, an empty Dict is passed
+        as tickers argument to filter_pairlist
+        """
+        return False
+
+    def short_desc(self) -> str:
+        """
+        Short whitelist method description - used for startup-messages
+        """
+        return f"{self.name} - Offseting pairs by {self._offset}."
+
+    def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
+        """
+        Filters and sorts pairlist and returns the whitelist again.
+        Called on each bot iteration - please use internal caching if necessary
+        :param pairlist: pairlist to filter or sort
+        :param tickers: Tickers (from exchange.get_tickers()). May be cached.
+        :return: new whitelist
+        """
+        if self._offset > len(pairlist):
+            self.log_once(f"Offset of {self._offset} is larger than " +
+                          f"pair count of {len(pairlist)}", logger.warning)
+        pairs = pairlist[self._offset:]
+        self.log_once(f"Searching {len(pairs)} pairs: {pairs}", logger.info)
+        return pairs

freqtrade/plugins/pairlist/VolatilityFilter.py

@@ -69,10 +69,10 @@ class VolatilityFilter(IPairList):
         """
         needed_pairs = [(p, '1d') for p in pairlist if p not in self._pair_cache]
 
-        since_ms = int(arrow.utcnow()
-                       .floor('day')
-                       .shift(days=-self._days - 1)
-                       .float_timestamp) * 1000
+        since_ms = (arrow.utcnow()
+                         .floor('day')
+                         .shift(days=-self._days - 1)
+                         .int_timestamp) * 1000
         # Get all candles
         candles = {}
         if needed_pairs:

freqtrade/plugins/pairlist/VolumePairList.py

@@ -6,9 +6,12 @@ Provides dynamic pair list based on trade volumes
 import logging
 from typing import Any, Dict, List
 
+import arrow
 from cachetools.ttl import TTLCache
 
 from freqtrade.exceptions import OperationalException
+from freqtrade.exchange import timeframe_to_minutes
+from freqtrade.misc import format_ms_time
 from freqtrade.plugins.pairlist.IPairList import IPairList
 
 
@@ -36,6 +39,35 @@ class VolumePairList(IPairList):
         self._min_value = self._pairlistconfig.get('min_value', 0)
         self._refresh_period = self._pairlistconfig.get('refresh_period', 1800)
         self._pair_cache: TTLCache = TTLCache(maxsize=1, ttl=self._refresh_period)
+        self._lookback_days = self._pairlistconfig.get('lookback_days', 0)
+        self._lookback_timeframe = self._pairlistconfig.get('lookback_timeframe', '1d')
+        self._lookback_period = self._pairlistconfig.get('lookback_period', 0)
+
+        if (self._lookback_days > 0) & (self._lookback_period > 0):
+            raise OperationalException(
+                'Ambigous configuration: lookback_days and lookback_period both set in pairlist '
+                'config. Please set lookback_days only or lookback_period and lookback_timeframe '
+                'and restart the bot.'
+            )
+
+        # overwrite lookback timeframe and days when lookback_days is set
+        if self._lookback_days > 0:
+            self._lookback_timeframe = '1d'
+            self._lookback_period = self._lookback_days
+
+        # get timeframe in minutes and seconds
+        self._tf_in_min = timeframe_to_minutes(self._lookback_timeframe)
+        self._tf_in_sec = self._tf_in_min * 60
+
+        # wether to use range lookback or not
+        self._use_range = (self._tf_in_min > 0) & (self._lookback_period > 0)
+
+        if self._use_range & (self._refresh_period < self._tf_in_sec):
+            raise OperationalException(
+                f'Refresh period of {self._refresh_period} seconds is smaller than one '
+                f'timeframe of {self._lookback_timeframe}. Please adjust refresh_period '
+                f'to at least {self._tf_in_sec} and restart the bot.'
+            )
 
         if not self._exchange.exchange_has('fetchTickers'):
             raise OperationalException(
@@ -47,6 +79,13 @@ class VolumePairList(IPairList):
             raise OperationalException(
                 f'key {self._sort_key} not in {SORT_VALUES}')
 
+        if self._lookback_period < 0:
+            raise OperationalException("VolumeFilter requires lookback_period to be >= 0")
+        if self._lookback_period > exchange.ohlcv_candle_limit(self._lookback_timeframe):
+            raise OperationalException("VolumeFilter requires lookback_period to not "
+                                       "exceed exchange max request size "
+                                       f"({exchange.ohlcv_candle_limit(self._lookback_timeframe)})")
+
     @property
     def needstickers(self) -> bool:
         """
@@ -78,7 +117,6 @@ class VolumePairList(IPairList):
             # Item found - no refresh necessary
             return pairlist
         else:
-
             # Use fresh pairlist
             # Check if pair quote currency equals to the stake currency.
             filtered_tickers = [
@@ -103,6 +141,60 @@ class VolumePairList(IPairList):
         # Use the incoming pairlist.
         filtered_tickers = [v for k, v in tickers.items() if k in pairlist]
 
+        # get lookback period in ms, for exchange ohlcv fetch
+        if self._use_range:
+            since_ms = int(arrow.utcnow()
+                           .floor('minute')
+                           .shift(minutes=-(self._lookback_period * self._tf_in_min)
+                                  - self._tf_in_min)
+                           .int_timestamp) * 1000
+
+            to_ms = int(arrow.utcnow()
+                        .floor('minute')
+                        .shift(minutes=-self._tf_in_min)
+                        .int_timestamp) * 1000
+
+            # todo: utc date output for starting date
+            self.log_once(f"Using volume range of {self._lookback_period} candles, timeframe: "
+                          f"{self._lookback_timeframe}, starting from {format_ms_time(since_ms)} "
+                          f"till {format_ms_time(to_ms)}", logger.info)
+            needed_pairs = [
+                (p, self._lookback_timeframe) for p in
+                [
+                    s['symbol'] for s in filtered_tickers
+                ] if p not in self._pair_cache
+            ]
+
+            # Get all candles
+            candles = {}
+            if needed_pairs:
+                candles = self._exchange.refresh_latest_ohlcv(
+                    needed_pairs, since_ms=since_ms, cache=False
+                )
+            for i, p in enumerate(filtered_tickers):
+                pair_candles = candles[
+                    (p['symbol'], self._lookback_timeframe)
+                ] if (p['symbol'], self._lookback_timeframe) in candles else None
+                # in case of candle data calculate typical price and quoteVolume for candle
+                if pair_candles is not None and not pair_candles.empty:
+                    pair_candles['typical_price'] = (pair_candles['high'] + pair_candles['low']
+                                                     + pair_candles['close']) / 3
+                    pair_candles['quoteVolume'] = (
+                        pair_candles['volume'] * pair_candles['typical_price']
+                    )
+
+                    # ensure that a rolling sum over the lookback_period is built
+                    # if pair_candles contains more candles than lookback_period
+                    quoteVolume = (pair_candles['quoteVolume']
+                                   .rolling(self._lookback_period)
+                                   .sum()
+                                   .iloc[-1])
+
+                    # replace quoteVolume with range quoteVolume sum calculated above
+                    filtered_tickers[i]['quoteVolume'] = quoteVolume
+                else:
+                    filtered_tickers[i]['quoteVolume'] = 0
+
         if self._min_value > 0:
             filtered_tickers = [
                     v for v in filtered_tickers if v[self._sort_key] > self._min_value]

freqtrade/plugins/pairlist/rangestabilityfilter.py

@@ -62,10 +62,10 @@ class RangeStabilityFilter(IPairList):
         """
         needed_pairs = [(p, '1d') for p in pairlist if p not in self._pair_cache]
 
-        since_ms = int(arrow.utcnow()
-                       .floor('day')
-                       .shift(days=-self._days - 1)
-                       .float_timestamp) * 1000
+        since_ms = (arrow.utcnow()
+                         .floor('day')
+                         .shift(days=-self._days - 1)
+                         .int_timestamp) * 1000
         # Get all candles
         candles = {}
         if needed_pairs:

freqtrade/resolvers/strategy_resolver.py

@@ -45,10 +45,6 @@ class StrategyResolver(IResolver):
             strategy_name, config=config,
             extra_dir=config.get('strategy_path'))
 
-        # make sure ask_strategy dict is available
-        if 'ask_strategy' not in config:
-            config['ask_strategy'] = {}
-
         if hasattr(strategy, 'ticker_interval') and not hasattr(strategy, 'timeframe'):
             # Assign ticker_interval to timeframe to keep compatibility
             if 'timeframe' not in config:
@@ -57,45 +53,54 @@ class StrategyResolver(IResolver):
                     )
                 strategy.timeframe = strategy.ticker_interval
 
+        if strategy._ft_params_from_file:
+            # Set parameters from Hyperopt results file
+            params = strategy._ft_params_from_file
+            strategy.minimal_roi = params.get('roi', strategy.minimal_roi)
+
+            strategy.stoploss = params.get('stoploss', {}).get('stoploss', strategy.stoploss)
+            trailing = params.get('trailing', {})
+            strategy.trailing_stop = trailing.get('trailing_stop', strategy.trailing_stop)
+            strategy.trailing_stop_positive = trailing.get('trailing_stop_positive',
+                                                           strategy.trailing_stop_positive)
+            strategy.trailing_stop_positive_offset = trailing.get(
+                'trailing_stop_positive_offset', strategy.trailing_stop_positive_offset)
+            strategy.trailing_only_offset_is_reached = trailing.get(
+                'trailing_only_offset_is_reached', strategy.trailing_only_offset_is_reached)
+
         # Set attributes
         # Check if we need to override configuration
         #             (Attribute name,                    default,     subkey)
-        attributes = [("minimal_roi",                     {"0": 10.0}, None),
-                      ("timeframe",                       None,        None),
-                      ("stoploss",                        None,        None),
-                      ("trailing_stop",                   None,        None),
-                      ("trailing_stop_positive",          None,        None),
-                      ("trailing_stop_positive_offset",   0.0,         None),
-                      ("trailing_only_offset_is_reached", None,        None),
-                      ("use_custom_stoploss",             None,        None),
-                      ("process_only_new_candles",        None,        None),
-                      ("order_types",                     None,        None),
-                      ("order_time_in_force",             None,        None),
-                      ("stake_currency",                  None,        None),
-                      ("stake_amount",                    None,        None),
-                      ("protections",                     None,        None),
-                      ("startup_candle_count",            None,        None),
-                      ("unfilledtimeout",                 None,        None),
-                      ("use_sell_signal",                 True,        'ask_strategy'),
-                      ("sell_profit_only",                False,       'ask_strategy'),
-                      ("ignore_roi_if_buy_signal",        False,       'ask_strategy'),
-                      ("sell_profit_offset",              0.0,         'ask_strategy'),
-                      ("disable_dataframe_checks",        False,       None),
-                      ("ignore_buying_expired_candle_after",  0,       'ask_strategy')
+        attributes = [("minimal_roi",                     {"0": 10.0}),
+                      ("timeframe",                       None),
+                      ("stoploss",                        None),
+                      ("trailing_stop",                   None),
+                      ("trailing_stop_positive",          None),
+                      ("trailing_stop_positive_offset",   0.0),
+                      ("trailing_only_offset_is_reached", None),
+                      ("use_custom_stoploss",             None),
+                      ("process_only_new_candles",        None),
+                      ("order_types",                     None),
+                      ("order_time_in_force",             None),
+                      ("stake_currency",                  None),
+                      ("stake_amount",                    None),
+                      ("protections",                     None),
+                      ("startup_candle_count",            None),
+                      ("unfilledtimeout",                 None),
+                      ("use_sell_signal",                 True),
+                      ("sell_profit_only",                False),
+                      ("ignore_roi_if_buy_signal",        False),
+                      ("sell_profit_offset",              0.0),
+                      ("disable_dataframe_checks",        False),
+                      ("ignore_buying_expired_candle_after",  0)
                       ]
-        for attribute, default, subkey in attributes:
-            if subkey:
-                StrategyResolver._override_attribute_helper(strategy, config.get(subkey, {}),
-                                                            attribute, default)
-            else:
-                StrategyResolver._override_attribute_helper(strategy, config,
-                                                            attribute, default)
+        for attribute, default in attributes:
+            StrategyResolver._override_attribute_helper(strategy, config,
+                                                        attribute, default)
 
         # Loop this list again to have output combined
-        for attribute, _, subkey in attributes:
-            if subkey and attribute in config[subkey]:
-                logger.info("Strategy using %s: %s", attribute, config[subkey][attribute])
-            elif attribute in config:
+        for attribute, _ in attributes:
+            if attribute in config:
                 logger.info("Strategy using %s: %s", attribute, config[attribute])
 
