chore: use string aliases for astype calls

freqtrade/data/btanalysis/bt_fileutils.py

@@ -10,7 +10,6 @@ from io import BytesIO, StringIO
 from pathlib import Path
 from typing import Any, Literal
 
-import numpy as np
 import pandas as pd
 
 from freqtrade.constants import LAST_BT_RESULT_FN
@@ -308,7 +307,7 @@ def get_backtest_market_change(filename: Path, include_ts: bool = True) -> pd.Da
     else:
         df = pd.read_feather(filename)
     if include_ts:
-        df.loc[:, "__date_ts"] = df.loc[:, "date"].dt.as_unit("ms").astype(np.int64)
+        df.loc[:, "__date_ts"] = df.loc[:, "date"].dt.as_unit("ms").astype("int64")
     return df
 
 
@@ -326,7 +325,7 @@ def get_backtest_wallet_change(filename: Path, strategy_name: str) -> pd.DataFra
         data = load_file_from_zip(filename, f"{filename.stem}_{strategy_name}_wallet.feather")
         df = pd.read_feather(BytesIO(data))
 
-        df.loc[:, "__date_ts"] = df.loc[:, "date"].dt.as_unit("ms").astype(np.int64)
+        df.loc[:, "__date_ts"] = df.loc[:, "date"].dt.as_unit("ms").astype("int64")
         return df
     except ValueError:
         pass

freqtrade/data/history/datahandlers/jsondatahandler.py

@@ -1,6 +1,5 @@
 import logging
 
-import numpy as np
 from pandas import DataFrame, read_json, to_datetime
 
 from freqtrade import misc
@@ -36,7 +35,7 @@ class JsonDataHandler(IDataHandler):
         self.create_dir_if_needed(filename)
         _data = data.copy()
         # Convert date to int (milliseconds)
-        _data["date"] = _data["date"].dt.as_unit("ms").astype(np.int64)
+        _data["date"] = _data["date"].dt.as_unit("ms").astype("int64")
 
         # Reset index, select only appropriate columns and save as json
         _data.reset_index(drop=True).loc[:, self._columns].to_json(

freqtrade/optimize/analysis/lookahead_helpers.py

@@ -126,14 +126,14 @@ class LookaheadAnalysisSubFunctions:
                 csv_df = add_or_update_row(csv_df, new_row_data)
 
         # Fill NaN values with a default value (e.g., 0)
-        csv_df["total_signals"] = csv_df["total_signals"].astype(int).fillna(0)
+        csv_df["total_signals"] = csv_df["total_signals"].astype("int64").fillna(0)
-        csv_df["biased_entry_signals"] = csv_df["biased_entry_signals"].astype(int).fillna(0)
+        csv_df["biased_entry_signals"] = csv_df["biased_entry_signals"].astype("int64").fillna(0)
-        csv_df["biased_exit_signals"] = csv_df["biased_exit_signals"].astype(int).fillna(0)
+        csv_df["biased_exit_signals"] = csv_df["biased_exit_signals"].astype("int64").fillna(0)
 
         # Convert columns to integers
-        csv_df["total_signals"] = csv_df["total_signals"].astype(int)
+        csv_df["total_signals"] = csv_df["total_signals"].astype("int64")
-        csv_df["biased_entry_signals"] = csv_df["biased_entry_signals"].astype(int)
+        csv_df["biased_entry_signals"] = csv_df["biased_entry_signals"].astype("int64")
-        csv_df["biased_exit_signals"] = csv_df["biased_exit_signals"].astype(int)
+        csv_df["biased_exit_signals"] = csv_df["biased_exit_signals"].astype("int64")
 
         logger.info(f"saving {config['lookahead_analysis_exportfilename']}")
         csv_df.to_csv(config["lookahead_analysis_exportfilename"], index=False)

tests/exchange_online/test_ccxt_compat.py

@@ -287,7 +287,7 @@ class TestCCXTExchange:
         # Check if last-timeframe is within the last 2 intervals
         now = datetime.now(UTC) - timedelta(minutes=(timeframe_to_minutes(timeframe) * 2))
         assert exch.klines(pair_tf).iloc[-1]["date"] >= timeframe_to_prev_date(timeframe, now)
-        assert exch.klines(pair_tf)["date"].astype(int).iloc[0] // 1e6 == since_ms
+        assert exch.klines(pair_tf)["date"].dt.as_unit("ms").astype("int64").iloc[0] == since_ms
 
     def _ccxt__async_get_candle_history(
         self, exchange, pair: str, timeframe: str, candle_type: CandleType, factor: float = 0.9