Dawn Foster geekygirldawn

## diary.md

      
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              June 16, 2023 08:42
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                Knative TOC 2023 Election - election officer diary
              
          
    Knative TOC 2023 Election - election officer diary

Note: all emails sent are recorded in this Google Doc: https://docs.google.com/document/d/1oqgy9VcmZP872hUS1dQyAd3H_88UpCDdakwqY128hKA

Find volunteers to be election officers for the election. At least one volunteer should have previous election officer experience
Create a PR on https://github.com/knative/community/blob/main/groups/committee-steering/groups.yaml to add election officers to elections@knative.team
Create a PR for the election: knative/community#1332, based on previous election files
Prepare an election announcement in Google Docs and ask for SC feedback
Send the announcement to Knative community (knative-dev mailing list and #knative Slack channel) on the date written in the election PR
Prepare reminder emails in advance


## chaoss_urls.py
# I created a super hacky Jupyter Notebook that looks at
# https://chaoss.community/kbtopic/all-metrics/ which
# contains a list of all of our metrics, and then uses
# BeautifulSoup + hackiness to extract the short link
# from the wordpress pages. I was in a hurry, so I
# printed the csv output to the screen instead of to
# a csv file.

import urllib.request as urllib2
from bs4 import BeautifulSoup

## totalContributionsEx.txt
Using the GiHub GraphQL API contributionsCollection, you can get this pretty easily.
You need to get it for each type of contribution, but then you can add them up. Then
you could loop through a list of users to get this for each of them.
Documentation: https://docs.github.com/en/graphql/reference/objects#contributionscollection

Example GraphQL API Query:

query totalContributions{
  user(login: "geekygirldawn") {
    name

## gist:a7d3feb5fef7497e793c6b83ffc7eb06
import pandas as pd
import matplotlib
import seaborn as sns
import matplotlib.pyplot as plt

pr_all['diff'] = pr_all.first_response_time - pr_all.pr_created_at
pr_all['yearmonth'] = pr_all['pr_created_at'].dt.strftime('%Y-%m')
pr_all['diff_days'] = pr_all['diff'] / datetime.timedelta(days=1)
year_month_list = pr_all.yearmonth.unique()
year_month_list.sort()
	# I created a super hacky Jupyter Notebook that looks at
	# https://chaoss.community/kbtopic/all-metrics/ which
	# contains a list of all of our metrics, and then uses
	# BeautifulSoup + hackiness to extract the short link
	# from the wordpress pages. I was in a hurry, so I
	# printed the csv output to the screen instead of to
	# a csv file.

	import urllib.request as urllib2
	from bs4 import BeautifulSoup
	Using the GiHub GraphQL API contributionsCollection, you can get this pretty easily.
	You need to get it for each type of contribution, but then you can add them up. Then
	you could loop through a list of users to get this for each of them.
	Documentation: https://docs.github.com/en/graphql/reference/objects#contributionscollection

	Example GraphQL API Query:

	query totalContributions{
	user(login: "geekygirldawn") {
	name
	import pandas as pd
	import matplotlib
	import seaborn as sns
	import matplotlib.pyplot as plt

	pr_all['diff'] = pr_all.first_response_time - pr_all.pr_created_at
	pr_all['yearmonth'] = pr_all['pr_created_at'].dt.strftime('%Y-%m')
	pr_all['diff_days'] = pr_all['diff'] / datetime.timedelta(days=1)
	year_month_list = pr_all.yearmonth.unique()
	year_month_list.sort()