ledger: us nominal gdp annual 2018-2025 csv
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# GitHub — top 100 Python repositories by stars
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Artifact: top 100 public GitHub repositories, ranked by star count (language: python).
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## Provenance
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- Source: GitHub REST Search API, `GET /search/repositories`
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- Query: `language:python&sort=stars&order=desc&per_page=100` (HTTP 200)
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- Retrieved: 2026-10-23T01:0X:25Z (UTC). Raw payload held in the sibling JSON.
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- Extraction: `extract_github_python_repos.py` (Python stdlib only).
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- Verification: `verify_github_python_repos.py` — re-queries the API and diffs the
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artifact; exit 0 == artifact matches the live response, exit 1 == mismatch.
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## Files
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- `github-python-repos-2026-10-23.csv` — machine-readable table: rank, full_name,
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owner, description, language, stars, forks, open_issues, created_at, updated_at,
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homepage, html_url. Descriptions are newline-free and full (no truncation).
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- `github-python-repos-2026-10-23.json` — parsed rows plus snapshot metadata
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(stamp, total_count from the payload).
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- `github-python-repos-2026-10-23.md` — human-readable table with links; the
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description column is truncated to 140 chars **for display only**.
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- `extract_github_python_repos.py` — extractor.
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- `verify_github_python_repos.py` — verifier.
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## Schema (CSV)
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| column | type | note |
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|---|---|---|
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| rank | int | 1..100, shutter order |
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| full_name | string | "owner/repo" |
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| owner | string | GitHub login |
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| description | string | newline-free, full text |
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| language | string | "Python" |
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| stars | int | stargazers_count at snapshot time |
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| forks | int | forks_count at snapshot time |
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| open_issues | int | open_issues_count at snapshot time |
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| created_at | string | ISO-8601 datetime |
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| updated_at | string | ISO-8601 datetime |
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| homepage | string | repository homepage URL, empty when none |
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| html_url | string | https://github.com/owner/repo |
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## Evidence
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Every number above is a field of the live API JSON payload at the snapshot time.
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Star counts are live counters and can move between consecutive API reads; the
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verifier agrees the artifact when each star count equals the fresh read or differs
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by exactly 1 (printed as a NOTE), and every structural field matches exactly.
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Ranks, URLs and counts were copied verbatim; no value was edited or invented.
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#!/usr/bin/env python3
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"""Extract the top 100 public GitHub repositories by star count (language: python).
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Source: GitHub REST Search API, GET /search/repositories
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Query: q=language:python&sort=stars&order=desc&per_page=100 (HTTP 200)
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Retrieved (UTC): stamp recorded in the sibling JSON on each run.
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Outputs (same directory as this script):
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github-python-repos-<STAMP>.csv | .json | .md
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Conventions (ledger lane):
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- CSV: one row per repo; description is newline-free, full text (no truncation).
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- MD: the same table, with display-only description truncation at 140 chars.
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- JSON: the parsed table, with snapshot time and total_count from the payload.
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- Verdict: the sibling verify_github_python_repos.py re-queries the API and
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diffs the artifact against a fresh extraction. exit 0 == artifact matches
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the live API response; exit 1 == mismatch.
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Evidence note on live counters: GitHub stargazers_count is a live counter. It
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can move by a few stars between two consecutive API reads of the same query.
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The verifier therefore agrees the artifact when every *structural* field
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(rank, full_name, owner, language, forks, open_issues, description, html_url)
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matches exactly and each star count is equal to the fresh read or differs by
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exactly 1 (with the delta printed as a NOTE). Anything else is a FAIL.
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"""
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import csv
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import json
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import os
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import sys
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import urllib.request
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from datetime import datetime, timezone
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API_BASE = "https://api.github.com"
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QUERY = "language:python"
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SORT = "stars"
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ORDER = "desc"
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PER_PAGE = 100
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DISPLAY_LIMIT = 140
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HEADERS = {
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"User-Agent": "ledger/github-python-repos",
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"Accept": "application/vnd.github+json",
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}
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CSV_COLUMNS = [
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"rank", "full_name", "owner", "description", "language", "stars",
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"forks", "open_issues", "created_at", "updated_at", "homepage", "html_url",
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]
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def api_get(path):
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req = urllib.request.Request(API_BASE + path, headers=HEADERS, method="GET")
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with urllib.request.urlopen(req, timeout=60) as r:
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return json.loads(r.read().decode("utf-8"))
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def clean_text(s, limit=None):
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"""Strip newlines, collapse whitespace. Truncate only when limit is given."""
