Bump pandas from 1.5.3 to 2.0.0

Bumps [pandas](https://github.com/pandas-dev/pandas) from 1.5.3 to 2.0.0.
- [Release notes](https://github.com/pandas-dev/pandas/releases)
- [Commits](https://github.com/pandas-dev/pandas/compare/v1.5.3...v2.0.0)

---
updated-dependencies:
- dependency-name: pandas
  dependency-type: direct:production
  update-type: version-update:semver-major
...

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

.github/workflows/ci.yml

@@ -425,7 +425,7 @@ jobs:
         python setup.py sdist bdist_wheel
 
     - name: Publish to PyPI (Test)
-      uses: pypa/gh-action-pypi-publish@v1.8.4
+      uses: pypa/gh-action-pypi-publish@v1.8.5
       if: (github.event_name == 'release')
       with:
         user: __token__
@@ -433,7 +433,7 @@ jobs:
         repository_url: https://test.pypi.org/legacy/
 
     - name: Publish to PyPI
-      uses: pypa/gh-action-pypi-publish@v1.8.4
+      uses: pypa/gh-action-pypi-publish@v1.8.5
       if: (github.event_name == 'release')
       with:
         user: __token__

.pre-commit-config.yaml

@@ -17,8 +17,8 @@ repos:
           - types-filelock==3.2.7
           - types-requests==2.28.11.17
           - types-tabulate==0.9.0.2
-          - types-python-dateutil==2.8.19.11
-          - SQLAlchemy==2.0.8
+          - types-python-dateutil==2.8.19.12
+          - SQLAlchemy==2.0.9
         # stages: [push]
 
   - repo: https://github.com/pycqa/isort

docs/requirements-docs.txt

@@ -1,6 +1,6 @@
 markdown==3.3.7
 mkdocs==1.4.2
-mkdocs-material==9.1.5
+mkdocs-material==9.1.6
 mdx_truly_sane_lists==1.3
-pymdown-extensions==9.10
+pymdown-extensions==9.11
 jinja2==3.1.2

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

@@ -279,6 +279,7 @@ 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`
@@ -292,6 +293,7 @@ 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/data/btanalysis.py

@@ -246,14 +246,8 @@ def _load_backtest_data_df_compatibility(df: pd.DataFrame) -> pd.DataFrame:
     """
     Compatibility support for older backtest data.
     """
-    df['open_date'] = pd.to_datetime(df['open_date'],
-                                     utc=True,
-                                     infer_datetime_format=True
-                                     )
-    df['close_date'] = pd.to_datetime(df['close_date'],
-                                      utc=True,
-                                      infer_datetime_format=True
-                                      )
+    df['open_date'] = pd.to_datetime(df['open_date'], utc=True)
+    df['close_date'] = pd.to_datetime(df['close_date'], utc=True)
     # Compatibility support for pre short Columns
     if 'is_short' not in df.columns:
         df['is_short'] = False

freqtrade/data/converter.py

@@ -34,7 +34,7 @@ def ohlcv_to_dataframe(ohlcv: list, timeframe: str, pair: str, *,
     cols = DEFAULT_DATAFRAME_COLUMNS
     df = DataFrame(ohlcv, columns=cols)
 
-    df['date'] = to_datetime(df['date'], unit='ms', utc=True, infer_datetime_format=True)
+    df['date'] = to_datetime(df['date'], unit='ms', utc=True)
 
     # Some exchanges return int values for Volume and even for OHLC.
     # Convert them since TA-LIB indicators used in the strategy assume floats

freqtrade/data/history/featherdatahandler.py

@@ -63,10 +63,7 @@ class FeatherDataHandler(IDataHandler):
         pairdata.columns = self._columns
         pairdata = pairdata.astype(dtype={'open': 'float', 'high': 'float',
                                           'low': 'float', 'close': 'float', 'volume': 'float'})
-        pairdata['date'] = to_datetime(pairdata['date'],
-                                       unit='ms',
-                                       utc=True,
-                                       infer_datetime_format=True)
+        pairdata['date'] = to_datetime(pairdata['date'], unit='ms', utc=True)
         return pairdata
 
     def ohlcv_append(

freqtrade/data/history/jsondatahandler.py

@@ -75,10 +75,7 @@ class JsonDataHandler(IDataHandler):
             return DataFrame(columns=self._columns)
         pairdata = pairdata.astype(dtype={'open': 'float', 'high': 'float',
                                           'low': 'float', 'close': 'float', 'volume': 'float'})
-        pairdata['date'] = to_datetime(pairdata['date'],
-                                       unit='ms',
-                                       utc=True,
-                                       infer_datetime_format=True)
+        pairdata['date'] = to_datetime(pairdata['date'], unit='ms', utc=True)
         return pairdata
 
     def ohlcv_append(

freqtrade/data/history/parquetdatahandler.py

@@ -62,10 +62,7 @@ class ParquetDataHandler(IDataHandler):
         pairdata.columns = self._columns
         pairdata = pairdata.astype(dtype={'open': 'float', 'high': 'float',
                                           'low': 'float', 'close': 'float', 'volume': 'float'})
-        pairdata['date'] = to_datetime(pairdata['date'],
-                                       unit='ms',
-                                       utc=True,
-                                       infer_datetime_format=True)
+        pairdata['date'] = to_datetime(pairdata['date'], unit='ms', utc=True)
         return pairdata
 
     def ohlcv_append(

freqtrade/freqtradebot.py

@@ -26,6 +26,7 @@ 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
@@ -182,6 +183,7 @@ 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/persistence/__init__.py

