mirror of
https://github.com/freqtrade/freqtrade.git
synced 2024-11-10 02:12:01 +00:00
Matthias
GitHub
commit
046ae18411
4
.github/workflows/ci.yml
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4
.github/workflows/ci.yml
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@ -351,7 +351,7 @@ jobs:
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python setup.py sdist bdist_wheel
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- name: Publish to PyPI (Test)
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uses: pypa/gh-action-pypi-publish@master
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uses: pypa/gh-action-pypi-publish@v1.5.0
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if: (github.event_name == 'release')
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with:
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user: __token__
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@ -359,7 +359,7 @@ jobs:
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repository_url: https://test.pypi.org/legacy/
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- name: Publish to PyPI
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uses: pypa/gh-action-pypi-publish@master
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uses: pypa/gh-action-pypi-publish@v1.5.0
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if: (github.event_name == 'release')
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with:
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user: __token__
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2
.gitignore
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2
.gitignore
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@ -80,6 +80,8 @@ instance/
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# Sphinx documentation
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docs/_build/
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# Mkdocs documentation
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site/
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# PyBuilder
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target/
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@ -15,9 +15,9 @@ repos:
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additional_dependencies:
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- types-cachetools==5.2.1
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- types-filelock==3.2.7
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- types-requests==2.28.0
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- types-requests==2.28.3
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- types-tabulate==0.8.11
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- types-python-dateutil==2.8.18
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- types-python-dateutil==2.8.19
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# stages: [push]
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- repo: https://github.com/pycqa/isort
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@ -155,7 +155,8 @@
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"entry_cancel": "on",
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"exit_cancel": "on",
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"protection_trigger": "off",
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"protection_trigger_global": "on"
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"protection_trigger_global": "on",
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"show_candle": "off"
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},
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"reload": true,
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"balance_dust_level": 0.01
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@ -116,6 +116,9 @@ This is similar to using multiple `--config` parameters, but simpler in usage as
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The table below will list all configuration parameters available.
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Freqtrade can also load many options via command line (CLI) arguments (check out the commands `--help` output for details).
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### Configuration option prevalence
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The prevalence for all Options is as follows:
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- CLI arguments override any other option
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@ -123,6 +126,8 @@ The prevalence for all Options is as follows:
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- Configuration files are used in sequence (the last file wins) and override Strategy configurations.
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- Strategy configurations are only used if they are not set via configuration or command-line arguments. These options are marked with [Strategy Override](#parameters-in-the-strategy) in the below table.
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### Parameters table
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Mandatory parameters are marked as **Required**, which means that they are required to be set in one of the possible ways.
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| Parameter | Description |
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@ -135,7 +140,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
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| `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
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| `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)
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| `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.
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| `timeframe` | The timeframe to use (e.g `1m`, `5m`, `15m`, `30m`, `1h` ...). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** String
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| `timeframe` | The timeframe to use (e.g `1m`, `5m`, `15m`, `30m`, `1h` ...). Usually missing in configuration, and specified in the strategy. [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** String
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| `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
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| `dry_run` | **Required.** Define if the bot must be in Dry Run or production mode. <br>*Defaults to `true`.* <br> **Datatype:** Boolean
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| `dry_run_wallet` | Define the starting amount in stake currency for the simulated wallet used by the bot running in Dry Run mode.<br>*Defaults to `1000`.* <br> **Datatype:** Float
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@ -148,13 +153,16 @@ Mandatory parameters are marked as **Required**, which means that they are requi
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| `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#trailing-stop-loss-only-once-the-trade-has-reached-a-certain-offset). [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `0.0` (no offset).* <br> **Datatype:** Float
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| `trailing_only_offset_is_reached` | Only apply trailing stoploss when the offset is reached. [stoploss documentation](stoploss.md). [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
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| `fee` | Fee used during backtesting / dry-runs. Should normally not be configured, which has freqtrade fall back to the exchange default fee. Set as ratio (e.g. 0.001 = 0.1%). Fee is applied twice for each trade, once when buying, once when selling. <br> **Datatype:** Float (as ratio)
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| `futures_funding_rate` | User-specified funding rate to be used when historical funding rates are not available from the exchange. This does not overwrite real historical rates. It is recommended that this be set to 0 unless you are testing a specific coin and you understand how the funding rate will affect freqtrade's profit calculations. [More information here](leverage.md#unavailable-funding-rates) <br>*Defaults to None.*<br> **Datatype:** Float
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| `trading_mode` | Specifies if you want to trade regularly, trade with leverage, or trade contracts whose prices are derived from matching cryptocurrency prices. [leverage documentation](leverage.md). <br>*Defaults to `"spot"`.* <br> **Datatype:** String
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| `margin_mode` | When trading with leverage, this determines if the collateral owned by the trader will be shared or isolated to each trading pair [leverage documentation](leverage.md). <br> **Datatype:** String
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| `liquidation_buffer` | A ratio specifying how large of a safety net to place between the liquidation price and the stoploss to prevent a position from reaching the liquidation price [leverage documentation](leverage.md). <br>*Defaults to `0.05`.* <br> **Datatype:** Float
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| | **Unfilled timeout**
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| `unfilledtimeout.entry` | **Required.** How long (in minutes or seconds) the bot will wait for an unfilled entry order to complete, after which the order will be cancelled and repeated at current (new) price, as long as there is a signal. [Strategy Override](#parameters-in-the-strategy).<br> **Datatype:** Integer
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| `unfilledtimeout.exit` | **Required.** How long (in minutes or seconds) the bot will wait for an unfilled exit order to complete, after which the order will be cancelled and repeated at current (new) price, as long as there is a signal. [Strategy Override](#parameters-in-the-strategy).<br> **Datatype:** Integer
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| `unfilledtimeout.unit` | Unit to use in unfilledtimeout setting. Note: If you set unfilledtimeout.unit to "seconds", "internals.process_throttle_secs" must be inferior or equal to timeout [Strategy Override](#parameters-in-the-strategy). <br> *Defaults to `minutes`.* <br> **Datatype:** String
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| `unfilledtimeout.exit_timeout_count` | How many times can exit orders time out. Once this number of timeouts is reached, an emergency exit is triggered. 0 to disable and allow unlimited order cancels. [Strategy Override](#parameters-in-the-strategy).<br>*Defaults to `0`.* <br> **Datatype:** Integer
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| | **Pricing**
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| `entry_pricing.price_side` | Select the side of the spread the bot should look at to get the entry rate. [More information below](#buy-price-side).<br> *Defaults to `same`.* <br> **Datatype:** String (either `ask`, `bid`, `same` or `other`).
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| `entry_pricing.price_last_balance` | **Required.** Interpolate the bidding price. More information [below](#entry-price-without-orderbook-enabled).
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| `entry_pricing.use_order_book` | Enable entering using the rates in [Order Book Entry](#entry-price-with-orderbook-enabled). <br> *Defaults to `True`.*<br> **Datatype:** Boolean
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@ -165,6 +173,8 @@ Mandatory parameters are marked as **Required**, which means that they are requi
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| `exit_pricing.price_last_balance` | Interpolate the exiting price. More information [below](#exit-price-without-orderbook-enabled).
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| `exit_pricing.use_order_book` | Enable exiting of open trades using [Order Book Exit](#exit-price-with-orderbook-enabled). <br> *Defaults to `True`.*<br> **Datatype:** Boolean
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| `exit_pricing.order_book_top` | Bot will use the top N rate in Order Book "price_side" to exit. I.e. a value of 2 will allow the bot to pick the 2nd ask rate in [Order Book Exit](#exit-price-with-orderbook-enabled)<br>*Defaults to `1`.* <br> **Datatype:** Positive Integer
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| `custom_price_max_distance_ratio` | Configure maximum distance ratio between current and custom entry or exit price. <br>*Defaults to `0.02` 2%).*<br> **Datatype:** Positive float
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| | **TODO**
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| `use_exit_signal` | Use exit signals produced by the strategy in addition to the `minimal_roi`. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `true`.* <br> **Datatype:** Boolean
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| `exit_profit_only` | Wait until the bot reaches `exit_profit_offset` before taking an exit decision. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.* <br> **Datatype:** Boolean
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| `exit_profit_offset` | Exit-signal is only active above this value. Only active in combination with `exit_profit_only=True`. [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `0.0`.* <br> **Datatype:** Float (as ratio)
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@ -172,8 +182,9 @@ Mandatory parameters are marked as **Required**, which means that they are requi
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| `ignore_buying_expired_candle_after` | Specifies the number of seconds until a buy signal is no longer used. <br> **Datatype:** Integer
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| `order_types` | Configure order-types depending on the action (`"entry"`, `"exit"`, `"stoploss"`, `"stoploss_on_exchange"`). [More information below](#understand-order_types). [Strategy Override](#parameters-in-the-strategy).<br> **Datatype:** Dict
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| `order_time_in_force` | Configure time in force for entry and exit orders. [More information below](#understand-order_time_in_force). [Strategy Override](#parameters-in-the-strategy). <br> **Datatype:** Dict
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| `custom_price_max_distance_ratio` | Configure maximum distance ratio between current and custom entry or exit price. <br>*Defaults to `0.02` 2%).*<br> **Datatype:** Positive float
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| `recursive_strategy_search` | Set to `true` to recursively search sub-directories inside `user_data/strategies` for a strategy. <br> **Datatype:** Boolean
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| `position_adjustment_enable` | Enables the strategy to use position adjustments (additional buys or sells). [More information here](strategy-callbacks.md#adjust-trade-position). <br> [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.*<br> **Datatype:** Boolean
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| `max_entry_position_adjustment` | Maximum additional order(s) for each open trade on top of the first entry Order. Set it to `-1` for unlimited additional orders. [More information here](strategy-callbacks.md#adjust-trade-position). <br> [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `-1`.*<br> **Datatype:** Positive Integer or -1
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| | **Exchange**
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| `exchange.name` | **Required.** Name of the exchange class to use. [List below](#user-content-what-values-for-exchangename). <br> **Datatype:** String
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| `exchange.sandbox` | Use the 'sandbox' version of the exchange, where the exchange provides a sandbox for risk-free integration. See [here](sandbox-testing.md) in more details.<br> **Datatype:** Boolean
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| `exchange.key` | API key to use for the exchange. Only required when you are in production mode.<br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
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@ -190,14 +201,19 @@ Mandatory parameters are marked as **Required**, which means that they are requi
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| `exchange.skip_open_order_update` | Skips open order updates on startup should the exchange cause problems. Only relevant in live conditions.<br>*Defaults to `false`<br> **Datatype:** Boolean
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| `exchange.unknown_fee_rate` | Fallback value to use when calculating trading fees. This can be useful for exchanges which have fees in non-tradable currencies. The value provided here will be multiplied with the "fee cost".<br>*Defaults to `None`<br> **Datatype:** float
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| `exchange.log_responses` | Log relevant exchange responses. For debug mode only - use with care.<br>*Defaults to `false`<br> **Datatype:** Boolean
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| `edge.*` | Please refer to [edge configuration document](edge.md) for detailed explanation.
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| `experimental.block_bad_exchanges` | Block exchanges known to not work with freqtrade. Leave on default unless you want to test if that exchange works now. <br>*Defaults to `true`.* <br> **Datatype:** Boolean
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| | **Plugins**
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| `edge.*` | Please refer to [edge configuration document](edge.md) for detailed explanation of all possible configuration options.
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| `pairlists` | Define one or more pairlists to be used. [More information](plugins.md#pairlists-and-pairlist-handlers). <br>*Defaults to `StaticPairList`.* <br> **Datatype:** List of Dicts
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| `protections` | Define one or more protections to be used. [More information](plugins.md#protections). <br> **Datatype:** List of Dicts
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| | **Telegram**
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| `telegram.enabled` | Enable the usage of Telegram. <br> **Datatype:** Boolean
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| `telegram.token` | Your Telegram bot token. Only required if `telegram.enabled` is `true`. <br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
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| `telegram.chat_id` | Your personal Telegram account id. Only required if `telegram.enabled` is `true`. <br>**Keep it in secret, do not disclose publicly.** <br> **Datatype:** String
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| `telegram.balance_dust_level` | Dust-level (in stake currency) - currencies with a balance below this will not be shown by `/balance`. <br> **Datatype:** float
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| `telegram.reload` | Allow "reload" buttons on telegram messages. <br>*Defaults to `True`.<br> **Datatype:** boolean
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| `telegram.notification_settings.*` | Detailed notification settings. Refer to the [telegram documentation](telegram-usage.md) for details.<br> **Datatype:** dictionary
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| | **Webhook**
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| `webhook.enabled` | Enable usage of Webhook notifications <br> **Datatype:** Boolean
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| `webhook.url` | URL for the webhook. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
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| `webhook.webhookentry` | Payload to send on entry. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
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@ -207,6 +223,7 @@ Mandatory parameters are marked as **Required**, which means that they are requi
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| `webhook.webhookexitcancel` | Payload to send on exit order cancel. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
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| `webhook.webhookexitfill` | Payload to send on exit order filled. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
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| `webhook.webhookstatus` | Payload to send on status calls. Only required if `webhook.enabled` is `true`. See the [webhook documentation](webhook-config.md) for more details. <br> **Datatype:** String
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| | **Rest API / FreqUI**
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| `api_server.enabled` | Enable usage of API Server. See the [API Server documentation](rest-api.md) for more details. <br> **Datatype:** Boolean
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| `api_server.listen_ip_address` | Bind IP address. See the [API Server documentation](rest-api.md) for more details. <br> **Datatype:** IPv4
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| `api_server.listen_port` | Bind Port. See the [API Server documentation](rest-api.md) for more details. <br>**Datatype:** Integer between 1024 and 65535
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@ -214,23 +231,22 @@ Mandatory parameters are marked as **Required**, which means that they are requi
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| `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
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| `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
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| `bot_name` | Name of the bot. Passed via API to a client - can be shown to distinguish / name bots.<br> *Defaults to `freqtrade`*<br> **Datatype:** String
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| `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
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| | **Other**
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| `initial_state` | Defines the initial application state. If set to stopped, then the bot has to be explicitly started via `/start` RPC command. <br>*Defaults to `stopped`.* <br> **Datatype:** Enum, either `stopped` or `running`
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| `force_entry_enable` | Enables the RPC Commands to force a Trade entry. More information below. <br> **Datatype:** Boolean
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| `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
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||||
| `strategy` | **Required** Defines Strategy class to use. Recommended to be set via `--strategy NAME`. <br> **Datatype:** ClassName
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||||
| `strategy_path` | Adds an additional strategy lookup path (must be a directory). <br> **Datatype:** String
|
||||
| `internals.process_throttle_secs` | Set the process throttle, or minimum loop duration for one bot iteration loop. Value in second. <br>*Defaults to `5` seconds.* <br> **Datatype:** Positive Integer
|
||||
| `internals.heartbeat_interval` | Print heartbeat message every N seconds. Set to 0 to disable heartbeat messages. <br>*Defaults to `60` seconds.* <br> **Datatype:** Positive Integer or 0
|
||||
| `internals.sd_notify` | Enables use of the sd_notify protocol to tell systemd service manager about changes in the bot state and issue keep-alive pings. See [here](installation.md#7-optional-configure-freqtrade-as-a-systemd-service) for more details. <br> **Datatype:** Boolean
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||||
| `logfile` | Specifies logfile name. Uses a rolling strategy for log file rotation for 10 files with the 1MB limit per file. <br> **Datatype:** String
|
||||
| `strategy` | **Required** Defines Strategy class to use. Recommended to be set via `--strategy NAME`. <br> **Datatype:** ClassName
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||||
| `strategy_path` | Adds an additional strategy lookup path (must be a directory). <br> **Datatype:** String
|
||||
| `recursive_strategy_search` | Set to `true` to recursively search sub-directories inside `user_data/strategies` for a strategy. <br> **Datatype:** Boolean
|
||||
| `user_data_dir` | Directory containing user data. <br> *Defaults to `./user_data/`*. <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
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||||
| `logfile` | Specifies logfile name. Uses a rolling strategy for log file rotation for 10 files with the 1MB limit per file. <br> **Datatype:** String
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||||
| `add_config_files` | Additional config files. These files will be loaded and merged with the current config file. The files are resolved relative to the initial file.<br> *Defaults to `[]`*. <br> **Datatype:** List of strings
|
||||
| `dataformat_ohlcv` | Data format to use to store historical candle (OHLCV) data. <br> *Defaults to `json`*. <br> **Datatype:** String
|
||||
| `dataformat_trades` | Data format to use to store historical trades data. <br> *Defaults to `jsongz`*. <br> **Datatype:** String
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||||
| `position_adjustment_enable` | Enables the strategy to use position adjustments (additional buys or sells). [More information here](strategy-callbacks.md#adjust-trade-position). <br> [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `false`.*<br> **Datatype:** Boolean
|
||||
| `max_entry_position_adjustment` | Maximum additional order(s) for each open trade on top of the first entry Order. Set it to `-1` for unlimited additional orders. [More information here](strategy-callbacks.md#adjust-trade-position). <br> [Strategy Override](#parameters-in-the-strategy). <br>*Defaults to `-1`.*<br> **Datatype:** Positive Integer or -1
|
||||
| `futures_funding_rate` | User-specified funding rate to be used when historical funding rates are not available from the exchange. This does not overwrite real historical rates. It is recommended that this be set to 0 unless you are testing a specific coin and you understand how the funding rate will affect freqtrade's profit calculations. [More information here](leverage.md#unavailable-funding-rates) <br>*Defaults to None.*<br> **Datatype:** Float
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||||
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### Parameters in the strategy
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|
||||
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|
|
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|
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@ -334,7 +334,7 @@ lev_tiers = exchange.fetch_leverage_tiers()
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# Assumes this is running in the root of the repository.
