lychiyu/freqtrade_origin
1
0
Fork 0
mirror of https://github.com/freqtrade/freqtrade.git synced 2024-11-10 10:21:59 +00:00
Code Issues Actions 2 Packages Projects Releases Wiki Activity

Merge pull request #3543 from freqtrade/new_Release

Browse Source 
New release 2020.6
This commit is contained in:
Matthias 2020-06-30 16:00:11 +02:00 committed by GitHub
commit d0d634260f
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
113 changed files with 2206 additions and 850 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

5
README.md
View File

@ -82,7 +82,8 @@ positional arguments:
new-hyperopt Create new hyperopt
new-strategy Create new strategy
download-data Download backtesting data.
convert-data Convert candle (OHLCV) data from one format to another.
convert-data Convert candle (OHLCV) data from one format to
another.
convert-trade-data Convert trade data from one format to another.
backtesting Backtesting module.
edge Edge module.
@ -94,7 +95,7 @@ positional arguments:
list-markets Print markets on exchange.
list-pairs Print pairs on exchange.
list-strategies Print available strategies.
list-timeframes Print available ticker intervals (timeframes) for the exchange.
list-timeframes Print available timeframes for the exchange.
show-trades Show trades.
test-pairlist Test your pairlist configuration.
plot-dataframe Plot candles with indicators.

12
config.json.example
View File

@ -4,7 +4,7 @@
"stake_amount": 0.05,
"tradable_balance_ratio": 0.99,
"fiat_display_currency": "USD",
"ticker_interval": "5m",
"timeframe": "5m",
"dry_run": false,
"cancel_open_orders_on_exit": false,
"trailing_stop": false,
@ -76,6 +76,16 @@
"token": "your_telegram_token",
"chat_id": "your_telegram_chat_id"
},
"api_server": {
"enabled": false,
"listen_ip_address": "127.0.0.1",
"listen_port": 8080,
"verbosity": "info",
"jwt_secret_key": "somethingrandom",
"CORS_origins": [],
"username": "",
"password": ""
},
"initial_state": "running",
"forcebuy_enable": false,
"internals": {

12
config_binance.json.example
View File

@ -4,7 +4,7 @@
"stake_amount": 0.05,
"tradable_balance_ratio": 0.99,
"fiat_display_currency": "USD",
"ticker_interval": "5m",
"timeframe": "5m",
"dry_run": true,
"cancel_open_orders_on_exit": false,
"trailing_stop": false,
@ -81,6 +81,16 @@
"token": "your_telegram_token",
"chat_id": "your_telegram_chat_id"
},
"api_server": {
"enabled": false,
"listen_ip_address": "127.0.0.1",
"listen_port": 8080,
"verbosity": "info",
"jwt_secret_key": "somethingrandom",
"CORS_origins": [],
"username": "",
"password": ""
},
"initial_state": "running",
"forcebuy_enable": false,
"internals": {

6
config_full.json.example
View File

@ -9,7 +9,7 @@
"last_stake_amount_min_ratio": 0.5,
"dry_run": false,
"cancel_open_orders_on_exit": false,
"ticker_interval": "5m",
"timeframe": "5m",
"trailing_stop": false,
"trailing_stop_positive": 0.005,
"trailing_stop_positive_offset": 0.0051,
@ -64,6 +64,7 @@
"sort_key": "quoteVolume",
"refresh_period": 1800
},
{"method": "AgeFilter", "min_days_listed": 10},
{"method": "PrecisionFilter"},
{"method": "PriceFilter", "low_price_ratio": 0.01},
{"method": "SpreadFilter", "max_spread_ratio": 0.005}
@ -121,7 +122,9 @@
"enabled": false,
"listen_ip_address": "127.0.0.1",
"listen_port": 8080,
"verbosity": "info",
"jwt_secret_key": "somethingrandom",
"CORS_origins": [],
"username": "freqtrader",
"password": "SuperSecurePassword"
},
@ -132,6 +135,7 @@
"process_throttle_secs": 5,
"heartbeat_interval": 60
},
"disable_dataframe_checks": false,
"strategy": "DefaultStrategy",
"strategy_path": "user_data/strategies/",
"dataformat_ohlcv": "json",

12
config_kraken.json.example
View File

@ -4,7 +4,7 @@
"stake_amount": 10,
"tradable_balance_ratio": 0.99,
"fiat_display_currency": "EUR",
"ticker_interval": "5m",
"timeframe": "5m",
"dry_run": true,
"cancel_open_orders_on_exit": false,
"trailing_stop": false,
@ -87,6 +87,16 @@
"token": "your_telegram_token",
"chat_id": "your_telegram_chat_id"
},
"api_server": {
"enabled": false,
"listen_ip_address": "127.0.0.1",
"listen_port": 8080,
"verbosity": "info",
"jwt_secret_key": "somethingrandom",
"CORS_origins": [],
"username": "",
"password": ""
},
"initial_state": "running",
"forcebuy_enable": false,
"internals": {

4
docs/advanced-hyperopt.md
View File

@ -63,8 +63,8 @@ class SuperDuperHyperOptLoss(IHyperOptLoss):
* 0.25: Avoiding trade loss
* 1.0 to total profit, compared to the expected value (`EXPECTED_MAX_PROFIT`) defined above
"""
total_profit = results.profit_percent.sum()
trade_duration = results.trade_duration.mean()
total_profit = results['profit_percent'].sum()
trade_duration = results['trade_duration'].mean()
trade_loss = 1 - 0.25 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5.8)
profit_loss = max(0, 1 - total_profit / EXPECTED_MAX_PROFIT)

48
docs/advanced-setup.md
View File

@ -4,6 +4,54 @@ This page explains some advanced tasks and configuration options that can be per
If you do not know what things mentioned here mean, you probably do not need it.
## Running multiple instances of Freqtrade
This section will show you how to run multiple bots at the same time, on the same machine.
### Things to consider
* Use different database files.
* Use different Telegram bots (requires multiple different configuration files; applies only when Telegram is enabled).
* Use different ports (applies only when Freqtrade REST API webserver is enabled).
### Different database files
In order to keep track of your trades, profits, etc., freqtrade is using a SQLite database where it stores various types of information such as the trades you performed in the past and the current position(s) you are holding at any time. This allows you to keep track of your profits, but most importantly, keep track of ongoing activity if the bot process would be restarted or would be terminated unexpectedly.
Freqtrade will, by default, use separate database files for dry-run and live bots (this assumes no database-url is given in either configuration nor via command line argument).
For live trading mode, the default database will be `tradesv3.sqlite` and for dry-run it will be `tradesv3.dryrun.sqlite`.
The optional argument to the trade command used to specify the path of these files is `--db-url`, which requires a valid SQLAlchemy url.
So when you are starting a bot with only the config and strategy arguments in dry-run mode, the following 2 commands would have the same outcome.
``` bash
freqtrade trade -c MyConfig.json -s MyStrategy
# is equivalent to
freqtrade trade -c MyConfig.json -s MyStrategy --db-url sqlite:///tradesv3.dryrun.sqlite
```
It means that if you are running the trade command in two different terminals, for example to test your strategy both for trades in USDT and in another instance for trades in BTC, you will have to run them with different databases.
If you specify the URL of a database which does not exist, freqtrade will create one with the name you specified. So to test your custom strategy with BTC and USDT stake currencies, you could use the following commands (in 2 separate terminals):
``` bash
# Terminal 1:
freqtrade trade -c MyConfigBTC.json -s MyCustomStrategy --db-url sqlite:///user_data/tradesBTC.dryrun.sqlite
# Terminal 2:
freqtrade trade -c MyConfigUSDT.json -s MyCustomStrategy --db-url sqlite:///user_data/tradesUSDT.dryrun.sqlite
```
Conversely, if you wish to do the same thing in production mode, you will also have to create at least one new database (in addition to the default one) and specify the path to the "live" databases, for example:
``` bash
# Terminal 1:
freqtrade trade -c MyConfigBTC.json -s MyCustomStrategy --db-url sqlite:///user_data/tradesBTC.live.sqlite
# Terminal 2:
freqtrade trade -c MyConfigUSDT.json -s MyCustomStrategy --db-url sqlite:///user_data/tradesUSDT.live.sqlite
```
For more information regarding usage of the sqlite databases, for example to manually enter or remove trades, please refer to the [SQL Cheatsheet](sql_cheatsheet.md).
## Configure the bot running as a systemd service
Copy the `freqtrade.service` file to your systemd user directory (usually `~/.config/systemd/user`) and update `WorkingDirectory` and `ExecStart` to match your setup.

10
docs/backtesting.md
View File

@ -12,7 +12,7 @@ real data. This is what we call
[backtesting](https://en.wikipedia.org/wiki/Backtesting).
Backtesting will use the crypto-currencies (pairs) from your config file and load historical candle (OHCLV) data from `user_data/data/<exchange>` by default.
If no data is available for the exchange / pair / timeframe (ticker interval) combination, backtesting will ask you to download them first using `freqtrade download-data`.
If no data is available for the exchange / pair / timeframe combination, backtesting will ask you to download them first using `freqtrade download-data`.
For details on downloading, please refer to the [Data Downloading](data-download.md) section in the documentation.
The result of backtesting will confirm if your bot has better odds of making a profit than a loss.
@ -35,7 +35,7 @@ freqtrade backtesting
#### With 1 min candle (OHLCV) data
```bash
freqtrade backtesting --ticker-interval 1m
freqtrade backtesting --timeframe 1m
```
#### Using a different on-disk historical candle (OHLCV) data source
@ -58,7 +58,7 @@ Where `-s SampleStrategy` refers to the class name within the strategy file `sam
#### Comparing multiple Strategies
```bash
freqtrade backtesting --strategy-list SampleStrategy1 AwesomeStrategy --ticker-interval 5m
freqtrade backtesting --strategy-list SampleStrategy1 AwesomeStrategy --timeframe 5m
```
Where `SampleStrategy1` and `AwesomeStrategy` refer to class names of strategies.
@ -228,13 +228,13 @@ You can then load the trades to perform further analysis as shown in our [data a
To compare multiple strategies, a list of Strategies can be provided to backtesting.
This is limited to 1 timeframe (ticker interval) value per run. However, data is only loaded once from disk so if you have multiple
This is limited to 1 timeframe value per run. However, data is only loaded once from disk so if you have multiple
strategies you'd like to compare, this will give a nice runtime boost.
All listed Strategies need to be in the same directory.
``` bash
freqtrade backtesting --timerange 20180401-20180410 --ticker-interval 5m --strategy-list Strategy001 Strategy002 --export trades
freqtrade backtesting --timerange 20180401-20180410 --timeframe 5m --strategy-list Strategy001 Strategy002 --export trades
```
This will save the results to `user_data/backtest_results/backtest-result-<strategy>.json`, injecting the strategy-name into the target filename.

50
docs/bot-usage.md
View File

@ -9,22 +9,35 @@ This page explains the different parameters of the bot and how to run it.
```
usage: freqtrade [-h] [-V]
{trade,backtesting,edge,hyperopt,create-userdir,list-exchanges,list-timeframes,download-data,plot-dataframe,plot-profit}
{trade,create-userdir,new-config,new-hyperopt,new-strategy,download-data,convert-data,convert-trade-data,backtesting,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-hyperopts,list-markets,list-pairs,list-strategies,list-timeframes,show-trades,test-pairlist,plot-dataframe,plot-profit}
...
Free, open source crypto trading bot
positional arguments:
{trade,backtesting,edge,hyperopt,create-userdir,list-exchanges,list-timeframes,download-data,plot-dataframe,plot-profit}
{trade,create-userdir,new-config,new-hyperopt,new-strategy,download-data,convert-data,convert-trade-data,backtesting,edge,hyperopt,hyperopt-list,hyperopt-show,list-exchanges,list-hyperopts,list-markets,list-pairs,list-strategies,list-timeframes,show-trades,test-pairlist,plot-dataframe,plot-profit}
trade Trade module.
create-userdir Create user-data directory.
new-config Create new config
new-hyperopt Create new hyperopt
new-strategy Create new strategy
download-data Download backtesting data.
convert-data Convert candle (OHLCV) data from one format to
another.
convert-trade-data Convert trade data from one format to another.
backtesting Backtesting module.
edge Edge module.
hyperopt Hyperopt module.
create-userdir Create user-data directory.
hyperopt-list List Hyperopt results
hyperopt-show Show details of Hyperopt results
list-exchanges Print available exchanges.
list-timeframes Print available ticker intervals (timeframes) for the
exchange.
download-data Download backtesting data.
list-hyperopts Print available hyperopt classes.
list-markets Print markets on exchange.
list-pairs Print pairs on exchange.
list-strategies Print available strategies.
list-timeframes Print available timeframes for the exchange.
show-trades Show trades.
test-pairlist Test your pairlist configuration.
plot-dataframe Plot candles with indicators.
plot-profit Generate plot showing profits.
@ -72,7 +85,6 @@ Strategy arguments:
Specify strategy class name which will be used by the
bot.
--strategy-path PATH Specify additional strategy lookup path.
.
```
@ -197,7 +209,7 @@ Backtesting also uses the config specified via `-c/--config`.
```
usage: freqtrade backtesting [-h] [-v] [--logfile FILE] [-V] [-c PATH]
[-d PATH] [--userdir PATH] [-s NAME]
[--strategy-path PATH] [-i TICKER_INTERVAL]
[--strategy-path PATH] [-i TIMEFRAME]
[--timerange TIMERANGE] [--max-open-trades INT]
[--stake-amount STAKE_AMOUNT] [--fee FLOAT]
[--eps] [--dmmp]
@ -206,7 +218,7 @@ usage: freqtrade backtesting [-h] [-v] [--logfile FILE] [-V] [-c PATH]
optional arguments:
-h, --help show this help message and exit
-i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
-i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME
Specify ticker interval (`1m`, `5m`, `30m`, `1h`,
`1d`).
--timerange TIMERANGE
@ -280,7 +292,7 @@ to find optimal parameter values for your strategy.
```
usage: freqtrade hyperopt [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
[--userdir PATH] [-s NAME] [--strategy-path PATH]
[-i TICKER_INTERVAL] [--timerange TIMERANGE]
[-i TIMEFRAME] [--timerange TIMERANGE]
[--max-open-trades INT]
[--stake-amount STAKE_AMOUNT] [--fee FLOAT]
[--hyperopt NAME] [--hyperopt-path PATH] [--eps]
@ -292,7 +304,7 @@ usage: freqtrade hyperopt [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
optional arguments:
-h, --help show this help message and exit
-i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
-i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME
Specify ticker interval (`1m`, `5m`, `30m`, `1h`,
`1d`).
--timerange TIMERANGE
@ -323,7 +335,7 @@ optional arguments:
--print-all Print all results, not only the best ones.
--no-color Disable colorization of hyperopt results. May be
useful if you are redirecting output to a file.
--print-json Print best results in JSON format.
--print-json Print output in JSON format.
-j JOBS, --job-workers JOBS
The number of concurrently running jobs for
hyperoptimization (hyperopt worker processes). If -1
@ -341,11 +353,11 @@ optional arguments:
class (IHyperOptLoss). Different functions can
generate completely different results, since the
target for optimization is different. Built-in
Hyperopt-loss-functions are:
DefaultHyperOptLoss, OnlyProfitHyperOptLoss,
SharpeHyperOptLoss, SharpeHyperOptLossDaily,
SortinoHyperOptLoss, SortinoHyperOptLossDaily.
(default: `DefaultHyperOptLoss`).
Hyperopt-loss-functions are: DefaultHyperOptLoss,
OnlyProfitHyperOptLoss, SharpeHyperOptLoss,
SharpeHyperOptLossDaily, SortinoHyperOptLoss,
SortinoHyperOptLossDaily.(default:
`DefaultHyperOptLoss`).
Common arguments:
-v, --verbose Verbose mode (-vv for more, -vvv to get all messages).
@ -378,13 +390,13 @@ To know your trade expectancy and winrate against historical data, you can use E
```
usage: freqtrade edge [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
[--userdir PATH] [-s NAME] [--strategy-path PATH]
[-i TICKER_INTERVAL] [--timerange TIMERANGE]
[-i TIMEFRAME] [--timerange TIMERANGE]
[--max-open-trades INT] [--stake-amount STAKE_AMOUNT]
[--fee FLOAT] [--stoplosses STOPLOSS_RANGE]
optional arguments:
-h, --help show this help message and exit
-i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
-i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME
Specify ticker interval (`1m`, `5m`, `30m`, `1h`,
`1d`).
--timerange TIMERANGE

75
docs/configuration.md
View File

@ -47,14 +47,14 @@ Mandatory parameters are marked as **Required**, which means that they are requi
| `amend_last_stake_amount` | Use reduced last stake amount if necessary. [More information below](#configuring-amount-per-trade). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
| `last_stake_amount_min_ratio` | Defines minimum stake amount that has to be left and executed. Applies only to the last stake amount when it's amended to a reduced value (i.e. if `amend_last_stake_amount` is set to `true`). [More information below](#configuring-amount-per-trade). <br>*Defaults to `0.5`.* <br> **Datatype:** Float (as ratio)
| `amount_reserve_percent` | Reserve some amount in min pair stake amount. The bot will reserve `amount_reserve_percent` + stoploss value when calculating min pair stake amount in order to avoid possible trade refusals. <br>*Defaults to `0.05` (5%).* <br> **Datatype:** Positive Float as ratio.
| `ticker_interval` | The timeframe (ticker interval) to use (e.g `1m`, `5m`, `15m`, `30m`, `1h` ...). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** String
| `timeframe` | The timeframe (former ticker interval) to use (e.g `1m`, `5m`, `15m`, `30m`, `1h` ...). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** String
| `fiat_display_currency` | Fiat currency used to show your profits. [More information below](#what-values-can-be-used-for-fiat_display_currency). <br> **Datatype:** String
| `dry_run` | **Required.** Define if the bot must be in Dry Run or production mode. <br>*Defaults to `true`.* <br> **Datatype:** Boolean
| `dry_run_wallet` | Define the starting amount in stake currency for the simulated wallet used by the bot running in the Dry Run mode.<br>*Defaults to `1000`.* <br> **Datatype:** Float
| `cancel_open_orders_on_exit` | Cancel open orders when the `/stop` RPC command is issued, `Ctrl+C` is pressed or the bot dies unexpectedly. When set to `true`, this allows you to use `/stop` to cancel unfilled and partially filled orders in the event of a market crash. It does not impact open positions. <br>*Defaults to `false`.* <br> **Datatype:** Boolean
| `process_only_new_candles` | Enable processing of indicators only when new candles arrive. If false each loop populates the indicators, this will mean the same candle is processed many times creating system load but can be useful of your strategy depends on tick data not only candle. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
| `minimal_roi` | **Required.** Set the threshold in percent the bot will use to sell a trade. [More information below](#understand-minimal_roi). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Dict
| `stoploss` | **Required.** Value of the stoploss in percent used by the bot. More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Float (as ratio)
| `minimal_roi` | **Required.** Set the threshold as ratio the bot will use to sell a trade. [More information below](#understand-minimal_roi). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Dict
| `stoploss` | **Required.** Value as ratio of the stoploss used by the bot. More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Float (as ratio)
| `trailing_stop` | Enables trailing stoploss (based on `stoploss` in either configuration or strategy file). More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Boolean
| `trailing_stop_positive` | Changes stoploss once profit has been reached. More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Float
| `trailing_stop_positive_offset` | Offset on when to apply `trailing_stop_positive`. Percentage value which should be positive. More details in the [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `0.0` (no offset).* <br> **Datatype:** Float
@ -83,7 +83,8 @@ Mandatory parameters are marked as **Required**, which means that they are requi
| `exchange.password` | API password to use for the exchange. Only required when you are in production mode and for exchanges that use password for API requests.<br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
| `exchange.pair_whitelist` | List of pairs to use by the bot for trading and to check for potential trades during backtesting. Not used by VolumePairList (see [below](#pairlists-and-pairlist-handlers)). <br> **Datatype:** List
| `exchange.pair_blacklist` | List of pairs the bot must absolutely avoid for trading and backtesting (see [below](#pairlists-and-pairlist-handlers)). <br> **Datatype:** List
| `exchange.ccxt_config` | Additional CCXT parameters passed to the regular 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) <br> **Datatype:** Dict
| `exchange.ccxt_config` | Additional CCXT parameters passed to both ccxt instances (sync and async). This is usually the correct place for ccxt configurations. Parameters may differ from exchange to exchange and are documented in the [ccxt documentation](https://ccxt.readthedocs.io/en/latest/manual.html#instantiation) <br> **Datatype:** Dict
| `exchange.ccxt_sync_config` | Additional CCXT parameters passed to the regular (sync) 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) <br> **Datatype:** Dict
| `exchange.ccxt_async_config` | 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) <br> **Datatype:** Dict
| `exchange.markets_refresh_interval` | The interval in minutes in which markets are reloaded. <br>*Defaults to `60` minutes.* <br> **Datatype:** Positive Integer
| `edge.*` | Please refer to [edge configuration document](edge.md) for detailed explanation.
@ -102,11 +103,13 @@ Mandatory parameters are marked as **Required**, which means that they are requi
| `api_server.enabled` | Enable usage of API Server. See the [API Server documentation](rest-api.md) for more details. <br> **Datatype:** Boolean
| `api_server.listen_ip_address` | Bind IP address. See the [API Server documentation](rest-api.md) for more details. <br> **Datatype:** IPv4
| `api_server.listen_port` | Bind Port. See the [API Server documentation](rest-api.md) for more details. <br>**Datatype:** Integer between 1024 and 65535
| `api_server.verbosity` | Logging verbosity. `info` will print all RPC Calls, while "error" will only display errors. <br>**Datatype:** Enum, either `info` or `error`. Defaults to `info`.
| `api_server.username` | Username for API server. See the [API Server documentation](rest-api.md) for more details. <br>**Keep it in secret, do not disclose publicly.**<br> **Datatype:** String
| `api_server.password` | Password for API server. See the [API Server documentation](rest-api.md) for more details. <br>**Keep it in secret, do not disclose publicly.**<br> **Datatype:** String
| `db_url` | Declares database URL to use. NOTE: This defaults to `sqlite:///tradesv3.dryrun.sqlite` if `dry_run` is `true`, and to `sqlite:///tradesv3.sqlite` for production instances. <br> **Datatype:** String, SQLAlchemy connect string
| `initial_state` | Defines the initial application state. More information below. <br>*Defaults to `stopped`.* <br> **Datatype:** Enum, either `stopped` or `running`
| `forcebuy_enable` | Enables the RPC Commands to force a buy. More information below. <br> **Datatype:** Boolean
| `disable_dataframe_checks` | Disable checking the OHLCV dataframe returned from the strategy methods for correctness. Only use when intentionally changing the dataframe and understand what you are doing. [Strategy Override](#parameters-in-the-strategy).<br> *Defaults to `False`*. <br> **Datatype:** Boolean
| `strategy` | **Required** Defines Strategy class to use. Recommended to be set via `--strategy NAME`. <br> **Datatype:** ClassName
| `strategy_path` | Adds an additional strategy lookup path (must be a directory). <br> **Datatype:** String
| `internals.process_throttle_secs` | Set the process throttle. Value in second. <br>*Defaults to `5` seconds.* <br> **Datatype:** Positive Integer
@ -123,7 +126,7 @@ The following parameters can be set in either configuration file or strategy.
Values set in the configuration file always overwrite values set in the strategy.
* `minimal_roi`
* `ticker_interval`
* `timeframe`
* `stoploss`
* `trailing_stop`
* `trailing_stop_positive`
@ -135,6 +138,7 @@ Values set in the configuration file always overwrite values set in the strategy
* `stake_currency`
* `stake_amount`
* `unfilledtimeout`
* `disable_dataframe_checks`
* `use_sell_signal` (ask_strategy)
* `sell_profit_only` (ask_strategy)
* `ignore_roi_if_buy_signal` (ask_strategy)
@ -214,7 +218,7 @@ To allow the bot to trade all the available `stake_currency` in your account (mi
### Understand minimal_roi
The `minimal_roi` configuration parameter is a JSON object where the key is a duration
in minutes and the value is the minimum ROI in percent.
in minutes and the value is the minimum ROI as ratio.
See the example below:
```json
@ -268,7 +272,7 @@ the static list of pairs) if we should buy.
### Understand order_types
The `order_types` configuration parameter maps actions (`buy`, `sell`, `stoploss`) to order-types (`market`, `limit`, ...) as well as configures stoploss to be on the exchange and defines stoploss on exchange update interval in seconds.
The `order_types` configuration parameter maps actions (`buy`, `sell`, `stoploss`, `emergencysell`) to order-types (`market`, `limit`, ...) as well as configures stoploss to be on the exchange and defines stoploss on exchange update interval in seconds.
This allows to buy using limit orders, sell using
limit-orders, and create stoplosses using using market orders. It also allows to set the
@ -284,8 +288,12 @@ If this is configured, the following 4 values (`buy`, `sell`, `stoploss` and
`emergencysell` is an optional value, which defaults to `market` and is used when creating stoploss on exchange orders fails.
The below is the default which is used if this is not configured in either strategy or configuration file.
Since `stoploss_on_exchange` uses limit orders, the exchange needs 2 prices, the stoploss_price and the Limit price.
`stoploss` defines the stop-price - and limit should be slightly below this. This defaults to 0.99 / 1% (configurable via `stoploss_on_exchange_limit_ratio`).
Not all Exchanges support `stoploss_on_exchange`. If an exchange supports both limit and market stoploss orders, then the value of `stoploss` will be used to determine the stoploss type.
If `stoploss_on_exchange` uses limit orders, the exchange needs 2 prices, the stoploss_price and the Limit price.
`stoploss` defines the stop-price - and limit should be slightly below this.
This defaults to 0.99 / 1% (configurable via `stoploss_on_exchange_limit_ratio`).
Calculation example: we bought the asset at 100$.
Stop-price is 95$, then limit would be `95 * 0.99 = 94.05$` - so the stoploss will happen between 95$ and 94.05$.
@ -327,7 +335,10 @@ Configuration:
refer to [the stoploss documentation](stoploss.md).
!!! Note
If `stoploss_on_exchange` is enabled and the stoploss is cancelled manually on the exchange, then the bot will create a new order.
If `stoploss_on_exchange` is enabled and the stoploss is cancelled manually on the exchange, then the bot will create a new stoploss order.
!!! Warning "Using market orders"
Please read the section [Market order pricing](#market-order-pricing) section when using market orders.
!!! Warning "Warning: stoploss_on_exchange failures"
If stoploss on exchange creation fails for some reason, then an "emergency sell" is initiated. By default, this will sell the asset using a market order. The order-type for the emergency-sell can be changed by setting the `emergencysell` value in the `order_types` dictionary - however this is not advised.
@ -455,6 +466,9 @@ Prices are always retrieved right before an order is placed, either by querying
!!! Note
Orderbook data used by Freqtrade are the data retrieved from exchange by the ccxt's function `fetch_order_book()`, i.e. are usually data from the L2-aggregated orderbook, while the ticker data are the structures returned by the ccxt's `fetch_ticker()`/`fetch_tickers()` functions. Refer to the ccxt library [documentation](https://github.com/ccxt/ccxt/wiki/Manual#market-data) for more details.
!!! Warning "Using market orders"
Please read the section [Market order pricing](#market-order-pricing) section when using market orders.
### Buy price
#### Check depth of market
@ -549,13 +563,36 @@ A fixed slot (mirroring `bid_strategy.order_book_top`) can be defined by setting
When not using orderbook (`ask_strategy.use_order_book=False`), the price at the `ask_strategy.price_side` side (defaults to `"ask"`) from the ticker will be used as the sell price.
### Market order pricing
When using market orders, prices should be configured to use the "correct" side of the orderbook to allow realistic pricing detection.
Assuming both buy and sell are using market orders, a configuration similar to the following might be used
``` jsonc
"order_types": {
"buy": "market",
"sell": "market"
// ...
},
"bid_strategy": {
"price_side": "ask",
// ...
},
"ask_strategy":{
"price_side": "bid",
// ...
},
```
Obviously, if only one side is using limit orders, different pricing combinations can be used.
## Pairlists and Pairlist Handlers
Pairlist Handlers define the list of pairs (pairlist) that the bot should trade. They are configured in the `pairlists` section of the configuration settings.
In your configuration, you can use Static Pairlist (defined by the [`StaticPairList`](#static-pair-list) Pairlist Handler) and Dynamic Pairlist (defined by the [`VolumePairList`](#volume-pair-list) Pairlist Handler).
Additionaly, [`PrecisionFilter`](#precisionfilter), [`PriceFilter`](#pricefilter), [`ShuffleFilter`](#shufflefilter) and [`SpreadFilter`](#spreadfilter) act as Pairlist Filters, removing certain pairs and/or moving their positions in the pairlist.
Additionaly, [`AgeFilter`](#agefilter), [`PrecisionFilter`](#precisionfilter), [`PriceFilter`](#pricefilter), [`ShuffleFilter`](#shufflefilter) and [`SpreadFilter`](#spreadfilter) act as Pairlist Filters, removing certain pairs and/or moving their positions in the pairlist.
If multiple Pairlist Handlers are used, they are chained and a combination of all Pairlist Handlers forms the resulting pairlist the bot uses for trading and backtesting. Pairlist Handlers are executed in the sequence they are configured. You should always configure either `StaticPairList` or `VolumePairList` as the starting Pairlist Handler.
@ -565,6 +602,7 @@ Inactive markets are always removed from the resulting pairlist. Explicitly blac
* [`StaticPairList`](#static-pair-list) (default, if not configured differently)
* [`VolumePairList`](#volume-pair-list)
* [`AgeFilter`](#agefilter)
* [`PrecisionFilter`](#precisionfilter)
* [`PriceFilter`](#pricefilter)
* [`ShuffleFilter`](#shufflefilter)
@ -587,7 +625,7 @@ It uses configuration from `exchange.pair_whitelist` and `exchange.pair_blacklis
#### Volume Pair List
`VolumePairList` employs sorting/filtering of pairs by their trading volume. I selects `number_assets` top pairs with sorting based on the `sort_key` (which can only be `quoteVolume`).
`VolumePairList` employs sorting/filtering of pairs by their trading volume. It selects `number_assets` top pairs with sorting based on the `sort_key` (which can only be `quoteVolume`).
When used in the chain of Pairlist Handlers in a non-leading position (after StaticPairList and other Pairlist Filters), `VolumePairList` considers outputs of previous Pairlist Handlers, adding its sorting/selection of the pairs by the trading volume.
@ -605,9 +643,19 @@ The `refresh_period` setting allows to define the period (in seconds), at which
"number_assets": 20,
"sort_key": "quoteVolume",
"refresh_period": 1800,
],
}],
```
#### AgeFilter
Removes pairs that have been listed on the exchange for less than `min_days_listed` days (defaults to `10`).
When pairs are first listed on an exchange they can suffer huge price drops and volatility
in the first few days while the pair goes through its price-discovery period. Bots can often
be caught out buying before the pair has finished dropping in price.
This filter allows freqtrade to ignore pairs until they have been listed for at least `min_days_listed` days.
#### PrecisionFilter
Filters low-value coins which would not allow setting stoplosses.
@ -655,6 +703,7 @@ The below example blacklists `BNB/BTC`, uses `VolumePairList` with `20` assets,
"number_assets": 20,
"sort_key": "quoteVolume",
},
{"method": "AgeFilter", "min_days_listed": 10},
{"method": "PrecisionFilter"},
{"method": "PriceFilter", "low_price_ratio": 0.01},
{"method": "SpreadFilter", "max_spread_ratio": 0.005},

4
docs/data-download.md
View File

@ -109,7 +109,7 @@ The following command will convert all candle (OHLCV) data available in `~/.freq
It'll also remove original json data files (`--erase` parameter).
``` bash
freqtrade convert-data --format-from json --format-to jsongz --data-dir ~/.freqtrade/data/binance -t 5m 15m --erase
freqtrade convert-data --format-from json --format-to jsongz --datadir ~/.freqtrade/data/binance -t 5m 15m --erase
```
#### Subcommand convert-trade data
@ -155,7 +155,7 @@ The following command will convert all available trade-data in `~/.freqtrade/dat
It'll also remove original jsongz data files (`--erase` parameter).
``` bash
freqtrade convert-trade-data --format-from jsongz --format-to json --data-dir ~/.freqtrade/data/kraken --erase
freqtrade convert-trade-data --format-from jsongz --format-to json --datadir ~/.freqtrade/data/kraken --erase
```
### Pairs file

43
docs/developer.md
View File

@ -92,13 +92,13 @@ docker-compose exec freqtrade_develop /bin/bash
You have a great idea for a new pair selection algorithm you would like to try out? Great.
Hopefully you also want to contribute this back upstream.
Whatever your motivations are - This should get you off the ground in trying to develop a new Pairlist provider.
Whatever your motivations are - This should get you off the ground in trying to develop a new Pairlist Handler.
First of all, have a look at the [VolumePairList](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/pairlist/VolumePairList.py) provider, and best copy this file with a name of your new Pairlist Provider.
First of all, have a look at the [VolumePairList](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/pairlist/VolumePairList.py) Handler, and best copy this file with a name of your new Pairlist Handler.
This is a simple provider, which however serves as a good example on how to start developing.
This is a simple Handler, which however serves as a good example on how to start developing.
Next, modify the classname of the provider (ideally align this with the Filename).
Next, modify the classname of the Handler (ideally align this with the module filename).
The base-class provides an instance of the exchange (`self._exchange`) the pairlist manager (`self._pairlistmanager`), as well as the main configuration (`self._config`), the pairlist dedicated configuration (`self._pairlistconfig`) and the absolute position within the list of pairlists.
@ -114,28 +114,44 @@ Now, let's step through the methods which require actions:
#### Pairlist configuration
Configuration for PairListProvider is done in the bot configuration file in the element `"pairlist"`.
This Pairlist-object may contain configurations with additional configurations for the configured pairlist.
By convention, `"number_assets"` is used to specify the maximum number of pairs to keep in the whitelist. Please follow this to ensure a consistent user experience.
Configuration for the chain of Pairlist Handlers is done in the bot configuration file in the element `"pairlists"`, an array of configuration parameters for each Pairlist Handlers in the chain.
Additional elements can be configured as needed. `VolumePairList` uses `"sort_key"` to specify the sorting value - however feel free to specify whatever is necessary for your great algorithm to be successfull and dynamic.
By convention, `"number_assets"` is used to specify the maximum number of pairs to keep in the pairlist. Please follow this to ensure a consistent user experience.
Additional parameters can be configured as needed. For instance, `VolumePairList` uses `"sort_key"` to specify the sorting value - however feel free to specify whatever is necessary for your great algorithm to be successfull and dynamic.
#### short_desc
Returns a description used for Telegram messages.
This should contain the name of the Provider, as well as a short description containing the number of assets. Please follow the format `"PairlistName - top/bottom X pairs"`.
This should contain the name of the Pairlist Handler, as well as a short description containing the number of assets. Please follow the format `"PairlistName - top/bottom X pairs"`.
#### gen_pairlist
Override this method if the Pairlist Handler can be used as the leading Pairlist Handler in the chain, defining the initial pairlist which is then handled by all Pairlist Handlers in the chain. Examples are `StaticPairList` and `VolumePairList`.
This is called with each iteration of the bot (only if the Pairlist Handler is at the first location) - so consider implementing caching for compute/network heavy calculations.
It must return the resulting pairlist (which may then be passed into the chain of Pairlist Handlers).
Validations are optional, the parent class exposes a `_verify_blacklist(pairlist)` and `_whitelist_for_active_markets(pairlist)` to do default filtering. Use this if you limit your result to a certain number of pairs - so the endresult is not shorter than expected.
#### filter_pairlist
Override this method and run all calculations needed in this method.
This method is called for each Pairlist Handler in the chain by the pairlist manager.
This is called with each iteration of the bot - so consider implementing caching for compute/network heavy calculations.
It get's passed a pairlist (which can be the result of previous pairlists) as well as `tickers`, a pre-fetched version of `get_tickers()`.
It must return the resulting pairlist (which may then be passed into the next pairlist filter).
The default implementation in the base class simply calls the `_validate_pair()` method for each pair in the pairlist, but you may override it. So you should either implement the `_validate_pair()` in your Pairlist Handler or override `filter_pairlist()` to do something else.
If overridden, it must return the resulting pairlist (which may then be passed into the next Pairlist Handler in the chain).
Validations are optional, the parent class exposes a `_verify_blacklist(pairlist)` and `_whitelist_for_active_markets(pairlist)` to do default filters. Use this if you limit your result to a certain number of pairs - so the endresult is not shorter than expected.
In `VolumePairList`, this implements different methods of sorting, does early validation so only the expected number of pairs is returned.
##### sample
``` python
@ -145,11 +161,6 @@ Validations are optional, the parent class exposes a `_verify_blacklist(pairlist
return pairs
```
#### _gen_pair_whitelist
This is a simple method used by `VolumePairList` - however serves as a good example.
In VolumePairList, this implements different methods of sorting, does early validation so only the expected number of pairs is returned.
## Implement a new Exchange (WIP)
!!! Note

3
docs/edge.md
View File

@ -148,7 +148,6 @@ Edge module has following configuration options:
| `enabled` | If true, then Edge will run periodically. <br>*Defaults to `false`.* <br> **Datatype:** Boolean
| `process_throttle_secs` | How often should Edge run in seconds. <br>*Defaults to `3600` (once per hour).* <br> **Datatype:** Integer
| `calculate_since_number_of_days` | Number of days of data against which Edge calculates Win Rate, Risk Reward and Expectancy. <br> **Note** that it downloads historical data so increasing this number would lead to slowing down the bot. <br>*Defaults to `7`.* <br> **Datatype:** Integer
| `capital_available_percentage` | **DEPRECATED - [replaced with `tradable_balance_ratio`](configuration.md#Available balance)** This is the percentage of the total capital on exchange in stake currency. <br>As an example if you have 10 ETH available in your wallet on the exchange and this value is 0.5 (which is 50%), then the bot will use a maximum amount of 5 ETH for trading and considers it as available capital. <br>*Defaults to `0.5`.* <br> **Datatype:** Float
| `allowed_risk` | Ratio of allowed risk per trade. <br>*Defaults to `0.01` (1%)).* <br> **Datatype:** Float
| `stoploss_range_min` | Minimum stoploss. <br>*Defaults to `-0.01`.* <br> **Datatype:** Float
| `stoploss_range_max` | Maximum stoploss. <br>*Defaults to `-0.10`.* <br> **Datatype:** Float
@ -156,7 +155,7 @@ Edge module has following configuration options:
| `minimum_winrate` | It filters out pairs which don't have at least minimum_winrate. <br>This comes handy if you want to be conservative and don't comprise win rate in favour of risk reward ratio. <br>*Defaults to `0.60`.* <br> **Datatype:** Float
| `minimum_expectancy` | It filters out pairs which have the expectancy lower than this number. <br>Having an expectancy of 0.20 means if you put 10$ on a trade you expect a 12$ return. <br>*Defaults to `0.20`.* <br> **Datatype:** Float
| `min_trade_number` | When calculating *W*, *R* and *E* (expectancy) against historical data, you always want to have a minimum number of trades. The more this number is the more Edge is reliable. <br>Having a win rate of 100% on a single trade doesn't mean anything at all. But having a win rate of 70% over past 100 trades means clearly something. <br>*Defaults to `10` (it is highly recommended not to decrease this number).* <br> **Datatype:** Integer
| `max_trade_duration_minute` | Edge will filter out trades with long duration. If a trade is profitable after 1 month, it is hard to evaluate the strategy based on it. But if most of trades are profitable and they have maximum duration of 30 minutes, then it is clearly a good sign.<br>**NOTICE:** While configuring this value, you should take into consideration your timeframe (ticker interval). As an example filtering out trades having duration less than one day for a strategy which has 4h interval does not make sense. Default value is set assuming your strategy interval is relatively small (1m or 5m, etc.).<br>*Defaults to `1440` (one day).* <br> **Datatype:** Integer
| `max_trade_duration_minute` | Edge will filter out trades with long duration. If a trade is profitable after 1 month, it is hard to evaluate the strategy based on it. But if most of trades are profitable and they have maximum duration of 30 minutes, then it is clearly a good sign.<br>**NOTICE:** While configuring this value, you should take into consideration your timeframe. As an example filtering out trades having duration less than one day for a strategy which has 4h interval does not make sense. Default value is set assuming your strategy interval is relatively small (1m or 5m, etc.).<br>*Defaults to `1440` (one day).* <br> **Datatype:** Integer
| `remove_pumps` | Edge will remove sudden pumps in a given market while going through historical data. However, given that pumps happen very often in crypto markets, we recommend you keep this off.<br>*Defaults to `false`.* <br> **Datatype:** Boolean
## Running Edge independently

33
docs/exchanges.md
View File

@ -30,6 +30,15 @@ Binance has been split into 3, and users must use the correct ccxt exchange ID f
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.
Due to the heavy rate-limiting applied by Kraken, the following configuration section should be used to download data:
``` json
"ccxt_async_config": {
"enableRateLimit": true,
"rateLimit": 3100
},
```
## Bittrex
### Order types
@ -62,6 +71,30 @@ res = [ f"{x['MarketCurrency']}/{x['BaseCurrency']}" for x in ct.publicGetMarket
print(res)
```
## FTX
!!! Tip "Stoploss on Exchange"
FTX supports `stoploss_on_exchange` and can use both stop-loss-market and stop-loss-limit orders. It provides great advantages, so we recommend to benefit from it.
You can use either `"limit"` or `"market"` in the `order_types.stoploss` configuration setting to decide.
### Using subaccounts
To use subaccounts with FTX, you need to edit the configuration and add the following:
``` json
"exchange": {
"ccxt_config": {
"headers": {
"FTX-SUBACCOUNT": "name"
}
},
}
```
!!! Note
Older versions of freqtrade may require this key to be added to `"ccxt_async_config"` as well.
## All exchanges
Should you experience constant errors with Nonce (like `InvalidNonce`), it is best to regenerate the API keys. Resetting Nonce is difficult and it's usually easier to regenerate the API keys.

