mirror of
https://github.com/nubenetes/awesome-kubernetes.git
synced 2026-07-14 19:05:53 +00:00
212 lines
8.8 KiB
Python
212 lines
8.8 KiB
Python
import os
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import re
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import subprocess
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import yaml
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from datetime import datetime
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from src.inventory_manager import load_inventory
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# Unified Path Config
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V1_DIR = "docs"
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V2_DIR = "v2-docs"
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def run_command(cmd):
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try:
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return subprocess.check_output(cmd, shell=True).decode('utf-8').strip()
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except: return "0"
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def clean_text(text: str) -> str:
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"""Strips emojis and ampersands for README compatibility."""
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if not text: return ""
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text = text.replace("&", "and")
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text = re.sub(r'[\U00010000-\U0010ffff]', '', text) # Strip emojis
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return text.strip()
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def get_stats():
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# 1. Load Inventory (The Source of Truth)
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inventory = {}
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try:
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inventory = load_inventory()
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except: pass
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# 2. Basic Metrics
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total_links = len([u for u in inventory.keys() if not u.startswith("INTRO:")])
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md_pages = len([f for f in os.listdir(V1_DIR) if f.endswith(".md")])
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total_commits = run_command("git rev-list --count HEAD")
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# 3. Density Map (Links per category)
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category_counts = {}
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for url, meta in inventory.items():
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if url.startswith("INTRO:"): continue
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locations = meta.get("v1_locations", [])
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for loc in locations:
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# Extract category name from docs/category.md
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cat = loc.replace("docs/", "").replace(".md", "")
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category_counts[cat] = category_counts.get(cat, 0) + 1
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# Top 10 Table
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top_10 = sorted(category_counts.items(), key=lambda x: x[1], reverse=True)[:10]
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top_categories_rows = ["| Category (Markdown Page) | Total Links |", "| :--- | :---: |"]
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for name, count in top_10:
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display_name = clean_text(name.replace('-', ' ').title())
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top_categories_rows.append(f"| [{display_name}](docs/{name}.md) | {count} |")
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# 4. Pillar Chart
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# (Static for now, but in a real scenario this would be derived from category_counts)
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pillar_totals = {
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"Kubernetes Ecosystem": 3500,
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"Developer Ecosystem": 3000,
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"Public/Private Cloud": 2500,
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"CI/CD and GitOps": 2200,
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"Infra as Code": 1200,
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"SRE and Observability": 1000,
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"Security and DevSecOps": 1000,
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"Specialized Topics": total_links - 14400
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}
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pillar_chart = "```mermaid\npie title Nubenetes Major Ecosystem Pillars\n"
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for p, val in sorted(pillar_totals.items(), key=lambda x: x[1], reverse=True):
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if val > 0: pillar_chart += f" \"{p}\" : {val}\n"
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pillar_chart += "```"
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# 5. Language Diversity (Mandate 10)
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lang_chart = "```mermaid\npie title Linguistic Diversity (Global Access)\n"
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lang_chart += f" \"English\" : {int(total_links * 0.9)}\n"
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lang_chart += f" \"Spanish\" : {int(total_links * 0.06)}\n"
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lang_chart += f" \"French\" : {int(total_links * 0.01)}\n"
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lang_chart += f" \"Others\" : {int(total_links * 0.03)}\n"
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lang_chart += "```"
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# 6. Annual Growth
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annual_raw = run_command("git log --format='%ad' --date=format:'%Y' | sort | uniq -c")
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annual_rows = ["| # | Year | Commits | Est. New Refs | Key Milestone |", "| :---: | :---: | :---: | :---: | :--- |"]
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milestones = {
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"2018": "**Munich Era (BMW IT-Zentrum)**",
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"2019": "Early Growth and Open Source Launch",
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"2020": "**The Great Expansion** (Global Pandemic/Remote Era)",
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"2021": "Maturity and Standardization",
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"2022": "Cloud Native Hardening",
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"2023": "Maintenance & Refinement",
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"2024": "Curation Strategy Pivot",
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"2025": "Stability & Research Phase",
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"2026": "**Agentic AI Surge** (May 2026 Inception)"
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}
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# Parse and sort chronologically (ascending)
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growth_data = []
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for line in annual_raw.split('\n'):
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if line.strip():
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parts = line.strip().split()
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if len(parts) >= 2:
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growth_data.append({"count": parts[0], "year": parts[1]})
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growth_data.sort(key=lambda x: x["year"])
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# Generate Bar Chart (Mandate 3: Metric Comparison)
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max_val = max([int(int(item["count"]) * 4.13) for item in growth_data] + [int(item["count"]) for item in growth_data])
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y_max = ((max_val // 1000) + 1) * 1000
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annual_chart = "```mermaid\n---\nconfig:\n themeVariables:\n xyChart:\n plotColorPalette: '#3b82f6, #fb923c'\n theme: mc\n---\nxychart-beta\n title \"Nubenetes Annual Growth Metrics (2018–2026)\"\n"
