def test_candles_analysis():
files = da.list_data_files()
# file1 = files["1M"][0]
# file2 = files["10M"][0]
# candles, df1, df2, time_match_df1, time_match_df2 = da.compare_candles_frequencies(file1, file2)
# df = da.format_df_candles(df1, time_match_df1, candles)
output = da.candles_analysis(files)
assert output is None
def test_filter_date_df():
files = da.list_data_files()
file1 = files["1M"][0]
file2 = files["10M"][0]
dates_overlapping = da.filter_overlapping_dates(file1, file2)
df1 = pandas.read_csv(file1)
output = da.filter_date_df(dates_overlapping, df1)
assert isinstance(output, pandas.DataFrame)
assert len(output) > 0
def test_format_df_candles():
files = da.list_data_files()
file1 = files["1M"][0]
file2 = files["10M"][0]
candles, df1, df2, time_match_df1, time_match_df2 = da.compare_candles_frequencies(
file1, file2)
output = da.format_df_candles(df1, time_match_df1, candles)
assert isinstance(output, pandas.DataFrame)
assert len(output) > 0
def test_filter_overlapping_dates():
files = da.list_data_files()
file1 = files["1M"][0]
file2 = files["3M"][0]
dates_duplicated = da.filter_overlapping_dates(file1, file2)
assert len(dates_duplicated) is 0
assert isinstance(dates_duplicated, list)
file2 = files["10M"][0]
dates_duplicated = da.filter_overlapping_dates(file1, file2)
assert len(dates_duplicated) > 0
assert isinstance(dates_duplicated, list)
def test_filter_overlapping_files_dfs():
files = da.list_data_files()
file1 = files["1M"][0]
file2 = files["10M"][0]
output = da.filter_overlapping_files_dfs(file1, file2)
assert len(output) == 2
assert len(output[0]) > 0
file1 = files["1M"][0]
file2 = files["3M"][0]
output = da.filter_overlapping_files_dfs(file1, file2)
assert len(output) == 2
assert len(output[0]) == 0
def test_compare_candles_frequencies():
files = da.list_data_files()
file1 = files["1M"][0]
file2 = files["10M"][0]
output = da.compare_candles_frequencies(file1, file2)
assert len(output) is 5
assert all(isinstance(n, int) for n in list(output[0]))
file1 = files["1M"][1]
file2 = files["10M"][0]
output = da.compare_candles_frequencies(file1, file2)
assert len(output) is 5
assert all(isinstance(n, int) for n in list(output[0]))
def test_filter_time_match():
files = da.list_data_files()
file1 = files["1M"][0]
file2 = files["10M"][0]
output = da.filter_time_match(file1, file2)
assert len(output) is 2
def test_list_data_files():
output = da.list_data_files()
assert isinstance(output, dict)
assert len(output.keys()) > 0
def test_filter_overlapping_files():
df_input = da.list_data_files()
output = da.filter_overlapping_files(df_input)
assert isinstance(output, dict)