14
docs/faq.md
View File

@ -45,6 +45,20 @@ the tutorial [here|Testing-new-strategies-with-Hyperopt](bot-usage.md#hyperopt-c
You can use the `/forcesell all` command from Telegram.
### I want to run multiple bots on the same machine
Please look at the [advanced setup documentation Page](advanced-setup.md#running-multiple-instances-of-freqtrade).
### I'm getting "Missing data fillup" messages in the log
This message is just a warning that the latest candles had missing candles in them.
Depending on the exchange, this can indicate that the pair didn't have a trade for the timeframe you are using - and the exchange does only return candles with volume.
On low volume pairs, this is a rather common occurance.
If this happens for all pairs in the pairlist, this might indicate a recent exchange downtime. Please check your exchange's public channels for details.
Irrespectively of the reason, Freqtrade will fill up these candles with "empty" candles, where open, high, low and close are set to the previous candle close - and volume is empty. In a chart, this will look like a `_` - and is aligned with how exchanges usually represent 0 volume candles.
### I'm getting the "RESTRICTED_MARKET" message in the log
Currently known to happen for US Bittrex users.

12
docs/hyperopt.md
View File

@ -124,9 +124,9 @@ To avoid naming collisions in the search-space, please prefix all sell-spaces wi
#### Using timeframe as a part of the Strategy
The Strategy class exposes the timeframe (ticker interval) value as the `self.ticker_interval` attribute.
The same value is available as class-attribute `HyperoptName.ticker_interval`.
In the case of the linked sample-value this would be `SampleHyperOpt.ticker_interval`.
The Strategy class exposes the timeframe value as the `self.timeframe` attribute.
The same value is available as class-attribute `HyperoptName.timeframe`.
In the case of the linked sample-value this would be `SampleHyperOpt.timeframe`.
## Solving a Mystery
@ -265,7 +265,7 @@ freqtrade hyperopt --timerange 20180401-20180501
Hyperopt can reuse `populate_indicators`, `populate_buy_trend`, `populate_sell_trend` from your strategy, assuming these methods are **not** in your custom hyperopt file, and a strategy is provided.
```bash
freqtrade hyperopt --strategy SampleStrategy --customhyperopt SampleHyperopt
freqtrade hyperopt --strategy SampleStrategy --hyperopt SampleHyperopt
```
### Running Hyperopt with Smaller Search Space
@ -403,7 +403,7 @@ As stated in the comment, you can also use it as the value of the `minimal_roi`
#### Default ROI Search Space
If you are optimizing ROI, Freqtrade creates the 'roi' optimization hyperspace for you -- it's the hyperspace of components for the ROI tables. By default, each ROI table generated by the Freqtrade consists of 4 rows (steps). Hyperopt implements adaptive ranges for ROI tables with ranges for values in the ROI steps that depend on the ticker_interval used. By default the values vary in the following ranges (for some of the most used timeframes, values are rounded to 5 digits after the decimal point):
If you are optimizing ROI, Freqtrade creates the 'roi' optimization hyperspace for you -- it's the hyperspace of components for the ROI tables. By default, each ROI table generated by the Freqtrade consists of 4 rows (steps). Hyperopt implements adaptive ranges for ROI tables with ranges for values in the ROI steps that depend on the timeframe used. By default the values vary in the following ranges (for some of the most used timeframes, values are rounded to 5 digits after the decimal point):
| # step | 1m | | 5m | | 1h | | 1d | |
| ------ | ------ | ----------------- | -------- | ----------- | ---------- | ----------------- | ------------ | ----------------- |
@ -412,7 +412,7 @@ If you are optimizing ROI, Freqtrade creates the 'roi' optimization hyperspace f
| 3 | 4...20 | 0.00387...0.01547 | 20...100 | 0.01...0.04 | 240...1200 | 0.02294...0.09177 | 5760...28800 | 0.04059...0.16237 |
| 4 | 6...44 | 0.0 | 30...220 | 0.0 | 360...2640 | 0.0 | 8640...63360 | 0.0 |
These ranges should be sufficient in most cases. The minutes in the steps (ROI dict keys) are scaled linearly depending on the timeframe (ticker interval) used. The ROI values in the steps (ROI dict values) are scaled logarithmically depending on the timeframe used.
These ranges should be sufficient in most cases. The minutes in the steps (ROI dict keys) are scaled linearly depending on the timeframe used. The ROI values in the steps (ROI dict values) are scaled logarithmically depending on the timeframe used.
If you have the `generate_roi_table()` and `roi_space()` methods in your custom hyperopt file, remove them in order to utilize these adaptive ROI tables and the ROI hyperoptimization space generated by Freqtrade by default.

2
docs/installation.md
View File

@ -13,7 +13,7 @@ Click each one for install guide:
* [Python >= 3.6.x](http://docs.python-guide.org/en/latest/starting/installation/)
* [pip](https://pip.pypa.io/en/stable/installing/)
* [git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)
* [virtualenv](https://virtualenv.pypa.io/en/stable/installation/) (Recommended)
* [virtualenv](https://virtualenv.pypa.io/en/stable/installation.html) (Recommended)
* [TA-Lib](https://mrjbq7.github.io/ta-lib/install.html) (install instructions below)
We also recommend a [Telegram bot](telegram-usage.md#setup-your-telegram-bot), which is optional but recommended.

15
docs/plotting.md
View File

@ -31,7 +31,7 @@ usage: freqtrade plot-dataframe [-h] [-v] [--logfile FILE] [-V] [-c PATH]
[--plot-limit INT] [--db-url PATH]
[--trade-source {DB,file}] [--export EXPORT]
[--export-filename PATH]
[--timerange TIMERANGE] [-i TICKER_INTERVAL]
[--timerange TIMERANGE] [-i TIMEFRAME]
[--no-trades]
optional arguments:
@ -65,7 +65,7 @@ optional arguments:
_today.json`
--timerange TIMERANGE
Specify what timerange of data to use.
-i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
-i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME
Specify ticker interval (`1m`, `5m`, `30m`, `1h`,
`1d`).
--no-trades Skip using trades from backtesting file and DB.
@ -227,7 +227,7 @@ usage: freqtrade plot-profit [-h] [-v] [--logfile FILE] [-V] [-c PATH]
[-d PATH] [--userdir PATH] [-p PAIRS [PAIRS ...]]
[--timerange TIMERANGE] [--export EXPORT]
[--export-filename PATH] [--db-url PATH]
[--trade-source {DB,file}] [-i TICKER_INTERVAL]
[--trade-source {DB,file}] [-i TIMEFRAME]
optional arguments:
-h, --help show this help message and exit
@ -250,7 +250,7 @@ optional arguments:
--trade-source {DB,file}
Specify the source for trades (Can be DB or file
(backtest file)) Default: file
-i TICKER_INTERVAL, --ticker-interval TICKER_INTERVAL
-i TIMEFRAME, --timeframe TIMEFRAME, --ticker-interval TIMEFRAME
Specify ticker interval (`1m`, `5m`, `30m`, `1h`,
`1d`).
@ -261,9 +261,10 @@ Common arguments:
details.
-V, --version show program's version number and exit
-c PATH, --config PATH
Specify configuration file (default: `config.json`).
Multiple --config options may be used. Can be set to
`-` to read config from stdin.
Specify configuration file (default:
`userdir/config.json` or `config.json` whichever
exists). Multiple --config options may be used. Can be
set to `-` to read config from stdin.
-d PATH, --datadir PATH
Path to directory with historical backtesting data.
--userdir PATH, --user-data-dir PATH

2
docs/requirements-docs.txt
View File

@ -1,2 +1,2 @@
mkdocs-material==5.2.1
mkdocs-material==5.3.3
mdx_truly_sane_lists==1.2

