Merge pull request #563 from gcarq/feature/typehints

Set correct typehints and minor code cleanups

freqtrade/analyze.py

@@ -3,13 +3,15 @@ Functions to analyze ticker data with indicators and produce buy and sell signal
 """
 from datetime import datetime, timedelta
 from enum import Enum
-from typing import Dict, List
+from typing import Dict, List, Tuple
+
 import arrow
 from pandas import DataFrame, to_datetime
+
 from freqtrade.exchange import get_ticker_history
 from freqtrade.logger import Logger
-from freqtrade.strategy.strategy import Strategy
 from freqtrade.persistence import Trade
+from freqtrade.strategy.strategy import Strategy
 
 
 class SignalType(Enum):
@@ -96,9 +98,7 @@ class Analyze(object):
         dataframe = self.populate_sell_trend(dataframe)
         return dataframe
 
-    # FIX: Maybe return False, if an error has occured,
-    #      Otherwise we might mask an error as an non-signal-scenario
-    def get_signal(self, pair: str, interval: int) -> (bool, bool):
+    def get_signal(self, pair: str, interval: int) -> Tuple[bool, bool]:
         """
         Calculates current signal based several technical analysis indicators
         :param pair: pair in format BTC_ANT or BTC-ANT
@@ -108,7 +108,7 @@ class Analyze(object):
         ticker_hist = get_ticker_history(pair, interval)
         if not ticker_hist:
             self.logger.warning('Empty ticker history for pair %s', pair)
-            return (False, False)  # return False ?
+            return False, False
 
         try:
             dataframe = self.analyze_ticker(ticker_hist)
@@ -118,18 +118,18 @@ class Analyze(object):
                 pair,
                 str(error)
             )
-            return (False, False)  # return False ?
+            return False, False
         except Exception as error:
             self.logger.exception(
                 'Unexpected error when analyzing ticker for pair %s: %s',
                 pair,
                 str(error)
             )
-            return (False, False)  # return False ?
+            return False, False
 
         if dataframe.empty:
             self.logger.warning('Empty dataframe for pair %s', pair)
-            return (False, False)  # return False ?
+            return False, False
 
         latest = dataframe.iloc[-1]
 
@@ -141,7 +141,7 @@ class Analyze(object):
                 pair,
                 (arrow.utcnow() - signal_date).seconds // 60
             )
-            return (False, False)  # return False ?
+            return False, False
 
         (buy, sell) = latest[SignalType.BUY.value] == 1, latest[SignalType.SELL.value] == 1
         self.logger.debug(
@@ -151,7 +151,7 @@ class Analyze(object):
             str(buy),
             str(sell)
         )
-        return (buy, sell)
+        return buy, sell
 
     def should_sell(self, trade: Trade, rate: float, date: datetime, buy: bool, sell: bool) -> bool:
         """

freqtrade/arguments.py

@@ -3,10 +3,10 @@ This module contains the argument manager class
 """
 
 import argparse
+import logging
 import os
 import re
-import logging
-from typing import List
+from typing import List, Tuple, Optional
 
 from freqtrade import __version__
 from freqtrade.constants import Constants
@@ -22,11 +22,11 @@ class Arguments(object):
         self.parsed_arg = None
         self.parser = argparse.ArgumentParser(description=description)
 
-    def _load_args(self):
+    def _load_args(self) -> None:
         self.common_args_parser()
         self._build_subcommands()
 
-    def get_parsed_arg(self) -> List[str]:
+    def get_parsed_arg(self) -> argparse.Namespace:
         """
         Return the list of arguments
         :return: List[str] List of arguments
@@ -37,7 +37,7 @@ class Arguments(object):
 
         return self.parsed_arg
 
-    def parse_args(self) -> List[str]:
+    def parse_args(self) -> argparse.Namespace:
         """
         Parses given arguments and returns an argparse Namespace instance.
         """
@@ -205,7 +205,7 @@ class Arguments(object):
         self.hyperopt_options(hyperopt_cmd)
 
     @staticmethod
-    def parse_timerange(text: str) -> (List, int, int):
+    def parse_timerange(text: str) -> Optional[Tuple[List, int, int]]:
         """
         Parse the value of the argument --timerange to determine what is the range desired
         :param text: value from --timerange
@@ -236,10 +236,10 @@ class Arguments(object):
                     stop = rvals[index]
                     if stype[1] != 'date':
                         stop = int(stop)
-                return (stype, start, stop)
+                return stype, start, stop
         raise Exception('Incorrect syntax for timerange "%s"' % text)
 
-    def scripts_options(self):
+    def scripts_options(self) -> None:
         """
         Parses given arguments for plot scripts.
         """

freqtrade/configuration.py

@@ -3,8 +3,9 @@ This module contains the configuration class
 """
 
 import json
+from argparse import Namespace
+from typing import Dict, Any
 
-from typing import Dict, List, Any
 from jsonschema import Draft4Validator, validate
 from jsonschema.exceptions import ValidationError, best_match
 
