Bump ta-lib from 0.4.25 to 0.4.26

Bumps [ta-lib](https://github.com/ta-lib/ta-lib-python) from 0.4.25 to 0.4.26.
- [Release notes](https://github.com/ta-lib/ta-lib-python/releases)
- [Changelog](https://github.com/TA-Lib/ta-lib-python/blob/master/CHANGELOG)
- [Commits](https://github.com/ta-lib/ta-lib-python/compare/TA_Lib-0.4.25...TA_Lib-0.4.26)

---
updated-dependencies:
- dependency-name: ta-lib
  dependency-type: direct:production
  update-type: version-update:semver-patch
...

Signed-off-by: dependabot[bot] <support@github.com>

docs/backtesting.md

@@ -274,19 +274,20 @@ A backtesting result will look like that:
 | XRP/BTC  |      35 |           0.66 |          22.96 |       0.00114897 |          11.48 | 3:49:00      |    12     0    23   34.3 |
 | ZEC/BTC  |      22 |          -0.46 |         -10.18 |      -0.00050971 |          -5.09 | 2:22:00      |     7     0    15   31.8 |
 | TOTAL    |     429 |           0.36 |         152.41 |       0.00762792 |          76.20 | 4:12:00      |   186     0   243   43.4 |
-========================================================= EXIT REASON STATS ==========================================================
-| Exit Reason        |   Exits |  Wins |  Draws |  Losses |
-|:-------------------|--------:|------:|-------:|--------:|
-| trailing_stop_loss |     205 |   150 |      0 |      55 |
-| stop_loss          |     166 |     0 |      0 |     166 |
-| exit_signal        |      56 |    36 |      0 |      20 |
-| force_exit         |       2 |     0 |      0 |       2 |
 ====================================================== LEFT OPEN TRADES REPORT ======================================================
 | Pair     |  Entries |   Avg Profit % |   Cum Profit % |   Tot Profit BTC |   Tot Profit % | Avg Duration   |  Win Draw Loss Win% |
 |:---------|---------:|---------------:|---------------:|-----------------:|---------------:|:---------------|--------------------:|
 | ADA/BTC  |        1 |           0.89 |           0.89 |       0.00004434 |           0.44 | 6:00:00        |    1    0    0  100 |
 | LTC/BTC  |        1 |           0.68 |           0.68 |       0.00003421 |           0.34 | 2:00:00        |    1    0    0  100 |
 | TOTAL    |        2 |           0.78 |           1.57 |       0.00007855 |           0.78 | 4:00:00        |    2    0    0  100 |
+==================== EXIT REASON STATS ====================
+| Exit Reason        |   Exits |  Wins |  Draws |  Losses |
+|:-------------------|--------:|------:|-------:|--------:|
+| trailing_stop_loss |     205 |   150 |      0 |      55 |
+| stop_loss          |     166 |     0 |      0 |     166 |
+| exit_signal        |      56 |    36 |      0 |      20 |
+| force_exit         |       2 |     0 |      0 |       2 |
+
 ================== SUMMARY METRICS ==================
 | Metric                      | Value               |
 |-----------------------------+---------------------|

docs/rest-api.md

@@ -9,9 +9,6 @@ This same command can also be used to update freqUI, should there be a new relea
 
 Once the bot is started in trade / dry-run mode (with `freqtrade trade`) - the UI will be available under the configured port below (usually `http://127.0.0.1:8080`).
 
-!!! info "Alpha release"
-    FreqUI is still considered an alpha release - if you encounter bugs or inconsistencies please open a [FreqUI issue](https://github.com/freqtrade/frequi/issues/new/choose).
-
 !!! Note "developers"
     Developers should not use this method, but instead use the method described in the [freqUI repository](https://github.com/freqtrade/frequi) to get the source-code of freqUI.
 

