GitHub_Track_issues_on_projects.md

Template request | Bug report | Generate Data Product

Tags: #github #repos #issues #operations #analytics #csv #plotly

Author: Sanjeet Attili

Description: This notebook allows users to track and manage issues related to their projects on GitHub.

Input

Imports libraries

import plotly.express as px
from naas_drivers import github

Setup GitHub

How to find your personal access token on Github?

• First we need to create a personal access token to get the details of our organization from here: https://github.com/settings/tokens
• You will be asked to select scopes for the token. Which scopes you choose will determine what information and actions you will be able to perform against the API.
• You should be careful with the ones prefixed with write:, delete: and admin: as these might be quite destructive.
• You can find description of each scope in docs here (https://docs.github.com/en/developers/apps/building-oauth-apps/scopes-for-oauth-apps).

# Project URL from web
PROJECT_URL = "https://github.com/orgs/jupyter-naas/projects"

# GitHub Token
GITHUB_TOKEN = "ghp_COJiJEU4cQR4rjsxxxxxx"

Setup variables

# Graph : bar order
STATUS_ORDER = ["Backlog", "To Do", "In Progress", "Review", "Done"]

# Outputs
csv_output = "GitHub_Issues.csv"

Model

Get issues from project on Github

df_issues = github.connect(GITHUB_TOKEN).projects.get_issues(PROJECT_URL)
df_issues.tail(15)

Create barchart

for index, s in enumerate(STATUS_ORDER):
    print(index, s)

def create_barchart(df, title, labels):
    # Get status
    status = df.issue_status.unique().tolist()
    status_order = []
    for index, s in enumerate(STATUS_ORDER):
        if s in status:
            status_order += [s]

    # Create fig
    fig = px.bar(
        df, title=title, x=status_order, y="count", text="count", labels=labels
    )
    fig.update_traces(marker_color="black")
    fig.update_layout(
        plot_bgcolor="#ffffff",
        width=1000,
        height=800,
        font=dict(family="Arial", size=14, color="black"),
        paper_bgcolor="white",
        yaxis_title="No of issues",
        yaxis_title_font=dict(family="Arial", size=11, color="black"),
        xaxis_title="Status",
        xaxis_title_font=dict(family="Arial", size=11, color="black"),
        margin_pad=10,
    )
    fig.show()
    return fig

Output

Save data in csv

df_issues.to_csv(csv_output, index=False)

Plotting a bar graph for total number of issues

# Dataframe
issues = (
    df_issues.groupby("issue_status")
    .agg({"issue_number": "count"})
    .reset_index()
    .rename(columns={"issue_number": "count"})
)

# Chart title
title = f"Github Project - {PROJECT_URL.split('/')[-2]} : {df_issues['project_name'].unique()[0]} <br><span style='font-size: 13px;'>Total issues: {issues['count'].sum()}</span>"

# Hover labels
labels = {"issue_status": "Issue status", "count": "Number of Issues"}
fig = create_barchart(issues, title, labels)

Plotting a bar graph for open issues

# Dataframe
open_issues = (
    df_issues[df_issues["issue_state"] == "open"]
    .groupby("issue_status")
    .agg({"issue_number": "count"})
    .reset_index()
    .rename(columns={"issue_number": "count"})
)

# Chart title
title = f"Github Project - {PROJECT_URL.split('/')[-2]} : {df_issues['project_name'].unique()[0]} <br><span style='font-size: 13px;'>Total open issues: {open_issues['count'].sum()}</span>"

# Hover labels
labels = {"issue_status": "Issue status", "count": "Number of Open issues"}
fig = create_barchart(open_issues, title, labels)

Plotting a bar graph for closed issues

# Dataframe
closed_issues = (
    df_issues[df_issues["issue_state"] == "closed"]
    .groupby("issue_status")
    .agg({"issue_number": "count"})
    .reset_index()
    .rename(columns={"issue_number": "count"})
)

# Chart title
title = f"Github Project - {PROJECT_URL.split('/')[-2]} : {df_issues['project_name'].unique()[0]} <br><span style='font-size: 13px;'>Total closed issues: {closed_issues['count'].sum()}</span>"

# Hover labels
labels = {"issue_status": "Issue status", "count": "Number of Closed issues"}

fig = create_barchart(closed_issues, title, labels)

Plotting a bar graph for stale issues

stale_issues = []
for item in df_issues.stale_issue:
    if item != "None":
        stale_issues.append(int(item.split()[-2]) >= 7)
    else:
        stale_issues.append(False)

df_issues["stale_bool"] = stale_issues
temp = df_issues[df_issues["stale_bool"] == True]
temp[temp["issue_state"] == "open"]

# Dataframe
open_stale_issues = (
    temp[temp["issue_state"] == "open"]
    .groupby("issue_status")
    .agg({"stale_bool": "count"})
    .reset_index()
    .rename(columns={"stale_bool": "count"})
)

# Chart title
title = f"Github Project - {PROJECT_URL.split('/')[-2]} : {df_issues['project_name'].unique()[0]} <br><span style='font-size: 13px;'>Total open stale issues: {open_stale_issues['count'].sum()}</span>"

# Hover labels
labels = {
    "issue_status": "Issue status",
    "count": "Number of Open issues with no activity since more than 7 days",
}
fig = create_barchart(open_stale_issues, title, labels)