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file = Path('freqtrade/exchange/binance_leverage_tiers.json')
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json.dump(lev_tiers, file.open('w'), indent=2)
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json.dump(dict(sorted(lev_tiers.items())), file.open('w'), indent=2)
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||||
|
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```
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||||
|
||||
|
|
|
|||
|
|
@ -40,13 +40,15 @@ pip install -r requirements-hyperopt.txt
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```
|
||||
usage: freqtrade hyperopt [-h] [-v] [--logfile FILE] [-V] [-c PATH] [-d PATH]
|
||||
[--userdir PATH] [-s NAME] [--strategy-path PATH]
|
||||
[-i TIMEFRAME] [--timerange TIMERANGE]
|
||||
[--recursive-strategy-search] [-i TIMEFRAME]
|
||||
[--timerange TIMERANGE]
|
||||
[--data-format-ohlcv {json,jsongz,hdf5}]
|
||||
[--max-open-trades INT]
|
||||
[--stake-amount STAKE_AMOUNT] [--fee FLOAT]
|
||||
[-p PAIRS [PAIRS ...]] [--hyperopt-path PATH]
|
||||
[--eps] [--dmmp] [--enable-protections]
|
||||
[--dry-run-wallet DRY_RUN_WALLET] [-e INT]
|
||||
[--dry-run-wallet DRY_RUN_WALLET]
|
||||
[--timeframe-detail TIMEFRAME_DETAIL] [-e INT]
|
||||
[--spaces {all,buy,sell,roi,stoploss,trailing,protection,default} [{all,buy,sell,roi,stoploss,trailing,protection,default} ...]]
|
||||
[--print-all] [--no-color] [--print-json] [-j JOBS]
|
||||
[--random-state INT] [--min-trades INT]
|
||||
|
|
@ -89,6 +91,9 @@ optional arguments:
|
|||
--dry-run-wallet DRY_RUN_WALLET, --starting-balance DRY_RUN_WALLET
|
||||
Starting balance, used for backtesting / hyperopt and
|
||||
dry-runs.
|
||||
--timeframe-detail TIMEFRAME_DETAIL
|
||||
Specify detail timeframe for backtesting (`1m`, `5m`,
|
||||
`30m`, `1h`, `1d`).
|
||||
-e INT, --epochs INT Specify number of epochs (default: 100).
|
||||
--spaces {all,buy,sell,roi,stoploss,trailing,protection,default} [{all,buy,sell,roi,stoploss,trailing,protection,default} ...]
|
||||
Specify which parameters to hyperopt. Space-separated
|
||||
|
|
@ -146,7 +151,9 @@ Strategy arguments:
|
|||
Specify strategy class name which will be used by the
|
||||
bot.
|
||||
--strategy-path PATH Specify additional strategy lookup path.
|
||||
|
||||
--recursive-strategy-search
|
||||
Recursively search for a strategy in the strategies
|
||||
folder.
|
||||
```
|
||||
|
||||
### Hyperopt checklist
|
||||
|
|
@ -271,7 +278,8 @@ The last one we call `trigger` and use it to decide which buy trigger we want to
|
|||
|
||||
!!! Note "Parameter space assignment"
|
||||
Parameters must either be assigned to a variable named `buy_*` or `sell_*` - or contain `space='buy'` | `space='sell'` to be assigned to a space correctly.
|
||||
If no parameter is available for a space, you'll receive the error that no space was found when running hyperopt.
|
||||
If no parameter is available for a space, you'll receive the error that no space was found when running hyperopt.
|
||||
Parameters with unclear space (e.g. `adx_period = IntParameter(4, 24, default=14)` - no explicit nor implicit space) will not be detected and will therefore be ignored.
|
||||
|
||||
So let's write the buy strategy using these values:
|
||||
|
||||
|
|
@ -334,6 +342,7 @@ There are four parameter types each suited for different purposes.
|
|||
## Optimizing an indicator parameter
|
||||
|
||||
Assuming you have a simple strategy in mind - a EMA cross strategy (2 Moving averages crossing) - and you'd like to find the ideal parameters for this strategy.
|
||||
By default, we assume a stoploss of 5% - and a take-profit (`minimal_roi`) of 10% - which means freqtrade will sell the trade once 10% profit has been reached.
|
||||
|
||||
``` python
|
||||
from pandas import DataFrame
|
||||
|
|
@ -348,6 +357,9 @@ import freqtrade.vendor.qtpylib.indicators as qtpylib
|
|||
class MyAwesomeStrategy(IStrategy):
|
||||
stoploss = -0.05
|
||||
timeframe = '15m'
|
||||
minimal_roi = {
|
||||
"0": 0.10
|
||||
},
|
||||
# Define the parameter spaces
|
||||
buy_ema_short = IntParameter(3, 50, default=5)
|
||||
buy_ema_long = IntParameter(15, 200, default=50)
|
||||
|
|
@ -382,7 +394,7 @@ class MyAwesomeStrategy(IStrategy):
|
|||
return dataframe
|
||||
|
||||
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
conditions = []
|
||||
conditions = []
|
||||
conditions.append(qtpylib.crossed_above(
|
||||
dataframe[f'ema_long_{self.buy_ema_long.value}'], dataframe[f'ema_short_{self.buy_ema_short.value}']
|
||||
))
|
||||
|
|
@ -403,7 +415,7 @@ Using `self.buy_ema_short.range` will return a range object containing all entri
|
|||
In this case (`IntParameter(3, 50, default=5)`), the loop would run for all numbers between 3 and 50 (`[3, 4, 5, ... 49, 50]`).
|
||||
By using this in a loop, hyperopt will generate 48 new columns (`['buy_ema_3', 'buy_ema_4', ... , 'buy_ema_50']`).
|
||||
|
||||
Hyperopt itself will then use the selected value to create the buy and sell signals
|
||||
Hyperopt itself will then use the selected value to create the buy and sell signals.
|
||||
|
||||
While this strategy is most likely too simple to provide consistent profit, it should serve as an example how optimize indicator parameters.
|
||||
|
||||
|
|
@ -862,10 +874,28 @@ You can also enable position stacking in the configuration file by explicitly se
|
|||
As hyperopt consumes a lot of memory (the complete data needs to be in memory once per parallel backtesting process), it's likely that you run into "out of memory" errors.
|
||||
To combat these, you have multiple options:
|
||||
|
||||
* reduce the amount of pairs
|
||||
* reduce the timerange used (`--timerange <timerange>`)
|
||||
* reduce the number of parallel processes (`-j <n>`)
|
||||
* Increase the memory of your machine
|
||||
* Reduce the amount of pairs.
|
||||
* Reduce the timerange used (`--timerange <timerange>`).
|
||||
* Avoid using `--timeframe-detail` (this loads a lot of additional data into memory).
|
||||
* Reduce the number of parallel processes (`-j <n>`).
|
||||
* Increase the memory of your machine.
|
||||
|
||||
|
||||
## The objective has been evaluated at this point before.
|
||||
|
||||
If you see `The objective has been evaluated at this point before.` - then this is a sign that your space has been exhausted, or is close to that.
|
||||
Basically all points in your space have been hit (or a local minima has been hit) - and hyperopt does no longer find points in the multi-dimensional space it did not try yet.
|
||||
Freqtrade tries to counter the "local minima" problem by using new, randomized points in this case.
|
||||
|
||||
Example:
|
||||
|
||||
``` python
|
||||
buy_ema_short = IntParameter(5, 20, default=10, space="buy", optimize=True)
|
||||
# This is the only parameter in the buy space
|
||||
```
|
||||
|
||||
The `buy_ema_short` space has 15 possible values (`5, 6, ... 19, 20`). If you now run hyperopt for the buy space, hyperopt will only have 15 values to try before running out of options.
|
||||
Your epochs should therefore be aligned to the possible values - or you should be ready to interrupt a run if you norice a lot of `The objective has been evaluated at this point before.` warnings.
|
||||
|
||||
## Show details of Hyperopt results
|
||||
|
||||
|
|
|
|||
|
|
@ -50,6 +50,8 @@ This applies across all pairs, unless `only_per_pair` is set to true, which will
|
|||
|
||||
Similarly, this protection will by default look at all trades (long and short). For futures bots, setting `only_per_side` will make the bot only consider one side, and will then only lock this one side, allowing for example shorts to continue after a series of long stoplosses.
|
||||
|
||||
`required_profit` will determine the required relative profit (or loss) for stoplosses to consider. This should normally not be set and defaults to 0.0 - which means all losing stoplosses will be triggering a block.
|
||||
|
||||
The below example stops trading for all pairs for 4 candles after the last trade if the bot hit stoploss 4 times within the last 24 candles.
|
||||
|
||||
``` python
|
||||
|
|
@ -61,6 +63,7 @@ def protections(self):
|
|||
"lookback_period_candles": 24,
|
||||
"trade_limit": 4,
|
||||
"stop_duration_candles": 4,
|
||||
"required_profit": 0.0,
|
||||
"only_per_pair": False,
|
||||
"only_per_side": False
|
||||
}
|
||||
|
|
|
|||
|
|
@ -1,5 +1,6 @@
|
|||
mkdocs==1.3.0
|
||||
mkdocs-material==8.3.8
|
||||
mdx_truly_sane_lists==1.2
|
||||
markdown==3.3.7
|
||||
mkdocs==1.3.1
|
||||
mkdocs-material==8.3.9
|
||||
mdx_truly_sane_lists==1.3
|
||||
pymdown-extensions==9.5
|
||||
jinja2==3.1.2
|
||||
|
|
|
|||
|
|
@ -175,8 +175,8 @@ Before this, `stoploss` is used for the trailing stoploss.
|
|||
* assuming the asset now increases to 102$
|
||||
* the stoploss will now be at 91.8$ - 10% below the highest observed rate
|
||||
* assuming the asset now increases to 103.5$ (above the offset configured)
|
||||
* the stop loss will now be -2% of 103$ = 101.42$
|
||||
* now the asset drops in value to 102\$, the stop loss will still be 101.42$ and would trigger once price breaks below 101.42$
|
||||
* the stop loss will now be -2% of 103.5$ = 101.43$
|
||||
* now the asset drops in value to 102\$, the stop loss will still be 101.43$ and would trigger once price breaks below 101.43$
|
||||
|
||||
### Trailing stop loss only once the trade has reached a certain offset
|
||||
|
||||
|
|
|
|||
|
|
@ -224,3 +224,5 @@ for val in self.buy_ema_short.range:
|
|||
# Append columns to existing dataframe
|
||||
merged_frame = pd.concat(frames, axis=1)
|
||||
```
|
||||
|
||||
Freqtrade does however also counter this by running `dataframe.copy()` on the dataframe right after the `populate_indicators()` method - so performance implications of this should be low to non-existant.
|
||||
|
|
|
|||
|
|
@ -82,8 +82,9 @@ Called before entering a trade, makes it possible to manage your position size w
|
|||
```python
|
||||
class AwesomeStrategy(IStrategy):
|
||||
def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
|
||||
proposed_stake: float, min_stake: float, max_stake: float,
|
||||
entry_tag: Optional[str], side: str, **kwargs) -> float:
|
||||
proposed_stake: float, min_stake: Optional[float], max_stake: float,
|
||||
leverage: float, entry_tag: Optional[str], side: str,
|
||||
**kwargs) -> float:
|
||||
|
||||
dataframe, _ = self.dp.get_analyzed_dataframe(pair=pair, timeframe=self.timeframe)
|
||||
current_candle = dataframe.iloc[-1].squeeze()
|
||||
|
|
@ -673,9 +674,10 @@ class DigDeeperStrategy(IStrategy):
|
|||
max_dca_multiplier = 5.5
|
||||
|
||||
# This is called when placing the initial order (opening trade)
|
||||
def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
|
||||
def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
|
||||
proposed_stake: float, min_stake: Optional[float], max_stake: float,
|
||||
entry_tag: Optional[str], side: str, **kwargs) -> float:
|
||||
leverage: float, entry_tag: Optional[str], side: str,
|
||||
**kwargs) -> float:
|
||||
|
||||
# We need to leave most of the funds for possible further DCA orders
|
||||
# This also applies to fixed stakes
|
||||
|
|
|
|||
|
|
@ -646,6 +646,9 @@ This is where calling `self.dp.current_whitelist()` comes in handy.
|
|||
return informative_pairs
|
||||
```
|
||||
|
||||
??? Note "Plotting with current_whitelist"
|
||||
Current whitelist is not supported for `plot-dataframe`, as this command is usually used by providing an explicit pairlist - and would therefore make the return values of this method misleading.
|
||||
|
||||
### *get_pair_dataframe(pair, timeframe)*
|
||||
|
||||
``` python
|
||||
|
|
|
|||
|
|
@ -31,11 +31,13 @@ pair = "BTC/USDT"
|
|||
```python
|
||||
# Load data using values set above
|
||||
from freqtrade.data.history import load_pair_history
|
||||
from freqtrade.enums import CandleType
|
||||
|
||||
candles = load_pair_history(datadir=data_location,
|
||||
timeframe=config["timeframe"],
|
||||
pair=pair,
|
||||
data_format = "hdf5",
|
||||
candle_type=CandleType.SPOT,
|
||||
)
|
||||
|
||||
# Confirm success
|
||||
|
|
@ -93,7 +95,7 @@ from freqtrade.data.btanalysis import load_backtest_data, load_backtest_stats
|
|||
|
||||
# if backtest_dir points to a directory, it'll automatically load the last backtest file.
|
||||
backtest_dir = config["user_data_dir"] / "backtest_results"
|
||||
# backtest_dir can also point to a specific file
|
||||
# backtest_dir can also point to a specific file
|
||||
# backtest_dir = config["user_data_dir"] / "backtest_results/backtest-result-2020-07-01_20-04-22.json"
|
||||
```
|
||||
|
||||
|
|
|
|||
|
|
@ -97,7 +97,8 @@ Example configuration showing the different settings:
|
|||
"entry_fill": "off",
|
||||
"exit_fill": "off",
|
||||
"protection_trigger": "off",
|
||||
"protection_trigger_global": "on"
|
||||
"protection_trigger_global": "on",
|
||||
"show_candle": "off"
|
||||
},
|
||||
"reload": true,
|
||||
"balance_dust_level": 0.01
|
||||
|
|
@ -108,7 +109,7 @@ Example configuration showing the different settings:
|
|||
`exit` notifications are sent when the order is placed, while `exit_fill` notifications are sent when the order is filled on the exchange.
|
||||
`*_fill` notifications are off by default and must be explicitly enabled.
|
||||
`protection_trigger` notifications are sent when a protection triggers and `protection_trigger_global` notifications trigger when global protections are triggered.
|
||||
|
||||
`show_candle` - show candle values as part of entry/exit messages. Only possible value is "ohlc".
|
||||
|
||||
`balance_dust_level` will define what the `/balance` command takes as "dust" - Currencies with a balance below this will be shown.
|
||||
`reload` allows you to disable reload-buttons on selected messages.
|
||||
|
|
|
|||
|
|
@ -1,5 +1,5 @@
|
|||
""" Freqtrade bot """
|
||||
__version__ = '2022.6'
|
||||
__version__ = '2022.7'
|
||||
|
||||
if 'dev' in __version__:
|
||||
try:
|
||||
|
|
|
|||
|
|
@ -28,7 +28,7 @@ ARGS_BACKTEST = ARGS_COMMON_OPTIMIZE + ["position_stacking", "use_max_market_pos
|
|||
|
||||
ARGS_HYPEROPT = ARGS_COMMON_OPTIMIZE + ["hyperopt", "hyperopt_path",
|
||||
"position_stacking", "use_max_market_positions",
|
||||
"enable_protections", "dry_run_wallet",
|
||||
"enable_protections", "dry_run_wallet", "timeframe_detail",
|
||||
"epochs", "spaces", "print_all",
|
||||
"print_colorized", "print_json", "hyperopt_jobs",
|
||||
"hyperopt_random_state", "hyperopt_min_trades",
|
||||
|
|
|
|||
|
|
@ -313,6 +313,10 @@ CONF_SCHEMA = {
|
|||
'type': 'string',
|
||||
'enum': TELEGRAM_SETTING_OPTIONS,
|
||||
},
|
||||
'show_candle': {
|
||||
'type': 'string',
|
||||
'enum': ['off', 'ohlc'],
|
||||
},
|
||||
}
|
||||
},
|
||||
'reload': {'type': 'boolean'},
|
||||
|
|
@ -538,3 +542,4 @@ TradeList = List[List]
|
|||
LongShort = Literal['long', 'short']
|
||||
EntryExit = Literal['entry', 'exit']
|
||||
BuySell = Literal['buy', 'sell']
|
||||
MakerTaker = Literal['maker', 'taker']
|
||||
|
|
|
|||
File diff suppressed because it is too large
Load Diff
|
|
@ -46,6 +46,7 @@ MAP_EXCHANGE_CHILDCLASS = {
|
|||
'binanceje': 'binance',
|
||||
'binanceusdm': 'binance',
|
||||
'okex': 'okx',
|
||||
'gate': 'gateio',
|
||||
}
|
||||
|
||||
SUPPORTED_EXCHANGES = [
|
||||
|
|
@ -63,17 +64,16 @@ EXCHANGE_HAS_REQUIRED = [
|
|||
'fetchOrder',
|
||||
'cancelOrder',
|
||||
'createOrder',
|
||||
# 'createLimitOrder', 'createMarketOrder',
|
||||
'fetchBalance',
|
||||
|
||||
# Public endpoints
|
||||
'loadMarkets',
|
||||
'fetchOHLCV',
|
||||
]
|
||||
|
||||
EXCHANGE_HAS_OPTIONAL = [
|
||||
# Private
|
||||
'fetchMyTrades', # Trades for order - fee detection
|
||||
'createLimitOrder', 'createMarketOrder', # Either OR for orders
|
||||
# 'setLeverage', # Margin/Futures trading
|
||||
# 'setMarginMode', # Margin/Futures trading
|
||||
# 'fetchFundingHistory', # Futures trading
|
||||
|
|
|
|||
|
|
@ -20,7 +20,7 @@ from ccxt import ROUND_DOWN, ROUND_UP, TICK_SIZE, TRUNCATE, Precise, decimal_to_
|
|||
from pandas import DataFrame
|
||||
|
||||
from freqtrade.constants import (DEFAULT_AMOUNT_RESERVE_PERCENT, NON_OPEN_EXCHANGE_STATES, BuySell,
|
||||
EntryExit, ListPairsWithTimeframes, PairWithTimeframe)
|
||||
EntryExit, ListPairsWithTimeframes, MakerTaker, PairWithTimeframe)
|
||||
from freqtrade.data.converter import ohlcv_to_dataframe, trades_dict_to_list
|
||||
from freqtrade.enums import OPTIMIZE_MODES, CandleType, MarginMode, TradingMode
|
||||
from freqtrade.exceptions import (DDosProtection, ExchangeError, InsufficientFundsError,
|
||||
|
|
@ -77,7 +77,9 @@ class Exchange:
|
|||
"mark_ohlcv_price": "mark",
|
||||
"mark_ohlcv_timeframe": "8h",
|
||||
"ccxt_futures_name": "swap",
|
||||
"fee_cost_in_contracts": False, # Fee cost needs contract conversion
|
||||
"needs_trading_fees": False, # use fetch_trading_fees to cache fees
|
||||
"order_props_in_contracts": ['amount', 'cost', 'filled', 'remaining'],
|
||||
}
|
||||
_ft_has: Dict = {}
|
||||
_ft_has_futures: Dict = {}
|
||||
|
|
@ -86,7 +88,8 @@ class Exchange:
|
|||
# TradingMode.SPOT always supported and not required in this list
|
||||
]
|
||||
|
||||
def __init__(self, config: Dict[str, Any], validate: bool = True) -> None:
|
||||
def __init__(self, config: Dict[str, Any], validate: bool = True,
|
||||
load_leverage_tiers: bool = False) -> None:
|
||||
"""
|
||||
Initializes this module with the given config,
|
||||
it does basic validation whether the specified exchange and pairs are valid.