docs/telegram-usage.md

@@ -279,7 +279,6 @@ Return a summary of your profit/loss and performance.
 >   ∙ `33.095 EUR`
 >
 > **Total Trade Count:** `138`
-> **Bot started:** `2022-07-11 18:40:44`
 > **First Trade opened:** `3 days ago`
 > **Latest Trade opened:** `2 minutes ago`
 > **Avg. Duration:** `2:33:45`
@@ -293,7 +292,6 @@ The relative profit of `15.2 Σ%` is be based on the starting capital - so in th
 Starting capital is either taken from the `available_capital` setting, or calculated by using current wallet size - profits.
 Profit Factor is calculated as gross profits / gross losses - and should serve as an overall metric for the strategy.
 Max drawdown corresponds to the backtesting metric `Absolute Drawdown (Account)` - calculated as `(Absolute Drawdown) / (DrawdownHigh + startingBalance)`.
-Bot started date will refer to the date the bot was first started. For older bots, this will default to the first trade's open date.
 
 ### /forceexit <trade_id>
 

freqtrade/freqai/data_kitchen.py

@@ -1291,7 +1291,7 @@ class FreqaiDataKitchen:
 
         return dataframe
 
-    def use_strategy_to_populate_indicators(
+    def use_strategy_to_populate_indicators(  # noqa: C901
         self,
         strategy: IStrategy,
         corr_dataframes: dict = {},
@@ -1362,12 +1362,12 @@ class FreqaiDataKitchen:
                 dataframe = self.populate_features(dataframe.copy(), corr_pair, strategy,
                                                    corr_dataframes, base_dataframes, True)
 
-        dataframe = strategy.set_freqai_targets(dataframe.copy(), metadata=metadata)
+        if self.live:
+            dataframe = strategy.set_freqai_targets(dataframe.copy(), metadata=metadata)
+            dataframe = self.remove_special_chars_from_feature_names(dataframe)
 
         self.get_unique_classes_from_labels(dataframe)
 
-        dataframe = self.remove_special_chars_from_feature_names(dataframe)
-
         if self.config.get('reduce_df_footprint', False):
             dataframe = reduce_dataframe_footprint(dataframe)
 

freqtrade/freqai/freqai_interface.py

@@ -306,7 +306,7 @@ class IFreqaiModel(ABC):
                 if check_features:
                     self.dd.load_metadata(dk)
                     dataframe_dummy_features = self.dk.use_strategy_to_populate_indicators(
-                        strategy, prediction_dataframe=dataframe.tail(1), pair=metadata["pair"]
+                        strategy, prediction_dataframe=dataframe.tail(1), pair=pair
                     )
                     dk.find_features(dataframe_dummy_features)
                     self.check_if_feature_list_matches_strategy(dk)
@@ -316,7 +316,7 @@ class IFreqaiModel(ABC):
             else:
                 if populate_indicators:
                     dataframe = self.dk.use_strategy_to_populate_indicators(
-                        strategy, prediction_dataframe=dataframe, pair=metadata["pair"]
+                        strategy, prediction_dataframe=dataframe, pair=pair
                     )
                     populate_indicators = False
 
@@ -332,6 +332,10 @@ class IFreqaiModel(ABC):
                 dataframe_train = dk.slice_dataframe(tr_train, dataframe_base_train)
                 dataframe_backtest = dk.slice_dataframe(tr_backtest, dataframe_base_backtest)
 
+                dataframe_train = dk.remove_special_chars_from_feature_names(dataframe_train)
+                dataframe_backtest = dk.remove_special_chars_from_feature_names(dataframe_backtest)
+                dk.get_unique_classes_from_labels(dataframe_train)
+
                 if not self.model_exists(dk):
                     dk.find_features(dataframe_train)
                     dk.find_labels(dataframe_train)

freqtrade/freqtradebot.py

@@ -26,7 +26,6 @@ from freqtrade.exchange import (ROUND_DOWN, ROUND_UP, timeframe_to_minutes, time
 from freqtrade.misc import safe_value_fallback, safe_value_fallback2
 from freqtrade.mixins import LoggingMixin
 from freqtrade.persistence import Order, PairLocks, Trade, init_db
-from freqtrade.persistence.key_value_store import set_startup_time
 from freqtrade.plugins.pairlistmanager import PairListManager
 from freqtrade.plugins.protectionmanager import ProtectionManager
 from freqtrade.resolvers import ExchangeResolver, StrategyResolver
@@ -183,7 +182,6 @@ class FreqtradeBot(LoggingMixin):
         performs startup tasks
         """
         migrate_binance_futures_names(self.config)
-        set_startup_time()
 
