Bump python-telegram-bot from 13.15 to 20.2

Bumps [python-telegram-bot](https://github.com/python-telegram-bot/python-telegram-bot) from 13.15 to 20.2.
- [Release notes](https://github.com/python-telegram-bot/python-telegram-bot/releases)
- [Changelog](https://github.com/python-telegram-bot/python-telegram-bot/blob/master/CHANGES.rst)
- [Commits](https://github.com/python-telegram-bot/python-telegram-bot/compare/v13.15...v20.2)

---
updated-dependencies:
- dependency-name: python-telegram-bot
  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/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/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.
 

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/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/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/rpc/rpc.py

@@ -1196,6 +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})
 

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
@@ -22,11 +22,11 @@ time-machine==2.9.0
 httpx==0.23.3
 
 # Convert jupyter notebooks to markdown documents
-nbconvert==7.2.10
+nbconvert==7.3.1
 
 # mypy types
 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

@@ -2,11 +2,11 @@ numpy==1.24.2
 pandas==1.5.3
 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
-python-telegram-bot==13.15
+SQLAlchemy==2.0.9
+python-telegram-bot==20.2
 arrow==1.2.3
 cachetools==4.2.2
 requests==2.28.2
@@ -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/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/rpc/test_rpc_apiserver.py

@@ -1405,10 +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}"
@@ -1442,6 +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'