         StrategyResolver._normalize_attributes(strategy)

freqtrade/rpc/api_server/api_backtest.py

@@ -0,0 +1,176 @@
+import asyncio
+import logging
+from copy import deepcopy
+
+from fastapi import APIRouter, BackgroundTasks, Depends
+
+from freqtrade.enums import BacktestState
+from freqtrade.exceptions import DependencyException
+from freqtrade.rpc.api_server.api_schemas import BacktestRequest, BacktestResponse
+from freqtrade.rpc.api_server.deps import get_config
+from freqtrade.rpc.api_server.webserver import ApiServer
+from freqtrade.rpc.rpc import RPCException
+
+
+logger = logging.getLogger(__name__)
+
+# Private API, protected by authentication
+router = APIRouter()
+
+
+@router.post('/backtest', response_model=BacktestResponse, tags=['webserver', 'backtest'])
+async def api_start_backtest(bt_settings: BacktestRequest, background_tasks: BackgroundTasks,
+                             config=Depends(get_config)):
+    """Start backtesting if not done so already"""
+    if ApiServer._bgtask_running:
+        raise RPCException('Bot Background task already running')
+
+    btconfig = deepcopy(config)
+    settings = dict(bt_settings)
+    # Pydantic models will contain all keys, but non-provided ones are None
+    for setting in settings.keys():
+        if settings[setting] is not None:
+            btconfig[setting] = settings[setting]
+
+    # Start backtesting
+    # Initialize backtesting object
+    def run_backtest():
+        from freqtrade.optimize.optimize_reports import generate_backtest_stats
+        from freqtrade.resolvers import StrategyResolver
+        asyncio.set_event_loop(asyncio.new_event_loop())
+        try:
+            # Reload strategy
+            lastconfig = ApiServer._bt_last_config
+            strat = StrategyResolver.load_strategy(btconfig)
+
+            if (
+                not ApiServer._bt
+                or lastconfig.get('timeframe') != strat.timeframe
+                or lastconfig.get('dry_run_wallet') != btconfig.get('dry_run_wallet', 0)
+            ):
+                from freqtrade.optimize.backtesting import Backtesting
+                ApiServer._bt = Backtesting(btconfig)
+
+            # Only reload data if timeframe or timerange changed.
+            if (
+                not ApiServer._bt_data
+                or not ApiServer._bt_timerange
+                or lastconfig.get('timerange') != btconfig['timerange']
+                or lastconfig.get('stake_amount') != btconfig.get('stake_amount')
+                or lastconfig.get('enable_protections') != btconfig.get('enable_protections')
+                or lastconfig.get('protections') != btconfig.get('protections', [])
+                or lastconfig.get('timeframe') != strat.timeframe
+            ):
+                lastconfig['timerange'] = btconfig['timerange']
+                lastconfig['protections'] = btconfig.get('protections', [])
+                lastconfig['enable_protections'] = btconfig.get('enable_protections')
+                lastconfig['dry_run_wallet'] = btconfig.get('dry_run_wallet')
+                lastconfig['timeframe'] = strat.timeframe
+                ApiServer._bt_data, ApiServer._bt_timerange = ApiServer._bt.load_bt_data()
+
+            ApiServer._bt.abort = False
+            min_date, max_date = ApiServer._bt.backtest_one_strategy(
+                strat, ApiServer._bt_data, ApiServer._bt_timerange)
+            ApiServer._bt.results = generate_backtest_stats(
+                ApiServer._bt_data, ApiServer._bt.all_results,
+                min_date=min_date, max_date=max_date)
+            logger.info("Backtest finished.")
+
+        except DependencyException as e:
+            logger.info(f"Backtesting caused an error: {e}")
+            pass
+        finally:
+            ApiServer._bgtask_running = False
+
+    background_tasks.add_task(run_backtest)
+    ApiServer._bgtask_running = True
+
+    return {
+        "status": "running",
+        "running": True,
+        "progress": 0,
+        "step": str(BacktestState.STARTUP),
+        "status_msg": "Backtest started",
+    }
+
+
+@router.get('/backtest', response_model=BacktestResponse, tags=['webserver', 'backtest'])
+def api_get_backtest():
+    """
+    Get backtesting result.
+    Returns Result after backtesting has been ran.
+    """
+    from freqtrade.persistence import LocalTrade
+    if ApiServer._bgtask_running:
+        return {
+            "status": "running",
+            "running": True,
+            "step": ApiServer._bt.progress.action if ApiServer._bt else str(BacktestState.STARTUP),
+            "progress": ApiServer._bt.progress.progress if ApiServer._bt else 0,
+            "trade_count": len(LocalTrade.trades),
+            "status_msg": "Backtest running",
+        }
+
+    if not ApiServer._bt:
+        return {
+            "status": "not_started",
+            "running": False,
+            "step": "",
+            "progress": 0,
+            "status_msg": "Backtest not yet executed"
+        }
+
+    return {
+        "status": "ended",
+        "running": False,
+        "status_msg": "Backtest ended",
+        "step": "finished",
+        "progress": 1,
+        "backtest_result": ApiServer._bt.results,
+    }
+
+
+@router.delete('/backtest', response_model=BacktestResponse, tags=['webserver', 'backtest'])
+def api_delete_backtest():
+    """Reset backtesting"""
+    if ApiServer._bgtask_running:
+        return {
+            "status": "running",
+            "running": True,
+            "step": "",
+            "progress": 0,
+            "status_msg": "Backtest running",
+        }
+    if ApiServer._bt:
+        del ApiServer._bt
+        ApiServer._bt = None
+        del ApiServer._bt_data
+        ApiServer._bt_data = None
+        logger.info("Backtesting reset")
+    return {
+        "status": "reset",
+        "running": False,
+        "step": "",
+        "progress": 0,
+        "status_msg": "Backtest reset",
+    }
+
+
+@router.get('/backtest/abort', response_model=BacktestResponse, tags=['webserver', 'backtest'])
+def api_backtest_abort():
+    if not ApiServer._bgtask_running:
+        return {
+            "status": "not_running",
+            "running": False,
+            "step": "",
+            "progress": 0,
+            "status_msg": "Backtest ended",
+        }
+    ApiServer._bt.abort = True
+    return {
+        "status": "stopping",
+        "running": False,
+        "step": "",
+        "progress": 0,
+        "status_msg": "Backtest ended",
+    }

freqtrade/rpc/api_server/api_schemas.py

@@ -67,12 +67,16 @@ class Profit(BaseModel):
     profit_closed_ratio_mean: float
     profit_closed_percent_sum: float
     profit_closed_ratio_sum: float
+    profit_closed_percent: float
+    profit_closed_ratio: float
     profit_closed_fiat: float
     profit_all_coin: float
     profit_all_percent_mean: float
     profit_all_ratio_mean: float
     profit_all_percent_sum: float
     profit_all_ratio_sum: float
+    profit_all_percent: float
+    profit_all_ratio: float
     profit_all_fiat: float
     trade_count: int
     closed_trade_count: int
@@ -115,19 +119,21 @@ class ShowConfig(BaseModel):
     dry_run: bool
     stake_currency: str
     stake_amount: Union[float, str]
+    available_capital: Optional[float]
+    stake_currency_decimals: int
     max_open_trades: int
     minimal_roi: Dict[str, Any]
-    stoploss: float
-    trailing_stop: bool
+    stoploss: Optional[float]
+    trailing_stop: Optional[bool]
     trailing_stop_positive: Optional[float]
     trailing_stop_positive_offset: Optional[float]
     trailing_only_offset_is_reached: Optional[bool]
     use_custom_stoploss: Optional[bool]
-    timeframe: str
+    timeframe: Optional[str]
     timeframe_ms: int
     timeframe_min: int
     exchange: str
-    strategy: str
+    strategy: Optional[str]
     forcebuy_enabled: bool
     ask_strategy: Dict[str, Any]
     bid_strategy: Dict[str, Any]
@@ -312,3 +318,24 @@ class PairHistory(BaseModel):
         json_encoders = {
             datetime: lambda v: v.strftime(DATETIME_PRINT_FORMAT),
         }
+
+
+class BacktestRequest(BaseModel):
+    strategy: str
+    timeframe: Optional[str]
+    timerange: Optional[str]
+    max_open_trades: Optional[int]
+    stake_amount: Optional[Union[float, str]]
+    enable_protections: bool
+    dry_run_wallet: Optional[float]
+
+
+class BacktestResponse(BaseModel):
+    status: str
+    running: bool
+    status_msg: str
+    step: str
+    progress: float
+    trade_count: Optional[float]
+    # TODO: Properly type backtestresult...
+    backtest_result: Optional[Dict[str, Any]]

freqtrade/rpc/api_server/api_v1.py

@@ -1,3 +1,4 @@
+import logging
 from copy import deepcopy
 from pathlib import Path
 from typing import List, Optional
@@ -22,6 +23,8 @@ from freqtrade.rpc.api_server.deps import get_config, get_rpc, get_rpc_optional
 from freqtrade.rpc.rpc import RPCException
 
 
+logger = logging.getLogger(__name__)
+
 # Public API, requires no auth.
 router_public = APIRouter()
 # Private API, protected by authentication
@@ -249,7 +252,7 @@ def list_available_pairs(timeframe: Optional[str] = None, stake_currency: Option
     pair_interval = sorted(pair_interval, key=lambda x: x[0])
 
     pairs = list({x[0] for x in pair_interval})
-
+    pairs.sort()
     result = {
         'length': len(pairs),
         'pairs': pairs,

freqtrade/rpc/api_server/web_ui.py

@@ -18,6 +18,17 @@ async def fallback():
     return FileResponse(str(Path(__file__).parent / 'ui/fallback_file.html'))
 
 
+@router_ui.get('/ui_version', include_in_schema=False)
+async def ui_version():
+    from freqtrade.commands.deploy_commands import read_ui_version
+    uibase = Path(__file__).parent / 'ui/installed/'
+    version = read_ui_version(uibase)
+
+    return {
+        "version": version if version else "not_installed",
+    }
+
+
 @router_ui.get('/{rest_of_path:path}', include_in_schema=False)
 async def index_html(rest_of_path: str):
     """

freqtrade/rpc/api_server/webserver.py

@@ -8,6 +8,7 @@ from fastapi import Depends, FastAPI
 from fastapi.middleware.cors import CORSMiddleware
 from starlette.responses import JSONResponse
 
+from freqtrade.exceptions import OperationalException
 from freqtrade.rpc.api_server.uvicorn_threaded import UvicornServer
 from freqtrade.rpc.rpc import RPC, RPCException, RPCHandler
 
@@ -28,17 +29,37 @@ class FTJSONResponse(JSONResponse):
 
 class ApiServer(RPCHandler):
 
+    __instance = None
+    __initialized = False
+
     _rpc: RPC
+    # Backtesting type: Backtesting
+    _bt = None
+    _bt_data = None
+    _bt_timerange = None
+    _bt_last_config: Dict[str, Any] = {}
     _has_rpc: bool = False
+    _bgtask_running: bool = False
     _config: Dict[str, Any] = {}
 
-    def __init__(self, rpc: RPC, config: Dict[str, Any]) -> None:
-        super().__init__(rpc, config)
-        self._server = None
+    def __new__(cls, *args, **kwargs):
+        """
+        This class is a singleton.
+        We'll only have one instance of it around.
+        """
+        if ApiServer.__instance is None:
+            ApiServer.__instance = object.__new__(cls)
+            ApiServer.__initialized = False
+        return ApiServer.__instance
 
-        ApiServer._rpc = rpc
-        ApiServer._has_rpc = True
+    def __init__(self, config: Dict[str, Any], standalone: bool = False) -> None:
         ApiServer._config = config
+        if self.__initialized and (standalone or self._standalone):
+            return
+        self._standalone: bool = standalone
+        self._server = None
+        ApiServer.__initialized = True
+
         api_config = self._config['api_server']
 
         self.app = FastAPI(title="Freqtrade API",
@@ -50,12 +71,33 @@ class ApiServer(RPCHandler):
 
         self.start_api()
 
+    def add_rpc_handler(self, rpc: RPC):
+        """
+        Attach rpc handler
+        """
+        if not self._has_rpc:
+            ApiServer._rpc = rpc
+            ApiServer._has_rpc = True
+        else:
+            # This should not happen assuming we didn't mess up.
+            raise OperationalException('RPC Handler already attached.')
+
     def cleanup(self) -> None:
         """ Cleanup pending module resources """
-        if self._server:
+        ApiServer._has_rpc = False
+        del ApiServer._rpc
+        if self._server and not self._standalone:
             logger.info("Stopping API Server")
             self._server.cleanup()
 
+    @classmethod
+    def shutdown(cls):
+        cls.__initialized = False
+        del cls.__instance
+        cls.__instance = None
+        cls._has_rpc = False
+        cls._rpc = None
+
     def send_msg(self, msg: Dict[str, str]) -> None:
         pass
 
@@ -68,6 +110,7 @@ class ApiServer(RPCHandler):
 
     def configure_app(self, app: FastAPI, config):
         from freqtrade.rpc.api_server.api_auth import http_basic_or_jwt_token, router_login
+        from freqtrade.rpc.api_server.api_backtest import router as api_backtest
         from freqtrade.rpc.api_server.api_v1 import router as api_v1
         from freqtrade.rpc.api_server.api_v1 import router_public as api_v1_public
         from freqtrade.rpc.api_server.web_ui import router_ui
@@ -77,6 +120,9 @@ class ApiServer(RPCHandler):
         app.include_router(api_v1, prefix="/api/v1",
                            dependencies=[Depends(http_basic_or_jwt_token)],
                            )
+        app.include_router(api_backtest, prefix="/api/v1",
+                           dependencies=[Depends(http_basic_or_jwt_token)],
+                           )
         app.include_router(router_login, prefix="/api/v1", tags=["auth"])
         # UI Router MUST be last!
         app.include_router(router_ui, prefix='')
@@ -125,6 +171,9 @@ class ApiServer(RPCHandler):
                                   )
         try:
             self._server = UvicornServer(uvconfig)
-            self._server.run_in_thread()
+            if self._standalone:
+                self._server.run()
+            else:
+                self._server.run_in_thread()
         except Exception:
             logger.exception("Api server failed to start.")