         self.rpc.startup_messages(self.config, self.pairlists, self.protections)
         # Update older trades with precision and precision mode

freqtrade/optimize/optimize_reports.py

@@ -865,6 +865,11 @@ def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency:
         print(' BACKTESTING REPORT '.center(len(table.splitlines()[0]), '='))
     print(table)
 
+    table = text_table_bt_results(results['left_open_trades'], stake_currency=stake_currency)
+    if isinstance(table, str) and len(table) > 0:
+        print(' LEFT OPEN TRADES REPORT '.center(len(table.splitlines()[0]), '='))
+    print(table)
+
     if (results.get('results_per_enter_tag') is not None
             or results.get('results_per_buy_tag') is not None):
         # results_per_buy_tag is deprecated and should be removed 2 versions after short golive.
@@ -884,11 +889,6 @@ def show_backtest_result(strategy: str, results: Dict[str, Any], stake_currency:
         print(' EXIT REASON STATS '.center(len(table.splitlines()[0]), '='))
     print(table)
 
-    table = text_table_bt_results(results['left_open_trades'], stake_currency=stake_currency)
-    if isinstance(table, str) and len(table) > 0:
-        print(' LEFT OPEN TRADES REPORT '.center(len(table.splitlines()[0]), '='))
-    print(table)
-
     for period in backtest_breakdown:
         days_breakdown_stats = generate_periodic_breakdown_stats(
             trade_list=results['trades'], period=period)
@@ -917,11 +917,11 @@ def show_backtest_results(config: Config, backtest_stats: Dict):
             strategy, results, stake_currency,
             config.get('backtest_breakdown', []))
 
-    if len(backtest_stats['strategy']) > 1:
+    if len(backtest_stats['strategy']) > 0:
         # Print Strategy summary table
 
         table = text_table_strategy(backtest_stats['strategy_comparison'], stake_currency)
-        print(f"{results['backtest_start']} -> {results['backtest_end']} |"
+        print(f"Backtested {results['backtest_start']} -> {results['backtest_end']} |"
               f" Max open trades : {results['max_open_trades']}")
         print(' STRATEGY SUMMARY '.center(len(table.splitlines()[0]), '='))
         print(table)

freqtrade/persistence/__init__.py

@@ -1,6 +1,5 @@
 # flake8: noqa: F401
 
-from freqtrade.persistence.key_value_store import KeyStoreKeys, KeyValueStore
 from freqtrade.persistence.models import init_db
 from freqtrade.persistence.pairlock_middleware import PairLocks
 from freqtrade.persistence.trade_model import LocalTrade, Order, Trade

