lychiyu/freqtrade_origin
1
0
Fork 0
mirror of https://github.com/freqtrade/freqtrade.git synced 2024-09-20 01:21:11 +00:00
Code Issues Actions 1 Packages Projects Releases Wiki Activity

Merge branch 'develop' into feat/new_args_system

Browse Source
This commit is contained in:
Matthias 2019-10-20 19:32:34 +02:00
commit f3cfe147b5
100 changed files with 2632 additions and 1112 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
CONTRIBUTING.md
View File

@ -114,6 +114,6 @@ Contributors may be given commit privileges. Preference will be given to those w
1. Access to resources for cross-platform development and testing.
1. Time to devote to the project regularly.
Beeing a Committer does not grant write permission on `develop` or `master` for security reasons (Users trust FreqTrade with their Exchange API keys).
Being a Committer does not grant write permission on `develop` or `master` for security reasons (Users trust FreqTrade with their Exchange API keys).
After beeing Committer for some time, a Committer may be named Core Committer and given full repository access.
After being Committer for some time, a Committer may be named Core Committer and given full repository access.

6
Dockerfile
View File

@ -1,4 +1,4 @@
FROM python:3.7.4-slim-stretch
FROM python:3.7.5-slim-stretch
RUN apt-get update \
&& apt-get -y install curl build-essential libssl-dev \
@ -16,9 +16,9 @@ RUN cd /tmp && /tmp/install_ta-lib.sh && rm -r /tmp/*ta-lib*
ENV LD_LIBRARY_PATH /usr/local/lib
# Install dependencies
COPY requirements.txt requirements-common.txt /freqtrade/
COPY requirements.txt requirements-common.txt requirements-hyperopt.txt /freqtrade/
RUN pip install numpy --no-cache-dir \
&& pip install -r requirements.txt --no-cache-dir
&& pip install -r requirements-hyperopt.txt --no-cache-dir
# Install and execute
COPY . /freqtrade/

10
config.json.example
View File

@ -22,7 +22,10 @@
"ask_strategy":{
"use_order_book": false,
"order_book_min": 1,
"order_book_max": 9
"order_book_max": 9,
"use_sell_signal": true,
"sell_profit_only": false,
"ignore_roi_if_buy_signal": false
},
"exchange": {
"name": "bittrex",
@ -49,11 +52,6 @@
"DOGE/BTC"
]
},
"experimental": {
"use_sell_signal": false,
"sell_profit_only": false,
"ignore_roi_if_buy_signal": false
},
"edge": {
"enabled": false,
"process_throttle_secs": 3600,

10
config_binance.json.example
View File

@ -22,7 +22,10 @@
"ask_strategy":{
"use_order_book": false,
"order_book_min": 1,
"order_book_max": 9
"order_book_max": 9,
"use_sell_signal": true,
"sell_profit_only": false,
"ignore_roi_if_buy_signal": false
},
"exchange": {
"name": "binance",
@ -51,11 +54,6 @@
"BNB/BTC"
]
},
"experimental": {
"use_sell_signal": false,
"sell_profit_only": false,
"ignore_roi_if_buy_signal": false
},
"edge": {
"enabled": false,
"process_throttle_secs": 3600,

10
config_full.json.example
View File

@ -33,7 +33,10 @@
"ask_strategy":{
"use_order_book": false,
"order_book_min": 1,
"order_book_max": 9
"order_book_max": 9,
"use_sell_signal": true,
"sell_profit_only": false,
"ignore_roi_if_buy_signal": false
},
"order_types": {
"buy": "limit",
@ -100,11 +103,6 @@
"max_trade_duration_minute": 1440,
"remove_pumps": false
},
"experimental": {
"use_sell_signal": false,
"sell_profit_only": false,
"ignore_roi_if_buy_signal": false
},
"telegram": {
"enabled": true,
"token": "your_telegram_token",

9
config_kraken.json.example
View File

@ -22,7 +22,11 @@
"ask_strategy":{
"use_order_book": false,
"order_book_min": 1,
"order_book_max": 9
"order_book_max": 9,
"use_sell_signal": true,
"sell_profit_only": false,
"ignore_roi_if_buy_signal": false
},
"exchange": {
"name": "kraken",
@ -66,5 +70,6 @@
"forcebuy_enable": false,
"internals": {
"process_throttle_secs": 5
}
},
"download_trades": true
}

20
docker-compose.develop.yml Normal file
View File

@ -0,0 +1,20 @@
---
version: '3'
services:
freqtrade_develop:
build:
context: .
dockerfile: "./Dockerfile.develop"
volumes:
- ".:/freqtrade"
entrypoint:
- "freqtrade"
freqtrade_bash:
build:
context: .
dockerfile: "./Dockerfile.develop"
volumes:
- ".:/freqtrade"
entrypoint:
- "/bin/bash"

8
docker-compose.yml Normal file
View File

@ -0,0 +1,8 @@
---
version: '3'
services:
freqtrade:
image: freqtradeorg/freqtrade:master
volumes:
- "./user_data:/freqtrade/user_data"
- "./config.json:/freqtrade/config.json"

23
docs/backtesting.md
View File

@ -39,7 +39,7 @@ Assume you downloaded the history data from the Bittrex exchange and kept it in
You can then use this data for backtesting as follows:
```bash
freqtrade backtesting --datadir user_data/data/bittrex-20180101
freqtrade --datadir user_data/data/bittrex-20180101 backtesting
```
#### With a (custom) strategy file
@ -72,6 +72,17 @@ The exported trades can be used for [further analysis](#further-backtest-result-
freqtrade backtesting --export trades --export-filename=backtest_samplestrategy.json
```
#### Supplying custom fee value
Sometimes your account has certain fee rebates (fee reductions starting with a certain account size or monthly volume), which are not visible to ccxt.
To account for this in backtesting, you can use `--fee 0.001` to supply this value to backtesting.
This fee must be a percentage, and will be applied twice (once for trade entry, and once for trade exit).
```bash
freqtrade backtesting --fee 0.001
```
#### Running backtest with smaller testset by using timerange
Use the `--timerange` argument to change how much of the testset you want to use.
@ -92,12 +103,6 @@ The full timerange specification:
- Use tickframes since 2018/01/31 till 2018/03/01 : `--timerange=20180131-20180301`
- Use tickframes between POSIX timestamps 1527595200 1527618600:
`--timerange=1527595200-1527618600`
- Use last 123 tickframes of data: `--timerange=-123`
- Use first 123 tickframes of data: `--timerange=123-`
- Use tickframes from line 123 through 456: `--timerange=123-456`
!!! warning
Be carefull when using non-date functions - these do not allow you to specify precise dates, so if you updated the test-data it will probably use a different dataset.
## Understand the backtesting result
@ -184,6 +189,7 @@ Hence, keep in mind that your performance is an integral mix of all different el
Since backtesting lacks some detailed information about what happens within a candle, it needs to take a few assumptions:
- Buys happen at open-price
- Sell signal sells happen at open-price of the following candle
- Low happens before high for stoploss, protecting capital first.
- ROI sells are compared to high - but the ROI value is used (e.g. ROI = 2%, high=5% - so the sell will be at 2%)
- Stoploss sells happen exactly at stoploss price, even if low was lower
@ -192,6 +198,9 @@ Since backtesting lacks some detailed information about what happens within a ca
- Low uses the adjusted stoploss (so sells with large high-low difference are backtested correctly)
- Sell-reason does not explain if a trade was positive or negative, just what triggered the sell (this can look odd if negative ROI values are used)
Taking these assumptions, backtesting tries to mirror real trading as closely as possible. However, backtesting will **never** replace running a strategy in dry-run mode.
Also, keep in mind that past results don't guarantee future success.
### Further backtest-result analysis
To further analyze your backtest results, you can [export the trades](#exporting-trades-to-file).

6
docs/bot-usage.md
View File

@ -119,7 +119,7 @@ user_data/
├── backtest_results
├── data
├── hyperopts
├── hyperopts_results
├── hyperopt_results
├── plot
└── strategies
```
@ -205,6 +205,8 @@ optional arguments:
Specify max_open_trades to use.
--stake_amount STAKE_AMOUNT
Specify stake_amount.
--fee FLOAT Specify fee ratio. Will be applied twice (on trade
entry and exit).
--eps, --enable-position-stacking
Allow buying the same pair multiple times (position
stacking).
@ -370,6 +372,8 @@ optional arguments:
Specify max_open_trades to use.
--stake_amount STAKE_AMOUNT
Specify stake_amount.
--fee FLOAT Specify fee ratio. Will be applied twice (on trade
entry and exit).
--stoplosses STOPLOSS_RANGE
Defines a range of stoploss values against which edge
will assess the strategy. The format is "min,max,step"

14
docs/configuration.md
View File

@ -59,12 +59,15 @@ Mandatory parameters are marked as **Required**, which means that they are requi
| `unfilledtimeout.sell` | 10 | **Required.** How long (in minutes) the bot will wait for an unfilled sell order to complete, after which the order will be cancelled.
| `bid_strategy.ask_last_balance` | 0.0 | **Required.** Set the bidding price. More information [below](#understand-ask_last_balance).
| `bid_strategy.use_order_book` | false | Allows buying of pair using the rates in Order Book Bids.
| `bid_strategy.order_book_top` | 0 | Bot will use the top N rate in Order Book Bids. Ie. a value of 2 will allow the bot to pick the 2nd bid rate in Order Book Bids.
| `bid_strategy.order_book_top` | 0 | Bot will use the top N rate in Order Book Bids. I.e. a value of 2 will allow the bot to pick the 2nd bid rate in Order Book Bids.
| `bid_strategy. check_depth_of_market.enabled` | false | Does not buy if the % difference of buy orders and sell orders is met in Order Book.
| `bid_strategy. check_depth_of_market.bids_to_ask_delta` | 0 | The % difference of buy orders and sell orders found in Order Book. A value lesser than 1 means sell orders is greater, while value greater than 1 means buy orders is higher.
| `ask_strategy.use_order_book` | false | Allows selling of open traded pair using the rates in Order Book Asks.
| `ask_strategy.order_book_min` | 0 | Bot will scan from the top min to max Order Book Asks searching for a profitable rate.
| `ask_strategy.order_book_max` | 0 | Bot will scan from the top min to max Order Book Asks searching for a profitable rate.
| `ask_strategy.use_sell_signal` | true | Use sell signals produced by the strategy in addition to the `minimal_roi`. [Strategy Override](#parameters-in-the-strategy).
| `ask_strategy.sell_profit_only` | false | Wait until the bot makes a positive profit before taking a sell decision. [Strategy Override](#parameters-in-the-strategy).
| `ask_strategy.ignore_roi_if_buy_signal` | false | 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).
| `order_types` | None | 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).
| `order_time_in_force` | None | Configure time in force for buy and sell orders. [More information below](#understand-order_time_in_force). [Strategy Override](#parameters-in-the-strategy).
| `exchange.name` | | **Required.** Name of the exchange class to use. [List below](#user-content-what-values-for-exchangename).
@ -78,9 +81,6 @@ Mandatory parameters are marked as **Required**, which means that they are requi
| `exchange.ccxt_async_config` | None | Additional CCXT parameters passed to the async ccxt instance. Parameters may differ from exchange to exchange and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation)
| `exchange.markets_refresh_interval` | 60 | The interval in minutes in which markets are reloaded.
| `edge` | false | Please refer to [edge configuration document](edge.md) for detailed explanation.
| `experimental.use_sell_signal` | false | Use your sell strategy in addition of the `minimal_roi`. [Strategy Override](#parameters-in-the-strategy).
| `experimental.sell_profit_only` | false | Waits until you have made a positive profit before taking a sell decision. [Strategy Override](#parameters-in-the-strategy).
| `experimental.ignore_roi_if_buy_signal` | false | Does not sell if the buy-signal is still active. Takes preference over `minimal_roi` and `use_sell_signal`. [Strategy Override](#parameters-in-the-strategy).
| `experimental.block_bad_exchanges` | true | Block exchanges known to not work with freqtrade. Leave on default unless you want to test if that exchange works now.
| `pairlist.method` | StaticPairList | Use static or dynamic volume-based pairlist. [More information below](#dynamic-pairlists).
| `pairlist.config` | None | Additional configuration for dynamic pairlists. [More information below](#dynamic-pairlists).
@ -116,9 +116,9 @@ Values set in the configuration file always overwrite values set in the strategy
* `process_only_new_candles`
* `order_types`
* `order_time_in_force`
* `use_sell_signal` (experimental)
* `sell_profit_only` (experimental)
* `ignore_roi_if_buy_signal` (experimental)
* `use_sell_signal` (ask_strategy)
* `sell_profit_only` (ask_strategy)
* `ignore_roi_if_buy_signal` (ask_strategy)
### Understand stake_amount

124
docs/data-analysis.md
View File

@ -61,34 +61,6 @@ except:
print(Path.cwd())
```
## Load existing objects into a Jupyter notebook
These examples assume that you have already generated data using the cli. They will allow you to drill deeper into your results, and perform analysis which otherwise would make the output very difficult to digest due to information overload.
### Load backtest results into a pandas dataframe
```python
from freqtrade.data.btanalysis import load_backtest_data
# Load backtest results
df = load_backtest_data("user_data/backtest_results/backtest-result.json")
# Show value-counts per pair
df.groupby("pair")["sell_reason"].value_counts()
```
### Load live trading results into a pandas dataframe
``` python
from freqtrade.data.btanalysis import load_trades_from_db
# Fetch trades from database
df = load_trades_from_db("sqlite:///tradesv3.sqlite")
# Display results
df.groupby("pair")["sell_reason"].value_counts()
```
### Load multiple configuration files
This option can be useful to inspect the results of passing in multiple configs.
@ -114,99 +86,9 @@ Best avoid relative paths, since this starts at the storage location of the jupy
}
```
### Load exchange data to a pandas dataframe
### Further Data analysis documentation
This loads candle data to a dataframe
```python
from pathlib import Path
from freqtrade.data.history import load_pair_history
# Load data using values passed to function
ticker_interval = "5m"
data_location = Path('user_data', 'data', 'bitrex')
pair = "BTC_USDT"
candles = load_pair_history(datadir=data_location,
ticker_interval=ticker_interval,
pair=pair)
# Confirm success
print(f"Loaded len(candles) rows of data for {pair} from {data_location}")
candles.head()
```
## Strategy debugging example
Debugging a strategy can be time-consuming. FreqTrade offers helper functions to visualize raw data.
### Define variables used in analyses
You can override strategy settings as demonstrated below.
```python
# Customize these according to your needs.
# Define some constants
ticker_interval = "5m"
# Name of the strategy class
strategy_name = 'SampleStrategy'
# Path to user data
user_data_dir = 'user_data'
# Location of the strategy
strategy_location = Path(user_data_dir, 'strategies')
# Location of the data
data_location = Path(user_data_dir, 'data', 'binance')
# Pair to analyze - Only use one pair here
pair = "BTC_USDT"
```
### Load exchange data
```python
from pathlib import Path
from freqtrade.data.history import load_pair_history
# Load data using values set above
candles = load_pair_history(datadir=data_location,
ticker_interval=ticker_interval,
pair=pair)
# Confirm success
print(f"Loaded {len(candles)} rows of data for {pair} from {data_location}")
candles.head()
```
### Load and run strategy
* Rerun each time the strategy file is changed
```python
from freqtrade.resolvers import StrategyResolver
# Load strategy using values set above
strategy = StrategyResolver({'strategy': strategy_name,
'user_data_dir': user_data_dir,
'strategy_path': strategy_location}).strategy
# Generate buy/sell signals using strategy
df = strategy.analyze_ticker(candles, {'pair': pair})
```
### Display the trade details
* Note that using `data.tail()` is preferable to `data.head()` as most indicators have some "startup" data at the top of the dataframe.
* Some possible problems
* Columns with NaN values at the end of the dataframe
* Columns used in `crossed*()` functions with completely different units
* Comparison with full backtest
* having 200 buy signals as output for one pair from `analyze_ticker()` does not necessarily mean that 200 trades will be made during backtesting.
* Assuming you use only one condition such as, `df['rsi'] < 30` as buy condition, this will generate multiple "buy" signals for each pair in sequence (until rsi returns > 29). The bot will only buy on the first of these signals (and also only if a trade-slot ("max_open_trades") is still available), or on one of the middle signals, as soon as a "slot" becomes available.
```python
# Report results
print(f"Generated {df['buy'].sum()} buy signals")
data = df.set_index('date', drop=True)
data.tail()
```
* [Strategy debugging](strategy_analysis_example.md) - also available as Jupyter notebook (`user_data/notebooks/strategy_analysis_example.ipynb`)
* [Plotting](plotting.md)
Feel free to submit an issue or Pull Request enhancing this document if you would like to share ideas on how to best analyze the data.

28
docs/data-download.md
View File

@ -38,7 +38,7 @@ Mixing different stake-currencies is allowed for this file, since it's only used
]
```
### start download
### Start download
Then run:
@ -57,6 +57,32 @@ This will download ticker data for all the currency pairs you defined in `pairs.
- Use `--timeframes` to specify which tickers to download. Default is `--timeframes 1m 5m` which will download 1-minute and 5-minute tickers.
- To use exchange, timeframe and list of pairs as defined in your configuration file, use the `-c/--config` option. With this, the script uses the whitelist defined in the config as the list of currency pairs to download data for and does not require the pairs.json file. You can combine `-c/--config` with most other options.
### Trades (tick) data
By default, `download-data` subcommand downloads Candles (OHLCV) data. Some exchanges also provide historic trade-data via their API.
This data can be useful if you need many different timeframes, since it is only downloaded once, and then resampled locally to the desired timeframes.
Since this data is large by default, the files use gzip by default. They are stored in your data-directory with the naming convention of `<pair>-trades.json.gz` (`ETH_BTC-trades.json.gz`). Incremental mode is also supported, as for historic OHLCV data, so downloading the data once per week with `--days 8` will create an incremental data-repository.
To use this mode, simply add `--dl-trades` to your call. This will swap the download method to download trades, and resamples the data locally.
Example call:
```bash
freqtrade download-data --exchange binance --pairs XRP/ETH ETH/BTC --days 20 --dl-trades
```
!!! Note
While this method uses async calls, it will be slow, since it requires the result of the previous call to generate the next request to the exchange.
!!! Warning
The historic trades are not available during Freqtrade dry-run and live trade modes because all exchanges tested provide this data with a delay of few 100 candles, so it's not suitable for real-time trading.
### Historic Kraken data
The Kraken API does only provide 720 historic candles, which is sufficient for FreqTrade dry-run and live trade modes, but is a problem for backtesting.
To download data for the Kraken exchange, using `--dl-trades` is mandatory, otherwise the bot will download the same 720 candles over and over, and you'll not have enough backtest data.
## Next step
Great, you now have backtest data downloaded, so you can now start [backtesting](backtesting.md) your strategy.

51
docs/developer.md
View File

@ -38,8 +38,48 @@ def test_method_to_test(caplog):
assert log_has("This event happened", caplog)
# Check regex with trailing number ...
assert log_has_re(r"This dynamic event happened and produced \d+", caplog)
```
### Local docker usage
The fastest and easiest way to start up is to use docker-compose.develop which gives developers the ability to start the bot up with all the required dependencies, *without* needing to install any freqtrade specific dependencies on your local machine.
#### Install
* [git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)
* [docker](https://docs.docker.com/install/)
* [docker-compose](https://docs.docker.com/compose/install/)
#### Starting the bot
##### Use the develop dockerfile
``` bash
rm docker-compose.yml && mv docker-compose.develop.yml docker-compose.yml
```
#### Docker Compose
##### Starting
``` bash
docker-compose up
```
![Docker compose up](https://user-images.githubusercontent.com/419355/65456322-47f63a80-de06-11e9-90c6-3c74d1bad0b8.png)
##### Rebuilding
``` bash
docker-compose build
```
##### Execing (effectively SSH into the container)
The `exec` command requires that the container already be running, if you want to start it
that can be effected by `docker-compose up` or `docker-compose run freqtrade_develop`
``` bash
docker-compose exec freqtrade_develop /bin/bash
```
![image](https://user-images.githubusercontent.com/419355/65456522-ba671a80-de06-11e9-9598-df9ca0d8dcac.png)
## Modules
### Dynamic Pairlist
@ -149,6 +189,15 @@ print(datetime.utcnow())
The output will show the last entry from the Exchange as well as the current UTC date.
If the day shows the same day, then the last candle can be assumed as incomplete and should be dropped (leave the setting `"ohlcv_partial_candle"` from the exchange-class untouched / True). Otherwise, set `"ohlcv_partial_candle"` to `False` to not drop Candles (shown in the example above).
## Updating example notebooks
To keep the jupyter notebooks aligned with the documentation, the following should be ran after updating a example notebook.
``` bash
jupyter nbconvert --ClearOutputPreprocessor.enabled=True --inplace user_data/notebooks/strategy_analysis_example.ipynb
jupyter nbconvert --ClearOutputPreprocessor.enabled=True --to markdown user_data/notebooks/strategy_analysis_example.ipynb --stdout > docs/strategy_analysis_example.md
```
## Creating a release
This part of the documentation is aimed at maintainers, and shows how to create a release.
@ -182,7 +231,7 @@ git log --oneline --no-decorate --no-merges master..develop
Once the PR against master is merged (best right after merging):
* Use the button "Draft a new release" in the Github UI (subsection releases)
* Use the version-number specified as tag.
* Use the version-number specified as tag.
* Use "master" as reference (this step comes after the above PR is merged).
* Use the above changelog as release comment (as codeblock)

5
docs/edge.md
View File

@ -249,13 +249,10 @@ freqtrade edge --stoplosses=-0.01,-0.1,-0.001 #min,max,step
freqtrade edge --timerange=20181110-20181113
```
Doing `--timerange=-200` will get the last 200 timeframes from your inputdata. You can also specify specific dates, or a range span indexed by start and stop.
Doing `--timerange=-20190901` will get all available data until September 1st (excluding September 1st 2019).
The full timerange specification:
* Use last 123 tickframes of data: `--timerange=-123`
* Use first 123 tickframes of data: `--timerange=123-`
* Use tickframes from line 123 through 456: `--timerange=123-456`
* Use tickframes till 2018/01/31: `--timerange=-20180131`
* Use tickframes since 2018/01/31: `--timerange=20180131-`
* Use tickframes since 2018/01/31 till 2018/03/01 : `--timerange=20180131-20180301`

4
docs/faq.md
View File

@ -38,7 +38,7 @@ like pauses. You can stop your bot, adjust settings and start it again.
### I want to improve the bot with a new strategy
That's great. We have a nice backtesting and hyperoptimizing setup. See
That's great. We have a nice backtesting and hyperoptimization setup. See
the tutorial [here|Testing-new-strategies-with-Hyperopt](bot-usage.md#hyperopt-commands).
### Is there a setting to only SELL the coins being held and not perform anymore BUYS?
@ -59,7 +59,7 @@ If you're a US customer, the bot will fail to create orders for these pairs, and
### How many epoch do I need to get a good Hyperopt result?
Per default Hyperopts without `-e` or `--epochs` parameter will only
Per default Hyperopt called without the `-e`/`--epochs` command line option will only
run 100 epochs, means 100 evals of your triggers, guards, ... Too few
to find a great result (unless if you are very lucky), so you probably
have to run it for 10.000 or more. But it will take an eternity to

12
docs/hyperopt.md
View File

@ -10,12 +10,12 @@ Hyperopt requires historic data to be available, just as backtesting does.
To learn how to get data for the pairs and exchange you're interrested in, head over to the [Data Downloading](data-download.md) section of the documentation.
!!! Bug
Hyperopt will crash when used with only 1 CPU Core as found out in [Issue #1133](https://github.com/freqtrade/freqtrade/issues/1133)
Hyperopt can crash when used with only 1 CPU Core as found out in [Issue #1133](https://github.com/freqtrade/freqtrade/issues/1133)
## Prepare Hyperopting
Before we start digging into Hyperopt, we recommend you to take a look at
an example hyperopt file located into [user_data/hyperopts/](https://github.com/freqtrade/freqtrade/blob/develop/user_data/hyperopts/sample_hyperopt.py)
the sample hyperopt file located in [user_data/hyperopts/](https://github.com/freqtrade/freqtrade/blob/develop/user_data/hyperopts/sample_hyperopt.py).
Configuring hyperopt is similar to writing your own strategy, and many tasks will be similar and a lot of code can be copied across from the strategy.
@ -64,9 +64,9 @@ multiple guards. The constructed strategy will be something like
"*buy exactly when close price touches lower bollinger band, BUT only if
ADX > 10*".
If you have updated the buy strategy, ie. changed the contents of
`populate_buy_trend()` method you have to update the `guards` and
`triggers` hyperopts must use.
If you have updated the buy strategy, i.e. changed the contents of
`populate_buy_trend()` method, you have to update the `guards` and
`triggers` your hyperopt must use correspondingly.
#### Sell optimization
@ -82,7 +82,7 @@ To avoid naming collisions in the search-space, please prefix all sell-spaces wi
#### Using ticker-interval as part of the Strategy
The Strategy exposes the ticker-interval as `self.ticker_interval`. The same value is available as class-attribute `HyperoptName.ticker_interval`.
In the case of the linked sample-value this would be `SampleHyperOpts.ticker_interval`.
In the case of the linked sample-value this would be `SampleHyperOpt.ticker_interval`.
## Solving a Mystery

4
docs/partials/header.html
View File

@ -49,4 +49,6 @@
</nav>
<!-- Place this tag in your head or just before your close body tag. -->
<script async defer src="https://buttons.github.io/buttons.js"></script>
</header>
<script src="https://code.jquery.com/jquery-3.4.1.min.js"
integrity="sha256-CSXorXvZcTkaix6Yvo6HppcZGetbYMGWSFlBw8HfCJo=" crossorigin="anonymous"></script>
</header>

2
docs/plotting.md
View File

@ -220,5 +220,5 @@ freqtrade plot-profit -p LTC/BTC --db-url sqlite:///tradesv3.sqlite --trade-sou
```
``` bash
freqtrade plot-profit --datadir user_data/data/binance_save/ -p LTC/BTC
freqtrade --datadir user_data/data/binance_save/ plot-profit -p LTC/BTC
```

3
docs/requirements-docs.txt
View File

@ -1 +1,2 @@
mkdocs-material==4.4.2
mkdocs-material==4.4.3
mdx_truly_sane_lists==1.2

1
docs/rest-api.md
View File

@ -100,7 +100,6 @@ python3 scripts/rest_client.py --config rest_config.json <command> [optional par
| `stopbuy` | | Stops the trader from opening new trades. Gracefully closes open trades according to their rules.
| `reload_conf` | | Reloads the configuration file
| `status` | | Lists all open trades
| `status table` | | List all open trades in a table format
| `count` | | Displays number of trades used and available
| `profit` | | Display a summary of your profit/loss from close trades and some stats about your performance
| `forcesell <trade_id>` | | Instantly sells the given trade (Ignoring `minimum_roi`).

27
docs/strategy-customization.md
View File

@ -138,15 +138,19 @@ def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
"""
dataframe.loc[
(
(dataframe['adx'] > 30) &
(dataframe['tema'] <= dataframe['bb_middleband']) &
(dataframe['tema'] > dataframe['tema'].shift(1))
(qtpylib.crossed_above(dataframe['rsi'], 30)) & # Signal: RSI crosses above 30
(dataframe['tema'] <= dataframe['bb_middleband']) & # Guard
(dataframe['tema'] > dataframe['tema'].shift(1)) & # Guard
(dataframe['volume'] > 0) # Make sure Volume is not 0
),
'buy'] = 1
return dataframe
```
!!! Note
Buying requires sellers to buy from - therefore volume needs to be > 0 (`dataframe['volume'] > 0`) to make sure that the bot does not buy/sell in no-activity periods.
### Sell signal rules
Edit the method `populate_sell_trend()` into your strategy file to update your sell strategy.
@ -168,9 +172,10 @@ def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame
"""
dataframe.loc[
(
(dataframe['adx'] > 70) &
(dataframe['tema'] > dataframe['bb_middleband']) &
(dataframe['tema'] < dataframe['tema'].shift(1))
(qtpylib.crossed_above(dataframe['rsi'], 70)) & # Signal: RSI crosses above 70
(dataframe['tema'] > dataframe['bb_middleband']) & # Guard
(dataframe['tema'] < dataframe['tema'].shift(1)) & # Guard
(dataframe['volume'] > 0) # Make sure Volume is not 0
),
'sell'] = 1
return dataframe
@ -246,9 +251,9 @@ Instead, have a look at the section [Storing information](#Storing-information)
### Storing information
Storing information can be accomplished by crating a new dictionary within the strategy class.
Storing information can be accomplished by creating a new dictionary within the strategy class.
The name of the variable can be choosen at will, but should be prefixed with `cust_` to avoid naming collisions with predefined strategy variables.
The name of the variable can be chosen at will, but should be prefixed with `cust_` to avoid naming collisions with predefined strategy variables.
```python
class Awesomestrategy(IStrategy):
@ -282,6 +287,8 @@ Please always check the mode of operation to select the correct method to get da
- `ohlcv(pair, ticker_interval)` - Currently cached ticker data for the pair, returns DataFrame or empty DataFrame.
- `historic_ohlcv(pair, ticker_interval)` - Returns historical data stored on disk.
- `get_pair_dataframe(pair, ticker_interval)` - This is a universal method, which returns either historical data (for backtesting) or cached live data (for the Dry-Run and Live-Run modes).
- `orderbook(pair, maximum)` - Returns latest orderbook data for the pair, a dict with bids/asks with a total of `maximum` entries.
- `market(pair)` - Returns market data for the pair: fees, limits, precisions, activity flag, etc. See [ccxt documentation](https://github.com/ccxt/ccxt/wiki/Manual#markets) for more details on Market data structure.
- `runmode` - Property containing the current runmode.
#### Example: fetch live ohlcv / historic data for the first informative pair
@ -344,9 +351,9 @@ def informative_pairs(self):
As these pairs will be refreshed as part of the regular whitelist refresh, it's best to keep this list short.
All intervals and all pairs can be specified as long as they are available (and active) on the used exchange.
It is however better to use resampling to longer time-intervals when possible
to avoid hammering the exchange with too many requests and risk beeing blocked.
to avoid hammering the exchange with too many requests and risk being blocked.
### Additional data - Wallets
### Additional data (Wallets)
The strategy provides access to the `Wallets` object. This contains the current balances on the exchange.

