68 lines
2.2 KiB
Python
Executable File
68 lines
2.2 KiB
Python
Executable File
#!/usr/bin/env python
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"""
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Script to list full details for a mrva-list file
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1. reads files containing
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{
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"mirva-list": [
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"NLPchina/elasticsearch-sqlctsj168cc4",
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"LMAX-Exchange/disruptorctsj3e75ec",
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"justauth/JustAuthctsj8a6177",
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"FasterXML/jackson-modules-basectsj2fe248",
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"ionic-team/capacitor-pluginsctsj38d457",
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"PaddlePaddle/PaddleOCRctsj60e555",
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"elastic/apm-agent-pythonctsj21dc64",
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"flipkart-incubator/zjsonpatchctsjc4db35",
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"stephane/libmodbusctsj54237e",
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"wso2/carbon-kernelctsj5a8a6e",
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"apache/servicecomb-packctsj4d98f5"
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]
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}
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2. reads a pandas dataframe stored in a csv file
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3. selects all rows from 2. that
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- contain the 'owner' column matching the string before the slash from 1. and
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- the 'name' column matching the string between the slash and the marker
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'ctsj' and
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- the 'CID' column matching the string after the marker 'ctsj'
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"""
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import argparse
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import json
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import sys
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#
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#* Process command line
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#
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parser = argparse.ArgumentParser(
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description="""Script to list full details for a mrva-list file""")
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parser.add_argument('mrva_list', type=str,
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help='The JSON file containing the mrva-list')
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parser.add_argument('info_csv', type=str,
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help='The CSV file containing the full information')
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args = parser.parse_args()
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#* Step 1: Read the JSON file containing the "mirva-list"
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with open(args.mrva_list, 'r') as f:
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data = json.load(f)
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# Extract and parse the "mirva-list"
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mirva_list = data['mirva-list']
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parsed_mirva_list = []
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for item in mirva_list:
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owner_name = item.split('/')[0]
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repo_name = item.split('/')[1].split('ctsj')[0]
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cid = item.split('/')[1].split('ctsj')[1]
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parsed_mirva_list.append((owner_name, repo_name, cid))
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#* Step 2: Read the CSV file into a pandas dataframe
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import pandas as pd
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df = pd.read_csv(args.info_csv)
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#* Step 3: Filter the dataframe based on the parsed "mirva-list"
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filtered_df = df[
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df.apply(lambda row:
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(row['owner'], row['name'], row['CID']) in parsed_mirva_list, axis=1)]
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# Optionally, you can save the filtered dataframe to a new CSV file
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filtered_df.to_csv(sys.stdout, index=False)
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