freqtrade/persistence/key_value_store.py

@@ -1,179 +0,0 @@
-from datetime import datetime, timezone
-from enum import Enum
-from typing import ClassVar, Optional, Union
-
-from sqlalchemy import String
-from sqlalchemy.orm import Mapped, mapped_column
-
-from freqtrade.persistence.base import ModelBase, SessionType
-
-
-ValueTypes = Union[str, datetime, float, int]
-
-
-class ValueTypesEnum(str, Enum):
-    STRING = 'str'
-    DATETIME = 'datetime'
-    FLOAT = 'float'
-    INT = 'int'
-
-
-class KeyStoreKeys(str, Enum):
-    BOT_START_TIME = 'bot_start_time'
-    STARTUP_TIME = 'startup_time'
-
-
-class _KeyValueStoreModel(ModelBase):
-    """
-    Pair Locks database model.
-    """
-    __tablename__ = 'KeyValueStore'
-    session: ClassVar[SessionType]
-
-    id: Mapped[int] = mapped_column(primary_key=True)
-
-    key: Mapped[KeyStoreKeys] = mapped_column(String(25), nullable=False, index=True)
-
-    value_type: Mapped[ValueTypesEnum] = mapped_column(String(20), nullable=False)
-
-    string_value: Mapped[Optional[str]]
-    datetime_value: Mapped[Optional[datetime]]
-    float_value: Mapped[Optional[float]]
-    int_value: Mapped[Optional[int]]
-
-
-class KeyValueStore():
-    """
-    Generic bot-wide, persistent key-value store
-    Can be used to store generic values, e.g. very first bot startup time.
-    Supports the types str, datetime, float and int.
-    """
-
-    @staticmethod
-    def store_value(key: KeyStoreKeys, value: ValueTypes) -> None:
-        """
-        Store the given value for the given key.
-        :param key: Key to store the value for - can be used in get-value to retrieve the key
-        :param value: Value to store - can be str, datetime, float or int
-        """
-        kv = _KeyValueStoreModel.session.query(_KeyValueStoreModel).filter(
-            _KeyValueStoreModel.key == key).first()
-        if kv is None:
-            kv = _KeyValueStoreModel(key=key)
-        if isinstance(value, str):
-            kv.value_type = ValueTypesEnum.STRING
-            kv.string_value = value
-        elif isinstance(value, datetime):
-            kv.value_type = ValueTypesEnum.DATETIME
-            kv.datetime_value = value
-        elif isinstance(value, float):
-            kv.value_type = ValueTypesEnum.FLOAT
-            kv.float_value = value
-        elif isinstance(value, int):
-            kv.value_type = ValueTypesEnum.INT
-            kv.int_value = value
-        else:
-            raise ValueError(f'Unknown value type {kv.value_type}')
-        _KeyValueStoreModel.session.add(kv)
-        _KeyValueStoreModel.session.commit()
-
-    @staticmethod
-    def delete_value(key: KeyStoreKeys) -> None:
-        """
-        Delete the value for the given key.
-        :param key: Key to delete the value for
-        """
-        kv = _KeyValueStoreModel.session.query(_KeyValueStoreModel).filter(
-            _KeyValueStoreModel.key == key).first()
-        if kv is not None:
-            _KeyValueStoreModel.session.delete(kv)
-            _KeyValueStoreModel.session.commit()
-
-    @staticmethod
-    def get_value(key: KeyStoreKeys) -> Optional[ValueTypes]:
-        """
-        Get the value for the given key.
-        :param key: Key to get the value for
-        """
-        kv = _KeyValueStoreModel.session.query(_KeyValueStoreModel).filter(
-            _KeyValueStoreModel.key == key).first()
-        if kv is None:
-            return None
-        if kv.value_type == ValueTypesEnum.STRING:
-            return kv.string_value
-        if kv.value_type == ValueTypesEnum.DATETIME and kv.datetime_value is not None:
-            return kv.datetime_value.replace(tzinfo=timezone.utc)
-        if kv.value_type == ValueTypesEnum.FLOAT:
-            return kv.float_value
-        if kv.value_type == ValueTypesEnum.INT:
-            return kv.int_value
-        # This should never happen unless someone messed with the database manually
-        raise ValueError(f'Unknown value type {kv.value_type}')  # pragma: no cover
-
-    @staticmethod
-    def get_string_value(key: KeyStoreKeys) -> Optional[str]:
-        """
-        Get the value for the given key.
-        :param key: Key to get the value for
-        """
-        kv = _KeyValueStoreModel.session.query(_KeyValueStoreModel).filter(
-            _KeyValueStoreModel.key == key,
-            _KeyValueStoreModel.value_type == ValueTypesEnum.STRING).first()
-        if kv is None:
-            return None
-        return kv.string_value
-
-    @staticmethod
-    def get_datetime_value(key: KeyStoreKeys) -> Optional[datetime]:
-        """
-        Get the value for the given key.
-        :param key: Key to get the value for
-        """
-        kv = _KeyValueStoreModel.session.query(_KeyValueStoreModel).filter(
-            _KeyValueStoreModel.key == key,
-            _KeyValueStoreModel.value_type == ValueTypesEnum.DATETIME).first()
-        if kv is None or kv.datetime_value is None:
-            return None
-        return kv.datetime_value.replace(tzinfo=timezone.utc)
-
-    @staticmethod
-    def get_float_value(key: KeyStoreKeys) -> Optional[float]:
-        """
-        Get the value for the given key.
-        :param key: Key to get the value for
-        """
-        kv = _KeyValueStoreModel.session.query(_KeyValueStoreModel).filter(
-            _KeyValueStoreModel.key == key,
-            _KeyValueStoreModel.value_type == ValueTypesEnum.FLOAT).first()
-        if kv is None:
-            return None
-        return kv.float_value
-
-    @staticmethod
-    def get_int_value(key: KeyStoreKeys) -> Optional[int]:
-        """
-        Get the value for the given key.
-        :param key: Key to get the value for
-        """
-        kv = _KeyValueStoreModel.session.query(_KeyValueStoreModel).filter(
-            _KeyValueStoreModel.key == key,
-            _KeyValueStoreModel.value_type == ValueTypesEnum.INT).first()
-        if kv is None:
-            return None
-        return kv.int_value
-
-
-def set_startup_time():
-    """
-    sets bot_start_time to the first trade open date - or "now" on new databases.
-    sets startup_time to "now"
-    """
-    st = KeyValueStore.get_value('bot_start_time')
-    if st is None:
-        from freqtrade.persistence import Trade
-        t = Trade.session.query(Trade).order_by(Trade.open_date.asc()).first()
-        if t is not None:
-            KeyValueStore.store_value('bot_start_time', t.open_date_utc)
-        else:
-            KeyValueStore.store_value('bot_start_time', datetime.now(timezone.utc))
-    KeyValueStore.store_value('startup_time', datetime.now(timezone.utc))

