Mercurial > repos > nml > biohansel_bionumeric_converter

annotate bionumeric_converter.py @ 1:07dfb8fd47f4 draft default tip

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planemo upload commit e0d65bf0850ce95ffb89982e61f2136fcf0359ee
author nml
date Mon, 13 May 2019 12:59:15 -0400
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1 #!/usr/bin/env python
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3 # Import dependancies needed
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4 import argparse
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6 import pandas as pd
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8 # Define the main function:
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11 def main():
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12 parser = argparse.ArgumentParser()
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13 parser.add_argument(
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14 '-f',
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15 '--filename',
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16 required=True,
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17 help='Specify your biohansel tsv or other tabular separated input')
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18 parser.add_argument(
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19 '-o',
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20 '--output',
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21 default='output.csv',
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22 help='Specify output name')
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23 args = parser.parse_args()
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24 tsv_file = args.filename
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25 out_name = args.output
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27 df_input = pd.read_csv(tsv_file, sep='\t')
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29 df_no_comma = df_input.replace(',', '/', regex=True)
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30 df = qc_shortener(df_no_comma)
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31 df.to_csv(out_name, index=False)
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33 # Shorten QC results:
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35
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36 def splittingstrings(string, length):
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37 return (string[0+i:length+i] for i in range(0, len(string), length))
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40 def qc_shortener(df):
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41 for i, row in df.iterrows():
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42 message = str(row['qc_message'])
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43 if len(message) > 150:
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44 message_list = list(splittingstrings(message, 150))
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45 df.at[i, 'qc_message'] = message_list[0]
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46 for val in range(1, len(message_list)):
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47 df.at[i, 'qc_message_{}'.format(val)] = message_list[val]
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48 return df
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51 if __name__ == '__main__':
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52 main()