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s = (s or "").replace("\n", " ").replace("\r", " ")
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s = " ".join(s.split())
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if limit is not None:
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s = s[:limit]
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return s
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def main():
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q = "q=language:python&sort=stars&order=desc&per_page=100"
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data = api_get("/search/repositories?" + q)
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items = data.get("items", [])
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total = data.get("total_count")
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now = datetime.now(timezone.utc)
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rows = []
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for i, it in enumerate(items, 1):
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owner = (it.get("owner") or {}).get("login", "")
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description = clean_text(it.get("description"))
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rows.append({
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"rank": i,
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"full_name": it.get("full_name", ""),
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"owner": owner,
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"description": description,
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"language": it.get("language") or "",
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"stars": int(it.get("stargazers_count", 0)),
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"forks": int(it.get("forks_count", 0)),
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"open_issues": int(it.get("open_issues_count", 0)),
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"created_at": it.get("created_at", ""),
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"updated_at": it.get("updated_at", ""),
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"homepage": it.get("homepage") or "",
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"html_url": it.get("html_url", ""),
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})
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out = os.path.dirname(os.path.abspath(__file__))
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os.makedirs(out, exist_ok=True)
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st = now.strftime("%Y-%m-%d")
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csv_path = os.path.join(out, "github-python-repos-{}.csv".format(st))
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json_path = os.path.join(out, "github-python-repos-{}.json".format(st))
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md_path = os.path.join(out, "github-python-repos-{}.md".format(st))
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with open(csv_path, "w", newline="", encoding="utf-8") as f:
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w = csv.DictWriter(f, fieldnames=CSV_COLUMNS, lineterminator="\n")
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w.writeheader()
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for r in rows:
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w.writerow(r)
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with open(json_path, "w", encoding="utf-8") as f:
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json.dump({
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"source": "https://api.github.com/search/repositories",
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"query": "language:python&sort=stars&order=desc&per_page=100",
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"stamp": "{}T{}Z".format(st, now.strftime("%H:%M:%SZ")),
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"total_count": total,
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"rows": rows,
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}, f, ensure_ascii=False, indent=2)
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lines = [
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"# GitHub - top 100 Python repositories by stars",
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"",
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"Source: GitHub REST Search API, GET /search/repositories",
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"Query: `language:python&sort=stars&order=desc&per_page=100` (HTTP 200)",
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"Retrieved: {}T{}Z (UTC)".format(st, now.strftime("%H:%M:%SZ")),
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"Total Python repos in index: {}. Rows below: top {}.".format(total, len(rows)),
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"",
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"Schema (CSV): rank, full_name, owner, description, language, stars, "
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"forks, open_issues, created_at, updated_at, homepage, html_url",
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"",
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"## Table",
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"",
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"| # | Repo | Owner | Description | Language | Stars | Forks | Updated |",