142
docs/strategy_analysis_example.md Normal file
View File

@ -0,0 +1,142 @@
# Strategy analysis example
Debugging a strategy can be time-consuming. FreqTrade offers helper functions to visualize raw data.
## Setup
```python
from pathlib import Path
# Customize these according to your needs.
# Define some constants
ticker_interval = "5m"
# Name of the strategy class
strategy_name = 'SampleStrategy'
# Path to user data
user_data_dir = Path('user_data')
# Location of the strategy
strategy_location = user_data_dir / 'strategies'
# Location of the data
data_location = Path(user_data_dir, 'data', 'binance')
# Pair to analyze - Only use one pair here
pair = "BTC_USDT"
```
```python
# Load data using values set above
from freqtrade.data.history import load_pair_history
candles = load_pair_history(datadir=data_location,
ticker_interval=ticker_interval,
pair=pair)
# Confirm success
print("Loaded " + str(len(candles)) + f" rows of data for {pair} from {data_location}")
candles.head()
```
## Load and run strategy
* Rerun each time the strategy file is changed
```python
# Load strategy using values set above
from freqtrade.resolvers import StrategyResolver
strategy = StrategyResolver({'strategy': strategy_name,
'user_data_dir': user_data_dir,
'strategy_path': strategy_location}).strategy
# Generate buy/sell signals using strategy
df = strategy.analyze_ticker(candles, {'pair': pair})
df.tail()
```
### Display the trade details
* Note that using `data.head()` would also work, however most indicators have some "startup" data at the top of the dataframe.
* Some possible problems
* Columns with NaN values at the end of the dataframe
* Columns used in `crossed*()` functions with completely different units
* Comparison with full backtest
* having 200 buy signals as output for one pair from `analyze_ticker()` does not necessarily mean that 200 trades will be made during backtesting.
* Assuming you use only one condition such as, `df['rsi'] < 30` as buy condition, this will generate multiple "buy" signals for each pair in sequence (until rsi returns > 29). The bot will only buy on the first of these signals (and also only if a trade-slot ("max_open_trades") is still available), or on one of the middle signals, as soon as a "slot" becomes available.
```python
# Report results
print(f"Generated {df['buy'].sum()} buy signals")
data = df.set_index('date', drop=False)
data.tail()
```
## Load existing objects into a Jupyter notebook
The following cells assume that you have already generated data using the cli.
They will allow you to drill deeper into your results, and perform analysis which otherwise would make the output very difficult to digest due to information overload.
### Load backtest results to pandas dataframe
Analyze a trades dataframe (also used below for plotting)
```python
from freqtrade.data.btanalysis import load_backtest_data
# Load backtest results
trades = load_backtest_data(user_data_dir / "backtest_results/backtest-result.json")
# Show value-counts per pair
trades.groupby("pair")["sell_reason"].value_counts()
```
### Load live trading results into a pandas dataframe
In case you did already some trading and want to analyze your performance
```python
from freqtrade.data.btanalysis import load_trades_from_db
# Fetch trades from database
trades = load_trades_from_db("sqlite:///tradesv3.sqlite")
# Display results
trades.groupby("pair")["sell_reason"].value_counts()
```
## Plot results
Freqtrade offers interactive plotting capabilities based on plotly.
```python
from freqtrade.plot.plotting import generate_candlestick_graph
# Limit graph period to keep plotly quick and reactive
data_red = data['2019-06-01':'2019-06-10']
# Generate candlestick graph
graph = generate_candlestick_graph(pair=pair,
data=data_red,
trades=trades,
indicators1=['sma20', 'ema50', 'ema55'],
indicators2=['rsi', 'macd', 'macdsignal', 'macdhist']
)
```
```python
# Show graph inline
# graph.show()
# Render graph in a seperate window
graph.show(renderer="browser")
```
Feel free to submit an issue or Pull Request enhancing this document if you would like to share ideas on how to best analyze the data.

13
docs/stylesheets/ft.extra.css Normal file
View File

@ -0,0 +1,13 @@
.rst-versions {
font-size: .7rem;
color: white;
}
.rst-versions.rst-badge .rst-current-version {
font-size: .7rem;
color: white;
}
.rst-versions .rst-other-versions {
color: white;
}

56
docs/utils.md Normal file
View File

@ -0,0 +1,56 @@
# Utility Subcommands
Besides the Live-Trade and Dry-Run run modes, the `backtesting`, `edge` and `hyperopt` optimization subcommands, and the `download-data` subcommand which prepares historical data, the bot contains a number of utility subcommands. They are described in this section.
## List Exchanges
Use the `list-exchanges` subcommand to see the exchanges available for the bot.
```
usage: freqtrade list-exchanges [-h] [-1] [-a]
optional arguments:
-h, --help show this help message and exit
-1, --one-column Print output in one column.
-a, --all Print all exchanges known to the ccxt library.
```
* Example: see exchanges available for the bot:
```
$ freqtrade list-exchanges
Exchanges available for Freqtrade: _1btcxe, acx, allcoin, bequant, bibox, binance, binanceje, binanceus, bitbank, bitfinex, bitfinex2, bitkk, bitlish, bitmart, bittrex, bitz, bleutrade, btcalpha, btcmarkets, btcturk, buda, cex, cobinhood, coinbaseprime, coinbasepro, coinex, cointiger, coss, crex24, digifinex, dsx, dx, ethfinex, fcoin, fcoinjp, gateio, gdax, gemini, hitbtc2, huobipro, huobiru, idex, kkex, kraken, kucoin, kucoin2, kuna, lbank, mandala, mercado, oceanex, okcoincny, okcoinusd, okex, okex3, poloniex, rightbtc, theocean, tidebit, upbit, zb
```
* Example: see all exchanges supported by the ccxt library (including 'bad' ones, i.e. those that are known to not work with Freqtrade):
```
$ freqtrade list-exchanges -a
All exchanges supported by the ccxt library: _1btcxe, acx, adara, allcoin, anxpro, bcex, bequant, bibox, bigone, binance, binanceje, binanceus, bit2c, bitbank, bitbay, bitfinex, bitfinex2, bitflyer, bitforex, bithumb, bitkk, bitlish, bitmart, bitmex, bitso, bitstamp, bitstamp1, bittrex, bitz, bl3p, bleutrade, braziliex, btcalpha, btcbox, btcchina, btcmarkets, btctradeim, btctradeua, btcturk, buda, bxinth, cex, chilebit, cobinhood, coinbase, coinbaseprime, coinbasepro, coincheck, coinegg, coinex, coinexchange, coinfalcon, coinfloor, coingi, coinmarketcap, coinmate, coinone, coinspot, cointiger, coolcoin, coss, crex24, crypton, deribit, digifinex, dsx, dx, ethfinex, exmo, exx, fcoin, fcoinjp, flowbtc, foxbit, fybse, gateio, gdax, gemini, hitbtc, hitbtc2, huobipro, huobiru, ice3x, idex, independentreserve, indodax, itbit, kkex, kraken, kucoin, kucoin2, kuna, lakebtc, latoken, lbank, liquid, livecoin, luno, lykke, mandala, mercado, mixcoins, negociecoins, nova, oceanex, okcoincny, okcoinusd, okex, okex3, paymium, poloniex, rightbtc, southxchange, stronghold, surbitcoin, theocean, therock, tidebit, tidex, upbit, vaultoro, vbtc, virwox, xbtce, yobit, zaif, zb
```
## List Timeframes
Use the `list-timeframes` subcommand to see the list of ticker intervals (timeframes) available for the exchange.
```
usage: freqtrade list-timeframes [-h] [--exchange EXCHANGE] [-1]
optional arguments:
-h, --help show this help message and exit
--exchange EXCHANGE Exchange name (default: `bittrex`). Only valid if no
config is provided.
-1, --one-column Print output in one column.
```
* Example: see the timeframes for the 'binance' exchange, set in the configuration file:
```
$ freqtrade -c config_binance.json list-timeframes
...
Timeframes available for the exchange `binance`: 1m, 3m, 5m, 15m, 30m, 1h, 2h, 4h, 6h, 8h, 12h, 1d, 3d, 1w, 1M
```
* Example: enumerate exchanges available for Freqtrade and print timeframes supported by each of them:
```
$ for i in `freqtrade list-exchanges -1`; do freqtrade list-timeframes --exchange $i; done
```

26
freqtrade/configuration/arguments.py
View File

@ -14,7 +14,8 @@ ARGS_STRATEGY = ["strategy", "strategy_path"]
ARGS_TRADE = ["db_url", "sd_notify", "dry_run"]
ARGS_COMMON_OPTIMIZE = ["ticker_interval", "timerange", "max_open_trades", "stake_amount"]
ARGS_COMMON_OPTIMIZE = ["ticker_interval", "timerange",
"max_open_trades", "stake_amount", "fee"]
ARGS_BACKTEST = ARGS_COMMON_OPTIMIZE + ["position_stacking", "use_max_market_positions",
"strategy_list", "export", "exportfilename"]
@ -28,11 +29,14 @@ ARGS_HYPEROPT = ARGS_COMMON_OPTIMIZE + ["hyperopt", "hyperopt_path",
ARGS_EDGE = ARGS_COMMON_OPTIMIZE + ["stoploss_range"]
ARGS_LIST_EXCHANGES = ["print_one_column"]
ARGS_LIST_EXCHANGES = ["print_one_column", "list_exchanges_all"]
ARGS_LIST_TIMEFRAMES = ["exchange", "print_one_column"]
ARGS_CREATE_USERDIR = ["user_data_dir"]
ARGS_DOWNLOAD_DATA = ["pairs", "pairs_file", "days", "exchange", "timeframes", "erase"]
ARGS_DOWNLOAD_DATA = ["pairs", "pairs_file", "days", "download_trades", "exchange",
"timeframes", "erase"]
ARGS_PLOT_DATAFRAME = ["pairs", "indicators1", "indicators2", "plot_limit",
"db_url", "trade_source", "export", "exportfilename",
@ -41,7 +45,9 @@ ARGS_PLOT_DATAFRAME = ["pairs", "indicators1", "indicators2", "plot_limit",
ARGS_PLOT_PROFIT = ["pairs", "timerange", "export", "exportfilename", "db_url",
"trade_source", "ticker_interval"]
NO_CONF_REQURIED = ["create-userdir", "download-data", "plot-dataframe", "plot-profit"]
NO_CONF_REQURIED = ["download-data", "list-timeframes", "plot-dataframe", "plot-profit"]
NO_CONF_ALLOWED = ["create-userdir", "list-exchanges"]
class Arguments:
@ -69,8 +75,6 @@ class Arguments:
"""
parsed_arg = self.parser.parse_args(self.args)
# When no config is provided, but a config exists, use that configuration!
# Workaround issue in argparse with action='append' and default value
# (see https://bugs.python.org/issue16399)
# Allow no-config for certain commands (like downloading / plotting)
@ -107,7 +111,7 @@ class Arguments:
from freqtrade.optimize import start_backtesting, start_hyperopt, start_edge
from freqtrade.utils import (start_create_userdir, start_download_data,
start_list_exchanges, start_trading)
start_list_exchanges, start_list_timeframes, start_trading)
from freqtrade.plot.plot_utils import start_plot_dataframe, start_plot_profit
subparsers = self.parser.add_subparsers(dest='command',
@ -156,6 +160,14 @@ class Arguments:
list_exchanges_cmd.set_defaults(func=start_list_exchanges)
self._build_args(optionlist=ARGS_LIST_EXCHANGES, parser=list_exchanges_cmd)
# Add list-timeframes subcommand
list_timeframes_cmd = subparsers.add_parser(
'list-timeframes',
help='Print available ticker intervals (timeframes) for the exchange.'
)
list_timeframes_cmd.set_defaults(func=start_list_timeframes)
self._build_args(optionlist=ARGS_LIST_TIMEFRAMES, parser=list_timeframes_cmd)
# Add download-data subcommand
download_data_cmd = subparsers.add_parser('download-data',
help='Download backtesting data.',

14
freqtrade/configuration/check_exchange.py
View File

@ -3,7 +3,7 @@ from typing import Any, Dict
from freqtrade import OperationalException
from freqtrade.exchange import (available_exchanges, get_exchange_bad_reason,
is_exchange_available, is_exchange_bad,
is_exchange_known_ccxt, is_exchange_bad,
is_exchange_officially_supported)
from freqtrade.state import RunMode
@ -31,15 +31,15 @@ def check_exchange(config: Dict[str, Any], check_for_bad: bool = True) -> bool:
raise OperationalException(
f'This command requires a configured exchange. You should either use '
f'`--exchange <exchange_name>` or specify a configuration file via `--config`.\n'
f'The following exchanges are supported by ccxt: '
f'The following exchanges are available for Freqtrade: '
f'{", ".join(available_exchanges())}'
)
if not is_exchange_available(exchange):
if not is_exchange_known_ccxt(exchange):
raise OperationalException(
f'Exchange "{exchange}" is not supported by ccxt '
f'Exchange "{exchange}" is not known to the ccxt library '
f'and therefore not available for the bot.\n'
f'The following exchanges are supported by ccxt: '
f'The following exchanges are available for Freqtrade: '
f'{", ".join(available_exchanges())}'
)
@ -51,8 +51,8 @@ def check_exchange(config: Dict[str, Any], check_for_bad: bool = True) -> bool:
logger.info(f'Exchange "{exchange}" is officially supported '
f'by the Freqtrade development team.')
else:
logger.warning(f'Exchange "{exchange}" is supported by ccxt '
f'and therefore available for the bot but not officially supported '
logger.warning(f'Exchange "{exchange}" is known to the the ccxt library, '
f'available for the bot, but not officially supported '
f'by the Freqtrade development team. '
f'It may work flawlessly (please report back) or have serious issues. '
f'Use it at your own discretion.')

22
freqtrade/configuration/cli_options.py
View File

@ -2,7 +2,6 @@
Definition of cli arguments used in arguments.py
"""
import argparse
import os
from freqtrade import __version__, constants
@ -145,8 +144,12 @@ AVAILABLE_CLI_OPTIONS = {
'Requires `--export` to be set as well. '
'Example: `--export-filename=user_data/backtest_results/backtest_today.json`',
metavar='PATH',
default=os.path.join('user_data', 'backtest_results',
'backtest-result.json'),
),
"fee": Arg(
'--fee',
help='Specify fee ratio. Will be applied twice (on trade entry and exit).',
type=float,
metavar='FLOAT',
),
# Edge
"stoploss_range": Arg(
@ -244,7 +247,12 @@ AVAILABLE_CLI_OPTIONS = {
# List exchanges
"print_one_column": Arg(
'-1', '--one-column',
help='Print exchanges in one column.',
help='Print output in one column.',
action='store_true',
),
"list_exchanges_all": Arg(
'-a', '--all',
help='Print all exchanges known to the ccxt library.',
action='store_true',
),
# Script options
@ -265,6 +273,12 @@ AVAILABLE_CLI_OPTIONS = {
type=check_int_positive,
metavar='INT',
),
"download_trades": Arg(
'--dl-trades',
help='Download trades instead of OHLCV data. The bot will resample trades to the '
'desired timeframe as specified as --timeframes/-t.',
action='store_true',
),
"exchange": Arg(
'--exchange',
help=f'Exchange name (default: `{constants.DEFAULT_EXCHANGE}`). '

30
freqtrade/configuration/configuration.py
View File

@ -9,8 +9,9 @@ from typing import Any, Callable, Dict, List, Optional
from freqtrade import OperationalException, constants
from freqtrade.configuration.check_exchange import check_exchange
from freqtrade.configuration.config_validation import (
validate_config_consistency, validate_config_schema)
from freqtrade.configuration.config_validation import (validate_config_consistency,
validate_config_schema)
from freqtrade.configuration.deprecated_settings import process_temporary_deprecated_settings
from freqtrade.configuration.directory_operations import (create_datadir,
create_userdata_dir)
from freqtrade.configuration.load_config import load_config_file
@ -75,6 +76,10 @@ class Configuration:
# Normalize config
if 'internals' not in config:
config['internals'] = {}
# TODO: This can be deleted along with removal of deprecated
# experimental settings
if 'ask_strategy' not in config:
config['ask_strategy'] = {}
# validate configuration before returning
logger.info('Validating configuration ...')
@ -106,6 +111,8 @@ class Configuration:
self._resolve_pairs_list(config)
process_temporary_deprecated_settings(config)
validate_config_consistency(config)
return config
@ -189,6 +196,13 @@ class Configuration:
config.update({'datadir': create_datadir(config, self.args.get("datadir", None))})
logger.info('Using data directory: %s ...', config.get('datadir'))
if self.args.get('exportfilename'):
self._args_to_config(config, argname='exportfilename',
logstring='Storing backtest results to {} ...')
else:
config['exportfilename'] = (config['user_data_dir']
/ 'backtest_results/backtest-result.json')
def _process_optimize_options(self, config: Dict[str, Any]) -> None:
# This will override the strategy configuration
@ -214,6 +228,10 @@ class Configuration:
logstring='Parameter --stake_amount detected, '
'overriding stake_amount to: {} ...')
self._args_to_config(config, argname='fee',
logstring='Parameter --fee detected, '
'setting fee to: {} ...')
self._args_to_config(config, argname='timerange',
logstring='Parameter --timerange detected: {} ...')
@ -228,9 +246,6 @@ class Configuration:
self._args_to_config(config, argname='export',
logstring='Parameter --export detected: {} ...')
self._args_to_config(config, argname='exportfilename',
logstring='Storing backtest results to {} ...')
# Edge section:
if 'stoploss_range' in self.args and self.args["stoploss_range"]:
txt_range = eval(self.args["stoploss_range"])
@ -305,6 +320,8 @@ class Configuration:
self._args_to_config(config, argname='days',
logstring='Detected --days: {}')
self._args_to_config(config, argname='download_trades',
logstring='Detected --dl-trades: {}')
def _process_runmode(self, config: Dict[str, Any]) -> None:
@ -327,7 +344,8 @@ class Configuration:
sample: logfun=len (prints the length of the found
configuration instead of the content)
"""
if argname in self.args and self.args[argname]:
if (argname in self.args and self.args[argname] is not None
and self.args[argname] is not False):
config.update({argname: self.args[argname]})
if logfun:

59
freqtrade/configuration/deprecated_settings.py Normal file
View File

@ -0,0 +1,59 @@
"""
Functions to handle deprecated settings
"""
import logging
from typing import Any, Dict
from freqtrade import OperationalException
logger = logging.getLogger(__name__)
def check_conflicting_settings(config: Dict[str, Any],
section1: str, name1: str,
section2: str, name2: str):
section1_config = config.get(section1, {})
section2_config = config.get(section2, {})
if name1 in section1_config and name2 in section2_config:
raise OperationalException(
f"Conflicting settings `{section1}.{name1}` and `{section2}.{name2}` "
"(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}` "
"setting instead."
)
def process_deprecated_setting(config: Dict[str, Any],
section1: str, name1: str,
section2: str, name2: str):
section2_config = config.get(section2, {})
if name2 in section2_config:
logger.warning(
"DEPRECATED: "
f"The `{section2}.{name2}` setting is deprecated and "
"will be removed in the next versions of Freqtrade. "
f"Please use the `{section1}.{name1}` setting in your configuration instead."
)
section1_config = config.get(section1, {})
section1_config[name1] = section2_config[name2]
def process_temporary_deprecated_settings(config: Dict[str, Any]) -> None:
check_conflicting_settings(config, 'ask_strategy', 'use_sell_signal',
'experimental', 'use_sell_signal')
check_conflicting_settings(config, 'ask_strategy', 'sell_profit_only',
'experimental', 'sell_profit_only')
check_conflicting_settings(config, 'ask_strategy', 'ignore_roi_if_buy_signal',
'experimental', 'ignore_roi_if_buy_signal')
process_deprecated_setting(config, 'ask_strategy', 'use_sell_signal',
'experimental', 'use_sell_signal')
process_deprecated_setting(config, 'ask_strategy', 'sell_profit_only',
'experimental', 'sell_profit_only')
process_deprecated_setting(config, 'ask_strategy', 'ignore_roi_if_buy_signal',
'experimental', 'ignore_roi_if_buy_signal')

11
freqtrade/configuration/timerange.py
View File

@ -42,9 +42,10 @@ class TimeRange:
(r'^-(\d{10})$', (None, 'date')),
(r'^(\d{10})-$', ('date', None)),
(r'^(\d{10})-(\d{10})$', ('date', 'date')),
(r'^(-\d+)$', (None, 'line')),
(r'^(\d+)-$', ('line', None)),
(r'^(\d+)-(\d+)$', ('index', 'index'))]
(r'^-(\d{13})$', (None, 'date')),
(r'^(\d{13})-$', ('date', None)),
(r'^(\d{13})-(\d{13})$', ('date', 'date')),
]
for rex, stype in syntax:
# Apply the regular expression to text
match = re.match(rex, text)
@ -57,6 +58,8 @@ class TimeRange:
starts = rvals[index]
if stype[0] == 'date' and len(starts) == 8:
start = arrow.get(starts, 'YYYYMMDD').timestamp
elif len(starts) == 13:
start = int(starts) // 1000
else:
start = int(starts)
index += 1
@ -64,6 +67,8 @@ class TimeRange:
stops = rvals[index]
if stype[1] == 'date' and len(stops) == 8:
stop = arrow.get(stops, 'YYYYMMDD').timestamp
elif len(stops) == 13:
stop = int(stops) // 1000
else:
stop = int(stops)
return TimeRange(stype[0], stype[1], start, stop)

10
freqtrade/constants.py
View File

@ -112,7 +112,10 @@ CONF_SCHEMA = {
'properties': {
'use_order_book': {'type': 'boolean'},
'order_book_min': {'type': 'number', 'minimum': 1},
'order_book_max': {'type': 'number', 'minimum': 1, 'maximum': 50}
'order_book_max': {'type': 'number', 'minimum': 1, 'maximum': 50},
'use_sell_signal': {'type': 'boolean'},
'sell_profit_only': {'type': 'boolean'},
'ignore_roi_if_buy_signal': {'type': 'boolean'}
}
},
'order_types': {
@ -142,7 +145,8 @@ CONF_SCHEMA = {
'properties': {
'use_sell_signal': {'type': 'boolean'},
'sell_profit_only': {'type': 'boolean'},
'ignore_roi_if_buy_signal_true': {'type': 'boolean'}
'ignore_roi_if_buy_signal': {'type': 'boolean'},
'block_bad_exchanges': {'type': 'boolean'}
}
},
'pairlist': {
@ -260,6 +264,6 @@ CONF_SCHEMA = {
'stake_amount',
'dry_run',
'bid_strategy',
'telegram'
'unfilledtimeout',
]
}

2
freqtrade/data/btanalysis.py
View File

@ -93,7 +93,7 @@ def load_trades_from_db(db_url: str) -> pd.DataFrame:
t.close_date.replace(tzinfo=pytz.UTC) if t.close_date else None,
t.calc_profit(), t.calc_profit_percent(),
t.open_rate, t.close_rate, t.amount,
(t.close_date.timestamp() - t.open_date.timestamp()
(round((t.close_date.timestamp() - t.open_date.timestamp()) / 60, 2)
if t.close_date else None),
t.sell_reason,
t.fee_open, t.fee_close,

22
freqtrade/data/converter.py
View File

@ -114,3 +114,25 @@ def order_book_to_dataframe(bids: list, asks: list) -> DataFrame:
keys=['b_sum', 'b_size', 'bids', 'asks', 'a_size', 'a_sum'])
# logger.info('order book %s', frame )
return frame
def trades_to_ohlcv(trades: list, timeframe: str) -> list:
"""
Converts trades list to ohlcv list
:param trades: List of trades, as returned by ccxt.fetch_trades.
:param timeframe: Ticker timeframe to resample data to
:return: ohlcv timeframe as list (as returned by ccxt.fetch_ohlcv)
"""
from freqtrade.exchange import timeframe_to_minutes
ticker_minutes = timeframe_to_minutes(timeframe)
df = pd.DataFrame(trades)
df['datetime'] = pd.to_datetime(df['datetime'])
df = df.set_index('datetime')
df_new = df['price'].resample(f'{ticker_minutes}min').ohlc()
df_new['volume'] = df['amount'].resample(f'{ticker_minutes}min').sum()
df_new['date'] = df_new.index.astype("int64") // 10 ** 6
# Drop 0 volume rows
df_new = df_new.dropna()
columns = ["date", "open", "high", "low", "close", "volume"]
return list(zip(*[df_new[x].values.tolist() for x in columns]))

14
freqtrade/data/dataprovider.py
View File

@ -6,7 +6,7 @@ Common Interface for bot and strategy to access data.
"""
import logging
from pathlib import Path
from typing import List, Tuple
from typing import Any, Dict, List, Optional, Tuple
from pandas import DataFrame
@ -85,6 +85,14 @@ class DataProvider:
logger.warning(f"No data found for ({pair}, {ticker_interval}).")
return data
def market(self, pair: str) -> Optional[Dict[str, Any]]:
"""
Return market data for the pair
:param pair: Pair to get the data for
:return: Market data dict from ccxt or None if market info is not available for the pair
"""
return self._exchange.markets.get(pair)
def ticker(self, pair: str):
"""
Return last ticker data
@ -92,9 +100,9 @@ class DataProvider:
# TODO: Implement me
pass
def orderbook(self, pair: str, maximum: int):
def orderbook(self, pair: str, maximum: int) -> Dict[str, List]:
"""
return latest orderbook data
fetch latest orderbook data
:param pair: pair to get the data for
:param maximum: Maximum number of orderbook entries to query
:return: dict including bids/asks with a total of `maximum` entries.

166
freqtrade/data/history.py
View File

@ -17,7 +17,7 @@ from pandas import DataFrame
from freqtrade import OperationalException, misc
from freqtrade.configuration import TimeRange
from freqtrade.data.converter import parse_ticker_dataframe
from freqtrade.data.converter import parse_ticker_dataframe, trades_to_ohlcv
from freqtrade.exchange import Exchange, timeframe_to_minutes
logger = logging.getLogger(__name__)
@ -33,20 +33,12 @@ def trim_tickerlist(tickerlist: List[Dict], timerange: TimeRange) -> List[Dict]:
start_index = 0
stop_index = len(tickerlist)
if timerange.starttype == 'line':
stop_index = timerange.startts
if timerange.starttype == 'index':
start_index = timerange.startts
elif timerange.starttype == 'date':
if timerange.starttype == 'date':
while (start_index < len(tickerlist) and
tickerlist[start_index][0] < timerange.startts * 1000):
start_index += 1
if timerange.stoptype == 'line':
start_index = max(len(tickerlist) + timerange.stopts, 0)
if timerange.stoptype == 'index':
stop_index = timerange.stopts
elif timerange.stoptype == 'date':
if timerange.stoptype == 'date':
while (stop_index > 0 and
tickerlist[stop_index-1][0] > timerange.stopts * 1000):
stop_index -= 1
@ -82,10 +74,42 @@ def store_tickerdata_file(datadir: Path, pair: str,
misc.file_dump_json(filename, data, is_zip=is_zip)
def load_trades_file(datadir: Path, pair: str,
timerange: Optional[TimeRange] = None) -> List[Dict]:
"""
Load a pair from file, either .json.gz or .json
:return: tradelist or empty list if unsuccesful
"""
filename = pair_trades_filename(datadir, pair)
tradesdata = misc.file_load_json(filename)
if not tradesdata:
return []
return tradesdata
def store_trades_file(datadir: Path, pair: str,
data: list, is_zip: bool = True):
"""
Stores tickerdata to file
"""
filename = pair_trades_filename(datadir, pair)
misc.file_dump_json(filename, data, is_zip=is_zip)
def _validate_pairdata(pair, pairdata, timerange: TimeRange):
if timerange.starttype == 'date' and pairdata[0][0] > timerange.startts * 1000:
logger.warning('Missing data at start for pair %s, data starts at %s',
pair, arrow.get(pairdata[0][0] // 1000).strftime('%Y-%m-%d %H:%M:%S'))
if timerange.stoptype == 'date' and pairdata[-1][0] < timerange.stopts * 1000:
logger.warning('Missing data at end for pair %s, data ends at %s',
pair, arrow.get(pairdata[-1][0] // 1000).strftime('%Y-%m-%d %H:%M:%S'))
def load_pair_history(pair: str,
ticker_interval: str,
datadir: Path,
timerange: TimeRange = TimeRange(None, None, 0, 0),
timerange: Optional[TimeRange] = None,
refresh_pairs: bool = False,
exchange: Optional[Exchange] = None,
fill_up_missing: bool = True,
@ -116,13 +140,8 @@ def load_pair_history(pair: str,
pairdata = load_tickerdata_file(datadir, pair, ticker_interval, timerange=timerange)
if pairdata:
if timerange.starttype == 'date' and pairdata[0][0] > timerange.startts * 1000:
logger.warning('Missing data at start for pair %s, data starts at %s',
pair, arrow.get(pairdata[0][0] // 1000).strftime('%Y-%m-%d %H:%M:%S'))
if timerange.stoptype == 'date' and pairdata[-1][0] < timerange.stopts * 1000:
logger.warning('Missing data at end for pair %s, data ends at %s',
pair,
arrow.get(pairdata[-1][0] // 1000).strftime('%Y-%m-%d %H:%M:%S'))
if timerange:
_validate_pairdata(pair, pairdata, timerange)
return parse_ticker_dataframe(pairdata, ticker_interval, pair=pair,
fill_missing=fill_up_missing,
drop_incomplete=drop_incomplete)
@ -139,7 +158,7 @@ def load_data(datadir: Path,
pairs: List[str],
refresh_pairs: bool = False,
exchange: Optional[Exchange] = None,
timerange: TimeRange = TimeRange(None, None, 0, 0),
timerange: Optional[TimeRange] = None,
fill_up_missing: bool = True,
) -> Dict[str, DataFrame]:
"""
@ -169,13 +188,20 @@ def pair_data_filename(datadir: Path, pair: str, ticker_interval: str) -> Path:
return filename
def load_cached_data_for_updating(datadir: Path, pair: str, ticker_interval: str,
timerange: Optional[TimeRange]) -> Tuple[List[Any],
Optional[int]]:
def pair_trades_filename(datadir: Path, pair: str) -> Path:
pair_s = pair.replace("/", "_")
filename = datadir.joinpath(f'{pair_s}-trades.json.gz')
return filename
def _load_cached_data_for_updating(datadir: Path, pair: str, ticker_interval: str,
timerange: Optional[TimeRange]) -> Tuple[List[Any],
Optional[int]]:
"""
Load cached data to download more data.
If timerange is passed in, checks wether data from an before the stored data will be downloaded.
If that's the case than what's available should be completely overwritten.
If timerange is passed in, checks whether data from an before the stored data will be
downloaded.
If that's the case then what's available should be completely overwritten.
Only used by download_pair_history().
"""
@ -238,7 +264,7 @@ def download_pair_history(datadir: Path,
f'and store in {datadir}.'
)
data, since_ms = load_cached_data_for_updating(datadir, pair, ticker_interval, timerange)
data, since_ms = _load_cached_data_for_updating(datadir, pair, ticker_interval, timerange)
logger.debug("Current Start: %s", misc.format_ms_time(data[1][0]) if data else 'None')
logger.debug("Current End: %s", misc.format_ms_time(data[-1][0]) if data else 'None')
@ -266,7 +292,7 @@ def download_pair_history(datadir: Path,
def refresh_backtest_ohlcv_data(exchange: Exchange, pairs: List[str], timeframes: List[str],
dl_path: Path, timerange: TimeRange,
dl_path: Path, timerange: Optional[TimeRange] = None,
erase=False) -> List[str]:
"""
Refresh stored ohlcv data for backtesting and hyperopt operations.
@ -294,6 +320,92 @@ def refresh_backtest_ohlcv_data(exchange: Exchange, pairs: List[str], timeframes
return pairs_not_available
def download_trades_history(datadir: Path,
exchange: Exchange,
pair: str,
timerange: Optional[TimeRange] = None) -> bool:
"""
Download trade history from the exchange.
Appends to previously downloaded trades data.
"""
try:
since = timerange.startts * 1000 if timerange and timerange.starttype == 'date' else None
trades = load_trades_file(datadir, pair)
from_id = trades[-1]['id'] if trades else None
logger.debug("Current Start: %s", trades[0]['datetime'] if trades else 'None')
logger.debug("Current End: %s", trades[-1]['datetime'] if trades else 'None')
new_trades = exchange.get_historic_trades(pair=pair,
since=since if since else
int(arrow.utcnow().shift(
days=-30).float_timestamp) * 1000,
# until=xxx,
from_id=from_id,
)
trades.extend(new_trades[1])
store_trades_file(datadir, pair, trades)
logger.debug("New Start: %s", trades[0]['datetime'])
logger.debug("New End: %s", trades[-1]['datetime'])
logger.info(f"New Amount of trades: {len(trades)}")
return True
except Exception as e:
logger.error(
f'Failed to download historic trades for pair: "{pair}". '
f'Error: {e}'
)
return False
def refresh_backtest_trades_data(exchange: Exchange, pairs: List[str], datadir: Path,
timerange: TimeRange, erase=False) -> List[str]:
"""
Refresh stored trades data.
Used by freqtrade download-data
:return: Pairs not available
"""
pairs_not_available = []
for pair in pairs:
if pair not in exchange.markets:
pairs_not_available.append(pair)
logger.info(f"Skipping pair {pair}...")
continue
dl_file = pair_trades_filename(datadir, pair)
if erase and dl_file.exists():
logger.info(
f'Deleting existing data for pair {pair}.')
dl_file.unlink()
logger.info(f'Downloading trades for pair {pair}.')
download_trades_history(datadir=datadir, exchange=exchange,
pair=pair,
timerange=timerange)
return pairs_not_available
def convert_trades_to_ohlcv(pairs: List[str], timeframes: List[str],
datadir: Path, timerange: TimeRange, erase=False) -> None:
"""
Convert stored trades data to ohlcv data
"""
for pair in pairs:
trades = load_trades_file(datadir, pair)
for timeframe in timeframes:
ohlcv_file = pair_data_filename(datadir, pair, timeframe)
if erase and ohlcv_file.exists():
logger.info(f'Deleting existing data for pair {pair}, interval {timeframe}.')
ohlcv_file.unlink()
ohlcv = trades_to_ohlcv(trades, timeframe)
# Store ohlcv
store_tickerdata_file(datadir, pair, timeframe, data=ohlcv)
def get_timeframe(data: Dict[str, DataFrame]) -> Tuple[arrow.Arrow, arrow.Arrow]:
"""
Get the maximum timeframe for the given backtest data