31
docs/rest-api.md
View File

@ -11,7 +11,9 @@ Sample configuration:
"enabled": true,
"listen_ip_address": "127.0.0.1",
"listen_port": 8080,
"verbosity": "info",
"jwt_secret_key": "somethingrandom",
"CORS_origins": [],
"username": "Freqtrader",
"password": "SuperSecret1!"
},
@ -109,7 +111,7 @@ python3 scripts/rest_client.py --config rest_config.json <command> [optional par
| `start` | | Starts the trader
| `stop` | | Stops the trader
| `stopbuy` | | Stops the trader from opening new trades. Gracefully closes open trades according to their rules.
| `reload_conf` | | Reloads the configuration file
| `reload_config` | | Reloads the configuration file
| `show_config` | | Shows part of the current configuration with relevant settings to operation
| `status` | | Lists all open trades
| `count` | | Displays number of trades used and available
@ -173,7 +175,7 @@ profit
Returns the profit summary
:returns: json object
reload_conf
reload_config
Reload configuration
:returns: json object
@ -195,7 +197,7 @@ stop
stopbuy
Stop buying (but handle sells gracefully).
use reload_conf to reset
use reload_config to reset
:returns: json object
version
@ -231,3 +233,26 @@ Since the access token has a short timeout (15 min) - the `token/refresh` reques
> curl -X POST --header "Authorization: Bearer ${refresh_token}"http://localhost:8080/api/v1/token/refresh
{"access_token":"eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJpYXQiOjE1ODkxMTk5NzQsIm5iZiI6MTU4OTExOTk3NCwianRpIjoiMDBjNTlhMWUtMjBmYS00ZTk0LTliZjAtNWQwNTg2MTdiZDIyIiwiZXhwIjoxNTg5MTIwODc0LCJpZGVudGl0eSI6eyJ1IjoiRnJlcXRyYWRlciJ9LCJmcmVzaCI6ZmFsc2UsInR5cGUiOiJhY2Nlc3MifQ.1seHlII3WprjjclY6DpRhen0rqdF4j6jbvxIhUFaSbs"}
```
## CORS
All web-based frontends are subject to [CORS](https://developer.mozilla.org/en-US/docs/Web/HTTP/CORS) - Cross-Origin Resource Sharing.
Since most of the requests to the Freqtrade API must be authenticated, a proper CORS policy is key to avoid security problems.
Also, the standard disallows `*` CORS policies for requests with credentials, so this setting must be set appropriately.
Users can configure this themselves via the `CORS_origins` configuration setting.
It consists of a list of allowed sites that are allowed to consume resources from the bot's API.
Assuming your application is deployed as `https://frequi.freqtrade.io/home/` - this would mean that the following configuration becomes necessary:
```jsonc
{
//...
"jwt_secret_key": "somethingrandom",
"CORS_origins": ["https://frequi.freqtrade.io"],
//...
}
```
!!! Note
We strongly recommend to also set `jwt_secret_key` to something random and known only to yourself to avoid unauthorized access to your bot.

6
docs/sql_cheatsheet.md
View File

@ -70,7 +70,7 @@ CREATE TABLE trades
min_rate FLOAT,
sell_reason VARCHAR,
strategy VARCHAR,
ticker_interval INTEGER,
timeframe INTEGER,
PRIMARY KEY (id),
CHECK (is_open IN (0, 1))
);
@ -101,7 +101,7 @@ SET is_open=0,
close_date=<close_date>,
close_rate=<close_rate>,
close_profit=close_rate/open_rate-1,
close_profit_abs = (amount * <close_rate> * (1 - fee_close) - (amount * open_rate * 1 - fee_open),
close_profit_abs = (amount * <close_rate> * (1 - fee_close) - (amount * open_rate * 1 - fee_open)),
sell_reason=<sell_reason>
WHERE id=<trade_ID_to_update>;
```
@ -114,7 +114,7 @@ SET is_open=0,
close_date='2017-12-20 03:08:45.103418',
close_rate=0.19638016,
close_profit=0.0496,
close_profit_abs = (amount * 0.19638016 * (1 - fee_close) - (amount * open_rate * 1 - fee_open)
close_profit_abs = (amount * 0.19638016 * (1 - fee_close) - (amount * open_rate * 1 - fee_open))
sell_reason='force_sell'
WHERE id=31;
```

6
docs/stoploss.md
View File

@ -1,6 +1,6 @@
# Stop Loss
The `stoploss` configuration parameter is loss in percentage that should trigger a sale.
The `stoploss` configuration parameter is loss as ratio that should trigger a sale.
For example, value `-0.10` will cause immediate sell if the profit dips below -10% for a given trade. This parameter is optional.
Most of the strategy files already include the optimal `stoploss` value.
@ -27,7 +27,7 @@ So this parameter will tell the bot how often it should update the stoploss orde
This same logic will reapply a stoploss order on the exchange should you cancel it accidentally.
!!! Note
Stoploss on exchange is only supported for Binance (stop-loss-limit) and Kraken (stop-loss-market) as of now.
Stoploss on exchange is only supported for Binance (stop-loss-limit), Kraken (stop-loss-market) and FTX (stop limit and stop-market) as of now.
## Static Stop Loss
@ -101,7 +101,7 @@ Simplified example:
## Changing stoploss on open trades
A stoploss on an open trade can be changed by changing the value in the configuration or strategy and use the `/reload_conf` command (alternatively, completely stopping and restarting the bot also works).
A stoploss on an open trade can be changed by changing the value in the configuration or strategy and use the `/reload_config` command (alternatively, completely stopping and restarting the bot also works).
The new stoploss value will be applied to open trades (and corresponding log-messages will be generated).

20
docs/strategy-customization.md
View File

@ -139,10 +139,10 @@ By letting the bot know how much history is needed, backtest trades can start at
#### Example
Let's try to backtest 1 month (January 2019) of 5m candles using the an example strategy with EMA100, as above.
Let's try to backtest 1 month (January 2019) of 5m candles using an example strategy with EMA100, as above.
``` bash
freqtrade backtesting --timerange 20190101-20190201 --ticker-interval 5m
freqtrade backtesting --timerange 20190101-20190201 --timeframe 5m
```
Assuming `startup_candle_count` is set to 100, backtesting knows it needs 100 candles to generate valid buy signals. It will load data from `20190101 - (100 * 5m)` - which is ~2019-12-31 15:30:00.
@ -248,7 +248,7 @@ minimal_roi = {
While technically not completely disabled, this would sell once the trade reaches 10000% Profit.
To use times based on candle duration (ticker_interval or timeframe), the following snippet can be handy.
To use times based on candle duration (timeframe), the following snippet can be handy.
This will allow you to change the ticket_interval for the strategy, and ROI times will still be set as candles (e.g. after 3 candles ...)
``` python
@ -256,12 +256,12 @@ from freqtrade.exchange import timeframe_to_minutes
class AwesomeStrategy(IStrategy):
ticker_interval = "1d"
ticker_interval_mins = timeframe_to_minutes(ticker_interval)
timeframe = "1d"
timeframe_mins = timeframe_to_minutes(timeframe)
minimal_roi = {
"0": 0.05, # 5% for the first 3 candles
str(ticker_interval_mins * 3)): 0.02, # 2% after 3 candles
str(ticker_interval_mins * 6)): 0.01, # 1% After 6 candles
str(timeframe_mins * 3)): 0.02, # 2% after 3 candles
str(timeframe_mins * 6)): 0.01, # 1% After 6 candles
}
```
@ -290,7 +290,7 @@ Common values are `"1m"`, `"5m"`, `"15m"`, `"1h"`, however all values supported
Please note that the same buy/sell signals may work well with one timeframe, but not with the others.
This setting is accessible within the strategy methods as the `self.ticker_interval` attribute.
This setting is accessible within the strategy methods as the `self.timeframe` attribute.
### Metadata dict
@ -400,7 +400,7 @@ This is where calling `self.dp.current_whitelist()` comes in handy.
class SampleStrategy(IStrategy):
# strategy init stuff...
ticker_interval = '5m'
timeframe = '5m'
# more strategy init stuff..
@ -557,7 +557,7 @@ Locks can also be lifted manually, by calling `self.unlock_pair(pair)`.
To verify if a pair is currently locked, use `self.is_pair_locked(pair)`.
!!! Note
Locked pairs are not persisted, so a restart of the bot, or calling `/reload_conf` will reset locked pairs.
Locked pairs are not persisted, so a restart of the bot, or calling `/reload_config` will reset locked pairs.
!!! Warning
Locking pairs is not functioning during backtesting.

4
docs/strategy_analysis_example.md
View File

@ -18,7 +18,7 @@ config = Configuration.from_files([])
# config = Configuration.from_files(["config.json"])
# Define some constants
config["ticker_interval"] = "5m"
config["timeframe"] = "5m"
# Name of the strategy class
config["strategy"] = "SampleStrategy"
# Location of the data
@ -33,7 +33,7 @@ pair = "BTC_USDT"
from freqtrade.data.history import load_pair_history
candles = load_pair_history(datadir=data_location,
timeframe=config["ticker_interval"],
timeframe=config["timeframe"],
pair=pair)
# Confirm success

8
docs/telegram-usage.md
View File

@ -52,7 +52,7 @@ official commands. You can ask at any moment for help with `/help`.
| `/start` | | Starts the trader
| `/stop` | | Stops the trader
| `/stopbuy` | | Stops the trader from opening new trades. Gracefully closes open trades according to their rules.
| `/reload_conf` | | Reloads the configuration file
| `/reload_config` | | Reloads the configuration file
| `/show_config` | | Shows part of the current configuration with relevant settings to operation
| `/status` | | Lists all open trades
| `/status table` | | List all open trades in a table format. Pending buy orders are marked with an asterisk (*) Pending sell orders are marked with a double asterisk (**)
@ -85,14 +85,14 @@ Below, example of Telegram message you will receive for each command.
### /stopbuy
> **status:** `Setting max_open_trades to 0. Run /reload_conf to reset.`
> **status:** `Setting max_open_trades to 0. Run /reload_config to reset.`
Prevents the bot from opening new trades by temporarily setting "max_open_trades" to 0. Open trades will be handled via their regular rules (ROI / Sell-signal, stoploss, ...).
After this, give the bot time to close off open trades (can be checked via `/status table`).
Once all positions are sold, run `/stop` to completely stop the bot.
`/reload_conf` resets "max_open_trades" to the value set in the configuration and resets this command.
`/reload_config` resets "max_open_trades" to the value set in the configuration and resets this command.
!!! Warning
The stop-buy signal is ONLY active while the bot is running, and is not persisted anyway, so restarting the bot will cause this to reset.
@ -209,7 +209,7 @@ Shows the current whitelist
Shows the current blacklist.
If Pair is set, then this pair will be added to the pairlist.
Also supports multiple pairs, seperated by a space.
Use `/reload_conf` to reset the blacklist.
Use `/reload_config` to reset the blacklist.
> Using blacklist `StaticPairList` with 2 pairs
>`DODGE/BTC`, `HOT/BTC`.

2
docs/utils.md
View File

@ -62,7 +62,7 @@ $ freqtrade new-config --config config_binance.json
? Please insert your stake currency: BTC
? Please insert your stake amount: 0.05
? Please insert max_open_trades (Integer or 'unlimited'): 3
? Please insert your timeframe (ticker interval): 5m
? Please insert your desired timeframe (e.g. 5m): 5m
? Please insert your display Currency (for reporting): USD
? Select exchange binance
? Do you want to enable Telegram? No

2
freqtrade/__init__.py
View File

@ -1,5 +1,5 @@
""" Freqtrade bot """
__version__ = '2020.5'
__version__ = '2020.6'
if __version__ == 'develop':

8
freqtrade/commands/arguments.py
View File

@ -15,7 +15,7 @@ ARGS_STRATEGY = ["strategy", "strategy_path"]
ARGS_TRADE = ["db_url", "sd_notify", "dry_run"]
ARGS_COMMON_OPTIMIZE = ["ticker_interval", "timerange",
ARGS_COMMON_OPTIMIZE = ["timeframe", "timerange",
"max_open_trades", "stake_amount", "fee"]
ARGS_BACKTEST = ARGS_COMMON_OPTIMIZE + ["position_stacking", "use_max_market_positions",
@ -59,10 +59,10 @@ ARGS_DOWNLOAD_DATA = ["pairs", "pairs_file", "days", "download_trades", "exchang
ARGS_PLOT_DATAFRAME = ["pairs", "indicators1", "indicators2", "plot_limit",
"db_url", "trade_source", "export", "exportfilename",
"timerange", "ticker_interval", "no_trades"]
"timerange", "timeframe", "no_trades"]
ARGS_PLOT_PROFIT = ["pairs", "timerange", "export", "exportfilename", "db_url",
"trade_source", "ticker_interval"]
"trade_source", "timeframe"]
ARGS_SHOW_TRADES = ["db_url", "trade_ids", "print_json"]
@ -318,7 +318,7 @@ class Arguments:
# Add list-timeframes subcommand
list_timeframes_cmd = subparsers.add_parser(
'list-timeframes',
help='Print available ticker intervals (timeframes) for the exchange.',
help='Print available timeframes for the exchange.',
parents=[_common_parser],
)
list_timeframes_cmd.set_defaults(func=start_list_timeframes)

4
freqtrade/commands/build_config_commands.py
View File

@ -75,8 +75,8 @@ def ask_user_config() -> Dict[str, Any]:
},
{
"type": "text",
"name": "ticker_interval",
"message": "Please insert your timeframe (ticker interval):",
"name": "timeframe",
"message": "Please insert your desired timeframe (e.g. 5m):",
"default": "5m",
},
{

4
freqtrade/commands/cli_options.py
View File

@ -110,8 +110,8 @@ AVAILABLE_CLI_OPTIONS = {
action='store_true',
),
# Optimize common
"ticker_interval": Arg(
'-i', '--ticker-interval',
"timeframe": Arg(
'-i', '--timeframe', '--ticker-interval',
help='Specify ticker interval (`1m`, `5m`, `30m`, `1h`, `1d`).',
),
"timerange": Arg(

4
freqtrade/commands/list_commands.py
View File

@ -102,8 +102,8 @@ def start_list_timeframes(args: Dict[str, Any]) -> None:
Print ticker intervals (timeframes) available on Exchange
"""
config = setup_utils_configuration(args, RunMode.UTIL_EXCHANGE)
# Do not use ticker_interval set in the config
config['ticker_interval'] = None
# Do not use timeframe set in the config
config['timeframe'] = None
# Init exchange
exchange = ExchangeResolver.load_exchange(config['exchange']['name'], config, validate=False)

1
freqtrade/commands/pairlist_commands.py
View File

@ -25,7 +25,6 @@ def start_test_pairlist(args: Dict[str, Any]) -> None:
results = {}
for curr in quote_currencies:
config['stake_currency'] = curr
# Do not use ticker_interval set in the config
pairlists = PairListManager(exchange, config)
pairlists.refresh_pairlist()
results[curr] = pairlists.whitelist

10
freqtrade/configuration/configuration.py
View File

@ -204,9 +204,9 @@ class Configuration:
def _process_optimize_options(self, config: Dict[str, Any]) -> None:
# This will override the strategy configuration
self._args_to_config(config, argname='ticker_interval',
logstring='Parameter -i/--ticker-interval detected ... '
'Using ticker_interval: {} ...')
self._args_to_config(config, argname='timeframe',
logstring='Parameter -i/--timeframe detected ... '
'Using timeframe: {} ...')
self._args_to_config(config, argname='position_stacking',
logstring='Parameter --enable-position-stacking detected ...')
@ -242,8 +242,8 @@ class Configuration:
self._args_to_config(config, argname='strategy_list',
logstring='Using strategy list of {} strategies', logfun=len)
self._args_to_config(config, argname='ticker_interval',
logstring='Overriding ticker interval with Command line argument')
self._args_to_config(config, argname='timeframe',
logstring='Overriding timeframe with Command line argument')
self._args_to_config(config, argname='export',
logstring='Parameter --export detected: {} ...')

13
freqtrade/configuration/deprecated_settings.py
View File

@ -60,10 +60,21 @@ def process_temporary_deprecated_settings(config: Dict[str, Any]) -> None:
if (config.get('edge', {}).get('enabled', False)
and 'capital_available_percentage' in config.get('edge', {})):
logger.warning(
raise OperationalException(
"DEPRECATED: "
"Using 'edge.capital_available_percentage' has been deprecated in favor of "
"'tradable_balance_ratio'. Please migrate your configuration to "
"'tradable_balance_ratio' and remove 'capital_available_percentage' "
"from the edge configuration."
)
if 'ticker_interval' in config:
logger.warning(
"DEPRECATED: "
"Please use 'timeframe' instead of 'ticker_interval."
)
if 'timeframe' in config:
raise OperationalException(
"Both 'timeframe' and 'ticker_interval' detected."
"Please remove 'ticker_interval' from your configuration to continue operating."
)
config['timeframe'] = config['ticker_interval']

11
freqtrade/constants.py
View File

@ -22,7 +22,8 @@ ORDERBOOK_SIDES = ['ask', 'bid']
ORDERTYPE_POSSIBILITIES = ['limit', 'market']
ORDERTIF_POSSIBILITIES = ['gtc', 'fok', 'ioc']
AVAILABLE_PAIRLISTS = ['StaticPairList', 'VolumePairList',
'PrecisionFilter', 'PriceFilter', 'ShuffleFilter', 'SpreadFilter']
'AgeFilter', 'PrecisionFilter', 'PriceFilter',
'ShuffleFilter', 'SpreadFilter']
AVAILABLE_DATAHANDLERS = ['json', 'jsongz']
DRY_RUN_WALLET = 1000
MATH_CLOSE_PREC = 1e-14 # Precision used for float comparisons
@ -71,7 +72,7 @@ CONF_SCHEMA = {
'type': 'object',
'properties': {
'max_open_trades': {'type': ['integer', 'number'], 'minimum': -1},
'ticker_interval': {'type': 'string'},
'timeframe': {'type': 'string'},
'stake_currency': {'type': 'string'},
'stake_amount': {
'type': ['number', 'string'],
@ -221,12 +222,16 @@ CONF_SCHEMA = {
},
'username': {'type': 'string'},
'password': {'type': 'string'},
'jwt_secret_key': {'type': 'string'},
'CORS_origins': {'type': 'array', 'items': {'type': 'string'}},
'verbosity': {'type': 'string', 'enum': ['error', 'info']},
},
'required': ['enabled', 'listen_ip_address', 'listen_port', 'username', 'password']
},
'db_url': {'type': 'string'},
'initial_state': {'type': 'string', 'enum': ['running', 'stopped']},
'forcebuy_enable': {'type': 'boolean'},
'disable_dataframe_checks': {'type': 'boolean'},
'internals': {
'type': 'object',
'default': {},
@ -285,7 +290,6 @@ CONF_SCHEMA = {
'process_throttle_secs': {'type': 'integer', 'minimum': 600},
'calculate_since_number_of_days': {'type': 'integer'},
'allowed_risk': {'type': 'number'},
'capital_available_percentage': {'type': 'number'},
'stoploss_range_min': {'type': 'number'},
'stoploss_range_max': {'type': 'number'},
'stoploss_range_step': {'type': 'number'},
@ -302,6 +306,7 @@ CONF_SCHEMA = {
SCHEMA_TRADE_REQUIRED = [
'exchange',
'timeframe',
'max_open_trades',
'stake_currency',
'stake_amount',

19
freqtrade/data/btanalysis.py
View File

@ -16,7 +16,7 @@ from freqtrade.persistence import Trade
logger = logging.getLogger(__name__)
# must align with columns in backtest.py
BT_DATA_COLUMNS = ["pair", "profitperc", "open_time", "close_time", "index", "duration",
BT_DATA_COLUMNS = ["pair", "profit_percent", "open_time", "close_time", "index", "duration",
"open_rate", "close_rate", "open_at_end", "sell_reason"]
@ -99,11 +99,11 @@ def load_trades_from_db(db_url: str) -> pd.DataFrame:
trades: pd.DataFrame = pd.DataFrame([], columns=BT_DATA_COLUMNS)
persistence.init(db_url, clean_open_orders=False)
columns = ["pair", "open_time", "close_time", "profit", "profitperc",
columns = ["pair", "open_time", "close_time", "profit", "profit_percent",
"open_rate", "close_rate", "amount", "duration", "sell_reason",
"fee_open", "fee_close", "open_rate_requested", "close_rate_requested",
"stake_amount", "max_rate", "min_rate", "id", "exchange",
"stop_loss", "initial_stop_loss", "strategy", "ticker_interval"]
"stop_loss", "initial_stop_loss", "strategy", "timeframe"]
trades = pd.DataFrame([(t.pair,
t.open_date.replace(tzinfo=timezone.utc),
@ -121,7 +121,7 @@ def load_trades_from_db(db_url: str) -> pd.DataFrame:
t.min_rate,
t.id, t.exchange,
t.stop_loss, t.initial_stop_loss,
t.strategy, t.ticker_interval
t.strategy, t.timeframe
)
for t in Trade.get_trades().all()],
columns=columns)
@ -190,7 +190,7 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str,
"""
Adds a column `col_name` with the cumulative profit for the given trades array.
:param df: DataFrame with date index
:param trades: DataFrame containing trades (requires columns close_time and profitperc)
:param trades: DataFrame containing trades (requires columns close_time and profit_percent)
:param col_name: Column name that will be assigned the results
:param timeframe: Timeframe used during the operations
:return: Returns df with one additional column, col_name, containing the cumulative profit.
@ -201,7 +201,8 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str,
from freqtrade.exchange import timeframe_to_minutes
timeframe_minutes = timeframe_to_minutes(timeframe)
# Resample to timeframe to make sure trades match candles
_trades_sum = trades.resample(f'{timeframe_minutes}min', on='close_time')[['profitperc']].sum()
_trades_sum = trades.resample(f'{timeframe_minutes}min', on='close_time'
)[['profit_percent']].sum()
df.loc[:, col_name] = _trades_sum.cumsum()
# Set first value to 0
df.loc[df.iloc[0].name, col_name] = 0
@ -211,13 +212,13 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str,
def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_time',
value_col: str = 'profitperc'
value_col: str = 'profit_percent'
) -> Tuple[float, pd.Timestamp, pd.Timestamp]:
"""
Calculate max drawdown and the corresponding close dates
:param trades: DataFrame containing trades (requires columns close_time and profitperc)
:param trades: DataFrame containing trades (requires columns close_time and profit_percent)
:param date_col: Column in DataFrame to use for dates (defaults to 'close_time')
:param value_col: Column in DataFrame to use for values (defaults to 'profitperc')
:param value_col: Column in DataFrame to use for values (defaults to 'profit_percent')
:return: Tuple (float, highdate, lowdate) with absolute max drawdown, high and low time
:raise: ValueError if trade-dataframe was found empty.
"""

6
freqtrade/data/converter.py
View File

@ -197,7 +197,7 @@ def trades_to_ohlcv(trades: List, timeframe: str) -> DataFrame:
df_new['date'] = df_new.index
# Drop 0 volume rows
df_new = df_new.dropna()
return df_new[DEFAULT_DATAFRAME_COLUMNS]
return df_new.loc[:, DEFAULT_DATAFRAME_COLUMNS]
def convert_trades_format(config: Dict[str, Any], convert_from: str, convert_to: str, erase: bool):
@ -236,12 +236,12 @@ def convert_ohlcv_format(config: Dict[str, Any], convert_from: str, convert_to:
from freqtrade.data.history.idatahandler import get_datahandler
src = get_datahandler(config['datadir'], convert_from)
trg = get_datahandler(config['datadir'], convert_to)
timeframes = config.get('timeframes', [config.get('ticker_interval')])
timeframes = config.get('timeframes', [config.get('timeframe')])
logger.info(f"Converting candle (OHLCV) for timeframe {timeframes}")
if 'pairs' not in config:
config['pairs'] = []
# Check timeframes or fall back to ticker_interval.
# Check timeframes or fall back to timeframe.
for timeframe in timeframes:
config['pairs'].extend(src.ohlcv_get_pairs(config['datadir'],
timeframe))

4
freqtrade/data/dataprovider.py
View File

@ -55,7 +55,7 @@ class DataProvider:
Use False only for read-only operations (where the dataframe is not modified)
"""
if self.runmode in (RunMode.DRY_RUN, RunMode.LIVE):
return self._exchange.klines((pair, timeframe or self._config['ticker_interval']),
return self._exchange.klines((pair, timeframe or self._config['timeframe']),
copy=copy)
else:
return DataFrame()
@ -67,7 +67,7 @@ class DataProvider:
:param timeframe: timeframe to get data for
"""
return load_pair_history(pair=pair,
timeframe=timeframe or self._config['ticker_interval'],
timeframe=timeframe or self._config['timeframe'],
datadir=self._config['datadir']
)

5
freqtrade/data/history/history_utils.py
View File

@ -270,6 +270,11 @@ def _download_trades_history(exchange: Exchange,
# DEFAULT_TRADES_COLUMNS: 0 -> timestamp
# DEFAULT_TRADES_COLUMNS: 1 -> id
if trades and since < trades[0][0]:
# since is before the first trade
logger.info(f"Start earlier than available data. Redownloading trades for {pair}...")
trades = []
from_id = trades[-1][1] if trades else None
if trades and since < trades[-1][0]:
# Reset since to the last available point

10
freqtrade/edge/edge_positioning.py
View File

@ -57,9 +57,7 @@ class Edge:
if self.config['stake_amount'] != UNLIMITED_STAKE_AMOUNT:
raise OperationalException('Edge works only with unlimited stake amount')
# Deprecated capital_available_percentage. Will use tradable_balance_ratio in the future.
self._capital_percentage: float = self.edge_config.get(
'capital_available_percentage', self.config['tradable_balance_ratio'])
self._capital_ratio: float = self.config['tradable_balance_ratio']
self._allowed_risk: float = self.edge_config.get('allowed_risk')
self._since_number_of_days: int = self.edge_config.get('calculate_since_number_of_days', 14)
self._last_updated: int = 0 # Timestamp of pairs last updated time
@ -100,14 +98,14 @@ class Edge:
datadir=self.config['datadir'],
pairs=pairs,
exchange=self.exchange,
timeframe=self.strategy.ticker_interval,
timeframe=self.strategy.timeframe,
timerange=self._timerange,
)
data = load_data(
datadir=self.config['datadir'],
pairs=pairs,
timeframe=self.strategy.ticker_interval,
timeframe=self.strategy.timeframe,
timerange=self._timerange,
startup_candles=self.strategy.startup_candle_count,
data_format=self.config.get('dataformat_ohlcv', 'json'),
@ -157,7 +155,7 @@ class Edge:
def stake_amount(self, pair: str, free_capital: float,
total_capital: float, capital_in_trade: float) -> float:
stoploss = self.stoploss(pair)
available_capital = (total_capital + capital_in_trade) * self._capital_percentage
available_capital = (total_capital + capital_in_trade) * self._capital_ratio
allowed_capital_at_risk = available_capital * self._allowed_risk
max_position_size = abs(allowed_capital_at_risk / stoploss)
position_size = min(max_position_size, free_capital)

46
freqtrade/exchange/exchange.py
View File

@ -79,7 +79,7 @@ class Exchange:
if config['dry_run']:
logger.info('Instance is running with dry_run enabled')
logger.info(f"Using CCXT {ccxt.__version__}")
exchange_config = config['exchange']
# Deep merge ft_has with default ft_has options
@ -98,12 +98,14 @@ class Exchange:
# Initialize ccxt objects
ccxt_config = self._ccxt_config.copy()
ccxt_config = deep_merge_dicts(exchange_config.get('ccxt_config', {}),
ccxt_config)
self._api = self._init_ccxt(
exchange_config, ccxt_kwargs=ccxt_config)
ccxt_config = deep_merge_dicts(exchange_config.get('ccxt_config', {}), ccxt_config)
ccxt_config = deep_merge_dicts(exchange_config.get('ccxt_sync_config', {}), ccxt_config)
self._api = self._init_ccxt(exchange_config, ccxt_kwargs=ccxt_config)
ccxt_async_config = self._ccxt_config.copy()
ccxt_async_config = deep_merge_dicts(exchange_config.get('ccxt_config', {}),
ccxt_async_config)
ccxt_async_config = deep_merge_dicts(exchange_config.get('ccxt_async_config', {}),
ccxt_async_config)
self._api_async = self._init_ccxt(
@ -113,7 +115,7 @@ class Exchange:
if validate:
# Check if timeframe is available
self.validate_timeframes(config.get('ticker_interval'))
self.validate_timeframes(config.get('timeframe'))
# Initial markets load
self._load_markets()
@ -188,7 +190,7 @@ class Exchange:
def markets(self) -> Dict:
"""exchange ccxt markets"""
if not self._api.markets:
logger.warning("Markets were not loaded. Loading them now..")
logger.info("Markets were not loaded. Loading them now..")
self._load_markets()
return self._api.markets
@ -273,8 +275,8 @@ class Exchange:
except ccxt.BaseError as e:
logger.warning('Unable to initialize markets. Reason: %s', e)
def _reload_markets(self) -> None:
"""Reload markets both sync and async, if refresh interval has passed"""
def reload_markets(self) -> None:
"""Reload markets both sync and async if refresh interval has passed """
# Check whether markets have to be reloaded
if (self._last_markets_refresh > 0) and (
self._last_markets_refresh + self.markets_refresh_interval
@ -283,6 +285,8 @@ class Exchange:
logger.debug("Performing scheduled market reload..")
try:
self._api.load_markets(reload=True)
# Also reload async markets to avoid issues with newly listed pairs
self._load_async_markets(reload=True)
self._last_markets_refresh = arrow.utcnow().timestamp
except ccxt.BaseError:
logger.exception("Could not reload markets.")
@ -887,14 +891,19 @@ class Exchange:
Async wrapper handling downloading trades using either time or id based methods.
"""
logger.debug(f"_async_get_trade_history(), pair: {pair}, "
f"since: {since}, until: {until}, from_id: {from_id}")
if until is None:
until = ccxt.Exchange.milliseconds()
logger.debug(f"Exchange milliseconds: {until}")
if self._trades_pagination == 'time':
return await self._async_get_trade_history_time(
pair=pair, since=since,
until=until or ccxt.Exchange.milliseconds())
pair=pair, since=since, until=until)
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
pair=pair, since=since, until=until, from_id=from_id
)
else:
raise OperationalException(f"Exchange {self.name} does use neither time, "
@ -945,6 +954,9 @@ class Exchange:
except ccxt.BaseError as e:
raise OperationalException(e) from e
# Assign method to get_stoploss_order to allow easy overriding in other classes
cancel_stoploss_order = cancel_order
def is_cancel_order_result_suitable(self, corder) -> bool:
if not isinstance(corder, dict):
return False
@ -997,6 +1009,9 @@ class Exchange:
except ccxt.BaseError as e:
raise OperationalException(e) from e
# Assign method to get_stoploss_order to allow easy overriding in other classes
get_stoploss_order = get_order
@retrier
def fetch_l2_order_book(self, pair: str, limit: int = 100) -> dict:
"""
@ -1102,9 +1117,12 @@ class Exchange:
order['fee']['cost'] / safe_value_fallback(order, order, 'filled', 'amount'), 8)
elif fee_curr in self.get_pair_quote_currency(order['symbol']):
# Quote currency - divide by cost
return round(order['fee']['cost'] / order['cost'], 8)
return round(order['fee']['cost'] / order['cost'], 8) if order['cost'] else None
else:
# If Fee currency is a different currency
if not order['cost']:
# If cost is None or 0.0 -> falsy, return None
return None
try:
comb = self.get_valid_pair_combination(fee_curr, self._config['stake_currency'])
tick = self.fetch_ticker(comb)

104
freqtrade/exchange/ftx.py
View File

@ -2,7 +2,12 @@
import logging
from typing import Dict
import ccxt
from freqtrade.exceptions import (DependencyException, InvalidOrderException,
OperationalException, TemporaryError)
from freqtrade.exchange import Exchange
from freqtrade.exchange.common import retrier
logger = logging.getLogger(__name__)
@ -10,5 +15,104 @@ logger = logging.getLogger(__name__)
class Ftx(Exchange):
_ft_has: Dict = {
"stoploss_on_exchange": True,
"ohlcv_candle_limit": 1500,
}
def stoploss_adjust(self, stop_loss: float, order: Dict) -> bool:
"""
Verify stop_loss against stoploss-order value (limit or price)
Returns True if adjustment is necessary.
"""
return order['type'] == 'stop' and stop_loss > float(order['price'])
def stoploss(self, pair: str, amount: float, stop_price: float, order_types: Dict) -> Dict:
"""
Creates a stoploss order.
depending on order_types.stoploss configuration, uses 'market' or limit order.
Limit orders are defined by having orderPrice set, otherwise a market order is used.
"""
limit_price_pct = order_types.get('stoploss_on_exchange_limit_ratio', 0.99)
limit_rate = stop_price * limit_price_pct
ordertype = "stop"
stop_price = self.price_to_precision(pair, stop_price)
if self._config['dry_run']:
dry_order = self.dry_run_order(
pair, ordertype, "sell", amount, stop_price)
return dry_order
try:
params = self._params.copy()
if order_types.get('stoploss', 'market') == 'limit':
# set orderPrice to place limit order, otherwise it's a market order
params['orderPrice'] = limit_rate
amount = self.amount_to_precision(pair, amount)
order = self._api.create_order(symbol=pair, type=ordertype, side='sell',
amount=amount, price=stop_price, params=params)
logger.info('stoploss order added for %s. '
'stop price: %s.', pair, stop_price)
return order
except ccxt.InsufficientFunds as e:
raise DependencyException(
f'Insufficient funds to create {ordertype} sell order on market {pair}. '
f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
f'Message: {e}') from e
except ccxt.InvalidOrder as e:
raise InvalidOrderException(
f'Could not create {ordertype} sell order on market {pair}. '
f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
