Lint fixes (#236)

* correct docstring

* add type annotation to trade_count_lock

* fix indentations

* allow globals in hyperopt.py

* fix import order

* simplify asserts

* use proper variable name

* simplify condition

* fix path operation that fails on windows
This commit is contained in:
Janne Sinivirta
2017-12-25 13:07:50 +02:00
committed by Michael Egger
parent 9959d53f5e
commit de33d69eed
5 changed files with 13 additions and 15 deletions

View File

@@ -58,7 +58,7 @@ def preprocess(tickerdata: Dict[str, List]) -> Dict[str, DataFrame]:
def testdata_path() -> str:
"""Return the path where testdata files are stored"""
return os.path.abspath(os.path.dirname(__file__)) + '/../tests/testdata'
return os.path.abspath(os.path.join(os.path.dirname(__file__), '..', 'tests', 'testdata'))
def download_pairs(pairs: List[str]) -> bool:

View File

@@ -68,14 +68,14 @@ def backtest(stake_amount: float, processed: Dict[str, DataFrame],
max_open_trades: int = 0, realistic: bool = True) -> DataFrame:
"""
Implements backtesting functionality
:param config: config to use
:param stake_amount: btc amount to use for each trade
:param processed: a processed dictionary with format {pair, data}
:param max_open_trades: maximum number of concurrent trades (default: 0, disabled)
:param realistic: do we try to simulate realistic trades? (default: True)
:return: DataFrame
"""
trades = []
trade_count_lock = {}
trade_count_lock: dict = {}
exchange._API = Bittrex({'key': '', 'secret': ''})
for pair, pair_data in processed.items():
pair_data['buy'], pair_data['sell'] = 0, 0
@@ -120,7 +120,7 @@ def backtest(stake_amount: float, processed: Dict[str, DataFrame],
current_profit_percent,
current_profit_BTC,
row2.Index - row.Index
)
)
)
break
labels = ['currency', 'profit_percent', 'profit_BTC', 'duration']

View File

@@ -1,4 +1,4 @@
# pragma pylint: disable=missing-docstring,W0212
# pragma pylint: disable=missing-docstring,W0212,W0603
import json
@@ -159,7 +159,7 @@ def format_results(results: DataFrame):
results.profit_percent.mean() * 100.0,
results.profit_BTC.sum(),
results.duration.mean() * 5,
)
)
def buy_strategy_generator(params):