@@ -17,7 +18,7 @@ class Configuration(object):
     Class to read and init the bot configuration
     Reuse this class for the bot, backtesting, hyperopt and every script that required configuration
     """
-    def __init__(self, args: List[str], do_not_init=False) -> None:
+    def __init__(self, args: Namespace) -> None:
         self.args = args
         self.logging = Logger(name=__name__)
         self.logger = self.logging.get_logger()

freqtrade/exchange/bittrex.py

@@ -1,8 +1,8 @@
 import logging
 from typing import Dict, List, Optional
 
-from bittrex.bittrex import Bittrex as _Bittrex
 from bittrex.bittrex import API_V1_1, API_V2_0
+from bittrex.bittrex import Bittrex as _Bittrex
 from requests.exceptions import ContentDecodingError
 
 from freqtrade import OperationalException

freqtrade/fiat_convert.py

@@ -5,12 +5,13 @@ e.g BTC to USD
 
 import logging
 import time
+
 from coinmarketcap import Market
 
 logger = logging.getLogger(__name__)
 
 
-class CryptoFiat():
+class CryptoFiat(object):
     """
     Object to describe what is the price of Crypto-currency in a FIAT
     """

freqtrade/freqtradebot.py

@@ -6,11 +6,14 @@ import copy
 import json
 import time
 import traceback
-from typing import Dict, List, Optional, Any, Callable
 from datetime import datetime
-import requests
+from typing import Dict, List, Optional, Any, Callable
+
 import arrow
+import requests
 from cachetools import cached, TTLCache
+
+from freqtrade import (DependencyException, OperationalException, exchange, persistence)
 from freqtrade.analyze import Analyze
 from freqtrade.constants import Constants
 from freqtrade.fiat_convert import CryptoToFiatConverter
@@ -18,7 +21,6 @@ from freqtrade.logger import Logger
 from freqtrade.persistence import Trade
 from freqtrade.rpc.rpc_manager import RPCManager
 from freqtrade.state import State
-from freqtrade import (DependencyException, OperationalException, exchange, persistence)
 
 
 class FreqtradeBot(object):
@@ -27,7 +29,7 @@ class FreqtradeBot(object):
     This is from here the bot start its logic.
     """
 
-    def __init__(self, config: Dict[str, Any], db_url: Optional[str] = None) -> bool:
+    def __init__(self, config: Dict[str, Any], db_url: Optional[str] = None):
         """
         Init all variables and object the bot need to work
         :param config: configuration dict, you can use the Configuration.get_config()

freqtrade/indicator_helpers.py

@@ -1,19 +1,19 @@
 from math import exp, pi, sqrt, cos
 
-import numpy
+import numpy as np
 import talib as ta
 from pandas import Series
 
 
-def went_up(series: Series) -> Series:
+def went_up(series: Series) -> bool:
     return series > series.shift(1)
 
 
-def went_down(series: Series) -> Series:
+def went_down(series: Series) -> bool:
     return series < series.shift(1)
 
 
-def ehlers_super_smoother(series: Series, smoothing: float = 6):
+def ehlers_super_smoother(series: Series, smoothing: float = 6) -> type(Series):
     magic = pi * sqrt(2) / smoothing
     a1 = exp(-magic)
     coeff2 = 2 * a1 * cos(magic)
@@ -29,7 +29,7 @@ def ehlers_super_smoother(series: Series, smoothing: float = 6):
     return filtered
 
 
-def fishers_inverse(series: Series, smoothing: float = 0):
+def fishers_inverse(series: Series, smoothing: float = 0) -> np.ndarray:
     """ Does a smoothed fishers inverse transformation.
         Can be used with any oscillator that goes from 0 to 100 like RSI or MFI """
     v1 = 0.1 * (series - 50)
@@ -37,4 +37,4 @@ def fishers_inverse(series: Series, smoothing: float = 0):
         v2 = ta.WMA(v1.values, timeperiod=smoothing)
     else:
         v2 = v1
-    return (numpy.exp(2 * v2)-1) / (numpy.exp(2 * v2) + 1)
+    return (np.exp(2 * v2)-1) / (np.exp(2 * v2) + 1)

freqtrade/main.py

@@ -6,17 +6,18 @@ Read the documentation to know what cli arguments you need.
 
 import logging
 import sys
-from typing import Dict
-from freqtrade.configuration import Configuration
+from typing import List
+
+from freqtrade import (__version__)
 from freqtrade.arguments import Arguments
+from freqtrade.configuration import Configuration
 from freqtrade.freqtradebot import FreqtradeBot
 from freqtrade.logger import Logger
-from freqtrade import (__version__)
 
 logger = Logger(name='freqtrade').get_logger()
 