freqtrade/rpc/rpc.py

@@ -18,7 +18,7 @@ from freqtrade.enums import SellType, State
 from freqtrade.exceptions import ExchangeError, PricingError
 from freqtrade.exchange import timeframe_to_minutes, timeframe_to_msecs
 from freqtrade.loggers import bufferHandler
-from freqtrade.misc import shorten_date
+from freqtrade.misc import decimals_per_coin, shorten_date
 from freqtrade.persistence import PairLocks, Trade
 from freqtrade.persistence.models import PairLock
 from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
@@ -104,7 +104,9 @@ class RPC:
         val = {
             'dry_run': config['dry_run'],
             'stake_currency': config['stake_currency'],
+            'stake_currency_decimals':  decimals_per_coin(config['stake_currency']),
             'stake_amount': config['stake_amount'],
+            'available_capital': config.get('available_capital'),
             'max_open_trades': (config['max_open_trades']
                                 if config['max_open_trades'] != float('inf') else -1),
             'minimal_roi': config['minimal_roi'].copy() if 'minimal_roi' in config else {},
@@ -117,9 +119,9 @@ class RPC:
             'bot_name': config.get('bot_name', 'freqtrade'),
             'timeframe': config.get('timeframe'),
             'timeframe_ms': timeframe_to_msecs(config['timeframe']
-                                               ) if 'timeframe' in config else '',
+                                               ) if 'timeframe' in config else 0,
             'timeframe_min': timeframe_to_minutes(config['timeframe']
-                                                  ) if 'timeframe' in config else '',
+                                                  ) if 'timeframe' in config else 0,
             'exchange': config['exchange']['name'],
             'strategy': config['strategy'],
             'forcebuy_enabled': config.get('forcebuy_enable', False),
@@ -152,7 +154,8 @@ class RPC:
                 # calculate profit and send message to user
                 if trade.is_open:
                     try:
-                        current_rate = self._freqtrade.exchange.get_sell_rate(trade.pair, False)
+                        current_rate = self._freqtrade.exchange.get_rate(
+                            trade.pair, refresh=False, side="sell")
                     except (ExchangeError, PricingError):
                         current_rate = NAN
                 else:
@@ -211,7 +214,8 @@ class RPC:
             for trade in trades:
                 # calculate profit and send message to user
                 try:
-                    current_rate = self._freqtrade.exchange.get_sell_rate(trade.pair, False)
+                    current_rate = self._freqtrade.exchange.get_rate(
+                        trade.pair, refresh=False, side="sell")
                 except (PricingError, ExchangeError):
                     current_rate = NAN
                 trade_percent = (100 * trade.calc_profit_ratio(current_rate))
@@ -270,10 +274,10 @@ class RPC:
                 'date': key,
                 'abs_profit': value["amount"],
                 'fiat_value': self._fiat_converter.convert_amount(
-                        value['amount'],
-                        stake_currency,
-                        fiat_display_currency
-                    ) if self._fiat_converter else 0,
+                    value['amount'],
+                    stake_currency,
+                    fiat_display_currency
+                ) if self._fiat_converter else 0,
                 'trade_count': value["trades"],
             }
             for key, value in profit_days.items()
@@ -370,7 +374,8 @@ class RPC:
             else:
                 # Get current rate
                 try:
-                    current_rate = self._freqtrade.exchange.get_sell_rate(trade.pair, False)
+                    current_rate = self._freqtrade.exchange.get_rate(
+                        trade.pair, refresh=False, side="sell")
                 except (PricingError, ExchangeError):
                     current_rate = NAN
                 profit_ratio = trade.calc_profit_ratio(rate=current_rate)
@@ -380,7 +385,7 @@ class RPC:
             )
             profit_all_ratio.append(profit_ratio)
 
-        best_pair = Trade.get_best_pair()
+        best_pair = Trade.get_best_pair(start_date)
 
         # Prepare data to display
         profit_closed_coin_sum = round(sum(profit_closed_coin), 8)
@@ -395,7 +400,12 @@ class RPC:
 
         profit_all_coin_sum = round(sum(profit_all_coin), 8)
         profit_all_ratio_mean = float(mean(profit_all_ratio) if profit_all_ratio else 0.0)
+        # Doing the sum is not right - overall profit needs to be based on initial capital
         profit_all_ratio_sum = sum(profit_all_ratio) if profit_all_ratio else 0.0
+        starting_balance = self._freqtrade.wallets.get_starting_balance()
+        profit_closed_ratio_fromstart = profit_closed_coin_sum / starting_balance
+        profit_all_ratio_fromstart = profit_all_coin_sum / starting_balance
+
         profit_all_fiat = self._fiat_converter.convert_amount(
             profit_all_coin_sum,
             stake_currency,
@@ -411,12 +421,16 @@ class RPC:
             'profit_closed_ratio_mean': profit_closed_ratio_mean,
             'profit_closed_percent_sum': round(profit_closed_ratio_sum * 100, 2),
             'profit_closed_ratio_sum': profit_closed_ratio_sum,
+            'profit_closed_ratio': profit_closed_ratio_fromstart,
+            'profit_closed_percent': round(profit_closed_ratio_fromstart * 100, 2),
             'profit_closed_fiat': profit_closed_fiat,
             'profit_all_coin': profit_all_coin_sum,
             'profit_all_percent_mean': round(profit_all_ratio_mean * 100, 2),
             'profit_all_ratio_mean': profit_all_ratio_mean,
             'profit_all_percent_sum': round(profit_all_ratio_sum * 100, 2),
             'profit_all_ratio_sum': profit_all_ratio_sum,
+            'profit_all_ratio': profit_all_ratio_fromstart,
+            'profit_all_percent': round(profit_all_ratio_fromstart * 100, 2),
             'profit_all_fiat': profit_all_fiat,
             'trade_count': len(trades),
             'closed_trade_count': len([t for t in trades if not t.is_open]),
@@ -540,7 +554,8 @@ class RPC:
 
             if not fully_canceled:
                 # Get current rate and execute sell
-                current_rate = self._freqtrade.exchange.get_sell_rate(trade.pair, False)
+                current_rate = self._freqtrade.exchange.get_rate(
+                    trade.pair, refresh=False, side="sell")
                 sell_reason = SellCheckTuple(sell_type=SellType.FORCE_SELL)
                 self._freqtrade.execute_sell(trade, current_rate, sell_reason)
         # ---- EOF def _exec_forcesell ----
@@ -760,7 +775,7 @@ class RPC:
         sell_signals = 0
         if has_content:
 
-            dataframe.loc[:, '__date_ts'] = dataframe.loc[:, 'date'].astype(int64) // 1000 // 1000
+            dataframe.loc[:, '__date_ts'] = dataframe.loc[:, 'date'].view(int64) // 1000 // 1000
             # Move open to seperate column when signal for easy plotting
             if 'buy' in dataframe.columns:
                 buy_mask = (dataframe['buy'] == 1)

freqtrade/rpc/rpc_manager.py

@@ -1,5 +1,5 @@
 """
-This module contains class to manage RPC communications (Telegram, Slack, ...)
+This module contains class to manage RPC communications (Telegram, API, ...)
 """
 import logging
 from typing import Any, Dict, List
@@ -13,7 +13,7 @@ logger = logging.getLogger(__name__)
 
 class RPCManager:
     """
-    Class to manage RPC objects (Telegram, Slack, ...)
+    Class to manage RPC objects (Telegram, API, ...)
     """
     def __init__(self, freqtrade) -> None:
         """ Initializes all enabled rpc modules """
@@ -36,15 +36,16 @@ class RPCManager:
         if config.get('api_server', {}).get('enabled', False):
             logger.info('Enabling rpc.api_server')
             from freqtrade.rpc.api_server import ApiServer
-
-            self.registered_modules.append(ApiServer(self._rpc, config))
+            apiserver = ApiServer(config)
+            apiserver.add_rpc_handler(self._rpc)
+            self.registered_modules.append(apiserver)
 
     def cleanup(self) -> None:
         """ Stops all enabled rpc modules """
         logger.info('Cleaning up rpc modules ...')
         while self.registered_modules:
             mod = self.registered_modules.pop()
-            logger.debug('Cleaning up rpc.%s ...', mod.name)
+            logger.info('Cleaning up rpc.%s ...', mod.name)
             mod.cleanup()
             del mod
 

freqtrade/rpc/telegram.py

@@ -24,7 +24,7 @@ from freqtrade.__init__ import __version__
 from freqtrade.constants import DUST_PER_COIN
 from freqtrade.enums import RPCMessageType
 from freqtrade.exceptions import OperationalException
-from freqtrade.misc import chunks, round_coin_value
+from freqtrade.misc import chunks, plural, round_coin_value
 from freqtrade.rpc import RPC, RPCException, RPCHandler
 
 
@@ -494,11 +494,11 @@ class Telegram(RPCHandler):
             start_date)
         profit_closed_coin = stats['profit_closed_coin']
         profit_closed_percent_mean = stats['profit_closed_percent_mean']
-        profit_closed_percent_sum = stats['profit_closed_percent_sum']
+        profit_closed_percent = stats['profit_closed_percent']
         profit_closed_fiat = stats['profit_closed_fiat']
         profit_all_coin = stats['profit_all_coin']
         profit_all_percent_mean = stats['profit_all_percent_mean']
-        profit_all_percent_sum = stats['profit_all_percent_sum']
+        profit_all_percent = stats['profit_all_percent']
         profit_all_fiat = stats['profit_all_fiat']
         trade_count = stats['trade_count']
         first_trade_date = stats['first_trade_date']
@@ -514,7 +514,7 @@ class Telegram(RPCHandler):
                 markdown_msg = ("*ROI:* Closed trades\n"
                                 f"∙ `{round_coin_value(profit_closed_coin, stake_cur)} "
                                 f"({profit_closed_percent_mean:.2f}%) "
-                                f"({profit_closed_percent_sum} \N{GREEK CAPITAL LETTER SIGMA}%)`\n"
+                                f"({profit_closed_percent} \N{GREEK CAPITAL LETTER SIGMA}%)`\n"
                                 f"∙ `{round_coin_value(profit_closed_fiat, fiat_disp_cur)}`\n")
             else:
                 markdown_msg = "`No closed trade` \n"
@@ -523,7 +523,7 @@ class Telegram(RPCHandler):
                 f"*ROI:* All trades\n"
                 f"∙ `{round_coin_value(profit_all_coin, stake_cur)} "
                 f"({profit_all_percent_mean:.2f}%) "
-                f"({profit_all_percent_sum} \N{GREEK CAPITAL LETTER SIGMA}%)`\n"
+                f"({profit_all_percent} \N{GREEK CAPITAL LETTER SIGMA}%)`\n"
                 f"∙ `{round_coin_value(profit_all_fiat, fiat_disp_cur)}`\n"
                 f"*Total Trade Count:* `{trade_count}`\n"
                 f"*{'First Trade opened' if not timescale else 'Showing Profit since'}:* "
@@ -598,7 +598,10 @@ class Telegram(RPCHandler):
                     "Starting capital: "
                     f"`{self._config['dry_run_wallet']}` {self._config['stake_currency']}.\n"
                 )
+            total_dust_balance = 0
+            total_dust_currencies = 0
             for curr in result['currencies']:
+                curr_output = ''
                 if curr['est_stake'] > balance_dust_level:
                     curr_output = (
                         f"*{curr['currency']}:*\n"
@@ -607,9 +610,9 @@ class Telegram(RPCHandler):
                         f"\t`Pending: {curr['used']:.8f}`\n"
                         f"\t`Est. {curr['stake']}: "
                         f"{round_coin_value(curr['est_stake'], curr['stake'], False)}`\n")
-                else:
-                    curr_output = (f"*{curr['currency']}:* not showing <{balance_dust_level} "
-                                   f"{curr['stake']} amount \n")
+                elif curr['est_stake'] <= balance_dust_level:
+                    total_dust_balance += curr['est_stake']
+                    total_dust_currencies += 1
 
                 # Handle overflowing message length
                 if len(output + curr_output) >= MAX_TELEGRAM_MESSAGE_LENGTH:
@@ -618,6 +621,14 @@ class Telegram(RPCHandler):
                 else:
                     output += curr_output
 
+            if total_dust_balance > 0:
+                output += (
+                    f"*{total_dust_currencies} Other "
+                    f"{plural(total_dust_currencies, 'Currency', 'Currencies')} "
+                    f"(< {balance_dust_level} {result['stake']}):*\n"
+                    f"\t`Est. {result['stake']}: "
+                    f"{round_coin_value(total_dust_balance, result['stake'], False)}`\n")
+
             output += ("\n*Estimated Value*:\n"
                        f"\t`{result['stake']}: {result['total']: .8f}`\n"
                        f"\t`{result['symbol']}: "

freqtrade/strategy/hyper.py

@@ -5,8 +5,10 @@ This module defines a base class for auto-hyperoptable strategies.
 import logging
 from abc import ABC, abstractmethod
 from contextlib import suppress
+from pathlib import Path
 from typing import Any, Dict, Iterator, List, Optional, Sequence, Tuple, Union
 
+from freqtrade.misc import deep_merge_dicts, json_load
 from freqtrade.optimize.hyperopt_tools import HyperoptTools
 
 
@@ -205,6 +207,21 @@ class DecimalParameter(NumericParameter):
         return SKDecimal(low=self.low, high=self.high, decimals=self._decimals, name=name,
                          **self._space_params)
 
+    @property
+    def range(self):
+        """
+        Get each value in this space as list.
+        Returns a List from low to high (inclusive) in Hyperopt mode.
+        Returns a List with 1 item (`value`) in "non-hyperopt" mode, to avoid
+        calculating 100ds of indicators.
+        """
+        if self.in_space and self.optimize:
+            low = int(self.low * pow(10, self._decimals))
+            high = int(self.high * pow(10, self._decimals)) + 1
+            return [round(n * pow(0.1, self._decimals), self._decimals) for n in range(low, high)]
+        else:
+            return [self.value]
+
 
 class CategoricalParameter(BaseParameter):
     default: Any
@@ -239,6 +256,19 @@ class CategoricalParameter(BaseParameter):
         """
         return Categorical(self.opt_range, name=name, **self._space_params)
 