6
freqtrade/edge/__init__.py
View File

@ -77,8 +77,10 @@ class Edge:
self._timerange: TimeRange = TimeRange.parse_timerange("%s-" % arrow.now().shift(
days=-1 * self._since_number_of_days).format('YYYYMMDD'))
self.fee = self.exchange.get_fee()
if config.get('fee'):
self.fee = config['fee']
else:
self.fee = self.exchange.get_fee()
def calculate(self) -> bool:
pairs = self.config['exchange']['pair_whitelist']

5
freqtrade/exchange/__init__.py
View File

@ -1,8 +1,9 @@
from freqtrade.exchange.exchange import Exchange # noqa: F401
from freqtrade.exchange.exchange import Exchange, MAP_EXCHANGE_CHILDCLASS # noqa: F401
from freqtrade.exchange.exchange import (get_exchange_bad_reason, # noqa: F401
is_exchange_bad,
is_exchange_available,
is_exchange_known_ccxt,
is_exchange_officially_supported,
ccxt_exchanges,
available_exchanges)
from freqtrade.exchange.exchange import (timeframe_to_seconds, # noqa: F401
timeframe_to_minutes,

2
freqtrade/exchange/binance.py
View File

@ -16,6 +16,8 @@ class Binance(Exchange):
_ft_has: Dict = {
"stoploss_on_exchange": True,
"order_time_in_force": ['gtc', 'fok', 'ioc'],
"trades_pagination": "id",
"trades_pagination_arg": "fromId",
}
def get_order_book(self, pair: str, limit: int = 100) -> dict:

270
freqtrade/exchange/exchange.py
View File

@ -27,11 +27,86 @@ logger = logging.getLogger(__name__)
API_RETRY_COUNT = 4
BAD_EXCHANGES = {
"bitmex": "Various reasons",
"bitmex": "Various reasons.",
"bitstamp": "Does not provide history. "
"Details in https://github.com/freqtrade/freqtrade/issues/1983",
"hitbtc": "This API cannot be used with Freqtrade. "
"Use `hitbtc2` exchange id to access this exchange.",
**dict.fromkeys([
'adara',
'anxpro',
'bigone',
'coinbase',
'coinexchange',
'coinmarketcap',
'lykke',
'xbtce',
], "Does not provide timeframes. ccxt fetchOHLCV: False"),
**dict.fromkeys([
'bcex',
'bit2c',
'bitbay',
'bitflyer',
'bitforex',
'bithumb',
'bitso',
'bitstamp1',
'bl3p',
'braziliex',
'btcbox',
'btcchina',
'btctradeim',
'btctradeua',
'bxinth',
'chilebit',
'coincheck',
'coinegg',
'coinfalcon',
'coinfloor',
'coingi',
'coinmate',
'coinone',
'coinspot',
'coolcoin',
'crypton',
'deribit',
'exmo',
'exx',
'flowbtc',
'foxbit',
'fybse',
# 'hitbtc',
'ice3x',
'independentreserve',
'indodax',
'itbit',
'lakebtc',
'latoken',
'liquid',
'livecoin',
'luno',
'mixcoins',
'negociecoins',
'nova',
'paymium',
'southxchange',
'stronghold',
'surbitcoin',
'therock',
'tidex',
'vaultoro',
'vbtc',
'virwox',
'yobit',
'zaif',
], "Does not provide timeframes. ccxt fetchOHLCV: emulated"),
}
MAP_EXCHANGE_CHILDCLASS = {
'binanceus': 'binance',
'binanceje': 'binance',
}
def retrier_async(f):
async def wrapper(*args, **kwargs):
@ -72,6 +147,8 @@ def retrier(f):
class Exchange:
_config: Dict = {}
# Parameters to add directly to buy/sell calls (like agreeing to trading agreement)
_params: Dict = {}
# Dict to specify which options each exchange implements
@ -82,6 +159,9 @@ class Exchange:
"order_time_in_force": ["gtc"],
"ohlcv_candle_limit": 500,
"ohlcv_partial_candle": True,
"trades_pagination": "time", # Possible are "time" or "id"
"trades_pagination_arg": "since",
}
_ft_has: Dict = {}
@ -125,6 +205,9 @@ class Exchange:
self._ohlcv_candle_limit = self._ft_has['ohlcv_candle_limit']
self._ohlcv_partial_candle = self._ft_has['ohlcv_partial_candle']
self._trades_pagination = self._ft_has['trades_pagination']
self._trades_pagination_arg = self._ft_has['trades_pagination_arg']
# Initialize ccxt objects
self._api = self._init_ccxt(
exchange_config, ccxt_kwargs=exchange_config.get('ccxt_config'))
@ -133,6 +216,9 @@ class Exchange:
logger.info('Using Exchange "%s"', self.name)
# Check if timeframe is available
self.validate_timeframes(config.get('ticker_interval'))
# Converts the interval provided in minutes in config to seconds
self.markets_refresh_interval: int = exchange_config.get(
"markets_refresh_interval", 60) * 60
@ -144,10 +230,6 @@ class Exchange:
self.validate_ordertypes(config.get('order_types', {}))
self.validate_order_time_in_force(config.get('order_time_in_force', {}))
if config.get('ticker_interval'):
# Check if timeframe is available
self.validate_timeframes(config['ticker_interval'])
def __del__(self):
"""
Destructor - clean up async stuff
@ -165,7 +247,7 @@ class Exchange:
# Find matching class for the given exchange name
name = exchange_config['name']
if not is_exchange_available(name, ccxt_module):
if not is_exchange_known_ccxt(name, ccxt_module):
raise OperationalException(f'Exchange {name} is not supported by ccxt')
ex_config = {
@ -199,6 +281,10 @@ class Exchange:
"""exchange ccxt id"""
return self._api.id
@property
def timeframes(self) -> List[str]:
return list((self._api.timeframes or {}).keys())
@property
def markets(self) -> Dict:
"""exchange ccxt markets"""
@ -291,7 +377,7 @@ class Exchange:
return pair
raise DependencyException(f"Could not combine {curr_1} and {curr_2} to get a valid pair.")
def validate_timeframes(self, timeframe: List[str]) -> None:
def validate_timeframes(self, timeframe: Optional[str]) -> None:
"""
Checks if ticker interval from config is a supported timeframe on the exchange
"""
@ -304,10 +390,9 @@ class Exchange:
f"for the exchange \"{self.name}\" and this exchange "
f"is therefore not supported. ccxt fetchOHLCV: {self.exchange_has('fetchOHLCV')}")
timeframes = self._api.timeframes
if timeframe not in timeframes:
if timeframe and (timeframe not in self.timeframes):
raise OperationalException(
f'Invalid ticker {timeframe}, this Exchange supports {timeframes}')
f"Invalid ticker interval '{timeframe}'. This exchange supports: {self.timeframes}")
def validate_ordertypes(self, order_types: Dict) -> None:
"""
@ -665,6 +750,154 @@ class Exchange:
except ccxt.BaseError as e:
raise OperationalException(f'Could not fetch ticker data. Msg: {e}') from e
@retrier_async
async def _async_fetch_trades(self, pair: str,
since: Optional[int] = None,
params: Optional[dict] = None) -> List[Dict]:
"""
Asyncronously gets trade history using fetch_trades.
Handles exchange errors, does one call to the exchange.
:param pair: Pair to fetch trade data for
:param since: Since as integer timestamp in milliseconds
returns: List of dicts containing trades
"""
try:
# fetch trades asynchronously
if params:
logger.debug("Fetching trades for pair %s, params: %s ", pair, params)
trades = await self._api_async.fetch_trades(pair, params=params, limit=1000)
else:
logger.debug(
"Fetching trades for pair %s, since %s %s...",
pair, since,
'(' + arrow.get(since // 1000).isoformat() + ') ' if since is not None else ''
)
trades = await self._api_async.fetch_trades(pair, since=since, limit=1000)
return trades
except ccxt.NotSupported as e:
raise OperationalException(
f'Exchange {self._api.name} does not support fetching historical trade data.'
f'Message: {e}') from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(f'Could not load trade history due to {e.__class__.__name__}. '
f'Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(f'Could not fetch trade data. Msg: {e}') from e
async def _async_get_trade_history_id(self, pair: str,
until: int,
since: Optional[int] = None,
from_id: Optional[str] = None) -> Tuple[str, List[Dict]]:
"""
Asyncronously gets trade history using fetch_trades
use this when exchange uses id-based iteration (check `self._trades_pagination`)
:param pair: Pair to fetch trade data for
:param since: Since as integer timestamp in milliseconds
:param until: Until as integer timestamp in milliseconds
:param from_id: Download data starting with ID (if id is known). Ignores "since" if set.
returns tuple: (pair, trades-list)
"""
trades: List[Dict] = []
if not from_id:
# Fetch first elements using timebased method to get an ID to paginate on
# Depending on the Exchange, this can introduce a drift at the start of the interval
# of up to an hour.
# e.g. Binance returns the "last 1000" candles within a 1h time interval
# - so we will miss the first trades.
t = await self._async_fetch_trades(pair, since=since)
from_id = t[-1]['id']
trades.extend(t[:-1])
while True:
t = await self._async_fetch_trades(pair,
params={self._trades_pagination_arg: from_id})
if len(t):
# Skip last id since its the key for the next call
trades.extend(t[:-1])
if from_id == t[-1]['id'] or t[-1]['timestamp'] > until:
logger.debug(f"Stopping because from_id did not change. "
f"Reached {t[-1]['timestamp']} > {until}")
# Reached the end of the defined-download period - add last trade as well.
trades.extend(t[-1:])
break
from_id = t[-1]['id']
else:
break
return (pair, trades)
async def _async_get_trade_history_time(self, pair: str, until: int,
since: Optional[int] = None) -> Tuple[str, List]:
"""
Asyncronously gets trade history using fetch_trades,
when the exchange uses time-based iteration (check `self._trades_pagination`)
:param pair: Pair to fetch trade data for
:param since: Since as integer timestamp in milliseconds
:param until: Until as integer timestamp in milliseconds
returns tuple: (pair, trades-list)
"""
trades: List[Dict] = []
while True:
t = await self._async_fetch_trades(pair, since=since)
if len(t):
since = t[-1]['timestamp']
trades.extend(t)
# Reached the end of the defined-download period
if until and t[-1]['timestamp'] > until:
logger.debug(
f"Stopping because until was reached. {t[-1]['timestamp']} > {until}")
break
else:
break
return (pair, trades)
async def _async_get_trade_history(self, pair: str,
since: Optional[int] = None,
until: Optional[int] = None,
from_id: Optional[str] = None) -> Tuple[str, List[Dict]]:
"""
Async wrapper handling downloading trades using either time or id based methods.
"""
if self._trades_pagination == 'time':
return await self._async_get_trade_history_time(
pair=pair, since=since,
until=until or ccxt.Exchange.milliseconds())
elif self._trades_pagination == 'id':
return await self._async_get_trade_history_id(
pair=pair, since=since,
until=until or ccxt.Exchange.milliseconds(), from_id=from_id
)
else:
raise OperationalException(f"Exchange {self.name} does use neither time, "
f"nor id based pagination")
def get_historic_trades(self, pair: str,
since: Optional[int] = None,
until: Optional[int] = None,
from_id: Optional[str] = None) -> Tuple[str, List]:
"""
Gets candle history using asyncio and returns the list of candles.
Handles all async doing.
Async over one pair, assuming we get `_ohlcv_candle_limit` candles per call.
:param pair: Pair to download
:param ticker_interval: Interval to get
:param since: Timestamp in milliseconds to get history from
:param until: Timestamp in milliseconds. Defaults to current timestamp if not defined.
:param from_id: Download data starting with ID (if id is known)
:returns List of tickers
"""
if not self.exchange_has("fetchTrades"):
raise OperationalException("This exchange does not suport downloading Trades.")
return asyncio.get_event_loop().run_until_complete(
self._async_get_trade_history(pair=pair, since=since,
until=until, from_id=from_id))
@retrier
def cancel_order(self, order_id: str, pair: str) -> None:
if self._config['dry_run']:
@ -768,18 +1001,29 @@ def get_exchange_bad_reason(exchange_name: str) -> str:
return BAD_EXCHANGES.get(exchange_name, "")
def is_exchange_available(exchange_name: str, ccxt_module=None) -> bool:
return exchange_name in available_exchanges(ccxt_module)
def is_exchange_known_ccxt(exchange_name: str, ccxt_module=None) -> bool:
return exchange_name in ccxt_exchanges(ccxt_module)
def is_exchange_officially_supported(exchange_name: str) -> bool:
return exchange_name in ['bittrex', 'binance']
def available_exchanges(ccxt_module=None) -> List[str]:
def ccxt_exchanges(ccxt_module=None) -> List[str]:
"""
Return the list of all exchanges known to ccxt
"""
return ccxt_module.exchanges if ccxt_module is not None else ccxt.exchanges
def available_exchanges(ccxt_module=None) -> List[str]:
"""
Return exchanges available to the bot, i.e. non-bad exchanges in the ccxt list
"""
exchanges = ccxt_exchanges(ccxt_module)
return [x for x in exchanges if not is_exchange_bad(x)]
def timeframe_to_seconds(ticker_interval: str) -> int:
"""
Translates the timeframe interval value written in the human readable

4
freqtrade/exchange/kraken.py
View File

@ -14,6 +14,10 @@ logger = logging.getLogger(__name__)
class Kraken(Exchange):
_params: Dict = {"trading_agreement": "agree"}
_ft_has: Dict = {
"trades_pagination": "id",
"trades_pagination_arg": "since",
}
@retrier
def get_balances(self) -> dict:

138
freqtrade/freqtradebot.py
View File

@ -1,7 +1,6 @@
"""
Freqtrade is the main module of this bot. It contains the class Freqtrade()
"""
import copy
import logging
import traceback
@ -12,7 +11,7 @@ from typing import Any, Dict, List, Optional, Tuple
import arrow
from requests.exceptions import RequestException
from freqtrade import (DependencyException, OperationalException, InvalidOrderException,
from freqtrade import (DependencyException, InvalidOrderException,
__version__, constants, persistence)
from freqtrade.data.converter import order_book_to_dataframe
from freqtrade.data.dataprovider import DataProvider
@ -135,12 +134,11 @@ class FreqtradeBot:
self.strategy.informative_pairs())
# First process current opened trades
for trade in trades:
self.process_maybe_execute_sell(trade)
self.process_maybe_execute_sells(trades)
# Then looking for buy opportunities
if len(trades) < self.config['max_open_trades']:
self.process_maybe_execute_buy()
self.process_maybe_execute_buys()
if 'unfilledtimeout' in self.config:
# Check and handle any timed out open orders
@ -262,11 +260,10 @@ class FreqtradeBot:
Checks pairs as long as the open trade count is below `max_open_trades`.
:return: True if at least one trade has been created.
"""
interval = self.strategy.ticker_interval
whitelist = copy.deepcopy(self.active_pair_whitelist)
if not whitelist:
logger.warning("Whitelist is empty.")
logger.info("Active pair whitelist is empty.")
return False
# Remove currently opened and latest pairs from whitelist
@ -276,7 +273,8 @@ class FreqtradeBot:
logger.debug('Ignoring %s in pair whitelist', trade.pair)
if not whitelist:
logger.info("No currency pair in whitelist, but checking to sell open trades.")
logger.info("No currency pair in active pair whitelist, "
"but checking to sell open trades.")
return False
buycount = 0
@ -285,8 +283,10 @@ class FreqtradeBot:
if self.strategy.is_pair_locked(_pair):
logger.info(f"Pair {_pair} is currently locked.")
continue
(buy, sell) = self.strategy.get_signal(
_pair, interval, self.dataprovider.ohlcv(_pair, self.strategy.ticker_interval))
_pair, self.strategy.ticker_interval,
self.dataprovider.ohlcv(_pair, self.strategy.ticker_interval))
if buy and not sell and len(Trade.get_open_trades()) < self.config['max_open_trades']:
stake_amount = self._get_trade_stake_amount(_pair)
@ -431,10 +431,9 @@ class FreqtradeBot:
return True
def process_maybe_execute_buy(self) -> None:
def process_maybe_execute_buys(self) -> None:
"""
Tries to execute a buy trade in a safe way
:return: True if executed
Tries to execute buy orders for trades in a safe way
"""
try:
# Create entity and execute trade
@ -443,40 +442,37 @@ class FreqtradeBot:
except DependencyException as exception:
logger.warning('Unable to create trade: %s', exception)
def process_maybe_execute_sell(self, trade: Trade) -> bool:
def process_maybe_execute_sells(self, trades: List[Any]) -> None:
"""
Tries to execute a sell trade
:return: True if executed
Tries to execute sell orders for trades in a safe way
"""
try:
self.update_trade_state(trade)
result = False
for trade in trades:
try:
self.update_trade_state(trade)
if self.strategy.order_types.get('stoploss_on_exchange') and trade.is_open:
result = self.handle_stoploss_on_exchange(trade)
if result:
self.wallets.update()
return result
if trade.is_open and trade.open_order_id is None:
if (self.strategy.order_types.get('stoploss_on_exchange') and
self.handle_stoploss_on_exchange(trade)):
result = True
continue
# Check if we can sell our current pair
result = self.handle_trade(trade)
if trade.open_order_id is None and self.handle_trade(trade):
result = True
# Updating wallets if any trade occured
if result:
self.wallets.update()
except DependencyException as exception:
logger.warning('Unable to sell trade: %s', exception)
return result
# Updating wallets if any trade occured
if result:
self.wallets.update()
except DependencyException as exception:
logger.warning('Unable to sell trade: %s', exception)
return False
def get_real_amount(self, trade: Trade, order: Dict) -> float:
def get_real_amount(self, trade: Trade, order: Dict, order_amount: float = None) -> float:
"""
Get real amount for the trade
Necessary for exchanges which charge fees in base currency (e.g. binance)
"""
order_amount = order['amount']
if order_amount is None:
order_amount = order['amount']
# Only run for closed orders
if trade.fee_open == 0 or order['status'] == 'open':
return order_amount
@ -513,7 +509,7 @@ class FreqtradeBot:
if not isclose(amount, order_amount, abs_tol=constants.MATH_CLOSE_PREC):
logger.warning(f"Amount {amount} does not match amount {trade.amount}")
raise OperationalException("Half bought? Amounts don't match")
raise DependencyException("Half bought? Amounts don't match")
real_amount = amount - fee_abs
if fee_abs != 0:
logger.info(f"Applying fee on amount for {trade} "
@ -541,7 +537,7 @@ class FreqtradeBot:
# Fee was applied, so set to 0
trade.fee_open = 0
except OperationalException as exception:
except DependencyException as exception:
logger.warning("Could not update trade amount: %s", exception)
trade.update(order)
@ -575,18 +571,20 @@ class FreqtradeBot:
:return: True if trade has been sold, False otherwise
"""
if not trade.is_open:
raise ValueError(f'Attempt to handle closed trade: {trade}')
raise DependencyException(f'Attempt to handle closed trade: {trade}')
logger.debug('Handling %s ...', trade)
(buy, sell) = (False, False)
experimental = self.config.get('experimental', {})
if experimental.get('use_sell_signal') or experimental.get('ignore_roi_if_buy_signal'):
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')):
(buy, sell) = self.strategy.get_signal(
trade.pair, self.strategy.ticker_interval,
self.dataprovider.ohlcv(trade.pair, self.strategy.ticker_interval))
config_ask_strategy = self.config.get('ask_strategy', {})
if config_ask_strategy.get('use_order_book', False):
logger.info('Using order book for selling...')
# logger.debug('Order book %s',orderBook)
@ -708,7 +706,7 @@ class FreqtradeBot:
if trade.stop_loss > float(order['info']['stopPrice']):
# we check if the update is neccesary
update_beat = self.strategy.order_types.get('stoploss_on_exchange_interval', 60)
if (datetime.utcnow() - trade.stoploss_last_update).total_seconds() > update_beat:
if (datetime.utcnow() - trade.stoploss_last_update).total_seconds() >= update_beat:
# cancelling the current stoploss on exchange first
logger.info('Trailing stoploss: cancelling current stoploss on exchange (id:{%s})'
'in order to add another one ...', order['id'])
@ -750,8 +748,8 @@ class FreqtradeBot:
"""
buy_timeout = self.config['unfilledtimeout']['buy']
sell_timeout = self.config['unfilledtimeout']['sell']
buy_timeoutthreashold = arrow.utcnow().shift(minutes=-buy_timeout).datetime
sell_timeoutthreashold = arrow.utcnow().shift(minutes=-sell_timeout).datetime
buy_timeout_threshold = arrow.utcnow().shift(minutes=-buy_timeout).datetime
sell_timeout_threshold = arrow.utcnow().shift(minutes=-sell_timeout).datetime
for trade in Trade.query.filter(Trade.open_order_id.isnot(None)).all():
try:
@ -775,21 +773,18 @@ class FreqtradeBot:
self.wallets.update()
continue
# Handle cancelled on exchange
if order['status'] == 'canceled':
if order['side'] == 'buy':
self.handle_buy_order_full_cancel(trade, "canceled on Exchange")
elif order['side'] == 'sell':
self.handle_timedout_limit_sell(trade, order)
self.wallets.update()
# Check if order is still actually open
elif order['status'] == 'open':
if order['side'] == 'buy' and ordertime < buy_timeoutthreashold:
self.handle_timedout_limit_buy(trade, order)
self.wallets.update()
elif order['side'] == 'sell' and ordertime < sell_timeoutthreashold:
self.handle_timedout_limit_sell(trade, order)
self.wallets.update()
if ((order['side'] == 'buy' and order['status'] == 'canceled')
or (order['status'] == 'open'
and order['side'] == 'buy' and ordertime < buy_timeout_threshold)):
self.handle_timedout_limit_buy(trade, order)
self.wallets.update()
elif ((order['side'] == 'sell' and order['status'] == 'canceled')
or (order['status'] == 'open'
and order['side'] == 'sell' and ordertime < sell_timeout_threshold)):
self.handle_timedout_limit_sell(trade, order)
self.wallets.update()
def handle_buy_order_full_cancel(self, trade: Trade, reason: str) -> None:
"""Close trade in database and send message"""
@ -805,16 +800,33 @@ class FreqtradeBot:
"""Buy timeout - cancel order
:return: True if order was fully cancelled
"""
self.exchange.cancel_order(trade.open_order_id, trade.pair)
if order['remaining'] == order['amount']:
reason = "cancelled due to timeout"
if order['status'] != 'canceled':
corder = self.exchange.cancel_order(trade.open_order_id, trade.pair)
else:
# Order was cancelled already, so we can reuse the existing dict
corder = order
reason = "canceled on Exchange"
if corder['remaining'] == corder['amount']:
# if trade is not partially completed, just delete the trade
self.handle_buy_order_full_cancel(trade, "cancelled due to timeout")
self.handle_buy_order_full_cancel(trade, reason)
return True
# if trade is partially complete, edit the stake details for the trade
# and close the order
trade.amount = order['amount'] - order['remaining']
trade.amount = corder['amount'] - corder['remaining']
trade.stake_amount = trade.amount * trade.open_rate
# verify if fees were taken from amount to avoid problems during selling
try:
new_amount = self.get_real_amount(trade, corder, trade.amount)
if not isclose(order['amount'], new_amount, abs_tol=constants.MATH_CLOSE_PREC):
trade.amount = new_amount
# Fee was applied, so set to 0
trade.fee_open = 0
except DependencyException as e:
logger.warning("Could not update trade amount: %s", e)
trade.open_order_id = None
logger.info('Partial buy order timeout for %s.', trade)
self.rpc.send_msg({

40
freqtrade/indicator_helpers.py
View File

@ -1,40 +0,0 @@
from math import cos, exp, pi, sqrt
import numpy as np
import talib as ta
from pandas import Series
def went_up(series: Series) -> bool:
return series > series.shift(1)
def went_down(series: Series) -> bool:
return series < series.shift(1)
def ehlers_super_smoother(series: Series, smoothing: float = 6) -> Series:
magic = pi * sqrt(2) / smoothing
a1 = exp(-magic)
coeff2 = 2 * a1 * cos(magic)
coeff3 = -a1 * a1
coeff1 = (1 - coeff2 - coeff3) / 2
filtered = series.copy()
for i in range(2, len(series)):
filtered.iloc[i] = coeff1 * (series.iloc[i] + series.iloc[i-1]) + \
coeff2 * filtered.iloc[i-1] + coeff3 * filtered.iloc[i-2]
return filtered
def fishers_inverse(series: Series, smoothing: float = 0) -> np.ndarray:
""" Does a smoothed fishers inverse transformation.
Can be used with any oscillator that goes from 0 to 100 like RSI or MFI """
v1 = 0.1 * (series - 50)
if smoothing > 0:
v2 = ta.WMA(v1.values, timeperiod=smoothing)
else:
v2 = v1
return (np.exp(2 * v2)-1) / (np.exp(2 * v2) + 1)

6
freqtrade/misc.py
View File

@ -72,8 +72,10 @@ def json_load(datafile: IO):
def file_load_json(file):
gzipfile = file.with_suffix(file.suffix + '.gz')
if file.suffix != ".gz":
gzipfile = file.with_suffix(file.suffix + '.gz')
else:
gzipfile = file
# Try gzip file first, otherwise regular json file.
if gzipfile.is_file():
logger.debug('Loading ticker data from file %s', gzipfile)

20
freqtrade/optimize/backtesting.py
View File

@ -63,9 +63,12 @@ class Backtesting:
self.config['exchange']['uid'] = ''
self.config['dry_run'] = True
self.strategylist: List[IStrategy] = []
self.exchange = ExchangeResolver(self.config['exchange']['name'], self.config).exchange
self.fee = self.exchange.get_fee()
if config.get('fee'):
self.fee = config['fee']
else:
self.fee = self.exchange.get_fee()
if self.config.get('runmode') != RunMode.HYPEROPT:
self.dataprovider = DataProvider(self.config, self.exchange)
@ -146,8 +149,8 @@ class Backtesting:
len(results[results.profit_abs < 0])
])
# Ignore type as floatfmt does allow tuples but mypy does not know that
return tabulate(tabular_data, headers=headers, # type: ignore
floatfmt=floatfmt, tablefmt="pipe")
return tabulate(tabular_data, headers=headers,
floatfmt=floatfmt, tablefmt="pipe") # type: ignore
def _generate_text_table_sell_reason(self, data: Dict[str, Dict], results: DataFrame) -> str:
"""
@ -185,8 +188,8 @@ class Backtesting:
len(results[results.profit_abs < 0])
])
# Ignore type as floatfmt does allow tuples but mypy does not know that
return tabulate(tabular_data, headers=headers, # type: ignore
floatfmt=floatfmt, tablefmt="pipe")
return tabulate(tabular_data, headers=headers,
floatfmt=floatfmt, tablefmt="pipe") # type: ignore
def _store_backtest_result(self, recordfilename: Path, results: DataFrame,
strategyname: Optional[str] = None) -> None:
@ -267,6 +270,11 @@ class Backtesting:
# - (Expected abs profit + open_rate + open_fee) / (fee_close -1)
closerate = - (trade.open_rate * roi + trade.open_rate *
(1 + trade.fee_open)) / (trade.fee_close - 1)
# Use the maximum between closerate and low as we
# cannot sell outside of a candle.
# Applies when using {"xx": -1} as roi to force sells after xx minutes
closerate = max(closerate, sell_row.low)
else:
# This should not be reached...
closerate = sell_row.open

2
freqtrade/optimize/default_hyperopt.py
View File

@ -11,7 +11,7 @@ import freqtrade.vendor.qtpylib.indicators as qtpylib
from freqtrade.optimize.hyperopt_interface import IHyperOpt
class DefaultHyperOpts(IHyperOpt):
class DefaultHyperOpt(IHyperOpt):
"""
Default hyperopt provided by the Freqtrade bot.
You can override it with your own Hyperopt