 
-def main(sysargv: Dict) -> None:
+def main(sysargv: List[str]) -> None:
     """
     This function will initiate the bot and start the trading loop.
     :return: None

freqtrade/misc.py

@@ -2,16 +2,19 @@
 Various tool function for Freqtrade and scripts
 """
 
-import re
 import json
 import logging
+import re
 from datetime import datetime
+from typing import Dict
+
 import numpy as np
+from pandas import DataFrame
 
 logger = logging.getLogger(__name__)
 
 
-def shorten_date(_date):
+def shorten_date(_date: str) -> str:
     """
     Trim the date so it fits on small screens
     """
@@ -28,7 +31,7 @@ def shorten_date(_date):
 # Matplotlib doesn't support ::datetime64, #
 # so we need to convert it into ::datetime #
 ############################################
-def datesarray_to_datetimearray(dates):
+def datesarray_to_datetimearray(dates: np.ndarray) -> np.ndarray:
     """
     Convert an pandas-array of timestamps into
     An numpy-array of datetimes
@@ -42,10 +45,10 @@ def datesarray_to_datetimearray(dates):
     return np.array(times)
 
 
-def common_datearray(dfs):
+def common_datearray(dfs: Dict[str, DataFrame]) -> np.ndarray:
     """
     Return dates from Dataframe
-    :param dfs: Dataframe
+    :param dfs: Dict with format pair: pair_data
     :return: List of dates
     """
     alldates = {}

freqtrade/optimize/__init__.py

@@ -1,20 +1,20 @@
 # pragma pylint: disable=missing-docstring
 
+import gzip
 import json
 import os
-from typing import Optional, List, Dict
-import gzip
-from freqtrade.exchange import get_ticker_history
+from typing import Optional, List, Dict, Tuple
 
 from freqtrade import misc
+from freqtrade.exchange import get_ticker_history
 from freqtrade.logger import Logger
 from user_data.hyperopt_conf import hyperopt_optimize_conf
 
 logger = Logger(name=__name__).get_logger()
 
 
-def trim_tickerlist(tickerlist, timerange):
-    (stype, start, stop) = timerange
+def trim_tickerlist(tickerlist: List[Dict], timerange: Tuple[Tuple, int, int]) -> List[Dict]:
+    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,
-              refresh_pairs: Optional[bool] = False, timerange=None) -> Dict[str, List]:
+def load_data(datadir: str, ticker_interval: int,
+              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

@@ -3,18 +3,19 @@
 """
 This module contains the backtesting logic
 """
+from argparse import Namespace
+from typing import Dict, Tuple, Any, List, Optional
 
-from typing import Dict, Tuple, Any
 import arrow
 from pandas import DataFrame, Series
 from tabulate import tabulate
 
 import freqtrade.optimize as optimize
-from freqtrade.arguments import Arguments
-from freqtrade.exchange import Bittrex
-from freqtrade.configuration import Configuration
 from freqtrade import exchange
 from freqtrade.analyze import Analyze
+from freqtrade.arguments import Arguments
+from freqtrade.configuration import Configuration
+from freqtrade.exchange import Bittrex
 from freqtrade.logger import Logger
 from freqtrade.misc import file_dump_json
 from freqtrade.persistence import Trade
@@ -101,7 +102,10 @@ 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 +136,7 @@ class Backtesting(object):
                     sell_row.date
         return None
 
-    def backtest(self, args) -> DataFrame:
+    def backtest(self, args: Dict) -> DataFrame:
         """
         Implements backtesting functionality
 
@@ -273,7 +277,7 @@ 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 +293,7 @@ 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

@@ -10,6 +10,7 @@ import os
 import pickle
 import signal
 import sys
+from argparse import Namespace
 from functools import reduce
 from math import exp
 from operator import itemgetter
@@ -22,11 +23,11 @@ from hyperopt.mongoexp import MongoTrials
 from pandas import DataFrame
 
 import freqtrade.vendor.qtpylib.indicators as qtpylib
-from freqtrade.configuration import Configuration
-from freqtrade.optimize import load_data
 from freqtrade.arguments import Arguments
-from freqtrade.optimize.backtesting import Backtesting
+from freqtrade.configuration import Configuration
 from freqtrade.logger import Logger
+from freqtrade.optimize import load_data
+from freqtrade.optimize.backtesting import Backtesting
 from user_data.hyperopt_conf import hyperopt_optimize_conf
 
 
@@ -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()

freqtrade/persistence.py

@@ -207,6 +207,7 @@ class Trade(_DECL_BASE):
         Calculates the profit in percentage (including fee).
         :param rate: rate to compare with (optional).
         If rate is not set self.close_rate will be used
+        :param fee: fee to use on the close rate (optional).
         :return: profit in percentage as float
         """
         getcontext().prec = 8

freqtrade/rpc/rpc.py

@@ -2,16 +2,19 @@
 This module contains class to define a RPC communications
 """
 