+    @property
+    def range(self):
+        """
+        Get each value in this space as list.
+        Returns a List of categories in Hyperopt mode.
+        Returns a List with 1 item (`value`) in "non-hyperopt" mode, to avoid
+        calculating 100ds of indicators.
+        """
+        if self.in_space and self.optimize:
+            return self.opt_range
+        else:
+            return [self.value]
+
 
 class HyperStrategyMixin(object):
     """
@@ -305,10 +335,36 @@ class HyperStrategyMixin(object):
         """
         Load Hyperoptable parameters
         """
-        self._load_params(getattr(self, 'buy_params', None), 'buy', hyperopt)
-        self._load_params(getattr(self, 'sell_params', None), 'sell', hyperopt)
+        params = self.load_params_from_file()
+        params = params.get('params', {})
+        self._ft_params_from_file = params
+        buy_params = deep_merge_dicts(params.get('buy', {}), getattr(self, 'buy_params', {}))
+        sell_params = deep_merge_dicts(params.get('sell', {}), getattr(self, 'sell_params', {}))
 
-    def _load_params(self, params: dict, space: str, hyperopt: bool = False) -> None:
+        self._load_params(buy_params, 'buy', hyperopt)
+        self._load_params(sell_params, 'sell', hyperopt)
+
+    def load_params_from_file(self) -> Dict:
+        filename_str = getattr(self, '__file__', '')
+        if not filename_str:
+            return {}
+        filename = Path(filename_str).with_suffix('.json')
+
+        if filename.is_file():
+            logger.info(f"Loading parameters from file {filename}")
+            try:
+                params = json_load(filename.open('r'))
+                if params.get('strategy_name') != self.__class__.__name__:
+                    raise OperationalException('Invalid parameter file provided.')
+                return params
+            except ValueError:
+                logger.warning("Invalid parameter file format.")
+                return {}
+        logger.info("Found no parameter file.")
+
+        return {}
+
+    def _load_params(self, params: Dict, space: str, hyperopt: bool = False) -> None:
         """
         Set optimizable parameter values.
         :param params: Dictionary with new parameter values.
@@ -335,7 +391,7 @@ class HyperStrategyMixin(object):
             else:
                 logger.info(f'Strategy Parameter(default): {attr_name} = {attr.value}')
 
-    def get_params_dict(self):
+    def get_no_optimize_params(self):
         """
         Returns list of Parameters that are not part of the current optimize job
         """

freqtrade/strategy/interface.py

@@ -62,6 +62,7 @@ class IStrategy(ABC, HyperStrategyMixin):
     _populate_fun_len: int = 0
     _buy_fun_len: int = 0
     _sell_fun_len: int = 0
+    _ft_params_from_file: Dict = {}
     # associated minimal roi
     minimal_roi: Dict
 
@@ -97,6 +98,11 @@ class IStrategy(ABC, HyperStrategyMixin):
     # run "populate_indicators" only for new candle
     process_only_new_candles: bool = False
 
+    use_sell_signal: bool
+    sell_profit_only: bool
+    sell_profit_offset: float
+    ignore_roi_if_buy_signal: bool
+
     # Number of seconds after which the candle will no longer result in a buy on expired candles
     ignore_buying_expired_candle_after: int = 0
 
@@ -298,6 +304,23 @@ class IStrategy(ABC, HyperStrategyMixin):
         """
         return None
 
+    def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
+                            proposed_stake: float, min_stake: float, max_stake: float,
+                            **kwargs) -> float:
+        """
+        Customize stake size for each new trade. This method is not called when edge module is
+        enabled.
+
+        :param pair: Pair that's currently analyzed
+        :param current_time: datetime object, containing the current datetime
+        :param current_rate: Rate, calculated based on pricing settings in ask_strategy.
+        :param proposed_stake: A stake amount proposed by the bot.
+        :param min_stake: Minimal stake size allowed by exchange.
+        :param max_stake: Balance available for trading.
+        :return: A stake size, which is between min_stake and max_stake.
+        """
+        return proposed_stake
+
     def informative_pairs(self) -> ListPairsWithTimeframes:
         """
         Define additional, informative pair/interval combinations to be cached from the exchange.
@@ -543,10 +566,9 @@ class IStrategy(ABC, HyperStrategyMixin):
         # Set current rate to high for backtesting sell
         current_rate = high or rate
         current_profit = trade.calc_profit_ratio(current_rate)
-        ask_strategy = self.config.get('ask_strategy', {})
 
         # if buy signal and ignore_roi is set, we don't need to evaluate min_roi.
-        roi_reached = (not (buy and ask_strategy.get('ignore_roi_if_buy_signal', False))
+        roi_reached = (not (buy and self.ignore_roi_if_buy_signal)
                        and self.min_roi_reached(trade=trade, current_profit=current_profit,
                                                 current_time=date))
 
@@ -556,11 +578,10 @@ class IStrategy(ABC, HyperStrategyMixin):
         current_rate = rate
         current_profit = trade.calc_profit_ratio(current_rate)
 
-        if (ask_strategy.get('sell_profit_only', False)
-                and current_profit <= ask_strategy.get('sell_profit_offset', 0)):
+        if (self.sell_profit_only and current_profit <= self.sell_profit_offset):
             # sell_profit_only and profit doesn't reach the offset - ignore sell signal
             pass
-        elif ask_strategy.get('use_sell_signal', True) and not buy:
+        elif self.use_sell_signal and not buy:
             if sell:
                 sell_signal = SellType.SELL_SIGNAL
             else:

freqtrade/templates/base_config.json.j2

@@ -15,7 +15,7 @@
     "bid_strategy": {
         "price_side": "bid",
         "ask_last_balance": 0.0,
-        "use_order_book": false,
+        "use_order_book": true,
         "order_book_top": 1,
         "check_depth_of_market": {
             "enabled": false,
@@ -24,12 +24,8 @@
     },
     "ask_strategy": {
         "price_side": "ask",
-        "use_order_book": false,
-        "order_book_min": 1,
-        "order_book_max": 1,
-        "use_sell_signal": true,
-        "sell_profit_only": false,
-        "ignore_roi_if_buy_signal": false
+        "use_order_book": true,
+        "order_book_top": 1,
     },
     {{ exchange | indent(4) }},
     "pairlists": [

freqtrade/templates/strategy_analysis_example.ipynb

@@ -188,6 +188,52 @@
     "trades.groupby(\"pair\")[\"sell_reason\"].value_counts()"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Plotting daily profit / equity line"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Plotting equity line (starting with 0 on day 1 and adding daily profit for each backtested day)\n",
+    "\n",
+    "from freqtrade.configuration import Configuration\n",
+    "from freqtrade.data.btanalysis import load_backtest_data, load_backtest_stats\n",
+    "import plotly.express as px\n",
+    "import pandas as pd\n",
+    "\n",
+    "# strategy = 'SampleStrategy'\n",
+    "# config = Configuration.from_files([\"user_data/config.json\"])\n",
+    "# backtest_dir = config[\"user_data_dir\"] / \"backtest_results\"\n",
+    "\n",
+    "stats = load_backtest_stats(backtest_dir)\n",
+    "strategy_stats = stats['strategy'][strategy]\n",
+    "\n",
+    "dates = []\n",
+    "profits = []\n",
+    "for date_profit in strategy_stats['daily_profit']:\n",
+    "    dates.append(date_profit[0])\n",
+    "    profits.append(date_profit[1])\n",
+    "\n",
+    "equity = 0\n",
+    "equity_daily = []\n",
+    "for daily_profit in profits:\n",
+    "    equity_daily.append(equity)\n",
+    "    equity += float(daily_profit)\n",
+    "\n",
+    "\n",
+    "df = pd.DataFrame({'dates': dates,'equity_daily': equity_daily})\n",
+    "\n",
+    "fig = px.line(df, x=\"dates\", y=\"equity_daily\")\n",
+    "fig.show()\n"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -329,7 +375,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.4"
+   "version": "3.8.5"
   },
   "mimetype": "text/x-python",
   "name": "python",

freqtrade/wallets.py

@@ -70,9 +70,7 @@ class Wallets:
         # If not backtesting...
         # TODO: potentially remove the ._log workaround to determine backtest mode.
         if self._log:
-            closed_trades = Trade.get_trades_proxy(is_open=False)
-            tot_profit = sum(
-                [trade.close_profit_abs for trade in closed_trades if trade.close_profit_abs])
+            tot_profit = Trade.get_total_closed_profit()
         else:
             tot_profit = LocalTrade.total_profit
         tot_in_trades = sum([trade.stake_amount for trade in open_trades])
@@ -131,7 +129,41 @@ class Wallets:
     def get_all_balances(self) -> Dict[str, Any]:
         return self._wallets
 
-    def _get_available_stake_amount(self, val_tied_up: float) -> float:
+    def get_starting_balance(self) -> float:
+        """
+        Retrieves starting balance - based on either available capital,
+        or by using current balance subtracting
+        """
+        if "available_capital" in self._config:
+            return self._config['available_capital']
+        else:
+            tot_profit = Trade.get_total_closed_profit()
+            open_stakes = Trade.total_open_trades_stakes()
+            available_balance = self.get_free(self._config['stake_currency'])
+            return available_balance - tot_profit + open_stakes
+
+    def get_total_stake_amount(self):
+        """
+        Return the total currently available balance in stake currency, including tied up stake and
+        respecting tradable_balance_ratio.
+        Calculated as
+        (<open_trade stakes> + free amount) * tradable_balance_ratio
+        """
+        val_tied_up = Trade.total_open_trades_stakes()
+        if "available_capital" in self._config:
+            starting_balance = self._config['available_capital']
+            tot_profit = Trade.get_total_closed_profit()
+            available_amount = starting_balance + tot_profit
+
+        else:
+            # Ensure <tradable_balance_ratio>% is used from the overall balance
+            # Otherwise we'd risk lowering stakes with each open trade.
+            # (tied up + current free) * ratio) - tied up
+            available_amount = ((val_tied_up + self.get_free(self._config['stake_currency'])) *
+                                self._config['tradable_balance_ratio'])
+        return available_amount
+
+    def get_available_stake_amount(self) -> float:
         """
         Return the total currently available balance in stake currency,
         respecting tradable_balance_ratio.
@@ -139,12 +171,8 @@ class Wallets:
         (<open_trade stakes> + free amount) * tradable_balance_ratio - <open_trade stakes>
         """
 
-        # Ensure <tradable_balance_ratio>% is used from the overall balance
-        # Otherwise we'd risk lowering stakes with each open trade.
-        # (tied up + current free) * ratio) - tied up
-        available_amount = ((val_tied_up + self.get_free(self._config['stake_currency'])) *
-                            self._config['tradable_balance_ratio']) - val_tied_up
-        return available_amount
+        free = self.get_free(self._config['stake_currency'])
+        return min(self.get_total_stake_amount() - Trade.total_open_trades_stakes(), free)
 
     def _calculate_unlimited_stake_amount(self, available_amount: float,
                                           val_tied_up: float) -> float:
@@ -193,7 +221,7 @@ class Wallets:
         # Ensure wallets are uptodate.
         self.update()
         val_tied_up = Trade.total_open_trades_stakes()
-        available_amount = self._get_available_stake_amount(val_tied_up)
+        available_amount = self.get_available_stake_amount()
 
         if edge:
             stake_amount = edge.stake_amount(
@@ -209,3 +237,30 @@ class Wallets:
                     available_amount, val_tied_up)
 
         return self._check_available_stake_amount(stake_amount, available_amount)
+
+    def _validate_stake_amount(self, pair, stake_amount, min_stake_amount):
+        if not stake_amount:
+            logger.debug(f"Stake amount is {stake_amount}, ignoring possible trade for {pair}.")
+            return 0
+
+        max_stake_amount = self.get_available_stake_amount()
+
+        if min_stake_amount > max_stake_amount:
+            if self._log:
+                logger.warning("Minimum stake amount > available balance.")
+            return 0
+        if min_stake_amount is not None and stake_amount < min_stake_amount:
+            stake_amount = min_stake_amount
+            if self._log:
+                logger.info(
+                    f"Stake amount for pair {pair} is too small "
+                    f"({stake_amount} < {min_stake_amount}), adjusting to {min_stake_amount}."
+                )
+        if stake_amount > max_stake_amount:
+            stake_amount = max_stake_amount
+            if self._log:
+                logger.info(
+                    f"Stake amount for pair {pair} is too big "
+                    f"({stake_amount} > {max_stake_amount}), adjusting to {max_stake_amount}."
+                )
+        return stake_amount

requirements-dev.txt

@@ -3,23 +3,23 @@
 -r requirements-plot.txt
 -r requirements-hyperopt.txt
 
-coveralls==3.1.0
+coveralls==3.2.0
 flake8==3.9.2
 flake8-type-annotations==0.1.0
 flake8-tidy-imports==4.3.0
-mypy==0.902
+mypy==0.910
 pytest==6.2.4
 pytest-asyncio==0.15.1
 pytest-cov==2.12.1
 pytest-mock==3.6.1
 pytest-random-order==1.0.4
-isort==5.8.0
+isort==5.9.2
 