4
freqtrade/optimize/edge_cli.py
View File

@ -69,8 +69,8 @@ class EdgeCli:
])
# Ignore type as floatfmt does allow tuples but mypy does not know that
return tabulate(tabular_data, headers=headers, # type: ignore
floatfmt=floatfmt, tablefmt="pipe")
return tabulate(tabular_data, headers=headers,
floatfmt=floatfmt, tablefmt="pipe") # type: ignore
def start(self) -> None:
result = self.edge.calculate()

8
freqtrade/optimize/hyperopt.py
View File

@ -98,10 +98,10 @@ class Hyperopt:
self.position_stacking = self.config.get('position_stacking', False)
if self.has_space('sell'):
# Make sure experimental is enabled
if 'experimental' not in self.config:
self.config['experimental'] = {}
self.config['experimental']['use_sell_signal'] = True
# Make sure use_sell_signal is enabled
if 'ask_strategy' not in self.config:
self.config['ask_strategy'] = {}
self.config['ask_strategy']['use_sell_signal'] = True
@staticmethod
def get_lock_filename(config) -> str:

29
freqtrade/plot/plotting.py
View File

@ -64,14 +64,13 @@ def add_indicators(fig, row, indicators: List[str], data: pd.DataFrame) -> make_
"""
for indicator in indicators:
if indicator in data:
# TODO: Figure out why scattergl causes problems
scattergl = go.Scatter(
scatter = go.Scatter(
x=data['date'],
y=data[indicator].values,
mode='lines',
name=indicator
)
fig.add_trace(scattergl, row, 1)
fig.add_trace(scatter, row, 1)
else:
logger.info(
'Indicator "%s" ignored. Reason: This indicator is not found '
@ -92,7 +91,7 @@ def add_profit(fig, row, data: pd.DataFrame, column: str, name: str) -> make_sub
:param name: Name to use
:return: fig with added profit plot
"""
profit = go.Scattergl(
profit = go.Scatter(
x=data.index,
y=data[column],
name=name,
@ -221,23 +220,27 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
else:
logger.warning("No sell-signals found.")
# TODO: Figure out why scattergl causes problems plotly/plotly.js#2284
if 'bb_lowerband' in data and 'bb_upperband' in data:
bb_lower = go.Scattergl(
bb_lower = go.Scatter(
x=data.date,
y=data.bb_lowerband,
name='BB lower',
showlegend=False,
line={'color': 'rgba(255,255,255,0)'},
)
bb_upper = go.Scattergl(
bb_upper = go.Scatter(
x=data.date,
y=data.bb_upperband,
name='BB upper',
name='Bollinger Band',
fill="tonexty",
fillcolor="rgba(0,176,246,0.2)",
line={'color': 'rgba(255,255,255,0)'},
)
fig.add_trace(bb_lower, 1, 1)
fig.add_trace(bb_upper, 1, 1)
if 'bb_upperband' in indicators1 and 'bb_lowerband' in indicators1:
indicators1.remove('bb_upperband')
indicators1.remove('bb_lowerband')
# Add indicators to main plot
fig = add_indicators(fig=fig, row=1, indicators=indicators1, data=data)
@ -248,11 +251,13 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
volume = go.Bar(
x=data['date'],
y=data['volume'],
name='Volume'
)
name='Volume',
marker_color='DarkSlateGrey',
marker_line_color='DarkSlateGrey'
)
fig.add_trace(volume, 2, 1)
# Add indicators to seperate row
# Add indicators to separate row
fig = add_indicators(fig=fig, row=3, indicators=indicators2, data=data)
return fig
@ -267,7 +272,7 @@ def generate_profit_graph(pairs: str, tickers: Dict[str, pd.DataFrame],
df_comb = create_cum_profit(df_comb, trades, 'cum_profit')
# Plot the pairs average close prices, and total profit growth
avgclose = go.Scattergl(
avgclose = go.Scatter(
x=df_comb.index,
y=df_comb['mean'],
name='Avg close price',

4
freqtrade/resolvers/exchange_resolver.py
View File

@ -3,7 +3,7 @@ This module loads custom exchanges
"""
import logging
from freqtrade.exchange import Exchange
from freqtrade.exchange import Exchange, MAP_EXCHANGE_CHILDCLASS
import freqtrade.exchange as exchanges
from freqtrade.resolvers import IResolver
@ -22,6 +22,8 @@ class ExchangeResolver(IResolver):
Load the custom class from config parameter
:param config: configuration dictionary
"""
# Map exchange name to avoid duplicate classes for identical exchanges
exchange_name = MAP_EXCHANGE_CHILDCLASS.get(exchange_name, exchange_name)
exchange_name = exchange_name.title()
try:
self.exchange = self._load_exchange(exchange_name, kwargs={'config': config})

20
freqtrade/resolvers/hyperopt_resolver.py
View File

@ -54,14 +54,8 @@ class HyperOptResolver(IResolver):
"""
current_path = Path(__file__).parent.parent.joinpath('optimize').resolve()
abs_paths = [
config['user_data_dir'].joinpath('hyperopts'),
current_path,
]
if extra_dir:
# Add extra hyperopt directory on top of search paths
abs_paths.insert(0, Path(extra_dir).resolve())
abs_paths = self.build_search_paths(config, current_path=current_path,
user_subdir='hyperopts', extra_dir=extra_dir)
hyperopt = self._load_object(paths=abs_paths, object_type=IHyperOpt,
object_name=hyperopt_name, kwargs={'config': config})
@ -112,14 +106,8 @@ class HyperOptLossResolver(IResolver):
"""
current_path = Path(__file__).parent.parent.joinpath('optimize').resolve()
abs_paths = [
config['user_data_dir'].joinpath('hyperopts'),
current_path,
]
if extra_dir:
# Add extra hyperopt directory on top of search paths
abs_paths.insert(0, Path(extra_dir).resolve())
abs_paths = self.build_search_paths(config, current_path=current_path,
user_subdir='hyperopts', extra_dir=extra_dir)
hyperoptloss = self._load_object(paths=abs_paths, object_type=IHyperOptLoss,
object_name=hyper_loss_name)

30
freqtrade/resolvers/iresolver.py
View File

@ -7,7 +7,7 @@ import importlib.util
import inspect
import logging
from pathlib import Path
from typing import Any, List, Optional, Tuple, Type, Union
from typing import Any, List, Optional, Tuple, Union, Generator
logger = logging.getLogger(__name__)
@ -17,15 +17,29 @@ class IResolver:
This class contains all the logic to load custom classes
"""
def build_search_paths(self, config, current_path: Path, user_subdir: str,
extra_dir: Optional[str] = None) -> List[Path]:
abs_paths = [
config['user_data_dir'].joinpath(user_subdir),
current_path,
]
if extra_dir:
# Add extra directory to the top of the search paths
abs_paths.insert(0, Path(extra_dir).resolve())
return abs_paths
@staticmethod
def _get_valid_object(object_type, module_path: Path,
object_name: str) -> Optional[Type[Any]]:
object_name: str) -> Generator[Any, None, None]:
"""
Returns the first object with matching object_type and object_name in the path given.
Generator returning objects with matching object_type and object_name in the path given.
:param object_type: object_type (class)
:param module_path: absolute path to the module
:param object_name: Class name of the object
:return: class or None
:return: generator containing matching objects
"""
# Generate spec based on absolute path
@ -42,7 +56,7 @@ class IResolver:
obj for name, obj in inspect.getmembers(module, inspect.isclass)
if object_name == name and object_type in obj.__bases__
)
return next(valid_objects_gen, None)
return valid_objects_gen
@staticmethod
def _search_object(directory: Path, object_type, object_name: str,
@ -59,9 +73,9 @@ class IResolver:
logger.debug('Ignoring %s', entry)
continue
module_path = entry.resolve()
obj = IResolver._get_valid_object(
object_type, module_path, object_name
)
obj = next(IResolver._get_valid_object(object_type, module_path, object_name), None)
if obj:
return (obj(**kwargs), module_path)
return (None, None)

10
freqtrade/resolvers/pairlist_resolver.py
View File

@ -1,7 +1,7 @@
# pragma pylint: disable=attribute-defined-outside-init
"""
This module load custom hyperopts
This module load custom pairlists
"""
import logging
from pathlib import Path
@ -15,7 +15,7 @@ logger = logging.getLogger(__name__)
class PairListResolver(IResolver):
"""
This class contains all the logic to load custom hyperopt class
This class contains all the logic to load custom PairList class
"""
__slots__ = ['pairlist']
@ -39,10 +39,8 @@ class PairListResolver(IResolver):
"""
current_path = Path(__file__).parent.parent.joinpath('pairlist').resolve()
abs_paths = [
config['user_data_dir'].joinpath('pairlist'),
current_path,
]
abs_paths = self.build_search_paths(config, current_path=current_path,
user_subdir='pairlist', extra_dir=None)
pairlist = self._load_object(paths=abs_paths, object_type=IPairList,
object_name=pairlist_name, kwargs=kwargs)

35
freqtrade/resolvers/strategy_resolver.py
View File

@ -41,13 +41,13 @@ class StrategyResolver(IResolver):
config=config,
extra_dir=config.get('strategy_path'))
# make sure experimental dict is available
if 'experimental' not in config:
config['experimental'] = {}
# make sure ask_strategy dict is available
if 'ask_strategy' not in config:
config['ask_strategy'] = {}
# Set attributes
# Check if we need to override configuration
# (Attribute name, default, experimental)
# (Attribute name, default, ask_strategy)
attributes = [("minimal_roi", {"0": 10.0}, False),
("ticker_interval", None, False),
("stoploss", None, False),
@ -60,20 +60,20 @@ class StrategyResolver(IResolver):
("order_time_in_force", None, False),
("stake_currency", None, False),
("stake_amount", None, False),
("use_sell_signal", False, True),
("use_sell_signal", True, True),
("sell_profit_only", False, True),
("ignore_roi_if_buy_signal", False, True),
]
for attribute, default, experimental in attributes:
if experimental:
self._override_attribute_helper(config['experimental'], attribute, default)
for attribute, default, ask_strategy in attributes:
if ask_strategy:
self._override_attribute_helper(config['ask_strategy'], attribute, default)
else:
self._override_attribute_helper(config, attribute, default)
# Loop this list again to have output combined
for attribute, _, exp in attributes:
if exp and attribute in config['experimental']:
logger.info("Strategy using %s: %s", attribute, config['experimental'][attribute])
if exp and attribute in config['ask_strategy']:
logger.info("Strategy using %s: %s", attribute, config['ask_strategy'][attribute])
elif attribute in config:
logger.info("Strategy using %s: %s", attribute, config[attribute])
@ -98,7 +98,10 @@ class StrategyResolver(IResolver):
logger.info("Override strategy '%s' with value in config file: %s.",
attribute, config[attribute])
elif hasattr(self.strategy, attribute):
config[attribute] = getattr(self.strategy, attribute)
val = getattr(self.strategy, attribute)
# None's cannot exist in the config, so do not copy them
if val is not None:
config[attribute] = val
# Explicitly check for None here as other "falsy" values are possible
elif default is not None:
setattr(self.strategy, attribute, default)
@ -124,14 +127,8 @@ class StrategyResolver(IResolver):
"""
current_path = Path(__file__).parent.parent.joinpath('strategy').resolve()
abs_paths = [
config['user_data_dir'].joinpath('strategies'),
current_path,
]
if extra_dir:
# Add extra strategy directory on top of search paths
abs_paths.insert(0, Path(extra_dir).resolve())
abs_paths = self.build_search_paths(config, current_path=current_path,
user_subdir='strategies', extra_dir=extra_dir)
if ":" in strategy_name:
logger.info("loading base64 encoded strategy")

2
freqtrade/rpc/rpc_manager.py
View File

@ -18,7 +18,7 @@ class RPCManager:
self.registered_modules: List[RPC] = []
# Enable telegram
if freqtrade.config['telegram'].get('enabled', False):
if freqtrade.config.get('telegram', {}).get('enabled', False):
logger.info('Enabling rpc.telegram ...')
from freqtrade.rpc.telegram import Telegram
self.registered_modules.append(Telegram(freqtrade))

25
freqtrade/strategy/interface.py
View File

@ -78,8 +78,8 @@ class IStrategy(ABC):
# trailing stoploss
trailing_stop: bool = False
trailing_stop_positive: float
trailing_stop_positive_offset: float
trailing_stop_positive: Optional[float] = None
trailing_stop_positive_offset: float = 0.0
trailing_only_offset_is_reached = False
# associated ticker interval
@ -309,9 +309,9 @@ class IStrategy(ABC):
# Set current rate to high for backtesting sell
current_rate = high or rate
current_profit = trade.calc_profit_percent(current_rate)
experimental = self.config.get('experimental', {})
config_ask_strategy = self.config.get('ask_strategy', {})
if buy and experimental.get('ignore_roi_if_buy_signal', False):
if buy and config_ask_strategy.get('ignore_roi_if_buy_signal', False):
# This one is noisy, commented out
# logger.debug(f"{trade.pair} - Buy signal still active. sell_flag=False")
return SellCheckTuple(sell_flag=False, sell_type=SellType.NONE)
@ -322,7 +322,7 @@ class IStrategy(ABC):
f"sell_type=SellType.ROI")
return SellCheckTuple(sell_flag=True, sell_type=SellType.ROI)
if experimental.get('sell_profit_only', False):
if config_ask_strategy.get('sell_profit_only', False):
# This one is noisy, commented out
# logger.debug(f"{trade.pair} - Checking if trade is profitable...")
if trade.calc_profit(rate=rate) <= 0:
@ -330,7 +330,7 @@ class IStrategy(ABC):
# logger.debug(f"{trade.pair} - Trade is not profitable. sell_flag=False")
return SellCheckTuple(sell_flag=False, sell_type=SellType.NONE)
if sell and not buy and experimental.get('use_sell_signal', False):
if sell and not buy and config_ask_strategy.get('use_sell_signal', True):
logger.debug(f"{trade.pair} - Sell signal received. sell_flag=True, "
f"sell_type=SellType.SELL_SIGNAL")
return SellCheckTuple(sell_flag=True, sell_type=SellType.SELL_SIGNAL)
@ -347,26 +347,23 @@ class IStrategy(ABC):
decides to sell or not
:param current_profit: current profit in percent
"""
trailing_stop = self.config.get('trailing_stop', False)
stop_loss_value = force_stoploss if force_stoploss else self.stoploss
# Initiate stoploss with open_rate. Does nothing if stoploss is already set.
trade.adjust_stop_loss(trade.open_rate, stop_loss_value, initial=True)
if trailing_stop:
if self.trailing_stop:
# trailing stoploss handling
sl_offset = self.config.get('trailing_stop_positive_offset') or 0.0
tsl_only_offset = self.config.get('trailing_only_offset_is_reached', False)
sl_offset = self.trailing_stop_positive_offset
# Make sure current_profit is calculated using high for backtesting.
high_profit = current_profit if not high else trade.calc_profit_percent(high)
# Don't update stoploss if trailing_only_offset_is_reached is true.
if not (tsl_only_offset and high_profit < sl_offset):
if not (self.trailing_only_offset_is_reached and high_profit < sl_offset):
# Specific handling for trailing_stop_positive
if 'trailing_stop_positive' in self.config and high_profit > sl_offset:
# Ignore mypy error check in configuration that this is a float
stop_loss_value = self.config.get('trailing_stop_positive') # type: ignore
if self.trailing_stop_positive is not None and high_profit > sl_offset:
stop_loss_value = self.trailing_stop_positive
logger.debug(f"{trade.pair} - Using positive stoploss: {stop_loss_value} "
f"offset: {sl_offset:.4g} profit: {current_profit:.4f}%")

50
freqtrade/utils.py
View File

@ -8,8 +8,10 @@ import arrow
from freqtrade import OperationalException
from freqtrade.configuration import Configuration, TimeRange
from freqtrade.configuration.directory_operations import create_userdata_dir
from freqtrade.data.history import refresh_backtest_ohlcv_data
from freqtrade.exchange import available_exchanges
from freqtrade.data.history import (convert_trades_to_ohlcv,
refresh_backtest_ohlcv_data,
refresh_backtest_trades_data)
from freqtrade.exchange import available_exchanges, ccxt_exchanges
from freqtrade.resolvers import ExchangeResolver
from freqtrade.state import RunMode
@ -50,12 +52,14 @@ def start_list_exchanges(args: Dict[str, Any]) -> None:
:param args: Cli args from Arguments()
:return: None
"""
exchanges = ccxt_exchanges() if args['list_exchanges_all'] else available_exchanges()
if args['print_one_column']:
print('\n'.join(available_exchanges()))
print('\n'.join(exchanges))
else:
print(f"Exchanges supported by ccxt and available for Freqtrade: "
f"{', '.join(available_exchanges())}")
if args['list_exchanges_all']:
print(f"All exchanges supported by the ccxt library: {', '.join(exchanges)}")
else:
print(f"Exchanges available for Freqtrade: {', '.join(exchanges)}")
def start_create_userdir(args: Dict[str, Any]) -> None:
@ -97,9 +101,19 @@ def start_download_data(args: Dict[str, Any]) -> None:
# Init exchange
exchange = ExchangeResolver(config['exchange']['name'], config).exchange
pairs_not_available = refresh_backtest_ohlcv_data(
exchange, pairs=config["pairs"], timeframes=config["timeframes"],
dl_path=Path(config['datadir']), timerange=timerange, erase=config.get("erase"))
if config.get('download_trades'):
pairs_not_available = refresh_backtest_trades_data(
exchange, pairs=config["pairs"], datadir=Path(config['datadir']),
timerange=timerange, erase=config.get("erase"))
# Convert downloaded trade data to different timeframes
convert_trades_to_ohlcv(
pairs=config["pairs"], timeframes=config["timeframes"],
datadir=Path(config['datadir']), timerange=timerange, erase=config.get("erase"))
else:
pairs_not_available = refresh_backtest_ohlcv_data(
exchange, pairs=config["pairs"], timeframes=config["timeframes"],
dl_path=Path(config['datadir']), timerange=timerange, erase=config.get("erase"))
except KeyboardInterrupt:
sys.exit("SIGINT received, aborting ...")
@ -108,3 +122,21 @@ def start_download_data(args: Dict[str, Any]) -> None:
if pairs_not_available:
logger.info(f"Pairs [{','.join(pairs_not_available)}] not available "
f"on exchange {config['exchange']['name']}.")
def start_list_timeframes(args: Dict[str, Any]) -> None:
"""
Print ticker intervals (timeframes) available on Exchange
"""
config = setup_utils_configuration(args, RunMode.OTHER)
# Do not use ticker_interval set in the config
config['ticker_interval'] = None
# Init exchange
exchange = ExchangeResolver(config['exchange']['name'], config).exchange
if args['print_one_column']:
print('\n'.join(exchange.timeframes))
else:
print(f"Timeframes available for the exchange `{config['exchange']['name']}`: "
f"{', '.join(exchange.timeframes)}")

18
mkdocs.yml
View File

@ -14,14 +14,17 @@ nav:
- Data Downloading: data-download.md
- Backtesting: backtesting.md
- Hyperopt: hyperopt.md
- Edge positioning: edge.md
- Edge Positioning: edge.md
- Utility Subcommands: utils.md
- FAQ: faq.md
- Data Analysis: data-analysis.md
- Plotting: plotting.md
- Data Analysis:
- Jupyter Notebooks: data-analysis.md
- Strategy analysis: strategy_analysis_example.md
- Plotting: plotting.md
- SQL Cheatsheet: sql_cheatsheet.md
- Sandbox testing: sandbox-testing.md
- Deprecated features: deprecated.md
- Contributors guide: developer.md
- Sandbox Testing: sandbox-testing.md
- Deprecated Features: deprecated.md
- Contributors Guide: developer.md
theme:
name: material
logo: 'images/logo.png'
@ -29,6 +32,8 @@ theme:
palette:
primary: 'blue grey'
accent: 'tear'
extra_css:
- 'stylesheets/ft.extra.css'
markdown_extensions:
- admonition
- codehilite:
@ -47,3 +52,4 @@ markdown_extensions:
- pymdownx.tasklist:
custom_checkbox: true
- pymdownx.tilde
- mdx_truly_sane_lists

10
requirements-common.txt
View File

@ -1,16 +1,16 @@
# requirements without requirements installable via conda
# mainly used for Raspberry pi installs
ccxt==1.18.1180
SQLAlchemy==1.3.8
ccxt==1.18.1260
SQLAlchemy==1.3.10
python-telegram-bot==12.1.1
arrow==0.15.2
cachetools==3.1.1
requests==2.22.0
urllib3==1.25.5
urllib3==1.25.6
wrapt==1.11.2
jsonschema==3.0.2
jsonschema==3.1.1
TA-Lib==0.4.17
tabulate==0.8.3
tabulate==0.8.5
coinmarketcap==5.0.3
# find first, C search in arrays

11
requirements-dev.txt
View File

@ -7,9 +7,12 @@ coveralls==1.8.2
flake8==3.7.8
flake8-type-annotations==0.1.0
flake8-tidy-imports==2.0.0
mypy==0.720
pytest==5.1.3
mypy==0.730
pytest==5.2.1
pytest-asyncio==0.10.0
pytest-cov==2.7.1
pytest-mock==1.10.4
pytest-cov==2.8.1
pytest-mock==1.11.1
pytest-random-order==1.0.4
# Convert jupyter notebooks to markdown documents
nbconvert==5.6.0

4
requirements-hyperopt.txt
View File

@ -1,9 +1,9 @@
# Include all requirements to run the bot.
# -r requirements.txt
-r requirements.txt
# Required for hyperopt
scipy==1.3.1
scikit-learn==0.21.3
scikit-optimize==0.5.2
filelock==3.0.12
joblib==0.13.2
joblib==0.14.0

5
scripts/pytest.sh Executable file
View File

@ -0,0 +1,5 @@
#!/bin/bash
echo "Running Unit tests"
pytest --random-order --cov=freqtrade --cov-config=.coveragerc tests/

1
setup.py
View File

@ -43,6 +43,7 @@ jupyter = [
'jupyter',
'nbstripout',
'ipykernel',
'nbconvert',
]
all_extra = api + plot + develop + jupyter + hyperopt

5
tests/config_test_comments.json
View File

@ -103,11 +103,6 @@
"max_trade_duration_minute": 1440,
"remove_pumps": false
},
"experimental": {
"use_sell_signal": false,
"sell_profit_only": false,
"ignore_roi_if_buy_signal": false
},
"telegram": {
// We can now comment out some settings
// "enabled": true,

138
tests/conftest.py
View File

@ -9,8 +9,8 @@ from pathlib import Path
from unittest.mock import MagicMock, PropertyMock
import arrow
import pytest
import numpy as np
import pytest
from telegram import Chat, Message, Update
from freqtrade import constants, persistence
@ -19,10 +19,10 @@ from freqtrade.data.converter import parse_ticker_dataframe
from freqtrade.edge import Edge, PairInfo
from freqtrade.exchange import Exchange
from freqtrade.freqtradebot import FreqtradeBot
from freqtrade.persistence import Trade
from freqtrade.resolvers import ExchangeResolver
from freqtrade.worker import Worker
logging.getLogger('').setLevel(logging.INFO)
@ -609,6 +609,14 @@ def limit_buy_order_old_partial():
}
@pytest.fixture
def limit_buy_order_old_partial_canceled(limit_buy_order_old_partial):
res = deepcopy(limit_buy_order_old_partial)
res['status'] = 'canceled'
res['fee'] = {'cost': 0.0001, 'currency': 'ETH'}
return res
@pytest.fixture
def limit_sell_order():
return {
@ -897,12 +905,6 @@ def result(testdatadir):
return parse_ticker_dataframe(json.load(data_file), '1m', pair="UNITTEST/BTC",
fill_missing=True)
# FIX:
# Create an fixture/function
# that inserts a trade of some type and open-status
# return the open-order-id
# See tests in rpc/main that could use this
@pytest.fixture(scope="function")
def trades_for_order():
@ -929,6 +931,110 @@ def trades_for_order():
'fee': {'cost': 0.008, 'currency': 'LTC'}}]
@pytest.fixture(scope="function")
def trades_history():
return [{'info': {'a': 126181329,
'p': '0.01962700',
'q': '0.04000000',
'f': 138604155,
'l': 138604155,
'T': 1565798399463,
'm': False,
'M': True},
'timestamp': 1565798399463,
'datetime': '2019-08-14T15:59:59.463Z',
'symbol': 'ETH/BTC',
'id': '126181329',
'order': None,
'type': None,
'takerOrMaker': None,
'side': 'buy',
'price': 0.019627,
'amount': 0.04,
'cost': 0.00078508,
'fee': None},
{'info': {'a': 126181330,
'p': '0.01962700',
'q': '0.24400000',
'f': 138604156,
'l': 138604156,
'T': 1565798399629,
'm': False,
'M': True},
'timestamp': 1565798399629,
'datetime': '2019-08-14T15:59:59.629Z',
'symbol': 'ETH/BTC',
'id': '126181330',
'order': None,
'type': None,
'takerOrMaker': None,
'side': 'buy',
'price': 0.019627,
'amount': 0.244,
'cost': 0.004788987999999999,
'fee': None},
{'info': {'a': 126181331,
'p': '0.01962600',
'q': '0.01100000',
'f': 138604157,
'l': 138604157,
'T': 1565798399752,
'm': True,
'M': True},
'timestamp': 1565798399752,
'datetime': '2019-08-14T15:59:59.752Z',
'symbol': 'ETH/BTC',
'id': '126181331',
'order': None,
'type': None,
'takerOrMaker': None,
'side': 'sell',
'price': 0.019626,
'amount': 0.011,
'cost': 0.00021588599999999999,
'fee': None},
{'info': {'a': 126181332,
'p': '0.01962600',
'q': '0.01100000',
'f': 138604158,
'l': 138604158,
'T': 1565798399862,
'm': True,
'M': True},
'timestamp': 1565798399862,
'datetime': '2019-08-14T15:59:59.862Z',
'symbol': 'ETH/BTC',
'id': '126181332',
'order': None,
'type': None,
'takerOrMaker': None,
'side': 'sell',
'price': 0.019626,
'amount': 0.011,
'cost': 0.00021588599999999999,
'fee': None},
{'info': {'a': 126181333,
'p': '0.01952600',
'q': '0.01200000',
'f': 138604158,
'l': 138604158,
'T': 1565798399872,
'm': True,
'M': True},
'timestamp': 1565798399872,
'datetime': '2019-08-14T15:59:59.872Z',
'symbol': 'ETH/BTC',
'id': '126181333',
'order': None,
'type': None,
'takerOrMaker': None,
'side': 'sell',
'price': 0.019626,
'amount': 0.011,
'cost': 0.00021588599999999999,
'fee': None}]
@pytest.fixture(scope="function")
def trades_for_order2():
return [{'info': {'id': 34567,
@ -1076,3 +1182,19 @@ def import_fails() -> None:
# restore previous importfunction
builtins.__import__ = realimport
@pytest.fixture(scope="function")
def open_trade():
return Trade(
pair='ETH/BTC',
open_rate=0.00001099,
exchange='bittrex',
open_order_id='123456789',
amount=90.99181073,
fee_open=0.0,
fee_close=0.0,
stake_amount=1,
open_date=arrow.utcnow().shift(minutes=-601).datetime,
is_open=True
)

8
tests/data/test_btanalysis.py
View File

@ -53,12 +53,12 @@ def test_load_trades_db(default_conf, fee, mocker):
def test_extract_trades_of_period(testdatadir):
pair = "UNITTEST/BTC"
timerange = TimeRange(None, 'line', 0, -1000)
# 2018-11-14 06:07:00
timerange = TimeRange('date', None, 1510639620, 0)
data = load_pair_history(pair=pair, ticker_interval='1m',
datadir=testdatadir, timerange=timerange)
# timerange = 2017-11-14 06:07 - 2017-11-14 22:58:00
trades = DataFrame(
{'pair': [pair, pair, pair, pair],
'profit_percent': [0.0, 0.1, -0.2, -0.5],
@ -108,7 +108,7 @@ def test_load_trades(default_conf, mocker):
def test_combine_tickers_with_mean(testdatadir):
pairs = ["ETH/BTC", "XLM/BTC"]
pairs = ["ETH/BTC", "ADA/BTC"]
tickers = load_data(datadir=testdatadir,
pairs=pairs,
ticker_interval='5m'
@ -116,7 +116,7 @@ def test_combine_tickers_with_mean(testdatadir):
df = combine_tickers_with_mean(tickers)
assert isinstance(df, DataFrame)
assert "ETH/BTC" in df.columns
assert "XLM/BTC" in df.columns
assert "ADA/BTC" in df.columns
assert "mean" in df.columns

32
tests/data/test_dataprovider.py
View File

@ -120,3 +120,35 @@ def test_refresh(mocker, default_conf, ticker_history):
assert len(refresh_mock.call_args[0]) == 1
assert len(refresh_mock.call_args[0][0]) == len(pairs) + len(pairs_non_trad)
assert refresh_mock.call_args[0][0] == pairs + pairs_non_trad
def test_orderbook(mocker, default_conf, order_book_l2):
api_mock = MagicMock()
api_mock.fetch_l2_order_book = order_book_l2
exchange = get_patched_exchange(mocker, default_conf, api_mock=api_mock)
dp = DataProvider(default_conf, exchange)
res = dp.orderbook('ETH/BTC', 5)
assert order_book_l2.call_count == 1
assert order_book_l2.call_args_list[0][0][0] == 'ETH/BTC'
assert order_book_l2.call_args_list[0][0][1] == 5
assert type(res) is dict
assert 'bids' in res
assert 'asks' in res
def test_market(mocker, default_conf, markets):
api_mock = MagicMock()
api_mock.markets = markets
exchange = get_patched_exchange(mocker, default_conf, api_mock=api_mock)
dp = DataProvider(default_conf, exchange)
res = dp.market('ETH/BTC')
assert type(res) is dict
assert 'symbol' in res
assert res['symbol'] == 'ETH/BTC'
res = dp.market('UNITTEST/BTC')
assert res is None

