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feat(stargazer-map): readable log-scale map with baked-in stats (#2953)
* feat(stargazer-map): readable log-scale map with baked-in stats Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> * fix(stargazer-map): count only current stargazers, honest caption wording Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> * refactor(stargazer-map): show shares only, drop absolute per-country counts Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 5 <noreply@anthropic.com>
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Alexandre
268
.github/generate_map.py
vendored
268
.github/generate_map.py
vendored
@@ -7,13 +7,14 @@ up once (unless the country entry is blank).
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"""
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import csv
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import math
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import os
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import sys
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import time
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from collections import Counter
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from pathlib import Path
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import plotly.express as px
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import plotly.graph_objects as go
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import pycountry
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import requests
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from geopy.geocoders import Nominatim
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@@ -25,6 +26,35 @@ GITHUB_TOKEN = os.getenv("GITHUB_TOKEN") # provided by workflow
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CSV_PATH = Path(".github/stargazer_countries.csv")
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PNG_PATH = Path(".github/stargazer_map.png")
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# ---- Rendering theme --------------------------------------------------------
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# Dark, opaque panel: GitHub does not swap the image between README themes, so
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# a single background has to work in both. A dark canvas with a bright
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# sequential ramp stays readable on light and dark pages alike.
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BG = "#0d1117" # page / ocean
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LAND = "#2b323c" # countries with zero stargazers (still visible)
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BORDER = "#0d1117" # country outlines, same as background
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FG = "#e6edf3" # primary text
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MUTED = "#8b98a5" # secondary text
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# Viridis truncated at 35 %: even a single stargazer gets a colour that is
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# clearly distinct from the empty-land grey.
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SCALE = ["#2c728e", "#21918c", "#35b779", "#90d743", "#fde725"]
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# pycountry names that are too long / too formal for a top-5 list
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SHORT_NAMES = {
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"Russian Federation": "Russia",
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"Korea, Republic of": "South Korea",
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"Korea, Democratic People's Republic of": "North Korea",
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"Iran, Islamic Republic of": "Iran",
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"Taiwan, Province of China": "Taiwan",
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"Viet Nam": "Vietnam",
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"Moldova, Republic of": "Moldova",
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"Bolivia, Plurinational State of": "Bolivia",
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"Venezuela, Bolivarian Republic of": "Venezuela",
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"Tanzania, United Republic of": "Tanzania",
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"Syrian Arab Republic": "Syria",
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}
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HEADERS = {
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"Authorization": f"token {GITHUB_TOKEN}",
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"Accept": "application/vnd.github.v3+json",
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@@ -92,30 +122,207 @@ def username_to_country(login):
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return ""
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def build_choropleth(percent_by_iso):
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iso, vals = zip(*percent_by_iso.items())
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fig = px.choropleth(
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locations=list(iso),
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locationmode="ISO-3",
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color=list(vals),
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color_continuous_scale="Greens",
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range_color=(0, max(vals) if vals else 1),
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def count_by_country(cache):
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"""Counter of country name -> stargazers, ignoring blank locations."""
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return Counter(c for c in cache.values() if c)
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def _log_ticks(lo, hi):
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"""Colourbar ticks at ... 0.1, 0.3, 1, 3, 10, 30 ... spanning [lo, hi]."""
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candidates = [m * 10**k for k in range(-3, 3) for m in (1, 3)]
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ticks = [t for t in candidates if lo / 1.5 <= t <= hi]
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return ticks or [hi]
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def _fmt_pct(value):
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"""1 -> '1%', 0.3 -> '0.3%' -- no trailing zeros."""
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return f"{value:.2f}".rstrip("0").rstrip(".") + "%"
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def build_figure(counts, total_stargazers):
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"""Build the choropleth figure from a {country name: stargazers} mapping."""
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by_iso = {}
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for name, n in counts.items():
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try:
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code = pycountry.countries.lookup(name).alpha_3
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except LookupError:
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print("Skip unknown country:", name)
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continue
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# two spellings can resolve to the same ISO code, so accumulate
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by_iso[code] = by_iso.get(code, 0) + n
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iso = list(by_iso)
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vals = [by_iso[k] for k in iso]
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# count only what is actually drawn, so the caption matches the map
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located = sum(vals) or 1
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pcts = [v / located * 100 for v in vals]
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lo, hi = (min(pcts), max(pcts)) if pcts else (1.0, 1.0)
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# The distribution is heavily long-tailed (the top country holds ~200x the
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# share of the tail), so a linear ramp collapses everything but a handful
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# of countries into the first colour step. Colour on log10 of the share.