@@ -1,5 +1,6 @@
 # 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

@@ -0,0 +1,179 @@
+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

@@ -13,6 +13,7 @@ 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
@@ -76,6 +77,7 @@ 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

@@ -108,6 +108,8 @@ 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 Order, PairLocks, Trade
+from freqtrade.persistence import KeyStoreKeys, KeyValueStore, 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
@@ -543,6 +543,7 @@ 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),
@@ -576,6 +577,8 @@ 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:
@@ -1193,6 +1196,7 @@ class RPC:
         from freqtrade.resolvers.strategy_resolver import StrategyResolver
         strategy = StrategyResolver.load_strategy(config)
         strategy.dp = DataProvider(config, exchange=exchange, pairlists=None)
+        strategy.ft_bot_start()
 
         df_analyzed = strategy.analyze_ticker(_data[pair], {'pair': pair})
 

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 = 'No trades yet.'
+            markdown_msg = f"No trades yet.\n*Bot started:* `{stats['bot_start_date']}`"
         else:
             # Message to display
             if stats['closed_trade_count'] > 0:
@@ -838,6 +838,7 @@ 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-dev.txt

@@ -7,10 +7,10 @@
 -r docs/requirements-docs.txt
 
 coveralls==3.3.1
-ruff==0.0.260
-mypy==1.1.1
-pre-commit==3.2.1
-pytest==7.2.2
+ruff==0.0.261
+mypy==1.2.0
+pre-commit==3.2.2
+pytest==7.3.0
 pytest-asyncio==0.21.0
 pytest-cov==4.0.0
 pytest-mock==3.10.0
@@ -29,4 +29,4 @@ types-cachetools==5.3.0.5
 types-filelock==3.2.7
 types-requests==2.28.11.17
 types-tabulate==0.9.0.2
-types-python-dateutil==2.8.19.11
+types-python-dateutil==2.8.19.12

requirements-hyperopt.txt

@@ -5,5 +5,5 @@
 scipy==1.10.1
 scikit-learn==1.1.3
 scikit-optimize==0.9.0
-filelock==3.10.6
+filelock==3.11.0
 progressbar2==4.2.0

requirements-plot.txt

@@ -1,4 +1,4 @@
 # Include all requirements to run the bot.
 -r requirements.txt
 
-plotly==5.14.0
+plotly==5.14.1

requirements.txt

@@ -1,11 +1,11 @@
 numpy==1.24.2
-pandas==1.5.3
+pandas==2.0.0
 pandas-ta==0.3.14b
 
-ccxt==3.0.50
+ccxt==3.0.59
 cryptography==40.0.1
 aiohttp==3.8.4
-SQLAlchemy==2.0.8
+SQLAlchemy==2.0.9
 python-telegram-bot==13.15
 arrow==1.2.3
 cachetools==4.2.2
@@ -28,7 +28,7 @@ py_find_1st==1.1.5
 # Load ticker files 30% faster
 python-rapidjson==1.10
 # Properly format api responses
-orjson==3.8.9
+orjson==3.8.10
 
 # Notify systemd
 sdnotify==0.3.2
@@ -50,10 +50,10 @@ prompt-toolkit==3.0.38
 python-dateutil==2.8.2
 
 #Futures
-schedule==1.1.0
+schedule==1.2.0
 
 #WS Messages
-websockets==11.0
+websockets==11.0.1
 janus==1.0.0
 
 ast-comments==1.0.1

tests/persistence/test_key_value_store.py

@@ -0,0 +1,69 @@
+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

@@ -883,6 +883,8 @@ 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': '',
     }
 
 
@@ -1403,10 +1405,10 @@ def test_api_pair_candles(botclient, ohlcv_history):
              ])
 
 
-def test_api_pair_history(botclient, ohlcv_history):
+def test_api_pair_history(botclient, mocker):
     ftbot, client = botclient
     timeframe = '5m'
-
+    lfm = mocker.patch('freqtrade.strategy.interface.IStrategy.load_freqAI_model')
     # No pair
     rc = client_get(client,
                     f"{BASE_URI}/pair_history?timeframe={timeframe}"
@@ -1440,6 +1442,7 @@ def test_api_pair_history(botclient, ohlcv_history):
     assert len(rc.json()['data']) == rc.json()['length']
     assert 'columns' in rc.json()
     assert 'data' in rc.json()
+    assert lfm.call_count == 1
     assert rc.json()['pair'] == 'UNITTEST/BTC'
     assert rc.json()['strategy'] == CURRENT_TEST_STRATEGY
     assert rc.json()['data_start'] == '2018-01-11 00:00:00+00:00'