|
||||
|
|
@ -174,29 +177,17 @@ class Exchange:
|
|||
logger.info(f'Using Exchange "{self.name}"')
|
||||
|
||||
if validate:
|
||||
# Check if timeframe is available
|
||||
self.validate_timeframes(config.get('timeframe'))
|
||||
|
||||
# Initial markets load
|
||||
self._load_markets()
|
||||
|
||||
# Check if all pairs are available
|
||||
self.validate_stakecurrency(config['stake_currency'])
|
||||
if not exchange_config.get('skip_pair_validation'):
|
||||
self.validate_pairs(config['exchange']['pair_whitelist'])
|
||||
self.validate_ordertypes(config.get('order_types', {}))
|
||||
self.validate_order_time_in_force(config.get('order_time_in_force', {}))
|
||||
self.validate_config(config)
|
||||
self.required_candle_call_count = self.validate_required_startup_candles(
|
||||
config.get('startup_candle_count', 0), config.get('timeframe', ''))
|
||||
self.validate_trading_mode_and_margin_mode(self.trading_mode, self.margin_mode)
|
||||
self.validate_pricing(config['exit_pricing'])
|
||||
self.validate_pricing(config['entry_pricing'])
|
||||
|
||||
# Converts the interval provided in minutes in config to seconds
|
||||
self.markets_refresh_interval: int = exchange_config.get(
|
||||
"markets_refresh_interval", 60) * 60
|
||||
|
||||
if self.trading_mode != TradingMode.SPOT:
|
||||
if self.trading_mode != TradingMode.SPOT and load_leverage_tiers:
|
||||
self.fill_leverage_tiers()
|
||||
self.additional_exchange_init()
|
||||
|
||||
|
|
@ -213,6 +204,20 @@ class Exchange:
|
|||
logger.info("Closing async ccxt session.")
|
||||
self.loop.run_until_complete(self._api_async.close())
|
||||
|
||||
def validate_config(self, config):
|
||||
# Check if timeframe is available
|
||||
self.validate_timeframes(config.get('timeframe'))
|
||||
|
||||
# Check if all pairs are available
|
||||
self.validate_stakecurrency(config['stake_currency'])
|
||||
if not config['exchange'].get('skip_pair_validation'):
|
||||
self.validate_pairs(config['exchange']['pair_whitelist'])
|
||||
self.validate_ordertypes(config.get('order_types', {}))
|
||||
self.validate_order_time_in_force(config.get('order_time_in_force', {}))
|
||||
self.validate_trading_mode_and_margin_mode(self.trading_mode, self.margin_mode)
|
||||
self.validate_pricing(config['exit_pricing'])
|
||||
self.validate_pricing(config['entry_pricing'])
|
||||
|
||||
def _init_ccxt(self, exchange_config: Dict[str, Any], ccxt_module: CcxtModuleType = ccxt,
|
||||
ccxt_kwargs: Dict = {}) -> ccxt.Exchange:
|
||||
"""
|
||||
|
|
@ -422,7 +427,7 @@ class Exchange:
|
|||
if 'symbol' in order and order['symbol'] is not None:
|
||||
contract_size = self._get_contract_size(order['symbol'])
|
||||
if contract_size != 1:
|
||||
for prop in ['amount', 'cost', 'filled', 'remaining']:
|
||||
for prop in self._ft_has.get('order_props_in_contracts', []):
|
||||
if prop in order and order[prop] is not None:
|
||||
order[prop] = order[prop] * contract_size
|
||||
return order
|
||||
|
|
@ -820,7 +825,7 @@ class Exchange:
|
|||
'price': rate,
|
||||
'average': rate,
|
||||
'amount': _amount,
|
||||
'cost': _amount * rate / leverage,
|
||||
'cost': _amount * rate,
|
||||
'type': ordertype,
|
||||
'side': side,
|
||||
'filled': 0,
|
||||
|
|
@ -846,20 +851,27 @@ class Exchange:
|
|||
'filled': _amount,
|
||||
'cost': (dry_order['amount'] * average) / leverage
|
||||
})
|
||||
dry_order = self.add_dry_order_fee(pair, dry_order)
|
||||
# market orders will always incurr taker fees
|
||||
dry_order = self.add_dry_order_fee(pair, dry_order, 'taker')
|
||||
|
||||
dry_order = self.check_dry_limit_order_filled(dry_order)
|
||||
dry_order = self.check_dry_limit_order_filled(dry_order, immediate=True)
|
||||
|
||||
self._dry_run_open_orders[dry_order["id"]] = dry_order
|
||||
# Copy order and close it - so the returned order is open unless it's a market order
|
||||
return dry_order
|
||||
|
||||
def add_dry_order_fee(self, pair: str, dry_order: Dict[str, Any]) -> Dict[str, Any]:
|
||||
def add_dry_order_fee(
|
||||
self,
|
||||
pair: str,
|
||||
dry_order: Dict[str, Any],
|
||||
taker_or_maker: MakerTaker,
|
||||
) -> Dict[str, Any]:
|
||||
fee = self.get_fee(pair, taker_or_maker=taker_or_maker)
|
||||
dry_order.update({
|
||||
'fee': {
|
||||
'currency': self.get_pair_quote_currency(pair),
|
||||
'cost': dry_order['cost'] * self.get_fee(pair),
|
||||
'rate': self.get_fee(pair)
|
||||
'cost': dry_order['cost'] * fee,
|
||||
'rate': fee
|
||||
}
|
||||
})
|
||||
return dry_order
|
||||
|
|
@ -925,7 +937,8 @@ class Exchange:
|
|||
pass
|
||||
return False
|
||||
|
||||
def check_dry_limit_order_filled(self, order: Dict[str, Any]) -> Dict[str, Any]:
|
||||
def check_dry_limit_order_filled(
|
||||
self, order: Dict[str, Any], immediate: bool = False) -> Dict[str, Any]:
|
||||
"""
|
||||
Check dry-run limit order fill and update fee (if it filled).
|
||||
"""
|
||||
|
|
@ -939,7 +952,12 @@ class Exchange:
|
|||
'filled': order['amount'],
|
||||
'remaining': 0,
|
||||
})
|
||||
self.add_dry_order_fee(pair, order)
|
||||
|
||||
self.add_dry_order_fee(
|
||||
pair,
|
||||
order,
|
||||
'taker' if immediate else 'maker',
|
||||
)
|
||||
|
||||
return order
|
||||
|
||||
|
|
@ -1246,7 +1264,7 @@ class Exchange:
|
|||
return False
|
||||
|
||||
required = ('fee', 'status', 'amount')
|
||||
return all(k in corder for k in required)
|
||||
return all(corder.get(k, None) is not None for k in required)
|
||||
|
||||
def cancel_order_with_result(self, order_id: str, pair: str, amount: float) -> Dict:
|
||||
"""
|
||||
|
|
@ -1597,7 +1615,7 @@ class Exchange:
|
|||
|
||||
@retrier
|
||||
def get_fee(self, symbol: str, type: str = '', side: str = '', amount: float = 1,
|
||||
price: float = 1, taker_or_maker: str = 'maker') -> float:
|
||||
price: float = 1, taker_or_maker: MakerTaker = 'maker') -> float:
|
||||
try:
|
||||
if self._config['dry_run'] and self._config.get('fee', None) is not None:
|
||||
return self._config['fee']
|
||||
|
|
@ -1631,27 +1649,35 @@ class Exchange:
|
|||
and order['fee']['cost'] is not None
|
||||
)
|
||||
|
||||
def calculate_fee_rate(self, order: Dict) -> Optional[float]:
|
||||
def calculate_fee_rate(
|
||||
self, fee: Dict, symbol: str, cost: float, amount: float) -> Optional[float]:
|
||||
"""
|
||||
Calculate fee rate if it's not given by the exchange.
|
||||
:param order: Order or trade (one trade) dict
|
||||
:param fee: ccxt Fee dict - must contain cost / currency / rate
|
||||
:param symbol: Symbol of the order
|
||||
:param cost: Total cost of the order
|
||||
:param amount: Amount of the order
|
||||
"""
|
||||
if order['fee'].get('rate') is not None:
|
||||
return order['fee'].get('rate')
|
||||
fee_curr = order['fee']['currency']
|
||||
if fee.get('rate') is not None:
|
||||
return fee.get('rate')
|
||||
fee_curr = fee.get('currency')
|
||||
if fee_curr is None:
|
||||
return None
|
||||
fee_cost = float(fee['cost'])
|
||||
if self._ft_has['fee_cost_in_contracts']:
|
||||
# Convert cost via "contracts" conversion
|
||||
fee_cost = self._contracts_to_amount(symbol, fee['cost'])
|
||||
|
||||
# Calculate fee based on order details
|
||||
if fee_curr in self.get_pair_base_currency(order['symbol']):
|
||||
if fee_curr == self.get_pair_base_currency(symbol):
|
||||
# Base currency - divide by amount
|
||||
return round(
|
||||
order['fee']['cost'] / safe_value_fallback2(order, order, 'filled', 'amount'), 8)
|
||||
elif fee_curr in self.get_pair_quote_currency(order['symbol']):
|
||||
return round(fee_cost / amount, 8)
|
||||
elif fee_curr == self.get_pair_quote_currency(symbol):
|
||||
# Quote currency - divide by cost
|
||||
return round(self._contracts_to_amount(
|
||||
order['symbol'], order['fee']['cost']) / order['cost'],
|
||||
8) if order['cost'] else None
|
||||
return round(fee_cost / cost, 8) if cost else None
|
||||
else:
|
||||
# If Fee currency is a different currency
|
||||
if not order['cost']:
|
||||
if not cost:
|
||||
# If cost is None or 0.0 -> falsy, return None
|
||||
return None
|
||||
try:
|
||||
|
|
@ -1663,19 +1689,28 @@ class Exchange:
|
|||
fee_to_quote_rate = self._config['exchange'].get('unknown_fee_rate', None)
|
||||
if not fee_to_quote_rate:
|
||||
return None
|
||||
return round((self._contracts_to_amount(
|
||||
order['symbol'], order['fee']['cost']) * fee_to_quote_rate) / order['cost'], 8)
|
||||
return round((fee_cost * fee_to_quote_rate) / cost, 8)
|
||||
|
||||
def extract_cost_curr_rate(self, order: Dict) -> Tuple[float, str, Optional[float]]:
|
||||
def extract_cost_curr_rate(self, fee: Dict, symbol: str, cost: float,
|
||||
amount: float) -> Tuple[float, str, Optional[float]]:
|
||||
"""
|
||||
Extract tuple of cost, currency, rate.
|
||||
Requires order_has_fee to run first!
|
||||
:param order: Order or trade (one trade) dict
|
||||
:param fee: ccxt Fee dict - must contain cost / currency / rate
|
||||
:param symbol: Symbol of the order
|
||||
:param cost: Total cost of the order
|
||||
:param amount: Amount of the order
|
||||
:return: Tuple with cost, currency, rate of the given fee dict
|
||||
"""
|
||||
return (order['fee']['cost'],
|
||||
order['fee']['currency'],
|
||||
self.calculate_fee_rate(order))
|
||||
return (float(fee['cost']),
|
||||
fee['currency'],
|
||||
self.calculate_fee_rate(
|
||||
fee,
|
||||
symbol,
|
||||
cost,
|
||||
amount
|
||||
)
|
||||
)
|
||||
|
||||
# Historic data
|
||||
|
||||
|
|
|
|||
|
|
@ -1,12 +1,13 @@
|
|||
""" Gate.io exchange subclass """
|
||||
import logging
|
||||
from datetime import datetime
|
||||
from typing import Dict, List, Optional, Tuple
|
||||
from typing import Any, Dict, List, Optional, Tuple
|
||||
|
||||
from freqtrade.constants import BuySell
|
||||
from freqtrade.enums import MarginMode, TradingMode
|
||||
from freqtrade.exceptions import OperationalException
|
||||
from freqtrade.exchange import Exchange
|
||||
from freqtrade.misc import safe_value_fallback2
|
||||
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
|
@ -32,7 +33,9 @@ class Gateio(Exchange):
|
|||
}
|
||||
|
||||
_ft_has_futures: Dict = {
|
||||
"needs_trading_fees": True
|
||||
"needs_trading_fees": True,
|
||||
"fee_cost_in_contracts": False, # Set explicitly to false for clarity
|
||||
"order_props_in_contracts": ['amount', 'filled', 'remaining'],
|
||||
}
|
||||
|
||||
_supported_trading_mode_margin_pairs: List[Tuple[TradingMode, MarginMode]] = [
|
||||
|
|
@ -95,12 +98,29 @@ class Gateio(Exchange):
|
|||
}
|
||||
return trades
|
||||
|
||||
def get_order_id_conditional(self, order: Dict[str, Any]) -> str:
|
||||
if self.trading_mode == TradingMode.FUTURES:
|
||||
return safe_value_fallback2(order, order, 'id_stop', 'id')
|
||||
return order['id']
|
||||
|
||||
def fetch_stoploss_order(self, order_id: str, pair: str, params: Dict = {}) -> Dict:
|
||||
return self.fetch_order(
|
||||
order = self.fetch_order(
|
||||
order_id=order_id,
|
||||
pair=pair,
|
||||
params={'stop': True}
|
||||
)
|
||||
if self.trading_mode == TradingMode.FUTURES:
|
||||
if order['status'] == 'closed':
|
||||
# Places a real order - which we need to fetch explicitly.
|
||||
new_orderid = order.get('info', {}).get('trade_id')
|
||||
if new_orderid:
|
||||
order1 = self.fetch_order(order_id=new_orderid, pair=pair, params=params)
|
||||
order1['id_stop'] = order1['id']
|
||||
order1['id'] = order_id
|
||||
order1['stopPrice'] = order.get('stopPrice')
|
||||
|
||||
return order1
|
||||
return order
|
||||
|
||||
def cancel_stoploss_order(self, order_id: str, pair: str, params: Dict = {}) -> Dict:
|
||||
return self.cancel_order(
|
||||
|
|
|
|||
|
|
@ -28,6 +28,7 @@ class Okx(Exchange):
|
|||
}
|
||||
_ft_has_futures: Dict = {
|
||||
"tickers_have_quoteVolume": False,
|
||||
"fee_cost_in_contracts": True,
|
||||
}
|
||||
|
||||
_supported_trading_mode_margin_pairs: List[Tuple[TradingMode, MarginMode]] = [
|
||||
|
|
|
|||
|
|
@ -65,7 +65,8 @@ class FreqtradeBot(LoggingMixin):
|
|||
# Check config consistency here since strategies can set certain options
|
||||
validate_config_consistency(config)
|
||||
|
||||
self.exchange = ExchangeResolver.load_exchange(self.config['exchange']['name'], self.config)
|
||||
self.exchange = ExchangeResolver.load_exchange(
|
||||
self.config['exchange']['name'], self.config, load_leverage_tiers=True)
|
||||
|
||||
init_db(self.config['db_url'])
|
||||
|
||||
|
|
@ -332,6 +333,8 @@ class FreqtradeBot(LoggingMixin):
|
|||
if not trade.is_open and not trade.fee_updated(trade.exit_side):
|
||||
# Get sell fee
|
||||
order = trade.select_order(trade.exit_side, False)
|
||||
if not order:
|
||||
order = trade.select_order('stoploss', False)
|
||||
if order:
|
||||
logger.info(
|
||||
f"Updating {trade.exit_side}-fee on trade {trade}"
|
||||
|
|
@ -634,7 +637,7 @@ class FreqtradeBot(LoggingMixin):
|
|||
pair=pair, order_type=order_type, amount=amount, rate=enter_limit_requested,
|
||||
time_in_force=time_in_force, current_time=datetime.now(timezone.utc),
|
||||
entry_tag=enter_tag, side=trade_side):
|
||||
logger.info(f"User requested abortion of buying {pair}")
|
||||
logger.info(f"User denied entry for {pair}.")
|
||||
return False
|
||||
order = self.exchange.create_order(
|
||||
pair=pair,
|
||||
|
|
@ -814,7 +817,7 @@ class FreqtradeBot(LoggingMixin):
|
|||
pair=pair, current_time=datetime.now(timezone.utc),
|
||||
current_rate=enter_limit_requested, proposed_stake=stake_amount,
|
||||
min_stake=min_stake_amount, max_stake=min(max_stake_amount, stake_available),
|
||||
entry_tag=entry_tag, side=trade_side
|
||||
leverage=leverage, entry_tag=entry_tag, side=trade_side
|
||||
)
|
||||
|
||||
stake_amount = self.wallets.validate_stake_amount(
|
||||
|
|
@ -1465,7 +1468,7 @@ class FreqtradeBot(LoggingMixin):
|
|||
time_in_force=time_in_force, exit_reason=exit_reason,
|
||||
sell_reason=exit_reason, # sellreason -> compatibility
|
||||
current_time=datetime.now(timezone.utc)):
|
||||
logger.info(f"User requested abortion of {trade.pair} exit.")