-from decimal import Decimal
 from datetime import datetime, timedelta
+from decimal import Decimal
+from typing import Tuple, Any
+
 import arrow
-from pandas import DataFrame
 import sqlalchemy as sql
+from pandas import DataFrame
+
+from freqtrade import exchange
 from freqtrade.logger import Logger
+from freqtrade.misc import shorten_date
 from freqtrade.persistence import Trade
 from freqtrade.state import State
-from freqtrade import exchange
-from freqtrade.misc import shorten_date
 
 
 class RPC(object):
@@ -30,7 +33,7 @@ class RPC(object):
             level=self.freqtrade.config.get('loglevel')
         ).get_logger()
 
-    def rpc_trade_status(self) -> (bool, Trade):
+    def rpc_trade_status(self) -> Tuple[bool, Any]:
         """
         Below follows the RPC backend it is prefixed with rpc_ to raise awareness that it is
         a remotely exposed function
@@ -39,9 +42,9 @@ class RPC(object):
         # Fetch open trade
         trades = Trade.query.filter(Trade.is_open.is_(True)).all()
         if self.freqtrade.get_state() != State.RUNNING:
-            return (True, '*Status:* `trader is not running`')
+            return True, '*Status:* `trader is not running`'
         elif not trades:
-            return (True, '*Status:* `no active trade`')
+            return True, '*Status:* `no active trade`'
         else:
             result = []
             for trade in trades:
@@ -80,14 +83,14 @@ class RPC(object):
                               ) if order else None,
                           )
                 result.append(message)
-            return (False, result)
+            return False, result
 
-    def rpc_status_table(self) -> (bool, DataFrame):
+    def rpc_status_table(self) -> Tuple[bool, Any]:
         trades = Trade.query.filter(Trade.is_open.is_(True)).all()
         if self.freqtrade.get_state() != State.RUNNING:
-            return (True, '*Status:* `trader is not running`')
+            return True, '*Status:* `trader is not running`'
         elif not trades:
-            return (True, '*Status:* `no active order`')
+            return True, '*Status:* `no active order`'
         else:
             trades_list = []
             for trade in trades:
@@ -107,14 +110,16 @@ class RPC(object):
             # consisting of (error_occured?, result)
             # Another approach would be to just return the
             # result, or raise error
-            return (False, df_statuses)
+            return False, df_statuses
 
-    def rpc_daily_profit(self, timescale, stake_currency, fiat_display_currency):
+    def rpc_daily_profit(
+            self, timescale: int,
+            stake_currency: str, fiat_display_currency: str) -> Tuple[bool, Any]:
         today = datetime.utcnow().date()
         profit_days = {}
 
         if not (isinstance(timescale, int) and timescale > 0):
-            return (True, '*Daily [n]:* `must be an integer greater than 0`')
+            return True, '*Daily [n]:* `must be an integer greater than 0`'
 
         fiat = self.freqtrade.fiat_converter
         for day in range(0, timescale):
@@ -153,9 +158,10 @@ class RPC(object):
             ]
             for key, value in profit_days.items()
         ]
-        return (False, stats)
+        return False, stats
 
-    def rpc_trade_statistics(self, stake_currency, fiat_display_currency) -> None:
+    def rpc_trade_statistics(
+            self, stake_currency: str, fiat_display_currency: str) -> Tuple[bool, Any]:
         """
         :return: cumulative profit statistics.
         """
@@ -190,15 +196,13 @@ class RPC(object):
             profit_all_percent.append(profit_percent)
 
         best_pair = Trade.session.query(
-                        Trade.pair,
-                        sql.func.sum(Trade.close_profit).label('profit_sum')
-            )\
-            .filter(Trade.is_open.is_(False))\
+            Trade.pair, sql.func.sum(Trade.close_profit).label('profit_sum')
+        ).filter(Trade.is_open.is_(False)) \
             .group_by(Trade.pair) \
             .order_by(sql.text('profit_sum DESC')).first()
 
         if not best_pair:
-            return (True, '*Status:* `no closed trade`')
+            return True, '*Status:* `no closed trade`'
 
         bp_pair, bp_rate = best_pair
 
@@ -239,7 +243,7 @@ class RPC(object):
             }
         )
 