freqtrade/persistence/models.py

@@ -13,7 +13,6 @@ from sqlalchemy.pool import StaticPool
 
 from freqtrade.exceptions import OperationalException
 from freqtrade.persistence.base import ModelBase
-from freqtrade.persistence.key_value_store import _KeyValueStoreModel
 from freqtrade.persistence.migrations import check_migrate
 from freqtrade.persistence.pairlock import PairLock
 from freqtrade.persistence.trade_model import Order, Trade
@@ -77,7 +76,6 @@ def init_db(db_url: str) -> None:
         bind=engine, autoflush=False), scopefunc=get_request_or_thread_id)
     Order.session = Trade.session
     PairLock.session = Trade.session
-    _KeyValueStoreModel.session = Trade.session
 
     previous_tables = inspect(engine).get_table_names()
     ModelBase.metadata.create_all(engine)

freqtrade/rpc/api_server/api_schemas.py

@@ -108,8 +108,6 @@ class Profit(BaseModel):
     max_drawdown: float
     max_drawdown_abs: float
     trading_volume: Optional[float]
-    bot_start_timestamp: int
-    bot_start_date: str
 
 
 class SellReason(BaseModel):

freqtrade/rpc/rpc.py

@@ -26,7 +26,7 @@ from freqtrade.exceptions import ExchangeError, PricingError
 from freqtrade.exchange import timeframe_to_minutes, timeframe_to_msecs
 from freqtrade.loggers import bufferHandler
 from freqtrade.misc import decimals_per_coin, shorten_date
-from freqtrade.persistence import KeyStoreKeys, KeyValueStore, Order, PairLocks, Trade
+from freqtrade.persistence import Order, PairLocks, Trade
 from freqtrade.persistence.models import PairLock
 from freqtrade.plugins.pairlist.pairlist_helpers import expand_pairlist
 from freqtrade.rpc.fiat_convert import CryptoToFiatConverter
@@ -543,7 +543,6 @@ class RPC:
         first_date = trades[0].open_date if trades else None
         last_date = trades[-1].open_date if trades else None
         num = float(len(durations) or 1)
-        bot_start = KeyValueStore.get_datetime_value(KeyStoreKeys.BOT_START_TIME)
         return {
             'profit_closed_coin': profit_closed_coin_sum,
             'profit_closed_percent_mean': round(profit_closed_ratio_mean * 100, 2),
@@ -577,8 +576,6 @@ class RPC:
             'max_drawdown': max_drawdown,
             'max_drawdown_abs': max_drawdown_abs,
             'trading_volume': trading_volume,
-            'bot_start_timestamp': int(bot_start.timestamp() * 1000) if bot_start else 0,
-            'bot_start_date': bot_start.strftime(DATETIME_PRINT_FORMAT) if bot_start else '',
         }
 