250
tests/data/test_history.py
View File

@ -1,7 +1,6 @@
# pragma pylint: disable=missing-docstring, protected-access, C0103
import json
import os
import uuid
from pathlib import Path
from shutil import copyfile
@ -14,49 +13,54 @@ from pandas import DataFrame
from freqtrade import OperationalException
from freqtrade.configuration import TimeRange
from freqtrade.data import history
from freqtrade.data.history import (download_pair_history,
load_cached_data_for_updating,
load_tickerdata_file,
from freqtrade.data.history import (_load_cached_data_for_updating,
convert_trades_to_ohlcv,
download_pair_history,
download_trades_history,
load_tickerdata_file, pair_data_filename,
pair_trades_filename,
refresh_backtest_ohlcv_data,
refresh_backtest_trades_data,
trim_tickerlist)
from freqtrade.exchange import timeframe_to_minutes
from freqtrade.misc import file_dump_json
from freqtrade.strategy.default_strategy import DefaultStrategy
from tests.conftest import get_patched_exchange, log_has, log_has_re, patch_exchange
from tests.conftest import (get_patched_exchange, log_has, log_has_re,
patch_exchange)
# Change this if modifying UNITTEST/BTC testdatafile
_BTC_UNITTEST_LENGTH = 13681
def _backup_file(file: str, copy_file: bool = False) -> None:
def _backup_file(file: Path, copy_file: bool = False) -> None:
"""
Backup existing file to avoid deleting the user file
:param file: complete path to the file
:param touch_file: create an empty file in replacement
:return: None
"""
file_swp = file + '.swp'
if os.path.isfile(file):
os.rename(file, file_swp)
file_swp = str(file) + '.swp'
if file.is_file():
file.rename(file_swp)
if copy_file:
copyfile(file_swp, file)
def _clean_test_file(file: str) -> None:
def _clean_test_file(file: Path) -> None:
"""
Backup existing file to avoid deleting the user file
:param file: complete path to the file
:return: None
"""
file_swp = file + '.swp'
file_swp = Path(str(file) + '.swp')
# 1. Delete file from the test
if os.path.isfile(file):
os.remove(file)
if file.is_file():
file.unlink()
# 2. Rollback to the initial file
if os.path.isfile(file_swp):
os.rename(file_swp, file)
if file_swp.is_file():
file_swp.rename(file)
def test_load_data_30min_ticker(mocker, caplog, default_conf, testdatadir) -> None:
@ -80,10 +84,10 @@ def test_load_data_7min_ticker(mocker, caplog, default_conf, testdatadir) -> Non
def test_load_data_1min_ticker(ticker_history, mocker, caplog, testdatadir) -> None:
mocker.patch('freqtrade.exchange.Exchange.get_historic_ohlcv', return_value=ticker_history)
file = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'UNITTEST_BTC-1m.json')
file = testdatadir / 'UNITTEST_BTC-1m.json'
_backup_file(file, copy_file=True)
history.load_data(datadir=testdatadir, ticker_interval='1m', pairs=['UNITTEST/BTC'])
assert os.path.isfile(file) is True
assert file.is_file()
assert not log_has(
'Download history data for pair: "UNITTEST/BTC", interval: 1m '
'and store in None.', caplog
@ -98,14 +102,14 @@ def test_load_data_with_new_pair_1min(ticker_history_list, mocker, caplog,
"""
mocker.patch('freqtrade.exchange.Exchange.get_historic_ohlcv', return_value=ticker_history_list)
exchange = get_patched_exchange(mocker, default_conf)
file = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'MEME_BTC-1m.json')
file = testdatadir / 'MEME_BTC-1m.json'
_backup_file(file)
# do not download a new pair if refresh_pairs isn't set
history.load_pair_history(datadir=testdatadir,
ticker_interval='1m',
pair='MEME/BTC')
assert os.path.isfile(file) is False
assert not file.is_file()
assert log_has(
'No history data for pair: "MEME/BTC", interval: 1m. '
'Use `freqtrade download-data` to download the data', caplog
@ -117,7 +121,7 @@ def test_load_data_with_new_pair_1min(ticker_history_list, mocker, caplog,
refresh_pairs=True,
exchange=exchange,
pair='MEME/BTC')
assert os.path.isfile(file) is True
assert file.is_file()
assert log_has_re(
'Download history data for pair: "MEME/BTC", interval: 1m '
'and store in .*', caplog
@ -135,6 +139,18 @@ def test_testdata_path(testdatadir) -> None:
assert str(Path('tests') / 'testdata') in str(testdatadir)
def test_pair_data_filename():
fn = pair_data_filename(Path('freqtrade/hello/world'), 'ETH/BTC', '5m')
assert isinstance(fn, Path)
assert fn == Path('freqtrade/hello/world/ETH_BTC-5m.json')
def test_pair_trades_filename():
fn = pair_trades_filename(Path('freqtrade/hello/world'), 'ETH/BTC')
assert isinstance(fn, Path)
assert fn == Path('freqtrade/hello/world/ETH_BTC-trades.json.gz')
def test_load_cached_data_for_updating(mocker) -> None:
datadir = Path(__file__).parent.parent.joinpath('testdata')
@ -151,43 +167,43 @@ def test_load_cached_data_for_updating(mocker) -> None:
# timeframe starts earlier than the cached data
# should fully update data
timerange = TimeRange('date', None, test_data[0][0] / 1000 - 1, 0)
data, start_ts = load_cached_data_for_updating(datadir, 'UNITTEST/BTC', '1m', timerange)
data, start_ts = _load_cached_data_for_updating(datadir, 'UNITTEST/BTC', '1m', timerange)
assert data == []
assert start_ts == test_data[0][0] - 1000
# same with 'line' timeframe
num_lines = (test_data[-1][0] - test_data[1][0]) / 1000 / 60 + 120
data, start_ts = load_cached_data_for_updating(datadir, 'UNITTEST/BTC', '1m',
TimeRange(None, 'line', 0, -num_lines))
data, start_ts = _load_cached_data_for_updating(datadir, 'UNITTEST/BTC', '1m',
TimeRange(None, 'line', 0, -num_lines))
assert data == []
assert start_ts < test_data[0][0] - 1
# timeframe starts in the center of the cached data
# should return the chached data w/o the last item
timerange = TimeRange('date', None, test_data[0][0] / 1000 + 1, 0)
data, start_ts = load_cached_data_for_updating(datadir, 'UNITTEST/BTC', '1m', timerange)
data, start_ts = _load_cached_data_for_updating(datadir, 'UNITTEST/BTC', '1m', timerange)
assert data == test_data[:-1]
assert test_data[-2][0] < start_ts < test_data[-1][0]
# same with 'line' timeframe
num_lines = (test_data[-1][0] - test_data[1][0]) / 1000 / 60 + 30
timerange = TimeRange(None, 'line', 0, -num_lines)
data, start_ts = load_cached_data_for_updating(datadir, 'UNITTEST/BTC', '1m', timerange)
data, start_ts = _load_cached_data_for_updating(datadir, 'UNITTEST/BTC', '1m', timerange)
assert data == test_data[:-1]
assert test_data[-2][0] < start_ts < test_data[-1][0]
# timeframe starts after the chached data
# should return the chached data w/o the last item
timerange = TimeRange('date', None, test_data[-1][0] / 1000 + 1, 0)
data, start_ts = load_cached_data_for_updating(datadir, 'UNITTEST/BTC', '1m', timerange)
data, start_ts = _load_cached_data_for_updating(datadir, 'UNITTEST/BTC', '1m', timerange)
assert data == test_data[:-1]
assert test_data[-2][0] < start_ts < test_data[-1][0]
# Try loading last 30 lines.
# Not supported by load_cached_data_for_updating, we always need to get the full data.
# Not supported by _load_cached_data_for_updating, we always need to get the full data.
num_lines = 30
timerange = TimeRange(None, 'line', 0, -num_lines)
data, start_ts = load_cached_data_for_updating(datadir, 'UNITTEST/BTC', '1m', timerange)
data, start_ts = _load_cached_data_for_updating(datadir, 'UNITTEST/BTC', '1m', timerange)
assert data == test_data[:-1]
assert test_data[-2][0] < start_ts < test_data[-1][0]
@ -195,27 +211,27 @@ def test_load_cached_data_for_updating(mocker) -> None:
# should return the chached data w/o the last item
num_lines = 30
timerange = TimeRange(None, 'line', 0, -num_lines)
data, start_ts = load_cached_data_for_updating(datadir, 'UNITTEST/BTC', '1m', timerange)
data, start_ts = _load_cached_data_for_updating(datadir, 'UNITTEST/BTC', '1m', timerange)
assert data == test_data[:-1]
assert test_data[-2][0] < start_ts < test_data[-1][0]
# no datafile exist
# should return timestamp start time
timerange = TimeRange('date', None, now_ts - 10000, 0)
data, start_ts = load_cached_data_for_updating(datadir, 'NONEXIST/BTC', '1m', timerange)
data, start_ts = _load_cached_data_for_updating(datadir, 'NONEXIST/BTC', '1m', timerange)
assert data == []
assert start_ts == (now_ts - 10000) * 1000
# same with 'line' timeframe
num_lines = 30
timerange = TimeRange(None, 'line', 0, -num_lines)
data, start_ts = load_cached_data_for_updating(datadir, 'NONEXIST/BTC', '1m', timerange)
data, start_ts = _load_cached_data_for_updating(datadir, 'NONEXIST/BTC', '1m', timerange)
assert data == []
assert start_ts == (now_ts - num_lines * 60) * 1000
# no datafile exist, no timeframe is set
# should return an empty array and None
data, start_ts = load_cached_data_for_updating(datadir, 'NONEXIST/BTC', '1m', None)
data, start_ts = _load_cached_data_for_updating(datadir, 'NONEXIST/BTC', '1m', None)
assert data == []
assert start_ts is None
@ -223,18 +239,18 @@ def test_load_cached_data_for_updating(mocker) -> None:
def test_download_pair_history(ticker_history_list, mocker, default_conf, testdatadir) -> None:
mocker.patch('freqtrade.exchange.Exchange.get_historic_ohlcv', return_value=ticker_history_list)
exchange = get_patched_exchange(mocker, default_conf)
file1_1 = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'MEME_BTC-1m.json')
file1_5 = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'MEME_BTC-5m.json')
file2_1 = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'CFI_BTC-1m.json')
file2_5 = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'CFI_BTC-5m.json')
file1_1 = testdatadir / 'MEME_BTC-1m.json'
file1_5 = testdatadir / 'MEME_BTC-5m.json'
file2_1 = testdatadir / 'CFI_BTC-1m.json'
file2_5 = testdatadir / 'CFI_BTC-5m.json'
_backup_file(file1_1)
_backup_file(file1_5)
_backup_file(file2_1)
_backup_file(file2_5)
assert os.path.isfile(file1_1) is False
assert os.path.isfile(file2_1) is False
assert not file1_1.is_file()
assert not file2_1.is_file()
assert download_pair_history(datadir=testdatadir, exchange=exchange,
pair='MEME/BTC',
@ -243,15 +259,15 @@ def test_download_pair_history(ticker_history_list, mocker, default_conf, testda
pair='CFI/BTC',
ticker_interval='1m')
assert not exchange._pairs_last_refresh_time
assert os.path.isfile(file1_1) is True
assert os.path.isfile(file2_1) is True
assert file1_1.is_file()
assert file2_1.is_file()
# clean files freshly downloaded
_clean_test_file(file1_1)
_clean_test_file(file2_1)
assert os.path.isfile(file1_5) is False
assert os.path.isfile(file2_5) is False
assert not file1_5.is_file()
assert not file2_5.is_file()
assert download_pair_history(datadir=testdatadir, exchange=exchange,
pair='MEME/BTC',
@ -260,8 +276,8 @@ def test_download_pair_history(ticker_history_list, mocker, default_conf, testda
pair='CFI/BTC',
ticker_interval='5m')
assert not exchange._pairs_last_refresh_time
assert os.path.isfile(file1_5) is True
assert os.path.isfile(file2_5) is True
assert file1_5.is_file()
assert file2_5.is_file()
# clean files freshly downloaded
_clean_test_file(file1_5)
@ -288,8 +304,8 @@ def test_download_backtesting_data_exception(ticker_history, mocker, caplog,
exchange = get_patched_exchange(mocker, default_conf)
file1_1 = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'MEME_BTC-1m.json')
file1_5 = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'MEME_BTC-5m.json')
file1_1 = testdatadir / 'MEME_BTC-1m.json'
file1_5 = testdatadir / 'MEME_BTC-5m.json'
_backup_file(file1_1)
_backup_file(file1_5)
@ -359,43 +375,12 @@ def test_init(default_conf, mocker) -> None:
)
def test_trim_tickerlist() -> None:
file = os.path.join(os.path.dirname(__file__), '..', 'testdata', 'UNITTEST_BTC-1m.json')
def test_trim_tickerlist(testdatadir) -> None:
file = testdatadir / 'UNITTEST_BTC-1m.json'
with open(file) as data_file:
ticker_list = json.load(data_file)
ticker_list_len = len(ticker_list)
# Test the pattern ^(-\d+)$
# This pattern uses the latest N elements
timerange = TimeRange(None, 'line', 0, -5)
ticker = trim_tickerlist(ticker_list, timerange)
ticker_len = len(ticker)
assert ticker_len == 5
assert ticker_list[0] is not ticker[0] # The first element should be different
assert ticker_list[-1] is ticker[-1] # The last element must be the same
# Test the pattern ^(\d+)-$
# This pattern keep X element from the end
timerange = TimeRange('line', None, 5, 0)
ticker = trim_tickerlist(ticker_list, timerange)
ticker_len = len(ticker)
assert ticker_len == 5
assert ticker_list[0] is ticker[0] # The first element must be the same
assert ticker_list[-1] is not ticker[-1] # The last element should be different
# Test the pattern ^(\d+)-(\d+)$
# This pattern extract a window
timerange = TimeRange('index', 'index', 5, 10)
ticker = trim_tickerlist(ticker_list, timerange)
ticker_len = len(ticker)
assert ticker_len == 5
assert ticker_list[0] is not ticker[0] # The first element should be different
assert ticker_list[5] is ticker[0] # The list starts at the index 5
assert ticker_list[9] is ticker[-1] # The list ends at the index 9 (5 elements)
# Test the pattern ^(\d{8})-(\d{8})$
# This pattern extract a window between the dates
timerange = TimeRange('date', 'date', ticker_list[5][0] / 1000, ticker_list[10][0] / 1000 - 1)
@ -435,13 +420,6 @@ def test_trim_tickerlist() -> None:
assert ticker_list_len == ticker_len
# Test invalid timerange (start after stop)
timerange = TimeRange('index', 'index', 10, 5)
with pytest.raises(ValueError, match=r'The timerange .* is incorrect'):
trim_tickerlist(ticker_list, timerange)
assert ticker_list_len == ticker_len
# passing empty list
timerange = TimeRange(None, None, None, 5)
ticker = trim_tickerlist([], timerange)
@ -449,22 +427,21 @@ def test_trim_tickerlist() -> None:
assert not ticker
def test_file_dump_json_tofile() -> None:
file = os.path.join(os.path.dirname(__file__), '..', 'testdata',
'test_{id}.json'.format(id=str(uuid.uuid4())))
def test_file_dump_json_tofile(testdatadir) -> None:
file = testdatadir / 'test_{id}.json'.format(id=str(uuid.uuid4()))
data = {'bar': 'foo'}
# check the file we will create does not exist
assert os.path.isfile(file) is False
assert not file.is_file()
# Create the Json file
file_dump_json(file, data)
# Check the file was create
assert os.path.isfile(file) is True
assert file.is_file()
# Open the Json file created and test the data is in it
with open(file) as data_file:
with file.open() as data_file:
json_from_file = json.load(data_file)
assert 'bar' in json_from_file
@ -571,3 +548,92 @@ def test_download_data_no_markets(mocker, default_conf, caplog, testdatadir):
assert "ETH/BTC" in unav_pairs
assert "XRP/BTC" in unav_pairs
assert log_has("Skipping pair ETH/BTC...", caplog)
def test_refresh_backtest_trades_data(mocker, default_conf, markets, caplog, testdatadir):
dl_mock = mocker.patch('freqtrade.data.history.download_trades_history', MagicMock())
mocker.patch(
'freqtrade.exchange.Exchange.markets', PropertyMock(return_value=markets)
)
mocker.patch.object(Path, "exists", MagicMock(return_value=True))
mocker.patch.object(Path, "unlink", MagicMock())
ex = get_patched_exchange(mocker, default_conf)
timerange = TimeRange.parse_timerange("20190101-20190102")
unavailable_pairs = refresh_backtest_trades_data(exchange=ex,
pairs=["ETH/BTC", "XRP/BTC", "XRP/ETH"],
datadir=testdatadir,
timerange=timerange, erase=True
)
assert dl_mock.call_count == 2
assert dl_mock.call_args[1]['timerange'].starttype == 'date'
assert log_has("Downloading trades for pair ETH/BTC.", caplog)
assert unavailable_pairs == ["XRP/ETH"]
assert log_has("Skipping pair XRP/ETH...", caplog)
def test_download_trades_history(trades_history, mocker, default_conf, testdatadir, caplog) -> None:
ght_mock = MagicMock(side_effect=lambda pair, *args, **kwargs: (pair, trades_history))
mocker.patch('freqtrade.exchange.Exchange.get_historic_trades',
ght_mock)
exchange = get_patched_exchange(mocker, default_conf)
file1 = testdatadir / 'ETH_BTC-trades.json.gz'
_backup_file(file1)
assert not file1.is_file()
assert download_trades_history(datadir=testdatadir, exchange=exchange,
pair='ETH/BTC')
assert log_has("New Amount of trades: 5", caplog)
assert file1.is_file()
# clean files freshly downloaded
_clean_test_file(file1)
mocker.patch('freqtrade.exchange.Exchange.get_historic_trades',
MagicMock(side_effect=ValueError))
assert not download_trades_history(datadir=testdatadir, exchange=exchange,
pair='ETH/BTC')
assert log_has_re('Failed to download historic trades for pair: "ETH/BTC".*', caplog)
def test_convert_trades_to_ohlcv(mocker, default_conf, testdatadir, caplog):
pair = 'XRP/ETH'
file1 = testdatadir / 'XRP_ETH-1m.json'
file5 = testdatadir / 'XRP_ETH-5m.json'
# Compare downloaded dataset with converted dataset
dfbak_1m = history.load_pair_history(datadir=testdatadir,
ticker_interval="1m",
pair=pair)
dfbak_5m = history.load_pair_history(datadir=testdatadir,
ticker_interval="5m",
pair=pair)
_backup_file(file1, copy_file=True)
_backup_file(file5)
tr = TimeRange.parse_timerange('20191011-20191012')
convert_trades_to_ohlcv([pair], timeframes=['1m', '5m'],
datadir=testdatadir, timerange=tr, erase=True)
assert log_has("Deleting existing data for pair XRP/ETH, interval 1m.", caplog)
# Load new data
df_1m = history.load_pair_history(datadir=testdatadir,
ticker_interval="1m",
pair=pair)
df_5m = history.load_pair_history(datadir=testdatadir,
ticker_interval="5m",
pair=pair)
assert df_1m.equals(dfbak_1m)
assert df_5m.equals(dfbak_5m)
_clean_test_file(file1)
_clean_test_file(file5)

10
tests/edge/test_edge.py
View File

@ -79,7 +79,7 @@ tc0 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
[1, 5000, 5025, 4975, 4987, 6172, 0, 1]], # enter trade (signal on last candle)
stop_loss=-0.99, roi=float('inf'), profit_perc=0.00,
stop_loss=-0.99, roi={"0": float('inf')}, profit_perc=0.00,
trades=[]
)
@ -94,7 +94,7 @@ tc1 = BTContainer(data=[
[5, 5000, 5025, 4975, 4987, 6172, 0, 1], # no action
[6, 5000, 5025, 4975, 4987, 6172, 0, 0], # should sell
],
stop_loss=-0.99, roi=float('inf'), profit_perc=0.00,
stop_loss=-0.99, roi={"0": float('inf')}, profit_perc=0.00,
trades=[BTrade(sell_reason=SellType.SELL_SIGNAL, open_tick=1, close_tick=2),
BTrade(sell_reason=SellType.SELL_SIGNAL, open_tick=4, close_tick=6)]
)
@ -106,7 +106,7 @@ tc2 = BTContainer(data=[
[1, 5000, 5025, 4600, 4987, 6172, 0, 0], # enter trade, stoploss hit
[2, 5000, 5025, 4975, 4987, 6172, 0, 0],
],
stop_loss=-0.01, roi=float('inf'), profit_perc=-0.01,
stop_loss=-0.01, roi={"0": float('inf')}, profit_perc=-0.01,
trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=1)]
)
@ -117,7 +117,7 @@ tc3 = BTContainer(data=[
[1, 5000, 5025, 4800, 4987, 6172, 0, 0], # enter trade, stoploss hit
[2, 5000, 5025, 4975, 4987, 6172, 0, 0],
],
stop_loss=-0.03, roi=float('inf'), profit_perc=-0.03,
stop_loss=-0.03, roi={"0": float('inf')}, profit_perc=-0.03,
trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=1)]
)
@ -128,7 +128,7 @@ tc4 = BTContainer(data=[
[1, 5000, 5025, 4800, 4987, 6172, 0, 1], # enter trade, stoploss hit, sell signal
[2, 5000, 5025, 4975, 4987, 6172, 0, 0],
],
stop_loss=-0.03, roi=float('inf'), profit_perc=-0.03,
stop_loss=-0.03, roi={"0": float('inf')}, profit_perc=-0.03,
trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=1)]
)

212
tests/exchange/test_exchange.py
View File

@ -142,6 +142,12 @@ def test_exchange_resolver(default_conf, mocker, caplog):
assert not log_has_re(r"No .* specific subclass found. Using the generic class instead.",
caplog)
# Test mapping
exchange = ExchangeResolver('binanceus', default_conf).exchange
assert isinstance(exchange, Exchange)
assert isinstance(exchange, Binance)
assert not isinstance(exchange, Kraken)
def test_validate_order_time_in_force(default_conf, mocker, caplog):
caplog.set_level(logging.INFO)
@ -409,7 +415,8 @@ def test_validate_timeframes_failed(default_conf, mocker):
mocker.patch('freqtrade.exchange.Exchange._init_ccxt', MagicMock(return_value=api_mock))
mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
with pytest.raises(OperationalException, match=r'Invalid ticker 3m, this Exchange supports.*'):
with pytest.raises(OperationalException,
match=r"Invalid ticker interval '3m'. This exchange supports.*"):
Exchange(default_conf)
@ -1135,6 +1142,13 @@ async def test__async_get_candle_history(default_conf, mocker, caplog, exchange_
await exchange._async_get_candle_history(pair, "5m",
(arrow.utcnow().timestamp - 2000) * 1000)
with pytest.raises(OperationalException, match=r'Exchange.* does not support fetching '
r'historical candlestick data\..*'):
api_mock.fetch_ohlcv = MagicMock(side_effect=ccxt.NotSupported("Not supported"))
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
await exchange._async_get_candle_history(pair, "5m",
(arrow.utcnow().timestamp - 2000) * 1000)
@pytest.mark.asyncio
async def test__async_get_candle_history_empty(default_conf, mocker, caplog):
@ -1306,6 +1320,196 @@ async def test___async_get_candle_history_sort(default_conf, mocker, exchange_na
assert ticks[9][5] == 2.31452783
@pytest.mark.asyncio
@pytest.mark.parametrize("exchange_name", EXCHANGES)
async def test__async_fetch_trades(default_conf, mocker, caplog, exchange_name,
trades_history):
caplog.set_level(logging.DEBUG)
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
# Monkey-patch async function
exchange._api_async.fetch_trades = get_mock_coro(trades_history)
pair = 'ETH/BTC'
res = await exchange._async_fetch_trades(pair, since=None, params=None)
assert type(res) is list
assert isinstance(res[0], dict)
assert isinstance(res[1], dict)
assert exchange._api_async.fetch_trades.call_count == 1
assert exchange._api_async.fetch_trades.call_args[0][0] == pair
assert exchange._api_async.fetch_trades.call_args[1]['limit'] == 1000
assert log_has_re(f"Fetching trades for pair {pair}, since .*", caplog)
caplog.clear()
exchange._api_async.fetch_trades.reset_mock()
res = await exchange._async_fetch_trades(pair, since=None, params={'from': '123'})
assert exchange._api_async.fetch_trades.call_count == 1
assert exchange._api_async.fetch_trades.call_args[0][0] == pair
assert exchange._api_async.fetch_trades.call_args[1]['limit'] == 1000
assert exchange._api_async.fetch_trades.call_args[1]['params'] == {'from': '123'}
assert log_has_re(f"Fetching trades for pair {pair}, params: .*", caplog)
exchange = Exchange(default_conf)
await async_ccxt_exception(mocker, default_conf, MagicMock(),
"_async_fetch_trades", "fetch_trades",
pair='ABCD/BTC', since=None)
api_mock = MagicMock()
with pytest.raises(OperationalException, match=r'Could not fetch trade data*'):
api_mock.fetch_trades = MagicMock(side_effect=ccxt.BaseError("Unknown error"))
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
await exchange._async_fetch_trades(pair, since=(arrow.utcnow().timestamp - 2000) * 1000)
with pytest.raises(OperationalException, match=r'Exchange.* does not support fetching '
r'historical trade data\..*'):
api_mock.fetch_trades = MagicMock(side_effect=ccxt.NotSupported("Not supported"))
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
await exchange._async_fetch_trades(pair, since=(arrow.utcnow().timestamp - 2000) * 1000)
@pytest.mark.asyncio
@pytest.mark.parametrize("exchange_name", EXCHANGES)
async def test__async_get_trade_history_id(default_conf, mocker, caplog, exchange_name,
trades_history):
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
pagination_arg = exchange._trades_pagination_arg
async def mock_get_trade_hist(pair, *args, **kwargs):
if 'since' in kwargs:
# Return first 3
return trades_history[:-2]
elif kwargs.get('params', {}).get(pagination_arg) == trades_history[-3]['id']:
# Return 2
return trades_history[-3:-1]
else:
# Return last 2
return trades_history[-2:]
# Monkey-patch async function
exchange._async_fetch_trades = MagicMock(side_effect=mock_get_trade_hist)
pair = 'ETH/BTC'
ret = await exchange._async_get_trade_history_id(pair, since=trades_history[0]["timestamp"],
until=trades_history[-1]["timestamp"]-1)
assert type(ret) is tuple
assert ret[0] == pair
assert type(ret[1]) is list
assert len(ret[1]) == len(trades_history)
assert exchange._async_fetch_trades.call_count == 3
fetch_trades_cal = exchange._async_fetch_trades.call_args_list
# first call (using since, not fromId)
assert fetch_trades_cal[0][0][0] == pair
assert fetch_trades_cal[0][1]['since'] == trades_history[0]["timestamp"]
# 2nd call
assert fetch_trades_cal[1][0][0] == pair
assert 'params' in fetch_trades_cal[1][1]
assert exchange._ft_has['trades_pagination_arg'] in fetch_trades_cal[1][1]['params']
@pytest.mark.asyncio
@pytest.mark.parametrize("exchange_name", EXCHANGES)
async def test__async_get_trade_history_time(default_conf, mocker, caplog, exchange_name,
trades_history):
caplog.set_level(logging.DEBUG)
async def mock_get_trade_hist(pair, *args, **kwargs):
if kwargs['since'] == trades_history[0]["timestamp"]:
return trades_history[:-1]
else:
return trades_history[-1:]
caplog.set_level(logging.DEBUG)
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
# Monkey-patch async function
exchange._async_fetch_trades = MagicMock(side_effect=mock_get_trade_hist)
pair = 'ETH/BTC'
ret = await exchange._async_get_trade_history_time(pair, since=trades_history[0]["timestamp"],
until=trades_history[-1]["timestamp"]-1)
assert type(ret) is tuple
assert ret[0] == pair
assert type(ret[1]) is list
assert len(ret[1]) == len(trades_history)
assert exchange._async_fetch_trades.call_count == 2
fetch_trades_cal = exchange._async_fetch_trades.call_args_list
# first call (using since, not fromId)
assert fetch_trades_cal[0][0][0] == pair
assert fetch_trades_cal[0][1]['since'] == trades_history[0]["timestamp"]
# 2nd call
assert fetch_trades_cal[1][0][0] == pair
assert fetch_trades_cal[0][1]['since'] == trades_history[0]["timestamp"]
assert log_has_re(r"Stopping because until was reached.*", caplog)
@pytest.mark.asyncio
@pytest.mark.parametrize("exchange_name", EXCHANGES)
async def test__async_get_trade_history_time_empty(default_conf, mocker, caplog, exchange_name,
trades_history):
caplog.set_level(logging.DEBUG)
async def mock_get_trade_hist(pair, *args, **kwargs):
if kwargs['since'] == trades_history[0]["timestamp"]:
return trades_history[:-1]
else:
return []
caplog.set_level(logging.DEBUG)
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
# Monkey-patch async function
exchange._async_fetch_trades = MagicMock(side_effect=mock_get_trade_hist)
pair = 'ETH/BTC'
ret = await exchange._async_get_trade_history_time(pair, since=trades_history[0]["timestamp"],
until=trades_history[-1]["timestamp"]-1)
assert type(ret) is tuple
assert ret[0] == pair
assert type(ret[1]) is list
assert len(ret[1]) == len(trades_history) - 1
assert exchange._async_fetch_trades.call_count == 2
fetch_trades_cal = exchange._async_fetch_trades.call_args_list
# first call (using since, not fromId)
assert fetch_trades_cal[0][0][0] == pair
assert fetch_trades_cal[0][1]['since'] == trades_history[0]["timestamp"]
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_get_historic_trades(default_conf, mocker, caplog, exchange_name, trades_history):
mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
pair = 'ETH/BTC'
exchange._async_get_trade_history_id = get_mock_coro((pair, trades_history))
exchange._async_get_trade_history_time = get_mock_coro((pair, trades_history))
ret = exchange.get_historic_trades(pair, since=trades_history[0]["timestamp"],
until=trades_history[-1]["timestamp"])
# Depending on the exchange, one or the other method should be called
assert sum([exchange._async_get_trade_history_id.call_count,
exchange._async_get_trade_history_time.call_count]) == 1
assert len(ret) == 2
assert ret[0] == pair
assert len(ret[1]) == len(trades_history)
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_get_historic_trades_notsupported(default_conf, mocker, caplog, exchange_name,
trades_history):
mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=False)
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
pair = 'ETH/BTC'
with pytest.raises(OperationalException,
match="This exchange does not suport downloading Trades."):
exchange.get_historic_trades(pair, since=trades_history[0]["timestamp"],
until=trades_history[-1]["timestamp"])
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_cancel_order_dry_run(default_conf, mocker, exchange_name):
default_conf['dry_run'] = True
@ -1452,13 +1656,17 @@ def test_merge_ft_has_dict(default_conf, mocker):
assert ex._ft_has == Exchange._ft_has_default
ex = Kraken(default_conf)
assert ex._ft_has == Exchange._ft_has_default
assert ex._ft_has != Exchange._ft_has_default
assert ex._ft_has['trades_pagination'] == 'id'
assert ex._ft_has['trades_pagination_arg'] == 'since'
# Binance defines different values
ex = Binance(default_conf)
assert ex._ft_has != Exchange._ft_has_default
assert ex._ft_has['stoploss_on_exchange']
assert ex._ft_has['order_time_in_force'] == ['gtc', 'fok', 'ioc']
assert ex._ft_has['trades_pagination'] == 'id'
assert ex._ft_has['trades_pagination_arg'] == 'fromId'
conf = copy.deepcopy(default_conf)
conf['exchange']['_ft_has_params'] = {"DeadBeef": 20,

4
tests/optimize/__init__.py
View File

@ -1,4 +1,4 @@
from typing import NamedTuple, List
from typing import Dict, List, NamedTuple
import arrow
from pandas import DataFrame
@ -25,7 +25,7 @@ class BTContainer(NamedTuple):
"""
data: List[float]
stop_loss: float
roi: float
roi: Dict[str, float]
trades: List[BTrade]
profit_perc: float
trailing_stop: bool = False