-    def rpc_balance(self, fiat_display_currency):
+    def rpc_balance(self, fiat_display_currency: str) -> Tuple[bool, Any]:
         """
         :return: current account balance per crypto
         """
@@ -248,7 +252,7 @@ class RPC(object):
             if c['Balance'] or c['Available'] or c['Pending']
         ]
         if not balances:
-            return (True, '`All balances are zero.`')
+            return True, '`All balances are zero.`'
 
         output = []
         total = 0.0
@@ -275,17 +279,17 @@ class RPC(object):
         fiat = self.freqtrade.fiat_converter
         symbol = fiat_display_currency
         value = fiat.convert_amount(total, 'BTC', symbol)
-        return (False, (output, total, symbol, value))
+        return False, (output, total, symbol, value)
 
     def rpc_start(self) -> (bool, str):
         """
         Handler for start.
         """
         if self.freqtrade.get_state() == State.RUNNING:
-            return (True, '*Status:* `already running`')
+            return True, '*Status:* `already running`'
 
         self.freqtrade.update_state(State.RUNNING)
-        return (False, '`Starting trader ...`')
+        return False, '`Starting trader ...`'
 
     def rpc_stop(self) -> (bool, str):
         """
@@ -293,18 +297,18 @@ class RPC(object):
         """
         if self.freqtrade.get_state() == State.RUNNING:
             self.freqtrade.update_state(State.STOPPED)
-            return (False, '`Stopping trader ...`')
+            return False, '`Stopping trader ...`'
 
-        return (True, '*Status:* `already stopped`')
+        return True, '*Status:* `already stopped`'
 
     # FIX: no test for this!!!!
-    def rpc_forcesell(self, trade_id) -> None:
+    def rpc_forcesell(self, trade_id) -> Tuple[bool, Any]:
         """
         Handler for forcesell <id>.
         Sells the given trade at current price
         :return: error or None
         """
-        def _exec_forcesell(trade: Trade) -> str:
+        def _exec_forcesell(trade: Trade) -> None:
             # Check if there is there is an open order
             if trade.open_order_id:
                 order = exchange.get_order(trade.open_order_id)
@@ -326,13 +330,13 @@ class RPC(object):
         # ---- EOF def _exec_forcesell ----
 
         if self.freqtrade.get_state() != State.RUNNING:
-            return (True, '`trader is not running`')
+            return True, '`trader is not running`'
 
         if trade_id == 'all':
             # Execute sell for all open orders
             for trade in Trade.query.filter(Trade.is_open.is_(True)).all():
                 _exec_forcesell(trade)
-            return (False, '')
+            return False, ''
 
         # Query for trade
         trade = Trade.query.filter(
@@ -343,18 +347,18 @@ class RPC(object):
         ).first()
         if not trade:
             self.logger.warning('forcesell: Invalid argument received')
-            return (True, 'Invalid argument.')
+            return True, 'Invalid argument.'
 
         _exec_forcesell(trade)
-        return (False, '')
+        return False, ''
 
-    def rpc_performance(self) -> None:
+    def rpc_performance(self) -> Tuple[bool, Any]:
         """
         Handler for performance.
         Shows a performance statistic from finished trades
         """
         if self.freqtrade.get_state() != State.RUNNING:
-            return (True, '`trader is not running`')
+            return True, '`trader is not running`'
 
         pair_rates = Trade.session.query(Trade.pair,
                                          sql.func.sum(Trade.close_profit).label('profit_sum'),
@@ -367,15 +371,15 @@ class RPC(object):
         for (pair, rate, count) in pair_rates:
             trades.append({'pair': pair, 'profit': round(rate * 100, 2), 'count': count})
 
-        return (False, trades)
+        return False, trades
 
-    def rpc_count(self) -> None:
+    def rpc_count(self) -> Tuple[bool, Any]:
         """
         Returns the number of trades running
         :return: None
         """
         if self.freqtrade.get_state() != State.RUNNING:
-            return (True, '`trader is not running`')
+            return True, '`trader is not running`'
 
         trades = Trade.query.filter(Trade.is_open.is_(True)).all()
-        return (False, trades)
+        return False, trades

freqtrade/rpc/rpc_manager.py

@@ -28,7 +28,7 @@ class RPCManager(object):
         self.telegram = None
         self._init()
 
-    def _init(self):
+    def _init(self) -> None:
         """
         Init RPC modules
         :return:

freqtrade/rpc/telegram.py

@@ -5,10 +5,12 @@ This module manage Telegram communication
 """
 
 from typing import Any, Callable
+
 from tabulate import tabulate
 from telegram import Bot, ParseMode, ReplyKeyboardMarkup, Update
 from telegram.error import NetworkError, TelegramError
 from telegram.ext import CommandHandler, Updater
+
 from freqtrade.__init__ import __version__
 from freqtrade.rpc.rpc import RPC
 

freqtrade/strategy/default_strategy.py

@@ -2,9 +2,10 @@
 
 import talib.abstract as ta
 from pandas import DataFrame
+
 import freqtrade.vendor.qtpylib.indicators as qtpylib
-from freqtrade.strategy.interface import IStrategy
 from freqtrade.indicator_helpers import fishers_inverse
+from freqtrade.strategy.interface import IStrategy
 
 class_name = 'DefaultStrategy'
 

freqtrade/strategy/interface.py

@@ -4,6 +4,7 @@ This module defines the interface to apply for strategies
 """
 
 from abc import ABC, abstractmethod
+
 from pandas import DataFrame
 
 

freqtrade/strategy/strategy.py

@@ -7,11 +7,12 @@ import importlib
 import os
 import sys
 from collections import OrderedDict
-from pandas import DataFrame
-from freqtrade.logger import Logger
-from freqtrade.constants import Constants
-from freqtrade.strategy.interface import IStrategy
 