|
||||
logger.info(f"User denied exit for {trade.pair}.")
|
||||
return False
|
||||
|
||||
try:
|
||||
|
|
@ -1742,7 +1745,8 @@ class FreqtradeBot(LoggingMixin):
|
|||
trade_base_currency = self.exchange.get_pair_base_currency(trade.pair)
|
||||
# use fee from order-dict if possible
|
||||
if self.exchange.order_has_fee(order):
|
||||
fee_cost, fee_currency, fee_rate = self.exchange.extract_cost_curr_rate(order)
|
||||
fee_cost, fee_currency, fee_rate = self.exchange.extract_cost_curr_rate(
|
||||
order['fee'], order['symbol'], order['cost'], order_obj.safe_filled)
|
||||
logger.info(f"Fee for Trade {trade} [{order_obj.ft_order_side}]: "
|
||||
f"{fee_cost:.8g} {fee_currency} - rate: {fee_rate}")
|
||||
if fee_rate is None or fee_rate < 0.02:
|
||||
|
|
@ -1780,7 +1784,15 @@ class FreqtradeBot(LoggingMixin):
|
|||
for exectrade in trades:
|
||||
amount += exectrade['amount']
|
||||
if self.exchange.order_has_fee(exectrade):
|
||||
fee_cost_, fee_currency, fee_rate_ = self.exchange.extract_cost_curr_rate(exectrade)
|
||||
# Prefer singular fee
|
||||
fees = [exectrade['fee']]
|
||||
else:
|
||||
fees = exectrade.get('fees', [])
|
||||
for fee in fees:
|
||||
|
||||
fee_cost_, fee_currency, fee_rate_ = self.exchange.extract_cost_curr_rate(
|
||||
fee, exectrade['symbol'], exectrade['cost'], exectrade['amount']
|
||||
)
|
||||
fee_cost += fee_cost_
|
||||
if fee_rate_ is not None:
|
||||
fee_rate_array.append(fee_rate_)
|
||||
|
|
|
|||
|
|
@ -84,7 +84,8 @@ class Backtesting:
|
|||
self.processed_dfs: Dict[str, Dict] = {}
|
||||
|
||||
self._exchange_name = self.config['exchange']['name']
|
||||
self.exchange = ExchangeResolver.load_exchange(self._exchange_name, self.config)
|
||||
self.exchange = ExchangeResolver.load_exchange(
|
||||
self._exchange_name, self.config, load_leverage_tiers=True)
|
||||
self.dataprovider = DataProvider(self.config, self.exchange)
|
||||
|
||||
if self.config.get('strategy_list'):
|
||||
|
|
@ -722,7 +723,7 @@ class Backtesting:
|
|||
pair=pair, current_time=current_time, current_rate=propose_rate,
|
||||
proposed_stake=stake_amount, min_stake=min_stake_amount,
|
||||
max_stake=min(stake_available, max_stake_amount),
|
||||
entry_tag=entry_tag, side=direction)
|
||||
leverage=leverage, entry_tag=entry_tag, side=direction)
|
||||
|
||||
stake_amount_val = self.wallets.validate_stake_amount(
|
||||
pair=pair,
|
||||
|
|
|
|||
|
|
@ -6,6 +6,7 @@ This module contains the hyperopt logic
|
|||
|
||||
import logging
|
||||
import random
|
||||
import sys
|
||||
import warnings
|
||||
from datetime import datetime, timezone
|
||||
from math import ceil
|
||||
|
|
@ -17,6 +18,7 @@ import rapidjson
|
|||
from colorama import Fore, Style
|
||||
from colorama import init as colorama_init
|
||||
from joblib import Parallel, cpu_count, delayed, dump, load, wrap_non_picklable_objects
|
||||
from joblib.externals import cloudpickle
|
||||
from pandas import DataFrame
|
||||
|
||||
from freqtrade.constants import DATETIME_PRINT_FORMAT, FTHYPT_FILEVERSION, LAST_BT_RESULT_FN
|
||||
|
|
@ -87,6 +89,7 @@ class Hyperopt:
|
|||
self.backtesting._set_strategy(self.backtesting.strategylist[0])
|
||||
self.custom_hyperopt.strategy = self.backtesting.strategy
|
||||
|
||||
self.hyperopt_pickle_magic(self.backtesting.strategy.__class__.__bases__)
|
||||
self.custom_hyperoptloss: IHyperOptLoss = HyperOptLossResolver.load_hyperoptloss(
|
||||
self.config)
|
||||
self.calculate_loss = self.custom_hyperoptloss.hyperopt_loss_function
|
||||
|
|
@ -137,6 +140,17 @@ class Hyperopt:
|
|||
logger.info(f"Removing `{p}`.")
|
||||
p.unlink()
|
||||
|
||||
def hyperopt_pickle_magic(self, bases) -> None:
|
||||
"""
|
||||
Hyperopt magic to allow strategy inheritance across files.
|
||||
For this to properly work, we need to register the module of the imported class
|
||||
to pickle as value.
|
||||
"""
|
||||
for modules in bases:
|
||||
if modules.__name__ != 'IStrategy':
|
||||
cloudpickle.register_pickle_by_value(sys.modules[modules.__module__])
|
||||
self.hyperopt_pickle_magic(modules.__bases__)
|
||||
|
||||
def _get_params_dict(self, dimensions: List[Dimension], raw_params: List[Any]) -> Dict:
|
||||
|
||||
# Ensure the number of dimensions match
|
||||
|
|
|
|||
|
|
@ -1,9 +1,10 @@
|
|||
import logging
|
||||
from typing import List
|
||||
|
||||
from sqlalchemy import inspect, text
|
||||
from sqlalchemy import inspect, select, text, tuple_, update
|
||||
|
||||
from freqtrade.exceptions import OperationalException
|
||||
from freqtrade.persistence.trade_model import Order, Trade
|
||||
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
|
@ -251,31 +252,31 @@ def set_sqlite_to_wal(engine):
|
|||
|
||||
def fix_old_dry_orders(engine):
|
||||
with engine.begin() as connection:
|
||||
connection.execute(
|
||||
text(
|
||||
"""
|
||||
update orders
|
||||
set ft_is_open = 0
|
||||
where ft_is_open = 1 and (ft_trade_id, order_id) not in (
|
||||
select id, stoploss_order_id from trades where stoploss_order_id is not null
|
||||
) and ft_order_side = 'stoploss'
|
||||
and order_id like 'dry_%'
|
||||
"""
|
||||
)
|
||||
)
|
||||
connection.execute(
|
||||
text(
|
||||
"""
|
||||
update orders
|
||||
set ft_is_open = 0
|
||||
where ft_is_open = 1
|
||||
and (ft_trade_id, order_id) not in (
|
||||
select id, open_order_id from trades where open_order_id is not null
|
||||
) and ft_order_side != 'stoploss'
|
||||
and order_id like 'dry_%'
|
||||
"""
|
||||
)
|
||||
)
|
||||
stmt = update(Order).where(
|
||||
Order.ft_is_open.is_(True),
|
||||
tuple_(Order.ft_trade_id, Order.order_id).not_in(
|
||||
select(
|
||||
Trade.id, Trade.stoploss_order_id
|
||||
).where(Trade.stoploss_order_id.is_not(None))
|
||||
),
|
||||
Order.ft_order_side == 'stoploss',
|
||||
Order.order_id.like('dry%'),
|
||||
|
||||
).values(ft_is_open=False)
|
||||
connection.execute(stmt)
|
||||
|
||||
stmt = update(Order).where(
|
||||
Order.ft_is_open.is_(True),
|
||||
tuple_(Order.ft_trade_id, Order.order_id).not_in(
|
||||
select(
|
||||
Trade.id, Trade.open_order_id
|
||||
).where(Trade.open_order_id.is_not(None))
|
||||
),
|
||||
Order.ft_order_side != 'stoploss',
|
||||
Order.order_id.like('dry%')
|
||||
|
||||
).values(ft_is_open=False)
|
||||
connection.execute(stmt)
|
||||
|
||||
|
||||
def check_migrate(engine, decl_base, previous_tables) -> None:
|
||||
|
|
|
|||
|
|
@ -821,7 +821,7 @@ class LocalTrade():
|
|||
self.open_rate = total_stake / total_amount
|
||||
self.stake_amount = total_stake / (self.leverage or 1.0)
|
||||
self.amount = total_amount
|
||||
self.fee_open_cost = self.fee_open * self.stake_amount
|
||||
self.fee_open_cost = self.fee_open * total_stake
|
||||
self.recalc_open_trade_value()
|
||||
if self.stop_loss_pct is not None and self.open_rate is not None:
|
||||
self.adjust_stop_loss(self.open_rate, self.stop_loss_pct)
|
||||
|
|
|
|||
|
|
@ -255,18 +255,18 @@ 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
|
||||
# Create description for exit summarizing the trade
|
||||
trades['desc'] = trades.apply(
|
||||
lambda row: f"{row['profit_ratio']:.2%}, " +
|
||||
(f"{row['enter_tag']}, " if row['enter_tag'] is not None else "") +
|
||||
f"{row['exit_reason']}, " +
|
||||
f"{row['trade_duration']} min",
|
||||
axis=1)
|
||||
trade_buys = go.Scatter(
|
||||
trade_entries = go.Scatter(
|
||||
x=trades["open_date"],
|
||||
y=trades["open_rate"],
|
||||
mode='markers',
|
||||
name='Trade buy',
|
||||
name='Trade entry',
|
||||
text=trades["desc"],
|
||||
marker=dict(
|
||||
symbol='circle-open',
|
||||
|
|
@ -277,12 +277,12 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
|
|||
)
|
||||
)
|
||||
|
||||
trade_sells = go.Scatter(
|
||||
trade_exits = go.Scatter(
|
||||
x=trades.loc[trades['profit_ratio'] > 0, "close_date"],
|
||||
y=trades.loc[trades['profit_ratio'] > 0, "close_rate"],
|
||||
text=trades.loc[trades['profit_ratio'] > 0, "desc"],
|
||||
mode='markers',
|
||||
name='Sell - Profit',
|
||||
name='Exit - Profit',
|
||||
marker=dict(
|
||||
symbol='square-open',
|
||||
size=11,
|
||||
|
|
@ -290,12 +290,12 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
|
|||
color='green'
|
||||
)
|
||||
)
|
||||
trade_sells_loss = go.Scatter(
|
||||
trade_exits_loss = go.Scatter(
|
||||
x=trades.loc[trades['profit_ratio'] <= 0, "close_date"],
|
||||
y=trades.loc[trades['profit_ratio'] <= 0, "close_rate"],
|
||||
text=trades.loc[trades['profit_ratio'] <= 0, "desc"],
|
||||
mode='markers',
|
||||
name='Sell - Loss',
|
||||
name='Exit - Loss',
|
||||
marker=dict(
|
||||
symbol='square-open',
|
||||
size=11,
|
||||
|
|
@ -303,9 +303,9 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots:
|
|||
color='red'
|
||||
)
|
||||
)
|
||||
fig.add_trace(trade_buys, 1, 1)
|
||||
fig.add_trace(trade_sells, 1, 1)
|
||||
fig.add_trace(trade_sells_loss, 1, 1)
|
||||
fig.add_trace(trade_entries, 1, 1)
|
||||
fig.add_trace(trade_exits, 1, 1)
|
||||
fig.add_trace(trade_exits_loss, 1, 1)
|
||||
else:
|
||||
logger.warning("No trades found.")
|
||||
return fig
|
||||
|
|
@ -444,7 +444,7 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
|
|||
Generate the graph from the data generated by Backtesting or from DB
|
||||
Volume will always be ploted in row2, so Row 1 and 3 are to our disposal for custom indicators
|
||||
:param pair: Pair to Display on the graph
|
||||
:param data: OHLCV DataFrame containing indicators and buy/sell signals
|
||||
:param data: OHLCV DataFrame containing indicators and entry/exit signals
|
||||
:param trades: All trades created
|
||||
:param indicators1: List containing Main plot indicators
|
||||
:param indicators2: List containing Sub plot indicators
|
||||
|
|
|
|||
|
|
@ -23,13 +23,14 @@ class StoplossGuard(IProtection):
|
|||
self._trade_limit = protection_config.get('trade_limit', 10)
|
||||
self._disable_global_stop = protection_config.get('only_per_pair', False)
|
||||
self._only_per_side = protection_config.get('only_per_side', False)
|
||||
self._profit_limit = protection_config.get('required_profit', 0.0)
|
||||
|
||||
def short_desc(self) -> str:
|
||||
"""
|
||||
Short method description - used for startup-messages
|
||||
"""
|
||||
return (f"{self.name} - Frequent Stoploss Guard, {self._trade_limit} stoplosses "
|
||||
f"within {self.lookback_period_str}.")
|
||||
f"with profit < {self._profit_limit:.2%} within {self.lookback_period_str}.")
|
||||
|
||||
def _reason(self) -> str:
|
||||
"""
|
||||
|
|
@ -49,7 +50,7 @@ class StoplossGuard(IProtection):
|
|||
trades = [trade for trade in trades1 if (str(trade.exit_reason) in (
|
||||
ExitType.TRAILING_STOP_LOSS.value, ExitType.STOP_LOSS.value,
|
||||
ExitType.STOPLOSS_ON_EXCHANGE.value)
|
||||
and trade.close_profit and trade.close_profit < 0)]
|
||||
and trade.close_profit and trade.close_profit < self._profit_limit)]
|
||||
|
||||
if self._only_per_side:
|
||||
# Long or short trades only
|
||||
|
|
|
|||
|
|
@ -18,7 +18,8 @@ class ExchangeResolver(IResolver):
|
|||
object_type = Exchange
|
||||
|
||||
@staticmethod
|
||||
def load_exchange(exchange_name: str, config: dict, validate: bool = True) -> Exchange:
|
||||
def load_exchange(exchange_name: str, config: dict, validate: bool = True,
|
||||
load_leverage_tiers: bool = False) -> Exchange:
|
||||
"""
|
||||
Load the custom class from config parameter
|
||||
:param exchange_name: name of the Exchange to load
|
||||
|
|
@ -29,9 +30,13 @@ class ExchangeResolver(IResolver):
|
|||
exchange_name = exchange_name.title()
|
||||
exchange = None
|
||||
try:
|
||||
exchange = ExchangeResolver._load_exchange(exchange_name,
|
||||
kwargs={'config': config,
|
||||
'validate': validate})
|
||||
exchange = ExchangeResolver._load_exchange(
|
||||
exchange_name,
|
||||
kwargs={
|
||||
'config': config,
|
||||
'validate': validate,
|
||||
'load_leverage_tiers': load_leverage_tiers}
|
||||
)
|
||||
except ImportError:
|
||||
logger.info(
|
||||
f"No {exchange_name} specific subclass found. Using the generic class instead.")
|
||||
|
|
|
|||
|
|
@ -37,7 +37,7 @@ def get_exchange(config=Depends(get_config)):
|
|||
if not ApiServer._exchange:
|
||||
from freqtrade.resolvers import ExchangeResolver
|
||||
ApiServer._exchange = ExchangeResolver.load_exchange(
|
||||
config['exchange']['name'], config)
|
||||
config['exchange']['name'], config, load_leverage_tiers=False)
|
||||
return ApiServer._exchange
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -243,6 +243,22 @@ class Telegram(RPCHandler):
|
|||
"""
|
||||
return f"{msg['exchange']}{' (dry)' if self._config['dry_run'] else ''}"
|
||||
|
||||
def _add_analyzed_candle(self, pair: str) -> str:
|
||||
candle_val = self._config['telegram'].get(
|
||||
'notification_settings', {}).get('show_candle', 'off')
|
||||
if candle_val != 'off':
|
||||
if candle_val == 'ohlc':
|
||||
analyzed_df, _ = self._rpc._freqtrade.dataprovider.get_analyzed_dataframe(
|
||||
pair, self._config['timeframe'])
|
||||
candle = analyzed_df.iloc[-1].squeeze() if len(analyzed_df) > 0 else None
|
||||
if candle is not None:
|
||||
return (
|
||||
f"*Candle OHLC*: `{candle['open']}, {candle['high']}, "
|
||||
f"{candle['low']}, {candle['close']}`\n"
|
||||
)
|
||||
|
||||
return ''
|
||||
|
||||
def _format_entry_msg(self, msg: Dict[str, Any]) -> str:
|
||||
if self._rpc._fiat_converter:
|
||||
msg['stake_amount_fiat'] = self._rpc._fiat_converter.convert_amount(
|
||||
|
|
@ -259,6 +275,7 @@ class Telegram(RPCHandler):
|
|||
f" {entry_side['entered'] if is_fill else entry_side['enter']} {msg['pair']}"
|
||||
f" (#{msg['trade_id']})\n"
|
||||
)
|
||||
message += self._add_analyzed_candle(msg['pair'])
|
||||
message += f"*Enter Tag:* `{msg['enter_tag']}`\n" if msg.get('enter_tag') else ""
|
||||
message += f"*Amount:* `{msg['amount']:.8f}`\n"
|
||||
if msg.get('leverage') and msg.get('leverage', 1.0) != 1.0:
|
||||
|
|
@ -306,6 +323,7 @@ class Telegram(RPCHandler):
|
|||
message = (
|
||||
f"{msg['emoji']} *{self._exchange_from_msg(msg)}:* "
|
||||
f"{'Exited' if is_fill else 'Exiting'} {msg['pair']} (#{msg['trade_id']})\n"
|
||||
f"{self._add_analyzed_candle(msg['pair'])}"
|
||||
f"*{'Profit' if is_fill else 'Unrealized Profit'}:* "
|
||||
f"`{msg['profit_ratio']:.2%}{msg['profit_extra']}`\n"
|
||||
f"*Enter Tag:* `{msg['enter_tag']}`\n"
|
||||
|
|
|
|||
|
|
@ -191,6 +191,7 @@ def detect_parameters(
|
|||
and attr.category is not None and attr.category != category):
|
||||
raise OperationalException(
|
||||
f'Inconclusive parameter name {attr_name}, category: {attr.category}.')