52
tests/optimize/test_backtest_detail.py
View File

@ -22,7 +22,7 @@ tc0 = BTContainer(data=[
[3, 5010, 5000, 4980, 5010, 6172, 0, 1],
[4, 5010, 4987, 4977, 4995, 6172, 0, 0],
[5, 4995, 4995, 4995, 4950, 6172, 0, 0]],
stop_loss=-0.01, roi=1, profit_perc=0.002, use_sell_signal=True,
stop_loss=-0.01, roi={"0": 1}, profit_perc=0.002, use_sell_signal=True,
trades=[BTrade(sell_reason=SellType.SELL_SIGNAL, open_tick=1, close_tick=4)]
)
@ -36,7 +36,7 @@ tc1 = BTContainer(data=[
[3, 4975, 5000, 4980, 4977, 6172, 0, 0],
[4, 4977, 4987, 4977, 4995, 6172, 0, 0],
[5, 4995, 4995, 4995, 4950, 6172, 0, 0]],
stop_loss=-0.01, roi=1, profit_perc=-0.01,
stop_loss=-0.01, roi={"0": 1}, profit_perc=-0.01,
trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2)]
)
@ -51,7 +51,7 @@ tc2 = BTContainer(data=[
[3, 4975, 5000, 4800, 4962, 6172, 0, 0], # exit with stoploss hit
[4, 4962, 4987, 4937, 4950, 6172, 0, 0],
[5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
stop_loss=-0.03, roi=1, profit_perc=-0.03,
stop_loss=-0.03, roi={"0": 1}, profit_perc=-0.03,
trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=3)]
)
@ -71,7 +71,7 @@ tc3 = BTContainer(data=[
[4, 4975, 5000, 4950, 4962, 6172, 0, 0], # enter trade 2 (signal on last candle)
[5, 4962, 4987, 4000, 4000, 6172, 0, 0], # exit with stoploss hit
[6, 4950, 4975, 4975, 4950, 6172, 0, 0]],
stop_loss=-0.02, roi=1, profit_perc=-0.04,
stop_loss=-0.02, roi={"0": 1}, profit_perc=-0.04,
trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2),
BTrade(sell_reason=SellType.STOP_LOSS, open_tick=4, close_tick=5)]
)
@ -88,7 +88,7 @@ tc4 = BTContainer(data=[
[3, 4975, 5000, 4950, 4962, 6172, 0, 0],
[4, 4962, 4987, 4937, 4950, 6172, 0, 0],
[5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
stop_loss=-0.02, roi=0.06, profit_perc=-0.02,
stop_loss=-0.02, roi={"0": 0.06}, profit_perc=-0.02,
trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2)]
)
@ -102,7 +102,7 @@ tc5 = BTContainer(data=[
[3, 4975, 6000, 4975, 6000, 6172, 0, 0], # ROI
[4, 4962, 4987, 4972, 4950, 6172, 0, 0],
[5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
stop_loss=-0.01, roi=0.03, profit_perc=0.03,
stop_loss=-0.01, roi={"0": 0.03}, profit_perc=0.03,
trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
)
@ -116,7 +116,7 @@ tc6 = BTContainer(data=[
[3, 4975, 5000, 4950, 4962, 6172, 0, 0],
[4, 4962, 4987, 4972, 4950, 6172, 0, 0],
[5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
stop_loss=-0.02, roi=0.05, profit_perc=-0.02,
stop_loss=-0.02, roi={"0": 0.05}, profit_perc=-0.02,
trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=2)]
)
@ -130,7 +130,7 @@ tc7 = BTContainer(data=[
[3, 4975, 5000, 4950, 4962, 6172, 0, 0],
[4, 4962, 4987, 4972, 4950, 6172, 0, 0],
[5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
stop_loss=-0.02, roi=0.03, profit_perc=0.03,
stop_loss=-0.02, roi={"0": 0.03}, profit_perc=0.03,
trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=2)]
)
@ -144,7 +144,7 @@ tc8 = BTContainer(data=[
[2, 5000, 5250, 4750, 4850, 6172, 0, 0],
[3, 4850, 5050, 4650, 4750, 6172, 0, 0],
[4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
stop_loss=-0.10, roi=0.10, profit_perc=-0.055, trailing_stop=True,
stop_loss=-0.10, roi={"0": 0.10}, profit_perc=-0.055, trailing_stop=True,
trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=3)]
)
@ -158,7 +158,7 @@ tc9 = BTContainer(data=[
[2, 5000, 5050, 4950, 5000, 6172, 0, 0],
[3, 5000, 5200, 4550, 4850, 6172, 0, 0],
[4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
stop_loss=-0.10, roi=0.10, profit_perc=-0.064, trailing_stop=True,
stop_loss=-0.10, roi={"0": 0.10}, profit_perc=-0.064, trailing_stop=True,
trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=3)]
)
@ -172,7 +172,7 @@ tc10 = BTContainer(data=[
[2, 5100, 5251, 5100, 5100, 6172, 0, 0],
[3, 4850, 5050, 4650, 4750, 6172, 0, 0],
[4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
stop_loss=-0.10, roi=0.10, profit_perc=-0.1, trailing_stop=True,
stop_loss=-0.10, roi={"0": 0.10}, profit_perc=-0.1, trailing_stop=True,
trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.10,
trailing_stop_positive=0.03,
trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=4)]
@ -188,7 +188,7 @@ tc11 = BTContainer(data=[
[2, 5100, 5251, 5100, 5100, 6172, 0, 0],
[3, 4850, 5050, 4650, 4750, 6172, 0, 0],
[4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
stop_loss=-0.10, roi=0.10, profit_perc=0.019, trailing_stop=True,
stop_loss=-0.10, roi={"0": 0.10}, profit_perc=0.019, trailing_stop=True,
trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.05,
trailing_stop_positive=0.03,
trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=3)]
@ -204,7 +204,7 @@ tc12 = BTContainer(data=[
[2, 5100, 5251, 4650, 5100, 6172, 0, 0],
[3, 4850, 5050, 4650, 4750, 6172, 0, 0],
[4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
stop_loss=-0.10, roi=0.10, profit_perc=0.019, trailing_stop=True,
stop_loss=-0.10, roi={"0": 0.10}, profit_perc=0.019, trailing_stop=True,
trailing_only_offset_is_reached=True, trailing_stop_positive_offset=0.05,
trailing_stop_positive=0.03,
trades=[BTrade(sell_reason=SellType.TRAILING_STOP_LOSS, open_tick=1, close_tick=2)]
@ -219,7 +219,7 @@ tc13 = BTContainer(data=[
[2, 5100, 5251, 4850, 5100, 6172, 0, 0],
[3, 4850, 5050, 4850, 4750, 6172, 0, 0],
[4, 4750, 4950, 4850, 4750, 6172, 0, 0]],
stop_loss=-0.10, roi=0.01, profit_perc=0.01,
stop_loss=-0.10, roi={"0": 0.01}, profit_perc=0.01,
trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=1)]
)
@ -232,7 +232,7 @@ tc14 = BTContainer(data=[
[2, 5100, 5251, 4850, 5100, 6172, 0, 0],
[3, 4850, 5050, 4850, 4750, 6172, 0, 0],
[4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
stop_loss=-0.05, roi=0.10, profit_perc=-0.05,
stop_loss=-0.05, roi={"0": 0.10}, profit_perc=-0.05,
trades=[BTrade(sell_reason=SellType.STOP_LOSS, open_tick=1, close_tick=1)]
)
@ -246,11 +246,26 @@ tc15 = BTContainer(data=[
[2, 5100, 5251, 4650, 5100, 6172, 0, 0],
[3, 4850, 5050, 4850, 4750, 6172, 0, 0],
[4, 4750, 4950, 4350, 4750, 6172, 0, 0]],
stop_loss=-0.05, roi=0.01, profit_perc=-0.04,
stop_loss=-0.05, roi={"0": 0.01}, profit_perc=-0.04,
trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=1),
BTrade(sell_reason=SellType.STOP_LOSS, open_tick=2, close_tick=2)]
)
# Test 16: Buy, hold for 65 mins, then forcesell using roi=-1
# Causes negative profit even though sell-reason is ROI.
# stop-loss: 10%, ROI: 10% (should not apply), -100% after 65 minutes (limits trade duration)
tc16 = BTContainer(data=[
# D O H L C V B S
[0, 5000, 5025, 4975, 4987, 6172, 1, 0],
[1, 5000, 5025, 4975, 4987, 6172, 0, 0],
[2, 4987, 5300, 4950, 5050, 6172, 0, 0],
[3, 4975, 5000, 4940, 4962, 6172, 0, 0], # ForceSell on ROI (roi=-1)
[4, 4962, 4987, 4972, 4950, 6172, 0, 0],
[5, 4950, 4975, 4925, 4950, 6172, 0, 0]],
stop_loss=-0.10, roi={"0": 0.10, "65": -1}, profit_perc=-0.012,
trades=[BTrade(sell_reason=SellType.ROI, open_tick=1, close_tick=3)]
)
TESTS = [
tc0,
tc1,
@ -268,6 +283,7 @@ TESTS = [
tc13,
tc14,
tc15,
tc16,
]
@ -277,7 +293,7 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
run functional tests
"""
default_conf["stoploss"] = data.stop_loss
default_conf["minimal_roi"] = {"0": data.roi}
default_conf["minimal_roi"] = data.roi
default_conf["ticker_interval"] = tests_ticker_interval
default_conf["trailing_stop"] = data.trailing_stop
default_conf["trailing_only_offset_is_reached"] = data.trailing_only_offset_is_reached
@ -285,7 +301,7 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
if data.trailing_stop_positive:
default_conf["trailing_stop_positive"] = data.trailing_stop_positive
default_conf["trailing_stop_positive_offset"] = data.trailing_stop_positive_offset
default_conf["experimental"] = {"use_sell_signal": data.use_sell_signal}
default_conf["ask_strategy"] = {"use_sell_signal": data.use_sell_signal}
mocker.patch("freqtrade.exchange.Exchange.get_fee", MagicMock(return_value=0.0))
patch_exchange(mocker)

77
tests/optimize/test_backtesting.py
View File

@ -26,6 +26,21 @@ from tests.conftest import (get_args, log_has, log_has_re, patch_exchange,
patched_configuration_load_config_file)
ORDER_TYPES = [
{
'buy': 'limit',
'sell': 'limit',
'stoploss': 'limit',
'stoploss_on_exchange': False
},
{
'buy': 'limit',
'sell': 'limit',
'stoploss': 'limit',
'stoploss_on_exchange': True
}]
def trim_dictlist(dict_list, num):
new = {}
for pair, pair_data in dict_list.items():
@ -34,7 +49,7 @@ def trim_dictlist(dict_list, num):
def load_data_test(what, testdatadir):
timerange = TimeRange(None, 'line', 0, -101)
timerange = TimeRange.parse_timerange('1510694220-1510700340')
pair = history.load_tickerdata_file(testdatadir, ticker_interval='1m',
pair='UNITTEST/BTC', timerange=timerange)
datalen = len(pair)
@ -211,7 +226,8 @@ def test_setup_bt_configuration_with_arguments(mocker, default_conf, caplog) ->
'--disable-max-market-positions',
'--timerange', ':100',
'--export', '/bar/foo',
'--export-filename', 'foo_bar.json'
'--export-filename', 'foo_bar.json',
'--fee', '0',
]
config = setup_configuration(get_args(args), RunMode.BACKTEST)
@ -243,6 +259,9 @@ def test_setup_bt_configuration_with_arguments(mocker, default_conf, caplog) ->
assert 'exportfilename' in config
assert log_has('Storing backtest results to {} ...'.format(config['exportfilename']), caplog)
assert 'fee' in config
assert log_has('Parameter --fee detected, setting fee to: {} ...'.format(config['fee']), caplog)
def test_setup_configuration_unlimited_stake_amount(mocker, default_conf, caplog) -> None:
default_conf['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT
@ -277,21 +296,6 @@ def test_start(mocker, fee, default_conf, caplog) -> None:
assert start_mock.call_count == 1
ORDER_TYPES = [
{
'buy': 'limit',
'sell': 'limit',
'stoploss': 'limit',
'stoploss_on_exchange': False
},
{
'buy': 'limit',
'sell': 'limit',
'stoploss': 'limit',
'stoploss_on_exchange': True
}]
@pytest.mark.parametrize("order_types", ORDER_TYPES)
def test_backtesting_init(mocker, default_conf, order_types) -> None:
"""
@ -314,10 +318,6 @@ def test_backtesting_init(mocker, default_conf, order_types) -> None:
def test_backtesting_init_no_ticker_interval(mocker, default_conf, caplog) -> None:
"""
Check that stoploss_on_exchange is set to False while backtesting
since backtesting assumes a perfect stoploss anyway.
"""
patch_exchange(mocker)
del default_conf['ticker_interval']
default_conf['strategy_list'] = ['DefaultStrategy',
@ -330,9 +330,20 @@ def test_backtesting_init_no_ticker_interval(mocker, default_conf, caplog) -> No
"or as cli argument `--ticker-interval 5m`", caplog)
def test_tickerdata_with_fee(default_conf, mocker, testdatadir) -> None:
patch_exchange(mocker)
default_conf['fee'] = 0.1234
fee_mock = mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.5))
backtesting = Backtesting(default_conf)
assert backtesting.fee == 0.1234
assert fee_mock.call_count == 0
def test_tickerdata_to_dataframe_bt(default_conf, mocker, testdatadir) -> None:
patch_exchange(mocker)
timerange = TimeRange(None, 'line', 0, -100)
# timerange = TimeRange(None, 'line', 0, -100)
timerange = TimeRange.parse_timerange('1510694220-1510700340')
tick = history.load_tickerdata_file(testdatadir, 'UNITTEST/BTC', '1m', timerange=timerange)
tickerlist = {'UNITTEST/BTC': parse_ticker_dataframe(tick, '1m', pair="UNITTEST/BTC",
fill_missing=True)}
@ -464,7 +475,7 @@ def test_backtesting_start(default_conf, mocker, testdatadir, caplog) -> None:
default_conf['ticker_interval'] = '1m'
default_conf['datadir'] = testdatadir
default_conf['export'] = None
default_conf['timerange'] = '-100'
default_conf['timerange'] = '-1510694220'
backtesting = Backtesting(default_conf)
backtesting.start()
@ -507,11 +518,12 @@ def test_backtesting_start_no_data(default_conf, mocker, caplog, testdatadir) ->
def test_backtest(default_conf, fee, mocker, testdatadir) -> None:
default_conf['ask_strategy']['use_sell_signal'] = False
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
patch_exchange(mocker)
backtesting = Backtesting(default_conf)
pair = 'UNITTEST/BTC'
timerange = TimeRange(None, 'line', 0, -201)
timerange = TimeRange('date', None, 1517227800, 0)
data = history.load_data(datadir=testdatadir, ticker_interval='5m', pairs=['UNITTEST/BTC'],
timerange=timerange)
data_processed = backtesting.strategy.tickerdata_to_dataframe(data)
@ -561,12 +573,13 @@ def test_backtest(default_conf, fee, mocker, testdatadir) -> None:
def test_backtest_1min_ticker_interval(default_conf, fee, mocker, testdatadir) -> None:
default_conf['ask_strategy']['use_sell_signal'] = False
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
patch_exchange(mocker)
backtesting = Backtesting(default_conf)
# Run a backtesting for an exiting 1min ticker_interval
timerange = TimeRange(None, 'line', 0, -200)
timerange = TimeRange.parse_timerange('1510688220-1510700340')
data = history.load_data(datadir=testdatadir, ticker_interval='1m', pairs=['UNITTEST/BTC'],
timerange=timerange)
processed = backtesting.strategy.tickerdata_to_dataframe(data)
@ -603,8 +616,6 @@ def test_backtest_pricecontours(default_conf, fee, mocker, testdatadir) -> None:
# TODO: Evaluate usefullness of this, the patterns and buy-signls are unrealistic
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
tests = [['raise', 19], ['lower', 0], ['sine', 35]]
# We need to enable sell-signal - otherwise it sells on ROI!!
default_conf['experimental'] = {"use_sell_signal": True}
for [contour, numres] in tests:
simple_backtest(default_conf, contour, numres, mocker, testdatadir)
@ -645,8 +656,6 @@ def test_backtest_alternate_buy_sell(default_conf, fee, mocker, testdatadir):
mocker.patch('freqtrade.optimize.backtesting.file_dump_json', MagicMock())
backtest_conf = _make_backtest_conf(mocker, conf=default_conf,
pair='UNITTEST/BTC', datadir=testdatadir)
# We need to enable sell-signal - otherwise it sells on ROI!!
default_conf['experimental'] = {"use_sell_signal": True}
default_conf['ticker_interval'] = '1m'
backtesting = Backtesting(default_conf)
backtesting.strategy.advise_buy = _trend_alternate # Override
@ -687,8 +696,6 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir)
# Remove data for one pair from the beginning of the data
data[pair] = data[pair][tres:].reset_index()
# We need to enable sell-signal - otherwise it sells on ROI!!
default_conf['experimental'] = {"use_sell_signal": True}
default_conf['ticker_interval'] = '5m'
backtesting = Backtesting(default_conf)
@ -817,7 +824,7 @@ def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir):
'--strategy', 'DefaultStrategy',
'--datadir', str(testdatadir),
'--ticker-interval', '1m',
'--timerange', '-100',
'--timerange', '1510694220-1510700340',
'--enable-position-stacking',
'--disable-max-market-positions'
]
@ -827,7 +834,7 @@ def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir):
exists = [
'Parameter -i/--ticker-interval detected ... Using ticker_interval: 1m ...',
'Ignoring max_open_trades (--disable-max-market-positions was used) ...',
'Parameter --timerange detected: -100 ...',
'Parameter --timerange detected: 1510694220-1510700340 ...',
f'Using data directory: {testdatadir} ...',
'Using stake_currency: BTC ...',
'Using stake_amount: 0.001 ...',
@ -863,7 +870,7 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
'--config', 'config.json',
'--datadir', str(testdatadir),
'--ticker-interval', '1m',
'--timerange', '-100',
'--timerange', '1510694220-1510700340',
'--enable-position-stacking',
'--disable-max-market-positions',
'--strategy-list',
@ -881,7 +888,7 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
exists = [
'Parameter -i/--ticker-interval detected ... Using ticker_interval: 1m ...',
'Ignoring max_open_trades (--disable-max-market-positions was used) ...',
'Parameter --timerange detected: -100 ...',
'Parameter --timerange detected: 1510694220-1510700340 ...',
f'Using data directory: {testdatadir} ...',
'Using stake_currency: BTC ...',
'Using stake_amount: 0.001 ...',

10
tests/optimize/test_edge_cli.py
View File

@ -98,6 +98,16 @@ def test_edge_init(mocker, edge_conf) -> None:
assert callable(edge_cli.edge.calculate)
def test_edge_init_fee(mocker, edge_conf) -> None:
patch_exchange(mocker)
edge_conf['fee'] = 0.1234
edge_conf['stake_amount'] = 20
fee_mock = mocker.patch('freqtrade.exchange.Exchange.get_fee', MagicMock(return_value=0.5))
edge_cli = EdgeCli(edge_conf)
assert edge_cli.edge.fee == 0.1234
assert fee_mock.call_count == 0
def test_generate_edge_table(edge_conf, mocker):
patch_exchange(mocker)
edge_cli = EdgeCli(edge_conf)

10
tests/optimize/test_hyperopt.py
View File

@ -12,7 +12,7 @@ from freqtrade import OperationalException
from freqtrade.data.converter import parse_ticker_dataframe
from freqtrade.data.history import load_tickerdata_file
from freqtrade.optimize import setup_configuration, start_hyperopt
from freqtrade.optimize.default_hyperopt import DefaultHyperOpts
from freqtrade.optimize.default_hyperopt import DefaultHyperOpt
from freqtrade.optimize.default_hyperopt_loss import DefaultHyperOptLoss
from freqtrade.optimize.hyperopt import Hyperopt
from freqtrade.resolvers.hyperopt_resolver import (HyperOptLossResolver,
@ -153,12 +153,12 @@ def test_setup_hyperopt_configuration_with_arguments(mocker, default_conf, caplo
def test_hyperoptresolver(mocker, default_conf, caplog) -> None:
patched_configuration_load_config_file(mocker, default_conf)
hyperopts = DefaultHyperOpts
delattr(hyperopts, 'populate_buy_trend')
delattr(hyperopts, 'populate_sell_trend')
hyperopt = DefaultHyperOpt
delattr(hyperopt, 'populate_buy_trend')
delattr(hyperopt, 'populate_sell_trend')
mocker.patch(
'freqtrade.resolvers.hyperopt_resolver.HyperOptResolver._load_hyperopt',
MagicMock(return_value=hyperopts(default_conf))
MagicMock(return_value=hyperopt(default_conf))
)
default_conf.update({'hyperopt': 'DefaultHyperOpts'})
x = HyperOptResolver(default_conf).hyperopt

158
tests/strategy/legacy_strategy.py
View File

@ -6,8 +6,6 @@ from pandas import DataFrame
# Add your lib to import here
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
import numpy # noqa
# This class is a sample. Feel free to customize it.
@ -17,7 +15,6 @@ class TestStrategyLegacy(IStrategy):
removed in a future update.
Please do not use this as a template, but refer to user_data/strategy/sample_strategy.py
for a uptodate version of this template.
"""
# Minimal ROI designed for the strategy.
@ -51,156 +48,9 @@ class TestStrategyLegacy(IStrategy):
# ADX
dataframe['adx'] = ta.ADX(dataframe)
"""
# Awesome oscillator
dataframe['ao'] = qtpylib.awesome_oscillator(dataframe)
# Commodity Channel Index: values Oversold:<-100, Overbought:>100
dataframe['cci'] = ta.CCI(dataframe)
# MACD
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
dataframe['macdsignal'] = macd['macdsignal']
dataframe['macdhist'] = macd['macdhist']
# MFI
dataframe['mfi'] = ta.MFI(dataframe)
# Minus Directional Indicator / Movement
dataframe['minus_dm'] = ta.MINUS_DM(dataframe)
dataframe['minus_di'] = ta.MINUS_DI(dataframe)
# Plus Directional Indicator / Movement
dataframe['plus_dm'] = ta.PLUS_DM(dataframe)
dataframe['plus_di'] = ta.PLUS_DI(dataframe)
dataframe['minus_di'] = ta.MINUS_DI(dataframe)
# ROC
dataframe['roc'] = ta.ROC(dataframe)
# RSI
dataframe['rsi'] = ta.RSI(dataframe)
# Inverse Fisher transform on RSI, values [-1.0, 1.0] (https://goo.gl/2JGGoy)
rsi = 0.1 * (dataframe['rsi'] - 50)
dataframe['fisher_rsi'] = (numpy.exp(2 * rsi) - 1) / (numpy.exp(2 * rsi) + 1)
# Inverse Fisher transform on RSI normalized, value [0.0, 100.0] (https://goo.gl/2JGGoy)
dataframe['fisher_rsi_norma'] = 50 * (dataframe['fisher_rsi'] + 1)
# Stoch
stoch = ta.STOCH(dataframe)
dataframe['slowd'] = stoch['slowd']
dataframe['slowk'] = stoch['slowk']
# Stoch fast
stoch_fast = ta.STOCHF(dataframe)
dataframe['fastd'] = stoch_fast['fastd']
dataframe['fastk'] = stoch_fast['fastk']
# Stoch RSI
stoch_rsi = ta.STOCHRSI(dataframe)
dataframe['fastd_rsi'] = stoch_rsi['fastd']
dataframe['fastk_rsi'] = stoch_rsi['fastk']
"""
# Overlap Studies
# ------------------------------------
# Bollinger bands
bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
dataframe['bb_lowerband'] = bollinger['lower']
dataframe['bb_middleband'] = bollinger['mid']
dataframe['bb_upperband'] = bollinger['upper']
"""
# EMA - Exponential Moving Average
dataframe['ema3'] = ta.EMA(dataframe, timeperiod=3)
dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5)
dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50)
dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
# SAR Parabol
dataframe['sar'] = ta.SAR(dataframe)
# SMA - Simple Moving Average
dataframe['sma'] = ta.SMA(dataframe, timeperiod=40)
"""
# TEMA - Triple Exponential Moving Average
dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
# Cycle Indicator
# ------------------------------------
# Hilbert Transform Indicator - SineWave
hilbert = ta.HT_SINE(dataframe)
dataframe['htsine'] = hilbert['sine']
dataframe['htleadsine'] = hilbert['leadsine']
# Pattern Recognition - Bullish candlestick patterns
# ------------------------------------
"""
# Hammer: values [0, 100]
dataframe['CDLHAMMER'] = ta.CDLHAMMER(dataframe)
# Inverted Hammer: values [0, 100]
dataframe['CDLINVERTEDHAMMER'] = ta.CDLINVERTEDHAMMER(dataframe)
# Dragonfly Doji: values [0, 100]
dataframe['CDLDRAGONFLYDOJI'] = ta.CDLDRAGONFLYDOJI(dataframe)
# Piercing Line: values [0, 100]
dataframe['CDLPIERCING'] = ta.CDLPIERCING(dataframe) # values [0, 100]
# Morningstar: values [0, 100]
dataframe['CDLMORNINGSTAR'] = ta.CDLMORNINGSTAR(dataframe) # values [0, 100]
# Three White Soldiers: values [0, 100]
dataframe['CDL3WHITESOLDIERS'] = ta.CDL3WHITESOLDIERS(dataframe) # values [0, 100]
"""
# Pattern Recognition - Bearish candlestick patterns
# ------------------------------------
"""
# Hanging Man: values [0, 100]
dataframe['CDLHANGINGMAN'] = ta.CDLHANGINGMAN(dataframe)
# Shooting Star: values [0, 100]
dataframe['CDLSHOOTINGSTAR'] = ta.CDLSHOOTINGSTAR(dataframe)
# Gravestone Doji: values [0, 100]
dataframe['CDLGRAVESTONEDOJI'] = ta.CDLGRAVESTONEDOJI(dataframe)
# Dark Cloud Cover: values [0, 100]
dataframe['CDLDARKCLOUDCOVER'] = ta.CDLDARKCLOUDCOVER(dataframe)
# Evening Doji Star: values [0, 100]
dataframe['CDLEVENINGDOJISTAR'] = ta.CDLEVENINGDOJISTAR(dataframe)
# Evening Star: values [0, 100]
dataframe['CDLEVENINGSTAR'] = ta.CDLEVENINGSTAR(dataframe)
"""
# Pattern Recognition - Bullish/Bearish candlestick patterns
# ------------------------------------
"""
# Three Line Strike: values [0, -100, 100]
dataframe['CDL3LINESTRIKE'] = ta.CDL3LINESTRIKE(dataframe)
# Spinning Top: values [0, -100, 100]
dataframe['CDLSPINNINGTOP'] = ta.CDLSPINNINGTOP(dataframe) # values [0, -100, 100]
# Engulfing: values [0, -100, 100]
dataframe['CDLENGULFING'] = ta.CDLENGULFING(dataframe) # values [0, -100, 100]
# Harami: values [0, -100, 100]
dataframe['CDLHARAMI'] = ta.CDLHARAMI(dataframe) # values [0, -100, 100]
# Three Outside Up/Down: values [0, -100, 100]
dataframe['CDL3OUTSIDE'] = ta.CDL3OUTSIDE(dataframe) # values [0, -100, 100]
# Three Inside Up/Down: values [0, -100, 100]
dataframe['CDL3INSIDE'] = ta.CDL3INSIDE(dataframe) # values [0, -100, 100]
"""
# Chart type
# ------------------------------------
"""
# Heikinashi stategy
heikinashi = qtpylib.heikinashi(dataframe)
dataframe['ha_open'] = heikinashi['open']
dataframe['ha_close'] = heikinashi['close']
dataframe['ha_high'] = heikinashi['high']
dataframe['ha_low'] = heikinashi['low']
"""
return dataframe
def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
@ -212,8 +62,8 @@ class TestStrategyLegacy(IStrategy):
dataframe.loc[
(
(dataframe['adx'] > 30) &
(dataframe['tema'] <= dataframe['bb_middleband']) &
(dataframe['tema'] > dataframe['tema'].shift(1))
(dataframe['tema'] > dataframe['tema'].shift(1)) &
(dataframe['volume'] > 0)
),
'buy'] = 1
@ -228,8 +78,8 @@ class TestStrategyLegacy(IStrategy):
dataframe.loc[
(
(dataframe['adx'] > 70) &
(dataframe['tema'] > dataframe['bb_middleband']) &
(dataframe['tema'] < dataframe['tema'].shift(1))
(dataframe['tema'] < dataframe['tema'].shift(1)) &
(dataframe['volume'] > 0)
),
'sell'] = 1
return dataframe

2
tests/strategy/test_interface.py
View File

@ -106,7 +106,7 @@ def test_get_signal_handles_exceptions(mocker, default_conf):
def test_tickerdata_to_dataframe(default_conf, testdatadir) -> None:
strategy = DefaultStrategy(default_conf)
timerange = TimeRange(None, 'line', 0, -100)
timerange = TimeRange.parse_timerange('1510694220-1510700340')
tick = load_tickerdata_file(testdatadir, 'UNITTEST/BTC', '1m', timerange=timerange)
tickerlist = {'UNITTEST/BTC': parse_ticker_dataframe(tick, '1m', pair="UNITTEST/BTC",
fill_missing=True)}