+from pandas import DataFrame
+
+from freqtrade.constants import Constants
+from freqtrade.logger import Logger
+from freqtrade.strategy.interface import IStrategy
 
 sys.path.insert(0, r'../../user_data/strategies')
 
@@ -59,7 +60,7 @@ class Strategy(object):
         # Minimal ROI designed for the strategy
         self.minimal_roi = OrderedDict(sorted(
             {int(key): value for (key, value) in self.custom_strategy.minimal_roi.items()}.items(),
-            key=lambda tuple: tuple[0]))  # sort after converting to number
+            key=lambda t: t[0]))  # sort after converting to number
 
         # Optimal stoploss designed for the strategy
         self.stoploss = float(self.custom_strategy.stoploss)

freqtrade/tests/conftest.py

@@ -1,14 +1,15 @@
 # pragma pylint: disable=missing-docstring
-from datetime import datetime
-from unittest.mock import MagicMock
-from functools import reduce
-import logging
 import json
+import logging
+from datetime import datetime
+from functools import reduce
+from unittest.mock import MagicMock
+
 import arrow
 import pytest
 from jsonschema import validate
-from telegram import Chat, Message, Update
 from sqlalchemy import create_engine
+from telegram import Chat, Message, Update
 
 from freqtrade.analyze import Analyze
 from freqtrade.constants import Constants

freqtrade/tests/exchange/test_exchange.py

@@ -1,15 +1,16 @@
 # pragma pylint: disable=missing-docstring, C0103, bad-continuation, global-statement
 # pragma pylint: disable=protected-access
-from unittest.mock import MagicMock
-from random import randint
 import logging
-from requests.exceptions import RequestException
-import pytest
+from random import randint
+from unittest.mock import MagicMock
 
+import pytest
+from requests.exceptions import RequestException
+
+import freqtrade.exchange as exchange
 from freqtrade import OperationalException
 from freqtrade.exchange import init, validate_pairs, buy, sell, get_balance, get_balances, \
     get_ticker, get_ticker_history, cancel_order, get_name, get_fee
-import freqtrade.exchange as exchange
 from freqtrade.tests.conftest import log_has
 
 API_INIT = False

freqtrade/tests/exchange/test_exchange_bittrex.py

@@ -1,10 +1,12 @@
 # pragma pylint: disable=missing-docstring, C0103, protected-access, unused-argument
 
 from unittest.mock import MagicMock
+
 import pytest
 from requests.exceptions import ContentDecodingError
-from freqtrade.exchange.bittrex import Bittrex
+
 import freqtrade.exchange.bittrex as btx
+from freqtrade.exchange.bittrex import Bittrex
 
 
 # Eat this flake8

freqtrade/tests/optimize/test_backtesting.py

@@ -1,20 +1,21 @@
 # pragma pylint: disable=missing-docstring, W0212, line-too-long, C0103, unused-argument
 
 import json
-import random
 import math
-from typing import List
+import random
 from copy import deepcopy
+from typing import List
 from unittest.mock import MagicMock
-from arrow import Arrow
-import pandas as pd
-import numpy as np
-from freqtrade import optimize
-from freqtrade.optimize.backtesting import Backtesting, start, setup_configuration
-from freqtrade.arguments import Arguments
-from freqtrade.analyze import Analyze
-from freqtrade.tests.conftest import default_conf, log_has
 
+import numpy as np
+import pandas as pd
+from arrow import Arrow
+
+from freqtrade import optimize
+from freqtrade.analyze import Analyze
+from freqtrade.arguments import Arguments
+from freqtrade.optimize.backtesting import Backtesting, start, setup_configuration
+from freqtrade.tests.conftest import default_conf, log_has
 
 # Avoid to reinit the same object again and again
 _BACKTESTING = Backtesting(default_conf())

freqtrade/tests/optimize/test_hyperopt.py

@@ -3,6 +3,7 @@ import json
 import os
 from copy import deepcopy
 from unittest.mock import MagicMock
+
 import pandas as pd
 
 from freqtrade.optimize.__init__ import load_tickerdata_file

freqtrade/tests/optimize/test_optimize.py

@@ -1,13 +1,14 @@
 # pragma pylint: disable=missing-docstring, protected-access, C0103
 