|
||||
|
||||
if (category == attr.category or
|
||||
(attr_name.startswith(category + '_') and attr.category is None)):
|
||||
yield attr_name, attr
|
||||
|
|
|
|||
|
|
@ -442,7 +442,8 @@ class IStrategy(ABC, HyperStrategyMixin):
|
|||
|
||||
def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
|
||||
proposed_stake: float, min_stake: Optional[float], max_stake: float,
|
||||
entry_tag: Optional[str], side: str, **kwargs) -> float:
|
||||
leverage: float, entry_tag: Optional[str], side: str,
|
||||
**kwargs) -> float:
|
||||
"""
|
||||
Customize stake size for each new trade.
|
||||
|
||||
|
|
@ -452,6 +453,7 @@ class IStrategy(ABC, HyperStrategyMixin):
|
|||
:param proposed_stake: A stake amount proposed by the bot.
|
||||
:param min_stake: Minimal stake size allowed by exchange.
|
||||
:param max_stake: Balance available for trading.
|
||||
:param leverage: Leverage selected for this trade.
|
||||
:param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
|
||||
:param side: 'long' or 'short' - indicating the direction of the proposed trade
|
||||
:return: A stake size, which is between min_stake and max_stake.
|
||||
|
|
|
|||
|
|
@ -51,11 +51,13 @@
|
|||
"source": [
|
||||
"# Load data using values set above\n",
|
||||
"from freqtrade.data.history import load_pair_history\n",
|
||||
"from freqtrade.enums import CandleType\n",
|
||||
"\n",
|
||||
"candles = load_pair_history(datadir=data_location,\n",
|
||||
" timeframe=config[\"timeframe\"],\n",
|
||||
" pair=pair,\n",
|
||||
" data_format = \"hdf5\",\n",
|
||||
" candle_type=CandleType.SPOT,\n",
|
||||
" )\n",
|
||||
"\n",
|
||||
"# Confirm success\n",
|
||||
|
|
|
|||
|
|
@ -79,9 +79,10 @@ def custom_exit_price(self, pair: str, trade: 'Trade',
|
|||
"""
|
||||
return proposed_rate
|
||||
|
||||
def custom_stake_amount(self, pair: str, current_time: 'datetime', current_rate: float,
|
||||
def custom_stake_amount(self, pair: str, current_time: datetime, current_rate: float,
|
||||
proposed_stake: float, min_stake: Optional[float], max_stake: float,
|
||||
entry_tag: 'Optional[str]', side: str, **kwargs) -> float:
|
||||
leverage: float, entry_tag: Optional[str], side: str,
|
||||
**kwargs) -> float:
|
||||
"""
|
||||
Customize stake size for each new trade.
|
||||
|
||||
|
|
@ -91,6 +92,7 @@ def custom_stake_amount(self, pair: str, current_time: 'datetime', current_rate:
|
|||
:param proposed_stake: A stake amount proposed by the bot.
|
||||
:param min_stake: Minimal stake size allowed by exchange.
|
||||
:param max_stake: Balance available for trading.
|
||||
:param leverage: Leverage selected for this trade.
|
||||
:param entry_tag: Optional entry_tag (buy_tag) if provided with the buy signal.
|
||||
:param side: 'long' or 'short' - indicating the direction of the proposed trade
|
||||
:return: A stake size, which is between min_stake and max_stake.
|
||||
|
|
|
|||
|
|
@ -7,12 +7,12 @@
|
|||
coveralls==3.3.1
|
||||
flake8==4.0.1
|
||||
flake8-tidy-imports==4.8.0
|
||||
mypy==0.961
|
||||
pre-commit==2.19.0
|
||||
mypy==0.971
|
||||
pre-commit==2.20.0
|
||||
pytest==7.1.2
|
||||
pytest-asyncio==0.18.3
|
||||
pytest-asyncio==0.19.0
|
||||
pytest-cov==3.0.0
|
||||
pytest-mock==3.8.1
|
||||
pytest-mock==3.8.2
|
||||
pytest-random-order==1.0.4
|
||||
isort==5.10.1
|
||||
# For datetime mocking
|
||||
|
|
@ -24,6 +24,6 @@ nbconvert==6.5.0
|
|||
# mypy types
|
||||
types-cachetools==5.2.1
|
||||
types-filelock==3.2.7
|
||||
types-requests==2.28.0
|
||||
types-requests==2.28.3
|
||||
types-tabulate==0.8.11
|
||||
types-python-dateutil==2.8.18
|
||||
types-python-dateutil==2.8.19
|
||||
|
|
|
|||
|
|
@ -1,18 +1,18 @@
|
|||
numpy==1.23.0
|
||||
numpy==1.23.1
|
||||
pandas==1.4.3
|
||||
pandas-ta==0.3.14b
|
||||
|
||||
ccxt==1.89.14
|
||||
ccxt==1.91.29
|
||||
# Pin cryptography for now due to rust build errors with piwheels
|
||||
cryptography==37.0.2
|
||||
cryptography==37.0.4
|
||||
aiohttp==3.8.1
|
||||
SQLAlchemy==1.4.39
|
||||
python-telegram-bot==13.12
|
||||
python-telegram-bot==13.13
|
||||
arrow==1.2.2
|
||||
cachetools==4.2.2
|
||||
requests==2.28.0
|
||||
urllib3==1.26.9
|
||||
jsonschema==4.6.0
|
||||
requests==2.28.1
|
||||
urllib3==1.26.10
|
||||
jsonschema==4.7.2
|
||||
TA-Lib==0.4.24
|
||||
technical==1.3.0
|
||||
tabulate==0.8.10
|
||||
|
|
@ -26,16 +26,16 @@ joblib==1.1.0
|
|||
py_find_1st==1.1.5
|
||||
|
||||
# Load ticker files 30% faster
|
||||
python-rapidjson==1.6
|
||||
python-rapidjson==1.8
|
||||
# Properly format api responses
|
||||
orjson==3.7.3
|
||||
orjson==3.7.8
|
||||
|
||||
# Notify systemd
|
||||
sdnotify==0.3.2
|
||||
|
||||
# API Server
|
||||
fastapi==0.78.0
|
||||
uvicorn==0.18.1
|
||||
fastapi==0.79.0
|
||||
uvicorn==0.18.2
|
||||
pyjwt==2.4.0
|
||||
aiofiles==0.8.0
|
||||
psutil==5.9.1
|
||||
|
|
@ -44,7 +44,7 @@ psutil==5.9.1
|
|||
colorama==0.4.5
|
||||
# Building config files interactively
|
||||
questionary==1.10.0
|
||||
prompt-toolkit==3.0.29
|
||||
prompt-toolkit==3.0.30
|
||||
# Extensions to datetime library
|
||||
python-dateutil==2.8.2
|
||||
|
||||
|
|
|
|||
|
|
@ -112,11 +112,8 @@ def patch_exchange(
|
|||
mock_supported_modes=True
|
||||
) -> None:
|
||||
mocker.patch('freqtrade.exchange.Exchange._load_async_markets', MagicMock(return_value={}))
|
||||
mocker.patch('freqtrade.exchange.Exchange.validate_pairs', MagicMock())
|
||||
mocker.patch('freqtrade.exchange.Exchange.validate_config', MagicMock())
|
||||
mocker.patch('freqtrade.exchange.Exchange.validate_timeframes', MagicMock())
|
||||
mocker.patch('freqtrade.exchange.Exchange.validate_ordertypes', MagicMock())
|
||||
mocker.patch('freqtrade.exchange.Exchange.validate_stakecurrency', MagicMock())
|
||||
mocker.patch('freqtrade.exchange.Exchange.validate_pricing')
|
||||
mocker.patch('freqtrade.exchange.Exchange.id', PropertyMock(return_value=id))
|
||||
mocker.patch('freqtrade.exchange.Exchange.name', PropertyMock(return_value=id.title()))
|
||||
mocker.patch('freqtrade.exchange.Exchange.precisionMode', PropertyMock(return_value=2))
|
||||
|
|
@ -151,7 +148,7 @@ def get_patched_exchange(mocker, config, api_mock=None, id='binance',
|
|||
patch_exchange(mocker, api_mock, id, mock_markets, mock_supported_modes)
|
||||
config['exchange']['name'] = id
|
||||
try:
|
||||
exchange = ExchangeResolver.load_exchange(id, config)
|
||||
exchange = ExchangeResolver.load_exchange(id, config, load_leverage_tiers=True)
|
||||
except ImportError:
|
||||
exchange = Exchange(config)
|
||||
return exchange
|
||||
|
|
@ -1694,6 +1691,7 @@ def limit_buy_order_old_partial():
|
|||
'price': 0.00001099,
|
||||
'amount': 90.99181073,
|
||||
'filled': 23.0,
|
||||
'cost': 90.99181073 * 23.0,
|
||||
'remaining': 67.99181073,
|
||||
'status': 'open'
|
||||
}
|
||||
|
|
@ -2611,7 +2609,7 @@ def open_trade_usdt():
|
|||
pair='ADA/USDT',
|
||||
open_rate=2.0,
|
||||
exchange='binance',
|
||||
open_order_id='123456789',
|
||||
open_order_id='123456789_exit',
|
||||
amount=30.0,
|
||||
fee_open=0.0,
|
||||
fee_close=0.0,
|
||||
|
|
@ -2636,6 +2634,23 @@ def open_trade_usdt():
|
|||
cost=trade.open_rate * trade.amount,
|
||||
order_date=trade.open_date,
|
||||
order_filled_date=trade.open_date,
|
||||
),
|
||||
Order(
|
||||
ft_order_side='exit',
|
||||
ft_pair=trade.pair,
|
||||
ft_is_open=True,
|
||||
order_id='123456789_exit',
|
||||
status="open",
|
||||
symbol=trade.pair,
|
||||
order_type="limit",
|
||||
side="sell",
|
||||
price=trade.open_rate,
|
||||
average=trade.open_rate,
|
||||
filled=trade.amount,
|
||||
remaining=0,
|
||||
cost=trade.open_rate * trade.amount,
|
||||
order_date=trade.open_date,
|
||||
order_filled_date=trade.open_date,
|
||||
)
|
||||
]
|
||||
return trade
|
||||
|
|
@ -3165,60 +3180,46 @@ def leverage_tiers():
|
|||
"AAVE/USDT": [
|
||||
{
|
||||
'min': 0,
|
||||
'max': 50000,
|
||||
'max': 5000,
|
||||
'mmr': 0.01,
|
||||
'lev': 50,
|
||||
'maintAmt': 0.0
|
||||
},
|
||||
{
|
||||
'min': 50000,
|
||||
'max': 250000,
|
||||
'min': 5000,
|
||||
'max': 25000,
|
||||
'mmr': 0.02,
|
||||
'lev': 25,
|
||||
'maintAmt': 500.0
|
||||
'maintAmt': 75.0
|
||||
},
|
||||
{
|
||||
'min': 25000,
|
||||
'max': 100000,
|
||||
'mmr': 0.05,
|
||||
'lev': 10,
|
||||
'maintAmt': 700.0
|
||||
},
|
||||
{
|
||||
'min': 100000,
|
||||
'max': 250000,
|
||||
'mmr': 0.1,
|
||||
'lev': 5,
|
||||
'maintAmt': 5700.0
|
||||
},
|
||||
{
|
||||
'min': 250000,
|
||||
'max': 1000000,
|
||||
'mmr': 0.05,
|
||||
'lev': 10,
|
||||
'maintAmt': 8000.0
|
||||
},
|
||||
{
|
||||
'min': 1000000,
|
||||
'max': 2000000,
|
||||
'mmr': 0.1,
|
||||
'lev': 5,
|
||||
'maintAmt': 58000.0
|
||||
},
|
||||
{
|
||||
'min': 2000000,
|
||||
'max': 5000000,
|
||||
'mmr': 0.125,
|
||||
'lev': 4,
|
||||
'maintAmt': 108000.0
|
||||
},
|
||||
{
|
||||
'min': 5000000,
|
||||
'max': 10000000,
|
||||
'mmr': 0.1665,
|
||||
'lev': 3,
|
||||
'maintAmt': 315500.0
|
||||
'lev': 2,
|
||||
'maintAmt': 11950.0
|
||||
},
|
||||
{
|
||||
'min': 10000000,
|
||||
'max': 20000000,
|
||||
'mmr': 0.25,
|
||||
'lev': 2,
|
||||
'maintAmt': 1150500.0
|
||||
'max': 50000000,
|
||||
'mmr': 0.5,
|
||||
'lev': 1,
|
||||
'maintAmt': 386950.0
|
||||
},
|
||||
{
|
||||
"min": 20000000,
|
||||
"max": 50000000,
|
||||
"mmr": 0.5,
|
||||
"lev": 1,
|
||||
"maintAmt": 6150500.0
|
||||
}
|
||||
],
|
||||
"ADA/BUSD": [
|
||||
{
|
||||
|
|
|
|||
|
|
@ -137,7 +137,8 @@ def exchange_futures(request, exchange_conf, class_mocker):
|
|||
'freqtrade.exchange.binance.Binance.fill_leverage_tiers')
|
||||
class_mocker.patch('freqtrade.exchange.exchange.Exchange.fetch_trading_fees')
|
||||
class_mocker.patch('freqtrade.exchange.okx.Okx.additional_exchange_init')
|
||||
exchange = ExchangeResolver.load_exchange(request.param, exchange_conf, validate=True)
|
||||
exchange = ExchangeResolver.load_exchange(
|
||||
request.param, exchange_conf, validate=True, load_leverage_tiers=True)
|
||||
|
||||
yield exchange, request.param
|
||||
|
||||
|
|
@ -153,6 +154,25 @@ class TestCCXTExchange():
|
|||
assert isinstance(markets[pair], dict)
|
||||
assert exchange.market_is_spot(markets[pair])
|
||||
|
||||
def test_has_validations(self, exchange):
|
||||
|
||||
exchange, exchangename = exchange
|
||||
|
||||
exchange.validate_ordertypes({
|
||||
'entry': 'limit',
|
||||
'exit': 'limit',
|
||||
'stoploss': 'limit',
|
||||
})
|
||||
|
||||
if exchangename == 'gateio':
|
||||
# gateio doesn't have market orders on spot
|
||||
return
|
||||
exchange.validate_ordertypes({
|
||||
'entry': 'market',
|
||||
'exit': 'market',
|
||||
'stoploss': 'market',
|
||||
})
|
||||
|
||||
def test_load_markets_futures(self, exchange_futures):
|
||||
exchange, exchangename = exchange_futures
|
||||
if not exchange:
|
||||
|
|
|
|||
|
|
@ -1135,7 +1135,58 @@ def test_create_dry_run_order(default_conf, mocker, side, exchange_name, leverag
|
|||
assert order["symbol"] == "ETH/BTC"
|
||||
assert order["amount"] == 1
|
||||
assert order["leverage"] == leverage
|
||||
assert order["cost"] == 1 * 200 / leverage
|
||||
assert order["cost"] == 1 * 200
|
||||
|
||||
|
||||
@pytest.mark.parametrize('side,is_short,order_reason', [
|
||||
("buy", False, "entry"),
|
||||
("sell", False, "exit"),
|
||||
("buy", True, "exit"),
|
||||
("sell", True, "entry"),
|
||||
])
|
||||
@pytest.mark.parametrize("order_type,price_side,fee", [
|
||||
("limit", "same", 1.0),
|
||||
("limit", "other", 2.0),
|
||||
("market", "same", 2.0),
|
||||
("market", "other", 2.0),
|
||||
])
|
||||
def test_create_dry_run_order_fees(
|
||||
default_conf,
|
||||
mocker,
|
||||
side,
|
||||
order_type,
|
||||
is_short,
|
||||
order_reason,
|
||||
price_side,
|
||||
fee,
|
||||
):
|
||||
mocker.patch(
|
||||
'freqtrade.exchange.Exchange.get_fee',
|
||||
side_effect=lambda symbol, taker_or_maker: 2.0 if taker_or_maker == 'taker' else 1.0
|
||||
)
|
||||
mocker.patch('freqtrade.exchange.Exchange._is_dry_limit_order_filled',
|
||||
return_value=price_side == 'other')
|
||||
exchange = get_patched_exchange(mocker, default_conf)
|
||||
|
||||
order = exchange.create_dry_run_order(
|
||||
pair='LTC/USDT',
|
||||
ordertype=order_type,
|
||||
side=side,
|
||||
amount=10,
|
||||
rate=2.0,
|
||||
leverage=1.0
|
||||
)
|
||||
if price_side == 'other' or order_type == 'market':
|
||||
assert order['fee']['rate'] == fee
|
||||
return
|
||||
else:
|
||||
assert order['fee'] is None
|
||||
|
||||
mocker.patch('freqtrade.exchange.Exchange._is_dry_limit_order_filled',
|
||||
return_value=price_side != 'other')
|
||||
|
||||
order1 = exchange.fetch_dry_run_order(order['id'])
|
||||
assert order1['fee']['rate'] == fee
|
||||
|
||||
|
||||
@pytest.mark.parametrize("side,startprice,endprice", [
|
||||
|
|
@ -2859,6 +2910,9 @@ def test_check_order_canceled_empty(mocker, default_conf, exchange_name, order,
|
|||
({'amount': 10.0, 'fee': {}}, False),
|
||||
({'result': 'testest123'}, False),
|
||||
('hello_world', False),
|
||||
({'status': 'canceled', 'amount': None, 'fee': None}, False),
|
||||
({'status': 'canceled', 'filled': None, 'amount': None, 'fee': None}, False),
|
||||
|
||||
])
|
||||
def test_is_cancel_order_result_suitable(mocker, default_conf, exchange_name, order, result):
|
||||
exchange = get_patched_exchange(mocker, default_conf, id=exchange_name)
|
||||
|
|
@ -3544,7 +3598,7 @@ def test_order_has_fee(order, expected) -> None:
|
|||
def test_extract_cost_curr_rate(mocker, default_conf, order, expected) -> None:
|
||||
mocker.patch('freqtrade.exchange.Exchange.calculate_fee_rate', MagicMock(return_value=0.01))
|
||||
ex = get_patched_exchange(mocker, default_conf)
|
||||
assert ex.extract_cost_curr_rate(order) == expected
|
||||
assert ex.extract_cost_curr_rate(order['fee'], order['symbol'], cost=20, amount=1) == expected
|
||||
|
||||
|
||||
@pytest.mark.parametrize("order,unknown_fee_rate,expected", [
|
||||
|
|
@ -3582,6 +3636,9 @@ def test_extract_cost_curr_rate(mocker, default_conf, order, expected) -> None:
|
|||
'fee': {'currency': 'POINT', 'cost': 2.0, 'rate': None}}, 1, 4.0),