f'Message: {e}') from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not place sell order due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
@retrier
def get_stoploss_order(self, order_id: str, pair: str) -> Dict:
if self._config['dry_run']:
try:
order = self._dry_run_open_orders[order_id]
return order
except KeyError as e:
# Gracefully handle errors with dry-run orders.
raise InvalidOrderException(
f'Tried to get an invalid dry-run-order (id: {order_id}). Message: {e}') from e
try:
orders = self._api.fetch_orders(pair, None, params={'type': 'stop'})
order = [order for order in orders if order['id'] == order_id]
if len(order) == 1:
return order[0]
else:
raise InvalidOrderException(f"Could not get stoploss order for id {order_id}")
except ccxt.InvalidOrder as e:
raise InvalidOrderException(
f'Tried to get an invalid order (id: {order_id}). Message: {e}') from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not get order due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e
@retrier
def cancel_stoploss_order(self, order_id: str, pair: str) -> Dict:
if self._config['dry_run']:
return {}
try:
return self._api.cancel_order(order_id, pair, params={'type': 'stop'})
except ccxt.InvalidOrder as e:
raise InvalidOrderException(
f'Could not cancel order. Message: {e}') from e
except (ccxt.NetworkError, ccxt.ExchangeError) as e:
raise TemporaryError(
f'Could not cancel order due to {e.__class__.__name__}. Message: {e}') from e
except ccxt.BaseError as e:
raise OperationalException(e) from e

36
freqtrade/freqtradebot.py
View File

@ -139,8 +139,8 @@ class FreqtradeBot:
:return: True if one or more trades has been created or closed, False otherwise
"""
# Check whether markets have to be reloaded
self.exchange._reload_markets()
# Check whether markets have to be reloaded and reload them when it's needed
self.exchange.reload_markets()
# Query trades from persistence layer
trades = Trade.get_open_trades()
@ -421,8 +421,8 @@ class FreqtradeBot:
# running get_signal on historical data fetched
(buy, sell) = self.strategy.get_signal(
pair, self.strategy.ticker_interval,
self.dataprovider.ohlcv(pair, self.strategy.ticker_interval))
pair, self.strategy.timeframe,
self.dataprovider.ohlcv(pair, self.strategy.timeframe))
if buy and not sell:
stake_amount = self.get_trade_stake_amount(pair)
@ -547,7 +547,7 @@ class FreqtradeBot:
exchange=self.exchange.id,
open_order_id=order_id,
strategy=self.strategy.get_strategy_name(),
ticker_interval=timeframe_to_minutes(self.config['ticker_interval'])
timeframe=timeframe_to_minutes(self.config['timeframe'])
)
# Update fees if order is closed
@ -676,6 +676,8 @@ class FreqtradeBot:
raise PricingError from e
else:
rate = self.exchange.fetch_ticker(pair)[ask_strategy['price_side']]
if rate is None:
raise PricingError(f"Sell-Rate for {pair} was empty.")
self._sell_rate_cache[pair] = rate
return rate
@ -696,14 +698,13 @@ class FreqtradeBot:
if (config_ask_strategy.get('use_sell_signal', True) or
config_ask_strategy.get('ignore_roi_if_buy_signal', False)):
(buy, sell) = self.strategy.get_signal(
trade.pair, self.strategy.ticker_interval,
self.dataprovider.ohlcv(trade.pair, self.strategy.ticker_interval))
trade.pair, self.strategy.timeframe,
self.dataprovider.ohlcv(trade.pair, self.strategy.timeframe))
if config_ask_strategy.get('use_order_book', False):
# logger.debug('Order book %s',orderBook)
order_book_min = config_ask_strategy.get('order_book_min', 1)
order_book_max = config_ask_strategy.get('order_book_max', 1)
logger.info(f'Using order book between {order_book_min} and {order_book_max} '
logger.debug(f'Using order book between {order_book_min} and {order_book_max} '
f'for selling {trade.pair}...')
order_book = self._order_book_gen(trade.pair, f"{config_ask_strategy['price_side']}s",
@ -719,6 +720,9 @@ class FreqtradeBot:
raise PricingError from e
logger.debug(f" order book {config_ask_strategy['price_side']} top {i}: "
f"{sell_rate:0.8f}")
# Assign sell-rate to cache - otherwise sell-rate is never updated in the cache,
# resulting in outdated RPC messages
self._sell_rate_cache[trade.pair] = sell_rate
if self._check_and_execute_sell(trade, sell_rate, buy, sell):
return True
@ -769,18 +773,18 @@ class FreqtradeBot:
try:
# First we check if there is already a stoploss on exchange
stoploss_order = self.exchange.get_order(trade.stoploss_order_id, trade.pair) \
stoploss_order = self.exchange.get_stoploss_order(trade.stoploss_order_id, trade.pair) \
if trade.stoploss_order_id else None
except InvalidOrderException as exception:
logger.warning('Unable to fetch stoploss order: %s', exception)
# We check if stoploss order is fulfilled
if stoploss_order and stoploss_order['status'] == 'closed':
if stoploss_order and stoploss_order['status'] in ('closed', 'triggered'):
trade.sell_reason = SellType.STOPLOSS_ON_EXCHANGE.value
self.update_trade_state(trade, stoploss_order, sl_order=True)
# Lock pair for one candle to prevent immediate rebuys
self.strategy.lock_pair(trade.pair,
timeframe_to_next_date(self.config['ticker_interval']))
timeframe_to_next_date(self.config['timeframe']))
self._notify_sell(trade, "stoploss")
return True
@ -802,7 +806,7 @@ class FreqtradeBot:
return False
# If stoploss order is canceled for some reason we add it
if stoploss_order and stoploss_order['status'] == 'canceled':
if stoploss_order and stoploss_order['status'] in ('canceled', 'cancelled'):
if self.create_stoploss_order(trade=trade, stop_price=trade.stop_loss,
rate=trade.stop_loss):
return False
@ -835,7 +839,7 @@ class FreqtradeBot:
logger.info('Trailing stoploss: cancelling current stoploss on exchange (id:{%s}) '
'in order to add another one ...', order['id'])
try:
self.exchange.cancel_order(order['id'], trade.pair)
self.exchange.cancel_stoploss_order(order['id'], trade.pair)
except InvalidOrderException:
logger.exception(f"Could not cancel stoploss order {order['id']} "
f"for pair {trade.pair}")
@ -1063,7 +1067,7 @@ class FreqtradeBot:
# First cancelling stoploss on exchange ...
if self.strategy.order_types.get('stoploss_on_exchange') and trade.stoploss_order_id:
try:
self.exchange.cancel_order(trade.stoploss_order_id, trade.pair)
self.exchange.cancel_stoploss_order(trade.stoploss_order_id, trade.pair)
except InvalidOrderException:
logger.exception(f"Could not cancel stoploss order {trade.stoploss_order_id}")
@ -1090,7 +1094,7 @@ class FreqtradeBot:
Trade.session.flush()
# Lock pair for one candle to prevent immediate rebuys
self.strategy.lock_pair(trade.pair, timeframe_to_next_date(self.config['ticker_interval']))
self.strategy.lock_pair(trade.pair, timeframe_to_next_date(self.config['timeframe']))
self._notify_sell(trade, order_type)

8
freqtrade/loggers.py
View File

@ -11,7 +11,7 @@ from freqtrade.exceptions import OperationalException
logger = logging.getLogger(__name__)
def _set_loggers(verbosity: int = 0) -> None:
def _set_loggers(verbosity: int = 0, api_verbosity: str = 'info') -> None:
"""
Set the logging level for third party libraries
:return: None
@ -28,6 +28,10 @@ def _set_loggers(verbosity: int = 0) -> None:
)
logging.getLogger('telegram').setLevel(logging.INFO)
logging.getLogger('werkzeug').setLevel(
logging.ERROR if api_verbosity == 'error' else logging.INFO
)
def setup_logging(config: Dict[str, Any]) -> None:
"""
@ -77,5 +81,5 @@ def setup_logging(config: Dict[str, Any]) -> None:
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
handlers=log_handlers
)
_set_loggers(verbosity)
_set_loggers(verbosity, config.get('api_server', {}).get('verbosity', 'info'))
logger.info('Verbosity set to %s', verbosity)

45
freqtrade/optimize/backtesting.py
View File

@ -18,7 +18,8 @@ from freqtrade.data.converter import trim_dataframe
from freqtrade.data.dataprovider import DataProvider
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
from freqtrade.optimize.optimize_reports import (show_backtest_results,
from freqtrade.optimize.optimize_reports import (generate_backtest_stats,
show_backtest_results,
store_backtest_result)
from freqtrade.pairlist.pairlistmanager import PairListManager
from freqtrade.persistence import Trade
@ -64,20 +65,6 @@ class Backtesting:
self.strategylist: List[IStrategy] = []
self.exchange = ExchangeResolver.load_exchange(self.config['exchange']['name'], self.config)
self.pairlists = PairListManager(self.exchange, self.config)
if 'VolumePairList' in self.pairlists.name_list:
raise OperationalException("VolumePairList not allowed for backtesting.")
self.pairlists.refresh_pairlist()
if len(self.pairlists.whitelist) == 0:
raise OperationalException("No pair in whitelist.")
if config.get('fee'):
self.fee = config['fee']
else:
self.fee = self.exchange.get_fee(symbol=self.pairlists.whitelist[0])
if self.config.get('runmode') != RunMode.HYPEROPT:
self.dataprovider = DataProvider(self.config, self.exchange)
IStrategy.dp = self.dataprovider
@ -94,12 +81,31 @@ class Backtesting:
self.strategylist.append(StrategyResolver.load_strategy(self.config))
validate_config_consistency(self.config)
if "ticker_interval" not in self.config:
if "timeframe" not in self.config:
raise OperationalException("Timeframe (ticker interval) needs to be set in either "
"configuration or as cli argument `--ticker-interval 5m`")
self.timeframe = str(self.config.get('ticker_interval'))
"configuration or as cli argument `--timeframe 5m`")
self.timeframe = str(self.config.get('timeframe'))
self.timeframe_min = timeframe_to_minutes(self.timeframe)
self.pairlists = PairListManager(self.exchange, self.config)
if 'VolumePairList' in self.pairlists.name_list:
raise OperationalException("VolumePairList not allowed for backtesting.")
if len(self.strategylist) > 1 and 'PrecisionFilter' in self.pairlists.name_list:
raise OperationalException(
"PrecisionFilter not allowed for backtesting multiple strategies."
)
self.pairlists.refresh_pairlist()
if len(self.pairlists.whitelist) == 0:
raise OperationalException("No pair in whitelist.")
if config.get('fee'):
self.fee = config['fee']
else:
self.fee = self.exchange.get_fee(symbol=self.pairlists.whitelist[0])
# Get maximum required startup period
self.required_startup = max([strat.startup_candle_count for strat in self.strategylist])
# Load one (first) strategy
@ -411,4 +417,5 @@ class Backtesting:
if self.config.get('export', False):
store_backtest_result(self.config['exportfilename'], all_results)
# Show backtest results
show_backtest_results(self.config, data, all_results)
stats = generate_backtest_stats(self.config, data, all_results)
show_backtest_results(self.config, stats)

4
freqtrade/optimize/default_hyperopt_loss.py
View File

@ -42,8 +42,8 @@ class DefaultHyperOptLoss(IHyperOptLoss):
* 0.25: Avoiding trade loss
* 1.0 to total profit, compared to the expected value (`EXPECTED_MAX_PROFIT`) defined above
"""
total_profit = results.profit_percent.sum()
trade_duration = results.trade_duration.mean()
total_profit = results['profit_percent'].sum()
trade_duration = results['trade_duration'].mean()
trade_loss = 1 - 0.25 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5.8)
profit_loss = max(0, 1 - total_profit / EXPECTED_MAX_PROFIT)

24
freqtrade/optimize/hyperopt.py
View File

@ -12,7 +12,7 @@ from math import ceil
from collections import OrderedDict
from operator import itemgetter
from pathlib import Path
from pprint import pprint
from pprint import pformat
from typing import Any, Dict, List, Optional
import rapidjson
@ -230,6 +230,9 @@ class Hyperopt:
if space in ['buy', 'sell']:
result_dict.setdefault('params', {}).update(space_params)
elif space == 'roi':
# TODO: get rid of OrderedDict when support for python 3.6 will be
# dropped (dicts keep the order as the language feature)
# Convert keys in min_roi dict to strings because
# rapidjson cannot dump dicts with integer keys...
# OrderedDict is used to keep the numeric order of the items
@ -244,11 +247,24 @@ class Hyperopt:
def _params_pretty_print(params, space: str, header: str) -> None:
if space in params:
space_params = Hyperopt._space_params(params, space, 5)
params_result = f"\n# {header}\n"
if space == 'stoploss':
print(header, space_params.get('stoploss'))
params_result += f"stoploss = {space_params.get('stoploss')}"
elif space == 'roi':
# TODO: get rid of OrderedDict when support for python 3.6 will be
# dropped (dicts keep the order as the language feature)
minimal_roi_result = rapidjson.dumps(
OrderedDict(
(str(k), v) for k, v in space_params.items()
),
default=str, indent=4, number_mode=rapidjson.NM_NATIVE)
params_result += f"minimal_roi = {minimal_roi_result}"
else:
print(header)
pprint(space_params, indent=4)
params_result += f"{space}_params = {pformat(space_params, indent=4)}"
params_result = params_result.replace("}", "\n}").replace("{", "{\n ")
params_result = params_result.replace("\n", "\n ")
print(params_result)
@staticmethod
def _space_params(params, space: str, r: int = None) -> Dict:

11
freqtrade/optimize/hyperopt_interface.py
View File

@ -31,13 +31,15 @@ class IHyperOpt(ABC):
Class attributes you can use:
ticker_interval -> int: value of the ticker interval to use for the strategy
"""
ticker_interval: str
ticker_interval: str # DEPRECATED
timeframe: str
def __init__(self, config: dict) -> None:
self.config = config
# Assign ticker_interval to be used in hyperopt
IHyperOpt.ticker_interval = str(config['ticker_interval'])
IHyperOpt.ticker_interval = str(config['timeframe']) # DEPRECATED
IHyperOpt.timeframe = str(config['timeframe'])
@staticmethod
def buy_strategy_generator(params: Dict[str, Any]) -> Callable:
@ -218,9 +220,10 @@ class IHyperOpt(ABC):
# Why do I still need such shamanic mantras in modern python?
def __getstate__(self):
state = self.__dict__.copy()
state['ticker_interval'] = self.ticker_interval
state['timeframe'] = self.timeframe
return state
def __setstate__(self, state):
self.__dict__.update(state)
IHyperOpt.ticker_interval = state['ticker_interval']
IHyperOpt.ticker_interval = state['timeframe']
IHyperOpt.timeframe = state['timeframe']

2
freqtrade/optimize/hyperopt_loss_interface.py
View File

@ -14,7 +14,7 @@ class IHyperOptLoss(ABC):
Interface for freqtrade hyperopt Loss functions.
Defines the custom loss function (`hyperopt_loss_function()` which is evaluated every epoch.)
"""
ticker_interval: str
timeframe: str
@staticmethod
@abstractmethod

2
freqtrade/optimize/hyperopt_loss_onlyprofit.py
View File

@ -34,5 +34,5 @@ class OnlyProfitHyperOptLoss(IHyperOptLoss):
"""
Objective function, returns smaller number for better results.
"""
total_profit = results.profit_percent.sum()
total_profit = results['profit_percent'].sum()
return 1 - total_profit / EXPECTED_MAX_PROFIT

234
freqtrade/optimize/optimize_reports.py
View File

@ -18,10 +18,7 @@ def store_backtest_result(recordfilename: Path, all_results: Dict[str, DataFrame
:param all_results: Dict of Dataframes, one results dataframe per strategy
"""
for strategy, results in all_results.items():
records = [(t.pair, t.profit_percent, t.open_time.timestamp(),
t.close_time.timestamp(), t.open_index - 1, t.trade_duration,
t.open_rate, t.close_rate, t.open_at_end, t.sell_reason.value)
for index, t in results.iterrows()]
records = backtest_result_to_list(results)
if records:
filename = recordfilename
@ -34,6 +31,18 @@ def store_backtest_result(recordfilename: Path, all_results: Dict[str, DataFrame
file_dump_json(filename, records)
def backtest_result_to_list(results: DataFrame) -> List[List]:
"""
Converts a list of Backtest-results to list
:param results: Dataframe containing results for one strategy
:return: List of Lists containing the trades
"""
return [[t.pair, t.profit_percent, t.open_time.timestamp(),
t.close_time.timestamp(), t.open_index - 1, t.trade_duration,
t.open_rate, t.close_rate, t.open_at_end, t.sell_reason.value]
for index, t in results.iterrows()]
def _get_line_floatfmt() -> List[str]:
"""
Generate floatformat (goes in line with _generate_result_line())
@ -56,25 +65,25 @@ def _generate_result_line(result: DataFrame, max_open_trades: int, first_column:
"""
return {
'key': first_column,
'trades': len(result.index),
'profit_mean': result.profit_percent.mean(),
'profit_mean_pct': result.profit_percent.mean() * 100.0,
'profit_sum': result.profit_percent.sum(),
'profit_sum_pct': result.profit_percent.sum() * 100.0,
'profit_total_abs': result.profit_abs.sum(),
'profit_total_pct': result.profit_percent.sum() * 100.0 / max_open_trades,
'trades': len(result),
'profit_mean': result['profit_percent'].mean(),
'profit_mean_pct': result['profit_percent'].mean() * 100.0,
'profit_sum': result['profit_percent'].sum(),
'profit_sum_pct': result['profit_percent'].sum() * 100.0,
'profit_total_abs': result['profit_abs'].sum(),
'profit_total_pct': result['profit_percent'].sum() * 100.0 / max_open_trades,
'duration_avg': str(timedelta(
minutes=round(result.trade_duration.mean()))
minutes=round(result['trade_duration'].mean()))
) if not result.empty else '0:00',
# 'duration_max': str(timedelta(
# minutes=round(result.trade_duration.max()))
# minutes=round(result['trade_duration'].max()))
# ) if not result.empty else '0:00',
# 'duration_min': str(timedelta(
# minutes=round(result.trade_duration.min()))
# minutes=round(result['trade_duration'].min()))
# ) if not result.empty else '0:00',
'wins': len(result[result.profit_abs > 0]),
'draws': len(result[result.profit_abs == 0]),
'losses': len(result[result.profit_abs < 0]),
'wins': len(result[result['profit_abs'] > 0]),
'draws': len(result[result['profit_abs'] == 0]),
'losses': len(result[result['profit_abs'] < 0]),
}
@ -93,8 +102,8 @@ def generate_pair_metrics(data: Dict[str, Dict], stake_currency: str, max_open_t
tabular_data = []
for pair in data:
result = results[results.pair == pair]
if skip_nan and result.profit_abs.isnull().all():
result = results[results['pair'] == pair]
if skip_nan and result['profit_abs'].isnull().all():
continue
tabular_data.append(_generate_result_line(result, max_open_trades, pair))
@ -104,25 +113,6 @@ def generate_pair_metrics(data: Dict[str, Dict], stake_currency: str, max_open_t
return tabular_data
def generate_text_table(pair_results: List[Dict[str, Any]], stake_currency: str) -> str:
"""
Generates and returns a text table for the given backtest data and the results dataframe
:param pair_results: List of Dictionaries - one entry per pair + final TOTAL row
:param stake_currency: stake-currency - used to correctly name headers
:return: pretty printed table with tabulate as string
"""
headers = _get_line_header('Pair', stake_currency)
floatfmt = _get_line_floatfmt()
output = [[
t['key'], t['trades'], t['profit_mean_pct'], t['profit_sum_pct'], t['profit_total_abs'],
t['profit_total_pct'], t['duration_avg'], t['wins'], t['draws'], t['losses']
] for t in pair_results]
# Ignore type as floatfmt does allow tuples but mypy does not know that
return tabulate(output, headers=headers,
floatfmt=floatfmt, tablefmt="orgtbl", stralign="right") # type: ignore
def generate_sell_reason_stats(max_open_trades: int, results: DataFrame) -> List[Dict]:
"""
Generate small table outlining Backtest results
@ -157,33 +147,6 @@ def generate_sell_reason_stats(max_open_trades: int, results: DataFrame) -> List
return tabular_data
def generate_text_table_sell_reason(sell_reason_stats: List[Dict[str, Any]],
stake_currency: str) -> str:
"""
Generate small table outlining Backtest results
:param sell_reason_stats: Sell reason metrics
:param stake_currency: Stakecurrency used
:return: pretty printed table with tabulate as string
"""
headers = [
'Sell Reason',
'Sells',
'Wins',
'Draws',
'Losses',
'Avg Profit %',
'Cum Profit %',
f'Tot Profit {stake_currency}',
'Tot Profit %',
]
output = [[
t['sell_reason'], t['trades'], t['wins'], t['draws'], t['losses'],
t['profit_mean_pct'], t['profit_sum_pct'], t['profit_total_abs'], t['profit_pct_total'],
] for t in sell_reason_stats]
return tabulate(output, headers=headers, tablefmt="orgtbl", stralign="right")
def generate_strategy_metrics(stake_currency: str, max_open_trades: int,
all_results: Dict) -> List[Dict]:
"""
@ -200,26 +163,6 @@ def generate_strategy_metrics(stake_currency: str, max_open_trades: int,
return tabular_data
def generate_text_table_strategy(strategy_results, stake_currency: str) -> str:
"""
Generate summary table per strategy
:param stake_currency: stake-currency - used to correctly name headers
:param max_open_trades: Maximum allowed open trades used for backtest
:param all_results: Dict of <Strategyname: BacktestResult> containing results for all strategies
:return: pretty printed table with tabulate as string
"""
floatfmt = _get_line_floatfmt()
headers = _get_line_header('Strategy', stake_currency)
output = [[
t['key'], t['trades'], t['profit_mean_pct'], t['profit_sum_pct'], t['profit_total_abs'],
t['profit_total_pct'], t['duration_avg'], t['wins'], t['draws'], t['losses']
] for t in strategy_results]
# Ignore type as floatfmt does allow tuples but mypy does not know that
return tabulate(output, headers=headers,
floatfmt=floatfmt, tablefmt="orgtbl", stralign="right") # type: ignore
def generate_edge_table(results: dict) -> str:
floatfmt = ('s', '.10g', '.2f', '.2f', '.2f', '.2f', 'd', 'd', 'd')
@ -246,12 +189,20 @@ def generate_edge_table(results: dict) -> str:
floatfmt=floatfmt, tablefmt="orgtbl", stralign="right") # type: ignore
def show_backtest_results(config: Dict, btdata: Dict[str, DataFrame],
all_results: Dict[str, DataFrame]):
def generate_backtest_stats(config: Dict, btdata: Dict[str, DataFrame],
all_results: Dict[str, DataFrame]) -> Dict[str, Any]:
"""
:param config: Configuration object used for backtest
:param btdata: Backtest data
:param all_results: backtest result - dictionary with { Strategy: results}.
:return:
Dictionary containing results per strategy and a stratgy summary.
"""
stake_currency = config['stake_currency']
max_open_trades = config['max_open_trades']
result: Dict[str, Any] = {'strategy': {}}
for strategy, results in all_results.items():
pair_results = generate_pair_metrics(btdata, stake_currency=stake_currency,
max_open_trades=max_open_trades,
results=results, skip_nan=False)
@ -261,21 +212,111 @@ def show_backtest_results(config: Dict, btdata: Dict[str, DataFrame],
max_open_trades=max_open_trades,
results=results.loc[results['open_at_end']],
skip_nan=True)
strat_stats = {
'trades': backtest_result_to_list(results),
'results_per_pair': pair_results,
'sell_reason_summary': sell_reason_stats,
'left_open_trades': left_open_results,
}
result['strategy'][strategy] = strat_stats
strategy_results = generate_strategy_metrics(stake_currency=stake_currency,
max_open_trades=max_open_trades,
all_results=all_results)
result['strategy_comparison'] = strategy_results
return result
###
# Start output section
###
def text_table_bt_results(pair_results: List[Dict[str, Any]], stake_currency: str) -> str:
"""
Generates and returns a text table for the given backtest data and the results dataframe
:param pair_results: List of Dictionaries - one entry per pair + final TOTAL row
:param stake_currency: stake-currency - used to correctly name headers
:return: pretty printed table with tabulate as string
"""
headers = _get_line_header('Pair', stake_currency)
floatfmt = _get_line_floatfmt()
output = [[
t['key'], t['trades'], t['profit_mean_pct'], t['profit_sum_pct'], t['profit_total_abs'],
t['profit_total_pct'], t['duration_avg'], t['wins'], t['draws'], t['losses']
] for t in pair_results]
# Ignore type as floatfmt does allow tuples but mypy does not know that
return tabulate(output, headers=headers,
floatfmt=floatfmt, tablefmt="orgtbl", stralign="right")
def text_table_sell_reason(sell_reason_stats: List[Dict[str, Any]], stake_currency: str) -> str:
"""
Generate small table outlining Backtest results
:param sell_reason_stats: Sell reason metrics
:param stake_currency: Stakecurrency used
:return: pretty printed table with tabulate as string
"""
headers = [
'Sell Reason',
'Sells',
'Wins',
'Draws',
'Losses',
'Avg Profit %',
'Cum Profit %',
f'Tot Profit {stake_currency}',
'Tot Profit %',
]
output = [[
t['sell_reason'], t['trades'], t['wins'], t['draws'], t['losses'],
t['profit_mean_pct'], t['profit_sum_pct'], t['profit_total_abs'], t['profit_pct_total'],
] for t in sell_reason_stats]
return tabulate(output, headers=headers, tablefmt="orgtbl", stralign="right")
def text_table_strategy(strategy_results, stake_currency: str) -> str:
"""
Generate summary table per strategy
:param stake_currency: stake-currency - used to correctly name headers
:param max_open_trades: Maximum allowed open trades used for backtest
:param all_results: Dict of <Strategyname: BacktestResult> containing results for all strategies
:return: pretty printed table with tabulate as string
"""
floatfmt = _get_line_floatfmt()
headers = _get_line_header('Strategy', stake_currency)
output = [[
t['key'], t['trades'], t['profit_mean_pct'], t['profit_sum_pct'], t['profit_total_abs'],
t['profit_total_pct'], t['duration_avg'], t['wins'], t['draws'], t['losses']
] for t in strategy_results]
# Ignore type as floatfmt does allow tuples but mypy does not know that
return tabulate(output, headers=headers,
floatfmt=floatfmt, tablefmt="orgtbl", stralign="right")
def show_backtest_results(config: Dict, backtest_stats: Dict):
stake_currency = config['stake_currency']
for strategy, results in backtest_stats['strategy'].items():
# Print results
print(f"Result for strategy {strategy}")
table = generate_text_table(pair_results, stake_currency=stake_currency)
table = text_table_bt_results(results['results_per_pair'], stake_currency=stake_currency)
if isinstance(table, str):
print(' BACKTESTING REPORT '.center(len(table.splitlines()[0]), '='))
print(table)
table = generate_text_table_sell_reason(sell_reason_stats=sell_reason_stats,
stake_currency=stake_currency,
)
table = text_table_sell_reason(sell_reason_stats=results['sell_reason_summary'],
stake_currency=stake_currency)
if isinstance(table, str):
print(' SELL REASON STATS '.center(len(table.splitlines()[0]), '='))
print(table)
table = generate_text_table(left_open_results, stake_currency=stake_currency)
table = text_table_bt_results(results['left_open_trades'], stake_currency=stake_currency)
if isinstance(table, str):
print(' LEFT OPEN TRADES REPORT '.center(len(table.splitlines()[0]), '='))
print(table)
@ -283,13 +324,10 @@ def show_backtest_results(config: Dict, btdata: Dict[str, DataFrame],
print('=' * len(table.splitlines()[0]))
print()
if len(all_results) > 1:
if len(backtest_stats['strategy']) > 1:
# Print Strategy summary table
strategy_results = generate_strategy_metrics(stake_currency=stake_currency,
max_open_trades=max_open_trades,
all_results=all_results)
table = generate_text_table_strategy(strategy_results, stake_currency)
table = text_table_strategy(backtest_stats['strategy_comparison'], stake_currency)
print(' STRATEGY SUMMARY '.center(len(table.splitlines()[0]), '='))
print(table)
print('=' * len(table.splitlines()[0]))

76
freqtrade/pairlist/AgeFilter.py Normal file
View File

@ -0,0 +1,76 @@
"""
Minimum age (days listed) pair list filter
"""
import logging
import arrow
from typing import Any, Dict
from freqtrade.misc import plural
from freqtrade.pairlist.IPairList import IPairList
logger = logging.getLogger(__name__)
class AgeFilter(IPairList):
# Checked symbols cache (dictionary of ticker symbol => timestamp)
_symbolsChecked: Dict[str, int] = {}
def __init__(self, exchange, pairlistmanager,
config: Dict[str, Any], pairlistconfig: Dict[str, Any],
pairlist_pos: int) -> None:
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
self._min_days_listed = pairlistconfig.get('min_days_listed', 10)
self._enabled = self._min_days_listed >= 1
@property
def needstickers(self) -> bool:
"""
Boolean property defining if tickers are necessary.
If no Pairlist requires tickers, an empty List is passed
as tickers argument to filter_pairlist
"""
return True
def short_desc(self) -> str:
"""
Short whitelist method description - used for startup-messages
"""
return (f"{self.name} - Filtering pairs with age less than "
f"{self._min_days_listed} {plural(self._min_days_listed, 'day')}.")
def _validate_pair(self, ticker: dict) -> bool:
"""
Validate age for the ticker
:param ticker: ticker dict as returned from ccxt.load_markets()
:return: True if the pair can stay, False if it should be removed
"""
# Check symbol in cache
if ticker['symbol'] in self._symbolsChecked:
return True
since_ms = int(arrow.utcnow()
.floor('day')
.shift(days=-self._min_days_listed)
.float_timestamp) * 1000
daily_candles = self._exchange.get_historic_ohlcv(pair=ticker['symbol'],
timeframe='1d',
since_ms=since_ms)
if daily_candles is not None:
if len(daily_candles) > self._min_days_listed:
# We have fetched at least the minimum required number of daily candles
# Add to cache, store the time we last checked this symbol
self._symbolsChecked[ticker['symbol']] = int(arrow.utcnow().float_timestamp) * 1000
return True
else:
self.log_on_refresh(logger.info, f"Removed {ticker['symbol']} from whitelist, "
f"because age is less than "
f"{self._min_days_listed} "
f"{plural(self._min_days_listed, 'day')}")
return False
return False

24
freqtrade/pairlist/IPairList.py
View File

@ -8,6 +8,7 @@ from typing import Any, Dict, List
from cachetools import TTLCache, cached
from freqtrade.exceptions import OperationalException
from freqtrade.exchange import market_is_active
@ -67,7 +68,7 @@ class IPairList(ABC):
def needstickers(self) -> bool:
"""
Boolean property defining if tickers are necessary.
If no Pairlist requries tickers, an empty List is passed
If no Pairlist requires tickers, an empty List is passed
as tickers argument to filter_pairlist
"""
@ -90,6 +91,24 @@ class IPairList(ABC):
"""
raise NotImplementedError()
def gen_pairlist(self, cached_pairlist: List[str], tickers: Dict) -> List[str]:
"""
Generate the pairlist.
This method is called once by the pairlistmanager in the refresh_pairlist()
method to supply the starting pairlist for the chain of the Pairlist Handlers.
Pairlist Filters (those Pairlist Handlers that cannot be used at the first
position in the chain) shall not override this base implementation --
it will raise the exception if a Pairlist Handler is used at the first
position in the chain.
:param cached_pairlist: Previously generated pairlist (cached)
:param tickers: Tickers (from exchange.get_tickers()).
:return: List of pairs
"""
raise OperationalException("This Pairlist Handler should not be used "
"at the first position in the list of Pairlist Handlers.")
def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
"""
Filters and sorts pairlist and returns the whitelist again.
@ -131,6 +150,9 @@ class IPairList(ABC):
black_listed
"""
markets = self._exchange.markets
if not markets:
raise OperationalException(
'Markets not loaded. Make sure that exchange is initialized correctly.')
sanitized_whitelist: List[str] = []
for pair in pairlist:

8
freqtrade/pairlist/PrecisionFilter.py
View File

@ -5,7 +5,7 @@ import logging
from typing import Any, Dict
from freqtrade.pairlist.IPairList import IPairList
from freqtrade.exceptions import OperationalException
logger = logging.getLogger(__name__)
@ -17,6 +17,10 @@ class PrecisionFilter(IPairList):
pairlist_pos: int) -> None:
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
if 'stoploss' not in self._config:
raise OperationalException(
'PrecisionFilter can only work with stoploss defined. Please add the '
'stoploss key to your configuration (overwrites eventual strategy settings).')
self._stoploss = self._config['stoploss']
self._enabled = self._stoploss != 0
@ -27,7 +31,7 @@ class PrecisionFilter(IPairList):
def needstickers(self) -> bool:
"""
Boolean property defining if tickers are necessary.
If no Pairlist requries tickers, an empty List is passed
If no Pairlist requires tickers, an empty List is passed
as tickers argument to filter_pairlist
"""
return True

2
freqtrade/pairlist/PriceFilter.py
View File

@ -24,7 +24,7 @@ class PriceFilter(IPairList):
def needstickers(self) -> bool:
"""
Boolean property defining if tickers are necessary.
