GitHub_Follow_stargazers_trend.ipynb

Kernel: Python 3

GitHub - Follow stargazers trend

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Tags: #github #stars #stargazers #naas_drivers #operations #analytics #html #plotly #csv #image #png

Author: Sanjeet Attili

Last update: 2023-04-12 (Created: 2023-03-24)

Description: This notebook creates a linechart to follow the trend of stars received on a specific repository. A csv, html and png files will be created as output with the possibility to be shared with a naas asset link.

References:

• GitHub - List Stargazers

• Naas drivers - GitHub

Input

Imports

import pandas as pd
from datetime import datetime
import plotly.graph_objects as go
from naas_drivers import github
import naas

Setup Variables

Create your GitHub personal access token

• token: GitHub personal access token

• repo_url: URL of the GitHub repository

• name_output: By default, we will use the repository name

• csv_output: By default, we will use the repository name + .csv extension

• html_output: By default, we will use the repository name + .html extension

• image_output: By default, we will use the repository name + .png extension

# Inputs
token = naas.secret.get("GITHUB_TOKEN") or "YOUR_GITHUB_TOKEN"
repo_url = "https://github.com/jupyter-naas/awesome-notebooks"

# Outputs
name_output = repo_url.split("/")[-1]
csv_output = f"{name_output}.csv"
html_output = f"{name_output}.html"
image_output = f"{name_output}.png"

Model

Get stargazers

df = github.connect(token).repos.get_stargazers(repo_url)
print('Row fetched:', len(df))
df.tail(3)

Get trend

def get_trend(df, date_col_name="STARRED_AT", value_col_name="ID", date_order="asc"):

    # Format date
    df[date_col_name] = pd.to_datetime(df[date_col_name]).dt.strftime("%Y-%m-%d")
    df = df.groupby(date_col_name, as_index=False).agg({value_col_name: "count"})
    d = datetime.now().date()
    d2 = df.loc[df.index[0], date_col_name]
    idx = pd.date_range(d2, d, freq="D")

    df.set_index(date_col_name, drop=True, inplace=True)
    df.index = pd.DatetimeIndex(df.index)
    df = df.reindex(idx, fill_value=0)
    df[date_col_name] = pd.DatetimeIndex(df.index)

    # Calc sum cum
    df["value_cum"] = df.agg({value_col_name: "cumsum"})
    return df.reset_index(drop=True)


df_trend = get_trend(df)
df_trend.tail(1)

Plotting a line chart to get trend

def create_linechart(df, date, value, repo_url):
    # Get repo name
    repo_name = repo_url.split("https://github.com/")[-1].split("/")[-1]

    # Get last value
    last_value = df.loc[df.index[-1], value]

    # Init
    fig = go.Figure()

    # Create fig
    fig.add_trace(
        go.Scatter(
            x=df[date].to_list(),
            y=df[value].to_list(),
            mode="lines+text",
            line=dict(color="black"),
        )
    )
    fig.update_traces(marker_color="black")
    fig.update_layout(
        title=f"⭐<b> Stars - {repo_name}</b><br><span style='font-size: 13px;'>Total stars as of today: {last_value}</span>",
        title_font=dict(family="Arial", size=18, color="black"),
        plot_bgcolor="#ffffff",
        width=1200,
        height=800,
        paper_bgcolor="white",
        xaxis_title="Date",
        xaxis_title_font=dict(family="Arial", size=11, color="black"),
        yaxis_title="No. of stars",
        yaxis_title_font=dict(family="Arial", size=11, color="black"),
        margin_pad=10,
    )
    fig.show()
    return fig


fig = create_linechart(df_trend, "STARRED_AT", "value_cum", repo_url)

Output

Save and share your csv file

# Save your dataframe in CSV
df_trend.to_csv(csv_output, index=False)

# Share output with naas
naas.asset.add(csv_output)

# -> Uncomment the line below to remove your asset
# naas.asset.delete(csv_output)

Save and share your graph in HTML

# Save your graph in HTML
fig.write_html(html_output)

# Share output with naas
naas.asset.add(html_output, params={"inline": True})

# -> Uncomment the line below to remove your asset
# naas.asset.delete(html_output)

Save and share your graph in image

# Save your graph in PNG
fig.write_image(image_output)

# Share output with naas
naas.asset.add(image_output, params={"inline": True})

# -> Uncomment the line below to remove your asset
# naas.asset.delete(image_output)