Add script and voters list for Feb 2021 elections

election/github_emails.py

@@ -1,4 +1,4 @@
-#!/user/bin/env python3
+#!/usr/bin/env python3
 
 """get_emails.py queries GitHub for the email addresses to use for usernames.
 

election/github_emails_2.py

@@ -0,0 +1,51 @@
+#!/usr/bin/env python3
+
+"""get_emails_2.py Extracts github IDs from a CSV and matches them
+to emails through a JSON map.
+
+The CVS input file can be obtained from devstats. Clink on the link:
+https://tekton.devstats.cd.foundation/d/9/developer-activity-counts-by-repository-group-table?inspect=1&inspectTab=data&viewPanel=1&orgId=1&var-period_name=Last%20year&var-metric=contributions&var-repogroup_name=All&var-country_name=All
+and use the download CSV button to download the CSV file.
+
+The script takes the JSON map from https://github.com/cncf/devstats/blob/master/github_users.json,
+which is one of the input files used by the CDF for devstats.
+
+The output will be a mapping of the GitHub username to the all email addresses
+contained in commits associated with this user in a csv file.
+
+Usage:
+  python3 github_emails_2.py --file users.csv
+"""
+import argparse
+import csv
+import requests
+from typing import List, Dict
+
+import pandas as pd
+
+EMAIL_MAP = "https://github.com/cncf/devstats/raw/master/github_users.json"
+
+if __name__ == '__main__':
+  arg_parser = argparse.ArgumentParser(
+      description="Try to find email addresses for GitHub usernames")
+  arg_parser.add_argument("--file", type=str, required=True,
+                          help="A file containing the GitHub usernames to query, separated by a newline")
+  arg_parser.add_argument("--csv", type=str, required=False,
+                          help="csv file to write with results")
+  args = arg_parser.parse_args()
+
+  csvfile = args.csv or "found_emails.csv"
+  missingfile = "missing_emails.csv"
+
+  # load data
+  users = pd.read_csv(args.file)
+  emailmap = pd.read_json(EMAIL_MAP)
+  emailmap = emailmap[~emailmap['email'].str.endswith('users.noreply.github.com')]
+
+  # filter eligible users
+  eligible = users[users['value'] >= 15]
+  found = pd.merge(eligible, emailmap, left_on='name', right_on='login', how='left', indicator=True).query('_merge == "both"').drop(columns='_merge')
+  found['email'] = found['email'].str.replace('!', '@')
+  missing = pd.merge(eligible, emailmap, left_on='name', right_on='login', how='left', indicator=True).query('_merge == "left_only"').drop(columns='_merge')
+  found.to_csv(csvfile, columns=['name_x', 'email'], header=False, index=False)
+  missing.to_csv(missingfile, columns=['name_x'], header=False, index=False)