If no Pairlist requries tickers, an empty List is passed
If no Pairlist requires tickers, an empty List is passed
as tickers argument to filter_pairlist
"""
return True

2
freqtrade/pairlist/ShuffleFilter.py
View File

@ -25,7 +25,7 @@ class ShuffleFilter(IPairList):
def needstickers(self) -> bool:
"""
Boolean property defining if tickers are necessary.
If no Pairlist requries tickers, an empty List is passed
If no Pairlist requires tickers, an empty List is passed
as tickers argument to filter_pairlist
"""
return False

2
freqtrade/pairlist/SpreadFilter.py
View File

@ -24,7 +24,7 @@ class SpreadFilter(IPairList):
def needstickers(self) -> bool:
"""
Boolean property defining if tickers are necessary.
If no Pairlist requries tickers, an empty List is passed
If no Pairlist requires tickers, an empty List is passed
as tickers argument to filter_pairlist
"""
return True

25
freqtrade/pairlist/StaticPairList.py
View File

@ -4,8 +4,9 @@ Static Pair List provider
Provides pair white list as it configured in config
"""
import logging
from typing import Dict, List
from typing import Any, Dict, List
from freqtrade.exceptions import OperationalException
from freqtrade.pairlist.IPairList import IPairList
@ -14,11 +15,20 @@ logger = logging.getLogger(__name__)
class StaticPairList(IPairList):
def __init__(self, exchange, pairlistmanager,
config: Dict[str, Any], pairlistconfig: Dict[str, Any],
pairlist_pos: int) -> None:
super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
if self._pairlist_pos != 0:
raise OperationalException(f"{self.name} can only be used in the first position "
"in the list of Pairlist Handlers.")
@property
def needstickers(self) -> bool:
"""
Boolean property defining if tickers are necessary.
If no Pairlist requries tickers, an empty List is passed
If no Pairlist requires tickers, an empty List is passed
as tickers argument to filter_pairlist
"""
return False
@ -30,6 +40,15 @@ class StaticPairList(IPairList):
"""
return f"{self.name}"
def gen_pairlist(self, cached_pairlist: List[str], tickers: Dict) -> List[str]:
"""
Generate the pairlist
:param cached_pairlist: Previously generated pairlist (cached)
:param tickers: Tickers (from exchange.get_tickers()).
:return: List of pairs
"""
return self._whitelist_for_active_markets(self._config['exchange']['pair_whitelist'])
def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
"""
Filters and sorts pairlist and returns the whitelist again.
@ -38,4 +57,4 @@ class StaticPairList(IPairList):
:param tickers: Tickers (from exchange.get_tickers()). May be cached.
:return: new whitelist
"""
return self._whitelist_for_active_markets(self._config['exchange']['pair_whitelist'])
return pairlist

60
freqtrade/pairlist/VolumePairList.py
View File

@ -54,7 +54,7 @@ class VolumePairList(IPairList):
def needstickers(self) -> bool:
"""
Boolean property defining if tickers are necessary.
If no Pairlist requries tickers, an empty List is passed
If no Pairlist requires tickers, an empty List is passed
as tickers argument to filter_pairlist
"""
return True
@ -68,6 +68,31 @@ class VolumePairList(IPairList):
"""
return f"{self.name} - top {self._pairlistconfig['number_assets']} volume pairs."
def gen_pairlist(self, cached_pairlist: List[str], tickers: Dict) -> List[str]:
"""
Generate the pairlist
:param cached_pairlist: Previously generated pairlist (cached)
:param tickers: Tickers (from exchange.get_tickers()).
:return: List of pairs
"""
# Generate dynamic whitelist
# Must always run if this pairlist is not the first in the list.
if self._last_refresh + self.refresh_period < datetime.now().timestamp():
self._last_refresh = int(datetime.now().timestamp())
# Use fresh pairlist
# Check if pair quote currency equals to the stake currency.
filtered_tickers = [
v for k, v in tickers.items()
if (self._exchange.get_pair_quote_currency(k) == self._stake_currency
and v[self._sort_key] is not None)]
pairlist = [s['symbol'] for s in filtered_tickers]
else:
# Use the cached pairlist if it's not time yet to refresh
pairlist = cached_pairlist
return pairlist
def filter_pairlist(self, pairlist: List[str], tickers: Dict) -> List[str]:
"""
Filters and sorts pairlist and returns the whitelist again.
@ -76,36 +101,7 @@ class VolumePairList(IPairList):
:param tickers: Tickers (from exchange.get_tickers()). May be cached.
:return: new whitelist
"""
# Generate dynamic whitelist
# Must always run if this pairlist is not the first in the list.
if (self._pairlist_pos != 0 or
(self._last_refresh + self.refresh_period < datetime.now().timestamp())):
self._last_refresh = int(datetime.now().timestamp())
pairs = self._gen_pair_whitelist(pairlist, tickers)
else:
pairs = pairlist
self.log_on_refresh(logger.info, f"Searching {self._number_pairs} pairs: {pairs}")
return pairs
def _gen_pair_whitelist(self, pairlist: List[str], tickers: Dict) -> List[str]:
"""
Updates the whitelist with with a dynamically generated list
:param pairlist: pairlist to filter or sort
:param tickers: Tickers (from exchange.get_tickers()).
:return: List of pairs
"""
if self._pairlist_pos == 0:
# If VolumePairList is the first in the list, use fresh pairlist
# Check if pair quote currency equals to the stake currency.
filtered_tickers = [
v for k, v in tickers.items()
if (self._exchange.get_pair_quote_currency(k) == self._stake_currency
and v[self._sort_key] is not None)]
else:
# If other pairlist is in front, use the incoming pairlist.
# Use the incoming pairlist.
filtered_tickers = [v for k, v in tickers.items() if k in pairlist]
if self._min_value > 0:
@ -120,4 +116,6 @@ class VolumePairList(IPairList):
# Limit pairlist to the requested number of pairs
pairs = pairs[:self._number_pairs]
self.log_on_refresh(logger.info, f"Searching {self._number_pairs} pairs: {pairs}")
return pairs

7
freqtrade/pairlist/pairlistmanager.py
View File

@ -87,6 +87,9 @@ class PairListManager():
# Adjust whitelist if filters are using tickers
pairlist = self._prepare_whitelist(self._whitelist.copy(), tickers)
# Generate the pairlist with first Pairlist Handler in the chain
pairlist = self._pairlist_handlers[0].gen_pairlist(self._whitelist, tickers)
# Process all Pairlist Handlers in the chain
for pairlist_handler in self._pairlist_handlers:
pairlist = pairlist_handler.filter_pairlist(pairlist, tickers)
@ -128,6 +131,6 @@ class PairListManager():
def create_pair_list(self, pairs: List[str], timeframe: str = None) -> ListPairsWithTimeframes:
"""
Create list of pair tuples with (pair, ticker_interval)
Create list of pair tuples with (pair, timeframe)
"""
return [(pair, timeframe or self._config['ticker_interval']) for pair in pairs]
return [(pair, timeframe or self._config['timeframe']) for pair in pairs]

54
freqtrade/persistence.py
View File

@ -86,7 +86,7 @@ def check_migrate(engine) -> None:
logger.debug(f'trying {table_back_name}')
# Check for latest column
if not has_column(cols, 'sell_order_status'):
if not has_column(cols, 'timeframe'):
logger.info(f'Running database migration - backup available as {table_back_name}')
fee_open = get_column_def(cols, 'fee_open', 'fee')
@ -107,7 +107,12 @@ def check_migrate(engine) -> None:
min_rate = get_column_def(cols, 'min_rate', 'null')
sell_reason = get_column_def(cols, 'sell_reason', 'null')
strategy = get_column_def(cols, 'strategy', 'null')
ticker_interval = get_column_def(cols, 'ticker_interval', 'null')
# If ticker-interval existed use that, else null.
if has_column(cols, 'ticker_interval'):
timeframe = get_column_def(cols, 'timeframe', 'ticker_interval')
else:
timeframe = get_column_def(cols, 'timeframe', 'null')
open_trade_price = get_column_def(cols, 'open_trade_price',
f'amount * open_rate * (1 + {fee_open})')
close_profit_abs = get_column_def(
@ -133,7 +138,7 @@ def check_migrate(engine) -> None:
stop_loss, stop_loss_pct, initial_stop_loss, initial_stop_loss_pct,
stoploss_order_id, stoploss_last_update,
max_rate, min_rate, sell_reason, sell_order_status, strategy,
ticker_interval, open_trade_price, close_profit_abs
timeframe, open_trade_price, close_profit_abs
)
select id, lower(exchange),
case
@ -155,7 +160,7 @@ def check_migrate(engine) -> None:
{stoploss_order_id} stoploss_order_id, {stoploss_last_update} stoploss_last_update,
{max_rate} max_rate, {min_rate} min_rate, {sell_reason} sell_reason,
{sell_order_status} sell_order_status,
{strategy} strategy, {ticker_interval} ticker_interval,
{strategy} strategy, {timeframe} timeframe,
{open_trade_price} open_trade_price, {close_profit_abs} close_profit_abs
from {table_back_name}
""")
@ -232,7 +237,7 @@ class Trade(_DECL_BASE):
sell_reason = Column(String, nullable=True)
sell_order_status = Column(String, nullable=True)
strategy = Column(String, nullable=True)
ticker_interval = Column(Integer, nullable=True)
timeframe = Column(Integer, nullable=True)
def __init__(self, **kwargs):
super().__init__(**kwargs)
@ -249,39 +254,57 @@ class Trade(_DECL_BASE):
'trade_id': self.id,
'pair': self.pair,
'is_open': self.is_open,
'exchange': self.exchange,
'amount': round(self.amount, 8),
'stake_amount': round(self.stake_amount, 8),
'strategy': self.strategy,
'ticker_interval': self.timeframe, # DEPRECATED
'timeframe': self.timeframe,
'fee_open': self.fee_open,
'fee_open_cost': self.fee_open_cost,
'fee_open_currency': self.fee_open_currency,
'fee_close': self.fee_close,
'fee_close_cost': self.fee_close_cost,
'fee_close_currency': self.fee_close_currency,
'open_date_hum': arrow.get(self.open_date).humanize(),
'open_date': self.open_date.strftime("%Y-%m-%d %H:%M:%S"),
'open_timestamp': int(self.open_date.timestamp() * 1000),
'open_rate': self.open_rate,
'open_rate_requested': self.open_rate_requested,
'open_trade_price': self.open_trade_price,
'close_date_hum': (arrow.get(self.close_date).humanize()
if self.close_date else None),
'close_date': (self.close_date.strftime("%Y-%m-%d %H:%M:%S")
if self.close_date else None),
'close_timestamp': int(self.close_date.timestamp() * 1000) if self.close_date else None,
'open_rate': self.open_rate,
'open_rate_requested': self.open_rate_requested,
'open_trade_price': self.open_trade_price,
'close_rate': self.close_rate,
'close_rate_requested': self.close_rate_requested,
'amount': round(self.amount, 8),
'stake_amount': round(self.stake_amount, 8),
'close_profit': self.close_profit,
'close_profit_abs': self.close_profit_abs,
'sell_reason': self.sell_reason,
'sell_order_status': self.sell_order_status,
'stop_loss': self.stop_loss,
'stop_loss': self.stop_loss, # Deprecated - should not be used
'stop_loss_abs': self.stop_loss,
'stop_loss_ratio': self.stop_loss_pct if self.stop_loss_pct else None,
'stop_loss_pct': (self.stop_loss_pct * 100) if self.stop_loss_pct else None,
'initial_stop_loss': self.initial_stop_loss,
'stoploss_order_id': self.stoploss_order_id,
'stoploss_last_update': (self.stoploss_last_update.strftime("%Y-%m-%d %H:%M:%S")
if self.stoploss_last_update else None),
'stoploss_last_update_timestamp': (int(self.stoploss_last_update.timestamp() * 1000)
if self.stoploss_last_update else None),
'initial_stop_loss': self.initial_stop_loss, # Deprecated - should not be used
'initial_stop_loss_abs': self.initial_stop_loss,
'initial_stop_loss_ratio': (self.initial_stop_loss_pct
if self.initial_stop_loss_pct else None),
'initial_stop_loss_pct': (self.initial_stop_loss_pct * 100
if self.initial_stop_loss_pct else None),
'min_rate': self.min_rate,
'max_rate': self.max_rate,
'strategy': self.strategy,
'ticker_interval': self.ticker_interval,
'open_order_id': self.open_order_id,
}
@ -357,7 +380,7 @@ class Trade(_DECL_BASE):
elif order_type in ('market', 'limit') and order['side'] == 'sell':
self.close(order['price'])
logger.info('%s_SELL has been fulfilled for %s.', order_type.upper(), self)
elif order_type in ('stop_loss_limit', 'stop-loss'):
elif order_type in ('stop_loss_limit', 'stop-loss', 'stop'):
self.stoploss_order_id = None
self.close_rate_requested = self.stop_loss
logger.info('%s is hit for %s.', order_type.upper(), self)
@ -546,6 +569,7 @@ class Trade(_DECL_BASE):
def get_best_pair():
"""
Get best pair with closed trade.
:returns: Tuple containing (pair, profit_sum)
"""
best_pair = Trade.session.query(
Trade.pair, func.sum(Trade.close_profit).label('profit_sum')

20
freqtrade/plot/plotting.py
View File

@ -45,7 +45,7 @@ def init_plotscript(config):
data = load_data(
datadir=config.get("datadir"),
pairs=pairs,
timeframe=config.get('ticker_interval', '5m'),
timeframe=config.get('timeframe', '5m'),
timerange=timerange,
data_format=config.get('dataformat_ohlcv', 'json'),
)
@ -162,7 +162,7 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
# Trades can be empty
if trades is not None and len(trades) > 0:
# Create description for sell summarizing the trade
trades['desc'] = trades.apply(lambda row: f"{round(row['profitperc'] * 100, 1)}%, "
trades['desc'] = trades.apply(lambda row: f"{round(row['profit_percent'] * 100, 1)}%, "
f"{row['sell_reason']}, {row['duration']} min",
axis=1)
trade_buys = go.Scatter(
@ -181,9 +181,9 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
)
trade_sells = go.Scatter(
x=trades.loc[trades['profitperc'] > 0, "close_time"],
y=trades.loc[trades['profitperc'] > 0, "close_rate"],
text=trades.loc[trades['profitperc'] > 0, "desc"],
x=trades.loc[trades['profit_percent'] > 0, "close_time"],
y=trades.loc[trades['profit_percent'] > 0, "close_rate"],
text=trades.loc[trades['profit_percent'] > 0, "desc"],
mode='markers',
name='Sell - Profit',
marker=dict(
@ -194,9 +194,9 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
)
)
trade_sells_loss = go.Scatter(
x=trades.loc[trades['profitperc'] <= 0, "close_time"],
y=trades.loc[trades['profitperc'] <= 0, "close_rate"],
text=trades.loc[trades['profitperc'] <= 0, "desc"],
x=trades.loc[trades['profit_percent'] <= 0, "close_time"],
y=trades.loc[trades['profit_percent'] <= 0, "close_rate"],
text=trades.loc[trades['profit_percent'] <= 0, "desc"],
mode='markers',
name='Sell - Loss',
marker=dict(
@ -487,7 +487,7 @@ def load_and_plot_trades(config: Dict[str, Any]):
plot_config=strategy.plot_config if hasattr(strategy, 'plot_config') else {}
)
store_plot_file(fig, filename=generate_plot_filename(pair, config['ticker_interval']),
store_plot_file(fig, filename=generate_plot_filename(pair, config['timeframe']),
directory=config['user_data_dir'] / "plot")
logger.info('End of plotting process. %s plots generated', pair_counter)
@ -515,6 +515,6 @@ def plot_profit(config: Dict[str, Any]) -> None:
# Create an average close price of all the pairs that were involved.
# this could be useful to gauge the overall market trend
fig = generate_profit_graph(plot_elements["pairs"], plot_elements["ohlcv"],
trades, config.get('ticker_interval', '5m'))
trades, config.get('timeframe', '5m'))
store_plot_file(fig, filename='freqtrade-profit-plot.html',
directory=config['user_data_dir'] / "plot", auto_open=True)

5
freqtrade/resolvers/hyperopt_resolver.py
View File

@ -77,8 +77,9 @@ class HyperOptLossResolver(IResolver):
config, kwargs={},
extra_dir=config.get('hyperopt_path'))
# Assign ticker_interval to be used in hyperopt
hyperoptloss.__class__.ticker_interval = str(config['ticker_interval'])
# Assign timeframe to be used in hyperopt
hyperoptloss.__class__.ticker_interval = str(config['timeframe'])
hyperoptloss.__class__.timeframe = str(config['timeframe'])
if not hasattr(hyperoptloss, 'hyperopt_loss_function'):
raise OperationalException(

60
freqtrade/resolvers/strategy_resolver.py
View File

@ -50,39 +50,51 @@ class StrategyResolver(IResolver):
if 'ask_strategy' not in config:
config['ask_strategy'] = {}
if hasattr(strategy, 'ticker_interval') and not hasattr(strategy, 'timeframe'):
# Assign ticker_interval to timeframe to keep compatibility
if 'timeframe' not in config:
logger.warning(
"DEPRECATED: Please migrate to using 'timeframe' instead of 'ticker_interval'."
)
strategy.timeframe = strategy.ticker_interval
# Set attributes
# Check if we need to override configuration
# (Attribute name, default, ask_strategy)
attributes = [("minimal_roi", {"0": 10.0}, False),
("ticker_interval", None, False),
("stoploss", None, False),
("trailing_stop", None, False),
("trailing_stop_positive", None, False),
("trailing_stop_positive_offset", 0.0, False),
("trailing_only_offset_is_reached", None, False),
("process_only_new_candles", None, False),
("order_types", None, False),
("order_time_in_force", None, False),
("stake_currency", None, False),
("stake_amount", None, False),
("startup_candle_count", None, False),
("unfilledtimeout", None, False),
("use_sell_signal", True, True),
("sell_profit_only", False, True),
("ignore_roi_if_buy_signal", False, True),
# (Attribute name, default, subkey)
attributes = [("minimal_roi", {"0": 10.0}, None),
("timeframe", None, None),
("stoploss", None, None),
("trailing_stop", None, None),
("trailing_stop_positive", None, None),
("trailing_stop_positive_offset", 0.0, None),
("trailing_only_offset_is_reached", None, None),
("process_only_new_candles", None, None),
("order_types", None, None),
("order_time_in_force", None, None),
("stake_currency", None, None),
("stake_amount", None, None),
("startup_candle_count", None, None),
("unfilledtimeout", None, None),
("use_sell_signal", True, 'ask_strategy'),
("sell_profit_only", False, 'ask_strategy'),
("ignore_roi_if_buy_signal", False, 'ask_strategy'),
("disable_dataframe_checks", False, None),
]
for attribute, default, ask_strategy in attributes:
if ask_strategy:
StrategyResolver._override_attribute_helper(strategy, config['ask_strategy'],
for attribute, default, subkey in attributes:
if subkey:
StrategyResolver._override_attribute_helper(strategy, config.get(subkey, {}),
attribute, default)
else:
StrategyResolver._override_attribute_helper(strategy, config,
attribute, default)
# Assign deprecated variable - to not break users code relying on this.
strategy.ticker_interval = strategy.timeframe
# Loop this list again to have output combined
for attribute, _, exp in attributes:
if exp and attribute in config['ask_strategy']:
logger.info("Strategy using %s: %s", attribute, config['ask_strategy'][attribute])
for attribute, _, subkey in attributes:
if subkey and attribute in config[subkey]:
logger.info("Strategy using %s: %s", attribute, config[subkey][attribute])
elif attribute in config:
logger.info("Strategy using %s: %s", attribute, config[attribute])

17
freqtrade/rpc/api_server.py
View File

@ -90,7 +90,9 @@ class ApiServer(RPC):
self._config = freqtrade.config
self.app = Flask(__name__)
self._cors = CORS(self.app,
resources={r"/api/*": {"supports_credentials": True, }}
resources={r"/api/*": {
"supports_credentials": True,
"origins": self._config['api_server'].get('CORS_origins', [])}}
)
# Setup the Flask-JWT-Extended extension
@ -172,8 +174,8 @@ class ApiServer(RPC):
self.app.add_url_rule(f'{BASE_URI}/stop', 'stop', view_func=self._stop, methods=['POST'])
self.app.add_url_rule(f'{BASE_URI}/stopbuy', 'stopbuy',
view_func=self._stopbuy, methods=['POST'])
self.app.add_url_rule(f'{BASE_URI}/reload_conf', 'reload_conf',
view_func=self._reload_conf, methods=['POST'])
self.app.add_url_rule(f'{BASE_URI}/reload_config', 'reload_config',
view_func=self._reload_config, methods=['POST'])
# Info commands
self.app.add_url_rule(f'{BASE_URI}/balance', 'balance',
view_func=self._balance, methods=['GET'])
@ -304,12 +306,12 @@ class ApiServer(RPC):
@require_login
@rpc_catch_errors
def _reload_conf(self):
def _reload_config(self):
"""
Handler for /reload_conf.
Handler for /reload_config.
Triggers a config file reload
"""
msg = self._rpc_reload_conf()
msg = self._rpc_reload_config()
return self.rest_dump(msg)
@require_login
@ -360,7 +362,6 @@ class ApiServer(RPC):
Returns a cumulative profit statistics
:return: stats
"""
logger.info("LocalRPC - Profit Command Called")
stats = self._rpc_trade_statistics(self._config['stake_currency'],
self._config.get('fiat_display_currency')
@ -377,8 +378,6 @@ class ApiServer(RPC):
Returns a cumulative performance statistics
:return: stats
"""
logger.info("LocalRPC - performance Command Called")
stats = self._rpc_performance()
return self.rest_dump(stats)

80
freqtrade/rpc/rpc.py
View File

@ -101,10 +101,13 @@ class RPC:
'trailing_stop_positive': config.get('trailing_stop_positive'),
'trailing_stop_positive_offset': config.get('trailing_stop_positive_offset'),
'trailing_only_offset_is_reached': config.get('trailing_only_offset_is_reached'),
'ticker_interval': config['ticker_interval'],
'ticker_interval': config['timeframe'], # DEPRECATED
'timeframe': config['timeframe'],
'exchange': config['exchange']['name'],
'strategy': config['strategy'],
'forcebuy_enabled': config.get('forcebuy_enable', False),
'ask_strategy': config.get('ask_strategy', {}),
'bid_strategy': config.get('bid_strategy', {}),
'state': str(self._freqtrade.state)
}
return val
@ -130,6 +133,14 @@ class RPC:
except DependencyException:
current_rate = NAN
current_profit = trade.calc_profit_ratio(current_rate)
current_profit_abs = trade.calc_profit(current_rate)
# Calculate guaranteed profit (in case of trailing stop)
stoploss_entry_dist = trade.calc_profit(trade.stop_loss)
stoploss_entry_dist_ratio = trade.calc_profit_ratio(trade.stop_loss)
# calculate distance to stoploss
stoploss_current_dist = trade.stop_loss - current_rate
stoploss_current_dist_ratio = stoploss_current_dist / current_rate
fmt_close_profit = (f'{round(trade.close_profit * 100, 2):.2f}%'
if trade.close_profit is not None else None)
trade_dict = trade.to_json()
@ -140,6 +151,11 @@ class RPC:
current_rate=current_rate,
current_profit=current_profit,
current_profit_pct=round(current_profit * 100, 2),
current_profit_abs=current_profit_abs,
stoploss_current_dist=stoploss_current_dist,
stoploss_current_dist_ratio=round(stoploss_current_dist_ratio, 8),
stoploss_entry_dist=stoploss_entry_dist,
stoploss_entry_dist_ratio=round(stoploss_entry_dist_ratio, 8),
open_order='({} {} rem={:.8f})'.format(
order['type'], order['side'], order['remaining']
) if order else None,
@ -281,15 +297,11 @@ class RPC:
best_pair = Trade.get_best_pair()
if not best_pair:
raise RPCException('no closed trade')
bp_pair, bp_rate = best_pair
# Prepare data to display
profit_closed_coin_sum = round(sum(profit_closed_coin), 8)
profit_closed_percent = (round(mean(profit_closed_ratio) * 100, 2) if profit_closed_ratio
else 0.0)
profit_closed_ratio_mean = mean(profit_closed_ratio) if profit_closed_ratio else 0.0
profit_closed_ratio_sum = sum(profit_closed_ratio) if profit_closed_ratio else 0.0
profit_closed_fiat = self._fiat_converter.convert_amount(
profit_closed_coin_sum,
stake_currency,
@ -297,29 +309,41 @@ class RPC:
) if self._fiat_converter else 0
profit_all_coin_sum = round(sum(profit_all_coin), 8)
profit_all_percent = round(mean(profit_all_ratio) * 100, 2) if profit_all_ratio else 0.0
profit_all_ratio_mean = mean(profit_all_ratio) if profit_all_ratio else 0.0
profit_all_ratio_sum = sum(profit_all_ratio) if profit_all_ratio else 0.0
profit_all_fiat = self._fiat_converter.convert_amount(
profit_all_coin_sum,
stake_currency,
fiat_display_currency
) if self._fiat_converter else 0
first_date = trades[0].open_date if trades else None
last_date = trades[-1].open_date if trades else None
num = float(len(durations) or 1)
return {
'profit_closed_coin': profit_closed_coin_sum,
'profit_closed_percent': profit_closed_percent,
'profit_closed_percent': round(profit_closed_ratio_mean * 100, 2), # DEPRECATED
'profit_closed_percent_mean': round(profit_closed_ratio_mean * 100, 2),
'profit_closed_ratio_mean': profit_closed_ratio_mean,
'profit_closed_percent_sum': round(profit_closed_ratio_sum * 100, 2),
'profit_closed_ratio_sum': profit_closed_ratio_sum,
'profit_closed_fiat': profit_closed_fiat,
'profit_all_coin': profit_all_coin_sum,
'profit_all_percent': profit_all_percent,
'profit_all_percent': round(profit_all_ratio_mean * 100, 2), # DEPRECATED
'profit_all_percent_mean': round(profit_all_ratio_mean * 100, 2),
'profit_all_ratio_mean': profit_all_ratio_mean,
'profit_all_percent_sum': round(profit_all_ratio_sum * 100, 2),
'profit_all_ratio_sum': profit_all_ratio_sum,
'profit_all_fiat': profit_all_fiat,
'trade_count': len(trades),
'first_trade_date': arrow.get(trades[0].open_date).humanize(),
'first_trade_timestamp': int(trades[0].open_date.timestamp() * 1000),
'latest_trade_date': arrow.get(trades[-1].open_date).humanize(),
'latest_trade_timestamp': int(trades[-1].open_date.timestamp() * 1000),
'closed_trade_count': len([t for t in trades if not t.is_open]),
'first_trade_date': arrow.get(first_date).humanize() if first_date else '',
'first_trade_timestamp': int(first_date.timestamp() * 1000) if first_date else 0,
'latest_trade_date': arrow.get(last_date).humanize() if last_date else '',
'latest_trade_timestamp': int(last_date.timestamp() * 1000) if last_date else 0,
'avg_duration': str(timedelta(seconds=sum(durations) / num)).split('.')[0],
'best_pair': bp_pair,
'best_rate': round(bp_rate * 100, 2),
'best_pair': best_pair[0] if best_pair else '',
'best_rate': round(best_pair[1] * 100, 2) if best_pair else 0,
}
def _rpc_balance(self, stake_currency: str, fiat_display_currency: str) -> Dict:
@ -395,9 +419,9 @@ class RPC:
return {'status': 'already stopped'}
def _rpc_reload_conf(self) -> Dict[str, str]:
""" Handler for reload_conf. """
self._freqtrade.state = State.RELOAD_CONF
def _rpc_reload_config(self) -> Dict[str, str]:
""" Handler for reload_config. """
self._freqtrade.state = State.RELOAD_CONFIG
return {'status': 'reloading config ...'}
def _rpc_stopbuy(self) -> Dict[str, str]:
@ -408,7 +432,7 @@ class RPC:
# Set 'max_open_trades' to 0
self._freqtrade.config['max_open_trades'] = 0
return {'status': 'No more buy will occur from now. Run /reload_conf to reset.'}
return {'status': 'No more buy will occur from now. Run /reload_config to reset.'}
def _rpc_forcesell(self, trade_id: str) -> Dict[str, str]:
"""
@ -533,16 +557,26 @@ class RPC:
def _rpc_blacklist(self, add: List[str] = None) -> Dict:
""" Returns the currently active blacklist"""
errors = {}
if add:
stake_currency = self._freqtrade.config.get('stake_currency')
for pair in add:
if (self._freqtrade.exchange.get_pair_quote_currency(pair) == stake_currency
and pair not in self._freqtrade.pairlists.blacklist):
if self._freqtrade.exchange.get_pair_quote_currency(pair) == stake_currency:
if pair not in self._freqtrade.pairlists.blacklist:
self._freqtrade.pairlists.blacklist.append(pair)
else:
errors[pair] = {
'error_msg': f'Pair {pair} already in pairlist.'}
else:
errors[pair] = {
'error_msg': f"Pair {pair} does not match stake currency."
}
res = {'method': self._freqtrade.pairlists.name_list,
'length': len(self._freqtrade.pairlists.blacklist),
'blacklist': self._freqtrade.pairlists.blacklist,
'errors': errors,
}
return res

4
freqtrade/rpc/rpc_manager.py
View File

@ -72,7 +72,7 @@ class RPCManager:
minimal_roi = config['minimal_roi']
stoploss = config['stoploss']
trailing_stop = config['trailing_stop']
ticker_interval = config['ticker_interval']
timeframe = config['timeframe']
exchange_name = config['exchange']['name']
strategy_name = config.get('strategy', '')
self.send_msg({
@ -81,7 +81,7 @@ class RPCManager:
f'*Stake per trade:* `{stake_amount} {stake_currency}`\n'
f'*Minimum ROI:* `{minimal_roi}`\n'
f'*{"Trailing " if trailing_stop else ""}Stoploss:* `{stoploss}`\n'
f'*Ticker Interval:* `{ticker_interval}`\n'
f'*Timeframe:* `{timeframe}`\n'
f'*Strategy:* `{strategy_name}`'
})
self.send_msg({

161
freqtrade/rpc/telegram.py
View File

@ -3,6 +3,7 @@
"""
This module manage Telegram communication
"""
import json
import logging
from typing import Any, Callable, Dict
@ -19,7 +20,6 @@ logger = logging.getLogger(__name__)
logger.debug('Included module rpc.telegram ...')
MAX_TELEGRAM_MESSAGE_LENGTH = 4096
@ -29,6 +29,7 @@ def authorized_only(command_handler: Callable[..., None]) -> Callable[..., Any]:
:param command_handler: Telegram CommandHandler
:return: decorated function
"""
def wrapper(self, *args, **kwargs):
""" Decorator logic """
update = kwargs.get('update') or args[0]
@ -94,8 +95,8 @@ class Telegram(RPC):
CommandHandler('performance', self._performance),
CommandHandler('daily', self._daily),
CommandHandler('count', self._count),
CommandHandler('reload_conf', self._reload_conf),
CommandHandler('show_config', self._show_config),
CommandHandler(['reload_config', 'reload_conf'], self._reload_config),
CommandHandler(['show_config', 'show_conf'], self._show_config),
CommandHandler('stopbuy', self._stopbuy),
CommandHandler('whitelist', self._whitelist),
CommandHandler('blacklist', self._blacklist),
@ -133,7 +134,7 @@ class Telegram(RPC):
else:
msg['stake_amount_fiat'] = 0
message = ("*{exchange}:* Buying {pair}\n"
message = ("\N{LARGE BLUE CIRCLE} *{exchange}:* Buying {pair}\n"
"*Amount:* `{amount:.8f}`\n"
"*Open Rate:* `{limit:.8f}`\n"
"*Current Rate:* `{current_rate:.8f}`\n"
@ -144,7 +145,8 @@ class Telegram(RPC):
message += ")`"
elif msg['type'] == RPCMessageType.BUY_CANCEL_NOTIFICATION:
message = "*{exchange}:* Cancelling Open Buy Order for {pair}".format(**msg)
message = ("\N{WARNING SIGN} *{exchange}:* "
"Cancelling Open Buy Order for {pair}".format(**msg))
elif msg['type'] == RPCMessageType.SELL_NOTIFICATION:
msg['amount'] = round(msg['amount'], 8)
@ -153,7 +155,9 @@ class Telegram(RPC):
microsecond=0) - msg['open_date'].replace(microsecond=0)
msg['duration_min'] = msg['duration'].total_seconds() / 60
message = ("*{exchange}:* Selling {pair}\n"
msg['emoji'] = self._get_sell_emoji(msg)
message = ("{emoji} *{exchange}:* Selling {pair}\n"
"*Amount:* `{amount:.8f}`\n"
"*Open Rate:* `{open_rate:.8f}`\n"
"*Current Rate:* `{current_rate:.8f}`\n"
@ -172,14 +176,14 @@ class Telegram(RPC):
' / {profit_fiat:.3f} {fiat_currency})`').format(**msg)
elif msg['type'] == RPCMessageType.SELL_CANCEL_NOTIFICATION:
message = ("*{exchange}:* Cancelling Open Sell Order "
message = ("\N{WARNING SIGN} *{exchange}:* Cancelling Open Sell Order "
"for {pair}. Reason: {reason}").format(**msg)
elif msg['type'] == RPCMessageType.STATUS_NOTIFICATION:
message = '*Status:* `{status}`'.format(**msg)
elif msg['type'] == RPCMessageType.WARNING_NOTIFICATION:
message = '*Warning:* `{status}`'.format(**msg)
message = '\N{WARNING SIGN} *Warning:* `{status}`'.format(**msg)
elif msg['type'] == RPCMessageType.CUSTOM_NOTIFICATION:
message = '{status}'.format(**msg)
@ -189,6 +193,20 @@ class Telegram(RPC):
self._send_msg(message)
def _get_sell_emoji(self, msg):
"""
Get emoji for sell-side
"""
if float(msg['profit_percent']) >= 5.0:
return "\N{ROCKET}"
elif float(msg['profit_percent']) >= 0.0:
return "\N{EIGHT SPOKED ASTERISK}"
elif msg['sell_reason'] == "stop_loss":
return"\N{WARNING SIGN}"
else:
return "\N{CROSS MARK}"
@authorized_only
def _status(self, update: Update, context: CallbackContext) -> None:
"""
@ -311,15 +329,16 @@ class Telegram(RPC):
stake_cur = self._config['stake_currency']
fiat_disp_cur = self._config.get('fiat_display_currency', '')
try:
stats = self._rpc_trade_statistics(
stake_cur,
fiat_disp_cur)
profit_closed_coin = stats['profit_closed_coin']
profit_closed_percent = stats['profit_closed_percent']
profit_closed_percent_mean = stats['profit_closed_percent_mean']
profit_closed_percent_sum = stats['profit_closed_percent_sum']
profit_closed_fiat = stats['profit_closed_fiat']
profit_all_coin = stats['profit_all_coin']
profit_all_percent = stats['profit_all_percent']
profit_all_percent_mean = stats['profit_all_percent_mean']
profit_all_percent_sum = stats['profit_all_percent_sum']
profit_all_fiat = stats['profit_all_fiat']
trade_count = stats['trade_count']
first_trade_date = stats['first_trade_date']
@ -327,22 +346,31 @@ class Telegram(RPC):
avg_duration = stats['avg_duration']
best_pair = stats['best_pair']
best_rate = stats['best_rate']
if stats['trade_count'] == 0:
markdown_msg = 'No trades yet.'
else:
# Message to display
markdown_msg = "*ROI:* Close trades\n" \
f"∙ `{profit_closed_coin:.8f} {stake_cur} "\
f"({profit_closed_percent:.2f}%)`\n" \