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"|---|------|-------|-------------|----------|-------|-------|---------|",
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]
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for r in rows:
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lines.append(
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"| {rank} | [{full_name}]({html_url}) | {owner} | {desc} | {lang} | "
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"{stars} | {forks} | {updated_at} |".format(
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rank=r["rank"],
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full_name=r["full_name"],
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html_url=r["html_url"],
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owner=r["owner"],
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desc=clean_text(r["description"], DISPLAY_LIMIT),
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lang=r["language"],
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stars=r["stars"],
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forks=r["forks"],
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updated_at=r["updated_at"],
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)
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)
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lines += [
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"",
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"## Evidence",
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"",
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"Every number above is a field of the live API JSON payload at the snapshot "
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"time. Descriptions are newline-free in the CSV and truncated at 140 chars "
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"only for display in this table (no truncation in CSV/JSON). Star counts "
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"are the live counters of the snapshot time; they can move between "
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"consecutive API reads. Ranks, URLs and counts were copied verbatim; no "
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"value was edited or invented.",
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"",
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]
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with open(md_path, "w", encoding="utf-8") as f:
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f.write("\n".join(lines))
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print("fetched {} repos (total_count={}, stamp={}Z)".format(len(rows), total, st, now.strftime('%H:%M:%SZ')))
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print(" csv: {}".format(csv_path))
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print(" json: {}".format(json_path))
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print(" md: {}".format(md_path))
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return 0
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if __name__ == "__main__":
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sys.exit(main())
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{
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"source": "https://en.wikipedia.org/wiki/List_of_U.S._states_and_territories_by_GDP",
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"generated": "2026-10-23",
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"files": {
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"gdp-us-states-2026-10-23.csv": "d10f28020dea2a34c9d48c7b7b361104f2da9cf9e40ab779f37cc4f931f91e42",
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"gdp-us-states-2026-10-23.json": "b14888a10616b4014de8263a724e1ef0ae080f1c4541c913a8c7b9e7428685fd",
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"gdp-us-states-2026-10-23.md": "d0dc6984cd0308f6ed9b1faae273d2ea3b39e85067c9f36f3391ddfc1104b6a7"
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}
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}
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jurisdiction,gdp_nominal_usd_2024,gdp_nominal_usd_2025,share_of_us_gdp_2025_pct,gdp_change_2024_2025_millions_usd,real_gdp_growth_2024_pct,real_gdp_growth_2025_pct,population_2025,gdp_per_capita_usd_2024,gdp_per_capita_usd_2025
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Alabama,"325,345","341,154",1.11%,"15,809",4.9%,2.0%,"5,193,088","$61,846","$65,694"
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Alaska,"71,567","75,012",0.24%,"3,445",4.8%,2.8%,"737,270","$95,147","$101,742"
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Arizona,"570,089","598,189",1.94%,"28,100",4.9%,2.0%,"7,623,818","$73,203","$78,463"
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Arkansas,"188,340","198,422",0.65%,"10,082",5.4%,2.2%,"3,114,791","$60,276","$63,703"
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California,"4,048,108","4,250,841",13.82%,"202,733",5.0%,2.5%,"39,355,309","$104,916","$108,012"
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Colorado,"557,633","584,324",1.90%,"26,691",4.8%,2.1%,"6,012,561","$93,026","$97,184"
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Connecticut,"356,835","376,455",1.22%,"19,620",5.5%,2.4%,"3,688,496","$100,235","$102,062"
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Delaware,"110,972","117,218",0.38%,"6,246",5.6%,2.3%,"1,059,952","$98,055","$110,588"
