tests: anal stretching to accomodate flake8

freqtrade/tests/optimize/test_backtesting.py

@@ -1,5 +1,3 @@
-# pragma pylint: disable=missing-docstring,W0212
-
 import math
 import os
 import pandas as pd
@@ -126,9 +124,10 @@ def test_download_backtesting_testdata(default_conf, ticker_history, mocker):
 def trim_dataframe(df, num):
     new = dict()
     for pair, pair_data in df.items():
-        new[pair] = pair_data[-num:] # last 50 rows
+        new[pair] = pair_data[-num:]  # last 50 rows
     return new
 
+
 def load_data_test(what):
     data = optimize.load_data(ticker_interval=1, pairs=['BTC_UNITEST'])
     data = trim_dataframe(data, -40)
@@ -136,63 +135,66 @@ def load_data_test(what):
 
     # Depending on the what parameter we now adjust the
     # loaded data:
-    # pair :: [{'O': 0.123, 'H': 0.123, 'L': 0.123, 'C': 0.123, 'V': 123.123, 'T': '2017-11-04T23:02:00', 'BV': 0.123}]
+    # pair :: [{'O': 0.123, 'H': 0.123, 'L': 0.123,
+    #           'C': 0.123, 'V': 123.123,
+    #           'T': '2017-11-04T23:02:00', 'BV': 0.123}]
     if what == 'raise':
-        o = h = l = c = 0.001
-        l -= 0.0001
+        o = 0.001
+        h = 0.001
+        ll = 0.001
+        c = 0.001
+        ll -= 0.0001
         h += 0.0001
         for frame in pair:
             o += 0.0001
             h += 0.0001
-            l += 0.0001
+            ll += 0.0001
             c += 0.0001
-            o = round(o,9) # round to satoshis
-            h = round(h,9)
-            l = round(l,9)
-            c = round(c,9)
-            frame['O'] = o
-            frame['H'] = h
-            frame['L'] = l
-            frame['C'] = c
+            # save prices rounded to satoshis
+            frame['O'] = round(o, 9)
+            frame['H'] = round(h, 9)
+            frame['L'] = round(ll, 9)
+            frame['C'] = round(c, 9)
     if what == 'lower':
-        o = h = l = c = 0.001
-        l -= 0.0001
+        o = 0.001
+        h = 0.001
+        ll = 0.001
+        c = 0.001
+        ll -= 0.0001
         h += 0.0001
         for frame in pair:
             o -= 0.0001
             h -= 0.0001
-            l -= 0.0001
+            ll -= 0.0001
             c -= 0.0001
-            o = round(o,9) # round to satoshis
-            h = round(h,9)
-            l = round(l,9)
-            c = round(c,9)
-            frame['O'] = o
-            frame['H'] = h
-            frame['L'] = l
-            frame['C'] = c
+            # save prices rounded to satoshis
+            frame['O'] = round(o, 9)
+            frame['H'] = round(h, 9)
+            frame['L'] = round(ll, 9)
+            frame['C'] = round(c, 9)
     if what == 'sine':
         i = 0
-        o = h = l = c = (2 + math.sin(i/10)) / 1000
+        o = (2 + math.sin(i/10)) / 1000
+        h = o
+        ll = o
+        c = o
         h += 0.0001
-        l -= 0.0001
+        ll -= 0.0001
         for frame in pair:
-            o = (2 + math.sin(i/10)) / 1000 
+            o = (2 + math.sin(i/10)) / 1000
             h = (2 + math.sin(i/10)) / 1000 + 0.0001
-            l = (2 + math.sin(i/10)) / 1000 - 0.0001
+            ll = (2 + math.sin(i/10)) / 1000 - 0.0001
             c = (2 + math.sin(i/10)) / 1000 - 0.000001
 
-            o = round(o,9) # round to satoshis
-            h = round(h,9)
-            l = round(l,9)
-            c = round(c,9)
-            frame['O'] = o
-            frame['H'] = h
-            frame['L'] = l
-            frame['C'] = c
+            # save prices rounded to satoshis
+            frame['O'] = round(o, 9)
+            frame['H'] = round(h, 9)
+            frame['L'] = round(ll, 9)
+            frame['C'] = round(c, 9)
             i += 1
     return data
 
+
 def simple_backtest(config, contour, num_results):
     data = load_data_test(contour)
     processed = optimize.preprocess(data)
@@ -204,23 +206,23 @@ def simple_backtest(config, contour, num_results):
 # Test backtest on offline data
 # loaded by freqdata/optimize/__init__.py::load_data()
 