f"∙ `{profit_closed_fiat:.3f} {fiat_disp_cur}`\n" \
f"*ROI:* All trades\n" \
f"∙ `{profit_all_coin:.8f} {stake_cur} ({profit_all_percent:.2f}%)`\n" \
f"∙ `{profit_all_fiat:.3f} {fiat_disp_cur}`\n" \
f"*Total Trade Count:* `{trade_count}`\n" \
f"*First Trade opened:* `{first_trade_date}`\n" \
f"*Latest Trade opened:* `{latest_trade_date}`\n" \
f"*Avg. Duration:* `{avg_duration}`\n" \
f"*Best Performing:* `{best_pair}: {best_rate:.2f}%`"
if stats['closed_trade_count'] > 0:
markdown_msg = ("*ROI:* Closed trades\n"
f"∙ `{profit_closed_coin:.8f} {stake_cur} "
f"({profit_closed_percent_mean:.2f}%) "
f"({profit_closed_percent_sum} \N{GREEK CAPITAL LETTER SIGMA}%)`\n"
f"∙ `{profit_closed_fiat:.3f} {fiat_disp_cur}`\n")
else:
markdown_msg = "`No closed trade` \n"
markdown_msg += (f"*ROI:* All trades\n"
f"∙ `{profit_all_coin:.8f} {stake_cur} "
f"({profit_all_percent_mean:.2f}%) "
f"({profit_all_percent_sum} \N{GREEK CAPITAL LETTER SIGMA}%)`\n"
f"∙ `{profit_all_fiat:.3f} {fiat_disp_cur}`\n"
f"*Total Trade Count:* `{trade_count}`\n"
f"*First Trade opened:* `{first_trade_date}`\n"
f"*Latest Trade opened:* `{latest_trade_date}`")
if stats['closed_trade_count'] > 0:
markdown_msg += (f"\n*Avg. Duration:* `{avg_duration}`\n"
f"*Best Performing:* `{best_pair}: {best_rate:.2f}%`")
self._send_msg(markdown_msg)
except RPCException as e:
self._send_msg(str(e))
@authorized_only
def _balance(self, update: Update, context: CallbackContext) -> None:
@ -361,11 +389,11 @@ class Telegram(RPC):
)
for currency in result['currencies']:
if currency['est_stake'] > 0.0001:
curr_output = "*{currency}:*\n" \
"\t`Available: {free: .8f}`\n" \
"\t`Balance: {balance: .8f}`\n" \
"\t`Pending: {used: .8f}`\n" \
"\t`Est. {stake}: {est_stake: .8f}`\n".format(**currency)
curr_output = ("*{currency}:*\n"
"\t`Available: {free: .8f}`\n"
"\t`Balance: {balance: .8f}`\n"
"\t`Pending: {used: .8f}`\n"
"\t`Est. {stake}: {est_stake: .8f}`\n").format(**currency)
else:
curr_output = "*{currency}:* not showing <1$ amount \n".format(**currency)
@ -376,9 +404,9 @@ class Telegram(RPC):
else:
output += curr_output
output += "\n*Estimated Value*:\n" \
"\t`{stake}: {total: .8f}`\n" \
"\t`{symbol}: {value: .2f}`\n".format(**result)
output += ("\n*Estimated Value*:\n"
"\t`{stake}: {total: .8f}`\n"
"\t`{symbol}: {value: .2f}`\n").format(**result)
self._send_msg(output)
except RPCException as e:
self._send_msg(str(e))
@ -408,15 +436,15 @@ class Telegram(RPC):
self._send_msg('Status: `{status}`'.format(**msg))
@authorized_only
def _reload_conf(self, update: Update, context: CallbackContext) -> None:
def _reload_config(self, update: Update, context: CallbackContext) -> None:
"""
Handler for /reload_conf.
Handler for /reload_config.
Triggers a config file reload
:param bot: telegram bot
:param update: message update
:return: None
"""
msg = self._rpc_reload_conf()
msg = self._rpc_reload_config()
self._send_msg('Status: `{status}`'.format(**msg))
@authorized_only
@ -534,6 +562,11 @@ class Telegram(RPC):
try:
blacklist = self._rpc_blacklist(context.args)
errmsgs = []
for pair, error in blacklist['errors'].items():
errmsgs.append(f"Error adding `{pair}` to blacklist: `{error['error_msg']}`")
if errmsgs:
self._send_msg('\n'.join(errmsgs))
message = f"Blacklist contains {blacklist['length']} pairs\n"
message += f"`{', '.join(blacklist['blacklist'])}`"
@ -566,32 +599,32 @@ class Telegram(RPC):
:param update: message update
:return: None
"""
forcebuy_text = "*/forcebuy <pair> [<rate>]:* `Instantly buys the given pair. " \
"Optionally takes a rate at which to buy.` \n"
message = "*/start:* `Starts the trader`\n" \
"*/stop:* `Stops the trader`\n" \
"*/status [table]:* `Lists all open trades`\n" \
" *table :* `will display trades in a table`\n" \
" `pending buy orders are marked with an asterisk (*)`\n" \
" `pending sell orders are marked with a double asterisk (**)`\n" \
"*/profit:* `Lists cumulative profit from all finished trades`\n" \
"*/forcesell <trade_id>|all:* `Instantly sells the given trade or all trades, " \
"regardless of profit`\n" \
f"{forcebuy_text if self._config.get('forcebuy_enable', False) else '' }" \
"*/performance:* `Show performance of each finished trade grouped by pair`\n" \
"*/daily <n>:* `Shows profit or loss per day, over the last n days`\n" \
"*/count:* `Show number of trades running compared to allowed number of trades`" \
"\n" \
"*/balance:* `Show account balance per currency`\n" \
"*/stopbuy:* `Stops buying, but handles open trades gracefully` \n" \
"*/reload_conf:* `Reload configuration file` \n" \
"*/show_config:* `Show running configuration` \n" \
"*/whitelist:* `Show current whitelist` \n" \
"*/blacklist [pair]:* `Show current blacklist, or adds one or more pairs " \
"to the blacklist.` \n" \
"*/edge:* `Shows validated pairs by Edge if it is enabled` \n" \
"*/help:* `This help message`\n" \
"*/version:* `Show version`"
forcebuy_text = ("*/forcebuy <pair> [<rate>]:* `Instantly buys the given pair. "
"Optionally takes a rate at which to buy.` \n")
message = ("*/start:* `Starts the trader`\n"
"*/stop:* `Stops the trader`\n"
"*/status [table]:* `Lists all open trades`\n"
" *table :* `will display trades in a table`\n"
" `pending buy orders are marked with an asterisk (*)`\n"
" `pending sell orders are marked with a double asterisk (**)`\n"
"*/profit:* `Lists cumulative profit from all finished trades`\n"
"*/forcesell <trade_id>|all:* `Instantly sells the given trade or all trades, "
"regardless of profit`\n"
f"{forcebuy_text if self._config.get('forcebuy_enable', False) else ''}"
"*/performance:* `Show performance of each finished trade grouped by pair`\n"
"*/daily <n>:* `Shows profit or loss per day, over the last n days`\n"
"*/count:* `Show number of trades running compared to allowed number of trades`"
"\n"
"*/balance:* `Show account balance per currency`\n"
"*/stopbuy:* `Stops buying, but handles open trades gracefully` \n"
"*/reload_config:* `Reload configuration file` \n"
"*/show_config:* `Show running configuration` \n"
"*/whitelist:* `Show current whitelist` \n"
"*/blacklist [pair]:* `Show current blacklist, or adds one or more pairs "
"to the blacklist.` \n"
"*/edge:* `Shows validated pairs by Edge if it is enabled` \n"
"*/help:* `This help message`\n"
"*/version:* `Show version`")
self._send_msg(message)
@ -633,8 +666,10 @@ class Telegram(RPC):
f"*Stake per trade:* `{val['stake_amount']} {val['stake_currency']}`\n"
f"*Max open Trades:* `{val['max_open_trades']}`\n"
f"*Minimum ROI:* `{val['minimal_roi']}`\n"
f"*Ask strategy:* ```\n{json.dumps(val['ask_strategy'])}```\n"
f"*Bid strategy:* ```\n{json.dumps(val['bid_strategy'])}```\n"
f"{sl_info}"
f"*Ticker Interval:* `{val['ticker_interval']}`\n"
f"*Timeframe:* `{val['timeframe']}`\n"
f"*Strategy:* `{val['strategy']}`\n"
f"*Current state:* `{val['state']}`"
)

2
freqtrade/state.py
View File

@ -12,7 +12,7 @@ class State(Enum):
"""
RUNNING = 1
STOPPED = 2
RELOAD_CONF = 3
RELOAD_CONFIG = 3
def __str__(self):
return f"{self.name.lower()}"

16
freqtrade/strategy/interface.py
View File

@ -62,7 +62,7 @@ class IStrategy(ABC):
Attributes you can use:
minimal_roi -> Dict: Minimal ROI designed for the strategy
stoploss -> float: optimal stoploss designed for the strategy
ticker_interval -> str: value of the timeframe (ticker interval) to use with the strategy
timeframe -> str: value of the timeframe (ticker interval) to use with the strategy
"""
# Strategy interface version
# Default to version 2
@ -85,8 +85,9 @@ class IStrategy(ABC):
trailing_stop_positive_offset: float = 0.0
trailing_only_offset_is_reached = False
# associated ticker interval
ticker_interval: str
# associated timeframe
ticker_interval: str # DEPRECATED
timeframe: str
# Optional order types
order_types: Dict = {
@ -106,6 +107,9 @@ class IStrategy(ABC):
# run "populate_indicators" only for new candle
process_only_new_candles: bool = False
# Disable checking the dataframe (converts the error into a warning message)
disable_dataframe_checks: bool = False
# Count of candles the strategy requires before producing valid signals
startup_candle_count: int = 0
@ -285,8 +289,7 @@ class IStrategy(ABC):
""" keep some data for dataframes """
return len(dataframe), dataframe["close"].iloc[-1], dataframe["date"].iloc[-1]
@staticmethod
def assert_df(dataframe: DataFrame, df_len: int, df_close: float, df_date: datetime):
def assert_df(self, dataframe: DataFrame, df_len: int, df_close: float, df_date: datetime):
""" make sure data is unmodified """
message = ""
if df_len != len(dataframe):
@ -296,6 +299,9 @@ class IStrategy(ABC):
elif df_date != dataframe["date"].iloc[-1]:
message = "last date"
if message:
if self.disable_dataframe_checks:
logger.warning(f"Dataframe returned from strategy has mismatching {message}.")
else:
raise StrategyError(f"Dataframe returned from strategy has mismatching {message}.")
def get_signal(self, pair: str, interval: str, dataframe: DataFrame) -> Tuple[bool, bool]:

12
freqtrade/templates/base_config.json.j2
View File

@ -4,7 +4,7 @@
"stake_amount": {{ stake_amount }},
"tradable_balance_ratio": 0.99,
"fiat_display_currency": "{{ fiat_display_currency }}",
"ticker_interval": "{{ ticker_interval }}",
"timeframe": "{{ timeframe }}",
"dry_run": {{ dry_run | lower }},
"cancel_open_orders_on_exit": false,
"unfilledtimeout": {
@ -53,6 +53,16 @@
"token": "{{ telegram_token }}",
"chat_id": "{{ telegram_chat_id }}"
},
"api_server": {
"enabled": false,
"listen_ip_address": "127.0.0.1",
"listen_port": 8080,
"verbosity": "info",
"jwt_secret_key": "somethingrandom",
"CORS_origins": [],
"username": "",
"password": ""
},
"initial_state": "running",
"forcebuy_enable": false,
"internals": {

4
freqtrade/templates/base_strategy.py.j2
View File

@ -51,8 +51,8 @@ class {{ strategy }}(IStrategy):
# trailing_stop_positive = 0.01
# trailing_stop_positive_offset = 0.0 # Disabled / not configured
# Optimal ticker interval for the strategy.
ticker_interval = '5m'
# Optimal timeframe for the strategy.
timeframe = '5m'
# Run "populate_indicators()" only for new candle.
process_only_new_candles = False

2
freqtrade/templates/sample_strategy.py
View File

@ -53,7 +53,7 @@ class SampleStrategy(IStrategy):
# trailing_stop_positive_offset = 0.0 # Disabled / not configured
# Optimal ticker interval for the strategy.
ticker_interval = '5m'
timeframe = '5m'
# Run "populate_indicators()" only for new candle.
process_only_new_candles = False

2
freqtrade/worker.py
View File

@ -71,7 +71,7 @@ class Worker:
state = None
while True:
state = self._worker(old_state=state)
if state == State.RELOAD_CONF:
if state == State.RELOAD_CONFIG:
self._reconfigure()
def _worker(self, old_state: Optional[State]) -> State:

12
requirements-common.txt
View File

@ -1,11 +1,11 @@
# requirements without requirements installable via conda
# mainly used for Raspberry pi installs
ccxt==1.28.49
SQLAlchemy==1.3.17
python-telegram-bot==12.7
arrow==0.15.6
cachetools==4.1.0
requests==2.23.0
ccxt==1.30.48
SQLAlchemy==1.3.18
python-telegram-bot==12.8
arrow==0.15.7
cachetools==4.1.1
requests==2.24.0
urllib3==1.25.9
wrapt==1.12.1
jsonschema==3.2.0

12
requirements-dev.txt
View File

@ -4,14 +4,14 @@
-r requirements-hyperopt.txt
coveralls==2.0.0
flake8==3.8.2
flake8==3.8.3
flake8-type-annotations==0.1.0
flake8-tidy-imports==4.1.0
mypy==0.770
pytest==5.4.2
pytest-asyncio==0.12.0
pytest-cov==2.9.0
pytest-mock==3.1.0
mypy==0.782
pytest==5.4.3
pytest-asyncio==0.14.0
pytest-cov==2.10.0
pytest-mock==3.1.1
pytest-random-order==1.0.4
# Convert jupyter notebooks to markdown documents

4
requirements-hyperopt.txt
View File

@ -2,9 +2,9 @@
-r requirements.txt
# Required for hyperopt
scipy==1.4.1
scipy==1.5.0
scikit-learn==0.23.1
scikit-optimize==0.7.4
filelock==3.0.12
joblib==0.15.1
progressbar2==3.51.3
progressbar2==3.51.4

2
requirements-plot.txt
View File

@ -1,5 +1,5 @@
# Include all requirements to run the bot.
-r requirements.txt
plotly==4.7.1
plotly==4.8.2

4
requirements.txt
View File

@ -1,5 +1,5 @@
# Load common requirements
-r requirements-common.txt
numpy==1.18.4
pandas==1.0.4
numpy==1.19.0
pandas==1.0.5

6
scripts/rest_client.py
View File

@ -80,18 +80,18 @@ class FtRestClient():
return self._post("stop")
def stopbuy(self):
"""Stop buying (but handle sells gracefully). Use `reload_conf` to reset.
"""Stop buying (but handle sells gracefully). Use `reload_config` to reset.
:return: json object
"""
return self._post("stopbuy")
def reload_conf(self):
def reload_config(self):
"""Reload configuration.
:return: json object
"""
return self._post("reload_conf")
return self._post("reload_config")
def balance(self):
"""Get the account balance.

2
setup.py
View File

@ -63,7 +63,7 @@ setup(name='freqtrade',
tests_require=['pytest', 'pytest-asyncio', 'pytest-cov', 'pytest-mock', ],
install_requires=[
# from requirements-common.txt
'ccxt>=1.18.1080',
'ccxt>=1.24.96',
'SQLAlchemy',
'python-telegram-bot',
'arrow',

4
tests/commands/test_build_config.py
View File

@ -44,7 +44,7 @@ def test_start_new_config(mocker, caplog, exchange):
'stake_currency': 'USDT',
'stake_amount': 100,
'fiat_display_currency': 'EUR',
'ticker_interval': '15m',
'timeframe': '15m',
'dry_run': True,
'exchange_name': exchange,
'exchange_key': 'sampleKey',
@ -68,7 +68,7 @@ def test_start_new_config(mocker, caplog, exchange):
result = rapidjson.loads(wt_mock.call_args_list[0][0][0],
parse_mode=rapidjson.PM_COMMENTS | rapidjson.PM_TRAILING_COMMAS)
assert result['exchange']['name'] == exchange
assert result['ticker_interval'] == '15m'
assert result['timeframe'] == '15m'
def test_start_new_config_exists(mocker, caplog):

3
tests/config_test_comments.json
View File

@ -9,7 +9,7 @@
"fiat_display_currency": "USD", // C++-style comment
"amount_reserve_percent" : 0.05, // And more, tabs before this comment
"dry_run": false,
"ticker_interval": "5m",
"timeframe": "5m",
"trailing_stop": false,
"trailing_stop_positive": 0.005,
"trailing_stop_positive_offset": 0.0051,
@ -92,7 +92,6 @@
"enabled": false,
"process_throttle_secs": 3600,
"calculate_since_number_of_days": 7,
"capital_available_percentage": 0.5,
"allowed_risk": 0.01,
"stoploss_range_min": -0.01,
"stoploss_range_max": -0.1,

6
tests/conftest.py
View File

@ -56,6 +56,7 @@ def patched_configuration_load_config_file(mocker, config) -> None:
def patch_exchange(mocker, api_mock=None, id='bittrex', mock_markets=True) -> None:
mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock(return_value={}))
mocker.patch('freqtrade.exchange.Exchange._load_markets', MagicMock(return_value={}))
mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
@ -247,7 +248,7 @@ def default_conf(testdatadir):
"stake_currency": "BTC",
"stake_amount": 0.001,
"fiat_display_currency": "USD",
"ticker_interval": '5m',
"timeframe": '5m',
"dry_run": True,
"cancel_open_orders_on_exit": False,
"minimal_roi": {
@ -1423,7 +1424,7 @@ def trades_for_order():
@pytest.fixture(scope="function")
def trades_history():
return [[1565798399463, '126181329', None, 'buy', 0.019627, 0.04, 0.00078508],
return [[1565798389463, '126181329', None, 'buy', 0.019627, 0.04, 0.00078508],
[1565798399629, '126181330', None, 'buy', 0.019627, 0.244, 0.004788987999999999],
[1565798399752, '126181331', None, 'sell', 0.019626, 0.011, 0.00021588599999999999],
[1565798399862, '126181332', None, 'sell', 0.019626, 0.011, 0.00021588599999999999],
@ -1590,6 +1591,7 @@ def buy_order_fee():
'datetime': str(arrow.utcnow().shift(minutes=-601).datetime),
'price': 0.245441,
'amount': 8.0,
'cost': 1.963528,
'remaining': 90.99181073,
'status': 'closed',
'fee': None

2
tests/data/test_btanalysis.py
View File

@ -47,7 +47,7 @@ def test_load_trades_from_db(default_conf, fee, mocker):
assert isinstance(trades, DataFrame)
assert "pair" in trades.columns
assert "open_time" in trades.columns
assert "profitperc" in trades.columns
assert "profit_percent" in trades.columns
for col in BT_DATA_COLUMNS:
if col not in ['index', 'open_at_end']:

42
tests/data/test_dataprovider.py
View File

@ -12,7 +12,7 @@ from tests.conftest import get_patched_exchange
def test_ohlcv(mocker, default_conf, ohlcv_history):
default_conf["runmode"] = RunMode.DRY_RUN
timeframe = default_conf["ticker_interval"]
timeframe = default_conf["timeframe"]
exchange = get_patched_exchange(mocker, default_conf)
exchange._klines[("XRP/BTC", timeframe)] = ohlcv_history
exchange._klines[("UNITTEST/BTC", timeframe)] = ohlcv_history
@ -53,47 +53,47 @@ def test_historic_ohlcv(mocker, default_conf, ohlcv_history):
def test_get_pair_dataframe(mocker, default_conf, ohlcv_history):
default_conf["runmode"] = RunMode.DRY_RUN
ticker_interval = default_conf["ticker_interval"]
timeframe = default_conf["timeframe"]
exchange = get_patched_exchange(mocker, default_conf)
exchange._klines[("XRP/BTC", ticker_interval)] = ohlcv_history
exchange._klines[("UNITTEST/BTC", ticker_interval)] = ohlcv_history
exchange._klines[("XRP/BTC", timeframe)] = ohlcv_history
exchange._klines[("UNITTEST/BTC", timeframe)] = ohlcv_history
dp = DataProvider(default_conf, exchange)
assert dp.runmode == RunMode.DRY_RUN
assert ohlcv_history.equals(dp.get_pair_dataframe("UNITTEST/BTC", ticker_interval))
assert isinstance(dp.get_pair_dataframe("UNITTEST/BTC", ticker_interval), DataFrame)
assert dp.get_pair_dataframe("UNITTEST/BTC", ticker_interval) is not ohlcv_history
assert not dp.get_pair_dataframe("UNITTEST/BTC", ticker_interval).empty
assert dp.get_pair_dataframe("NONESENSE/AAA", ticker_interval).empty
assert ohlcv_history.equals(dp.get_pair_dataframe("UNITTEST/BTC", timeframe))
assert isinstance(dp.get_pair_dataframe("UNITTEST/BTC", timeframe), DataFrame)
assert dp.get_pair_dataframe("UNITTEST/BTC", timeframe) is not ohlcv_history
assert not dp.get_pair_dataframe("UNITTEST/BTC", timeframe).empty
assert dp.get_pair_dataframe("NONESENSE/AAA", timeframe).empty
# Test with and without parameter
assert dp.get_pair_dataframe("UNITTEST/BTC", ticker_interval)\
assert dp.get_pair_dataframe("UNITTEST/BTC", timeframe)\
.equals(dp.get_pair_dataframe("UNITTEST/BTC"))
default_conf["runmode"] = RunMode.LIVE
dp = DataProvider(default_conf, exchange)
assert dp.runmode == RunMode.LIVE
assert isinstance(dp.get_pair_dataframe("UNITTEST/BTC", ticker_interval), DataFrame)
assert dp.get_pair_dataframe("NONESENSE/AAA", ticker_interval).empty
assert isinstance(dp.get_pair_dataframe("UNITTEST/BTC", timeframe), DataFrame)
assert dp.get_pair_dataframe("NONESENSE/AAA", timeframe).empty
historymock = MagicMock(return_value=ohlcv_history)
mocker.patch("freqtrade.data.dataprovider.load_pair_history", historymock)
default_conf["runmode"] = RunMode.BACKTEST
dp = DataProvider(default_conf, exchange)
assert dp.runmode == RunMode.BACKTEST
assert isinstance(dp.get_pair_dataframe("UNITTEST/BTC", ticker_interval), DataFrame)
# assert dp.get_pair_dataframe("NONESENSE/AAA", ticker_interval).empty
assert isinstance(dp.get_pair_dataframe("UNITTEST/BTC", timeframe), DataFrame)
# assert dp.get_pair_dataframe("NONESENSE/AAA", timeframe).empty
def test_available_pairs(mocker, default_conf, ohlcv_history):
exchange = get_patched_exchange(mocker, default_conf)
ticker_interval = default_conf["ticker_interval"]
exchange._klines[("XRP/BTC", ticker_interval)] = ohlcv_history
exchange._klines[("UNITTEST/BTC", ticker_interval)] = ohlcv_history
timeframe = default_conf["timeframe"]
exchange._klines[("XRP/BTC", timeframe)] = ohlcv_history
exchange._klines[("UNITTEST/BTC", timeframe)] = ohlcv_history
dp = DataProvider(default_conf, exchange)
assert len(dp.available_pairs) == 2
assert dp.available_pairs == [("XRP/BTC", ticker_interval), ("UNITTEST/BTC", ticker_interval), ]
assert dp.available_pairs == [("XRP/BTC", timeframe), ("UNITTEST/BTC", timeframe), ]
def test_refresh(mocker, default_conf, ohlcv_history):
@ -101,10 +101,10 @@ def test_refresh(mocker, default_conf, ohlcv_history):
mocker.patch("freqtrade.exchange.Exchange.refresh_latest_ohlcv", refresh_mock)
exchange = get_patched_exchange(mocker, default_conf, id="binance")
ticker_interval = default_conf["ticker_interval"]
pairs = [("XRP/BTC", ticker_interval), ("UNITTEST/BTC", ticker_interval)]
timeframe = default_conf["timeframe"]
pairs = [("XRP/BTC", timeframe), ("UNITTEST/BTC", timeframe)]
pairs_non_trad = [("ETH/USDT", ticker_interval), ("BTC/TUSD", "1h")]
pairs_non_trad = [("ETH/USDT", timeframe), ("BTC/TUSD", "1h")]
dp = DataProvider(default_conf, exchange)
dp.refresh(pairs)

28
tests/data/test_history.py
View File

@ -354,7 +354,7 @@ def test_init(default_conf, mocker) -> None:
assert {} == load_data(
datadir=Path(''),
pairs=[],
timeframe=default_conf['ticker_interval']
timeframe=default_conf['timeframe']
)
@ -363,13 +363,13 @@ def test_init_with_refresh(default_conf, mocker) -> None:
refresh_data(
datadir=Path(''),
pairs=[],
timeframe=default_conf['ticker_interval'],
timeframe=default_conf['timeframe'],
exchange=exchange
)
assert {} == load_data(
datadir=Path(''),
pairs=[],
timeframe=default_conf['ticker_interval']
timeframe=default_conf['timeframe']
)
@ -557,6 +557,7 @@ def test_download_trades_history(trades_history, mocker, default_conf, testdatad
assert ght_mock.call_count == 1
# Check this in seconds - since we had to convert to seconds above too.
assert int(ght_mock.call_args_list[0][1]['since'] // 1000) == since_time2 - 5
assert ght_mock.call_args_list[0][1]['from_id'] is not None
# clean files freshly downloaded
_clean_test_file(file1)
@ -568,6 +569,27 @@ def test_download_trades_history(trades_history, mocker, default_conf, testdatad
pair='ETH/BTC')
assert log_has_re('Failed to download historic trades for pair: "ETH/BTC".*', caplog)
file2 = testdatadir / 'XRP_ETH-trades.json.gz'
_backup_file(file2, True)
ght_mock.reset_mock()
mocker.patch('freqtrade.exchange.Exchange.get_historic_trades',
ght_mock)
# Since before first start date
since_time = int(trades_history[0][0] // 1000) - 500
timerange = TimeRange('date', None, since_time, 0)
assert _download_trades_history(data_handler=data_handler, exchange=exchange,
pair='XRP/ETH', timerange=timerange)
assert ght_mock.call_count == 1
assert int(ght_mock.call_args_list[0][1]['since'] // 1000) == since_time
assert ght_mock.call_args_list[0][1]['from_id'] is None
assert log_has_re(r'Start earlier than available data. Redownloading trades for.*', caplog)
_clean_test_file(file2)
def test_convert_trades_to_ohlcv(mocker, default_conf, testdatadir, caplog):

10
tests/edge/test_edge.py
View File

@ -27,7 +27,7 @@ from tests.optimize import (BTContainer, BTrade, _build_backtest_dataframe,
####################################################################
tests_start_time = arrow.get(2018, 10, 3)
ticker_interval_in_minute = 60
timeframe_in_minute = 60
_ohlc = {'date': 0, 'buy': 1, 'open': 2, 'high': 3, 'low': 4, 'close': 5, 'sell': 6, 'volume': 7}
# Helpers for this test file
@ -49,7 +49,7 @@ def _build_dataframe(buy_ohlc_sell_matrice):
'date': tests_start_time.shift(
minutes=(
ohlc[0] *
ticker_interval_in_minute)).timestamp *
timeframe_in_minute)).timestamp *
1000,
'buy': ohlc[1],
'open': ohlc[2],
@ -70,7 +70,7 @@ def _build_dataframe(buy_ohlc_sell_matrice):
def _time_on_candle(number):
return np.datetime64(tests_start_time.shift(
minutes=(number * ticker_interval_in_minute)).timestamp * 1000, 'ms')
minutes=(number * timeframe_in_minute)).timestamp * 1000, 'ms')
# End helper functions
@ -262,7 +262,7 @@ def mocked_load_data(datadir, pairs=[], timeframe='0m',
NEOBTC = [
[
tests_start_time.shift(minutes=(x * ticker_interval_in_minute)).timestamp * 1000,
tests_start_time.shift(minutes=(x * timeframe_in_minute)).timestamp * 1000,
math.sin(x * hz) / 1000 + base,
math.sin(x * hz) / 1000 + base + 0.0001,
math.sin(x * hz) / 1000 + base - 0.0001,
@ -274,7 +274,7 @@ def mocked_load_data(datadir, pairs=[], timeframe='0m',
base = 0.002
LTCBTC = [
[
tests_start_time.shift(minutes=(x * ticker_interval_in_minute)).timestamp * 1000,
tests_start_time.shift(minutes=(x * timeframe_in_minute)).timestamp * 1000,
math.sin(x * hz) / 1000 + base,
math.sin(x * hz) / 1000 + base + 0.0001,
math.sin(x * hz) / 1000 + base - 0.0001,

117
tests/exchange/test_exchange.py
View File

@ -25,7 +25,7 @@ from freqtrade.resolvers.exchange_resolver import ExchangeResolver
from tests.conftest import get_patched_exchange, log_has, log_has_re
# Make sure to always keep one exchange here which is NOT subclassed!!
EXCHANGES = ['bittrex', 'binance', 'kraken', ]
EXCHANGES = ['bittrex', 'binance', 'kraken', 'ftx']
# Source: https://stackoverflow.com/questions/29881236/how-to-mock-asyncio-coroutines
@ -88,15 +88,19 @@ def test_init_ccxt_kwargs(default_conf, mocker, caplog):
caplog.clear()
conf = copy.deepcopy(default_conf)
conf['exchange']['ccxt_config'] = {'TestKWARG': 11}
conf['exchange']['ccxt_sync_config'] = {'TestKWARG44': 11}
conf['exchange']['ccxt_async_config'] = {'asyncio_loop': True}
asynclogmsg = "Applying additional ccxt config: {'TestKWARG': 11, 'asyncio_loop': True}"
ex = Exchange(conf)
assert not log_has("Applying additional ccxt config: {'aiohttp_trust_env': True}", caplog)
assert not ex._api_async.aiohttp_trust_env
assert hasattr(ex._api, 'TestKWARG')
assert ex._api.TestKWARG == 11
assert not hasattr(ex._api_async, 'TestKWARG')
assert log_has("Applying additional ccxt config: {'TestKWARG': 11}", caplog)
# ccxt_config is assigned to both sync and async
assert not hasattr(ex._api_async, 'TestKWARG44')
assert hasattr(ex._api_async, 'TestKWARG')
assert log_has("Applying additional ccxt config: {'TestKWARG': 11, 'TestKWARG44': 11}", caplog)
assert log_has(asynclogmsg, caplog)
def test_destroy(default_conf, mocker, caplog):
@ -315,7 +319,12 @@ def test_set_sandbox_exception(default_conf, mocker):
def test__load_async_markets(default_conf, mocker, caplog):
exchange = get_patched_exchange(mocker, default_conf)
mocker.patch('freqtrade.exchange.Exchange._init_ccxt')
mocker.patch('freqtrade.exchange.Exchange.validate_pairs')
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes')
mocker.patch('freqtrade.exchange.Exchange._load_markets')
mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency')
exchange = Exchange(default_conf)
exchange._api_async.load_markets = get_mock_coro(None)
exchange._load_async_markets()
assert exchange._api_async.load_markets.call_count == 1
@ -348,7 +357,7 @@ def test__load_markets(default_conf, mocker, caplog):
assert ex.markets == expected_return
def test__reload_markets(default_conf, mocker, caplog):
def test_reload_markets(default_conf, mocker, caplog):
caplog.set_level(logging.DEBUG)
initial_markets = {'ETH/BTC': {}}
@ -361,23 +370,26 @@ def test__reload_markets(default_conf, mocker, caplog):
default_conf['exchange']['markets_refresh_interval'] = 10
exchange = get_patched_exchange(mocker, default_conf, api_mock, id="binance",
mock_markets=False)
exchange._load_async_markets = MagicMock()
exchange._last_markets_refresh = arrow.utcnow().timestamp
updated_markets = {'ETH/BTC': {}, "LTC/BTC": {}}
assert exchange.markets == initial_markets
# less than 10 minutes have passed, no reload
exchange._reload_markets()
exchange.reload_markets()
assert exchange.markets == initial_markets
assert exchange._load_async_markets.call_count == 0
# more than 10 minutes have passed, reload is executed
exchange._last_markets_refresh = arrow.utcnow().timestamp - 15 * 60
exchange._reload_markets()
exchange.reload_markets()
assert exchange.markets == updated_markets
assert exchange._load_async_markets.call_count == 1
assert log_has('Performing scheduled market reload..', caplog)
def test__reload_markets_exception(default_conf, mocker, caplog):
def test_reload_markets_exception(default_conf, mocker, caplog):
caplog.set_level(logging.DEBUG)
api_mock = MagicMock()
@ -386,7 +398,7 @@ def test__reload_markets_exception(default_conf, mocker, caplog):
exchange = get_patched_exchange(mocker, default_conf, api_mock, id="binance")
# less than 10 minutes have passed, no reload
exchange._reload_markets()
exchange.reload_markets()
assert exchange._last_markets_refresh == 0
assert log_has_re(r"Could not reload markets.*", caplog)
@ -574,7 +586,7 @@ def test_validate_pairs_stakecompatibility_fail(default_conf, mocker, caplog):
('5m'), ("1m"), ("15m"), ("1h")
])
def test_validate_timeframes(default_conf, mocker, timeframe):
default_conf["ticker_interval"] = timeframe
default_conf["timeframe"] = timeframe
api_mock = MagicMock()
id_mock = PropertyMock(return_value='test_exchange')
type(api_mock).id = id_mock
@ -592,7 +604,7 @@ def test_validate_timeframes(default_conf, mocker, timeframe):
def test_validate_timeframes_failed(default_conf, mocker):
default_conf["ticker_interval"] = "3m"
default_conf["timeframe"] = "3m"
api_mock = MagicMock()
id_mock = PropertyMock(return_value='test_exchange')
type(api_mock).id = id_mock
@ -609,7 +621,7 @@ def test_validate_timeframes_failed(default_conf, mocker):
with pytest.raises(OperationalException,
match=r"Invalid timeframe '3m'. This exchange supports.*"):
Exchange(default_conf)
default_conf["ticker_interval"] = "15s"
default_conf["timeframe"] = "15s"
with pytest.raises(OperationalException,
match=r"Timeframes < 1m are currently not supported by Freqtrade."):
@ -617,7 +629,7 @@ def test_validate_timeframes_failed(default_conf, mocker):
def test_validate_timeframes_emulated_ohlcv_1(default_conf, mocker):
default_conf["ticker_interval"] = "3m"
default_conf["timeframe"] = "3m"
api_mock = MagicMock()
id_mock = PropertyMock(return_value='test_exchange')
type(api_mock).id = id_mock
@ -637,7 +649,7 @@ def test_validate_timeframes_emulated_ohlcv_1(default_conf, mocker):
def test_validate_timeframes_emulated_ohlcvi_2(default_conf, mocker):
default_conf["ticker_interval"] = "3m"
default_conf["timeframe"] = "3m"
api_mock = MagicMock()
id_mock = PropertyMock(return_value='test_exchange')
type(api_mock).id = id_mock
@ -658,7 +670,7 @@ def test_validate_timeframes_emulated_ohlcvi_2(default_conf, mocker):
def test_validate_timeframes_not_in_config(default_conf, mocker):
del default_conf["ticker_interval"]
del default_conf["timeframe"]
api_mock = MagicMock()
id_mock = PropertyMock(return_value='test_exchange')
type(api_mock).id = id_mock
@ -1254,7 +1266,8 @@ def test_get_historic_ohlcv(default_conf, mocker, caplog, exchange_name):
exchange._async_get_candle_history = Mock(wraps=mock_candle_hist)
# one_call calculation * 1.8 should do 2 calls
since = 5 * 60 * 500 * 1.8
since = 5 * 60 * exchange._ft_has['ohlcv_candle_limit'] * 1.8
ret = exchange.get_historic_ohlcv(pair, "5m", int((arrow.utcnow().timestamp - since) * 1000))
assert exchange._async_get_candle_history.call_count == 2
@ -1346,7 +1359,7 @@ async def test__async_get_candle_history(default_conf, mocker, caplog, exchange_
# exchange = Exchange(default_conf)
await async_ccxt_exception(mocker, default_conf, MagicMock(),
"_async_get_candle_history", "fetch_ohlcv",
pair='ABCD/BTC', timeframe=default_conf['ticker_interval'])
pair='ABCD/BTC', timeframe=default_conf['timeframe'])
api_mock = MagicMock()
with pytest.raises(OperationalException,
@ -1476,7 +1489,7 @@ async def test___async_get_candle_history_sort(default_conf, mocker, exchange_na
exchange._api_async.fetch_ohlcv = get_mock_coro(ohlcv)
sort_mock = mocker.patch('freqtrade.exchange.exchange.sorted', MagicMock(side_effect=sort_data))
# Test the OHLCV data sort
res = await exchange._async_get_candle_history('ETH/BTC', default_conf['ticker_interval'])
res = await exchange._async_get_candle_history('ETH/BTC', default_conf['timeframe'])
assert res[0] == 'ETH/BTC'
res_ohlcv = res[2]
@ -1513,9 +1526,9 @@ async def test___async_get_candle_history_sort(default_conf, mocker, exchange_na
# Reset sort mock
sort_mock = mocker.patch('freqtrade.exchange.sorted', MagicMock(side_effect=sort_data))
# Test the OHLCV data sort
res = await exchange._async_get_candle_history('ETH/BTC', default_conf['ticker_interval'])
res = await exchange._async_get_candle_history('ETH/BTC', default_conf['timeframe'])
assert res[0] == 'ETH/BTC'
assert res[1] == default_conf['ticker_interval']
assert res[1] == default_conf['timeframe']
res_ohlcv = res[2]