     def _rpc_balance(self, stake_currency: str, fiat_display_currency: str) -> Dict:

freqtrade/rpc/telegram.py

@@ -819,7 +819,7 @@ class Telegram(RPCHandler):
         best_pair = stats['best_pair']
         best_pair_profit_ratio = stats['best_pair_profit_ratio']
         if stats['trade_count'] == 0:
-            markdown_msg = f"No trades yet.\n*Bot started:* `{stats['bot_start_date']}`"
+            markdown_msg = 'No trades yet.'
         else:
             # Message to display
             if stats['closed_trade_count'] > 0:
@@ -838,7 +838,6 @@ class Telegram(RPCHandler):
                 f"({profit_all_percent} \N{GREEK CAPITAL LETTER SIGMA}%)`\n"
                 f"∙ `{round_coin_value(profit_all_fiat, fiat_disp_cur)}`\n"
                 f"*Total Trade Count:* `{trade_count}`\n"
-                f"*Bot started:* `{stats['bot_start_date']}`\n"
                 f"*{'First Trade opened' if not timescale else 'Showing Profit since'}:* "
                 f"`{first_trade_date}`\n"
                 f"*Latest Trade opened:* `{latest_trade_date}`\n"

requirements.txt

@@ -12,7 +12,7 @@ cachetools==4.2.2
 requests==2.28.2
 urllib3==1.26.15
 jsonschema==4.17.3
-TA-Lib==0.4.25
+TA-Lib==0.4.26
 technical==1.4.0
 tabulate==0.9.0
 pycoingecko==3.1.0

tests/freqai/conftest.py

@@ -119,6 +119,7 @@ def make_unfiltered_dataframe(mocker, freqai_conf):
     freqai = strategy.freqai
     freqai.live = True
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     freqai.dk.pair = "ADA/BTC"
     data_load_timerange = TimeRange.parse_timerange("20180110-20180130")
     freqai.dd.load_all_pair_histories(data_load_timerange, freqai.dk)
@@ -152,6 +153,7 @@ def make_data_dictionary(mocker, freqai_conf):
     freqai = strategy.freqai
     freqai.live = True
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     freqai.dk.pair = "ADA/BTC"
     data_load_timerange = TimeRange.parse_timerange("20180110-20180130")
     freqai.dd.load_all_pair_histories(data_load_timerange, freqai.dk)

tests/freqai/test_freqai_datadrawer.py

@@ -19,6 +19,7 @@ def test_update_historic_data(mocker, freqai_conf):
     freqai = strategy.freqai
     freqai.live = True
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     timerange = TimeRange.parse_timerange("20180110-20180114")
 
     freqai.dd.load_all_pair_histories(timerange, freqai.dk)
@@ -41,6 +42,7 @@ def test_load_all_pairs_histories(mocker, freqai_conf):
     freqai = strategy.freqai
     freqai.live = True
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     timerange = TimeRange.parse_timerange("20180110-20180114")
     freqai.dd.load_all_pair_histories(timerange, freqai.dk)
 
