def test_dispatch_and_verify():
    # WONTFIX
    loc = Locations(2010, 1)
    csv_text = loc.interim_csv.read_text(encoding='utf-8')
    values = list(evaluate(csv_text, UNITS, YAML_DOC))
    dfs = {}
    for freq in 'aqm':
        df = create_dataframe(values, freq)
        dfs[freq] = df
        verify(df, freq)
Beispiel #2
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def parse(year,
          month,
          units_dict=UNITS,
          yaml_doc=YAML_DOC,
          data_root=DATA_ROOT,
          validator=verify):
    # filesystem
    loc = Locations(year, month, data_root)
    #parse    
    text = loc.interim_csv.read_text(encoding='utf-8')
    values = list(evaluate(text, units_dict, yaml_doc))    
    # save three dataframes
    dfs = {}
    for freq in 'aqm':
        df = create_dataframe(values, freq)
        dfs[freq] = df
        validator(df, freq)
        df.to_csv(str(loc.processed_csv(freq)))
    return dfs
Beispiel #3
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def isolation1(): 
    doc = SRC.read_text(encoding='utf-8') 
    return evaluate(doc, UNITS, YAML_DOC)  
Beispiel #4
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def save(year, month, dfs, data_root=DATA_ROOT, output_root=OUTPUT_ROOT):     
    loc = Locations(year, month, data_root)
    oloc = OutputLocations(output_root)
    if is_latest(year, month):
        to_latest(year, month, loc)
        save_excel(oloc.xlsx, dfs)
        
def all_months():
    for year, month in reversed(supported_dates()[:-2]):        
        print("\n"*5, year, month)        
        dfa, dfq, dfm = unpack(parse(year, month))

#for speed tests
SRC = Locations(2018, 1).interim_csv
TEST_DOC = SRC.read_text(encoding='utf-8') 
TEST_VALUES = list(evaluate(TEST_DOC, UNITS, YAML_DOC))

def isolation1(): 
    doc = SRC.read_text(encoding='utf-8') 
    return evaluate(doc, UNITS, YAML_DOC)  

def isolation2():
    dfs = {}
    for freq in 'aqm':
        df = create_dataframe(TEST_VALUES, freq)
        dfs[freq] = df
        verify(df, freq)        
        df.to_csv('temp.txt')
    return dfs    

if __name__ == '__main__':