 # Convert jupyter notebooks to markdown documents
-nbconvert==6.0.7
+nbconvert==6.1.0
 
 # mypy types
-types-cachetools==0.1.8
+types-cachetools==0.1.9
 types-filelock==0.1.4
-types-requests==0.1.13
+types-requests==2.25.0
 types-tabulate==0.1.1

requirements-plot.txt

@@ -1,5 +1,5 @@
 # Include all requirements to run the bot.
 -r requirements.txt
 
-plotly==4.14.3
+plotly==5.1.0
 

requirements.txt

@@ -1,19 +1,19 @@
-numpy==1.20.3
-pandas==1.2.4
+numpy==1.21.1
+pandas==1.3.1
 
-ccxt==1.51.77
+ccxt==1.53.72
 # Pin cryptography for now due to rust build errors with piwheels
 cryptography==3.4.7
 aiohttp==3.7.4.post0
-SQLAlchemy==1.4.18
-python-telegram-bot==13.6
-arrow==1.1.0
+SQLAlchemy==1.4.22
+python-telegram-bot==13.7
+arrow==1.1.1
 cachetools==4.2.2
-requests==2.25.1
-urllib3==1.26.5
+requests==2.26.0
+urllib3==1.26.6
 wrapt==1.12.1
 jsonschema==3.2.0
-TA-Lib==0.4.20
+TA-Lib==0.4.21
 technical==1.3.0
 tabulate==0.8.9
 pycoingecko==2.2.0
@@ -25,13 +25,13 @@ blosc==1.10.4
 py_find_1st==1.1.5
 
 # Load ticker files 30% faster
-python-rapidjson==1.0
+python-rapidjson==1.4
 
 # Notify systemd
 sdnotify==0.3.2
 
 # API Server
-fastapi==0.65.2
+fastapi==0.67.0
 uvicorn==0.14.0
 pyjwt==2.1.0
 aiofiles==0.7.0
@@ -39,5 +39,5 @@ aiofiles==0.7.0
 # Support for colorized terminal output
 colorama==0.4.4
 # Building config files interactively
-questionary==1.9.0
+questionary==1.10.0
 prompt-toolkit==3.0.19

setup.sh

@@ -4,8 +4,12 @@
 function check_installed_pip() {
    ${PYTHON} -m pip > /dev/null
    if [ $? -ne 0 ]; then
-        echo "pip not found (called as '${PYTHON} -m pip'). Please make sure that pip is available for ${PYTHON}."
-        exit 1
+        echo "-----------------------------"
+        echo "Installing Pip for ${PYTHON}"
+        echo "-----------------------------"
+        curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
+        ${PYTHON} get-pip.py
+        rm get-pip.py
    fi
 }
 
@@ -17,35 +21,19 @@ function check_installed_python() {
         exit 2
     fi
 
-    which python3.8
-    if [ $? -eq 0 ]; then
-        echo "using Python 3.8"
-        PYTHON=python3.8
-        check_installed_pip
-        return
-    fi
+    for v in 9 8 7
+    do
+        PYTHON="python3.${v}"
+        which $PYTHON
+        if [ $? -eq 0 ]; then
+            echo "using ${PYTHON}"
+            check_installed_pip
+            return
+        fi
+    done 
 
-    which python3.9
-    if [ $? -eq 0 ]; then
-        echo "using Python 3.9"
-        PYTHON=python3.9
-        check_installed_pip
-        return
-    fi
-
-    which python3.7
-    if [ $? -eq 0 ]; then
-        echo "using Python 3.7"
-        PYTHON=python3.7
-        check_installed_pip
-        return
-    fi
-
-
-   if [ -z ${PYTHON} ]; then
-        echo "No usable python found. Please make sure to have python3.7 or newer installed"
-        exit 1
-   fi
+    echo "No usable python found. Please make sure to have python3.7 or newer installed"
+    exit 1
 }
 
 function updateenv() {
@@ -122,6 +110,25 @@ function install_talib() {
     cd ..
 }
 
+function install_mac_newer_python_dependencies() {    
+    
+    if [ ! $(brew --prefix --installed hdf5 2>/dev/null) ]
+    then
+        echo "-------------------------"
+        echo "Installing hdf5"
+        echo "-------------------------"
+        brew install hdf5
+    fi
+
+    if [ ! $(brew --prefix --installed c-blosc 2>/dev/null) ]
+    then
+        echo "-------------------------"
+        echo "Installing c-blosc"
+        echo "-------------------------"
+        brew install c-blosc
+    fi    
+}
+
 # Install bot MacOS
 function install_macos() {
     if [ ! -x "$(command -v brew)" ]
@@ -131,14 +138,19 @@ function install_macos() {
         echo "-------------------------"
         /usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
     fi
+    #Gets number after decimal in python version
+    version=$(egrep -o 3.\[0-9\]+ <<< $PYTHON | sed 's/3.//g')
+    
+    if [[ $version -ge 9 ]]; then               #Checks if python version >= 3.9
+        install_mac_newer_python_dependencies
+    fi
     install_talib
-    test_and_fix_python_on_mac
 }
 
 # Install bot Debian_ubuntu
 function install_debian() {
     sudo apt-get update
-    sudo apt-get install -y build-essential autoconf libtool pkg-config make wget git libpython3-dev
+    sudo apt-get install -y build-essential autoconf libtool pkg-config make wget git $(echo lib${PYTHON}-dev ${PYTHON}-venv)
     install_talib
 }
 
@@ -189,19 +201,6 @@ function reset() {
     updateenv
 }
 
-function test_and_fix_python_on_mac() {
-
-    if ! [ -x "$(command -v python3.6)" ]
-    then
-        echo "-------------------------"
-        echo "Fixing Python"
-        echo "-------------------------"
-        echo "Python 3.6 is not linked in your system. Fixing it..."
-        brew link --overwrite python
-        echo
-    fi
-}
-
 function config() {
 
     echo "-------------------------"
@@ -240,12 +239,12 @@ function install() {
 }
 
 function plot() {
-echo "
------------------------------------------
-Installing dependencies for Plotting scripts
------------------------------------------
-"
-${PYTHON} -m pip install plotly --upgrade
+    echo "
+    -----------------------------------------
+    Installing dependencies for Plotting scripts
+    -----------------------------------------
+    "
+    ${PYTHON} -m pip install plotly --upgrade
 }
 
 function help() {

tests/commands/test_commands.py

@@ -13,7 +13,7 @@ from freqtrade.commands import (start_convert_data, start_create_userdir, start_
                                 start_list_data, start_list_exchanges, start_list_hyperopts,
                                 start_list_markets, start_list_strategies, start_list_timeframes,
                                 start_new_hyperopt, start_new_strategy, start_show_trades,
-                                start_test_pairlist, start_trading)
+                                start_test_pairlist, start_trading, start_webserver)
 from freqtrade.commands.deploy_commands import (clean_ui_subdir, download_and_install_ui,
                                                 get_ui_download_url, read_ui_version)
 from freqtrade.configuration import setup_utils_configuration
@@ -26,7 +26,7 @@ from tests.conftest_trades import MOCK_TRADE_COUNT
 
 def test_setup_utils_configuration():
     args = [
-        'list-exchanges', '--config', 'config_bittrex.json.example',
+        'list-exchanges', '--config', 'config_examples/config_bittrex.example.json',
     ]
 
     config = setup_utils_configuration(get_args(args), RunMode.OTHER)
@@ -45,7 +45,7 @@ def test_start_trading_fail(mocker, caplog):
     exitmock = mocker.patch("freqtrade.worker.Worker.exit", MagicMock())
     args = [
         'trade',
-        '-c', 'config_bittrex.json.example'
+        '-c', 'config_examples/config_bittrex.example.json'
     ]
     start_trading(get_args(args))
     assert exitmock.call_count == 1
@@ -58,6 +58,18 @@ def test_start_trading_fail(mocker, caplog):
     assert log_has('Fatal exception!', caplog)
 
 
+def test_start_webserver(mocker, caplog):
+
+    api_server_mock = mocker.patch("freqtrade.rpc.api_server.ApiServer", )
+
+    args = [
+        'webserver',
+        '-c', 'config_examples/config_bittrex.example.json'
+    ]
+    start_webserver(get_args(args))
+    assert api_server_mock.call_count == 1
+
+
 def test_list_exchanges(capsys):
 
     args = [
@@ -127,10 +139,10 @@ def test_list_timeframes(mocker, capsys):
                        match=r"This command requires a configured exchange.*"):
         start_list_timeframes(pargs)
 
-    # Test with --config config_bittrex.json.example
+    # Test with --config config_examples/config_bittrex.example.json
     args = [
         "list-timeframes",
-        '--config', 'config_bittrex.json.example',
+        '--config', 'config_examples/config_bittrex.example.json',
     ]
     start_list_timeframes(get_args(args))
     captured = capsys.readouterr()
@@ -174,7 +186,7 @@ def test_list_timeframes(mocker, capsys):
     # Test with --one-column
     args = [
         "list-timeframes",
-        '--config', 'config_bittrex.json.example',
+        '--config', 'config_examples/config_bittrex.example.json',
         "--one-column",
     ]
     start_list_timeframes(get_args(args))
@@ -214,10 +226,10 @@ def test_list_markets(mocker, markets, capsys):
                        match=r"This command requires a configured exchange.*"):
         start_list_markets(pargs, False)
 
-    # Test with --config config_bittrex.json.example
+    # Test with --config config_examples/config_bittrex.example.json
     args = [
         "list-markets",
-        '--config', 'config_bittrex.json.example',
+        '--config', 'config_examples/config_bittrex.example.json',
         "--print-list",
     ]
     start_list_markets(get_args(args), False)
@@ -244,7 +256,7 @@ def test_list_markets(mocker, markets, capsys):
     # Test with --all: all markets
     args = [
         "list-markets", "--all",
-        '--config', 'config_bittrex.json.example',
+        '--config', 'config_examples/config_bittrex.example.json',
         "--print-list",
     ]
     start_list_markets(get_args(args), False)
@@ -257,7 +269,7 @@ def test_list_markets(mocker, markets, capsys):
     # Test list-pairs subcommand: active pairs
     args = [
         "list-pairs",
-        '--config', 'config_bittrex.json.example',
+        '--config', 'config_examples/config_bittrex.example.json',
         "--print-list",
     ]
     start_list_markets(get_args(args), True)
@@ -269,7 +281,7 @@ def test_list_markets(mocker, markets, capsys):
     # Test list-pairs subcommand with --all: all pairs
     args = [
         "list-pairs", "--all",
-        '--config', 'config_bittrex.json.example',
+        '--config', 'config_examples/config_bittrex.example.json',
         "--print-list",
     ]
     start_list_markets(get_args(args), True)
@@ -282,7 +294,7 @@ def test_list_markets(mocker, markets, capsys):
     # active markets, base=ETH, LTC
     args = [
         "list-markets",
-        '--config', 'config_bittrex.json.example',
+        '--config', 'config_examples/config_bittrex.example.json',
         "--base", "ETH", "LTC",
         "--print-list",
     ]
@@ -295,7 +307,7 @@ def test_list_markets(mocker, markets, capsys):
     # active markets, base=LTC
     args = [
         "list-markets",
-        '--config', 'config_bittrex.json.example',
+        '--config', 'config_examples/config_bittrex.example.json',
         "--base", "LTC",
         "--print-list",
     ]
@@ -308,7 +320,7 @@ def test_list_markets(mocker, markets, capsys):
     # active markets, quote=USDT, USD
     args = [
         "list-markets",
-        '--config', 'config_bittrex.json.example',
+        '--config', 'config_examples/config_bittrex.example.json',
         "--quote", "USDT", "USD",
         "--print-list",
     ]
@@ -321,7 +333,7 @@ def test_list_markets(mocker, markets, capsys):
     # active markets, quote=USDT
     args = [
         "list-markets",
-        '--config', 'config_bittrex.json.example',
+        '--config', 'config_examples/config_bittrex.example.json',
         "--quote", "USDT",
         "--print-list",
     ]
@@ -334,7 +346,7 @@ def test_list_markets(mocker, markets, capsys):
     # active markets, base=LTC, quote=USDT
     args = [
         "list-markets",
-        '--config', 'config_bittrex.json.example',
+        '--config', 'config_examples/config_bittrex.example.json',
         "--base", "LTC", "--quote", "USDT",
         "--print-list",
     ]
@@ -347,7 +359,7 @@ def test_list_markets(mocker, markets, capsys):
     # active pairs, base=LTC, quote=USDT
     args = [
         "list-pairs",
-        '--config', 'config_bittrex.json.example',
+        '--config', 'config_examples/config_bittrex.example.json',
         "--base", "LTC", "--quote", "USD",
         "--print-list",
     ]
@@ -360,7 +372,7 @@ def test_list_markets(mocker, markets, capsys):
     # active markets, base=LTC, quote=USDT, NONEXISTENT
     args = [
         "list-markets",
-        '--config', 'config_bittrex.json.example',
+        '--config', 'config_examples/config_bittrex.example.json',
         "--base", "LTC", "--quote", "USDT", "NONEXISTENT",
         "--print-list",
     ]
@@ -373,7 +385,7 @@ def test_list_markets(mocker, markets, capsys):
     # active markets, base=LTC, quote=NONEXISTENT
     args = [
         "list-markets",
-        '--config', 'config_bittrex.json.example',
+        '--config', 'config_examples/config_bittrex.example.json',
         "--base", "LTC", "--quote", "NONEXISTENT",
         "--print-list",
     ]
@@ -386,7 +398,7 @@ def test_list_markets(mocker, markets, capsys):
     # Test tabular output
     args = [
         "list-markets",
-        '--config', 'config_bittrex.json.example',
+        '--config', 'config_examples/config_bittrex.example.json',
     ]
     start_list_markets(get_args(args), False)
     captured = capsys.readouterr()
@@ -396,7 +408,7 @@ def test_list_markets(mocker, markets, capsys):
     # Test tabular output, no markets found
     args = [
         "list-markets",
-        '--config', 'config_bittrex.json.example',
+        '--config', 'config_examples/config_bittrex.example.json',
         "--base", "LTC", "--quote", "NONEXISTENT",
     ]
     start_list_markets(get_args(args), False)
@@ -408,7 +420,7 @@ def test_list_markets(mocker, markets, capsys):
     # Test --print-json
     args = [
         "list-markets",
-        '--config', 'config_bittrex.json.example',
+        '--config', 'config_examples/config_bittrex.example.json',
         "--print-json"
     ]
     start_list_markets(get_args(args), False)
@@ -420,7 +432,7 @@ def test_list_markets(mocker, markets, capsys):
     # Test --print-csv
     args = [
         "list-markets",
-        '--config', 'config_bittrex.json.example',
+        '--config', 'config_examples/config_bittrex.example.json',
         "--print-csv"
     ]
     start_list_markets(get_args(args), False)
@@ -432,7 +444,7 @@ def test_list_markets(mocker, markets, capsys):
     # Test --one-column
     args = [
         "list-markets",
-        '--config', 'config_bittrex.json.example',
+        '--config', 'config_examples/config_bittrex.example.json',
         "--one-column"
     ]
     start_list_markets(get_args(args), False)
@@ -444,7 +456,7 @@ def test_list_markets(mocker, markets, capsys):
     # Test --one-column
     args = [
         "list-markets",
-        '--config', 'config_bittrex.json.example',
+        '--config', 'config_examples/config_bittrex.example.json',
         "--one-column"
     ]
     with pytest.raises(OperationalException, match=r"Cannot get markets.*"):
@@ -887,7 +899,7 @@ def test_start_test_pairlist(mocker, caplog, tickers, default_conf, capsys):
     patched_configuration_load_config_file(mocker, default_conf)
     args = [
         'test-pairlist',
-        '-c', 'config_bittrex.json.example'
+        '-c', 'config_examples/config_bittrex.example.json'
     ]
 