@@ -60,6 +62,7 @@ def test_get_base_and_corr_dataframes(mocker, freqai_conf):
     freqai = strategy.freqai
     freqai.live = True
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     timerange = TimeRange.parse_timerange("20180110-20180114")
     freqai.dd.load_all_pair_histories(timerange, freqai.dk)
     sub_timerange = TimeRange.parse_timerange("20180111-20180114")
@@ -87,6 +90,7 @@ def test_use_strategy_to_populate_indicators(mocker, freqai_conf):
     freqai = strategy.freqai
     freqai.live = True
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     timerange = TimeRange.parse_timerange("20180110-20180114")
     freqai.dd.load_all_pair_histories(timerange, freqai.dk)
     sub_timerange = TimeRange.parse_timerange("20180111-20180114")
@@ -103,8 +107,9 @@ def test_get_timerange_from_live_historic_predictions(mocker, freqai_conf):
     exchange = get_patched_exchange(mocker, freqai_conf)
     strategy.dp = DataProvider(freqai_conf, exchange)
     freqai = strategy.freqai
-    freqai.live = True
+    freqai.live = False
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = False
     timerange = TimeRange.parse_timerange("20180126-20180130")
     freqai.dd.load_all_pair_histories(timerange, freqai.dk)
     sub_timerange = TimeRange.parse_timerange("20180128-20180130")

tests/freqai/test_freqai_datakitchen.py

@@ -180,6 +180,7 @@ def test_get_full_model_path(mocker, freqai_conf, model):
     freqai = strategy.freqai
     freqai.live = True
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     timerange = TimeRange.parse_timerange("20180110-20180130")
     freqai.dd.load_all_pair_histories(timerange, freqai.dk)
 

tests/freqai/test_freqai_interface.py

@@ -87,6 +87,7 @@ def test_extract_data_and_train_model_Standard(mocker, freqai_conf, model, pca,
     freqai.live = True
     freqai.can_short = can_short
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     freqai.dk.set_paths('ADA/BTC', 10000)
     timerange = TimeRange.parse_timerange("20180110-20180130")
     freqai.dd.load_all_pair_histories(timerange, freqai.dk)
@@ -135,6 +136,7 @@ def test_extract_data_and_train_model_MultiTargets(mocker, freqai_conf, model, s
     freqai = strategy.freqai
     freqai.live = True
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     timerange = TimeRange.parse_timerange("20180110-20180130")
     freqai.dd.load_all_pair_histories(timerange, freqai.dk)
 
@@ -178,6 +180,7 @@ def test_extract_data_and_train_model_Classifiers(mocker, freqai_conf, model):
     freqai = strategy.freqai
     freqai.live = True
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     timerange = TimeRange.parse_timerange("20180110-20180130")
     freqai.dd.load_all_pair_histories(timerange, freqai.dk)
 
@@ -371,6 +374,9 @@ def test_backtesting_fit_live_predictions(mocker, freqai_conf, caplog):
     sub_timerange = TimeRange.parse_timerange("20180129-20180130")
     corr_df, base_df = freqai.dd.get_base_and_corr_dataframes(sub_timerange, "LTC/BTC", freqai.dk)
     df = freqai.dk.use_strategy_to_populate_indicators(strategy, corr_df, base_df, "LTC/BTC")
+    df = strategy.set_freqai_targets(df.copy(), metadata={"pair": "LTC/BTC"})
+    df = freqai.dk.remove_special_chars_from_feature_names(df)
+    freqai.dk.get_unique_classes_from_labels(df)
     freqai.dk.pair = "ADA/BTC"
     freqai.dk.full_df = df.fillna(0)
     freqai.dk.full_df
@@ -394,6 +400,7 @@ def test_principal_component_analysis(mocker, freqai_conf):
     freqai = strategy.freqai
     freqai.live = True
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     timerange = TimeRange.parse_timerange("20180110-20180130")
     freqai.dd.load_all_pair_histories(timerange, freqai.dk)
 
@@ -425,10 +432,12 @@ def test_plot_feature_importance(mocker, freqai_conf):
     freqai = strategy.freqai
     freqai.live = True
     freqai.dk = FreqaiDataKitchen(freqai_conf)
+    freqai.dk.live = True
     timerange = TimeRange.parse_timerange("20180110-20180130")
     freqai.dd.load_all_pair_histories(timerange, freqai.dk)
 