|
||||
({'symbol': 'POINT/BTC', 'amount': 0.04, 'cost': 0.5,
|
||||
'fee': {'currency': 'POINT', 'cost': 2.0, 'rate': None}}, 2, 8.0),
|
||||
# Missing currency
|
||||
({'symbol': 'ETH/BTC', 'amount': 0.04, 'cost': 0.05,
|
||||
'fee': {'currency': None, 'cost': 0.005}}, None, None),
|
||||
])
|
||||
def test_calculate_fee_rate(mocker, default_conf, order, expected, unknown_fee_rate) -> None:
|
||||
mocker.patch('freqtrade.exchange.Exchange.fetch_ticker', return_value={'last': 0.081})
|
||||
|
|
@ -3590,7 +3647,8 @@ def test_calculate_fee_rate(mocker, default_conf, order, expected, unknown_fee_r
|
|||
|
||||
ex = get_patched_exchange(mocker, default_conf)
|
||||
|
||||
assert ex.calculate_fee_rate(order) == expected
|
||||
assert ex.calculate_fee_rate(order['fee'], order['symbol'],
|
||||
cost=order['cost'], amount=order['amount']) == expected
|
||||
|
||||
|
||||
@pytest.mark.parametrize('retrycount,max_retries,expected', [
|
||||
|
|
|
|||
|
|
@ -53,6 +53,25 @@ def test_fetch_stoploss_order_gateio(default_conf, mocker):
|
|||
assert fetch_order_mock.call_args_list[0][1]['pair'] == 'ETH/BTC'
|
||||
assert fetch_order_mock.call_args_list[0][1]['params'] == {'stop': True}
|
||||
|
||||
default_conf['trading_mode'] = 'futures'
|
||||
default_conf['margin_mode'] = 'isolated'
|
||||
|
||||
exchange = get_patched_exchange(mocker, default_conf, id='gateio')
|
||||
|
||||
exchange.fetch_order = MagicMock(return_value={
|
||||
'status': 'closed',
|
||||
'id': '1234',
|
||||
'stopPrice': 5.62,
|
||||
'info': {
|
||||
'trade_id': '222555'
|
||||
}
|
||||
})
|
||||
|
||||
exchange.fetch_stoploss_order('1234', 'ETH/BTC')
|
||||
assert exchange.fetch_order.call_count == 2
|
||||
assert exchange.fetch_order.call_args_list[0][1]['order_id'] == '1234'
|
||||
assert exchange.fetch_order.call_args_list[1][1]['order_id'] == '222555'
|
||||
|
||||
|
||||
def test_cancel_stoploss_order_gateio(default_conf, mocker):
|
||||
exchange = get_patched_exchange(mocker, default_conf, id='gateio')
|
||||
|
|
|
|||
|
|
@ -18,11 +18,11 @@ def hyperopt_conf(default_conf):
|
|||
'runmode': RunMode.HYPEROPT,
|
||||
'strategy': 'HyperoptableStrategy',
|
||||
'hyperopt_loss': 'ShortTradeDurHyperOptLoss',
|
||||
'hyperopt_path': str(Path(__file__).parent / 'hyperopts'),
|
||||
'epochs': 1,
|
||||
'timerange': None,
|
||||
'spaces': ['default'],
|
||||
'hyperopt_jobs': 1,
|
||||
'hyperopt_path': str(Path(__file__).parent / 'hyperopts'),
|
||||
'epochs': 1,
|
||||
'timerange': None,
|
||||
'spaces': ['default'],
|
||||
'hyperopt_jobs': 1,
|
||||
'hyperopt_min_trades': 1,
|
||||
})
|
||||
return hyperconf
|
||||
|
|
|
|||
|
|
@ -90,28 +90,6 @@ def load_data_test(what, testdatadir):
|
|||
fill_missing=True)}
|
||||
|
||||
|
||||
def simple_backtest(config, contour, mocker, testdatadir) -> None:
|
||||
patch_exchange(mocker)
|
||||
config['timeframe'] = '1m'
|
||||
backtesting = Backtesting(config)
|
||||
backtesting._set_strategy(backtesting.strategylist[0])
|
||||
|
||||
data = load_data_test(contour, testdatadir)
|
||||
processed = backtesting.strategy.advise_all_indicators(data)
|
||||
min_date, max_date = get_timerange(processed)
|
||||
assert isinstance(processed, dict)
|
||||
results = backtesting.backtest(
|
||||
processed=processed,
|
||||
start_date=min_date,
|
||||
end_date=max_date,
|
||||
max_open_trades=1,
|
||||
position_stacking=False,
|
||||
enable_protections=config.get('enable_protections', False),
|
||||
)
|
||||
# results :: <class 'pandas.core.frame.DataFrame'>
|
||||
return results
|
||||
|
||||
|
||||
# FIX: fixturize this?
|
||||
def _make_backtest_conf(mocker, datadir, conf=None, pair='UNITTEST/BTC'):
|
||||
data = history.load_data(datadir=datadir, timeframe='1m', pairs=[pair])
|
||||
|
|
@ -942,6 +920,7 @@ def test_backtest_dataprovider_analyzed_df(default_conf, fee, mocker, testdatadi
|
|||
def test_backtest_pricecontours_protections(default_conf, fee, mocker, testdatadir) -> None:
|
||||
# While this test IS a copy of test_backtest_pricecontours, it's needed to ensure
|
||||
# results do not carry-over to the next run, which is not given by using parametrize.
|
||||
patch_exchange(mocker)
|
||||
default_conf['protections'] = [
|
||||
{
|
||||
"method": "CooldownPeriod",
|
||||
|
|
@ -949,6 +928,7 @@ def test_backtest_pricecontours_protections(default_conf, fee, mocker, testdatad
|
|||
}]
|
||||
|
||||
default_conf['enable_protections'] = True
|
||||
default_conf['timeframe'] = '1m'
|
||||
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
|
||||
mocker.patch("freqtrade.exchange.Exchange.get_min_pair_stake_amount", return_value=0.00001)
|
||||
mocker.patch("freqtrade.exchange.Exchange.get_max_pair_stake_amount", return_value=float('inf'))
|
||||
|
|
@ -959,12 +939,27 @@ def test_backtest_pricecontours_protections(default_conf, fee, mocker, testdatad
|
|||
['sine', 9],
|
||||
['raise', 10],
|
||||
]
|
||||
backtesting = Backtesting(default_conf)
|
||||
backtesting._set_strategy(backtesting.strategylist[0])
|
||||
|
||||
# While entry-signals are unrealistic, running backtesting
|
||||
# over and over again should not cause different results
|
||||
for [contour, numres] in tests:
|
||||
# Debug output for random test failure
|
||||
print(f"{contour}, {numres}")
|
||||
assert len(simple_backtest(default_conf, contour, mocker, testdatadir)['results']) == numres
|
||||
data = load_data_test(contour, testdatadir)
|
||||
processed = backtesting.strategy.advise_all_indicators(data)
|
||||
min_date, max_date = get_timerange(processed)
|
||||
assert isinstance(processed, dict)
|
||||
results = backtesting.backtest(
|
||||
processed=processed,
|
||||
start_date=min_date,
|
||||
end_date=max_date,
|
||||
max_open_trades=1,
|
||||
position_stacking=False,
|
||||
enable_protections=default_conf.get('enable_protections', False),
|
||||
)
|
||||
assert len(results['results']) == numres
|
||||
|
||||
|
||||
@pytest.mark.parametrize('protections,contour,expected', [
|
||||
|
|
@ -990,7 +985,25 @@ def test_backtest_pricecontours(default_conf, fee, mocker, testdatadir,
|
|||
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
|
||||
# While entry-signals are unrealistic, running backtesting
|
||||
# over and over again should not cause different results
|
||||
assert len(simple_backtest(default_conf, contour, mocker, testdatadir)['results']) == expected
|
||||
|
||||
patch_exchange(mocker)
|
||||
default_conf['timeframe'] = '1m'
|
||||
backtesting = Backtesting(default_conf)
|
||||
backtesting._set_strategy(backtesting.strategylist[0])
|
||||
|
||||
data = load_data_test(contour, testdatadir)
|
||||
processed = backtesting.strategy.advise_all_indicators(data)
|
||||
min_date, max_date = get_timerange(processed)
|
||||
assert isinstance(processed, dict)
|
||||
results = backtesting.backtest(
|
||||
processed=processed,
|
||||
start_date=min_date,
|
||||
end_date=max_date,
|
||||
max_open_trades=1,
|
||||
position_stacking=False,
|
||||
enable_protections=default_conf.get('enable_protections', False),
|
||||
)
|
||||
assert len(results['results']) == expected
|
||||
|
||||
|
||||
def test_backtest_clash_buy_sell(mocker, default_conf, testdatadir):
|
||||
|
|
|
|||
|
|
@ -1,7 +1,7 @@
|
|||
# pragma pylint: disable=missing-docstring,W0212,C0103
|
||||
from datetime import datetime, timedelta
|
||||
from pathlib import Path
|
||||
from unittest.mock import ANY, MagicMock
|
||||
from unittest.mock import ANY, MagicMock, PropertyMock
|
||||
|
||||
import pandas as pd
|
||||
import pytest
|
||||
|
|
@ -18,8 +18,8 @@ from freqtrade.optimize.hyperopt_tools import HyperoptTools
|
|||
from freqtrade.optimize.optimize_reports import generate_strategy_stats
|
||||
from freqtrade.optimize.space import SKDecimal
|
||||
from freqtrade.strategy import IntParameter
|
||||
from tests.conftest import (CURRENT_TEST_STRATEGY, get_args, log_has, log_has_re, patch_exchange,
|
||||
patched_configuration_load_config_file)
|
||||
from tests.conftest import (CURRENT_TEST_STRATEGY, get_args, get_markets, log_has, log_has_re,
|
||||
patch_exchange, patched_configuration_load_config_file)
|
||||
|
||||
|
||||
def generate_result_metrics():
|
||||
|
|
@ -855,7 +855,7 @@ def test_in_strategy_auto_hyperopt(mocker, hyperopt_conf, tmpdir, fee) -> None:
|
|||
'strategy': 'HyperoptableStrategy',
|
||||
'user_data_dir': Path(tmpdir),
|
||||
'hyperopt_random_state': 42,
|
||||
'spaces': ['all']
|
||||
'spaces': ['all'],
|
||||
})
|
||||
hyperopt = Hyperopt(hyperopt_conf)
|
||||
hyperopt.backtesting.exchange.get_max_leverage = MagicMock(return_value=1.0)
|
||||
|
|
@ -883,6 +883,45 @@ def test_in_strategy_auto_hyperopt(mocker, hyperopt_conf, tmpdir, fee) -> None:
|
|||
hyperopt.get_optimizer([], 2)
|
||||
|
||||
|
||||
def test_in_strategy_auto_hyperopt_with_parallel(mocker, hyperopt_conf, tmpdir, fee) -> None:
|
||||
mocker.patch('freqtrade.exchange.Exchange.validate_config', MagicMock())
|
||||
mocker.patch('freqtrade.exchange.Exchange.get_fee', fee)
|
||||
mocker.patch('freqtrade.exchange.Exchange._load_markets')
|
||||
mocker.patch('freqtrade.exchange.Exchange.markets',
|
||||
PropertyMock(return_value=get_markets()))
|
||||
(Path(tmpdir) / 'hyperopt_results').mkdir(parents=True)
|
||||
# No hyperopt needed
|
||||
hyperopt_conf.update({
|
||||
'strategy': 'HyperoptableStrategy',
|
||||
'user_data_dir': Path(tmpdir),
|
||||
'hyperopt_random_state': 42,
|
||||
'spaces': ['all'],
|
||||
# Enforce parallelity
|
||||
'epochs': 2,
|
||||
'hyperopt_jobs': 2,
|
||||
'fee': fee.return_value,
|
||||
})
|
||||
hyperopt = Hyperopt(hyperopt_conf)
|
||||
hyperopt.backtesting.exchange.get_max_leverage = lambda *x, **xx: 1.0
|
||||
hyperopt.backtesting.exchange.get_min_pair_stake_amount = lambda *x, **xx: 1.0
|
||||
hyperopt.backtesting.exchange.get_max_pair_stake_amount = lambda *x, **xx: 100.0
|
||||
|
||||
assert isinstance(hyperopt.custom_hyperopt, HyperOptAuto)
|
||||
assert isinstance(hyperopt.backtesting.strategy.buy_rsi, IntParameter)
|
||||
assert hyperopt.backtesting.strategy.bot_loop_started is True
|
||||
|
||||
assert hyperopt.backtesting.strategy.buy_rsi.in_space is True
|
||||
assert hyperopt.backtesting.strategy.buy_rsi.value == 35
|
||||
assert hyperopt.backtesting.strategy.sell_rsi.value == 74
|
||||
assert hyperopt.backtesting.strategy.protection_cooldown_lookback.value == 30
|
||||
buy_rsi_range = hyperopt.backtesting.strategy.buy_rsi.range
|
||||
assert isinstance(buy_rsi_range, range)
|
||||
# Range from 0 - 50 (inclusive)
|
||||
assert len(list(buy_rsi_range)) == 51
|
||||
|
||||
hyperopt.start()
|
||||
|
||||
|
||||
def test_SKDecimal():
|
||||
space = SKDecimal(1, 2, decimals=2)
|
||||
assert 1.5 in space
|
||||
|
|
|
|||
|
|
@ -6,6 +6,7 @@ import pytest
|
|||
from freqtrade import constants
|
||||
from freqtrade.enums import ExitType
|
||||
from freqtrade.persistence import PairLocks, Trade
|
||||
from freqtrade.persistence.trade_model import Order
|
||||
from freqtrade.plugins.protectionmanager import ProtectionManager
|
||||
from tests.conftest import get_patched_freqtradebot, log_has_re
|
||||
|
||||
|
|
@ -30,7 +31,37 @@ def generate_mock_trade(pair: str, fee: float, is_open: bool,
|
|||
amount=0.01 / open_rate,
|
||||
exchange='binance',
|
||||
is_short=is_short,
|
||||
leverage=1,
|
||||
)
|
||||
|
||||
trade.orders.append(Order(
|
||||
ft_order_side=trade.entry_side,
|
||||
order_id=f'{pair}-{trade.entry_side}-{trade.open_date}',
|
||||
ft_pair=pair,
|
||||
amount=trade.amount,
|
||||
filled=trade.amount,
|
||||
remaining=0,
|
||||
price=open_rate,
|
||||
average=open_rate,
|
||||
status="closed",
|
||||
order_type="market",
|
||||
side=trade.entry_side,
|
||||
))
|
||||
if not is_open:
|
||||
trade.orders.append(Order(
|
||||
ft_order_side=trade.exit_side,
|
||||
order_id=f'{pair}-{trade.exit_side}-{trade.close_date}',
|
||||
ft_pair=pair,
|
||||
amount=trade.amount,
|
||||
filled=trade.amount,
|
||||
remaining=0,
|
||||
price=open_rate * (2 - profit_rate if is_short else profit_rate),
|
||||
average=open_rate * (2 - profit_rate if is_short else profit_rate),
|
||||
status="closed",
|
||||
order_type="market",
|
||||
side=trade.exit_side,
|
||||
))
|
||||
|
||||
trade.recalc_open_trade_value()
|
||||
if not is_open:
|
||||
trade.close(open_rate * (2 - profit_rate if is_short else profit_rate))
|
||||
|
|
@ -393,7 +424,7 @@ def test_MaxDrawdown(mocker, default_conf, fee, caplog):
|
|||
@pytest.mark.parametrize("protectionconf,desc_expected,exception_expected", [
|
||||
({"method": "StoplossGuard", "lookback_period": 60, "trade_limit": 2, "stop_duration": 60},
|
||||
"[{'StoplossGuard': 'StoplossGuard - Frequent Stoploss Guard, "
|
||||
"2 stoplosses within 60 minutes.'}]",
|
||||
"2 stoplosses with profit < 0.00% within 60 minutes.'}]",
|
||||
None
|
||||
),
|
||||
({"method": "CooldownPeriod", "stop_duration": 60},
|
||||
|
|
@ -411,9 +442,9 @@ def test_MaxDrawdown(mocker, default_conf, fee, caplog):
|
|||
None
|
||||
),
|
||||
({"method": "StoplossGuard", "lookback_period_candles": 12, "trade_limit": 2,
|
||||
"stop_duration": 60},
|
||||
"required_profit": -0.05, "stop_duration": 60},
|
||||
"[{'StoplossGuard': 'StoplossGuard - Frequent Stoploss Guard, "
|
||||
"2 stoplosses within 12 candles.'}]",
|
||||
"2 stoplosses with profit < -5.00% within 12 candles.'}]",
|
||||
None
|
||||
),
|
||||
({"method": "CooldownPeriod", "stop_duration_candles": 5},
|
||||
|
|
|
|||
|
|
@ -830,6 +830,8 @@ def test_rpc_force_exit(default_conf, ticker, fee, mocker) -> None:
|
|||
assert cancel_order_mock.call_count == 2
|
||||
assert trade.amount == amount
|
||||
|
||||
trade = Trade.query.filter(Trade.id == '3').first()
|
||||
|
||||
# make an limit-sell open trade
|
||||
mocker.patch(
|
||||
'freqtrade.exchange.Exchange.fetch_order',
|
||||
|
|
|
|||
|
|
@ -1398,10 +1398,10 @@ def test_api_strategies(botclient):
|
|||
|
||||
assert rc.json() == {'strategies': [
|
||||
'HyperoptableStrategy',
|
||||
'HyperoptableStrategyV2',