     start_test_pairlist(get_args(args))
@@ -901,7 +913,7 @@ def test_start_test_pairlist(mocker, caplog, tickers, default_conf, capsys):
 
     args = [
         'test-pairlist',
-        '-c', 'config_bittrex.json.example',
+        '-c', 'config_examples/config_bittrex.example.json',
         '--one-column',
     ]
     start_test_pairlist(get_args(args))
@@ -910,7 +922,7 @@ def test_start_test_pairlist(mocker, caplog, tickers, default_conf, capsys):
 
     args = [
         'test-pairlist',
-        '-c', 'config_bittrex.json.example',
+        '-c', 'config_examples/config_bittrex.example.json',
         '--print-json',
     ]
     start_test_pairlist(get_args(args))
@@ -1168,6 +1180,7 @@ def test_hyperopt_show(mocker, capsys, saved_hyperopt_results):
         'freqtrade.optimize.hyperopt_tools.HyperoptTools.load_previous_results',
         MagicMock(return_value=saved_hyperopt_results)
     )
+    mocker.patch('freqtrade.commands.hyperopt_commands.show_backtest_result')
 
     args = [
         "hyperopt-show",

tests/conftest.py

@@ -290,8 +290,7 @@ def get_default_conf(testdatadir):
         },
         "ask_strategy": {
             "use_order_book": False,
-            "order_book_min": 1,
-            "order_book_max": 1
+            "order_book_top": 1,
         },
         "exchange": {
             "name": "binance",
@@ -325,6 +324,7 @@ def get_default_conf(testdatadir):
         "verbosity": 3,
         "strategy_path": str(Path(__file__).parent / "strategy" / "strats"),
         "strategy": "DefaultStrategy",
+        "disableparamexport": True,
         "internals": {},
         "export": "none",
     }
@@ -1762,7 +1762,7 @@ def rpc_balance():
             'total': 0.1,
             'free': 0.01,
             'used': 0.0
-            },
+        },
         'EUR': {
             'total': 10.0,
             'free': 10.0,
@@ -1954,12 +1954,13 @@ def saved_hyperopt_results():
             'params_dict': {
                 'mfi-value': 15, 'fastd-value': 20, 'adx-value': 25, 'rsi-value': 28, 'mfi-enabled': False, 'fastd-enabled': True, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'macd_cross_signal', 'sell-mfi-value': 88, 'sell-fastd-value': 97, 'sell-adx-value': 51, 'sell-rsi-value': 67, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper', 'roi_t1': 1190, 'roi_t2': 541, 'roi_t3': 408, 'roi_p1': 0.026035863879169705, 'roi_p2': 0.12508730043628782, 'roi_p3': 0.27766427921605896, 'stoploss': -0.2562930402099556},  # noqa: E501
             'params_details': {'buy': {'mfi-value': 15, 'fastd-value': 20, 'adx-value': 25, 'rsi-value': 28, 'mfi-enabled': False, 'fastd-enabled': True, 'adx-enabled': True, 'rsi-enabled': True, 'trigger': 'macd_cross_signal'}, 'sell': {'sell-mfi-value': 88, 'sell-fastd-value': 97, 'sell-adx-value': 51, 'sell-rsi-value': 67, 'sell-mfi-enabled': False, 'sell-fastd-enabled': False, 'sell-adx-enabled': True, 'sell-rsi-enabled': True, 'sell-trigger': 'sell-bb_upper'}, 'roi': {0: 0.4287874435315165, 408: 0.15112316431545753, 949: 0.026035863879169705, 2139: 0}, 'stoploss': {'stoploss': -0.2562930402099556}},  # noqa: E501
-            'results_metrics': {'total_trades': 2, 'wins': 0, 'draws': 0, 'losses': 2, 'profit_mean': -0.01254995, 'profit_median': -0.012222, 'profit_total': -0.00125625, 'profit_total_abs': -2.50999, 'holding_avg': timedelta(minutes=3930.0)},  # noqa: E501
+            'results_metrics': {'total_trades': 2, 'wins': 0, 'draws': 0, 'losses': 2, 'profit_mean': -0.01254995, 'profit_median': -0.012222, 'profit_total': -0.00125625, 'profit_total_abs': -2.50999, 'holding_avg': timedelta(minutes=3930.0), 'stake_currency': 'BTC', 'strategy_name': 'SampleStrategy'},  # noqa: E501
             'results_explanation': '     2 trades. Avg profit  -1.25%. Total profit -0.00125625 BTC (  -2.51Σ%). Avg duration 3930.0 min.',  # noqa: E501
             'total_profit': -0.00125625,
             'current_epoch': 1,
             'is_initial_point': True,
-            'is_best': True
+            'is_best': True,
+
         }, {
             'loss': 20.0,
             'params_dict': {

tests/exchange/test_exchange.py

@@ -673,7 +673,7 @@ def test_validate_pairs_restricted(default_conf, mocker, caplog):
     api_mock = MagicMock()
     type(api_mock).load_markets = MagicMock(return_value={
         'ETH/BTC': {'quote': 'BTC'}, 'LTC/BTC': {'quote': 'BTC'},
-        'XRP/BTC': {'quote': 'BTC', 'info': {'IsRestricted': True}},
+        'XRP/BTC': {'quote': 'BTC', 'info': {'prohibitedIn': ['US']}},
         'NEO/BTC': {'quote': 'BTC', 'info': 'TestString'},  # info can also be a string ...
     })
     mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
@@ -1783,14 +1783,14 @@ def test_get_buy_rate(mocker, default_conf, caplog, side, ask, bid,
     mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
                  return_value={'ask': ask, 'last': last, 'bid': bid})
 
-    assert exchange.get_buy_rate('ETH/BTC', True) == expected
+    assert exchange.get_rate('ETH/BTC', refresh=True, side="buy") == expected
     assert not log_has("Using cached buy rate for ETH/BTC.", caplog)
 
-    assert exchange.get_buy_rate('ETH/BTC', False) == expected
+    assert exchange.get_rate('ETH/BTC', refresh=False, side="buy") == expected
     assert log_has("Using cached buy rate for ETH/BTC.", caplog)
     # Running a 2nd time with Refresh on!
     caplog.clear()
-    assert exchange.get_buy_rate('ETH/BTC', True) == expected
+    assert exchange.get_rate('ETH/BTC', refresh=True, side="buy") == expected
     assert not log_has("Using cached buy rate for ETH/BTC.", caplog)
 
 
@@ -1825,12 +1825,12 @@ def test_get_sell_rate(default_conf, mocker, caplog, side, bid, ask,
 
     # Test regular mode
     exchange = get_patched_exchange(mocker, default_conf)
-    rate = exchange.get_sell_rate(pair, True)
+    rate = exchange.get_rate(pair, refresh=True, side="sell")
     assert not log_has("Using cached sell rate for ETH/BTC.", caplog)
     assert isinstance(rate, float)
     assert rate == expected
     # Use caching
-    rate = exchange.get_sell_rate(pair, False)
+    rate = exchange.get_rate(pair, refresh=False, side="sell")
     assert rate == expected
     assert log_has("Using cached sell rate for ETH/BTC.", caplog)
 
@@ -1844,16 +1844,15 @@ def test_get_sell_rate_orderbook(default_conf, mocker, caplog, side, expected, o
     # Test orderbook mode
     default_conf['ask_strategy']['price_side'] = side
     default_conf['ask_strategy']['use_order_book'] = True
-    default_conf['ask_strategy']['order_book_min'] = 1
-    default_conf['ask_strategy']['order_book_max'] = 2
+    default_conf['ask_strategy']['order_book_top'] = 1
     pair = "ETH/BTC"
     mocker.patch('freqtrade.exchange.Exchange.fetch_l2_order_book', order_book_l2)
     exchange = get_patched_exchange(mocker, default_conf)
-    rate = exchange.get_sell_rate(pair, True)
+    rate = exchange.get_rate(pair, refresh=True, side="sell")
     assert not log_has("Using cached sell rate for ETH/BTC.", caplog)
     assert isinstance(rate, float)
     assert rate == expected
-    rate = exchange.get_sell_rate(pair, False)
+    rate = exchange.get_rate(pair, refresh=False, side="sell")
     assert rate == expected
     assert log_has("Using cached sell rate for ETH/BTC.", caplog)
 
@@ -1862,16 +1861,16 @@ def test_get_sell_rate_orderbook_exception(default_conf, mocker, caplog):
     # Test orderbook mode
     default_conf['ask_strategy']['price_side'] = 'ask'
     default_conf['ask_strategy']['use_order_book'] = True
-    default_conf['ask_strategy']['order_book_min'] = 1
-    default_conf['ask_strategy']['order_book_max'] = 2
+    default_conf['ask_strategy']['order_book_top'] = 1
     pair = "ETH/BTC"
     # Test What happens if the exchange returns an empty orderbook.
     mocker.patch('freqtrade.exchange.Exchange.fetch_l2_order_book',
                  return_value={'bids': [[]], 'asks': [[]]})
     exchange = get_patched_exchange(mocker, default_conf)
     with pytest.raises(PricingError):
-        exchange.get_sell_rate(pair, True)
-    assert log_has("Sell Price at location from orderbook could not be determined.", caplog)
+        exchange.get_rate(pair, refresh=True, side="sell")
+    assert log_has_re(r"Sell Price at location 1 from orderbook could not be determined\..*",
+                      caplog)
 
 
 def test_get_sell_rate_exception(default_conf, mocker, caplog):
@@ -1882,18 +1881,18 @@ def test_get_sell_rate_exception(default_conf, mocker, caplog):
                  return_value={'ask': None, 'bid': 0.12, 'last': None})
     exchange = get_patched_exchange(mocker, default_conf)
     with pytest.raises(PricingError, match=r"Sell-Rate for ETH/BTC was empty."):
-        exchange.get_sell_rate(pair, True)
+        exchange.get_rate(pair, refresh=True, side="sell")
 
     exchange._config['ask_strategy']['price_side'] = 'bid'
-    assert exchange.get_sell_rate(pair, True) == 0.12
+    assert exchange.get_rate(pair, refresh=True, side="sell") == 0.12
     # Reverse sides
     mocker.patch('freqtrade.exchange.Exchange.fetch_ticker',
                  return_value={'ask': 0.13, 'bid': None, 'last': None})
     with pytest.raises(PricingError, match=r"Sell-Rate for ETH/BTC was empty."):
-        exchange.get_sell_rate(pair, True)
+        exchange.get_rate(pair, refresh=True, side="sell")
 
     exchange._config['ask_strategy']['price_side'] = 'ask'
-    assert exchange.get_sell_rate(pair, True) == 0.13
+    assert exchange.get_rate(pair, refresh=True, side="sell") == 0.13
 
 
 def make_fetch_ohlcv_mock(data):
@@ -2204,7 +2203,7 @@ def test_cancel_order_dry_run(default_conf, mocker, exchange_name):
     ({'status': 'canceled', 'filled': 10.0}, False),
     ({'status': 'unknown', 'filled': 10.0}, False),
     ({'result': 'testest123'}, False),
-    ])
+])
 def test_check_order_canceled_empty(mocker, default_conf, exchange_name, order, result):
     exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
     assert exchange.check_order_canceled_empty(order) == result

tests/optimize/__init__.py

@@ -34,6 +34,7 @@ class BTContainer(NamedTuple):
     trailing_stop_positive: Optional[float] = None
     trailing_stop_positive_offset: float = 0.0
     use_sell_signal: bool = False
+    use_custom_stoploss: bool = False
 
 
 def _get_frame_time_from_offset(offset):

tests/optimize/test_backtest_detail.py

@@ -501,6 +501,21 @@ tc31 = BTContainer(data=[
     trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=1)]
 )
 