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ticks = _log_ticks(lo, hi)
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fig = go.Figure(
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go.Choropleth(
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locations=iso,
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locationmode="ISO-3",
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z=[math.log10(p) for p in pcts],
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zmin=math.log10(lo) - 0.15, # keep the smallest share off the floor
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zmax=math.log10(hi),
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colorscale=SCALE,
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marker_line_color=BORDER,
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marker_line_width=0.5,
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colorbar=dict(
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title=dict(
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text="share of located stargazers (log scale)",
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font=dict(color=MUTED, size=13),
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side="top",
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),
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orientation="h",
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x=0.52,
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y=0.02,
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xanchor="center",
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yanchor="bottom",
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thickness=12,
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len=0.34,
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outlinewidth=0,
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tickvals=[math.log10(t) for t in ticks],
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ticktext=[_fmt_pct(t) for t in ticks],
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tickfont=dict(color=MUTED, size=12),
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),
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)
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)
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fig.update_layout(
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coloraxis_colorbar=dict(
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title="% stargazers",
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orientation="h", # <-- échelle horizontale
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x=0.5, # <-- centré
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y=0, # <-- tout en bas
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xanchor="center",
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yanchor="bottom",
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thickness=15,
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len=0.7, # <-- longueur de l'échelle, ajustable
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fig.update_geos(
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projection_type="natural earth",
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showframe=False,
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showcoastlines=False,
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showland=True,
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landcolor=LAND,
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showocean=True,
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oceancolor=BG,
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showlakes=False,
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bgcolor=BG,
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lataxis_range=[-56, 84], # crop Antarctica, it is always empty
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lonaxis_range=[-176, 186],
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domain=dict(x=[0.0, 1.0], y=[0.04, 0.92]),
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)
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repo = REPO or "this repository"
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caption = (
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f"{total_stargazers:,} stargazers"
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f" | {located:,} mapped to a country"
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f" | {len(by_iso)} countries"
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)
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annotations = [
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dict(
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text=f"<b>Stargazers of {repo}</b>",
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x=0.012,
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y=0.985,
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xref="paper",
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yref="paper",
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xanchor="left",
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yanchor="top",
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showarrow=False,
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font=dict(color=FG, size=25),
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),
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dict(
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text=caption,
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x=0.012,
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y=0.925,
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xref="paper",
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yref="paper",
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xanchor="left",
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yanchor="top",
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showarrow=False,
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font=dict(color=MUTED, size=15),
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),
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dict(
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text="Countries in grey have no located stargazer.<br>"
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"Location is read from the public GitHub profile,<br>"
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"so the map covers the located subset only.",
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x=0.988,
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y=0.05,
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xref="paper",
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yref="paper",
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xanchor="right",
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yanchor="bottom",
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align="right",
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showarrow=False,
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font=dict(color=MUTED, size=12),
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),
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]
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# Top 5, laid out as two separate annotations (names, share) so each column
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# stays aligned whatever the country name length -- HTML text in an SVG
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# annotation collapses padding spaces, so a monospace table would not line
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# up.
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top = counts.most_common(5)
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if top:
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base_y = 0.40
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columns = [
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(
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0.022,
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"left",
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"<br>".join(
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f"{i}. {SHORT_NAMES.get(name, name)}"
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for i, (name, _) in enumerate(top, 1)
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),
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FG,
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),
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(
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0.215,
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"right",
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"<br>".join(f"{n / located * 100:.1f}%" for _, n in top),
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FG,
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),
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]
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annotations.append(
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dict(
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text="<b>TOP COUNTRIES</b>",
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x=0.022,
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y=base_y,
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xref="paper",
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yref="paper",
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xanchor="left",
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yanchor="top",
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showarrow=False,
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font=dict(color=MUTED, size=13),
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)
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)
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annotations += [
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dict(
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text=text,
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x=x,
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y=base_y - 0.055,
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xref="paper",
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yref="paper",
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xanchor=anchor,
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yanchor="top",
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align=anchor,
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showarrow=False,
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font=dict(color=color, size=15),
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)
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for x, anchor, text, color in columns
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]
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fig.update_layout(
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width=1240,
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height=680,
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paper_bgcolor=BG,
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plot_bgcolor=BG,
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margin=dict(l=0, r=0, t=0, b=0),
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annotations=annotations,
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)
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PNG_PATH.parent.mkdir(parents=True, exist_ok=True)
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fig.write_image(str(PNG_PATH), scale=2)
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return fig
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def build_choropleth(counts, total_stargazers, path=PNG_PATH):
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fig = build_figure(counts, total_stargazers)
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path.parent.mkdir(parents=True, exist_ok=True)
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# 1.5x of 1240x680 -> 1860x1020, sharp on HiDPI at README width without
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# committing a multi-megabyte PNG every week.
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fig.write_image(str(path), scale=1.5)
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def main():
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@@ -145,23 +352,12 @@ def main():
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save_cache(cache)
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# Build stats
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countries = [c for c in cache.values() if c]
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counts = Counter(countries)
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total = sum(counts.values()) or 1
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pct_by_country = {c: v / total for c, v in counts.items()}
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# convert to ISO-3 for plotly
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pct_by_iso = {}
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for c, pct in pct_by_country.items():
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try:
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iso = pycountry.countries.lookup(c).alpha_3
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pct_by_iso[iso] = pct * 100 # plotly wants numeric
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except LookupError:
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print("Skip unknown country:", c)
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# The cache is never pruned, so it still holds users who have since
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# unstarred. Keep them for future geocoding, but render only current stars.
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counts = count_by_country({u: cache[u] for u in users})
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print("Rendering PNG map…")
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build_choropleth(pct_by_iso)
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build_choropleth(counts, len(users))
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print(
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"Done – files saved:",
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CSV_PATH.relative_to("."),
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