27
tests/strategy/test_strategy.py
View File

@ -1,6 +1,5 @@
# pragma pylint: disable=missing-docstring, protected-access, C0103
import logging
import tempfile
import warnings
from base64 import urlsafe_b64encode
from os import path
@ -39,7 +38,7 @@ def test_search_strategy():
def test_load_strategy(default_conf, result):
default_conf.update({'strategy': 'SampleStrategy'})
resolver = StrategyResolver(default_conf)
assert 'adx' in resolver.strategy.advise_indicators(result, {'pair': 'ETH/BTC'})
assert 'rsi' in resolver.strategy.advise_indicators(result, {'pair': 'ETH/BTC'})
def test_load_strategy_base64(result, caplog, default_conf):
@ -48,10 +47,10 @@ def test_load_strategy_base64(result, caplog, default_conf):
default_conf.update({'strategy': 'SampleStrategy:{}'.format(encoded_string)})
resolver = StrategyResolver(default_conf)
assert 'adx' in resolver.strategy.advise_indicators(result, {'pair': 'ETH/BTC'})
assert 'rsi' in resolver.strategy.advise_indicators(result, {'pair': 'ETH/BTC'})
# Make sure strategy was loaded from base64 (using temp directory)!!
assert log_has_re(r"Using resolved strategy SampleStrategy from '"
+ tempfile.gettempdir() + r"/.*/SampleStrategy\.py'\.\.\.", caplog)
r".*(/|\\).*(/|\\)SampleStrategy\.py'\.\.\.", caplog)
def test_load_strategy_invalid_directory(result, caplog, default_conf):
@ -265,23 +264,23 @@ def test_strategy_override_use_sell_signal(caplog, default_conf):
'strategy': 'DefaultStrategy',
})
resolver = StrategyResolver(default_conf)
assert not resolver.strategy.use_sell_signal
assert resolver.strategy.use_sell_signal
assert isinstance(resolver.strategy.use_sell_signal, bool)
# must be inserted to configuration
assert 'use_sell_signal' in default_conf['experimental']
assert not default_conf['experimental']['use_sell_signal']
assert 'use_sell_signal' in default_conf['ask_strategy']
assert default_conf['ask_strategy']['use_sell_signal']
default_conf.update({
'strategy': 'DefaultStrategy',
'experimental': {
'use_sell_signal': True,
'ask_strategy': {
'use_sell_signal': False,
},
})
resolver = StrategyResolver(default_conf)
assert resolver.strategy.use_sell_signal
assert not resolver.strategy.use_sell_signal
assert isinstance(resolver.strategy.use_sell_signal, bool)
assert log_has("Override strategy 'use_sell_signal' with value in config file: True.", caplog)
assert log_has("Override strategy 'use_sell_signal' with value in config file: False.", caplog)
def test_strategy_override_use_sell_profit_only(caplog, default_conf):
@ -293,12 +292,12 @@ def test_strategy_override_use_sell_profit_only(caplog, default_conf):
assert not resolver.strategy.sell_profit_only
assert isinstance(resolver.strategy.sell_profit_only, bool)
# must be inserted to configuration
assert 'sell_profit_only' in default_conf['experimental']
assert not default_conf['experimental']['sell_profit_only']
assert 'sell_profit_only' in default_conf['ask_strategy']
assert not default_conf['ask_strategy']['sell_profit_only']
default_conf.update({
'strategy': 'DefaultStrategy',
'experimental': {
'ask_strategy': {
'sell_profit_only': True,
},
})

40
tests/test_arguments.py
View File

@ -1,5 +1,7 @@
# pragma pylint: disable=missing-docstring, C0103
import argparse
from pathlib import Path
from unittest.mock import MagicMock
import pytest
@ -177,6 +179,44 @@ def test_plot_profit_options() -> None:
assert pargs["db_url"] == "sqlite:///whatever.sqlite"
def test_config_notallowed(mocker) -> None:
mocker.patch.object(Path, "is_file", MagicMock(return_value=False))
args = [
'create-userdir',
]
pargs = Arguments(args).get_parsed_arg()
assert pargs["config"] is None
# When file exists:
mocker.patch.object(Path, "is_file", MagicMock(return_value=True))
args = [
'create-userdir',
]
pargs = Arguments(args).get_parsed_arg()
# config is not added even if it exists, since create-userdir is in the notallowed list
assert pargs["config"] is None
def test_config_notrequired(mocker) -> None:
mocker.patch.object(Path, "is_file", MagicMock(return_value=False))
args = [
'download-data',
]
pargs = Arguments(args).get_parsed_arg()
assert pargs["config"] is None
# When file exists:
mocker.patch.object(Path, "is_file", MagicMock(return_value=True))
args = [
'download-data',
]
pargs = Arguments(args).get_parsed_arg()
# config is added if it exists
assert pargs["config"] == ['config.json']
def test_check_int_positive() -> None:
assert check_int_positive("3") == 3
assert check_int_positive("1") == 1

146
tests/test_configuration.py
View File

@ -14,6 +14,9 @@ from freqtrade.configuration import (Arguments, Configuration,
validate_config_consistency)
from freqtrade.configuration.check_exchange import check_exchange
from freqtrade.configuration.config_validation import validate_config_schema
from freqtrade.configuration.deprecated_settings import (check_conflicting_settings,
process_deprecated_setting,
process_temporary_deprecated_settings)
from freqtrade.configuration.directory_operations import (create_datadir,
create_userdata_dir)
from freqtrade.configuration.load_config import load_config_file
@ -418,14 +421,14 @@ def test_setup_configuration_with_arguments(mocker, default_conf, caplog) -> Non
assert 'pair_whitelist' in config['exchange']
assert 'datadir' in config
assert log_has('Using data directory: {} ...'.format("/foo/bar"), caplog)
assert log_has('Using user-data directory: {} ...'.format("/tmp/freqtrade"), caplog)
assert log_has('Using user-data directory: {} ...'.format(Path("/tmp/freqtrade")), caplog)
assert 'user_data_dir' in config
assert 'ticker_interval' in config
assert log_has('Parameter -i/--ticker-interval detected ... Using ticker_interval: 1m ...',
caplog)
assert 'position_stacking'in config
assert 'position_stacking' in config
assert log_has('Parameter --enable-position-stacking detected ...', caplog)
assert 'use_max_market_positions' in config
@ -528,7 +531,8 @@ def test_check_exchange(default_conf, caplog) -> None:
# Test an available exchange, supported by ccxt
default_conf.get('exchange').update({'name': 'huobipro'})
assert check_exchange(default_conf)
assert log_has_re(r"Exchange .* is supported by ccxt and .* not officially supported "
assert log_has_re(r"Exchange .* is known to the the ccxt library, available for the bot, "
r"but not officially supported "
r"by the Freqtrade development team\. .*", caplog)
caplog.clear()
@ -542,16 +546,16 @@ def test_check_exchange(default_conf, caplog) -> None:
# Test a 'bad' exchange with check_for_bad=False
default_conf.get('exchange').update({'name': 'bitmex'})
assert check_exchange(default_conf, False)
assert log_has_re(r"Exchange .* is supported by ccxt and .* not officially supported "
assert log_has_re(r"Exchange .* is known to the the ccxt library, available for the bot, "
r"but not officially supported "
r"by the Freqtrade development team\. .*", caplog)
caplog.clear()
# Test an invalid exchange
default_conf.get('exchange').update({'name': 'unknown_exchange'})
with pytest.raises(
OperationalException,
match=r'.*Exchange "unknown_exchange" is not supported by ccxt '
match=r'Exchange "unknown_exchange" is not known to the ccxt library '
r'and therefore not available for the bot.*'
):
check_exchange(default_conf)
@ -670,9 +674,9 @@ def test_create_userdata_dir(mocker, default_conf, caplog) -> None:
x = create_userdata_dir('/tmp/bar', create_dir=True)
assert md.call_count == 7
assert md.call_args[1]['parents'] is False
assert log_has('Created user-data directory: /tmp/bar', caplog)
assert log_has(f'Created user-data directory: {Path("/tmp/bar")}', caplog)
assert isinstance(x, Path)
assert str(x) == "/tmp/bar"
assert str(x) == str(Path("/tmp/bar"))
def test_create_userdata_dir_exists(mocker, default_conf, caplog) -> None:
@ -687,7 +691,8 @@ def test_create_userdata_dir_exists_exception(mocker, default_conf, caplog) -> N
mocker.patch.object(Path, "is_dir", MagicMock(return_value=False))
md = mocker.patch.object(Path, 'mkdir', MagicMock())
with pytest.raises(OperationalException, match=r'Directory `/tmp/bar` does not exist.*'):
with pytest.raises(OperationalException,
match=r'Directory `.{1,2}tmp.{1,2}bar` does not exist.*'):
create_userdata_dir('/tmp/bar', create_dir=False)
assert md.call_count == 0
@ -918,3 +923,126 @@ def test_pairlist_resolving_fallback(mocker):
assert config['pairs'] == ['ETH/BTC', 'XRP/BTC']
assert config['exchange']['name'] == 'binance'
assert config['datadir'] == str(Path.cwd() / "user_data/data/binance")
@pytest.mark.parametrize("setting", [
("ask_strategy", "use_sell_signal", True,
"experimental", "use_sell_signal", False),
("ask_strategy", "sell_profit_only", False,
"experimental", "sell_profit_only", True),
("ask_strategy", "ignore_roi_if_buy_signal", False,
"experimental", "ignore_roi_if_buy_signal", True),
])
def test_process_temporary_deprecated_settings(mocker, default_conf, setting, caplog):
patched_configuration_load_config_file(mocker, default_conf)
# Create sections for new and deprecated settings
# (they may not exist in the config)
default_conf[setting[0]] = {}
default_conf[setting[3]] = {}
# Assign new setting
default_conf[setting[0]][setting[1]] = setting[2]
# Assign deprecated setting
default_conf[setting[3]][setting[4]] = setting[5]
# New and deprecated settings are conflicting ones
with pytest.raises(OperationalException, match=r'DEPRECATED'):
process_temporary_deprecated_settings(default_conf)
caplog.clear()
# Delete new setting
del default_conf[setting[0]][setting[1]]
process_temporary_deprecated_settings(default_conf)
assert log_has_re('DEPRECATED', caplog)
# The value of the new setting shall have been set to the
# value of the deprecated one
assert default_conf[setting[0]][setting[1]] == setting[5]
def test_check_conflicting_settings(mocker, default_conf, caplog):
patched_configuration_load_config_file(mocker, default_conf)
# Create sections for new and deprecated settings
# (they may not exist in the config)
default_conf['sectionA'] = {}
default_conf['sectionB'] = {}
# Assign new setting
default_conf['sectionA']['new_setting'] = 'valA'
# Assign deprecated setting
default_conf['sectionB']['deprecated_setting'] = 'valB'
# New and deprecated settings are conflicting ones
with pytest.raises(OperationalException, match=r'DEPRECATED'):
check_conflicting_settings(default_conf,
'sectionA', 'new_setting',
'sectionB', 'deprecated_setting')
caplog.clear()
# Delete new setting (deprecated exists)
del default_conf['sectionA']['new_setting']
check_conflicting_settings(default_conf,
'sectionA', 'new_setting',
'sectionB', 'deprecated_setting')
assert not log_has_re('DEPRECATED', caplog)
assert 'new_setting' not in default_conf['sectionA']
caplog.clear()
# Assign new setting
default_conf['sectionA']['new_setting'] = 'valA'
# Delete deprecated setting
del default_conf['sectionB']['deprecated_setting']
check_conflicting_settings(default_conf,
'sectionA', 'new_setting',
'sectionB', 'deprecated_setting')
assert not log_has_re('DEPRECATED', caplog)
assert default_conf['sectionA']['new_setting'] == 'valA'
def test_process_deprecated_setting(mocker, default_conf, caplog):
patched_configuration_load_config_file(mocker, default_conf)
# Create sections for new and deprecated settings
# (they may not exist in the config)
default_conf['sectionA'] = {}
default_conf['sectionB'] = {}
# Assign new setting
default_conf['sectionA']['new_setting'] = 'valA'
# Assign deprecated setting
default_conf['sectionB']['deprecated_setting'] = 'valB'
# Both new and deprecated settings exists
process_deprecated_setting(default_conf,
'sectionA', 'new_setting',
'sectionB', 'deprecated_setting')
assert log_has_re('DEPRECATED', caplog)
# The value of the new setting shall have been set to the
# value of the deprecated one
assert default_conf['sectionA']['new_setting'] == 'valB'
caplog.clear()
# Delete new setting (deprecated exists)
del default_conf['sectionA']['new_setting']
process_deprecated_setting(default_conf,
'sectionA', 'new_setting',
'sectionB', 'deprecated_setting')
assert log_has_re('DEPRECATED', caplog)
# The value of the new setting shall have been set to the
# value of the deprecated one
assert default_conf['sectionA']['new_setting'] == 'valB'
caplog.clear()
# Assign new setting
default_conf['sectionA']['new_setting'] = 'valA'
# Delete deprecated setting
del default_conf['sectionB']['deprecated_setting']
process_deprecated_setting(default_conf,
'sectionA', 'new_setting',
'sectionB', 'deprecated_setting')
assert not log_has_re('DEPRECATED', caplog)
assert default_conf['sectionA']['new_setting'] == 'valA'

442
tests/test_freqtradebot.py
View File

@ -655,7 +655,8 @@ def test_create_trades_no_pairs_let(default_conf, ticker, limit_buy_order, fee,
assert freqtrade.create_trades()
assert not freqtrade.create_trades()
assert log_has("No currency pair in whitelist, but checking to sell open trades.", caplog)
assert log_has("No currency pair in active pair whitelist, "
"but checking to sell open trades.", caplog)
def test_create_trades_no_pairs_in_whitelist(default_conf, ticker, limit_buy_order, fee,
@ -674,7 +675,7 @@ def test_create_trades_no_pairs_in_whitelist(default_conf, ticker, limit_buy_ord
patch_get_signal(freqtrade)
assert not freqtrade.create_trades()
assert log_has("Whitelist is empty.", caplog)
assert log_has("Active pair whitelist is empty.", caplog)
def test_create_trades_no_signal(default_conf, fee, mocker) -> None:
@ -1057,8 +1058,9 @@ def test_add_stoploss_on_exchange(mocker, default_conf, limit_buy_order) -> None
trade.open_order_id = None
trade.stoploss_order_id = None
trade.is_open = True
trades = [trade]
freqtrade.process_maybe_execute_sell(trade)
freqtrade.process_maybe_execute_sells(trades)
assert trade.stoploss_order_id == '13434334'
assert stoploss_limit.call_count == 1
assert trade.is_open is True
@ -1447,7 +1449,7 @@ def test_tsl_on_exchange_compatible_with_edge(mocker, edge_conf, fee, caplog,
# setting stoploss
freqtrade.strategy.stoploss = -0.02
# setting stoploss_on_exchange_interval to 0 second
# setting stoploss_on_exchange_interval to 0 seconds
freqtrade.strategy.order_types['stoploss_on_exchange_interval'] = 0
patch_get_signal(freqtrade)
@ -1518,26 +1520,26 @@ def test_tsl_on_exchange_compatible_with_edge(mocker, edge_conf, fee, caplog,
stop_price=0.00002344 * 0.99)
def test_process_maybe_execute_buy(mocker, default_conf, caplog) -> None:
def test_process_maybe_execute_buys(mocker, default_conf, caplog) -> None:
freqtrade = get_patched_freqtradebot(mocker, default_conf)
mocker.patch('freqtrade.freqtradebot.FreqtradeBot.create_trades', MagicMock(return_value=False))
freqtrade.process_maybe_execute_buy()
freqtrade.process_maybe_execute_buys()
assert log_has('Found no buy signals for whitelisted currencies. Trying again...', caplog)
def test_process_maybe_execute_buy_exception(mocker, default_conf, caplog) -> None:
def test_process_maybe_execute_buys_exception(mocker, default_conf, caplog) -> None:
freqtrade = get_patched_freqtradebot(mocker, default_conf)
mocker.patch(
'freqtrade.freqtradebot.FreqtradeBot.create_trades',
MagicMock(side_effect=DependencyException)
)
freqtrade.process_maybe_execute_buy()
freqtrade.process_maybe_execute_buys()
assert log_has('Unable to create trade: ', caplog)
def test_process_maybe_execute_sell(mocker, default_conf, limit_buy_order, caplog) -> None:
def test_process_maybe_execute_sells(mocker, default_conf, limit_buy_order, caplog) -> None:
freqtrade = get_patched_freqtradebot(mocker, default_conf)
mocker.patch('freqtrade.freqtradebot.FreqtradeBot.handle_trade', MagicMock(return_value=True))
@ -1549,7 +1551,8 @@ def test_process_maybe_execute_sell(mocker, default_conf, limit_buy_order, caplo
trade = MagicMock()
trade.open_order_id = '123'
trade.open_fee = 0.001
assert not freqtrade.process_maybe_execute_sell(trade)
trades = [trade]
assert not freqtrade.process_maybe_execute_sells(trades)
# Test amount not modified by fee-logic
assert not log_has(
'Applying fee to amount for Trade {} from 90.99181073 to 90.81'.format(trade), caplog
@ -1557,24 +1560,25 @@ def test_process_maybe_execute_sell(mocker, default_conf, limit_buy_order, caplo
mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount', return_value=90.81)
# test amount modified by fee-logic
assert not freqtrade.process_maybe_execute_sell(trade)
assert not freqtrade.process_maybe_execute_sells(trades)
def test_process_maybe_execute_sell_exception(mocker, default_conf,
limit_buy_order, caplog) -> None:
def test_process_maybe_execute_sells_exception(mocker, default_conf,
limit_buy_order, caplog) -> None:
freqtrade = get_patched_freqtradebot(mocker, default_conf)
mocker.patch('freqtrade.exchange.Exchange.get_order', return_value=limit_buy_order)
trade = MagicMock()
trade.open_order_id = '123'
trade.open_fee = 0.001
trades = [trade]
# Test raise of DependencyException exception
mocker.patch(
'freqtrade.freqtradebot.FreqtradeBot.update_trade_state',
side_effect=DependencyException()
)
freqtrade.process_maybe_execute_sell(trade)
freqtrade.process_maybe_execute_sells(trades)
assert log_has('Unable to sell trade: ', caplog)
@ -1674,7 +1678,7 @@ def test_update_trade_state_exception(mocker, default_conf,
# Test raise of OperationalException exception
mocker.patch(
'freqtrade.freqtradebot.FreqtradeBot.get_real_amount',
side_effect=OperationalException()
side_effect=DependencyException()
)
freqtrade.update_trade_state(trade)
assert log_has('Could not update trade amount: ', caplog)
@ -1768,8 +1772,6 @@ def test_handle_trade(default_conf, limit_buy_order, limit_sell_order,
def test_handle_overlpapping_signals(default_conf, ticker, limit_buy_order,
fee, markets, mocker) -> None:
default_conf.update({'experimental': {'use_sell_signal': True}})
patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
@ -1824,7 +1826,6 @@ def test_handle_overlpapping_signals(default_conf, ticker, limit_buy_order,
def test_handle_trade_roi(default_conf, ticker, limit_buy_order,
fee, mocker, markets, caplog) -> None:
caplog.set_level(logging.DEBUG)
default_conf.update({'experimental': {'use_sell_signal': True}})
patch_RPCManager(mocker)
patch_exchange(mocker)
@ -1856,10 +1857,10 @@ def test_handle_trade_roi(default_conf, ticker, limit_buy_order,
caplog)
def test_handle_trade_experimental(
def test_handle_trade_use_sell_signal(
default_conf, ticker, limit_buy_order, fee, mocker, markets, caplog) -> None:
# use_sell_signal is True buy default
caplog.set_level(logging.DEBUG)
default_conf.update({'experimental': {'use_sell_signal': True}})
patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
@ -1911,11 +1912,12 @@ def test_close_trade(default_conf, ticker, limit_buy_order, limit_sell_order,
trade.update(limit_sell_order)
assert trade.is_open is False
with pytest.raises(ValueError, match=r'.*closed trade.*'):
with pytest.raises(DependencyException, match=r'.*closed trade.*'):
freqtrade.handle_trade(trade)
def test_check_handle_timedout_buy(default_conf, ticker, limit_buy_order_old, fee, mocker) -> None:
def test_check_handle_timedout_buy(default_conf, ticker, limit_buy_order_old, open_trade,
fee, mocker) -> None:
rpc_mock = patch_RPCManager(mocker)
cancel_order_mock = MagicMock()
patch_exchange(mocker)
@ -1928,31 +1930,18 @@ def test_check_handle_timedout_buy(default_conf, ticker, limit_buy_order_old, fe
)
freqtrade = FreqtradeBot(default_conf)
trade_buy = Trade(
pair='ETH/BTC',
open_rate=0.00001099,
exchange='bittrex',
open_order_id='123456789',
amount=90.99181073,
fee_open=0.0,
fee_close=0.0,
stake_amount=1,
open_date=arrow.utcnow().shift(minutes=-601).datetime,
is_open=True
)
Trade.session.add(trade_buy)
Trade.session.add(open_trade)
# check it does cancel buy orders over the time limit
freqtrade.check_handle_timedout()
assert cancel_order_mock.call_count == 1
assert rpc_mock.call_count == 1
trades = Trade.query.filter(Trade.open_order_id.is_(trade_buy.open_order_id)).all()
trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
nb_trades = len(trades)
assert nb_trades == 0
def test_check_handle_cancelled_buy(default_conf, ticker, limit_buy_order_old,
def test_check_handle_cancelled_buy(default_conf, ticker, limit_buy_order_old, open_trade,
fee, mocker, caplog) -> None:
""" Handle Buy order cancelled on exchange"""
rpc_mock = patch_RPCManager(mocker)
@ -1968,32 +1957,19 @@ def test_check_handle_cancelled_buy(default_conf, ticker, limit_buy_order_old,
)
freqtrade = FreqtradeBot(default_conf)
trade_buy = Trade(
pair='ETH/BTC',
open_rate=0.00001099,
exchange='bittrex',
open_order_id='123456789',
amount=90.99181073,
fee_open=0.0,
fee_close=0.0,
stake_amount=1,
open_date=arrow.utcnow().shift(minutes=-601).datetime,
is_open=True
)
Trade.session.add(trade_buy)
Trade.session.add(open_trade)
# check it does cancel buy orders over the time limit
freqtrade.check_handle_timedout()
assert cancel_order_mock.call_count == 0
assert rpc_mock.call_count == 1
trades = Trade.query.filter(Trade.open_order_id.is_(trade_buy.open_order_id)).all()
trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
nb_trades = len(trades)
assert nb_trades == 0
assert log_has_re("Buy order canceled on Exchange for Trade.*", caplog)
def test_check_handle_timedout_buy_exception(default_conf, ticker, limit_buy_order_old,
def test_check_handle_timedout_buy_exception(default_conf, ticker, limit_buy_order_old, open_trade,
fee, mocker) -> None:
rpc_mock = patch_RPCManager(mocker)
cancel_order_mock = MagicMock()
@ -2008,31 +1984,19 @@ def test_check_handle_timedout_buy_exception(default_conf, ticker, limit_buy_ord
)
freqtrade = FreqtradeBot(default_conf)
trade_buy = Trade(
pair='ETH/BTC',
open_rate=0.00001099,
exchange='bittrex',
open_order_id='123456789',
amount=90.99181073,
fee_open=0.0,
fee_close=0.0,
stake_amount=1,
open_date=arrow.utcnow().shift(minutes=-601).datetime,
is_open=True
)
Trade.session.add(trade_buy)
Trade.session.add(open_trade)
# check it does cancel buy orders over the time limit
freqtrade.check_handle_timedout()
assert cancel_order_mock.call_count == 0
assert rpc_mock.call_count == 0
trades = Trade.query.filter(Trade.open_order_id.is_(trade_buy.open_order_id)).all()
trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
nb_trades = len(trades)
assert nb_trades == 1
def test_check_handle_timedout_sell(default_conf, ticker, limit_sell_order_old, mocker) -> None:
def test_check_handle_timedout_sell(default_conf, ticker, limit_sell_order_old, mocker,
open_trade) -> None:
rpc_mock = patch_RPCManager(mocker)
cancel_order_mock = MagicMock()
patch_exchange(mocker)
@ -2044,30 +2008,20 @@ def test_check_handle_timedout_sell(default_conf, ticker, limit_sell_order_old,
)
freqtrade = FreqtradeBot(default_conf)
trade_sell = Trade(
pair='ETH/BTC',
open_rate=0.00001099,
exchange='bittrex',
open_order_id='123456789',
amount=90.99181073,
fee_open=0.0,
fee_close=0.0,
stake_amount=1,
open_date=arrow.utcnow().shift(hours=-5).datetime,
close_date=arrow.utcnow().shift(minutes=-601).datetime,
is_open=False
)
open_trade.open_date = arrow.utcnow().shift(hours=-5).datetime
open_trade.close_date = arrow.utcnow().shift(minutes=-601).datetime
open_trade.is_open = False
Trade.session.add(trade_sell)
Trade.session.add(open_trade)
# check it does cancel sell orders over the time limit
freqtrade.check_handle_timedout()
assert cancel_order_mock.call_count == 1
assert rpc_mock.call_count == 1
assert trade_sell.is_open is True
assert open_trade.is_open is True
def test_check_handle_cancelled_sell(default_conf, ticker, limit_sell_order_old,
def test_check_handle_cancelled_sell(default_conf, ticker, limit_sell_order_old, open_trade,
mocker, caplog) -> None:
""" Handle sell order cancelled on exchange"""
rpc_mock = patch_RPCManager(mocker)
@ -2082,34 +2036,24 @@ def test_check_handle_cancelled_sell(default_conf, ticker, limit_sell_order_old,
)
freqtrade = FreqtradeBot(default_conf)
trade_sell = Trade(
pair='ETH/BTC',
open_rate=0.00001099,
exchange='bittrex',
open_order_id='123456789',
amount=90.99181073,
fee_open=0.0,
fee_close=0.0,
stake_amount=1,
open_date=arrow.utcnow().shift(hours=-5).datetime,
close_date=arrow.utcnow().shift(minutes=-601).datetime,
is_open=False
)
open_trade.open_date = arrow.utcnow().shift(hours=-5).datetime
open_trade.close_date = arrow.utcnow().shift(minutes=-601).datetime
open_trade.is_open = False
Trade.session.add(trade_sell)
Trade.session.add(open_trade)
# check it does cancel sell orders over the time limit
freqtrade.check_handle_timedout()
assert cancel_order_mock.call_count == 0
assert rpc_mock.call_count == 1
assert trade_sell.is_open is True
assert open_trade.is_open is True
assert log_has_re("Sell order canceled on exchange for Trade.*", caplog)
def test_check_handle_timedout_partial(default_conf, ticker, limit_buy_order_old_partial,
mocker) -> None:
open_trade, mocker) -> None:
rpc_mock = patch_RPCManager(mocker)
cancel_order_mock = MagicMock()
cancel_order_mock = MagicMock(return_value=limit_buy_order_old_partial)
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
@ -2119,33 +2063,97 @@ def test_check_handle_timedout_partial(default_conf, ticker, limit_buy_order_old
)
freqtrade = FreqtradeBot(default_conf)
trade_buy = Trade(
pair='ETH/BTC',
open_rate=0.00001099,
exchange='bittrex',
open_order_id='123456789',
amount=90.99181073,
fee_open=0.0,
fee_close=0.0,
stake_amount=1,
open_date=arrow.utcnow().shift(minutes=-601).datetime,
is_open=True
)
Trade.session.add(trade_buy)
Trade.session.add(open_trade)
# check it does cancel buy orders over the time limit
# note this is for a partially-complete buy order
freqtrade.check_handle_timedout()
assert cancel_order_mock.call_count == 1
assert rpc_mock.call_count == 1
trades = Trade.query.filter(Trade.open_order_id.is_(trade_buy.open_order_id)).all()
trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
assert len(trades) == 1
assert trades[0].amount == 23.0
assert trades[0].stake_amount == trade_buy.open_rate * trades[0].amount
assert trades[0].stake_amount == open_trade.open_rate * trades[0].amount
def test_check_handle_timedout_exception(default_conf, ticker, mocker, caplog) -> None:
def test_check_handle_timedout_partial_fee(default_conf, ticker, open_trade, caplog, fee,
limit_buy_order_old_partial, trades_for_order,
limit_buy_order_old_partial_canceled, mocker) -> None:
rpc_mock = patch_RPCManager(mocker)
cancel_order_mock = MagicMock(return_value=limit_buy_order_old_partial_canceled)
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_order=MagicMock(return_value=limit_buy_order_old_partial),
cancel_order=cancel_order_mock,
get_trades_for_order=MagicMock(return_value=trades_for_order),
)
freqtrade = FreqtradeBot(default_conf)
assert open_trade.amount == limit_buy_order_old_partial['amount']
open_trade.fee_open = fee()
open_trade.fee_close = fee()
Trade.session.add(open_trade)
# cancelling a half-filled order should update the amount to the bought amount
# and apply fees if necessary.
freqtrade.check_handle_timedout()
assert log_has_re(r"Applying fee on amount for Trade.* Order", caplog)
assert cancel_order_mock.call_count == 1
assert rpc_mock.call_count == 1
trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
assert len(trades) == 1
# Verify that tradehas been updated
assert trades[0].amount == (limit_buy_order_old_partial['amount'] -
limit_buy_order_old_partial['remaining']) - 0.0001
assert trades[0].open_order_id is None
assert trades[0].fee_open == 0
def test_check_handle_timedout_partial_except(default_conf, ticker, open_trade, caplog, fee,
limit_buy_order_old_partial, trades_for_order,
limit_buy_order_old_partial_canceled, mocker) -> None:
rpc_mock = patch_RPCManager(mocker)
cancel_order_mock = MagicMock(return_value=limit_buy_order_old_partial_canceled)
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_order=MagicMock(return_value=limit_buy_order_old_partial),
cancel_order=cancel_order_mock,
get_trades_for_order=MagicMock(return_value=trades_for_order),
)
mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_real_amount',
MagicMock(side_effect=DependencyException))
freqtrade = FreqtradeBot(default_conf)
assert open_trade.amount == limit_buy_order_old_partial['amount']
open_trade.fee_open = fee()
open_trade.fee_close = fee()
Trade.session.add(open_trade)
# cancelling a half-filled order should update the amount to the bought amount
# and apply fees if necessary.
freqtrade.check_handle_timedout()
assert log_has_re(r"Could not update trade amount: .*", caplog)
assert cancel_order_mock.call_count == 1
assert rpc_mock.call_count == 1
trades = Trade.query.filter(Trade.open_order_id.is_(open_trade.open_order_id)).all()
assert len(trades) == 1
# Verify that tradehas been updated
assert trades[0].amount == (limit_buy_order_old_partial['amount'] -
limit_buy_order_old_partial['remaining'])
assert trades[0].open_order_id is None
assert trades[0].fee_open == fee()
def test_check_handle_timedout_exception(default_conf, ticker, open_trade, mocker, caplog) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
cancel_order_mock = MagicMock()
@ -2163,34 +2171,20 @@ def test_check_handle_timedout_exception(default_conf, ticker, mocker, caplog) -
)
freqtrade = FreqtradeBot(default_conf)
open_date = arrow.utcnow().shift(minutes=-601)
trade_buy = Trade(
pair='ETH/BTC',
open_rate=0.00001099,
exchange='bittrex',
open_order_id='123456789',
amount=90.99181073,
fee_open=0.0,
fee_close=0.0,
stake_amount=1,
open_date=open_date.datetime,
is_open=True
)
Trade.session.add(trade_buy)
Trade.session.add(open_trade)
freqtrade.check_handle_timedout()
assert log_has_re(r"Cannot query order for Trade\(id=1, pair=ETH/BTC, amount=90.99181073, "
r"open_rate=0.00001099, open_since="
f"{open_date.strftime('%Y-%m-%d %H:%M:%S')}"
f"{open_trade.open_date.strftime('%Y-%m-%d %H:%M:%S')}"
r"\) due to Traceback \(most recent call last\):\n*",
caplog)
def test_handle_timedout_limit_buy(mocker, default_conf) -> None:
def test_handle_timedout_limit_buy(mocker, default_conf, limit_buy_order) -> None:
patch_RPCManager(mocker)
patch_exchange(mocker)
cancel_order_mock = MagicMock()
cancel_order_mock = MagicMock(return_value=limit_buy_order)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
cancel_order=cancel_order_mock
@ -2200,13 +2194,14 @@ def test_handle_timedout_limit_buy(mocker, default_conf) -> None:
Trade.session = MagicMock()
trade = MagicMock()
order = {'remaining': 1,
'amount': 1}
assert freqtrade.handle_timedout_limit_buy(trade, order)
limit_buy_order['remaining'] = limit_buy_order['amount']
assert freqtrade.handle_timedout_limit_buy(trade, limit_buy_order)
assert cancel_order_mock.call_count == 1
cancel_order_mock.reset_mock()
limit_buy_order['amount'] = 2
assert not freqtrade.handle_timedout_limit_buy(trade, limit_buy_order)
assert cancel_order_mock.call_count == 1
order['amount'] = 2
assert not freqtrade.handle_timedout_limit_buy(trade, order)
assert cancel_order_mock.call_count == 2
def test_handle_timedout_limit_sell(mocker, default_conf) -> None:
@ -2418,13 +2413,6 @@ def test_execute_sell_with_stoploss_on_exchange(default_conf,
default_conf['exchange']['name'] = 'binance'
rpc_mock = patch_RPCManager(mocker)
patch_exchange(mocker)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
stoploss_limit = MagicMock(return_value={
'id': 123,
'info': {
@ -2433,11 +2421,16 @@ def test_execute_sell_with_stoploss_on_exchange(default_conf,
})
cancel_order = MagicMock(return_value=True)
mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
mocker.patch('freqtrade.exchange.Exchange.stoploss_limit', stoploss_limit)
mocker.patch('freqtrade.exchange.Exchange.cancel_order', cancel_order)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
markets=PropertyMock(return_value=markets),
symbol_amount_prec=lambda s, x, y: y,
symbol_price_prec=lambda s, x, y: y,
stoploss_limit=stoploss_limit,
cancel_order=cancel_order,
)
freqtrade = FreqtradeBot(default_conf)
freqtrade.strategy.order_types['stoploss_on_exchange'] = True
@ -2448,8 +2441,9 @@ def test_execute_sell_with_stoploss_on_exchange(default_conf,
trade = Trade.query.first()
assert trade
trades = [trade]
freqtrade.process_maybe_execute_sell(trade)
freqtrade.process_maybe_execute_sells(trades)
# Increase the price and sell it
mocker.patch.multiple(
@ -2477,7 +2471,9 @@ def test_may_execute_sell_after_stoploss_on_exchange_hit(default_conf,
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
markets=PropertyMock(return_value=markets)
markets=PropertyMock(return_value=markets),
symbol_amount_prec=lambda s, x, y: y,
symbol_price_prec=lambda s, x, y: y,
)
stoploss_limit = MagicMock(return_value={
@ -2487,8 +2483,6 @@ def test_may_execute_sell_after_stoploss_on_exchange_hit(default_conf,
}
})
mocker.patch('freqtrade.exchange.Exchange.symbol_amount_prec', lambda s, x, y: y)
mocker.patch('freqtrade.exchange.Exchange.symbol_price_prec', lambda s, x, y: y)
mocker.patch('freqtrade.exchange.Binance.stoploss_limit', stoploss_limit)
freqtrade = FreqtradeBot(default_conf)
@ -2498,7 +2492,8 @@ def test_may_execute_sell_after_stoploss_on_exchange_hit(default_conf,
# Create some test data
freqtrade.create_trades()
trade = Trade.query.first()
freqtrade.process_maybe_execute_sell(trade)
trades = [trade]
freqtrade.process_maybe_execute_sells(trades)
assert trade
assert trade.stoploss_order_id == '123'
assert trade.open_order_id is None
@ -2526,13 +2521,122 @@ def test_may_execute_sell_after_stoploss_on_exchange_hit(default_conf,
})
mocker.patch('freqtrade.exchange.Exchange.get_order', stoploss_limit_executed)
freqtrade.process_maybe_execute_sell(trade)
freqtrade.process_maybe_execute_sells(trades)
assert trade.stoploss_order_id is None
assert trade.is_open is False
assert trade.sell_reason == SellType.STOPLOSS_ON_EXCHANGE.value
assert rpc_mock.call_count == 2
def test_may_execute_sell_stoploss_on_exchange_multi(default_conf,
ticker, fee,
limit_buy_order,
markets, mocker) -> None:
"""
Tests workflow of selling stoploss_on_exchange.
Sells
* first trade as stoploss
* 2nd trade is kept
* 3rd trade is sold via sell-signal
"""
default_conf['max_open_trades'] = 3
default_conf['exchange']['name'] = 'binance'
patch_RPCManager(mocker)
patch_exchange(mocker)
stoploss_limit = {
'id': 123,
'info': {}
}
stoploss_order_open = {
"id": "123",
"timestamp": 1542707426845,
"datetime": "2018-11-20T09:50:26.845Z",
"lastTradeTimestamp": None,
"symbol": "BTC/USDT",
"type": "stop_loss_limit",
"side": "sell",
"price": 1.08801,
"amount": 90.99181074,
"cost": 0.0,
"average": 0.0,
"filled": 0.0,
"remaining": 0.0,
"status": "open",
"fee": None,
"trades": None
}
stoploss_order_closed = stoploss_order_open.copy()
stoploss_order_closed['status'] = 'closed'
# Sell first trade based on stoploss, keep 2nd and 3rd trade open
stoploss_order_mock = MagicMock(
side_effect=[stoploss_order_closed, stoploss_order_open, stoploss_order_open])
# Sell 3rd trade (not called for the first trade)
should_sell_mock = MagicMock(side_effect=[
SellCheckTuple(sell_flag=False, sell_type=SellType.NONE),
SellCheckTuple(sell_flag=True, sell_type=SellType.SELL_SIGNAL)]
)
cancel_order_mock = MagicMock()
mocker.patch('freqtrade.exchange.Binance.stoploss_limit', stoploss_limit)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_ticker=ticker,
get_fee=fee,
markets=PropertyMock(return_value=markets),
symbol_amount_prec=lambda s, x, y: y,
symbol_price_prec=lambda s, x, y: y,
get_order=stoploss_order_mock,
cancel_order=cancel_order_mock,
)
wallets_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.freqtradebot.FreqtradeBot',
create_stoploss_order=MagicMock(return_value=True),
update_trade_state=MagicMock(),
_notify_sell=MagicMock(),
)
mocker.patch("freqtrade.strategy.interface.IStrategy.should_sell", should_sell_mock)
mocker.patch("freqtrade.wallets.Wallets.update", wallets_mock)
freqtrade = FreqtradeBot(default_conf)
freqtrade.strategy.order_types['stoploss_on_exchange'] = True
# Switch ordertype to market to close trade immediately
freqtrade.strategy.order_types['sell'] = 'market'
patch_get_signal(freqtrade)
# Create some test data
freqtrade.create_trades()
wallets_mock.reset_mock()
Trade.session = MagicMock()
trades = Trade.query.all()
# Make sure stoploss-order is open and trade is bought (since we mock update_trade_state)
for trade in trades:
trade.stoploss_order_id = 3
trade.open_order_id = None
freqtrade.process_maybe_execute_sells(trades)
assert should_sell_mock.call_count == 2
# Only order for 3rd trade needs to be cancelled
assert cancel_order_mock.call_count == 1
# Wallets should only be called once per sell cycle
assert wallets_mock.call_count == 1
trade = trades[0]
assert trade.sell_reason == SellType.STOPLOSS_ON_EXCHANGE.value
assert not trade.is_open
trade = trades[1]
assert not trade.sell_reason
assert trade.is_open
trade = trades[2]
assert trade.sell_reason == SellType.SELL_SIGNAL.value
assert not trade.is_open
def test_execute_sell_market_order(default_conf, ticker, fee,
ticker_sell_up, markets, mocker) -> None:
rpc_mock = patch_RPCManager(mocker)
@ -2600,7 +2704,7 @@ def test_sell_profit_only_enable_profit(default_conf, limit_buy_order,
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
default_conf['experimental'] = {
default_conf['ask_strategy'] = {
'use_sell_signal': True,
'sell_profit_only': True,
}
@ -2632,7 +2736,7 @@ def test_sell_profit_only_disable_profit(default_conf, limit_buy_order,
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
default_conf['experimental'] = {
default_conf['ask_strategy'] = {
'use_sell_signal': True,
'sell_profit_only': False,
}
@ -2662,7 +2766,7 @@ def test_sell_profit_only_enable_loss(default_conf, limit_buy_order, fee, market
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
default_conf['experimental'] = {
default_conf['ask_strategy'] = {
'use_sell_signal': True,
'sell_profit_only': True,
}
@ -2692,7 +2796,7 @@ def test_sell_profit_only_disable_loss(default_conf, limit_buy_order, fee, marke
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
default_conf['experimental'] = {
default_conf['ask_strategy'] = {
'use_sell_signal': True,
'sell_profit_only': False,
}
@ -2761,7 +2865,7 @@ def test_ignore_roi_if_buy_signal(default_conf, limit_buy_order, fee, markets, m
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
default_conf['experimental'] = {
default_conf['ask_strategy'] = {
'ignore_roi_if_buy_signal': True
}
freqtrade = FreqtradeBot(default_conf)
@ -3029,7 +3133,7 @@ def test_disable_ignore_roi_if_buy_signal(default_conf, limit_buy_order,
get_fee=fee,
markets=PropertyMock(return_value=markets)
)
default_conf['experimental'] = {
default_conf['ask_strategy'] = {
'ignore_roi_if_buy_signal': False
}
freqtrade = FreqtradeBot(default_conf)
@ -3251,7 +3355,7 @@ def test_get_real_amount_wrong_amount(default_conf, trades_for_order, buy_order_
patch_get_signal(freqtrade)
# Amount does not change
with pytest.raises(OperationalException, match=r"Half bought\? Amounts don't match"):
with pytest.raises(DependencyException, match=r"Half bought\? Amounts don't match"):
freqtrade.get_real_amount(trade, limit_buy_order)

