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match_committers_pr.py
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#!/usr/bin/env python
# coding: utf-8
# In[98]:
import os
#import cudf.pandas
import pandas as pd
import numpy as np
from ast import literal_eval
from collections import OrderedDict, defaultdict
import yaml
import requests
import time
import re
#cudf.pandas.install()
import random
import glob
os.environ['NUMEXPR_MAX_THREADS'] = '48'
os.environ['NUMEXPR_NUM_THREADS'] = '36'
# In[2]:
pd.set_option('display.max_columns', None)
# In[3]:
def tryReadParquet(file, cols):
try:
return pd.read_parquet(file)[cols]
except:
return pd.DataFrame()
commit_list = glob.glob('data/github_commits/parquet/filtered_github_data/*_pr_*.parquet')
commit_list.extend(glob.glob('data/github_commits/parquet/github_data_pre_18/*_pr_*.parquet'))
commit_list.extend(glob.glob('data/github_commits/parquet/github_data_2324/*_pr_*.parquet'))
commit_cols = ['pr_number', 'repo_name', 'repo_id', 'commit author name', 'commit author email', 'committer name', 'commmitter email',
'commit sha']
df_pr = pd.concat([tryReadParquet(ele, commit_cols) for ele in commit_list]).drop_duplicates()
# In[7]:
df_committers = df_pr.dropna()
df_committers_uq = pd.concat([
df_committers[['pr_number', 'repo_name', 'repo_id', 'commit author name', 'commit author email']].drop_duplicates().rename(
{'commit author name': 'name', 'commit author email': 'email'}, axis = 1),
df_committers[['pr_number', 'repo_name','repo_id', 'committer name', 'commmitter email']].drop_duplicates().rename(
{'committer name': 'name', 'commmitter email': 'email'}, axis = 1)])[['name', 'email']].drop_duplicates().dropna()
# In[55]:
df_committers['commit author details'] = df_committers['commit author name'] + "_"+df_committers['commit author email']
df_committers['commit_repo'] = df_committers['commit sha'] + "_" + df_committers['repo_name']
df_author_emails = df_committers[~df_committers['commit author name'].isna()].groupby(
'commit author details')[['commit_repo']].agg(list)
df_author_emails['commit_repo'] = df_author_emails['commit_repo'].apply(lambda x: random.sample(x, min(5, len(x))))
dict_author_emails = df_author_emails.to_dict()['commit_repo']
# In[56]:
df_committers['committer details'] = df_committers['committer name'] + "_"+df_committers['commmitter email']
df_committer_emails = df_committers[~df_committers['committer name'].isna()].groupby(
'committer details')[['commit_repo']].agg(list)
df_committer_emails['commit_repo'] = df_committer_emails['commit_repo'].apply(lambda x: random.sample(x, min(5, len(x))))
dict_committer_emails = df_committer_emails.to_dict()['commit_repo']
# In[74]:
df_committers_uq['commit_repo'] = df_committers_uq.apply(
lambda x: dict_author_emails.get(x['name']+"_"+x['email'], np.nan), axis = 1)
df_committers_uq['user_type'] = df_committers_uq['commit_repo'].apply(
lambda x: 'author' if type(x) == list else 'committer')
df_committers_uq['commit_repo'] = df_committers_uq.apply(
lambda x: dict_committer_emails[x['name']+"_"+x['email']]
if type(x['commit_repo']) != list else x['commit_repo'], axis = 1)
# In[95]:
username = "liaochris"
token = os.environ['token']
# In[101]:
def getCommits(commit_repo, user_type):
success = False
i = 0
while (not success) or i < len(commit_repo):
repo_info = commit_repo[i].split("_")[1]
sha = commit_repo[i].split("_")[0]
api_url = f"https://api.github.com/repos/{repo_info}/commits/{sha}"
with requests.get(api_url, auth=(username,token)) as url:
try:
data = url.json()
info = data[user_type]
time.sleep(.75)
if info != None:
success = True
return [info['login'], info['id'], info['type'], info['site_admin']]
i+=1
except:
print(data)
i+=1
return np.nan
df_committers_uq = pd.merge(df_committers_uq.drop('committer_info', axis = 1), pd.read_csv('data/merged_data/committers_info_push.csv', index_col = 0)[['name','email','committer_info']], how = 'left')
df_committers_uq['committer_info'] = df_committers_uq['committer_info'].apply(lambda x: literal_eval(x) if not pd.isnull(x) else x)
# In[104]:
ncount = 1000
df_committers_uq.reset_index(drop = True, inplace = True)
indices = np.array_split(df_committers_uq[df_committers_uq['committer_info'].isna()].index, ncount)
for i in np.arange(start, ncount, 1):
print(f"Iter {i}")
df_committers_uq.loc[indices[i], 'committer_info'] = df_committers_uq.loc[indices[i]].apply(