|
||||
'InformativeDecoratorTest',
|
||||
'StrategyTestV2',
|
||||
'StrategyTestV3',
|
||||
'StrategyTestV3Analysis',
|
||||
'StrategyTestV3Futures'
|
||||
]}
|
||||
|
||||
|
|
|
|||
|
|
@ -12,6 +12,7 @@ from unittest.mock import ANY, MagicMock
|
|||
|
||||
import arrow
|
||||
import pytest
|
||||
from pandas import DataFrame
|
||||
from telegram import Chat, Message, ReplyKeyboardMarkup, Update
|
||||
from telegram.error import BadRequest, NetworkError, TelegramError
|
||||
|
||||
|
|
@ -685,6 +686,7 @@ def test_profit_handle(default_conf_usdt, update, ticker_usdt, ticker_sell_up, f
|
|||
# Simulate fulfilled LIMIT_SELL order for trade
|
||||
oobj = Order.parse_from_ccxt_object(
|
||||
limit_sell_order_usdt, limit_sell_order_usdt['symbol'], 'sell')
|
||||
trade.orders.append(oobj)
|
||||
trade.update_trade(oobj)
|
||||
|
||||
trade.close_date = datetime.now(timezone.utc)
|
||||
|
|
@ -706,7 +708,7 @@ def test_profit_handle(default_conf_usdt, update, ticker_usdt, ticker_sell_up, f
|
|||
assert '*Best Performing:* `ETH/USDT: 9.45%`' in msg_mock.call_args_list[-1][0][0]
|
||||
assert '*Max Drawdown:*' in msg_mock.call_args_list[-1][0][0]
|
||||
assert '*Profit factor:*' in msg_mock.call_args_list[-1][0][0]
|
||||
assert '*Trading volume:* `60 USDT`' in msg_mock.call_args_list[-1][0][0]
|
||||
assert '*Trading volume:* `126 USDT`' in msg_mock.call_args_list[-1][0][0]
|
||||
|
||||
|
||||
@pytest.mark.parametrize('is_short', [True, False])
|
||||
|
|
@ -1655,8 +1657,17 @@ def test_show_config_handle(default_conf, update, mocker) -> None:
|
|||
(RPCMessageType.ENTRY, 'Long', 'long_signal_01', 1.0),
|
||||
(RPCMessageType.ENTRY, 'Long', 'long_signal_01', 5.0),
|
||||
(RPCMessageType.ENTRY, 'Short', 'short_signal_01', 2.0)])
|
||||
def test_send_msg_buy_notification(default_conf, mocker, caplog, message_type,
|
||||
enter, enter_signal, leverage) -> None:
|
||||
def test_send_msg_enter_notification(default_conf, mocker, caplog, message_type,
|
||||
enter, enter_signal, leverage) -> None:
|
||||
default_conf['telegram']['notification_settings']['show_candle'] = 'ohlc'
|
||||
df = DataFrame({
|
||||
'open': [1.1],
|
||||
'high': [2.2],
|
||||
'low': [1.0],
|
||||
'close': [1.5],
|
||||
})
|
||||
mocker.patch('freqtrade.data.dataprovider.DataProvider.get_analyzed_dataframe',
|
||||
return_value=(df, 1))
|
||||
|
||||
msg = {
|
||||
'type': message_type,
|
||||
|
|
@ -1674,6 +1685,7 @@ def test_send_msg_buy_notification(default_conf, mocker, caplog, message_type,
|
|||
'fiat_currency': 'USD',
|
||||
'current_rate': 1.099e-05,
|
||||
'amount': 1333.3333333333335,
|
||||
'analyzed_candle': {'open': 1.1, 'high': 2.2, 'low': 1.0, 'close': 1.5},
|
||||
'open_date': arrow.utcnow().shift(hours=-1)
|
||||
}
|
||||
telegram, freqtradebot, msg_mock = get_telegram_testobject(mocker, default_conf)
|
||||
|
|
@ -1683,6 +1695,7 @@ def test_send_msg_buy_notification(default_conf, mocker, caplog, message_type,
|
|||
|
||||
assert msg_mock.call_args[0][0] == (
|
||||
f'\N{LARGE BLUE CIRCLE} *Binance (dry):* {enter} ETH/BTC (#1)\n'
|
||||
'*Candle OHLC*: `1.1, 2.2, 1.0, 1.5`\n'
|
||||
f'*Enter Tag:* `{enter_signal}`\n'
|
||||
'*Amount:* `1333.33333333`\n'
|
||||
f'{leverage_text}'
|
||||
|
|
@ -1710,7 +1723,8 @@ def test_send_msg_buy_notification(default_conf, mocker, caplog, message_type,
|
|||
@pytest.mark.parametrize('message_type,enter_signal', [
|
||||
(RPCMessageType.ENTRY_CANCEL, 'long_signal_01'),
|
||||
(RPCMessageType.ENTRY_CANCEL, 'short_signal_01')])
|
||||
def test_send_msg_buy_cancel_notification(default_conf, mocker, message_type, enter_signal) -> None:
|
||||
def test_send_msg_enter_cancel_notification(
|
||||
default_conf, mocker, message_type, enter_signal) -> None:
|
||||
|
||||
telegram, _, msg_mock = get_telegram_testobject(mocker, default_conf)
|
||||
|
||||
|
|
|
|||
|
|
@ -1,13 +1,13 @@
|
|||
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
|
||||
|
||||
from pandas import DataFrame
|
||||
from strategy_test_v2 import StrategyTestV2
|
||||
from strategy_test_v3 import StrategyTestV3
|
||||
|
||||
import freqtrade.vendor.qtpylib.indicators as qtpylib
|
||||
from freqtrade.strategy import BooleanParameter, DecimalParameter, IntParameter, RealParameter
|
||||
|
||||
|
||||
class HyperoptableStrategy(StrategyTestV2):
|
||||
class HyperoptableStrategy(StrategyTestV3):
|
||||
"""
|
||||
Default Strategy provided by freqtrade bot.
|
||||
Please do not modify this strategy, it's intended for internal use only.
|
||||
|
|
|
|||
54
tests/strategy/strats/hyperoptable_strategy_v2.py
Normal file
54
tests/strategy/strats/hyperoptable_strategy_v2.py
Normal file
|
|
@ -0,0 +1,54 @@
|
|||
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
|
||||
|
||||
from strategy_test_v2 import StrategyTestV2
|
||||
|
||||
from freqtrade.strategy import BooleanParameter, DecimalParameter, IntParameter, RealParameter
|
||||
|
||||
|
||||
class HyperoptableStrategyV2(StrategyTestV2):
|
||||
"""
|
||||
Default Strategy provided by freqtrade bot.
|
||||
Please do not modify this strategy, it's intended for internal use only.
|
||||
Please look at the SampleStrategy in the user_data/strategy directory
|
||||
or strategy repository https://github.com/freqtrade/freqtrade-strategies
|
||||
for samples and inspiration.
|
||||
"""
|
||||
|
||||
buy_params = {
|
||||
'buy_rsi': 35,
|
||||
# Intentionally not specified, so "default" is tested
|
||||
# 'buy_plusdi': 0.4
|
||||
}
|
||||
|
||||
sell_params = {
|
||||
'sell_rsi': 74,
|
||||
'sell_minusdi': 0.4
|
||||
}
|
||||
|
||||
buy_plusdi = RealParameter(low=0, high=1, default=0.5, space='buy')
|
||||
sell_rsi = IntParameter(low=50, high=100, default=70, space='sell')
|
||||
sell_minusdi = DecimalParameter(low=0, high=1, default=0.5001, decimals=3, space='sell',
|
||||
load=False)
|
||||
protection_enabled = BooleanParameter(default=True)
|
||||
protection_cooldown_lookback = IntParameter([0, 50], default=30)
|
||||
|
||||
@property
|
||||
def protections(self):
|
||||
prot = []
|
||||
if self.protection_enabled.value:
|
||||
prot.append({
|
||||
"method": "CooldownPeriod",
|
||||
"stop_duration_candles": self.protection_cooldown_lookback.value
|
||||
})
|
||||
return prot
|
||||
|
||||
bot_loop_started = False
|
||||
|
||||
def bot_loop_start(self):
|
||||
self.bot_loop_started = True
|
||||
|
||||
def bot_start(self, **kwargs) -> None:
|
||||
"""
|
||||
Parameters can also be defined here ...
|
||||
"""
|
||||
self.buy_rsi = IntParameter([0, 50], default=30, space='buy')
|
||||
|
|
@ -1,175 +0,0 @@
|
|||
# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
|
||||
|
||||
import talib.abstract as ta
|
||||
from pandas import DataFrame
|
||||
|
||||
import freqtrade.vendor.qtpylib.indicators as qtpylib
|
||||
from freqtrade.strategy import (BooleanParameter, DecimalParameter, IntParameter, IStrategy,
|
||||
RealParameter)
|
||||
|
||||
|
||||
class StrategyTestV3Analysis(IStrategy):
|
||||
"""
|
||||
Strategy used by tests freqtrade bot.
|
||||
Please do not modify this strategy, it's intended for internal use only.
|
||||
Please look at the SampleStrategy in the user_data/strategy directory
|
||||
or strategy repository https://github.com/freqtrade/freqtrade-strategies
|
||||
for samples and inspiration.
|
||||
"""
|
||||
INTERFACE_VERSION = 3
|
||||
|
||||
# Minimal ROI designed for the strategy
|
||||
minimal_roi = {
|
||||
"40": 0.0,
|
||||
"30": 0.01,
|
||||
"20": 0.02,
|
||||
"0": 0.04
|
||||
}
|
||||
|
||||
# Optimal stoploss designed for the strategy
|
||||
stoploss = -0.10
|
||||
|
||||
# Optimal timeframe for the strategy
|
||||
timeframe = '5m'
|
||||
|
||||
# Optional order type mapping
|
||||
order_types = {
|
||||
'entry': 'limit',
|
||||
'exit': 'limit',
|
||||
'stoploss': 'limit',
|
||||
'stoploss_on_exchange': False
|
||||
}
|
||||
|
||||
# Number of candles the strategy requires before producing valid signals
|
||||
startup_candle_count: int = 20
|
||||
|
||||
# Optional time in force for orders
|
||||
order_time_in_force = {
|
||||
'entry': 'gtc',
|
||||
'exit': 'gtc',
|
||||
}
|
||||
|
||||
buy_params = {
|
||||
'buy_rsi': 35,
|
||||
# Intentionally not specified, so "default" is tested
|
||||
# 'buy_plusdi': 0.4
|
||||
}
|
||||
|
||||
sell_params = {
|
||||
'sell_rsi': 74,
|
||||
'sell_minusdi': 0.4
|
||||
}
|
||||
|
||||
buy_rsi = IntParameter([0, 50], default=30, space='buy')
|
||||
buy_plusdi = RealParameter(low=0, high=1, default=0.5, space='buy')
|
||||
sell_rsi = IntParameter(low=50, high=100, default=70, space='sell')
|
||||
sell_minusdi = DecimalParameter(low=0, high=1, default=0.5001, decimals=3, space='sell',
|
||||
load=False)
|
||||
protection_enabled = BooleanParameter(default=True)
|
||||
protection_cooldown_lookback = IntParameter([0, 50], default=30)
|
||||
|
||||
# TODO: Can this work with protection tests? (replace HyperoptableStrategy implicitly ... )
|
||||
# @property
|
||||
# def protections(self):
|
||||
# prot = []
|
||||
# if self.protection_enabled.value:
|
||||
# prot.append({
|
||||
# "method": "CooldownPeriod",
|
||||
# "stop_duration_candles": self.protection_cooldown_lookback.value
|
||||
# })
|
||||
# return prot
|
||||
|
||||
bot_started = False
|
||||
|
||||
def bot_start(self):
|
||||
self.bot_started = True
|
||||
|
||||
def informative_pairs(self):
|
||||
|
||||
return []
|
||||
|
||||
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
|
||||
# Momentum Indicator
|
||||
# ------------------------------------
|
||||
|
||||
# ADX
|
||||
dataframe['adx'] = ta.ADX(dataframe)
|
||||
|
||||
# MACD
|
||||
macd = ta.MACD(dataframe)
|
||||
dataframe['macd'] = macd['macd']
|
||||
dataframe['macdsignal'] = macd['macdsignal']
|
||||
dataframe['macdhist'] = macd['macdhist']
|
||||
|
||||
# Minus Directional Indicator / Movement
|
||||
dataframe['minus_di'] = ta.MINUS_DI(dataframe)
|
||||
|
||||
# Plus Directional Indicator / Movement
|
||||
dataframe['plus_di'] = ta.PLUS_DI(dataframe)
|
||||
|
||||
# RSI
|
||||
dataframe['rsi'] = ta.RSI(dataframe)
|
||||
|
||||
# Stoch fast
|
||||
stoch_fast = ta.STOCHF(dataframe)
|
||||
dataframe['fastd'] = stoch_fast['fastd']
|
||||
dataframe['fastk'] = stoch_fast['fastk']
|
||||
|
||||
# Bollinger bands
|
||||
bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
|
||||
dataframe['bb_lowerband'] = bollinger['lower']
|
||||
dataframe['bb_middleband'] = bollinger['mid']
|
||||
dataframe['bb_upperband'] = bollinger['upper']
|
||||
|
||||
# EMA - Exponential Moving Average
|
||||
dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
|
||||
|
||||
return dataframe
|
||||
|
||||
def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
|
||||
dataframe.loc[
|
||||
(
|
||||
(dataframe['rsi'] < self.buy_rsi.value) &
|
||||
(dataframe['fastd'] < 35) &
|
||||
(dataframe['adx'] > 30) &
|
||||
(dataframe['plus_di'] > self.buy_plusdi.value)
|
||||
) |
|
||||
(
|
||||
(dataframe['adx'] > 65) &
|
||||
(dataframe['plus_di'] > self.buy_plusdi.value)
|
||||
),
|
||||
['enter_long', 'enter_tag']] = 1, 'enter_tag_long'
|
||||
|
||||
dataframe.loc[
|
||||
(
|
||||
qtpylib.crossed_below(dataframe['rsi'], self.sell_rsi.value)
|
||||
),
|
||||
['enter_short', 'enter_tag']] = 1, 'enter_tag_short'
|
||||
|
||||
return dataframe
|
||||
|
||||
def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
|
||||
dataframe.loc[
|
||||
(
|
||||
(
|
||||
(qtpylib.crossed_above(dataframe['rsi'], self.sell_rsi.value)) |
|
||||
(qtpylib.crossed_above(dataframe['fastd'], 70))
|
||||
) &
|
||||
(dataframe['adx'] > 10) &
|
||||
(dataframe['minus_di'] > 0)
|
||||
) |
|
||||
(
|
||||
(dataframe['adx'] > 70) &
|
||||
(dataframe['minus_di'] > self.sell_minusdi.value)
|
||||
),
|
||||
['exit_long', 'exit_tag']] = 1, 'exit_tag_long'
|
||||
|
||||
dataframe.loc[
|
||||
(
|
||||
qtpylib.crossed_above(dataframe['rsi'], self.buy_rsi.value)
|
||||
),
|
||||
['exit_long', 'exit_tag']] = 1, 'exit_tag_short'
|
||||
|
||||
return dataframe
|
||||
|
|
@ -916,7 +916,7 @@ def test_hyperopt_parameters():
|
|||
|
||||
|
||||
def test_auto_hyperopt_interface(default_conf):
|
||||
default_conf.update({'strategy': 'HyperoptableStrategy'})
|
||||
default_conf.update({'strategy': 'HyperoptableStrategyV2'})
|
||||
PairLocks.timeframe = default_conf['timeframe']
|
||||
strategy = StrategyResolver.load_strategy(default_conf)
|
||||
strategy.ft_bot_start()
|
||||
|
|
|
|||
|
|
@ -2060,8 +2060,9 @@ def test_update_trade_state_orderexception(mocker, default_conf_usdt, caplog) ->
|
|||
|
||||
@pytest.mark.parametrize("is_short", [False, True])
|
||||
def test_update_trade_state_sell(
|
||||
default_conf_usdt, trades_for_order, limit_order_open, limit_order, is_short, mocker,
|
||||
default_conf_usdt, trades_for_order, limit_order_open, limit_order, is_short, mocker
|
||||
):
|
||||
buy_order = limit_order[entry_side(is_short)]
|
||||
open_order = limit_order_open[exit_side(is_short)]
|
||||
l_order = limit_order[exit_side(is_short)]
|
||||
mocker.patch('freqtrade.exchange.Exchange.get_trades_for_order', return_value=trades_for_order)
|
||||
|
|
@ -2088,6 +2089,9 @@ def test_update_trade_state_sell(
|
|||
leverage=1,
|
||||
is_short=is_short,
|
||||
)
|
||||
order = Order.parse_from_ccxt_object(buy_order, 'LTC/ETH', entry_side(is_short))
|
||||
trade.orders.append(order)
|
||||
|
||||
order = Order.parse_from_ccxt_object(open_order, 'LTC/ETH', exit_side(is_short))
|
||||
trade.orders.append(order)
|
||||
assert order.status == 'open'
|
||||
|
|
@ -2135,8 +2139,6 @@ def test_handle_trade(
|
|||
assert trade
|
||||
|
||||
time.sleep(0.01) # Race condition fix
|
||||
oobj = Order.parse_from_ccxt_object(enter_order, enter_order['symbol'], entry_side(is_short))
|
||||
trade.update_trade(oobj)
|
||||
assert trade.is_open is True
|
||||
freqtrade.wallets.update()
|
||||
|
||||
|
|
@ -2146,11 +2148,15 @@ def test_handle_trade(
|
|||
assert trade.open_order_id == exit_order['id']
|
||||
|
||||
# Simulate fulfilled LIMIT_SELL order for trade
|
