Merge pull request #2833 from hroff-1902/type-hints

Add some type hints

freqtrade/optimize/backtesting.py

@@ -9,6 +9,7 @@ from datetime import datetime, timedelta
 from pathlib import Path
 from typing import Any, Dict, List, NamedTuple, Optional
 
+import arrow
 from pandas import DataFrame
 
 from freqtrade.configuration import (TimeRange, remove_credentials,
@@ -24,7 +25,7 @@ from freqtrade.optimize.optimize_reports import (
 from freqtrade.persistence import Trade
 from freqtrade.resolvers import ExchangeResolver, StrategyResolver
 from freqtrade.state import RunMode
-from freqtrade.strategy.interface import IStrategy, SellType
+from freqtrade.strategy.interface import IStrategy, SellCheckTuple, SellType
 
 logger = logging.getLogger(__name__)
 
@@ -148,7 +149,7 @@ class Backtesting:
             logger.info(f'Dumping backtest results to {recordfilename}')
             file_dump_json(recordfilename, records)
 
-    def _get_ticker_list(self, processed) -> Dict[str, DataFrame]:
+    def _get_ticker_list(self, processed: Dict) -> Dict[str, DataFrame]:
         """
         Helper function to convert a processed tickerlist into a list for performance reasons.
 
@@ -175,7 +176,8 @@ class Backtesting:
             ticker[pair] = [x for x in ticker_data.itertuples()]
         return ticker
 
-    def _get_close_rate(self, sell_row, trade: Trade, sell, trade_dur) -> float:
+    def _get_close_rate(self, sell_row, trade: Trade, sell: SellCheckTuple,
+                        trade_dur: int) -> float:
         """
         Get close rate for backtesting result
         """
@@ -280,7 +282,7 @@ class Backtesting:
         return None
 
     def backtest(self, processed: Dict, stake_amount: float,
-                 start_date, end_date,
+                 start_date: arrow.Arrow, end_date: arrow.Arrow,
                  max_open_trades: int = 0, position_stacking: bool = False) -> DataFrame:
         """
         Implement backtesting functionality

freqtrade/optimize/hyperopt.py

@@ -118,11 +118,11 @@ class Hyperopt:
         self.print_json = self.config.get('print_json', False)
 
     @staticmethod
-    def get_lock_filename(config) -> str:
+    def get_lock_filename(config: Dict[str, Any]) -> str:
 
         return str(config['user_data_dir'] / 'hyperopt.lock')
 
-    def clean_hyperopt(self):
+    def clean_hyperopt(self) -> None:
         """
         Remove hyperopt pickle files to restart hyperopt.
         """
@@ -159,7 +159,7 @@ class Hyperopt:
                         f"saved to '{self.trials_file}'.")
 
     @staticmethod
-    def _read_trials(trials_file) -> List:
+    def _read_trials(trials_file: Path) -> List:
         """
         Read hyperopt trials file
         """
@@ -190,7 +190,7 @@ class Hyperopt:
         return result
 
     @staticmethod
-    def print_epoch_details(results, total_epochs, print_json: bool,
+    def print_epoch_details(results, total_epochs: int, print_json: bool,
                             no_header: bool = False, header_str: str = None) -> None:
         """
         Display details of the hyperopt result
@@ -219,7 +219,7 @@ class Hyperopt:
             Hyperopt._params_pretty_print(params, 'trailing', "Trailing stop:")
 
     @staticmethod
-    def _params_update_for_json(result_dict, params, space: str):
+    def _params_update_for_json(result_dict, params, space: str) -> None:
         if space in params:
             space_params = Hyperopt._space_params(params, space)
             if space in ['buy', 'sell']:
@@ -236,7 +236,7 @@ class Hyperopt:
                 result_dict.update(space_params)
 
     @staticmethod
-    def _params_pretty_print(params, space: str, header: str):
+    def _params_pretty_print(params, space: str, header: str) -> None:
         if space in params:
             space_params = Hyperopt._space_params(params, space, 5)
             if space == 'stoploss':
@@ -252,7 +252,7 @@ class Hyperopt:
         return round_dict(d, r) if r else d
 
     @staticmethod
-    def is_best_loss(results, current_best_loss) -> bool:
+    def is_best_loss(results, current_best_loss: float) -> bool:
         return results['loss'] < current_best_loss
 
     def print_results(self, results) -> None:
@@ -439,7 +439,7 @@ class Hyperopt:
             random_state=self.random_state,
         )
 
-    def fix_optimizer_models_list(self):
+    def fix_optimizer_models_list(self) -> None:
         """
         WORKAROUND: Since skopt is not actively supported, this resolves problems with skopt
         memory usage, see also: https://github.com/scikit-optimize/scikit-optimize/pull/746
@@ -461,7 +461,7 @@ class Hyperopt:
                         wrap_non_picklable_objects(self.generate_optimizer))(v, i) for v in asked)
 
     @staticmethod
-    def load_previous_results(trials_file) -> List:
+    def load_previous_results(trials_file: Path) -> List:
         """
         Load data for epochs from the file if we have one
         """