-    freqai.dd.pair_dict = MagicMock()
+    freqai.dd.pair_dict = {"ADA/BTC": {"model_filename": "fake_name",
+                                       "trained_timestamp": 1, "data_path": "", "extras": {}}}
 
     data_load_timerange = TimeRange.parse_timerange("20180110-20180130")
     new_timerange = TimeRange.parse_timerange("20180120-20180130")

tests/persistence/test_key_value_store.py

@@ -1,69 +0,0 @@
-from datetime import datetime, timedelta, timezone
-
-import pytest
-
-from freqtrade.persistence.key_value_store import KeyValueStore, set_startup_time
-from tests.conftest import create_mock_trades_usdt
-
-
-@pytest.mark.usefixtures("init_persistence")
-def test_key_value_store(time_machine):
-    start = datetime(2023, 1, 1, 4, tzinfo=timezone.utc)
-    time_machine.move_to(start, tick=False)
-
-    KeyValueStore.store_value("test", "testStringValue")
-    KeyValueStore.store_value("test_dt", datetime.now(timezone.utc))
-    KeyValueStore.store_value("test_float", 22.51)
-    KeyValueStore.store_value("test_int", 15)
-
-    assert KeyValueStore.get_value("test") == "testStringValue"
-    assert KeyValueStore.get_value("test") == "testStringValue"
-    assert KeyValueStore.get_string_value("test") == "testStringValue"
-    assert KeyValueStore.get_value("test_dt") == datetime.now(timezone.utc)
-    assert KeyValueStore.get_datetime_value("test_dt") == datetime.now(timezone.utc)
-    assert KeyValueStore.get_string_value("test_dt") is None
-    assert KeyValueStore.get_float_value("test_dt") is None
-    assert KeyValueStore.get_int_value("test_dt") is None
-    assert KeyValueStore.get_value("test_float") == 22.51
-    assert KeyValueStore.get_float_value("test_float") == 22.51
-    assert KeyValueStore.get_value("test_int") == 15
-    assert KeyValueStore.get_int_value("test_int") == 15
-    assert KeyValueStore.get_datetime_value("test_int") is None
-
-    time_machine.move_to(start + timedelta(days=20, hours=5), tick=False)
-    assert KeyValueStore.get_value("test_dt") != datetime.now(timezone.utc)
-    assert KeyValueStore.get_value("test_dt") == start
-    # Test update works
-    KeyValueStore.store_value("test_dt", datetime.now(timezone.utc))
-    assert KeyValueStore.get_value("test_dt") == datetime.now(timezone.utc)
-
-    KeyValueStore.store_value("test_float", 23.51)
-    assert KeyValueStore.get_value("test_float") == 23.51
-    # test deleting
-    KeyValueStore.delete_value("test_float")
-    assert KeyValueStore.get_value("test_float") is None
-    # Delete same value again (should not fail)
-    KeyValueStore.delete_value("test_float")
-
-    with pytest.raises(ValueError, match=r"Unknown value type"):
-        KeyValueStore.store_value("test_float", {'some': 'dict'})
-
-
-@pytest.mark.usefixtures("init_persistence")
-def test_set_startup_time(fee, time_machine):
-    create_mock_trades_usdt(fee)
-    start = datetime.now(timezone.utc)
-    time_machine.move_to(start, tick=False)
-    set_startup_time()
-
-    assert KeyValueStore.get_value("startup_time") == start
-    initial_time = KeyValueStore.get_value("bot_start_time")
-    assert initial_time <= start
-
-    # Simulate bot restart
-    new_start = start + timedelta(days=5)
-    time_machine.move_to(new_start, tick=False)
-    set_startup_time()
-
-    assert KeyValueStore.get_value("startup_time") == new_start
-    assert KeyValueStore.get_value("bot_start_time") == initial_time

tests/rpc/test_rpc_apiserver.py

@@ -883,8 +883,6 @@ def test_api_profit(botclient, mocker, ticker, fee, markets, is_short, expected)
         'max_drawdown': ANY,
         'max_drawdown_abs': ANY,
         'trading_volume': expected['trading_volume'],
-        'bot_start_timestamp': 0,
-        'bot_start_date': '',
     }