# Sorted not called again - data is already in order
assert sort_mock.call_count == 0
@ -1729,6 +1742,7 @@ def test_cancel_order_dry_run(default_conf, mocker, exchange_name):
default_conf['dry_run'] = True
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
assert exchange.cancel_order(order_id='123', pair='TKN/BTC') == {}
assert exchange.cancel_stoploss_order(order_id='123', pair='TKN/BTC') == {}
@pytest.mark.parametrize("exchange_name", EXCHANGES)
@ -1813,6 +1827,25 @@ def test_cancel_order(default_conf, mocker, exchange_name):
order_id='_', pair='TKN/BTC')
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_cancel_stoploss_order(default_conf, mocker, exchange_name):
default_conf['dry_run'] = False
api_mock = MagicMock()
api_mock.cancel_order = MagicMock(return_value=123)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
assert exchange.cancel_stoploss_order(order_id='_', pair='TKN/BTC') == 123
with pytest.raises(InvalidOrderException):
api_mock.cancel_order = MagicMock(side_effect=ccxt.InvalidOrder("Did not find order"))
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
exchange.cancel_stoploss_order(order_id='_', pair='TKN/BTC')
assert api_mock.cancel_order.call_count == 1
ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
"cancel_stoploss_order", "cancel_order",
order_id='_', pair='TKN/BTC')
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_get_order(default_conf, mocker, exchange_name):
default_conf['dry_run'] = True
@ -1842,6 +1875,38 @@ def test_get_order(default_conf, mocker, exchange_name):
order_id='_', pair='TKN/BTC')
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_get_stoploss_order(default_conf, mocker, exchange_name):
# Don't test FTX here - that needs a seperate test
if exchange_name == 'ftx':
return
default_conf['dry_run'] = True
order = MagicMock()
order.myid = 123
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
exchange._dry_run_open_orders['X'] = order
assert exchange.get_stoploss_order('X', 'TKN/BTC').myid == 123
with pytest.raises(InvalidOrderException, match=r'Tried to get an invalid dry-run-order.*'):
exchange.get_stoploss_order('Y', 'TKN/BTC')
default_conf['dry_run'] = False
api_mock = MagicMock()
api_mock.fetch_order = MagicMock(return_value=456)
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
assert exchange.get_stoploss_order('X', 'TKN/BTC') == 456
with pytest.raises(InvalidOrderException):
api_mock.fetch_order = MagicMock(side_effect=ccxt.InvalidOrder("Order not found"))
exchange = get_patched_exchange(mocker, default_conf, api_mock, id=exchange_name)
exchange.get_stoploss_order(order_id='_', pair='TKN/BTC')
assert api_mock.fetch_order.call_count == 1
ccxt_exceptionhandlers(mocker, default_conf, api_mock, exchange_name,
'get_stoploss_order', 'fetch_order',
order_id='_', pair='TKN/BTC')
@pytest.mark.parametrize("exchange_name", EXCHANGES)
def test_name(default_conf, mocker, exchange_name):
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
@ -2188,12 +2253,18 @@ def test_extract_cost_curr_rate(mocker, default_conf, order, expected) -> None:
'fee': {'currency': 'NEO', 'cost': 0.0012}}, 0.001944),
({'symbol': 'ETH/BTC', 'amount': 2.21, 'cost': 0.02992561,
'fee': {'currency': 'NEO', 'cost': 0.00027452}}, 0.00074305),
# TODO: More tests here!
# Rate included in return - return as is
({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.05,
'fee': {'currency': 'USDT', 'cost': 0.34, 'rate': 0.01}}, 0.01),
({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.05,
'fee': {'currency': 'USDT', 'cost': 0.34, 'rate': 0.005}}, 0.005),
# 0.1% filled - no costs (kraken - #3431)
({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.0,
'fee': {'currency': 'BTC', 'cost': 0.0, 'rate': None}}, None),
({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.0,
'fee': {'currency': 'ETH', 'cost': 0.0, 'rate': None}}, 0.0),
({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.0,
'fee': {'currency': 'NEO', 'cost': 0.0, 'rate': None}}, None),
])
def test_calculate_fee_rate(mocker, default_conf, order, expected) -> None:
mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', return_value={'last': 0.081})

163
tests/exchange/test_ftx.py Normal file
View File

@ -0,0 +1,163 @@
# pragma pylint: disable=missing-docstring, C0103, bad-continuation, global-statement
# pragma pylint: disable=protected-access
from random import randint
from unittest.mock import MagicMock
import ccxt
import pytest
from freqtrade.exceptions import (DependencyException, InvalidOrderException,
OperationalException, TemporaryError)
from tests.conftest import get_patched_exchange
from .test_exchange import ccxt_exceptionhandlers
STOPLOSS_ORDERTYPE = 'stop'
def test_stoploss_order_ftx(default_conf, mocker):
api_mock = MagicMock()
order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
api_mock.create_order = MagicMock(return_value={
'id': order_id,
'info': {
'foo': 'bar'
}
})
default_conf['dry_run'] = False
mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
exchange = get_patched_exchange(mocker, default_conf, api_mock, 'ftx')
# stoploss_on_exchange_limit_ratio is irrelevant for ftx market orders
order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=190,
order_types={'stoploss_on_exchange_limit_ratio': 1.05})
assert api_mock.create_order.call_args_list[0][1]['symbol'] == 'ETH/BTC'
assert api_mock.create_order.call_args_list[0][1]['type'] == STOPLOSS_ORDERTYPE
assert api_mock.create_order.call_args_list[0][1]['side'] == 'sell'
assert api_mock.create_order.call_args_list[0][1]['amount'] == 1
assert api_mock.create_order.call_args_list[0][1]['price'] == 190
assert 'orderPrice' not in api_mock.create_order.call_args_list[0][1]['params']
assert api_mock.create_order.call_count == 1
api_mock.create_order.reset_mock()
order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
assert 'id' in order
assert 'info' in order
assert order['id'] == order_id
assert api_mock.create_order.call_args_list[0][1]['symbol'] == 'ETH/BTC'
assert api_mock.create_order.call_args_list[0][1]['type'] == STOPLOSS_ORDERTYPE
assert api_mock.create_order.call_args_list[0][1]['side'] == 'sell'
assert api_mock.create_order.call_args_list[0][1]['amount'] == 1
assert api_mock.create_order.call_args_list[0][1]['price'] == 220
assert 'orderPrice' not in api_mock.create_order.call_args_list[0][1]['params']
api_mock.create_order.reset_mock()
order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220,
order_types={'stoploss': 'limit'})
assert 'id' in order
assert 'info' in order
assert order['id'] == order_id
assert api_mock.create_order.call_args_list[0][1]['symbol'] == 'ETH/BTC'
assert api_mock.create_order.call_args_list[0][1]['type'] == STOPLOSS_ORDERTYPE
assert api_mock.create_order.call_args_list[0][1]['side'] == 'sell'
assert api_mock.create_order.call_args_list[0][1]['amount'] == 1
assert api_mock.create_order.call_args_list[0][1]['price'] == 220
assert 'orderPrice' in api_mock.create_order.call_args_list[0][1]['params']
assert api_mock.create_order.call_args_list[0][1]['params']['orderPrice'] == 217.8
# test exception handling
with pytest.raises(DependencyException):
api_mock.create_order = MagicMock(side_effect=ccxt.InsufficientFunds("0 balance"))
exchange = get_patched_exchange(mocker, default_conf, api_mock, 'ftx')
exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
with pytest.raises(InvalidOrderException):
api_mock.create_order = MagicMock(
side_effect=ccxt.InvalidOrder("ftx Order would trigger immediately."))
exchange = get_patched_exchange(mocker, default_conf, api_mock, 'ftx')
exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
with pytest.raises(TemporaryError):
api_mock.create_order = MagicMock(side_effect=ccxt.NetworkError("No connection"))
exchange = get_patched_exchange(mocker, default_conf, api_mock, 'ftx')
exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
with pytest.raises(OperationalException, match=r".*DeadBeef.*"):
api_mock.create_order = MagicMock(side_effect=ccxt.BaseError("DeadBeef"))
exchange = get_patched_exchange(mocker, default_conf, api_mock, 'ftx')
exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
def test_stoploss_order_dry_run_ftx(default_conf, mocker):
api_mock = MagicMock()
default_conf['dry_run'] = True
mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
exchange = get_patched_exchange(mocker, default_conf, api_mock, 'ftx')
api_mock.create_order.reset_mock()
order = exchange.stoploss(pair='ETH/BTC', amount=1, stop_price=220, order_types={})
assert 'id' in order
assert 'info' in order
assert 'type' in order
assert order['type'] == STOPLOSS_ORDERTYPE
assert order['price'] == 220
assert order['amount'] == 1
def test_stoploss_adjust_ftx(mocker, default_conf):
exchange = get_patched_exchange(mocker, default_conf, id='ftx')
order = {
'type': STOPLOSS_ORDERTYPE,
'price': 1500,
}
assert exchange.stoploss_adjust(1501, order)
assert not exchange.stoploss_adjust(1499, order)
# Test with invalid order case ...
order['type'] = 'stop_loss_limit'
assert not exchange.stoploss_adjust(1501, order)
def test_get_stoploss_order(default_conf, mocker):
default_conf['dry_run'] = True
order = MagicMock()
order.myid = 123
exchange = get_patched_exchange(mocker, default_conf, id='ftx')
exchange._dry_run_open_orders['X'] = order
assert exchange.get_stoploss_order('X', 'TKN/BTC').myid == 123
with pytest.raises(InvalidOrderException, match=r'Tried to get an invalid dry-run-order.*'):
exchange.get_stoploss_order('Y', 'TKN/BTC')
default_conf['dry_run'] = False
api_mock = MagicMock()
api_mock.fetch_orders = MagicMock(return_value=[{'id': 'X', 'status': '456'}])
exchange = get_patched_exchange(mocker, default_conf, api_mock, id='ftx')
assert exchange.get_stoploss_order('X', 'TKN/BTC')['status'] == '456'
api_mock.fetch_orders = MagicMock(return_value=[{'id': 'Y', 'status': '456'}])
exchange = get_patched_exchange(mocker, default_conf, api_mock, id='ftx')
with pytest.raises(InvalidOrderException, match=r"Could not get stoploss order for id X"):
exchange.get_stoploss_order('X', 'TKN/BTC')['status']
with pytest.raises(InvalidOrderException):
api_mock.fetch_orders = MagicMock(side_effect=ccxt.InvalidOrder("Order not found"))
exchange = get_patched_exchange(mocker, default_conf, api_mock, id='ftx')
exchange.get_stoploss_order(order_id='_', pair='TKN/BTC')
assert api_mock.fetch_orders.call_count == 1
ccxt_exceptionhandlers(mocker, default_conf, api_mock, 'ftx',
'get_stoploss_order', 'fetch_orders',
order_id='_', pair='TKN/BTC')

10
tests/exchange/test_kraken.py
View File

@ -11,6 +11,8 @@ from freqtrade.exceptions import (DependencyException, InvalidOrderException,
from tests.conftest import get_patched_exchange
from tests.exchange.test_exchange import ccxt_exceptionhandlers
STOPLOSS_ORDERTYPE = 'stop-loss'
def test_buy_kraken_trading_agreement(default_conf, mocker):
api_mock = MagicMock()
@ -159,7 +161,6 @@ def test_get_balances_prod(default_conf, mocker):
def test_stoploss_order_kraken(default_conf, mocker):
api_mock = MagicMock()
order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
order_type = 'stop-loss'
api_mock.create_order = MagicMock(return_value={
'id': order_id,
@ -187,7 +188,7 @@ def test_stoploss_order_kraken(default_conf, mocker):
assert 'info' in order
assert order['id'] == order_id
assert api_mock.create_order.call_args_list[0][1]['symbol'] == 'ETH/BTC'
assert api_mock.create_order.call_args_list[0][1]['type'] == order_type
assert api_mock.create_order.call_args_list[0][1]['type'] == STOPLOSS_ORDERTYPE
assert api_mock.create_order.call_args_list[0][1]['side'] == 'sell'
assert api_mock.create_order.call_args_list[0][1]['amount'] == 1
assert api_mock.create_order.call_args_list[0][1]['price'] == 220
@ -218,7 +219,6 @@ def test_stoploss_order_kraken(default_conf, mocker):
def test_stoploss_order_dry_run_kraken(default_conf, mocker):
api_mock = MagicMock()
order_type = 'stop-loss'
default_conf['dry_run'] = True
mocker.patch('freqtrade.exchange.Exchange.amount_to_precision', lambda s, x, y: y)
mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
@ -233,7 +233,7 @@ def test_stoploss_order_dry_run_kraken(default_conf, mocker):
assert 'info' in order
assert 'type' in order
assert order['type'] == order_type
assert order['type'] == STOPLOSS_ORDERTYPE
assert order['price'] == 220
assert order['amount'] == 1
@ -241,7 +241,7 @@ def test_stoploss_order_dry_run_kraken(default_conf, mocker):
def test_stoploss_adjust_kraken(mocker, default_conf):
exchange = get_patched_exchange(mocker, default_conf, id='kraken')
order = {
'type': 'stop-loss',
'type': STOPLOSS_ORDERTYPE,
'price': 1500,
}
assert exchange.stoploss_adjust(1501, order)

2
tests/optimize/test_backtest_detail.py
View File

@ -360,7 +360,7 @@ def test_backtest_results(default_conf, fee, mocker, caplog, data) -> None:
"""
default_conf["stoploss"] = data.stop_loss
default_conf["minimal_roi"] = data.roi
default_conf["ticker_interval"] = tests_timeframe
default_conf["timeframe"] = tests_timeframe
default_conf["trailing_stop"] = data.trailing_stop
default_conf["trailing_only_offset_is_reached"] = data.trailing_only_offset_is_reached
# Only add this to configuration If it's necessary

94
tests/optimize/test_backtesting.py
View File

@ -81,7 +81,7 @@ def load_data_test(what, testdatadir):
def simple_backtest(config, contour, num_results, mocker, testdatadir) -> None:
patch_exchange(mocker)
config['ticker_interval'] = '1m'
config['timeframe'] = '1m'
backtesting = Backtesting(config)
data = load_data_test(contour, testdatadir)
@ -165,7 +165,7 @@ def test_setup_optimize_configuration_without_arguments(mocker, default_conf, ca
assert 'pair_whitelist' in config['exchange']
assert 'datadir' in config
assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
assert 'ticker_interval' in config
assert 'timeframe' in config
assert not log_has_re('Parameter -i/--ticker-interval detected .*', caplog)
assert 'position_stacking' not in config
@ -189,7 +189,7 @@ def test_setup_bt_configuration_with_arguments(mocker, default_conf, caplog) ->
'--config', 'config.json',
'--strategy', 'DefaultStrategy',
'--datadir', '/foo/bar',
'--ticker-interval', '1m',
'--timeframe', '1m',
'--enable-position-stacking',
'--disable-max-market-positions',
'--timerange', ':100',
@ -208,8 +208,8 @@ def test_setup_bt_configuration_with_arguments(mocker, default_conf, caplog) ->
assert config['runmode'] == RunMode.BACKTEST
assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
assert 'ticker_interval' in config
assert log_has('Parameter -i/--ticker-interval detected ... Using ticker_interval: 1m ...',
assert 'timeframe' in config
assert log_has('Parameter -i/--timeframe detected ... Using timeframe: 1m ...',
caplog)
assert 'position_stacking' in config
@ -286,9 +286,9 @@ def test_backtesting_init(mocker, default_conf, order_types) -> None:
assert not backtesting.strategy.order_types["stoploss_on_exchange"]
def test_backtesting_init_no_ticker_interval(mocker, default_conf, caplog) -> None:
def test_backtesting_init_no_timeframe(mocker, default_conf, caplog) -> None:
patch_exchange(mocker)
del default_conf['ticker_interval']
del default_conf['timeframe']
default_conf['strategy_list'] = ['DefaultStrategy',
'SampleStrategy']
@ -333,11 +333,12 @@ def test_backtesting_start(default_conf, mocker, testdatadir, caplog) -> None:
mocker.patch('freqtrade.data.history.get_timerange', get_timerange)
patch_exchange(mocker)
mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest')
mocker.patch('freqtrade.optimize.backtesting.generate_backtest_stats')
mocker.patch('freqtrade.optimize.backtesting.show_backtest_results')
mocker.patch('freqtrade.pairlist.pairlistmanager.PairListManager.whitelist',
PropertyMock(return_value=['UNITTEST/BTC']))
default_conf['ticker_interval'] = '1m'
default_conf['timeframe'] = '1m'
default_conf['datadir'] = testdatadir
default_conf['export'] = None
default_conf['timerange'] = '-1510694220'
@ -367,7 +368,7 @@ def test_backtesting_start_no_data(default_conf, mocker, caplog, testdatadir) ->
mocker.patch('freqtrade.pairlist.pairlistmanager.PairListManager.whitelist',
PropertyMock(return_value=['UNITTEST/BTC']))
default_conf['ticker_interval'] = "1m"
default_conf['timeframe'] = "1m"
default_conf['datadir'] = testdatadir
default_conf['export'] = None
default_conf['timerange'] = '20180101-20180102'
@ -387,7 +388,7 @@ def test_backtesting_no_pair_left(default_conf, mocker, caplog, testdatadir) ->
mocker.patch('freqtrade.pairlist.pairlistmanager.PairListManager.whitelist',
PropertyMock(return_value=[]))
default_conf['ticker_interval'] = "1m"
default_conf['timeframe'] = "1m"
default_conf['datadir'] = testdatadir
default_conf['export'] = None
default_conf['timerange'] = '20180101-20180102'
@ -400,6 +401,38 @@ def test_backtesting_no_pair_left(default_conf, mocker, caplog, testdatadir) ->
Backtesting(default_conf)
def test_backtesting_pairlist_list(default_conf, mocker, caplog, testdatadir, tickers) -> None:
mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
mocker.patch('freqtrade.exchange.Exchange.get_tickers', tickers)
mocker.patch('freqtrade.exchange.Exchange.price_to_precision', lambda s, x, y: y)
mocker.patch('freqtrade.data.history.get_timerange', get_timerange)
patch_exchange(mocker)
mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest')
mocker.patch('freqtrade.pairlist.pairlistmanager.PairListManager.whitelist',
PropertyMock(return_value=['XRP/BTC']))
mocker.patch('freqtrade.pairlist.pairlistmanager.PairListManager.refresh_pairlist')
default_conf['ticker_interval'] = "1m"
default_conf['datadir'] = testdatadir
default_conf['export'] = None
# Use stoploss from strategy
del default_conf['stoploss']
default_conf['timerange'] = '20180101-20180102'
default_conf['pairlists'] = [{"method": "VolumePairList", "number_assets": 5}]
with pytest.raises(OperationalException, match='VolumePairList not allowed for backtesting.'):
Backtesting(default_conf)
default_conf['pairlists'] = [{"method": "StaticPairList"}, {"method": "PrecisionFilter"}, ]
Backtesting(default_conf)
# Multiple strategies
default_conf['strategy_list'] = ['DefaultStrategy', 'TestStrategyLegacy']
with pytest.raises(OperationalException,
match='PrecisionFilter not allowed for backtesting multiple strategies.'):
Backtesting(default_conf)
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)
@ -453,7 +486,7 @@ def test_backtest(default_conf, fee, mocker, testdatadir) -> None:
t["close_rate"], 6) < round(ln.iloc[0]["high"], 6))
def test_backtest_1min_ticker_interval(default_conf, fee, mocker, testdatadir) -> None:
def test_backtest_1min_timeframe(default_conf, fee, mocker, testdatadir) -> None:
default_conf['ask_strategy']['use_sell_signal'] = False
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
patch_exchange(mocker)
@ -534,7 +567,7 @@ def test_backtest_alternate_buy_sell(default_conf, fee, mocker, testdatadir):
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
backtest_conf = _make_backtest_conf(mocker, conf=default_conf,
pair='UNITTEST/BTC', datadir=testdatadir)
default_conf['ticker_interval'] = '1m'
default_conf['timeframe'] = '1m'
backtesting = Backtesting(default_conf)
backtesting.strategy.advise_buy = _trend_alternate # Override
backtesting.strategy.advise_sell = _trend_alternate # Override
@ -573,7 +606,7 @@ 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()
default_conf['ticker_interval'] = '5m'
default_conf['timeframe'] = '5m'
backtesting = Backtesting(default_conf)
backtesting.strategy.advise_buy = _trend_alternate_hold # Override
@ -612,8 +645,9 @@ def test_backtest_multi_pair(default_conf, fee, mocker, tres, pair, testdatadir)
def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir):
patch_exchange(mocker)
mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', MagicMock())
mocker.patch('freqtrade.optimize.backtesting.show_backtest_results', MagicMock())
mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest')
mocker.patch('freqtrade.optimize.backtesting.generate_backtest_stats')
mocker.patch('freqtrade.optimize.backtesting.show_backtest_results')
mocker.patch('freqtrade.pairlist.pairlistmanager.PairListManager.whitelist',
PropertyMock(return_value=['UNITTEST/BTC']))
patched_configuration_load_config_file(mocker, default_conf)
@ -623,7 +657,7 @@ def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir):
'--config', 'config.json',
'--strategy', 'DefaultStrategy',
'--datadir', str(testdatadir),
'--ticker-interval', '1m',
'--timeframe', '1m',
'--timerange', '1510694220-1510700340',
'--enable-position-stacking',
'--disable-max-market-positions'
@ -632,7 +666,7 @@ def test_backtest_start_timerange(default_conf, mocker, caplog, testdatadir):
start_backtesting(args)
# check the logs, that will contain the backtest result
exists = [
'Parameter -i/--ticker-interval detected ... Using ticker_interval: 1m ...',
'Parameter -i/--timeframe detected ... Using timeframe: 1m ...',
'Ignoring max_open_trades (--disable-max-market-positions was used) ...',
'Parameter --timerange detected: 1510694220-1510700340 ...',
f'Using data directory: {testdatadir} ...',
@ -657,17 +691,17 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
mocker.patch('freqtrade.pairlist.pairlistmanager.PairListManager.whitelist',
PropertyMock(return_value=['UNITTEST/BTC']))
mocker.patch('freqtrade.optimize.backtesting.Backtesting.backtest', backtestmock)
gen_table_mock = MagicMock()
text_table_mock = MagicMock()
sell_reason_mock = MagicMock()
gen_strattable_mock = MagicMock()
gen_strat_summary = MagicMock()
strattable_mock = MagicMock()
strat_summary = MagicMock()
mocker.patch.multiple('freqtrade.optimize.optimize_reports',
generate_text_table=gen_table_mock,
generate_text_table_strategy=gen_strattable_mock,
text_table_bt_results=text_table_mock,
text_table_strategy=strattable_mock,
generate_pair_metrics=MagicMock(),
generate_sell_reason_stats=sell_reason_mock,
generate_strategy_metrics=gen_strat_summary,
generate_strategy_metrics=strat_summary,
)
patched_configuration_load_config_file(mocker, default_conf)
@ -676,7 +710,7 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
'--config', 'config.json',
'--datadir', str(testdatadir),
'--strategy-path', str(Path(__file__).parents[1] / 'strategy/strats'),
'--ticker-interval', '1m',
'--timeframe', '1m',
'--timerange', '1510694220-1510700340',
'--enable-position-stacking',
'--disable-max-market-positions',
@ -688,14 +722,14 @@ def test_backtest_start_multi_strat(default_conf, mocker, caplog, testdatadir):
start_backtesting(args)
# 2 backtests, 4 tables
assert backtestmock.call_count == 2
assert gen_table_mock.call_count == 4
assert gen_strattable_mock.call_count == 1
assert text_table_mock.call_count == 4
assert strattable_mock.call_count == 1
assert sell_reason_mock.call_count == 2
assert gen_strat_summary.call_count == 1
assert strat_summary.call_count == 1
# check the logs, that will contain the backtest result
exists = [
'Parameter -i/--ticker-interval detected ... Using ticker_interval: 1m ...',
'Parameter -i/--timeframe detected ... Using timeframe: 1m ...',
'Ignoring max_open_trades (--disable-max-market-positions was used) ...',
'Parameter --timerange detected: 1510694220-1510700340 ...',
f'Using data directory: {testdatadir} ...',
@ -765,7 +799,7 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat
'--config', 'config.json',
'--datadir', str(testdatadir),
'--strategy-path', str(Path(__file__).parents[1] / 'strategy/strats'),
'--ticker-interval', '1m',
'--timeframe', '1m',
'--timerange', '1510694220-1510700340',
'--enable-position-stacking',
'--disable-max-market-positions',
@ -778,7 +812,7 @@ def test_backtest_start_multi_strat_nomock(default_conf, mocker, caplog, testdat
# check the logs, that will contain the backtest result
exists = [
'Parameter -i/--ticker-interval detected ... Using ticker_interval: 1m ...',
'Parameter -i/--timeframe detected ... Using timeframe: 1m ...',
'Ignoring max_open_trades (--disable-max-market-positions was used) ...',
'Parameter --timerange detected: 1510694220-1510700340 ...',
f'Using data directory: {testdatadir} ...',

8
tests/optimize/test_edge_cli.py
View File

@ -29,7 +29,7 @@ def test_setup_optimize_configuration_without_arguments(mocker, default_conf, ca
assert 'pair_whitelist' in config['exchange']
assert 'datadir' in config
assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
assert 'ticker_interval' in config
assert 'timeframe' in config
assert not log_has_re('Parameter -i/--ticker-interval detected .*', caplog)
assert 'timerange' not in config
@ -48,7 +48,7 @@ def test_setup_edge_configuration_with_arguments(mocker, edge_conf, caplog) -> N
'--config', 'config.json',
'--strategy', 'DefaultStrategy',
'--datadir', '/foo/bar',
'--ticker-interval', '1m',
'--timeframe', '1m',
'--timerange', ':100',
'--stoplosses=-0.01,-0.10,-0.001'
]
@ -62,8 +62,8 @@ def test_setup_edge_configuration_with_arguments(mocker, edge_conf, caplog) -> N
assert 'datadir' in config
assert config['runmode'] == RunMode.EDGE
assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
assert 'ticker_interval' in config
assert log_has('Parameter -i/--ticker-interval detected ... Using ticker_interval: 1m ...',
assert 'timeframe' in config
assert log_has('Parameter -i/--timeframe detected ... Using timeframe: 1m ...',
caplog)
assert 'timerange' in config

13
tests/optimize/test_hyperopt.py
View File

@ -94,7 +94,7 @@ def test_setup_hyperopt_configuration_without_arguments(mocker, default_conf, ca
assert 'pair_whitelist' in config['exchange']
assert 'datadir' in config
assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
assert 'ticker_interval' in config
assert 'timeframe' in config
assert not log_has_re('Parameter -i/--ticker-interval detected .*', caplog)
assert 'position_stacking' not in config
@ -117,7 +117,7 @@ def test_setup_hyperopt_configuration_with_arguments(mocker, default_conf, caplo
'--config', 'config.json',
'--hyperopt', 'DefaultHyperOpt',
'--datadir', '/foo/bar',
'--ticker-interval', '1m',
'--timeframe', '1m',
'--timerange', ':100',
'--enable-position-stacking',
'--disable-max-market-positions',
@ -136,8 +136,8 @@ def test_setup_hyperopt_configuration_with_arguments(mocker, default_conf, caplo
assert config['runmode'] == RunMode.HYPEROPT
assert log_has('Using data directory: {} ...'.format(config['datadir']), caplog)
assert 'ticker_interval' in config
assert log_has('Parameter -i/--ticker-interval detected ... Using ticker_interval: 1m ...',
assert 'timeframe' in config
assert log_has('Parameter -i/--timeframe detected ... Using timeframe: 1m ...',
caplog)
assert 'position_stacking' in config
@ -197,7 +197,8 @@ def test_hyperoptresolver(mocker, default_conf, caplog) -> None:
"Using populate_sell_trend from the strategy.", caplog)
assert log_has("Hyperopt class does not provide populate_buy_trend() method. "
"Using populate_buy_trend from the strategy.", caplog)
assert hasattr(x, "ticker_interval")
assert hasattr(x, "ticker_interval") # DEPRECATED
assert hasattr(x, "timeframe")
def test_hyperoptresolver_wrongname(mocker, default_conf, caplog) -> None:
@ -544,7 +545,7 @@ def test_start_calls_optimizer(mocker, default_conf, caplog, capsys) -> None:
)
patch_exchange(mocker)
# Co-test loading timeframe from strategy
del default_conf['ticker_interval']
del default_conf['timeframe']
default_conf.update({'config': 'config.json.example',
'hyperopt': 'DefaultHyperOpt',
'epochs': 1,

17
tests/optimize/test_optimize_reports.py
View File

@ -7,13 +7,13 @@ from arrow import Arrow
from freqtrade.edge import PairInfo
from freqtrade.optimize.optimize_reports import (
generate_pair_metrics, generate_edge_table, generate_sell_reason_stats,
generate_text_table, generate_text_table_sell_reason, generate_strategy_metrics,
generate_text_table_strategy, store_backtest_result)
text_table_bt_results, text_table_sell_reason, generate_strategy_metrics,
text_table_strategy, store_backtest_result)
from freqtrade.strategy.interface import SellType
from tests.conftest import patch_exchange
def test_generate_text_table(default_conf, mocker):
def test_text_table_bt_results(default_conf, mocker):
results = pd.DataFrame(
{
@ -40,8 +40,7 @@ def test_generate_text_table(default_conf, mocker):
pair_results = generate_pair_metrics(data={'ETH/BTC': {}}, stake_currency='BTC',
max_open_trades=2, results=results)
assert generate_text_table(pair_results,
stake_currency='BTC') == result_str
assert text_table_bt_results(pair_results, stake_currency='BTC') == result_str
def test_generate_pair_metrics(default_conf, mocker):
@ -69,7 +68,7 @@ def test_generate_pair_metrics(default_conf, mocker):
pytest.approx(pair_results[-1]['profit_sum_pct']) == pair_results[-1]['profit_sum'] * 100)
def test_generate_text_table_sell_reason(default_conf):
def test_text_table_sell_reason(default_conf):
results = pd.DataFrame(
{
@ -97,7 +96,7 @@ def test_generate_text_table_sell_reason(default_conf):
sell_reason_stats = generate_sell_reason_stats(max_open_trades=2,
results=results)
assert generate_text_table_sell_reason(sell_reason_stats=sell_reason_stats,
assert text_table_sell_reason(sell_reason_stats=sell_reason_stats,
stake_currency='BTC') == result_str
@ -136,7 +135,7 @@ def test_generate_sell_reason_stats(default_conf):
assert stop_result['profit_mean_pct'] == round(stop_result['profit_mean'] * 100, 2)
def test_generate_text_table_strategy(default_conf, mocker):
def test_text_table_strategy(default_conf, mocker):
results = {}
results['TestStrategy1'] = pd.DataFrame(
{
@ -178,7 +177,7 @@ def test_generate_text_table_strategy(default_conf, mocker):
max_open_trades=2,
all_results=results)
assert generate_text_table_strategy(strategy_results, 'BTC') == result_str
assert text_table_strategy(strategy_results, 'BTC') == result_str
def test_generate_edge_table(edge_conf, mocker):

169
tests/pairlist/test_pairlist.py
View File

@ -19,7 +19,8 @@ def whitelist_conf(default_conf):
'TKN/BTC',
'TRST/BTC',
'SWT/BTC',
'BCC/BTC'
'BCC/BTC',
'HOT/BTC',
]
default_conf['exchange']['pair_blacklist'] = [
'BLK/BTC'
@ -56,6 +57,31 @@ def whitelist_conf_2(default_conf):
return default_conf
@pytest.fixture(scope="function")
def whitelist_conf_3(default_conf):
default_conf['stake_currency'] = 'BTC'
default_conf['exchange']['pair_whitelist'] = [
'ETH/BTC', 'TKN/BTC', 'BLK/BTC', 'LTC/BTC',
'BTT/BTC', 'HOT/BTC', 'FUEL/BTC', 'XRP/BTC'
]
default_conf['exchange']['pair_blacklist'] = [
'BLK/BTC'
]
default_conf['pairlists'] = [
{
"method": "VolumePairList",
"number_assets": 5,
"sort_key": "quoteVolume",
"refresh_period": 0,
},
{
"method": "AgeFilter",
"min_days_listed": 2
}
]
return default_conf
@pytest.fixture(scope="function")
def static_pl_conf(whitelist_conf):
whitelist_conf['pairlists'] = [
@ -219,17 +245,28 @@ def test_VolumePairList_refresh_empty(mocker, markets_empty, whitelist_conf):
# No pair for ETH, all handlers
([{"method": "StaticPairList"},
{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
{"method": "AgeFilter", "min_days_listed": 2},
{"method": "PrecisionFilter"},
{"method": "PriceFilter", "low_price_ratio": 0.03},
{"method": "SpreadFilter", "max_spread_ratio": 0.005},
{"method": "ShuffleFilter"}],
"ETH", []),
# AgeFilter and VolumePairList (require 2 days only, all should pass age test)
([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
{"method": "AgeFilter", "min_days_listed": 2}],
"BTC", ['ETH/BTC', 'TKN/BTC', 'LTC/BTC', 'XRP/BTC', 'HOT/BTC']),
# AgeFilter and VolumePairList (require 10 days, all should fail age test)
([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
{"method": "AgeFilter", "min_days_listed": 10}],
"BTC", []),
# Precisionfilter and quote volume
([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
{"method": "PrecisionFilter"}], "BTC", ['ETH/BTC', 'TKN/BTC', 'LTC/BTC', 'XRP/BTC']),
{"method": "PrecisionFilter"}],
"BTC", ['ETH/BTC', 'TKN/BTC', 'LTC/BTC', 'XRP/BTC']),
# Precisionfilter bid
([{"method": "VolumePairList", "number_assets": 5, "sort_key": "bidVolume"},
{"method": "PrecisionFilter"}], "BTC", ['FUEL/BTC', 'XRP/BTC', 'LTC/BTC', 'TKN/BTC']),