+# Test 32: trailing_stop should be triggered immediately on trade open candle.
+# stop-loss: 1%, ROI: 10% (should not apply)
+tc32 = BTContainer(data=[
+    # D   O     H     L     C    V    B  S
+    [0, 5000, 5050, 4950, 5000, 6172, 1, 0],
+    [1, 5000, 5500, 5000, 4900, 6172, 0, 0],    # enter trade (signal on last candle) and stop
+    [2, 4900, 5250, 4500, 5100, 6172, 0, 0],
+    [3, 5100, 5100, 4650, 4750, 6172, 0, 0],
+    [4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
+    stop_loss=-0.01, roi={"0": 0.10}, profit_perc=-0.01, trailing_stop=True,
+    trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.02,
+    trailing_stop_positive=0.01, use_custom_stoploss=True,
+    trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=1)]
+)
+
 TESTS = [
     tc0,
     tc1,
@@ -534,6 +549,7 @@ TESTS = [
     tc29,
     tc30,
     tc31,
+    tc32,
 ]
 
 
@@ -551,7 +567,7 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
     if data.trailing_stop_positive is not None:
         default_conf["trailing_stop_positive"] = data.trailing_stop_positive
     default_conf["trailing_stop_positive_offset"] = data.trailing_stop_positive_offset
-    default_conf["ask_strategy"] = {"use_sell_signal": data.use_sell_signal}
+    default_conf["use_sell_signal"] = data.use_sell_signal
 
     mocker.patch("freqtrade.exchange.Exchange.get_fee", return_value=0.0)
     mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
@@ -561,6 +577,7 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
     backtesting._set_strategy(backtesting.strategylist[0])
     backtesting.strategy.advise_buy = lambda a, m: frame
     backtesting.strategy.advise_sell = lambda a, m: frame
+    backtesting.strategy.use_custom_stoploss = data.use_custom_stoploss
     caplog.set_level(logging.DEBUG)
 
     pair = "UNITTEST/BTC"

tests/optimize/test_backtesting.py

@@ -346,6 +346,20 @@ def test_data_to_dataframe_bt(default_conf, mocker, testdatadir) -> None:
     assert processed['UNITTEST/BTC'].equals(processed2['UNITTEST/BTC'])
 
 
+def test_backtest_abort(default_conf, mocker, testdatadir) -> None:
+    patch_exchange(mocker)
+    backtesting = Backtesting(default_conf)
+    backtesting.check_abort()
+
+    backtesting.abort = True
+
+    with pytest.raises(DependencyException, match="Stop requested"):
+        backtesting.check_abort()
+    # abort flag resets
+    assert backtesting.abort is False
+    assert backtesting.progress.progress == 0
+
+
 def test_backtesting_start(default_conf, mocker, testdatadir, caplog) -> None:
     def get_timerange(input1):
         return Arrow(2017, 11, 14, 21, 17), Arrow(2017, 11, 14, 22, 59)
@@ -465,7 +479,7 @@ def test_backtesting_pairlist_list(default_conf, mocker, caplog, testdatadir, ti
 
 
 def test_backtest__enter_trade(default_conf, fee, mocker) -> None:
-    default_conf['ask_strategy']['use_sell_signal'] = False
+    default_conf['use_sell_signal'] = False
     mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
     mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
     patch_exchange(mocker)
@@ -496,6 +510,17 @@ def test_backtest__enter_trade(default_conf, fee, mocker) -> None:
     trade = backtesting._enter_trade(pair, row=row)
     assert trade is not None
 
+    backtesting.strategy.custom_stake_amount = lambda **kwargs: 123.5
+    trade = backtesting._enter_trade(pair, row=row)
+    assert trade
+    assert trade.stake_amount == 123.5
+
+    # In case of error - use proposed stake
+    backtesting.strategy.custom_stake_amount = lambda **kwargs: 20 / 0
+    trade = backtesting._enter_trade(pair, row=row)
+    assert trade
+    assert trade.stake_amount == 495
+
     # Stake-amount too high!
     mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=600.0)
 
@@ -511,7 +536,7 @@ def test_backtest__enter_trade(default_conf, fee, mocker) -> None:
 
 
 def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None:
-    default_conf['ask_strategy']['use_sell_signal'] = False
+    default_conf['use_sell_signal'] = False
     mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
     mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
     patch_exchange(mocker)
@@ -574,7 +599,7 @@ def test_backtest_one(default_conf, fee, mocker, testdatadir) -> None:
 
 
 def test_backtest_1min_timeframe(default_conf, fee, mocker, testdatadir) -> None:
-    default_conf['ask_strategy']['use_sell_signal'] = False
+    default_conf['use_sell_signal'] = False
     mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
     mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
     patch_exchange(mocker)
@@ -819,7 +844,7 @@ def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir):
 @pytest.mark.filterwarnings("ignore:deprecated")
 def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
 
-    default_conf['ask_strategy'].update({
+    default_conf.update({
         "use_sell_signal": True,
         "sell_profit_only": False,
         "sell_profit_offset": 0.0,
@@ -894,7 +919,7 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
 
 @pytest.mark.filterwarnings("ignore:deprecated")
 def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdatadir, capsys):
-    default_conf['ask_strategy'].update({
+    default_conf.update({
         "use_sell_signal": True,
         "sell_profit_only": False,
         "sell_profit_offset": 0.0,
@@ -993,4 +1018,5 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat
     assert 'BACKTESTING REPORT' in captured.out
     assert 'SELL REASON STATS' in captured.out
     assert 'LEFT OPEN TRADES REPORT' in captured.out
+    assert '2017-11-14 21:17:00 -> 2017-11-14 22:58:00 | Max open trades : 1' in captured.out
     assert 'STRATEGY SUMMARY' in captured.out

tests/optimize/test_hyperopt.py

@@ -1,9 +1,6 @@
 # pragma pylint: disable=missing-docstring,W0212,C0103
-import logging
-import re
 from datetime import datetime
 from pathlib import Path
-from typing import Dict, List
 from unittest.mock import ANY, MagicMock
 
 import pandas as pd
@@ -28,12 +25,6 @@ from tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
 from .hyperopts.default_hyperopt import DefaultHyperOpt
 
 
-# Functions for recurrent object patching
-def create_results() -> List[Dict]:
-
-    return [{'loss': 1, 'result': 'foo', 'params': {}, 'is_best': True}]
-
-
 def test_setup_hyperopt_configuration_without_arguments(mocker, default_conf, caplog) -> None:
     patched_configuration_load_config_file(mocker, default_conf)
 
@@ -303,52 +294,6 @@ def test_no_log_if_loss_does_not_improve(hyperopt, caplog) -> None:
     assert caplog.record_tuples == []
 
 
-def test_save_results_saves_epochs(mocker, hyperopt, tmpdir, caplog) -> None:
-    # Test writing to temp dir and reading again
-    epochs = create_results()
-    hyperopt.results_file = Path(tmpdir / 'ut_results.fthypt')
-
-    caplog.set_level(logging.DEBUG)
-
-    for epoch in epochs:
-        hyperopt._save_result(epoch)
-    assert log_has(f"1 epoch saved to '{hyperopt.results_file}'.", caplog)
-
-    hyperopt._save_result(epochs[0])
-    assert log_has(f"2 epochs saved to '{hyperopt.results_file}'.", caplog)
-
-    hyperopt_epochs = HyperoptTools.load_previous_results(hyperopt.results_file)
-    assert len(hyperopt_epochs) == 2
-
-
-def test_load_previous_results(testdatadir, caplog) -> None:
-
-    results_file = testdatadir / 'hyperopt_results_SampleStrategy.pickle'
-
-    hyperopt_epochs = HyperoptTools.load_previous_results(results_file)
-
-    assert len(hyperopt_epochs) == 5
-    assert log_has_re(r"Reading pickled epochs from .*", caplog)
-
-    caplog.clear()
-
-    # Modern version
-    results_file = testdatadir / 'strategy_SampleStrategy.fthypt'
-
-    hyperopt_epochs = HyperoptTools.load_previous_results(results_file)
-
-    assert len(hyperopt_epochs) == 5
-    assert log_has_re(r"Reading epochs from .*", caplog)
-
-
-def test_load_previous_results2(mocker, testdatadir, caplog) -> None:
-    mocker.patch('freqtrade.optimize.hyperopt_tools.HyperoptTools._read_results_pickle',
-                 return_value=[{'asdf': '222'}])
-    results_file = testdatadir / 'hyperopt_results_SampleStrategy.pickle'
-    with pytest.raises(OperationalException, match=r"The file .* incompatible.*"):
-        HyperoptTools.load_previous_results(results_file)
-
-
 def test_roi_table_generation(hyperopt) -> None:
     params = {
         'roi_t1': 5,
@@ -362,6 +307,18 @@ def test_roi_table_generation(hyperopt) -> None:
     assert hyperopt.custom_hyperopt.generate_roi_table(params) == {0: 6, 15: 3, 25: 1, 30: 0}
 
 
+def test_params_no_optimize_details(hyperopt) -> None:
+    hyperopt.config['spaces'] = ['buy']
+    res = hyperopt._get_no_optimize_details()
+    assert isinstance(res, dict)
+    assert "trailing" in res
+    assert res["trailing"]['trailing_stop'] is False
+    assert "roi" in res
+    assert res['roi']['0'] == 0.04
+    assert "stoploss" in res
+    assert res['stoploss']['stoploss'] == -0.1
+
+
 def test_start_calls_optimizer(mocker, hyperopt_conf, capsys) -> None:
     dumper = mocker.patch('freqtrade.optimize.hyperopt.dump')
     dumper2 = mocker.patch('freqtrade.optimize.hyperopt.Hyperopt._save_result')
@@ -467,40 +424,6 @@ def test_hyperopt_format_results(hyperopt):
     assert '0:50:00 min' in result
 
 
-@pytest.mark.parametrize("spaces, expected_results", [
-    (['buy'],
-     {'buy': True, 'sell': False, 'roi': False, 'stoploss': False, 'trailing': False}),
-    (['sell'],
-     {'buy': False, 'sell': True, 'roi': False, 'stoploss': False, 'trailing': False}),
-    (['roi'],
-     {'buy': False, 'sell': False, 'roi': True, 'stoploss': False, 'trailing': False}),
-    (['stoploss'],
-     {'buy': False, 'sell': False, 'roi': False, 'stoploss': True, 'trailing': False}),
-    (['trailing'],
-     {'buy': False, 'sell': False, 'roi': False, 'stoploss': False, 'trailing': True}),
-    (['buy', 'sell', 'roi', 'stoploss'],
-     {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': False}),
-    (['buy', 'sell', 'roi', 'stoploss', 'trailing'],
-     {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}),
-    (['buy', 'roi'],
-     {'buy': True, 'sell': False, 'roi': True, 'stoploss': False, 'trailing': False}),
-    (['all'],
-     {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}),
-    (['default'],
-     {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': False}),
-    (['default', 'trailing'],
-     {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}),
-    (['all', 'buy'],
-     {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}),
-    (['default', 'buy'],
-     {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': False}),
-])
-def test_has_space(hyperopt_conf, spaces, expected_results):
-    for s in ['buy', 'sell', 'roi', 'stoploss', 'trailing']:
-        hyperopt_conf.update({'spaces': spaces})
-        assert HyperoptTools.has_space(hyperopt_conf, s) == expected_results[s]
-
-
 def test_populate_indicators(hyperopt, testdatadir) -> None:
     data = load_data(testdatadir, '1m', ['UNITTEST/BTC'], fill_up_missing=True)
     dataframes = hyperopt.backtesting.strategy.ohlcvdata_to_dataframe(data)
@@ -686,6 +609,8 @@ def test_generate_optimizer(mocker, hyperopt_conf) -> None:
 def test_clean_hyperopt(mocker, hyperopt_conf, caplog):
     patch_exchange(mocker)
 
+    mocker.patch("freqtrade.strategy.hyper.HyperStrategyMixin.load_params_from_file",
+                 MagicMock(return_value={}))
     mocker.patch("freqtrade.optimize.hyperopt.Path.is_file", MagicMock(return_value=True))
     unlinkmock = mocker.patch("freqtrade.optimize.hyperopt.Path.unlink", MagicMock())
     h = Hyperopt(hyperopt_conf)
@@ -1068,42 +993,6 @@ def test_simplified_interface_failed(mocker, hyperopt_conf, method, space) -> No
         hyperopt.start()
 