||||
oobj = Order.parse_from_ccxt_object(exit_order, exit_order['symbol'], exit_side(is_short))
|
||||
trade.update_trade(oobj)
|
||||
trade.orders[-1].ft_is_open = False
|
||||
trade.orders[-1].status = 'closed'
|
||||
trade.orders[-1].filled = trade.orders[-1].remaining
|
||||
trade.orders[-1].remaining = 0.0
|
||||
|
||||
assert trade.close_rate == 2.0 if is_short else 2.2
|
||||
assert trade.close_profit == close_profit
|
||||
trade.update_trade(trade.orders[-1])
|
||||
|
||||
assert trade.close_rate == (2.0 if is_short else 2.2)
|
||||
assert pytest.approx(trade.close_profit) == close_profit
|
||||
assert trade.calc_profit(trade.close_rate) == 5.685
|
||||
assert trade.close_date is not None
|
||||
assert trade.exit_reason == 'sell_signal1'
|
||||
|
|
@ -2753,6 +2759,8 @@ def test_check_handle_cancelled_exit(
|
|||
cancel_order_mock = MagicMock()
|
||||
limit_sell_order_old.update({"status": "canceled", 'filled': 0.0})
|
||||
limit_sell_order_old['side'] = 'buy' if is_short else 'sell'
|
||||
limit_sell_order_old['id'] = open_trade_usdt.open_order_id
|
||||
|
||||
patch_exchange(mocker)
|
||||
mocker.patch.multiple(
|
||||
'freqtrade.exchange.Exchange',
|
||||
|
|
@ -2787,6 +2795,7 @@ def test_manage_open_orders_partial(
|
|||
rpc_mock = patch_RPCManager(mocker)
|
||||
open_trade.is_short = is_short
|
||||
open_trade.leverage = leverage
|
||||
open_trade.orders[0].ft_order_side = 'sell' if is_short else 'buy'
|
||||
limit_buy_order_old_partial['id'] = open_trade.open_order_id
|
||||
limit_buy_order_old_partial['side'] = 'sell' if is_short else 'buy'
|
||||
limit_buy_canceled = deepcopy(limit_buy_order_old_partial)
|
||||
|
|
@ -2872,6 +2881,7 @@ def test_manage_open_orders_partial_except(
|
|||
limit_buy_order_old_partial_canceled, mocker
|
||||
) -> None:
|
||||
open_trade.is_short = is_short
|
||||
open_trade.orders[0].ft_order_side = 'sell' if is_short else 'buy'
|
||||
rpc_mock = patch_RPCManager(mocker)
|
||||
limit_buy_order_old_partial_canceled['id'] = open_trade.open_order_id
|
||||
limit_buy_order_old_partial['id'] = open_trade.open_order_id
|
||||
|
|
@ -3090,7 +3100,27 @@ def test_handle_cancel_exit_limit(mocker, default_conf_usdt, fee) -> None:
|
|||
close_date=arrow.utcnow().datetime,
|
||||
exit_reason="sell_reason_whatever",
|
||||
)
|
||||
order = {'remaining': 1,
|
||||
trade.orders = [
|
||||
Order(
|
||||
ft_order_side='buy',
|
||||
ft_pair=trade.pair,
|
||||
ft_is_open=True,
|
||||
order_id='123456',
|
||||
status="closed",
|
||||
symbol=trade.pair,
|
||||
order_type="market",
|
||||
side="buy",
|
||||
price=trade.open_rate,
|
||||
average=trade.open_rate,
|
||||
filled=trade.amount,
|
||||
remaining=0,
|
||||
cost=trade.open_rate * trade.amount,
|
||||
order_date=trade.open_date,
|
||||
order_filled_date=trade.open_date,
|
||||
),
|
||||
]
|
||||
order = {'id': "123456",
|
||||
'remaining': 1,
|
||||
'amount': 1,
|
||||
'status': "open"}
|
||||
reason = CANCEL_REASON['TIMEOUT']
|
||||
|
|
@ -3626,7 +3656,7 @@ def test_execute_trade_exit_market_order(
|
|||
'freqtrade.exchange.Exchange',
|
||||
fetch_ticker=ticker_usdt,
|
||||
get_fee=fee,
|
||||
_is_dry_limit_order_filled=MagicMock(return_value=False),
|
||||
_is_dry_limit_order_filled=MagicMock(return_value=True),
|
||||
)
|
||||
patch_whitelist(mocker, default_conf_usdt)
|
||||
freqtrade = FreqtradeBot(default_conf_usdt)
|
||||
|
|
@ -3642,7 +3672,8 @@ def test_execute_trade_exit_market_order(
|
|||
# Increase the price and sell it
|
||||
mocker.patch.multiple(
|
||||
'freqtrade.exchange.Exchange',
|
||||
fetch_ticker=ticker_usdt_sell_up
|
||||
fetch_ticker=ticker_usdt_sell_up,
|
||||
_is_dry_limit_order_filled=MagicMock(return_value=False),
|
||||
)
|
||||
freqtrade.config['order_types']['exit'] = 'market'
|
||||
|
||||
|
|
@ -3655,7 +3686,7 @@ def test_execute_trade_exit_market_order(
|
|||
assert not trade.is_open
|
||||
assert trade.close_profit == profit_ratio
|
||||
|
||||
assert rpc_mock.call_count == 3
|
||||
assert rpc_mock.call_count == 4
|
||||
last_msg = rpc_mock.call_args_list[-2][0][0]
|
||||
assert {
|
||||
'type': RPCMessageType.EXIT,
|
||||
|
|
|
|||
|
|
@ -481,6 +481,7 @@ def test_update_limit_order(fee, caplog, limit_buy_order_usdt, limit_sell_order_
|
|||
|
||||
trade.open_order_id = 'something'
|
||||
oobj = Order.parse_from_ccxt_object(enter_order, 'ADA/USDT', entry_side)
|
||||
trade.orders.append(oobj)
|
||||
trade.update_trade(oobj)
|
||||
assert trade.open_order_id is None
|
||||
assert trade.open_rate == open_rate
|
||||
|
|
@ -496,11 +497,12 @@ def test_update_limit_order(fee, caplog, limit_buy_order_usdt, limit_sell_order_
|
|||
trade.open_order_id = 'something'
|
||||
time_machine.move_to("2022-03-31 21:45:05 +00:00")
|
||||
oobj = Order.parse_from_ccxt_object(exit_order, 'ADA/USDT', exit_side)
|
||||
trade.orders.append(oobj)
|
||||
trade.update_trade(oobj)
|
||||
|
||||
assert trade.open_order_id is None
|
||||
assert trade.close_rate == close_rate
|
||||
assert trade.close_profit == profit
|
||||
assert pytest.approx(trade.close_profit) == profit
|
||||
assert trade.close_date is not None
|
||||
assert log_has_re(f"LIMIT_{exit_side.upper()} has been fulfilled for "
|
||||
r"Trade\(id=2, pair=ADA/USDT, amount=30.00000000, "
|
||||
|
|
@ -529,6 +531,7 @@ def test_update_market_order(market_buy_order_usdt, market_sell_order_usdt, fee,
|
|||
|
||||
trade.open_order_id = 'something'
|
||||
oobj = Order.parse_from_ccxt_object(market_buy_order_usdt, 'ADA/USDT', 'buy')
|
||||
trade.orders.append(oobj)
|
||||
trade.update_trade(oobj)
|
||||
assert trade.open_order_id is None
|
||||
assert trade.open_rate == 2.0
|
||||
|
|
@ -543,10 +546,11 @@ def test_update_market_order(market_buy_order_usdt, market_sell_order_usdt, fee,
|
|||
trade.is_open = True
|
||||
trade.open_order_id = 'something'
|
||||
oobj = Order.parse_from_ccxt_object(market_sell_order_usdt, 'ADA/USDT', 'sell')
|
||||
trade.orders.append(oobj)
|
||||
trade.update_trade(oobj)
|
||||
assert trade.open_order_id is None
|
||||
assert trade.close_rate == 2.2
|
||||
assert trade.close_profit == round(0.0945137157107232, 8)
|
||||
assert pytest.approx(trade.close_profit) == 0.094513715710723
|
||||
assert trade.close_date is not None
|
||||
assert log_has_re(r"MARKET_SELL has been fulfilled for Trade\(id=1, "
|
||||
r"pair=ADA/USDT, amount=30.00000000, is_short=False, leverage=1.0, "
|
||||
|
|
@ -624,14 +628,41 @@ def test_trade_close(limit_buy_order_usdt, limit_sell_order_usdt, fee):
|
|||
open_date=datetime.now(tz=timezone.utc) - timedelta(minutes=10),
|
||||
interest_rate=0.0005,
|
||||
exchange='binance',
|
||||
trading_mode=margin
|
||||
trading_mode=margin,
|
||||
leverage=1.0,
|
||||
)
|
||||
trade.orders.append(Order(
|
||||
ft_order_side=trade.entry_side,
|
||||
order_id=f'{trade.pair}-{trade.entry_side}-{trade.open_date}',
|
||||
ft_pair=trade.pair,
|
||||
amount=trade.amount,
|
||||
filled=trade.amount,
|
||||
remaining=0,
|
||||
price=trade.open_rate,
|
||||
average=trade.open_rate,
|
||||
status="closed",
|
||||
order_type="limit",
|
||||
side=trade.entry_side,
|
||||
))
|
||||
trade.orders.append(Order(
|
||||
ft_order_side=trade.exit_side,
|
||||
order_id=f'{trade.pair}-{trade.exit_side}-{trade.open_date}',
|
||||
ft_pair=trade.pair,
|
||||
amount=trade.amount,
|
||||
filled=trade.amount,
|
||||
remaining=0,
|
||||
price=2.2,
|
||||
average=2.2,
|
||||
status="closed",
|
||||
order_type="limit",
|
||||
side=trade.exit_side,
|
||||
))
|
||||
assert trade.close_profit is None
|
||||
assert trade.close_date is None
|
||||
assert trade.is_open is True
|
||||
trade.close(2.2)
|
||||
assert trade.is_open is False
|
||||
assert trade.close_profit == round(0.0945137157107232, 8)
|
||||
assert pytest.approx(trade.close_profit) == 0.094513715
|
||||
assert trade.close_date is not None
|
||||
|
||||
new_date = arrow.Arrow(2020, 2, 2, 15, 6, 1).datetime,
|
||||
|
|
@ -1200,7 +1231,7 @@ def test_migrate_new(mocker, default_conf, fee, caplog):
|
|||
0.00258580, {stake}, {amount},
|
||||
'2019-11-28 12:44:24.000000',
|
||||
0.0, 0.0, 0.0, '5m',
|
||||
'buy_order', 'stop_order_id222')
|
||||
'buy_order', 'dry_stop_order_id222')
|
||||
""".format(fee=fee.return_value,
|
||||
stake=default_conf.get("stake_amount"),
|
||||
amount=amount
|
||||
|
|
@ -1226,7 +1257,7 @@ def test_migrate_new(mocker, default_conf, fee, caplog):
|
|||
'buy',
|
||||
'ETC/BTC',
|
||||
0,
|
||||
'buy_order',
|
||||
'dry_buy_order',
|
||||
'closed',
|
||||
'ETC/BTC',
|
||||
'limit',
|
||||
|
|
@ -1238,12 +1269,44 @@ def test_migrate_new(mocker, default_conf, fee, caplog):
|
|||
{amount * 0.00258580}
|
||||
),
|
||||
(
|
||||
1,
|
||||
'buy',
|
||||
'ETC/BTC',
|
||||
1,
|
||||
'dry_buy_order22',
|
||||
'canceled',
|
||||
'ETC/BTC',
|
||||
'limit',
|
||||
'buy',
|
||||
0.00258580,
|
||||
{amount},
|
||||
{amount},
|
||||
0,
|
||||
{amount * 0.00258580}
|
||||
),
|
||||
(
|
||||
1,
|
||||
'stoploss',
|
||||
'ETC/BTC',
|
||||
1,
|
||||
'dry_stop_order_id11X',
|
||||
'canceled',
|
||||
'ETC/BTC',
|
||||
'limit',
|
||||
'sell',
|
||||
0.00258580,
|
||||
{amount},
|
||||
{amount},
|
||||
0,
|
||||
'stop_order_id222',
|
||||
'closed',
|
||||
{amount * 0.00258580}
|
||||
),
|
||||
(
|
||||
1,
|
||||
'stoploss',
|
||||
'ETC/BTC',
|
||||
1,
|
||||
'dry_stop_order_id222',
|
||||
'open',
|
||||
'ETC/BTC',
|
||||
'limit',
|
||||
'sell',
|
||||
|
|
@ -1292,7 +1355,7 @@ def test_migrate_new(mocker, default_conf, fee, caplog):
|
|||
assert trade.exit_reason is None
|
||||
assert trade.strategy is None
|
||||
assert trade.timeframe == '5m'
|
||||
assert trade.stoploss_order_id == 'stop_order_id222'
|
||||
assert trade.stoploss_order_id == 'dry_stop_order_id222'
|
||||
assert trade.stoploss_last_update is None
|
||||
assert log_has("trying trades_bak1", caplog)
|
||||
assert log_has("trying trades_bak2", caplog)
|
||||
|
|
@ -1302,12 +1365,21 @@ def test_migrate_new(mocker, default_conf, fee, caplog):
|
|||
assert trade.close_profit_abs is None
|
||||
|
||||
orders = trade.orders
|
||||
assert len(orders) == 2
|
||||
assert orders[0].order_id == 'buy_order'
|
||||
assert len(orders) == 4
|
||||
assert orders[0].order_id == 'dry_buy_order'
|
||||
assert orders[0].ft_order_side == 'buy'
|
||||
|
||||
assert orders[1].order_id == 'stop_order_id222'
|
||||
assert orders[1].ft_order_side == 'stoploss'
|
||||
assert orders[-1].order_id == 'dry_stop_order_id222'
|
||||
assert orders[-1].ft_order_side == 'stoploss'
|
||||
assert orders[-1].ft_is_open is True
|
||||
|
||||
assert orders[1].order_id == 'dry_buy_order22'
|
||||
assert orders[1].ft_order_side == 'buy'
|
||||
assert orders[1].ft_is_open is False
|
||||
|
||||
assert orders[2].order_id == 'dry_stop_order_id11X'
|
||||
assert orders[2].ft_order_side == 'stoploss'
|
||||
assert orders[2].ft_is_open is False
|
||||
|
||||
|
||||
def test_migrate_too_old(mocker, default_conf, fee, caplog):
|
||||
|
|
|
|||
|
|
@ -72,7 +72,7 @@ def test_add_indicators(default_conf, testdatadir, caplog):
|
|||
|
||||
strategy = StrategyResolver.load_strategy(default_conf)
|
||||
|
||||
# Generate buy/sell signals and indicators
|
||||
# Generate entry/exit signals and indicators
|
||||
data = strategy.analyze_ticker(data, {'pair': pair})
|
||||
fig = generate_empty_figure()
|
||||
|
||||
|
|
@ -113,7 +113,7 @@ def test_add_areas(default_conf, testdatadir, caplog):
|
|||
ind_plain = {"macd": {"fill_to": "macdhist"}}
|
||||
strategy = StrategyResolver.load_strategy(default_conf)
|
||||
|
||||
# Generate buy/sell signals and indicators
|
||||
# Generate entry/exit signals and indicators
|
||||
data = strategy.analyze_ticker(data, {'pair': pair})
|
||||
fig = generate_empty_figure()
|
||||
|
||||
|
|
@ -165,24 +165,24 @@ def test_plot_trades(testdatadir, caplog):
|
|||
fig = plot_trades(fig, trades)
|
||||
figure = fig1.layout.figure
|
||||
|
||||
# Check buys - color, should be in first graph, ...
|
||||
trade_buy = find_trace_in_fig_data(figure.data, 'Trade buy')
|
||||
assert isinstance(trade_buy, go.Scatter)
|
||||
assert trade_buy.yaxis == 'y'
|
||||
assert len(trades) == len(trade_buy.x)
|
||||
assert trade_buy.marker.color == 'cyan'
|
||||
assert trade_buy.marker.symbol == 'circle-open'
|
||||
assert trade_buy.text[0] == '3.99%, buy_tag, roi, 15 min'
|
||||
# Check entry - color, should be in first graph, ...
|
||||
trade_entries = find_trace_in_fig_data(figure.data, 'Trade entry')
|
||||
assert isinstance(trade_entries, go.Scatter)
|
||||
assert trade_entries.yaxis == 'y'
|
||||
assert len(trades) == len(trade_entries.x)
|
||||
assert trade_entries.marker.color == 'cyan'
|
||||
assert trade_entries.marker.symbol == 'circle-open'
|
||||
assert trade_entries.text[0] == '3.99%, buy_tag, roi, 15 min'
|
||||
|
||||
trade_sell = find_trace_in_fig_data(figure.data, 'Sell - Profit')
|
||||
assert isinstance(trade_sell, go.Scatter)
|
||||
assert trade_sell.yaxis == 'y'
|
||||
assert len(trades.loc[trades['profit_ratio'] > 0]) == len(trade_sell.x)
|
||||
assert trade_sell.marker.color == 'green'
|
||||
assert trade_sell.marker.symbol == 'square-open'
|
||||
assert trade_sell.text[0] == '3.99%, buy_tag, roi, 15 min'
|
||||
trade_exit = find_trace_in_fig_data(figure.data, 'Exit - Profit')
|
||||
assert isinstance(trade_exit, go.Scatter)
|
||||
assert trade_exit.yaxis == 'y'
|
||||
assert len(trades.loc[trades['profit_ratio'] > 0]) == len(trade_exit.x)
|
||||
assert trade_exit.marker.color == 'green'
|
||||
assert trade_exit.marker.symbol == 'square-open'
|
||||
assert trade_exit.text[0] == '3.99%, buy_tag, roi, 15 min'
|
||||
|
||||
trade_sell_loss = find_trace_in_fig_data(figure.data, 'Sell - Loss')
|
||||
trade_sell_loss = find_trace_in_fig_data(figure.data, 'Exit - Loss')
|
||||
assert isinstance(trade_sell_loss, go.Scatter)
|
||||
assert trade_sell_loss.yaxis == 'y'
|
||||
assert len(trades.loc[trades['profit_ratio'] <= 0]) == len(trade_sell_loss.x)
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user