{"method": "PrecisionFilter"}],
"BTC", ['FUEL/BTC', 'XRP/BTC', 'LTC/BTC', 'TKN/BTC']),
# PriceFilter and VolumePairList
([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
{"method": "PriceFilter", "low_price_ratio": 0.03}],
@ -249,11 +286,11 @@ def test_VolumePairList_refresh_empty(mocker, markets_empty, whitelist_conf):
"BTC", ['ETH/BTC', 'TKN/BTC', 'LTC/BTC']),
# StaticPairlist only
([{"method": "StaticPairList"}],
"BTC", ['ETH/BTC', 'TKN/BTC']),
"BTC", ['ETH/BTC', 'TKN/BTC', 'HOT/BTC']),
# Static Pairlist before VolumePairList - sorting changes
([{"method": "StaticPairList"},
{"method": "VolumePairList", "number_assets": 5, "sort_key": "bidVolume"}],
"BTC", ['TKN/BTC', 'ETH/BTC']),
"BTC", ['HOT/BTC', 'TKN/BTC', 'ETH/BTC']),
# SpreadFilter
([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
{"method": "SpreadFilter", "max_spread_ratio": 0.005}],
@ -269,22 +306,75 @@ def test_VolumePairList_refresh_empty(mocker, markets_empty, whitelist_conf):
# ShuffleFilter, no seed
([{"method": "VolumePairList", "number_assets": 5, "sort_key": "quoteVolume"},
{"method": "ShuffleFilter"}],
"USDT", 3),
"USDT", 3), # whitelist_result is integer -- check only length of randomized pairlist
# AgeFilter only
([{"method": "AgeFilter", "min_days_listed": 2}],
"BTC", 'filter_at_the_beginning'), # OperationalException expected
# PrecisionFilter after StaticPairList
([{"method": "StaticPairList"},
{"method": "PrecisionFilter"}],
"BTC", ['ETH/BTC', 'TKN/BTC']),
# PrecisionFilter only
([{"method": "PrecisionFilter"}],
"BTC", 'filter_at_the_beginning'), # OperationalException expected
# PriceFilter after StaticPairList
([{"method": "StaticPairList"},
{"method": "PriceFilter", "low_price_ratio": 0.02}],
"BTC", ['ETH/BTC', 'TKN/BTC']),
# PriceFilter only
([{"method": "PriceFilter", "low_price_ratio": 0.02}],
"BTC", 'filter_at_the_beginning'), # OperationalException expected
# ShuffleFilter after StaticPairList
([{"method": "StaticPairList"},
{"method": "ShuffleFilter", "seed": 42}],
"BTC", ['TKN/BTC', 'ETH/BTC', 'HOT/BTC']),
# ShuffleFilter only
([{"method": "ShuffleFilter", "seed": 42}],
"BTC", 'filter_at_the_beginning'), # OperationalException expected
# SpreadFilter after StaticPairList
([{"method": "StaticPairList"},
{"method": "SpreadFilter", "max_spread_ratio": 0.005}],
"BTC", ['ETH/BTC', 'TKN/BTC']),
# SpreadFilter only
([{"method": "SpreadFilter", "max_spread_ratio": 0.005}],
"BTC", 'filter_at_the_beginning'), # OperationalException expected
# Static Pairlist after VolumePairList, on a non-first position
([{"method": "VolumePairList", "number_assets": 5, "sort_key": "bidVolume"},
{"method": "StaticPairList"}],
"BTC", 'static_in_the_middle'),
])
def test_VolumePairList_whitelist_gen(mocker, whitelist_conf, shitcoinmarkets, tickers,
pairlists, base_currency, whitelist_result,
caplog) -> None:
ohlcv_history_list, pairlists, base_currency,
whitelist_result, caplog) -> None:
whitelist_conf['pairlists'] = pairlists
whitelist_conf['stake_currency'] = base_currency
mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
if whitelist_result == 'static_in_the_middle':
with pytest.raises(OperationalException,
match=r"StaticPairList can only be used in the first position "
r"in the list of Pairlist Handlers."):
freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
return
freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
mocker.patch.multiple('freqtrade.exchange.Exchange',
get_tickers=tickers,
markets=PropertyMock(return_value=shitcoinmarkets),
markets=PropertyMock(return_value=shitcoinmarkets)
)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_historic_ohlcv=MagicMock(return_value=ohlcv_history_list),
)
# Set whitelist_result to None if pairlist is invalid and should produce exception
if whitelist_result == 'filter_at_the_beginning':
with pytest.raises(OperationalException,
match=r"This Pairlist Handler should not be used at the first position "
r"in the list of Pairlist Handlers."):
freqtrade.pairlists.refresh_pairlist()
else:
freqtrade.pairlists.refresh_pairlist()
whitelist = freqtrade.pairlists.whitelist
@ -297,13 +387,17 @@ def test_VolumePairList_whitelist_gen(mocker, whitelist_conf, shitcoinmarkets, t
len(whitelist) == whitelist_result
for pairlist in pairlists:
if pairlist['method'] == 'AgeFilter' and pairlist['min_days_listed'] and \
len(ohlcv_history_list) <= pairlist['min_days_listed']:
assert log_has_re(r'^Removed .* from whitelist, because age is less than '
r'.* day.*', caplog)
if pairlist['method'] == 'PrecisionFilter' and whitelist_result:
assert log_has_re(r'^Removed .* from whitelist, because stop price .* '
r'would be <= stop limit.*', caplog)
if pairlist['method'] == 'PriceFilter' and whitelist_result:
assert (log_has_re(r'^Removed .* from whitelist, because 1 unit is .*%$', caplog) or
log_has_re(r"^Removed .* from whitelist, because ticker\['last'\] is empty.*",
caplog))
log_has_re(r"^Removed .* from whitelist, because ticker\['last'\] "
r"is empty.*", caplog))
if pairlist['method'] == 'VolumePairList':
logmsg = ("DEPRECATED: using any key other than quoteVolume for "
"VolumePairList is deprecated.")
@ -313,6 +407,17 @@ def test_VolumePairList_whitelist_gen(mocker, whitelist_conf, shitcoinmarkets, t
assert not log_has(logmsg, caplog)
def test_PrecisionFilter_error(mocker, whitelist_conf, tickers) -> None:
whitelist_conf['pairlists'] = [{"method": "StaticPairList"}, {"method": "PrecisionFilter"}]
del whitelist_conf['stoploss']
mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))
with pytest.raises(OperationalException,
match=r"PrecisionFilter can only work with stoploss defined\..*"):
PairListManager(MagicMock, whitelist_conf)
def test_gen_pair_whitelist_not_supported(mocker, default_conf, tickers) -> None:
default_conf['pairlists'] = [{'method': 'VolumePairList', 'number_assets': 10}]
@ -372,6 +477,23 @@ def test__whitelist_for_active_markets(mocker, whitelist_conf, markets, pairlist
assert log_message in caplog.text
@pytest.mark.parametrize("pairlist", AVAILABLE_PAIRLISTS)
def test__whitelist_for_active_markets_empty(mocker, whitelist_conf, markets, pairlist, tickers):
whitelist_conf['pairlists'][0]['method'] = pairlist
mocker.patch('freqtrade.exchange.Exchange.exchange_has', return_value=True)
freqtrade = get_patched_freqtradebot(mocker, whitelist_conf)
mocker.patch.multiple('freqtrade.exchange.Exchange',
markets=PropertyMock(return_value=None),
get_tickers=tickers
)
# Assign starting whitelist
pairlist_handler = freqtrade.pairlists._pairlist_handlers[0]
with pytest.raises(OperationalException, match=r'Markets not loaded.*'):
pairlist_handler._whitelist_for_active_markets(['ETH/BTC'])
def test_volumepairlist_invalid_sortvalue(mocker, markets, whitelist_conf):
whitelist_conf['pairlists'][0].update({"sort_key": "asdf"})
@ -402,6 +524,29 @@ def test_volumepairlist_caching(mocker, markets, whitelist_conf, tickers):
assert freqtrade.pairlists._pairlist_handlers[0]._last_refresh == lrf
def test_agefilter_caching(mocker, markets, whitelist_conf_3, tickers, ohlcv_history_list):
mocker.patch.multiple('freqtrade.exchange.Exchange',
markets=PropertyMock(return_value=markets),
exchange_has=MagicMock(return_value=True),
get_tickers=tickers
)
mocker.patch.multiple(
'freqtrade.exchange.Exchange',
get_historic_ohlcv=MagicMock(return_value=ohlcv_history_list),
)
freqtrade = get_patched_freqtradebot(mocker, whitelist_conf_3)
assert freqtrade.exchange.get_historic_ohlcv.call_count == 0
freqtrade.pairlists.refresh_pairlist()
assert freqtrade.exchange.get_historic_ohlcv.call_count > 0
previous_call_count = freqtrade.exchange.get_historic_ohlcv.call_count
freqtrade.pairlists.refresh_pairlist()
# Should not have increased since first call.
assert freqtrade.exchange.get_historic_ohlcv.call_count == previous_call_count
def test_pairlistmanager_no_pairlist(mocker, markets, whitelist_conf, caplog):
mocker.patch('freqtrade.exchange.Exchange.exchange_has', MagicMock(return_value=True))

92
tests/rpc/test_rpc.py
View File

@ -42,8 +42,12 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
rpc._rpc_trade_status()
freqtradebot.enter_positions()
trades = Trade.get_open_trades()
trades[0].open_order_id = None
freqtradebot.exit_positions(trades)
results = rpc._rpc_trade_status()
assert {
assert results[0] == {
'trade_id': 1,
'pair': 'ETH/BTC',
'base_currency': 'BTC',
@ -54,11 +58,11 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
'fee_open': ANY,
'fee_open_cost': ANY,
'fee_open_currency': ANY,
'fee_close': ANY,
'fee_close': fee.return_value,
'fee_close_cost': ANY,
'fee_close_currency': ANY,
'open_rate_requested': ANY,
'open_trade_price': ANY,
'open_trade_price': 0.0010025,
'close_rate_requested': ANY,
'sell_reason': ANY,
'sell_order_status': ANY,
@ -66,6 +70,7 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
'max_rate': ANY,
'strategy': ANY,
'ticker_interval': ANY,
'timeframe': ANY,
'open_order_id': ANY,
'close_date': None,
'close_date_hum': None,
@ -77,21 +82,35 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
'stake_amount': 0.001,
'close_profit': None,
'close_profit_pct': None,
'close_profit_abs': None,
'current_profit': -0.00408133,
'current_profit_pct': -0.41,
'stop_loss': 0.0,
'initial_stop_loss': 0.0,
'initial_stop_loss_pct': None,
'stop_loss_pct': None,
'open_order': '(limit buy rem=0.00000000)'
} == results[0]
'current_profit_abs': -4.09e-06,
'stop_loss': 9.882e-06,
'stop_loss_abs': 9.882e-06,
'stop_loss_pct': -10.0,
'stop_loss_ratio': -0.1,
'stoploss_order_id': None,
'stoploss_last_update': ANY,
'stoploss_last_update_timestamp': ANY,
'initial_stop_loss': 9.882e-06,
'initial_stop_loss_abs': 9.882e-06,
'initial_stop_loss_pct': -10.0,
'initial_stop_loss_ratio': -0.1,
'stoploss_current_dist': -1.1080000000000002e-06,
'stoploss_current_dist_ratio': -0.10081893,
'stoploss_entry_dist': -0.00010475,
'stoploss_entry_dist_ratio': -0.10448878,
'open_order': None,
'exchange': 'bittrex',
}
mocker.patch('freqtrade.freqtradebot.FreqtradeBot.get_sell_rate',
MagicMock(side_effect=DependencyException("Pair 'ETH/BTC' not available")))
results = rpc._rpc_trade_status()
assert isnan(results[0]['current_profit'])
assert isnan(results[0]['current_rate'])
assert {
assert results[0] == {
'trade_id': 1,
'pair': 'ETH/BTC',
'base_currency': 'BTC',
@ -102,7 +121,7 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
'fee_open': ANY,
'fee_open_cost': ANY,
'fee_open_currency': ANY,
'fee_close': ANY,
'fee_close': fee.return_value,
'fee_close_cost': ANY,
'fee_close_currency': ANY,
'open_rate_requested': ANY,
@ -114,6 +133,7 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
'max_rate': ANY,
'strategy': ANY,
'ticker_interval': ANY,
'timeframe': ANY,
'open_order_id': ANY,
'close_date': None,
'close_date_hum': None,
@ -125,14 +145,28 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
'stake_amount': 0.001,
'close_profit': None,
'close_profit_pct': None,
'close_profit_abs': None,
'current_profit': ANY,
'current_profit_pct': ANY,
'stop_loss': 0.0,
'initial_stop_loss': 0.0,
'initial_stop_loss_pct': None,
'stop_loss_pct': None,
'open_order': '(limit buy rem=0.00000000)'
} == results[0]
'current_profit_abs': ANY,
'stop_loss': 9.882e-06,
'stop_loss_abs': 9.882e-06,
'stop_loss_pct': -10.0,
'stop_loss_ratio': -0.1,
'stoploss_order_id': None,
'stoploss_last_update': ANY,
'stoploss_last_update_timestamp': ANY,
'initial_stop_loss': 9.882e-06,
'initial_stop_loss_abs': 9.882e-06,
'initial_stop_loss_pct': -10.0,
'initial_stop_loss_ratio': -0.1,
'stoploss_current_dist': ANY,
'stoploss_current_dist_ratio': ANY,
'stoploss_entry_dist': -0.00010475,
'stoploss_entry_dist_ratio': -0.10448878,
'open_order': None,
'exchange': 'bittrex',
}
def test_rpc_status_table(default_conf, ticker, fee, mocker) -> None:
@ -279,8 +313,12 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
rpc = RPC(freqtradebot)
rpc._fiat_converter = CryptoToFiatConverter()
with pytest.raises(RPCException, match=r'.*no closed trade*'):
rpc._rpc_trade_statistics(stake_currency, fiat_display_currency)
res = rpc._rpc_trade_statistics(stake_currency, fiat_display_currency)
assert res['trade_count'] == 0
assert res['first_trade_date'] == ''
assert res['first_trade_timestamp'] == 0
assert res['latest_trade_date'] == ''
assert res['latest_trade_timestamp'] == 0
# Create some test data
freqtradebot.enter_positions()
@ -556,7 +594,7 @@ def test_rpc_stopbuy(mocker, default_conf) -> None:
assert freqtradebot.config['max_open_trades'] != 0
result = rpc._rpc_stopbuy()
assert {'status': 'No more buy will occur from now. Run /reload_conf to reset.'} == result
assert {'status': 'No more buy will occur from now. Run /reload_config to reset.'} == result
assert freqtradebot.config['max_open_trades'] == 0
@ -833,6 +871,20 @@ def test_rpc_blacklist(mocker, default_conf) -> None:
assert ret['blacklist'] == default_conf['exchange']['pair_blacklist']
assert ret['blacklist'] == ['DOGE/BTC', 'HOT/BTC', 'ETH/BTC']
ret = rpc._rpc_blacklist(["ETH/BTC"])
assert 'errors' in ret
assert isinstance(ret['errors'], dict)
assert ret['errors']['ETH/BTC']['error_msg'] == 'Pair ETH/BTC already in pairlist.'
ret = rpc._rpc_blacklist(["ETH/ETH"])
assert 'StaticPairList' in ret['method']
assert len(ret['blacklist']) == 3
assert ret['blacklist'] == default_conf['exchange']['pair_blacklist']
assert ret['blacklist'] == ['DOGE/BTC', 'HOT/BTC', 'ETH/BTC']
assert 'errors' in ret
assert isinstance(ret['errors'], dict)
assert ret['errors']['ETH/ETH']['error_msg'] == 'Pair ETH/ETH does not match stake currency.'
def test_rpc_edge_disabled(mocker, default_conf) -> None:
mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())

106
tests/rpc/test_rpc_apiserver.py
View File

@ -24,6 +24,7 @@ def botclient(default_conf, mocker):
default_conf.update({"api_server": {"enabled": True,
"listen_ip_address": "127.0.0.1",
"listen_port": 8080,
"CORS_origins": ['http://example.com'],
"username": _TEST_USER,
"password": _TEST_PASS,
}})
@ -40,13 +41,13 @@ def client_post(client, url, data={}):
content_type="application/json",
data=data,
headers={'Authorization': _basic_auth_str(_TEST_USER, _TEST_PASS),
'Origin': 'example.com'})
'Origin': 'http://example.com'})
def client_get(client, url):
# Add fake Origin to ensure CORS kicks in
return client.get(url, headers={'Authorization': _basic_auth_str(_TEST_USER, _TEST_PASS),
'Origin': 'example.com'})
'Origin': 'http://example.com'})
def assert_response(response, expected_code=200, needs_cors=True):
@ -54,6 +55,7 @@ def assert_response(response, expected_code=200, needs_cors=True):
assert response.content_type == "application/json"
if needs_cors:
assert ('Access-Control-Allow-Credentials', 'true') in response.headers._list
assert ('Access-Control-Allow-Origin', 'http://example.com') in response.headers._list
def test_api_not_found(botclient):
@ -110,7 +112,7 @@ def test_api_token_login(botclient):
rc = client.get(f"{BASE_URI}/count",
content_type="application/json",
headers={'Authorization': f'Bearer {rc.json["access_token"]}',
'Origin': 'example.com'})
'Origin': 'http://example.com'})
assert_response(rc)
@ -122,7 +124,7 @@ def test_api_token_refresh(botclient):
content_type="application/json",
data=None,
headers={'Authorization': f'Bearer {rc.json["refresh_token"]}',
'Origin': 'example.com'})
'Origin': 'http://example.com'})
assert_response(rc)
assert 'access_token' in rc.json
assert 'refresh_token' not in rc.json
@ -251,10 +253,10 @@ def test_api_cleanup(default_conf, mocker, caplog):
def test_api_reloadconf(botclient):
ftbot, client = botclient
rc = client_post(client, f"{BASE_URI}/reload_conf")
rc = client_post(client, f"{BASE_URI}/reload_config")
assert_response(rc)
assert rc.json == {'status': 'reloading config ...'}
assert ftbot.state == State.RELOAD_CONF
assert ftbot.state == State.RELOAD_CONFIG
def test_api_stopbuy(botclient):
@ -263,7 +265,7 @@ def test_api_stopbuy(botclient):
rc = client_post(client, f"{BASE_URI}/stopbuy")
assert_response(rc)
assert rc.json == {'status': 'No more buy will occur from now. Run /reload_conf to reset.'}
assert rc.json == {'status': 'No more buy will occur from now. Run /reload_config to reset.'}
assert ftbot.config['max_open_trades'] == 0
@ -323,8 +325,11 @@ def test_api_show_config(botclient, mocker):
assert 'dry_run' in rc.json
assert rc.json['exchange'] == 'bittrex'
assert rc.json['ticker_interval'] == '5m'
assert rc.json['timeframe'] == '5m'
assert rc.json['state'] == 'running'
assert not rc.json['trailing_stop']
assert 'bid_strategy' in rc.json
assert 'ask_strategy' in rc.json
def test_api_daily(botclient, mocker, ticker, fee, markets):
@ -396,9 +401,8 @@ def test_api_profit(botclient, mocker, ticker, fee, markets, limit_buy_order, li
)
rc = client_get(client, f"{BASE_URI}/profit")
assert_response(rc, 502)
assert len(rc.json) == 1
assert rc.json == {"error": "Error querying _profit: no closed trade"}
assert_response(rc, 200)
assert rc.json['trade_count'] == 0
ftbot.enter_positions()
trade = Trade.query.first()
@ -406,8 +410,11 @@ def test_api_profit(botclient, mocker, ticker, fee, markets, limit_buy_order, li
# Simulate fulfilled LIMIT_BUY order for trade
trade.update(limit_buy_order)
rc = client_get(client, f"{BASE_URI}/profit")
assert_response(rc, 502)
assert rc.json == {"error": "Error querying _profit: no closed trade"}
assert_response(rc, 200)
# One open trade
assert rc.json['trade_count'] == 1
assert rc.json['best_pair'] == ''
assert rc.json['best_rate'] == 0
trade.update(limit_sell_order)
@ -426,10 +433,19 @@ def test_api_profit(botclient, mocker, ticker, fee, markets, limit_buy_order, li
'profit_all_coin': 6.217e-05,
'profit_all_fiat': 0,
'profit_all_percent': 6.2,
'profit_all_percent_mean': 6.2,
'profit_all_ratio_mean': 0.06201058,
'profit_all_percent_sum': 6.2,
'profit_all_ratio_sum': 0.06201058,
'profit_closed_coin': 6.217e-05,
'profit_closed_fiat': 0,
'profit_closed_percent': 6.2,
'trade_count': 1
'profit_closed_ratio_mean': 0.06201058,
'profit_closed_percent_mean': 6.2,
'profit_closed_ratio_sum': 0.06201058,
'profit_closed_percent_sum': 6.2,
'trade_count': 1,
'closed_trade_count': 1,
}
@ -492,6 +508,10 @@ def test_api_status(botclient, mocker, ticker, fee, markets):
assert rc.json == []
ftbot.enter_positions()
trades = Trade.get_open_trades()
trades[0].open_order_id = None
ftbot.exit_positions(trades)
rc = client_get(client, f"{BASE_URI}/status")
assert_response(rc)
assert len(rc.json) == 1
@ -502,21 +522,34 @@ def test_api_status(botclient, mocker, ticker, fee, markets):
'close_timestamp': None,
'close_profit': None,
'close_profit_pct': None,
'close_profit_abs': None,
'close_rate': None,
'current_profit': -0.00408133,
'current_profit_pct': -0.41,
'current_profit_abs': -4.09e-06,
'current_rate': 1.099e-05,
'initial_stop_loss': 0.0,
'initial_stop_loss_pct': None,
'open_date': ANY,
'open_date_hum': 'just now',
'open_timestamp': ANY,
'open_order': '(limit buy rem=0.00000000)',
'open_order': None,
'open_rate': 1.098e-05,
'pair': 'ETH/BTC',
'stake_amount': 0.001,
'stop_loss': 0.0,
'stop_loss_pct': None,
'stop_loss': 9.882e-06,
'stop_loss_abs': 9.882e-06,
'stop_loss_pct': -10.0,
'stop_loss_ratio': -0.1,
'stoploss_order_id': None,
'stoploss_last_update': ANY,
'stoploss_last_update_timestamp': ANY,
'initial_stop_loss': 9.882e-06,
'initial_stop_loss_abs': 9.882e-06,
'initial_stop_loss_pct': -10.0,
'initial_stop_loss_ratio': -0.1,
'stoploss_current_dist': -1.1080000000000002e-06,
'stoploss_current_dist_ratio': -0.10081893,
'stoploss_entry_dist': -0.00010475,
'stoploss_entry_dist_ratio': -0.10448878,
'trade_id': 1,
'close_rate_requested': None,
'current_rate': 1.099e-05,
@ -528,15 +561,18 @@ def test_api_status(botclient, mocker, ticker, fee, markets):
'fee_open_currency': None,
'open_date': ANY,
'is_open': True,
'max_rate': 0.0,
'min_rate': None,
'open_order_id': ANY,
'max_rate': 1.099e-05,
'min_rate': 1.098e-05,
'open_order_id': None,
'open_rate_requested': 1.098e-05,
'open_trade_price': 0.0010025,
'sell_reason': None,
'sell_order_status': None,
'strategy': 'DefaultStrategy',
'ticker_interval': 5}]
'ticker_interval': 5,
'timeframe': 5,
'exchange': 'bittrex',
}]
def test_api_version(botclient):
@ -554,7 +590,9 @@ def test_api_blacklist(botclient, mocker):
assert_response(rc)
assert rc.json == {"blacklist": ["DOGE/BTC", "HOT/BTC"],
"length": 2,
"method": ["StaticPairList"]}
"method": ["StaticPairList"],
"errors": {},
}
# Add ETH/BTC to blacklist
rc = client_post(client, f"{BASE_URI}/blacklist",
@ -562,7 +600,9 @@ def test_api_blacklist(botclient, mocker):
assert_response(rc)
assert rc.json == {"blacklist": ["DOGE/BTC", "HOT/BTC", "ETH/BTC"],
"length": 3,
"method": ["StaticPairList"]}
"method": ["StaticPairList"],
"errors": {},
}
def test_api_whitelist(botclient):
@ -613,12 +653,11 @@ def test_api_forcebuy(botclient, mocker, fee):
data='{"pair": "ETH/BTC"}')
assert_response(rc)
assert rc.json == {'amount': 1,
'trade_id': None,
'close_date': None,
'close_date_hum': None,
'close_timestamp': None,
'close_rate': 0.265441,
'initial_stop_loss': None,
'initial_stop_loss_pct': None,
'open_date': ANY,
'open_date_hum': 'just now',
'open_timestamp': ANY,
@ -626,9 +665,18 @@ def test_api_forcebuy(botclient, mocker, fee):
'pair': 'ETH/ETH',
'stake_amount': 1,
'stop_loss': None,
'stop_loss_abs': None,
'stop_loss_pct': None,
'trade_id': None,
'stop_loss_ratio': None,
'stoploss_order_id': None,
'stoploss_last_update': None,
'stoploss_last_update_timestamp': None,
'initial_stop_loss': None,
'initial_stop_loss_abs': None,
'initial_stop_loss_pct': None,
'initial_stop_loss_ratio': None,
'close_profit': None,
'close_profit_abs': None,
'close_rate_requested': None,
'fee_close': 0.0025,
'fee_close_cost': None,
@ -645,7 +693,9 @@ def test_api_forcebuy(botclient, mocker, fee):
'sell_reason': None,
'sell_order_status': None,
'strategy': None,
'ticker_interval': None
'ticker_interval': None,
'timeframe': None,
'exchange': 'bittrex',
}

115
tests/rpc/test_rpc_telegram.py
View File

@ -71,10 +71,11 @@ def test_init(default_conf, mocker, caplog) -> None:
assert start_polling.dispatcher.add_handler.call_count > 0
assert start_polling.start_polling.call_count == 1
message_str = "rpc.telegram is listening for following commands: [['status'], ['profit'], " \
"['balance'], ['start'], ['stop'], ['forcesell'], ['forcebuy'], " \
"['performance'], ['daily'], ['count'], ['reload_conf'], ['show_config'], " \
"['stopbuy'], ['whitelist'], ['blacklist'], ['edge'], ['help'], ['version']]"
message_str = ("rpc.telegram is listening for following commands: [['status'], ['profit'], "
"['balance'], ['start'], ['stop'], ['forcesell'], ['forcebuy'], "
"['performance'], ['daily'], ['count'], ['reload_config', 'reload_conf'], "
"['show_config', 'show_conf'], ['stopbuy'], ['whitelist'], ['blacklist'], "
"['edge'], ['help'], ['version']]")
assert log_has(message_str, caplog)
@ -420,7 +421,7 @@ def test_profit_handle(default_conf, update, ticker, ticker_sell_up, fee,
telegram._profit(update=update, context=MagicMock())
assert msg_mock.call_count == 1
assert 'no closed trade' in msg_mock.call_args_list[0][0][0]
assert 'No trades yet.' in msg_mock.call_args_list[0][0][0]
msg_mock.reset_mock()
# Create some test data
@ -432,7 +433,10 @@ def test_profit_handle(default_conf, update, ticker, ticker_sell_up, fee,
telegram._profit(update=update, context=MagicMock())
assert msg_mock.call_count == 1
assert 'no closed trade' in msg_mock.call_args_list[-1][0][0]
assert 'No closed trade' in msg_mock.call_args_list[-1][0][0]
assert '*ROI:* All trades' in msg_mock.call_args_list[-1][0][0]
assert ('∙ `-0.00000500 BTC (-0.50%) (-0.5 \N{GREEK CAPITAL LETTER SIGMA}%)`'
in msg_mock.call_args_list[-1][0][0])
msg_mock.reset_mock()
# Update the ticker with a market going up
@ -444,11 +448,13 @@ def test_profit_handle(default_conf, update, ticker, ticker_sell_up, fee,
telegram._profit(update=update, context=MagicMock())
assert msg_mock.call_count == 1
assert '*ROI:* Close trades' in msg_mock.call_args_list[-1][0][0]
assert '∙ `0.00006217 BTC (6.20%)`' in msg_mock.call_args_list[-1][0][0]
assert '*ROI:* Closed trades' in msg_mock.call_args_list[-1][0][0]
assert ('∙ `0.00006217 BTC (6.20%) (6.2 \N{GREEK CAPITAL LETTER SIGMA}%)`'
in msg_mock.call_args_list[-1][0][0])
assert '∙ `0.933 USD`' in msg_mock.call_args_list[-1][0][0]
assert '*ROI:* All trades' in msg_mock.call_args_list[-1][0][0]
assert '∙ `0.00006217 BTC (6.20%)`' in msg_mock.call_args_list[-1][0][0]
assert ('∙ `0.00006217 BTC (6.20%) (6.2 \N{GREEK CAPITAL LETTER SIGMA}%)`'
in msg_mock.call_args_list[-1][0][0])
assert '∙ `0.933 USD`' in msg_mock.call_args_list[-1][0][0]
assert '*Best Performing:* `ETH/BTC: 6.20%`' in msg_mock.call_args_list[-1][0][0]
@ -661,11 +667,11 @@ def test_stopbuy_handle(default_conf, update, mocker) -> None:
telegram._stopbuy(update=update, context=MagicMock())
assert freqtradebot.config['max_open_trades'] == 0
assert msg_mock.call_count == 1
assert 'No more buy will occur from now. Run /reload_conf to reset.' \
assert 'No more buy will occur from now. Run /reload_config to reset.' \
in msg_mock.call_args_list[0][0][0]
def test_reload_conf_handle(default_conf, update, mocker) -> None:
def test_reload_config_handle(default_conf, update, mocker) -> None:
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
@ -678,8 +684,8 @@ def test_reload_conf_handle(default_conf, update, mocker) -> None:
freqtradebot.state = State.RUNNING
assert freqtradebot.state == State.RUNNING
telegram._reload_conf(update=update, context=MagicMock())
assert freqtradebot.state == State.RELOAD_CONF
telegram._reload_config(update=update, context=MagicMock())
assert freqtradebot.state == State.RELOAD_CONFIG
assert msg_mock.call_count == 1
assert 'reloading config' in msg_mock.call_args_list[0][0][0]
@ -1011,9 +1017,8 @@ def test_count_handle(default_conf, update, ticker, fee, mocker) -> None:
msg_mock.reset_mock()
telegram._count(update=update, context=MagicMock())
msg = '<pre> current max total stake\n--------- ----- -------------\n' \
' 1 {} {}</pre>'\
.format(
msg = ('<pre> current max total stake\n--------- ----- -------------\n'
' 1 {} {}</pre>').format(
default_conf['max_open_trades'],
default_conf['stake_amount']
)
@ -1085,6 +1090,18 @@ def test_blacklist_static(default_conf, update, mocker) -> None:
in msg_mock.call_args_list[0][0][0])
assert freqtradebot.pairlists.blacklist == ["DOGE/BTC", "HOT/BTC", "ETH/BTC"]
msg_mock.reset_mock()
context = MagicMock()
context.args = ["ETH/ETH"]
telegram._blacklist(update=update, context=context)
assert msg_mock.call_count == 2
assert ("Error adding `ETH/ETH` to blacklist: `Pair ETH/ETH does not match stake currency.`"
in msg_mock.call_args_list[0][0][0])
assert ("Blacklist contains 3 pairs\n`DOGE/BTC, HOT/BTC, ETH/BTC`"
in msg_mock.call_args_list[1][0][0])
assert freqtradebot.pairlists.blacklist == ["DOGE/BTC", "HOT/BTC", "ETH/BTC"]
def test_edge_disabled(default_conf, update, mocker) -> None:
msg_mock = MagicMock()
@ -1208,7 +1225,7 @@ def test_send_msg_buy_notification(default_conf, mocker) -> None:
'open_date': arrow.utcnow().shift(hours=-1)
})
assert msg_mock.call_args[0][0] \
== '*Bittrex:* Buying ETH/BTC\n' \
== '\N{LARGE BLUE CIRCLE} *Bittrex:* Buying ETH/BTC\n' \
'*Amount:* `1333.33333333`\n' \
'*Open Rate:* `0.00001099`\n' \
'*Current Rate:* `0.00001099`\n' \
@ -1230,7 +1247,7 @@ def test_send_msg_buy_cancel_notification(default_conf, mocker) -> None:
'pair': 'ETH/BTC',
})
assert msg_mock.call_args[0][0] \
== ('*Bittrex:* Cancelling Open Buy Order for ETH/BTC')
== ('\N{WARNING SIGN} *Bittrex:* Cancelling Open Buy Order for ETH/BTC')
def test_send_msg_sell_notification(default_conf, mocker) -> None:
@ -1263,7 +1280,7 @@ def test_send_msg_sell_notification(default_conf, mocker) -> None:
'close_date': arrow.utcnow(),
})
assert msg_mock.call_args[0][0] \
== ('*Binance:* Selling KEY/ETH\n'
== ('\N{WARNING SIGN} *Binance:* Selling KEY/ETH\n'
'*Amount:* `1333.33333333`\n'
'*Open Rate:* `0.00007500`\n'
'*Current Rate:* `0.00003201`\n'
@ -1291,7 +1308,7 @@ def test_send_msg_sell_notification(default_conf, mocker) -> None:
'close_date': arrow.utcnow(),
})
assert msg_mock.call_args[0][0] \
== ('*Binance:* Selling KEY/ETH\n'
== ('\N{WARNING SIGN} *Binance:* Selling KEY/ETH\n'
'*Amount:* `1333.33333333`\n'
'*Open Rate:* `0.00007500`\n'
'*Current Rate:* `0.00003201`\n'
@ -1321,7 +1338,8 @@ def test_send_msg_sell_cancel_notification(default_conf, mocker) -> None:
'reason': 'Cancelled on exchange'
})
assert msg_mock.call_args[0][0] \
== ('*Binance:* Cancelling Open Sell Order for KEY/ETH. Reason: Cancelled on exchange')
== ('\N{WARNING SIGN} *Binance:* Cancelling Open Sell Order for KEY/ETH. '
'Reason: Cancelled on exchange')
msg_mock.reset_mock()
telegram.send_msg({
@ -1331,7 +1349,7 @@ def test_send_msg_sell_cancel_notification(default_conf, mocker) -> None:
'reason': 'timeout'
})
assert msg_mock.call_args[0][0] \
== ('*Binance:* Cancelling Open Sell Order for KEY/ETH. Reason: timeout')
== ('\N{WARNING SIGN} *Binance:* Cancelling Open Sell Order for KEY/ETH. Reason: timeout')
# Reset singleton function to avoid random breaks
telegram._fiat_converter.convert_amount = old_convamount
@ -1365,7 +1383,7 @@ def test_warning_notification(default_conf, mocker) -> None:
'type': RPCMessageType.WARNING_NOTIFICATION,
'status': 'message'
})
assert msg_mock.call_args[0][0] == '*Warning:* `message`'
assert msg_mock.call_args[0][0] == '\N{WARNING SIGN} *Warning:* `message`'
def test_custom_notification(default_conf, mocker) -> None:
@ -1423,12 +1441,11 @@ def test_send_msg_buy_notification_no_fiat(default_conf, mocker) -> None:
'amount': 1333.3333333333335,
'open_date': arrow.utcnow().shift(hours=-1)
})
assert msg_mock.call_args[0][0] \
== '*Bittrex:* Buying ETH/BTC\n' \
'*Amount:* `1333.33333333`\n' \
'*Open Rate:* `0.00001099`\n' \
'*Current Rate:* `0.00001099`\n' \
'*Total:* `(0.001000 BTC)`'
assert msg_mock.call_args[0][0] == ('\N{LARGE BLUE CIRCLE} *Bittrex:* Buying ETH/BTC\n'
'*Amount:* `1333.33333333`\n'
'*Open Rate:* `0.00001099`\n'
'*Current Rate:* `0.00001099`\n'
'*Total:* `(0.001000 BTC)`')
def test_send_msg_sell_notification_no_fiat(default_conf, mocker) -> None:
@ -1459,15 +1476,37 @@ def test_send_msg_sell_notification_no_fiat(default_conf, mocker) -> None:
'open_date': arrow.utcnow().shift(hours=-2, minutes=-35, seconds=-3),
'close_date': arrow.utcnow(),
})
assert msg_mock.call_args[0][0] \
== '*Binance:* Selling KEY/ETH\n' \
'*Amount:* `1333.33333333`\n' \
'*Open Rate:* `0.00007500`\n' \
'*Current Rate:* `0.00003201`\n' \
'*Close Rate:* `0.00003201`\n' \
'*Sell Reason:* `stop_loss`\n' \
'*Duration:* `2:35:03 (155.1 min)`\n' \
'*Profit:* `-57.41%`'
assert msg_mock.call_args[0][0] == ('\N{WARNING SIGN} *Binance:* Selling KEY/ETH\n'
'*Amount:* `1333.33333333`\n'
'*Open Rate:* `0.00007500`\n'
'*Current Rate:* `0.00003201`\n'
'*Close Rate:* `0.00003201`\n'
'*Sell Reason:* `stop_loss`\n'
'*Duration:* `2:35:03 (155.1 min)`\n'
'*Profit:* `-57.41%`')
@pytest.mark.parametrize('msg,expected', [
({'profit_percent': 20.1, 'sell_reason': 'roi'}, "\N{ROCKET}"),
({'profit_percent': 5.1, 'sell_reason': 'roi'}, "\N{ROCKET}"),
({'profit_percent': 2.56, 'sell_reason': 'roi'}, "\N{EIGHT SPOKED ASTERISK}"),
({'profit_percent': 1.0, 'sell_reason': 'roi'}, "\N{EIGHT SPOKED ASTERISK}"),
({'profit_percent': 0.0, 'sell_reason': 'roi'}, "\N{EIGHT SPOKED ASTERISK}"),
({'profit_percent': -5.0, 'sell_reason': 'stop_loss'}, "\N{WARNING SIGN}"),
({'profit_percent': -2.0, 'sell_reason': 'sell_signal'}, "\N{CROSS MARK}"),
])
def test__sell_emoji(default_conf, mocker, msg, expected):
del default_conf['fiat_display_currency']
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.rpc.telegram.Telegram',
_init=MagicMock(),
_send_msg=msg_mock
)
freqtradebot = get_patched_freqtradebot(mocker, default_conf)
telegram = Telegram(freqtradebot)
assert telegram._get_sell_emoji(msg) == expected
def test__send_msg(default_conf, mocker) -> None:

Some files were not shown because too many files have changed in this diff Show More