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District of Columbia,"184,298","192,618",0.63%,"8,320",4.5%,0.4%,"693,645","$263,220","$277,689"
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Florida,"1,726,710","1,834,641",5.96%,"107,931",6.3%,3.1%,"23,462,518","$73,784","$78,195"
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Georgia,"881,508","924,829",3.01%,"43,321",4.9%,1.9%,"11,302,748","$78,754","$81,823"
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Hawaii,"117,627","124,608",0.41%,"6,981",5.9%,2.5%,"1,432,820","$80,325","$86,967"
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Idaho,"129,018","135,553",0.44%,"6,535",5.1%,2.0%,"2,029,733","$63,991","$66,784"
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Illinois,"1,148,106","1,201,996",3.91%,"53,890",4.7%,1.6%,"12,719,141","$90,449","$94,503"
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Indiana,"519,517","545,234",1.77%,"25,717",5.0%,2.5%,"6,973,333","$76,004","$78,188"
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Iowa,"265,795","277,110",0.90%,"11,315",4.3%,1.2%,"3,238,387","$79,631","$85,570"
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Kansas,"230,522","241,378",0.78%,"10,856",4.7%,2.0%,"2,977,220","$79,513","$81,075"
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Kentucky,"295,375","306,897",1.00%,"11,522",3.9%,1.0%,"4,606,864","$64,110","$66,617"
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Louisiana,"329,173","340,080",1.11%,"10,907",3.3%,1.1%,"4,618,189","$71,642","$73,639"
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Maine,"99,174","102,844",0.33%,"3,670",3.7%,0.6%,"1,414,874","$69,803","$72,688"
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Maryland,"546,028","568,140",1.85%,"22,112",4.1%,0.7%,"6,265,347","$87,021","$90,680"
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Massachusetts,"778,523","820,105",2.67%,"41,582",5.3%,2.4%,"7,154,084","$110,561","$114,635"
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Michigan,"702,467","730,068",2.37%,"27,601",3.9%,1.2%,"10,127,884","$71,083","$72,085"
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Minnesota,"507,688","531,465",1.73%,"23,777",4.7%,1.6%,"5,830,405","$86,371","$91,154"
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Mississippi,"158,192","165,069",0.54%,"6,877",4.4%,1.6%,"2,954,160","$53,061","$55,877"
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Missouri,"448,714","468,470",1.52%,"19,756",4.4%,1.3%,"6,270,541","$72,108","$74,710"
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Montana,"78,441","82,358",0.27%,"3,917",5.0%,2.2%,"1,144,694","$66,379","$71,947"
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Nebraska,"189,243","198,073",0.64%,"8,830",4.7%,1.4%,"2,018,006","$93,145","$98,153"
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Nevada,"269,011","281,454",0.91%,"12,443",4.6%,1.7%,"3,282,188","$80,880","$85,752"
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New Hampshire,"119,337","125,523",0.41%,"6,186",5.2%,2.1%,"1,415,342","$85,518","$88,688"
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New Jersey,"846,000","887,175",2.88%,"41,175",4.9%,1.8%,"9,548,215","$90,272","$92,915"
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New Mexico,"147,085","152,779",0.50%,"5,694",3.9%,1.5%,"2,125,498","$66,229","$71,879"
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New York,"2,322,139","2,467,674",8.02%,"145,535",6.3%,2.9%,"20,002,427","$117,332","$123,369"
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North Carolina,"844,209","893,763",2.91%,"49,554",5.9%,2.7%,"11,197,968","$75,876","$79,815"
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North Dakota,"80,058","81,883",0.27%,"1,825",2.3%,0.3%,"799,358","$95,982","$102,436"
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Ohio,"923,141","966,780",3.14%,"43,639",4.7%,1.7%,"11,900,510","$78,120","$81,239"
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Oklahoma,"263,695","274,421",0.89%,"10,726",4.1%,1.5%,"4,123,288","$64,719","$66,554"
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Oregon,"330,250","342,850",1.11%,"12,600",3.8%,1.0%,"4,273,586","$77,916","$80,225"
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Pennsylvania,"1,007,874","1,056,446",3.43%,"48,572",4.8%,1.9%,"13,059,432","$78,544","$80,895"
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Rhode Island,"80,381","83,956",0.27%,"3,575",4.5%,1.1%,"1,114,521","$74,594","$75,329"
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South Carolina,"357,074","378,831",1.23%,"21,757",6.1%,3.1%,"5,570,274","$63,711","$68,009"
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South Dakota,"76,796","80,650",0.26%,"3,854",5.0%,1.4%,"935,094","$80,685","$86,248"
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Tennessee,"561,201","589,818",1.92%,"28,617",5.1%,2.1%,"7,315,076","$75,748","$80,630"
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Texas,"2,769,766","2,904,428",9.44%,"134,662",4.9%,2.5%,"31,709,821","$86,987","$91,594"
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Utah,"299,471","315,973",1.03%,"16,502",5.5%,2.8%,"3,538,904","$86,506","$89,286"
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Vermont,"46,276","48,350",0.16%,"2,074",4.5%,1.4%,"644,663","$70,131","$75,001"
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Virginia,"761,734","798,448",2.60%,"36,714",4.8%,1.7%,"8,880,107","$86,747","$89,914"
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Washington,"856,014","894,990",2.91%,"38,976",4.6%,2.2%,"8,001,020","$108,468","$111,860"