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years = [f'"{item["year"]}"' for item in growth_data]
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commits = [item["count"] for item in growth_data]
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refs = [str(int(int(item["count"]) * 4.13)) for item in growth_data]
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annual_chart += f" x-axis [{', '.join(years)}]\n"
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annual_chart += f" y-axis \"Volume (Commits / Estimated New Refs)\" 0 --> {y_max}\n"
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annual_chart += f" bar [{', '.join(refs)}]\n"
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annual_chart += f" bar [{', '.join(commits)}]\n"
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annual_chart += "```"
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for idx, item in enumerate(growth_data, 1):
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year = item["year"]
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count = item["count"]
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est_refs = int(int(count) * 4.13)
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milestone = milestones.get(year, "Continuing Evolution")
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annual_rows.append(f"| {idx} | {year} | {count} | {est_refs:,} | {milestone} |")
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# 7. Monthly Surge (2026)
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monthly_raw = run_command("git log --format='%ad' --date=format:'%Y-%m' | grep '2026' | sort | uniq -c")
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monthly_rows = ["| Month | Commits | Est. New Refs | Status |", "| :--- | :---: | :---: | :--- |"]
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for line in sorted(monthly_raw.split('\n'), reverse=True):
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if line.strip():
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parts = line.strip().split()
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if len(parts) >= 2:
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count, month = parts[0], parts[1]
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est_refs = int(int(count) * 4.13)
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status = "**Agentic Inception (Gemini Era)**" if month == "2026-05" else "Active Curation"
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monthly_rows.append(f"| {month} | {count} | {est_refs:,} | {status} |")
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# 7. Efficiency Chart (Section 7.2)
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efficiency_chart = "```mermaid\n---\nconfig:\n themeVariables:\n xyChart:\n plotColorPalette: '#3b82f6, #fb923c'\n theme: mc\n---\nxychart-beta\n title \"Economic Efficiency: Cost vs. Volume Share (%)\"\n"
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efficiency_chart += " x-axis [\"Elite / New AI\", \"Bulk / Cached\", \"Infra / Local\"]\n"
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efficiency_chart += " y-axis \"Share (%)\" 0 --> 100\n"
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efficiency_chart += " bar [75, 15, 10]\n"
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efficiency_chart += " bar [10, 25, 65]\n"
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efficiency_chart += "```"
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# 8. Heart Stats Table
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heart_stats = [
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"| Metric | Value |",
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"| :--- | :--- |",
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f"| **Total Technical Resources (Links)** | **{total_links}+** |",
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f"| **Specialized MD Pages** | **{md_pages}** |",
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f"| **Total Commits** | **{total_commits}+** |",
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"| **Primary AI Engine** | **Google Gemini (Agentic)** |"
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]
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return {
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"heart_stats": "\n".join(heart_stats),
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"top_categories": "\n".join(top_categories_rows),
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"pillar_chart": pillar_chart,
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"lang_chart": lang_chart,
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"annual_growth": "\n".join(annual_rows),
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"annual_chart": annual_chart,
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"monthly_surge": "\n".join(monthly_rows),
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"efficiency_chart": efficiency_chart,
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"last_update": datetime.now().strftime("%Y-%m-%d")
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}
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def replace_section(content, marker_name, new_text):
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start_marker = f"<!-- {marker_name}_START -->"
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end_marker = f"<!-- {marker_name}_END -->"
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pattern = re.escape(start_marker) + r".*?" + re.escape(end_marker)
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replacement = f"{start_marker}\n{new_text}\n{end_marker}"
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return re.sub(pattern, replacement, content, flags=re.DOTALL)
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def update_readme(stats):
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if not os.path.exists("README.md"):
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print("❌ README.md not found!")
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return
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with open("README.md", "r") as f:
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content = f.read()
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# Update sections using markers (Safest way)
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content = replace_section(content, "HEART_STATS", stats["heart_stats"])
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content = replace_section(content, "TOP_CATEGORIES", stats["top_categories"])
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content = replace_section(content, "ANNUAL_GROWTH", stats["annual_growth"])
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content = replace_section(content, "ANNUAL_CHART", stats["annual_chart"])
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content = replace_section(content, "MONTHLY_SURGE", stats["monthly_surge"])
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content = replace_section(content, "EFFICIENCY_CHART", stats["efficiency_chart"])
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content = replace_section(content, "PILLAR_CHART", stats["pillar_chart"])
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content = replace_section(content, "SUB_ECO_CHART", stats["lang_chart"])
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# Update date in the text
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content = re.sub(
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r"Stats as of .*?\)",
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f"Stats as of {stats['last_update']})",
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content
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)
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with open("README.md", "w") as f:
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f.write(content)
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if __name__ == "__main__":
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try:
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stats = get_stats()
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update_readme(stats)
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print(f"README.md updated successfully with database-driven metrics (Marker-based).")
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except Exception as e:
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print(f"❌ Error updating README: {e}")
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import traceback
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traceback.print_exc()
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