optimize: set correct typehints

freqtrade/optimize/__init__.py

@@ -2,7 +2,7 @@
 
 import json
 import os
-from typing import Optional, List, Dict
+from typing import Optional, List, Dict, Tuple
 import gzip
 from freqtrade.exchange import get_ticker_history
 
@@ -13,8 +13,8 @@ from user_data.hyperopt_conf import hyperopt_optimize_conf
 logger = Logger(name=__name__).get_logger()
 
 
-def trim_tickerlist(tickerlist, timerange):
+def trim_tickerlist(tickerlist: List[Dict], timerange: Tuple[Tuple, int, int]) -> List[Dict]:
-    (stype, start, stop) = timerange
+    stype, start, stop = timerange
     if stype == (None, 'line'):
         return tickerlist[stop:]
     elif stype == ('line', None):
@@ -25,7 +25,10 @@ def trim_tickerlist(tickerlist, timerange):
     return tickerlist
 
 
-def load_tickerdata_file(datadir, pair, ticker_interval, timerange=None):
+def load_tickerdata_file(
+        datadir: str, pair: str,
+        ticker_interval: int,
+        timerange: Optional[Tuple[Tuple, int, int]] = None) -> Optional[List[Dict]]:
     """
     Load a pair from file,
     :return dict OR empty if unsuccesful
@@ -55,12 +58,12 @@ def load_tickerdata_file(datadir, pair, ticker_interval, timerange=None):
     return pairdata
 
 
-def load_data(datadir: str, ticker_interval: int, pairs: Optional[List[str]] = None,
+def load_data(datadir: str, ticker_interval: int,
-              refresh_pairs: Optional[bool] = False, timerange=None) -> Dict[str, List]:
+              pairs: Optional[List[str]] = None,
+              refresh_pairs: Optional[bool] = False,
+              timerange: Optional[Tuple[Tuple, int, int]] = None) -> Dict[str, List]:
     """
     Loads ticker history data for the given parameters
-    :param ticker_interval: ticker interval in minutes
-    :param pairs: list of pairs
     :return: dict
     """
     result = {}

freqtrade/optimize/backtesting.py

@@ -3,8 +3,8 @@
 """
 This module contains the backtesting logic
 """
-
+from argparse import Namespace
-from typing import Dict, Tuple, Any
+from typing import Dict, Tuple, Any, List, Optional
 import arrow
 from pandas import DataFrame, Series
 from tabulate import tabulate
@@ -101,7 +101,10 @@ class Backtesting(object):
         ])
         return tabulate(tabular_data, headers=headers, floatfmt=floatfmt)
 
-    def _get_sell_trade_entry(self, pair, buy_row, partial_ticker, trade_count_lock, args):
+    def _get_sell_trade_entry(
+            self, pair: str, buy_row: DataFrame,
+            partial_ticker: List, trade_count_lock: Dict, args: Dict) -> Optional[Tuple]:
+
         stake_amount = args['stake_amount']
         max_open_trades = args.get('max_open_trades', 0)
         trade = Trade(
@@ -132,7 +135,7 @@ class Backtesting(object):
                     sell_row.date
         return None
 
-    def backtest(self, args) -> DataFrame:
+    def backtest(self, args: Dict) -> DataFrame:
         """
         Implements backtesting functionality
 
@@ -273,7 +276,7 @@ class Backtesting(object):
         )
 
 
-def setup_configuration(args) -> Dict[str, Any]:
+def setup_configuration(args: Namespace) -> Dict[str, Any]:
     """
     Prepare the configuration for the backtesting
     :param args: Cli args from Arguments()
@@ -289,7 +292,7 @@ def setup_configuration(args) -> Dict[str, Any]:
     return config
 
 
-def start(args) -> None:
+def start(args: Namespace) -> None:
     """
     Start Backtesting script
     :param args: Cli args from Arguments()

freqtrade/optimize/hyperopt.py

@@ -10,10 +10,11 @@ import os
 import pickle
 import signal
 import sys
+from argparse import Namespace
 from functools import reduce
 from math import exp
 from operator import itemgetter
-from typing import Dict, Any, Callable
+from typing import Dict, Any, Callable, List
 
 import numpy
 import talib.abstract as ta
@@ -240,7 +241,7 @@ class Hyperopt(Backtesting):
         return trade_loss + profit_loss + duration_loss
 
     @staticmethod
-    def generate_roi_table(params) -> Dict[int, float]:
+    def generate_roi_table(params: Dict) -> Dict[int, float]:
         """
         Generate the ROI table thqt will be used by Hyperopt
         """
@@ -335,7 +336,7 @@ class Hyperopt(Backtesting):
             ]),
         }
 
-    def has_space(self, space) -> bool:
+    def has_space(self, space: str) -> bool:
         """
         Tell if a space value is contained in the configuration
         """
@@ -433,7 +434,7 @@ class Hyperopt(Backtesting):
 
         return populate_buy_trend
 
-    def generate_optimizer(self, params) -> Dict:
+    def generate_optimizer(self, params: Dict) -> Dict:
         if self.has_space('roi'):
             self.analyze.strategy.minimal_roi = self.generate_roi_table(params)
 
@@ -496,7 +497,7 @@ class Hyperopt(Backtesting):
                     results.duration.mean(),
                 )
 
-    def start(self):
+    def start(self) -> None:
         timerange = Arguments.parse_timerange(self.config.get('timerange'))
         data = load_data(
             datadir=self.config.get('datadir'),
@@ -571,7 +572,7 @@ class Hyperopt(Backtesting):
         # Store trials result to file to resume next time
         self.save_trials()
 
-    def signal_handler(self, sig, frame):
+    def signal_handler(self, sig, frame) -> None:
         """
         Hyperopt SIGINT handler
         """
@@ -585,7 +586,7 @@ class Hyperopt(Backtesting):
         sys.exit(0)
 
 
-def start(args) -> None:
+def start(args: Namespace) -> None:
     """
     Start Backtesting script
     :param args: Cli args from Arguments()