15
tests/test_indicator_helpers.py
View File

@ -1,15 +0,0 @@
# pragma pylint: disable=missing-docstring
import pandas as pd
from freqtrade.indicator_helpers import went_down, went_up
def test_went_up():
series = pd.Series([1, 2, 3, 1])
assert went_up(series).equals(pd.Series([False, True, True, False]))
def test_went_down():
series = pd.Series([1, 2, 3, 1])
assert went_down(series).equals(pd.Series([False, False, False, True]))

22
tests/test_plotting.py
View File

@ -53,11 +53,11 @@ def test_init_plotscript(default_conf, mocker, testdatadir):
assert "trades" in ret
assert "pairs" in ret
default_conf['pairs'] = ["POWR/BTC", "XLM/BTC"]
default_conf['pairs'] = ["POWR/BTC", "ADA/BTC"]
ret = init_plotscript(default_conf)
assert "tickers" in ret
assert "POWR/BTC" in ret["tickers"]
assert "XLM/BTC" in ret["tickers"]
assert "ADA/BTC" in ret["tickers"]
def test_add_indicators(default_conf, testdatadir, caplog):
@ -197,8 +197,7 @@ def test_generate_candlestick_graph_no_trades(default_conf, mocker, testdatadir)
# All buy-signals should be plotted
assert int(data.sell.sum()) == len(sell.x)
assert find_trace_in_fig_data(figure.data, "BB lower")
assert find_trace_in_fig_data(figure.data, "BB upper")
assert find_trace_in_fig_data(figure.data, "Bollinger Band")
assert row_mock.call_count == 2
assert trades_mock.call_count == 1
@ -215,11 +214,12 @@ def test_generate_plot_file(mocker, caplog):
store_plot_file(fig, filename="freqtrade-plot-UNITTEST_BTC-5m.html",
directory=Path("user_data/plots"))
expected_fn = str(Path("user_data/plots/freqtrade-plot-UNITTEST_BTC-5m.html"))
assert plot_mock.call_count == 1
assert plot_mock.call_args[0][0] == fig
assert (plot_mock.call_args_list[0][1]['filename']
== "user_data/plots/freqtrade-plot-UNITTEST_BTC-5m.html")
assert log_has("Stored plot as user_data/plots/freqtrade-plot-UNITTEST_BTC-5m.html",
== expected_fn)
assert log_has(f"Stored plot as {expected_fn}",
caplog)
@ -239,7 +239,7 @@ def test_add_profit(testdatadir):
fig1 = add_profit(fig, row=2, data=cum_profits, column='cum_profits', name='Profits')
figure = fig1.layout.figure
profits = find_trace_in_fig_data(figure.data, "Profits")
assert isinstance(profits, go.Scattergl)
assert isinstance(profits, go.Scatter)
assert profits.yaxis == "y2"
@ -247,7 +247,7 @@ def test_generate_profit_graph(testdatadir):
filename = testdatadir / "backtest-result_test.json"
trades = load_backtest_data(filename)
timerange = TimeRange.parse_timerange("20180110-20180112")
pairs = ["POWR/BTC", "XLM/BTC"]
pairs = ["POWR/BTC", "ADA/BTC"]
tickers = history.load_data(datadir=testdatadir,
pairs=pairs,
@ -268,14 +268,14 @@ def test_generate_profit_graph(testdatadir):
assert len(figure.data) == 4
avgclose = find_trace_in_fig_data(figure.data, "Avg close price")
assert isinstance(avgclose, go.Scattergl)
assert isinstance(avgclose, go.Scatter)
profit = find_trace_in_fig_data(figure.data, "Profit")
assert isinstance(profit, go.Scattergl)
assert isinstance(profit, go.Scatter)
for pair in pairs:
profit_pair = find_trace_in_fig_data(figure.data, f"Profit {pair}")
assert isinstance(profit_pair, go.Scattergl)
assert isinstance(profit_pair, go.Scatter)
def test_start_plot_dataframe(mocker):

12
tests/test_timerange.py
View File

@ -5,9 +5,6 @@ from freqtrade.configuration import TimeRange
def test_parse_timerange_incorrect() -> None:
assert TimeRange(None, 'line', 0, -200) == TimeRange.parse_timerange('-200')
assert TimeRange('line', None, 200, 0) == TimeRange.parse_timerange('200-')
assert TimeRange('index', 'index', 200, 500) == TimeRange.parse_timerange('200-500')
assert TimeRange('date', None, 1274486400, 0) == TimeRange.parse_timerange('20100522-')
assert TimeRange(None, 'date', 0, 1274486400) == TimeRange.parse_timerange('-20100522')
@ -20,9 +17,14 @@ def test_parse_timerange_incorrect() -> None:
timerange = TimeRange.parse_timerange('1231006505-1233360000')
assert TimeRange('date', 'date', 1231006505, 1233360000) == timerange
# TODO: Find solution for the following case (passing timestamp in ms)
timerange = TimeRange.parse_timerange('1231006505000-1233360000000')
assert TimeRange('date', 'date', 1231006505, 1233360000) != timerange
assert TimeRange('date', 'date', 1231006505, 1233360000) == timerange
timerange = TimeRange.parse_timerange('1231006505000-')
assert TimeRange('date', None, 1231006505, 0) == timerange
timerange = TimeRange.parse_timerange('-1231006505000')
assert TimeRange(None, 'date', 0, 1231006505) == timerange
with pytest.raises(Exception, match=r'Incorrect syntax.*'):
TimeRange.parse_timerange('-')

144
tests/test_utils.py
View File

@ -7,7 +7,8 @@ import pytest
from freqtrade import OperationalException
from freqtrade.state import RunMode
from freqtrade.utils import (setup_utils_configuration, start_create_userdir,
start_download_data, start_list_exchanges)
start_download_data, start_list_exchanges,
start_list_timeframes)
from tests.conftest import get_args, log_has, patch_exchange
@ -31,7 +32,7 @@ def test_list_exchanges(capsys):
start_list_exchanges(get_args(args))
captured = capsys.readouterr()
assert re.match(r"Exchanges supported by ccxt and available.*", captured.out)
assert re.match(r"Exchanges available for Freqtrade.*", captured.out)
assert re.match(r".*binance,.*", captured.out)
assert re.match(r".*bittrex,.*", captured.out)
@ -43,10 +44,125 @@ def test_list_exchanges(capsys):
start_list_exchanges(get_args(args))
captured = capsys.readouterr()
assert not re.match(r"Exchanges supported by ccxt and available.*", captured.out)
assert re.search(r"^binance$", captured.out, re.MULTILINE)
assert re.search(r"^bittrex$", captured.out, re.MULTILINE)
# Test with --all
args = [
"list-exchanges",
"--all",
]
start_list_exchanges(get_args(args))
captured = capsys.readouterr()
assert re.match(r"All exchanges supported by the ccxt library.*", captured.out)
assert re.match(r".*binance,.*", captured.out)
assert re.match(r".*bittrex,.*", captured.out)
assert re.match(r".*bitmex,.*", captured.out)
# Test with --one-column --all
args = [
"list-exchanges",
"--one-column",
"--all",
]
start_list_exchanges(get_args(args))
captured = capsys.readouterr()
assert re.search(r"^binance$", captured.out, re.MULTILINE)
assert re.search(r"^bittrex$", captured.out, re.MULTILINE)
assert re.search(r"^bitmex$", captured.out, re.MULTILINE)
def test_list_timeframes(mocker, capsys):
api_mock = MagicMock()
api_mock.timeframes = {'1m': 'oneMin',
'5m': 'fiveMin',
'30m': 'thirtyMin',
'1h': 'hour',
'1d': 'day',
}
patch_exchange(mocker, api_mock=api_mock)
args = [
"list-timeframes",
]
pargs = get_args(args)
pargs['config'] = None
with pytest.raises(OperationalException,
match=r"This command requires a configured exchange.*"):
start_list_timeframes(pargs)
# Test with --config config.json.example
args = [
'--config', 'config.json.example',
"list-timeframes",
]
start_list_timeframes(get_args(args))
captured = capsys.readouterr()
assert re.match("Timeframes available for the exchange `bittrex`: "
"1m, 5m, 30m, 1h, 1d",
captured.out)
# Test with --exchange bittrex
args = [
"list-timeframes",
"--exchange", "bittrex",
]
start_list_timeframes(get_args(args))
captured = capsys.readouterr()
assert re.match("Timeframes available for the exchange `bittrex`: "
"1m, 5m, 30m, 1h, 1d",
captured.out)
api_mock.timeframes = {'1m': '1m',
'5m': '5m',
'15m': '15m',
'30m': '30m',
'1h': '1h',
'6h': '6h',
'12h': '12h',
'1d': '1d',
'3d': '3d',
}
patch_exchange(mocker, api_mock=api_mock)
# Test with --exchange binance
args = [
"list-timeframes",
"--exchange", "binance",
]
start_list_timeframes(get_args(args))
captured = capsys.readouterr()
assert re.match("Timeframes available for the exchange `binance`: "
"1m, 5m, 15m, 30m, 1h, 6h, 12h, 1d, 3d",
captured.out)
# Test with --one-column
args = [
'--config', 'config.json.example',
"list-timeframes",
"--one-column",
]
start_list_timeframes(get_args(args))
captured = capsys.readouterr()
assert re.search(r"^1m$", captured.out, re.MULTILINE)
assert re.search(r"^5m$", captured.out, re.MULTILINE)
assert re.search(r"^1h$", captured.out, re.MULTILINE)
assert re.search(r"^1d$", captured.out, re.MULTILINE)
# Test with --exchange binance --one-column
args = [
"list-timeframes",
"--exchange", "binance",
"--one-column",
]
start_list_timeframes(get_args(args))
captured = capsys.readouterr()
assert re.search(r"^1m$", captured.out, re.MULTILINE)
assert re.search(r"^5m$", captured.out, re.MULTILINE)
assert re.search(r"^1h$", captured.out, re.MULTILINE)
assert re.search(r"^1d$", captured.out, re.MULTILINE)
def test_create_datadir_failed(caplog):
@ -144,3 +260,25 @@ def test_download_data_no_pairs(mocker, caplog):
with pytest.raises(OperationalException,
match=r"Downloading data requires a list of pairs\..*"):
start_download_data(pargs)
def test_download_data_trades(mocker, caplog):
dl_mock = mocker.patch('freqtrade.utils.refresh_backtest_trades_data',
MagicMock(return_value=[]))
convert_mock = mocker.patch('freqtrade.utils.convert_trades_to_ohlcv',
MagicMock(return_value=[]))
patch_exchange(mocker)
mocker.patch(
'freqtrade.exchange.Exchange.markets', PropertyMock(return_value={})
)
args = [
"download-data",
"--exchange", "kraken",
"--pairs", "ETH/BTC", "XRP/BTC",
"--days", "20",
"--dl-trades"
]
start_download_data(get_args(args))
assert dl_mock.call_args[1]['timerange'].starttype == "date"
assert dl_mock.call_count == 1
assert convert_mock.call_count == 1

1
tests/testdata/ADA_BTC-1m.json vendored
View File

File diff suppressed because one or more lines are too long

1
tests/testdata/DASH_BTC-1m.json vendored
View File

File diff suppressed because one or more lines are too long

1
tests/testdata/ETC_BTC-1m.json vendored
View File

File diff suppressed because one or more lines are too long

1
tests/testdata/ETH_BTC-1m.json vendored
View File

File diff suppressed because one or more lines are too long

1
tests/testdata/LTC_BTC-1m.json vendored
View File

File diff suppressed because one or more lines are too long

1
tests/testdata/NXT_BTC-1m.json vendored
View File

File diff suppressed because one or more lines are too long

1
tests/testdata/POWR_BTC-1m.json vendored
View File

File diff suppressed because one or more lines are too long

1
tests/testdata/XLM_BTC-1m.json vendored
View File

File diff suppressed because one or more lines are too long

1
tests/testdata/XMR_BTC-1m.json vendored
View File

File diff suppressed because one or more lines are too long

1
tests/testdata/XRP_ETH-1m.json vendored Normal file
View File

File diff suppressed because one or more lines are too long

1
tests/testdata/XRP_ETH-5m.json vendored Normal file
View File

File diff suppressed because one or more lines are too long

BIN
tests/testdata/XRP_ETH-trades.json.gz vendored Normal file
View File

Binary file not shown.

1
tests/testdata/ZEC_BTC-1m.json vendored
View File

File diff suppressed because one or more lines are too long

138
user_data/notebooks/strategy_analysis_example.ipynb
View File

@ -4,7 +4,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"## Strategy debugging example\n",
"# Strategy analysis example\n",
"\n",
"Debugging a strategy can be time-consuming. FreqTrade offers helper functions to visualize raw data."
]
@ -22,31 +22,7 @@
"metadata": {},
"outputs": [],
"source": [
"# Change directory\n",
"# Modify this cell to insure that the output shows the correct path.\n",
"import os\n",
"from pathlib import Path\n",
"\n",
"# Define all paths relative to the project root shown in the cell output\n",
"project_root = \"somedir/freqtrade\"\n",
"i=0\n",
"try:\n",
" os.chdirdir(project_root)\n",
" assert Path('LICENSE').is_file()\n",
"except:\n",
" while i<4 and (not Path('LICENSE').is_file()):\n",
" os.chdir(Path(Path.cwd(), '../'))\n",
" i+=1\n",
" project_root = Path.cwd()\n",
"print(Path.cwd())"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Customize these according to your needs.\n",
"\n",
"# Define some constants\n",
@ -54,9 +30,9 @@
"# Name of the strategy class\n",
"strategy_name = 'SampleStrategy'\n",
"# Path to user data\n",
"user_data_dir = 'user_data'\n",
"user_data_dir = Path('user_data')\n",
"# Location of the strategy\n",
"strategy_location = Path(user_data_dir, 'strategies')\n",
"strategy_location = user_data_dir / 'strategies'\n",
"# Location of the data\n",
"data_location = Path(user_data_dir, 'data', 'binance')\n",
"# Pair to analyze - Only use one pair here\n",
@ -70,7 +46,6 @@
"outputs": [],
"source": [
"# Load data using values set above\n",
"from pathlib import Path\n",
"from freqtrade.data.history import load_pair_history\n",
"\n",
"candles = load_pair_history(datadir=data_location,\n",
@ -132,10 +107,111 @@
"source": [
"# Report results\n",
"print(f\"Generated {df['buy'].sum()} buy signals\")\n",
"data = df.set_index('date', drop=True)\n",
"data = df.set_index('date', drop=False)\n",
"data.tail()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Load existing objects into a Jupyter notebook\n",
"\n",
"The following cells assume that you have already generated data using the cli. \n",
"They will allow you to drill deeper into your results, and perform analysis which otherwise would make the output very difficult to digest due to information overload."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Load backtest results to pandas dataframe\n",
"\n",
"Analyze a trades dataframe (also used below for plotting)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from freqtrade.data.btanalysis import load_backtest_data\n",
"\n",
"# Load backtest results\n",
"trades = load_backtest_data(user_data_dir / \"backtest_results/backtest-result.json\")\n",
"\n",
"# Show value-counts per pair\n",
"trades.groupby(\"pair\")[\"sell_reason\"].value_counts()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Load live trading results into a pandas dataframe\n",
"\n",
"In case you did already some trading and want to analyze your performance"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from freqtrade.data.btanalysis import load_trades_from_db\n",
"\n",
"# Fetch trades from database\n",
"trades = load_trades_from_db(\"sqlite:///tradesv3.sqlite\")\n",
"\n",
"# Display results\n",
"trades.groupby(\"pair\")[\"sell_reason\"].value_counts()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Plot results\n",
"\n",
"Freqtrade offers interactive plotting capabilities based on plotly."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from freqtrade.plot.plotting import generate_candlestick_graph\n",
"# Limit graph period to keep plotly quick and reactive\n",
"\n",
"data_red = data['2019-06-01':'2019-06-10']\n",
"# Generate candlestick graph\n",
"graph = generate_candlestick_graph(pair=pair,\n",
" data=data_red,\n",
" trades=trades,\n",
" indicators1=['sma20', 'ema50', 'ema55'],\n",
" indicators2=['rsi', 'macd', 'macdsignal', 'macdhist']\n",
" )\n",
"\n",
"\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# Show graph inline\n",
"# graph.show()\n",
"\n",
"# Render graph in a seperate window\n",
"graph.show(renderer=\"browser\")\n"
]
},
{
"cell_type": "markdown",
"metadata": {},
@ -161,7 +237,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.3"
"version": "3.7.4"
},
"mimetype": "text/x-python",
"name": "python",
@ -212,5 +288,5 @@
"version": 3
},
"nbformat": 4,
"nbformat_minor": 2
"nbformat_minor": 4
}

51
user_data/strategies/sample_strategy.py
View File

@ -27,40 +27,39 @@ class SampleStrategy(IStrategy):
- the prototype for the methods: minimal_roi, stoploss, populate_indicators, populate_buy_trend,
populate_sell_trend, hyperopt_space, buy_strategy_generator
"""
# Strategy intervace version - allow new iterations of the strategy interface.
# Strategy interface version - allow new iterations of the strategy interface.
# Check the documentation or the Sample strategy to get the latest version.
INTERFACE_VERSION = 2
# Minimal ROI designed for the strategy.
# This attribute will be overridden if the config file contains "minimal_roi"
# This attribute will be overridden if the config file contains "minimal_roi".
minimal_roi = {
"40": 0.0,
"30": 0.01,
"20": 0.02,
"60": 0.01,
"30": 0.02,
"0": 0.04
}
# Optimal stoploss designed for the strategy
# This attribute will be overridden if the config file contains "stoploss"
# Optimal stoploss designed for the strategy.
# This attribute will be overridden if the config file contains "stoploss".
stoploss = -0.10
# trailing stoploss
# Trailing stoploss
trailing_stop = False
# trailing_stop_positive = 0.01
# trailing_stop_positive_offset = 0.0 # Disabled / not configured
# Optimal ticker interval for the strategy
# Optimal ticker interval for the strategy.
ticker_interval = '5m'
# run "populate_indicators" only for new candle
# Run "populate_indicators()" only for new candle.
process_only_new_candles = False
# Experimental settings (configuration will overide these if set)
use_sell_signal = False
# These values can be overridden in the "ask_strategy" section in the config.
use_sell_signal = True
sell_profit_only = False
ignore_roi_if_buy_signal = False
# Optional order type mapping
# Optional order type mapping.
order_types = {
'buy': 'limit',
'sell': 'limit',
@ -68,7 +67,7 @@ class SampleStrategy(IStrategy):
'stoploss_on_exchange': False
}
# Optional order time in force
# Optional order time in force.
order_time_in_force = {
'buy': 'gtc',
'sell': 'gtc'
@ -99,13 +98,16 @@ class SampleStrategy(IStrategy):
:return: a Dataframe with all mandatory indicators for the strategies
"""
# Momentum Indicator
# Momentum Indicators
# ------------------------------------
# RSI
dataframe['rsi'] = ta.RSI(dataframe)
"""
# ADX
dataframe['adx'] = ta.ADX(dataframe)
"""
# Awesome oscillator
dataframe['ao'] = qtpylib.awesome_oscillator(dataframe)
@ -133,9 +135,6 @@ class SampleStrategy(IStrategy):
# ROC
dataframe['roc'] = ta.ROC(dataframe)
# RSI
dataframe['rsi'] = ta.RSI(dataframe)
# Inverse Fisher transform on RSI, values [-1.0, 1.0] (https://goo.gl/2JGGoy)
rsi = 0.1 * (dataframe['rsi'] - 50)
dataframe['fisher_rsi'] = (numpy.exp(2 * rsi) - 1) / (numpy.exp(2 * rsi) + 1)
@ -255,7 +254,7 @@ class SampleStrategy(IStrategy):
dataframe['ha_low'] = heikinashi['low']
"""
# Retrieve best bid and best ask
# Retrieve best bid and best ask from the orderbook
# ------------------------------------
"""
# first check if dataprovider is available
@ -277,9 +276,9 @@ class SampleStrategy(IStrategy):
"""
dataframe.loc[
(
(dataframe['adx'] > 30) &
(dataframe['tema'] <= dataframe['bb_middleband']) &
(dataframe['tema'] > dataframe['tema'].shift(1)) &
(qtpylib.crossed_above(dataframe['rsi'], 30)) & # Signal: RSI crosses above 30
(dataframe['tema'] <= dataframe['bb_middleband']) & # Guard: tema below BB middle
(dataframe['tema'] > dataframe['tema'].shift(1)) & # Guard: tema is raising
(dataframe['volume'] > 0) # Make sure Volume is not 0
),
'buy'] = 1
@ -295,9 +294,9 @@ class SampleStrategy(IStrategy):
"""
dataframe.loc[
(
(dataframe['adx'] > 70) &
(dataframe['tema'] > dataframe['bb_middleband']) &
(dataframe['tema'] < dataframe['tema'].shift(1)) &
(qtpylib.crossed_above(dataframe['rsi'], 70)) & # Signal: RSI crosses above 70
(dataframe['tema'] > dataframe['bb_middleband']) & # Guard: tema above BB middle
(dataframe['tema'] < dataframe['tema'].shift(1)) & # Guard: tema is falling
(dataframe['volume'] > 0) # Make sure Volume is not 0
),
'sell'] = 1