-import os
 import json
+import os
 import uuid
 from shutil import copyfile
+
 from freqtrade import optimize
+from freqtrade.misc import file_dump_json
 from freqtrade.optimize.__init__ import make_testdata_path, download_pairs, \
     download_backtesting_testdata, load_tickerdata_file, trim_tickerlist
-from freqtrade.misc import file_dump_json
 from freqtrade.tests.conftest import log_has
 
 # Change this if modifying BTC_UNITEST testdatafile

freqtrade/tests/rpc/test_rpc_telegram.py

@@ -6,23 +6,23 @@ Unit test file for rpc/telegram.py
 """
 
 import re
+from copy import deepcopy
 from datetime import datetime
 from random import randint
 from unittest.mock import MagicMock
-from copy import deepcopy
 
 from sqlalchemy import create_engine
 from telegram import Update, Message, Chat
 from telegram.error import NetworkError
 
 from freqtrade import __version__
-from freqtrade.rpc.telegram import authorized_only
 from freqtrade.freqtradebot import FreqtradeBot
-from freqtrade.rpc.telegram import Telegram
 from freqtrade.persistence import Trade
+from freqtrade.rpc.telegram import Telegram
+from freqtrade.rpc.telegram import authorized_only
 from freqtrade.state import State
-from freqtrade.tests.test_freqtradebot import patch_get_signal, patch_coinmarketcap
 from freqtrade.tests.conftest import get_patched_freqtradebot, log_has
+from freqtrade.tests.test_freqtradebot import patch_get_signal, patch_coinmarketcap
 
 
 class DummyCls(Telegram):

freqtrade/tests/strategy/test_default_strategy.py

@@ -1,8 +1,10 @@
 import json
+
 import pytest
 from pandas import DataFrame
-from freqtrade.strategy.default_strategy import DefaultStrategy, class_name
+
 from freqtrade.analyze import Analyze
+from freqtrade.strategy.default_strategy import DefaultStrategy, class_name
 
 
 @pytest.fixture

freqtrade/tests/strategy/test_strategy.py

@@ -1,6 +1,7 @@
 # pragma pylint: disable=missing-docstring, protected-access, C0103
 
 import logging
+
 from freqtrade.strategy.strategy import Strategy
 
 

freqtrade/tests/test_analyze.py

@@ -5,8 +5,9 @@ Unit test file for analyse.py
 """
 
 import datetime
-from unittest.mock import MagicMock
 import logging
+from unittest.mock import MagicMock
+
 import arrow
 from pandas import DataFrame
 
@@ -14,7 +15,6 @@ from freqtrade.analyze import Analyze, SignalType
 from freqtrade.optimize.__init__ import load_tickerdata_file
 from freqtrade.tests.conftest import log_has
 
-
 # Avoid to reinit the same object again and again
 _ANALYZE = Analyze({'strategy': 'default_strategy'})
 

freqtrade/tests/test_arguments.py

@@ -6,6 +6,7 @@ Unit test file for arguments.py
 
 import argparse
 import logging
+
 import pytest
 
 from freqtrade.arguments import Arguments

freqtrade/tests/test_configuration.py

@@ -4,10 +4,10 @@
 Unit test file for configuration.py
 """
 import json
-
 from copy import deepcopy
-import pytest
 from unittest.mock import MagicMock
+
+import pytest
 from jsonschema import ValidationError
 
 from freqtrade.arguments import Arguments

freqtrade/tests/test_dataframe.py

@@ -2,8 +2,8 @@
 
 import pandas
 
-from freqtrade.optimize import load_data
 from freqtrade.analyze import Analyze
+from freqtrade.optimize import load_data
 from freqtrade.strategy.strategy import Strategy
 
 _pairs = ['BTC_ETH']

freqtrade/tests/test_freqtradebot.py

@@ -5,22 +5,23 @@ Unit test file for freqtradebot.py
 """
 
 import logging
+import re
 import time
-from unittest.mock import MagicMock
 from copy import deepcopy
 from typing import Dict, Optional
+from unittest.mock import MagicMock
+
 import arrow
 import pytest
 import requests
-import re
 from sqlalchemy import create_engine
 
-from freqtrade.tests.conftest import log_has
 from freqtrade import DependencyException, OperationalException
 from freqtrade.exchange import Exchanges
 from freqtrade.freqtradebot import FreqtradeBot
-from freqtrade.state import State
 from freqtrade.persistence import Trade
+from freqtrade.state import State
+from freqtrade.tests.conftest import log_has
 
 
 # Functions for recurrent object patching

freqtrade/tests/test_indicator_helpers.py

@@ -1,4 +1,5 @@
 import pandas as pd
+
 from freqtrade.indicator_helpers import went_up, went_down
 