lambda x: getCommits(x['commit_repo'],x['user_type']), axis = 1)
df_committers_uq.to_parquet('data/merged_data/committers_info_pr.parquet')
# same email
email_info_dict = df_committers_uq[['email', 'committer_info']].dropna().astype(str).drop_duplicates().set_index('email').to_dict()['committer_info']
df_committers_uq['committer_info'] = df_committers_uq.apply(lambda x: email_info_dict.get(x['email'], np.nan) if \
type(x) != list else x['committer_info'], axis = 1)
# email trick
ends_with_ind = df_committers_uq[df_committers_uq.apply(lambda x:
(x['email'].endswith("@users.noreply.github.com") if not pd.isnull(x['email']) else False) and \
pd.isnull(x['committer_info']), axis = 1)].index
df_committers_uq.loc[ends_with_ind, 'committer_info'] = df_committers_uq.loc[ends_with_ind, 'email'].apply(lambda x: x.replace("@users.noreply.github.com","").replace("@","").split("+"))
df_committers_uq['committer_info'] = df_committers_uq['committer_info'].apply(lambda x: str(x) if type(x) == list else x)
# same name, same repo -> fill in
df_committers_uq['repo'] = df_committers_uq['commit_repo'].apply(lambda x: x.split("_")[1])
df_committers_uq['name_repo'] = df_committers_uq['name']+"_"+df_committers_uq['repo']
name_repo_info = df_committers_uq[['name_repo', 'committer_info']].drop_duplicates().dropna().set_index('name_repo').to_dict()['committer_info']
df_committers_uq['committer_info'] = df_committers_uq.apply(lambda x: name_repo_info.get(x['name_repo'], np.nan) if \
pd.isnull(x['committer_info']) else x['committer_info'], axis = 1)
df_committers_uq.drop(['name_repo', 'repo'], axis = 1, inplace = True)
df_committers_uq['committer_info'] = df_committers_uq['committer_info'].apply(lambda x: literal_eval(x) if type(x) == str else x)
df_committers_uq['committer_info'] = df_committers_uq['committer_info'].apply(lambda x: np.nan if type(x) == list and len(x) == 0 else x)
## full info grab
val_inds = df_committers_uq[df_committers_uq['committer_info'].apply(lambda x: type(x) == list and len(x) == 4)].index
df_committers_uq.loc[val_inds, 'actor_login'] = df_committers_uq.loc[val_inds, 'committer_info'].apply(lambda x: x[0])
df_committers_uq.loc[val_inds, 'actor_id'] = df_committers_uq.loc[val_inds, 'committer_info'].apply(lambda x: x[1])
df_committers_uq.loc[val_inds, 'user_type'] = df_committers_uq.loc[val_inds, 'committer_info'].apply(lambda x: x[2])
df_committers_uq.loc[val_inds, 'site_admin'] = df_committers_uq.loc[val_inds, 'committer_info'].apply(lambda x: x[3])
## username and id
three_ind = df_committers_uq[df_committers_uq['committer_info'].apply(lambda x: type(x) == list and len(x)==3)]['committer_info'].index
df_committers_uq.loc[three_ind, 'committer_info'] = pd.Series([[7869818, 'rayrrr']])
val_inds = df_committers_uq[df_committers_uq['committer_info'].apply(lambda x: type(x) == list and len(x) == 2 and x[0] != '{ID}')].index
# fix corrupted cases
df_committers_uq.loc[val_inds, 'committer_info'] = df_committers_uq.loc[val_inds, 'committer_info'].apply(
lambda x: [str(ele).replace('user.email47079615','47079615').replace('user.email=1699478','1699478').replace(
'j38999128','38999128').replace('Fredrik Mellström 11281108','11281108').replace('\x96','') if type(ele) == str else ele for ele in x])
df_committers_uq.loc[val_inds, 'committer_info'] = df_committers_uq.loc[val_inds, 'committer_info'].apply(
lambda x: [3577255, 'palmtree5'] if (x[0] == 'palmtree5' and str(x[1]) == '3577255') else x)
df_committers_uq.loc[val_inds, 'actor_login'] = df_committers_uq.loc[val_inds, 'committer_info'].apply(lambda x: x[1])
df_committers_uq.loc[val_inds, 'committer_info'] = df_committers_uq.loc[val_inds, 'committer_info'].apply(
lambda x: [re.sub('[^0-9]','', x[0]).replace('\x96','') if type(x[0]) == str else x[0], x[1]])
df_committers_uq.loc[val_inds, 'actor_id'] = df_committers_uq.loc[val_inds, 'committer_info'].apply(
lambda x: pd.to_numeric(x[0]))
# just username or just id
val_inds = df_committers_uq[df_committers_uq['committer_info'].apply(lambda x: type(x) == list and len(x) == 1 and
pd.isnull(pd.to_numeric(x[0], errors = 'coerce')))].index
df_committers_uq.loc[val_inds, 'actor_login'] = df_committers_uq.loc[val_inds, 'committer_info'].apply(lambda x: x[0])
df_committers_uq.to_parquet('data/merged_data/committers_info_pr.parquet', engine = 'fastparquet')