-def test_backtest(default_conf, mocker):
+
+def test_backtest2(default_conf, mocker):
     mocker.patch.dict('freqtrade.main._CONF', default_conf)
     data = optimize.load_data(ticker_interval=5, pairs=['BTC_ETH'])
     results = backtest(default_conf['stake_amount'], optimize.preprocess(data), 10, True)
     num_resutls = len(results)
     assert num_resutls > 0
 
+
 def test_processed(default_conf, mocker):
     mocker.patch.dict('freqtrade.main._CONF', default_conf)
     data = load_data_test('raise')
-    processed = optimize.preprocess(data)
+    assert optimize.preprocess(data)
+
 
 def test_raise(default_conf, mocker):
     mocker.patch.dict('freqtrade.main._CONF', default_conf)
     tests = [['raise', 359], ['lower', 0], ['sine', 1734]]
     for [contour, numres] in tests:
         simple_backtest(default_conf, contour, numres)
-
-
-

freqtrade/tests/test_acl_pair.py

@@ -1,27 +1,20 @@
+from freqtrade.main import refresh_whitelist
 
 # whitelist, blacklist, filtering, all of that will
 # eventually become some rules to run on a generic ACL engine
-
 # perhaps try to anticipate that by using some python package
 
-import pytest
-from unittest.mock import MagicMock
-import copy
 
-from freqtrade.main import refresh_whitelist
-#from freqtrade.exchange import Exchanges
-from freqtrade import exchange
-
-# "deep equal"
-def assert_list_equal (l1, l2):
+def assert_list_equal(l1, l2):
     for pair in l1:
         assert pair in l2
     for pair in l2:
         assert pair in l1
 
+
 def whitelist_conf():
     return {
-        "stake_currency":"BTC",
+        "stake_currency": "BTC",
         "exchange": {
             "pair_whitelist": [
                 "BTC_ETH",
@@ -33,13 +26,15 @@ def whitelist_conf():
         },
     }
 
+
 def get_health():
     return [{'Currency': 'ETH',
              'IsActive': True
-            },
+             },
             {'Currency': 'TKN',
              'IsActive': True
-            }]
+             }]
+
 
 def get_health_empty():
     return []
@@ -47,6 +42,7 @@ def get_health_empty():
 # below three test could be merged into a single
 # test that ran randomlly generated health lists
 
+
 def test_refresh_whitelist(mocker):
     conf = whitelist_conf()
     mocker.patch.dict('freqtrade.main._CONF', conf)
@@ -59,6 +55,7 @@ def test_refresh_whitelist(mocker):
     # Ensure all except those in whitelist are removed
     assert_list_equal(whitelist, pairslist)
 
+
 def test_refresh_whitelist_dynamic(mocker):
     conf = whitelist_conf()
     mocker.patch.dict('freqtrade.main._CONF', conf)
@@ -70,6 +67,7 @@ def test_refresh_whitelist_dynamic(mocker):
     pairslist = conf['exchange']['pair_whitelist']
     assert_list_equal(whitelist, pairslist)
 
+
 def test_refresh_whitelist_dynamic_empty(mocker):
     conf = whitelist_conf()
     mocker.patch.dict('freqtrade.main._CONF', conf)

freqtrade/tests/test_dataframe.py

@@ -1,13 +1,11 @@
-
-import pytest
 import pandas
 
 from freqtrade import analyze
 import freqtrade.optimize
-from pandas import DataFrame
 
 _pairs = ['BTC_ETH']
 
+
 def load_dataframe_pair(pairs):
     ld = freqtrade.optimize.load_data(ticker_interval=5, pairs=pairs)
     assert isinstance(ld, dict)
@@ -16,12 +14,14 @@ def load_dataframe_pair(pairs):
     dataframe = analyze.analyze_ticker(dataframe)
     return dataframe
 
+
 def test_dataframe_load():
     dataframe = load_dataframe_pair(_pairs)
     assert isinstance(dataframe, pandas.core.frame.DataFrame)
 
+
 def test_dataframe_columns_exists():
     dataframe = load_dataframe_pair(_pairs)
-    assert 'high'  in dataframe.columns
-    assert 'low'   in dataframe.columns
+    assert 'high' in dataframe.columns
+    assert 'low' in dataframe.columns
     assert 'close' in dataframe.columns