 

freqtrade/tests/test_logger.py

@@ -3,6 +3,7 @@ Unit test file for logger.py
 """
 
 import logging
+
 from freqtrade.logger import Logger
 
 

freqtrade/tests/test_main.py

@@ -4,6 +4,7 @@ Unit test file for main.py
 
 import logging
 from unittest.mock import MagicMock
+
 import pytest
 
 from freqtrade.main import main, set_loggers

freqtrade/tests/test_misc.py

@@ -6,10 +6,11 @@ Unit test file for misc.py
 
 import datetime
 from unittest.mock import MagicMock
+
 from freqtrade.analyze import Analyze
-from freqtrade.optimize.__init__ import load_tickerdata_file
 from freqtrade.misc import (shorten_date, datesarray_to_datetimearray,
                             common_datearray, file_dump_json)
+from freqtrade.optimize.__init__ import load_tickerdata_file
 
 
 def test_shorten_date() -> None:

freqtrade/tests/test_persistence.py

@@ -1,7 +1,9 @@
 # pragma pylint: disable=missing-docstring, C0103
 import os
+
 import pytest
 from sqlalchemy import create_engine
+
 from freqtrade.exchange import Exchanges
 from freqtrade.persistence import Trade, init, clean_dry_run_db
 

freqtrade/tests/testdata/download_backtest_data.py

@@ -1,12 +1,12 @@
 #!/usr/bin/env python3
 
 """This script generate json data from bittrex"""
-import sys
 import json
+import sys
 
 from freqtrade import exchange
-from freqtrade.exchange import Bittrex
 from freqtrade import misc
+from freqtrade.exchange import Bittrex
 
 parser = misc.common_args_parser('download utility')
 parser.add_argument(

scripts/plot_dataframe.py

@@ -13,8 +13,9 @@ Optional Cli parameters
 """
 
 import sys
+from argparse import Namespace
 
-from typing import Dict
+from typing import List
 
 from plotly import tools
 from plotly.offline import plot
@@ -30,10 +31,9 @@ import freqtrade.optimize as optimize
 logger = Logger(name="Graph dataframe").get_logger()
 
 
-def plot_analyzed_dataframe(args) -> None:
+def plot_analyzed_dataframe(args: Namespace) -> None:
     """
     Calls analyze() and plots the returned dataframe
-    :param pair: pair as str
     :return: None
     """
     pair = args.pair.replace('-', '_')
@@ -153,7 +153,7 @@ def plot_analyzed_dataframe(args) -> None:
     plot(fig, filename='freqtrade-plot.html')
 
 
-def plot_parse_args(args):
+def plot_parse_args(args: List[str]) -> Namespace:
     """
     Parse args passed to the script
     :param args: Cli arguments
@@ -168,7 +168,7 @@ def plot_parse_args(args):
     return arguments.parse_args()
 
 
-def main(sysargv: Dict) -> None:
+def main(sysargv: List[str]) -> None:
     """
     This function will initiate the bot and start the trading loop.
     :return: None

scripts/plot_profit.py

@@ -13,7 +13,8 @@ Optional Cli parameters
 
 import sys
 import json
-from typing import Dict
+from argparse import Namespace
+from typing import List, Optional
 import numpy as np
 
 from plotly import tools
@@ -34,8 +35,11 @@ logger = Logger(name="Graph profits").get_logger()
 
 # data:: [ pair,      profit-%,  enter,         exit,        time, duration]
 # data:: ["BTC_ETH", 0.0023975, "1515598200", "1515602100", "2018-01-10 07:30:00+00:00", 65]
-def make_profit_array(data, px, min_date, interval, filter_pairs=[]):
+def make_profit_array(
+        data: List, px: int, min_date: int,
+        interval: int, filter_pairs: Optional[List] = None) -> np.ndarray:
     pg = np.zeros(px)
+    filter_pairs = filter_pairs or []
     # Go through the trades
     # and make an total profit
     # array
@@ -63,7 +67,7 @@ def make_profit_array(data, px, min_date, interval, filter_pairs=[]):
     return pg
 
 
-def plot_profit(args) -> None:
+def plot_profit(args: Namespace) -> None:
     """
     Plots the total profit for all pairs.
     Note, the profit calculation isn't realistic.
@@ -183,14 +187,14 @@ def plot_profit(args) -> None:
     plot(fig, filename='freqtrade-profit-plot.html')
 
 
-def define_index(min_date, max_date, interval):
+def define_index(min_date: int, max_date: int, interval: int) -> int:
     """
     Return the index of a specific date
     """
     return int((max_date - min_date) / (interval * 60))
 
 
-def plot_parse_args(args):
+def plot_parse_args(args: List[str]) -> Namespace:
     """
     Parse args passed to the script
     :param args: Cli arguments
@@ -205,7 +209,7 @@ def plot_parse_args(args):
     return arguments.parse_args()
 
 
-def main(sysargv: Dict) -> None:
+def main(sysargv: List[str]) -> None:
     """
     This function will initiate the bot and start the trading loop.
     :return: None