 
-def test_show_epoch_details(capsys):
-    test_result = {
-        'params_details': {
-            'trailing': {
-                'trailing_stop': True,
-                'trailing_stop_positive': 0.02,
-                'trailing_stop_positive_offset': 0.04,
-                'trailing_only_offset_is_reached': True
-            },
-            'roi': {
-                0: 0.18,
-                90: 0.14,
-                225: 0.05,
-                430: 0},
-        },
-        'results_explanation': 'foo result',
-        'is_initial_point': False,
-        'total_profit': 0,
-        'current_epoch': 2,  # This starts from 1 (in a human-friendly manner)
-        'is_best': True
-    }
-
-    HyperoptTools.show_epoch_details(test_result, 5, False, no_header=True)
-    captured = capsys.readouterr()
-    assert '# Trailing stop:' in captured.out
-    # re.match(r"Pairs for .*", captured.out)
-    assert re.search(r'^\s+trailing_stop = True$', captured.out, re.MULTILINE)
-    assert re.search(r'^\s+trailing_stop_positive = 0.02$', captured.out, re.MULTILINE)
-    assert re.search(r'^\s+trailing_stop_positive_offset = 0.04$', captured.out, re.MULTILINE)
-    assert re.search(r'^\s+trailing_only_offset_is_reached = True$', captured.out, re.MULTILINE)
-
-    assert '# ROI table:' in captured.out
-    assert re.search(r'^\s+minimal_roi = \{$', captured.out, re.MULTILINE)
-    assert re.search(r'^\s+\"90\"\:\s0.14,\s*$', captured.out, re.MULTILINE)
-
-
 def test_in_strategy_auto_hyperopt(mocker, hyperopt_conf, tmpdir, fee) -> None:
     patch_exchange(mocker)
     mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
@@ -1143,17 +1032,3 @@ def test_SKDecimal():
     assert space.transform([2.0]) == [200]
     assert space.transform([1.0]) == [100]
     assert space.transform([1.5, 1.6]) == [150, 160]
-
-
-def test___pprint():
-    params = {'buy_std': 1.2, 'buy_rsi': 31, 'buy_enable': True, 'buy_what': 'asdf'}
-    non_params = {'buy_notoptimied': 55}
-
-    x = HyperoptTools._pprint(params, non_params)
-    assert x == """{
-    "buy_std": 1.2,
-    "buy_rsi": 31,
-    "buy_enable": True,
-    "buy_what": "asdf",
-    "buy_notoptimied": 55,  # value loaded from strategy
-}"""

tests/optimize/test_hyperopt_tools.py

@@ -0,0 +1,317 @@
+import logging
+import re
+from pathlib import Path
+from typing import Dict, List
+
+import numpy as np
+import pytest
+import rapidjson
+
+from freqtrade.constants import FTHYPT_FILEVERSION
+from freqtrade.exceptions import OperationalException
+from freqtrade.optimize.hyperopt_tools import HyperoptTools, hyperopt_serializer
+from tests.conftest import log_has, log_has_re
+
+
+# Functions for recurrent object patching
+def create_results() -> List[Dict]:
+
+    return [{'loss': 1, 'result': 'foo', 'params': {}, 'is_best': True}]
+
+
+def test_save_results_saves_epochs(hyperopt, tmpdir, caplog) -> None:
+    # Test writing to temp dir and reading again
+    epochs = create_results()
+    hyperopt.results_file = Path(tmpdir / 'ut_results.fthypt')
+
+    caplog.set_level(logging.DEBUG)
+
+    for epoch in epochs:
+        hyperopt._save_result(epoch)
+    assert log_has(f"1 epoch saved to '{hyperopt.results_file}'.", caplog)
+
+    hyperopt._save_result(epochs[0])
+    assert log_has(f"2 epochs saved to '{hyperopt.results_file}'.", caplog)
+
+    hyperopt_epochs = HyperoptTools.load_previous_results(hyperopt.results_file)
+    assert len(hyperopt_epochs) == 2
+
+
+def test_load_previous_results(testdatadir, caplog) -> None:
+
+    results_file = testdatadir / 'hyperopt_results_SampleStrategy.pickle'
+
+    hyperopt_epochs = HyperoptTools.load_previous_results(results_file)
+
+    assert len(hyperopt_epochs) == 5
+    assert log_has_re(r"Reading pickled epochs from .*", caplog)
+
+    caplog.clear()
+
+    # Modern version
+    results_file = testdatadir / 'strategy_SampleStrategy.fthypt'
+
+    hyperopt_epochs = HyperoptTools.load_previous_results(results_file)
+
+    assert len(hyperopt_epochs) == 5
+    assert log_has_re(r"Reading epochs from .*", caplog)
+
+
+def test_load_previous_results2(mocker, testdatadir, caplog) -> None:
+    mocker.patch('freqtrade.optimize.hyperopt_tools.HyperoptTools._read_results_pickle',
+                 return_value=[{'asdf': '222'}])
+    results_file = testdatadir / 'hyperopt_results_SampleStrategy.pickle'
+    with pytest.raises(OperationalException, match=r"The file .* incompatible.*"):
+        HyperoptTools.load_previous_results(results_file)
+
+
+@pytest.mark.parametrize("spaces, expected_results", [
+    (['buy'],
+     {'buy': True, 'sell': False, 'roi': False, 'stoploss': False, 'trailing': False}),
+    (['sell'],
+     {'buy': False, 'sell': True, 'roi': False, 'stoploss': False, 'trailing': False}),
+    (['roi'],
+     {'buy': False, 'sell': False, 'roi': True, 'stoploss': False, 'trailing': False}),
+    (['stoploss'],
+     {'buy': False, 'sell': False, 'roi': False, 'stoploss': True, 'trailing': False}),
+    (['trailing'],
+     {'buy': False, 'sell': False, 'roi': False, 'stoploss': False, 'trailing': True}),
+    (['buy', 'sell', 'roi', 'stoploss'],
+     {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': False}),
+    (['buy', 'sell', 'roi', 'stoploss', 'trailing'],
+     {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}),
+    (['buy', 'roi'],
+     {'buy': True, 'sell': False, 'roi': True, 'stoploss': False, 'trailing': False}),
+    (['all'],
+     {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}),
+    (['default'],
+     {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': False}),
+    (['default', 'trailing'],
+     {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}),
+    (['all', 'buy'],
+     {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': True}),
+    (['default', 'buy'],
+     {'buy': True, 'sell': True, 'roi': True, 'stoploss': True, 'trailing': False}),
+])
+def test_has_space(hyperopt_conf, spaces, expected_results):
+    for s in ['buy', 'sell', 'roi', 'stoploss', 'trailing']:
+        hyperopt_conf.update({'spaces': spaces})
+        assert HyperoptTools.has_space(hyperopt_conf, s) == expected_results[s]
+
+
+def test_show_epoch_details(capsys):
+    test_result = {
+        'params_details': {
+            'trailing': {
+                'trailing_stop': True,
+                'trailing_stop_positive': 0.02,
+                'trailing_stop_positive_offset': 0.04,
+                'trailing_only_offset_is_reached': True
+            },
+            'roi': {
+                0: 0.18,
+                90: 0.14,
+                225: 0.05,
+                430: 0},
+        },
+        'results_explanation': 'foo result',
+        'is_initial_point': False,
+        'total_profit': 0,
+        'current_epoch': 2,  # This starts from 1 (in a human-friendly manner)
+        'is_best': True
+    }
+
+    HyperoptTools.show_epoch_details(test_result, 5, False, no_header=True)
+    captured = capsys.readouterr()
+    assert '# Trailing stop:' in captured.out
+    # re.match(r"Pairs for .*", captured.out)
+    assert re.search(r'^\s+trailing_stop = True$', captured.out, re.MULTILINE)
+    assert re.search(r'^\s+trailing_stop_positive = 0.02$', captured.out, re.MULTILINE)
+    assert re.search(r'^\s+trailing_stop_positive_offset = 0.04$', captured.out, re.MULTILINE)
+    assert re.search(r'^\s+trailing_only_offset_is_reached = True$', captured.out, re.MULTILINE)
+
+    assert '# ROI table:' in captured.out
+    assert re.search(r'^\s+minimal_roi = \{$', captured.out, re.MULTILINE)
+    assert re.search(r'^\s+\"90\"\:\s0.14,\s*$', captured.out, re.MULTILINE)
+
+
+def test__pprint_dict():
+    params = {'buy_std': 1.2, 'buy_rsi': 31, 'buy_enable': True, 'buy_what': 'asdf'}
+    non_params = {'buy_notoptimied': 55}
+
+    x = HyperoptTools._pprint_dict(params, non_params)
+    assert x == """{
+    "buy_std": 1.2,
+    "buy_rsi": 31,
+    "buy_enable": True,
+    "buy_what": "asdf",
+    "buy_notoptimied": 55,  # value loaded from strategy
+}"""
+
+
+def test_get_strategy_filename(default_conf):
+
+    x = HyperoptTools.get_strategy_filename(default_conf, 'DefaultStrategy')
+    assert isinstance(x, Path)
+    assert x == Path(__file__).parents[1] / 'strategy/strats/default_strategy.py'
+
+    x = HyperoptTools.get_strategy_filename(default_conf, 'NonExistingStrategy')
+    assert x is None
+
+
+def test_export_params(tmpdir):
+
+    filename = Path(tmpdir) / "DefaultStrategy.json"
+    assert not filename.is_file()
+    params = {
+        "params_details": {
+            "buy": {
+                "buy_rsi": 30
+            },
+            "sell": {
+                "sell_rsi": 70
+            },
+            "roi": {
+                "0": 0.528,
+                "346": 0.08499,
+                "507": 0.049,
+                "1595": 0
+            }
+        },
+        "params_not_optimized": {
+            "stoploss": -0.05,
+            "trailing": {
+                "trailing_stop": False,
+                "trailing_stop_positive": 0.05,
+                "trailing_stop_positive_offset": 0.1,
+                "trailing_only_offset_is_reached": True
+            },
+        }
+
+    }
+    HyperoptTools.export_params(params, "DefaultStrategy", filename)
+
+    assert filename.is_file()
+
+    content = rapidjson.load(filename.open('r'))
+    assert content['strategy_name'] == 'DefaultStrategy'
+    assert 'params' in content
+    assert "buy" in content["params"]
+    assert "sell" in content["params"]
+    assert "roi" in content["params"]
+    assert "stoploss" in content["params"]
+    assert "trailing" in content["params"]
+
+
+def test_try_export_params(default_conf, tmpdir, caplog, mocker):
+    default_conf['disableparamexport'] = False
+    export_mock = mocker.patch("freqtrade.optimize.hyperopt_tools.HyperoptTools.export_params")
+
+    filename = Path(tmpdir) / "DefaultStrategy.json"
+    assert not filename.is_file()
+    params = {
+        "params_details": {
+            "buy": {
+                "buy_rsi": 30
+            },
+            "sell": {
+                "sell_rsi": 70
+            },
+            "roi": {
+                "0": 0.528,
+                "346": 0.08499,
+                "507": 0.049,
+                "1595": 0
+            }
+        },
+        "params_not_optimized": {
+            "stoploss": -0.05,
+            "trailing": {
+                "trailing_stop": False,
+                "trailing_stop_positive": 0.05,
+                "trailing_stop_positive_offset": 0.1,
+                "trailing_only_offset_is_reached": True
+            },
+        },
+        FTHYPT_FILEVERSION: 2,
+
+    }
+    HyperoptTools.try_export_params(default_conf, "DefaultStrategy22", params)
+
+    assert log_has("Strategy not found, not exporting parameter file.", caplog)
+    assert export_mock.call_count == 0
+    caplog.clear()
+
+    HyperoptTools.try_export_params(default_conf, "DefaultStrategy", params)
+
+    assert export_mock.call_count == 1
+    assert export_mock.call_args_list[0][0][1] == 'DefaultStrategy'
+    assert export_mock.call_args_list[0][0][2].name == 'default_strategy.json'
+
+
+def test_params_print(capsys):
+
+    params = {
+        "buy": {
+            "buy_rsi": 30
+        },
+        "sell": {
+            "sell_rsi": 70
+        },
+    }
+    non_optimized = {
+        "buy": {
+            "buy_adx": 44
+        },
+        "sell": {
+            "sell_adx": 65
+        },
+        "stoploss": {
+            "stoploss": -0.05,
+        },
+        "roi": {
+            "0": 0.05,
+            "20": 0.01,
+        },
+        "trailing": {
+            "trailing_stop": False,
+            "trailing_stop_positive": 0.05,
+            "trailing_stop_positive_offset": 0.1,
+            "trailing_only_offset_is_reached": True
+        },
+
+    }
+    HyperoptTools._params_pretty_print(params, 'buy', 'No header', non_optimized)
+
+    captured = capsys.readouterr()
+    assert re.search("# No header", captured.out)
+    assert re.search('"buy_rsi": 30,\n', captured.out)
+    assert re.search('"buy_adx": 44,  # value loaded.*\n', captured.out)
+    assert not re.search("sell", captured.out)
+
+    HyperoptTools._params_pretty_print(params, 'sell', 'Sell Header', non_optimized)
+    captured = capsys.readouterr()
+    assert re.search("# Sell Header", captured.out)
+    assert re.search('"sell_rsi": 70,\n', captured.out)
+    assert re.search('"sell_adx": 65,  # value loaded.*\n', captured.out)
+
+    HyperoptTools._params_pretty_print(params, 'roi', 'ROI Table:', non_optimized)
+    captured = capsys.readouterr()
+    assert re.search("# ROI Table:  # value loaded.*\n", captured.out)
+    assert re.search('minimal_roi = {\n', captured.out)
+    assert re.search('"20": 0.01\n', captured.out)
+
+    HyperoptTools._params_pretty_print(params, 'trailing', 'Trailing stop:', non_optimized)
+    captured = capsys.readouterr()
+    assert re.search("# Trailing stop:", captured.out)
+    assert re.search('trailing_stop = False  # value loaded.*\n', captured.out)
+    assert re.search('trailing_stop_positive = 0.05  # value loaded.*\n', captured.out)
+    assert re.search('trailing_stop_positive_offset = 0.1  # value loaded.*\n', captured.out)
+    assert re.search('trailing_only_offset_is_reached = True  # value loaded.*\n', captured.out)
+
+
+def test_hyperopt_serializer():
+
+    assert isinstance(hyperopt_serializer(np.int_(5)), int)
+    assert isinstance(hyperopt_serializer(np.bool_(True)), bool)
+    assert isinstance(hyperopt_serializer(np.bool_(False)), bool)