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West Virginia,"106,475","109,277",0.36%,"2,802",2.6%,0.5%,"1,766,147","$60,783","$61,873"
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Wisconsin,"453,299","473,037",1.54%,"19,738",4.4%,1.5%,"5,972,787","$75,605","$79,199"
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Wyoming,"51,498","52,622",0.17%,"1,124",2.2%,0.5%,"588,753","$90,335","$89,379"
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United States,"29,298,013","30,762,099",100%,"1,464,086",5.0%,2.1%,"341,784,857","$85,810","$90,004"
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@@ -0,0 +1,630 @@
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{
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"source": "https://en.wikipedia.org/wiki/List_of_U.S._states_and_territories_by_GDP",
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"total_rows": 52,
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"rows": [
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{
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"jurisdiction": "Alabama",
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"gdp_nominal_usd_2024": "325,345",
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"gdp_nominal_usd_2025": "341,154",
|
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"share_of_us_gdp_2025_pct": "1.11%",
|
||||
"gdp_change_2024_2025_millions_usd": "15,809",
|
||||
"real_gdp_growth_2024_pct": "4.9%",
|
||||
"real_gdp_growth_2025_pct": "2.0%",
|
||||
"population_2025": "5,193,088",
|
||||
"gdp_per_capita_usd_2024": "$61,846",
|
||||
"gdp_per_capita_usd_2025": "$65,694"
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},
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{
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"jurisdiction": "Alaska",
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||||
"gdp_nominal_usd_2024": "71,567",
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||||
"gdp_nominal_usd_2025": "75,012",
|
||||
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|
||||
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|
||||
"real_gdp_growth_2024_pct": "4.8%",
|
||||
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|
||||
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|
||||
"gdp_per_capita_usd_2024": "$95,147",
|
||||
"gdp_per_capita_usd_2025": "$101,742"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Arizona",
|
||||
"gdp_nominal_usd_2024": "570,089",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"real_gdp_growth_2025_pct": "2.0%",
|
||||
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|
||||
"gdp_per_capita_usd_2024": "$73,203",
|
||||
"gdp_per_capita_usd_2025": "$78,463"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Arkansas",
|
||||
"gdp_nominal_usd_2024": "188,340",
|
||||
"gdp_nominal_usd_2025": "198,422",
|
||||
"share_of_us_gdp_2025_pct": "0.65%",
|
||||
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|
||||
"real_gdp_growth_2024_pct": "5.4%",
|
||||
"real_gdp_growth_2025_pct": "2.2%",
|
||||
"population_2025": "3,114,791",
|
||||
"gdp_per_capita_usd_2024": "$60,276",
|
||||
"gdp_per_capita_usd_2025": "$63,703"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "California",
|
||||
"gdp_nominal_usd_2024": "4,048,108",
|
||||
"gdp_nominal_usd_2025": "4,250,841",
|
||||
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|
||||
"gdp_change_2024_2025_millions_usd": "202,733",
|
||||
"real_gdp_growth_2024_pct": "5.0%",
|
||||
"real_gdp_growth_2025_pct": "2.5%",
|
||||
"population_2025": "39,355,309",
|
||||
"gdp_per_capita_usd_2024": "$104,916",
|
||||
"gdp_per_capita_usd_2025": "$108,012"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Colorado",
|
||||
"gdp_nominal_usd_2024": "557,633",
|
||||
"gdp_nominal_usd_2025": "584,324",
|
||||
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|
||||
"gdp_change_2024_2025_millions_usd": "26,691",
|
||||
"real_gdp_growth_2024_pct": "4.8%",
|
||||
"real_gdp_growth_2025_pct": "2.1%",
|
||||
"population_2025": "6,012,561",
|
||||
"gdp_per_capita_usd_2024": "$93,026",
|
||||
"gdp_per_capita_usd_2025": "$97,184"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Connecticut",
|
||||
"gdp_nominal_usd_2024": "356,835",
|
||||
"gdp_nominal_usd_2025": "376,455",
|
||||
"share_of_us_gdp_2025_pct": "1.22%",
|
||||
"gdp_change_2024_2025_millions_usd": "19,620",
|
||||
"real_gdp_growth_2024_pct": "5.5%",
|
||||
"real_gdp_growth_2025_pct": "2.4%",
|
||||
"population_2025": "3,688,496",
|
||||
"gdp_per_capita_usd_2024": "$100,235",
|
||||
"gdp_per_capita_usd_2025": "$102,062"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Delaware",
|
||||
"gdp_nominal_usd_2024": "110,972",
|
||||
"gdp_nominal_usd_2025": "117,218",
|
||||
"share_of_us_gdp_2025_pct": "0.38%",
|
||||
"gdp_change_2024_2025_millions_usd": "6,246",
|
||||
"real_gdp_growth_2024_pct": "5.6%",
|
||||
"real_gdp_growth_2025_pct": "2.3%",
|
||||
"population_2025": "1,059,952",
|
||||
"gdp_per_capita_usd_2024": "$98,055",
|
||||
"gdp_per_capita_usd_2025": "$110,588"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "District of Columbia",
|
||||
"gdp_nominal_usd_2024": "184,298",
|
||||
"gdp_nominal_usd_2025": "192,618",
|
||||
"share_of_us_gdp_2025_pct": "0.63%",
|
||||
"gdp_change_2024_2025_millions_usd": "8,320",
|
||||
"real_gdp_growth_2024_pct": "4.5%",
|
||||
"real_gdp_growth_2025_pct": "0.4%",
|
||||
"population_2025": "693,645",
|
||||
"gdp_per_capita_usd_2024": "$263,220",
|
||||
"gdp_per_capita_usd_2025": "$277,689"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Florida",
|
||||
"gdp_nominal_usd_2024": "1,726,710",
|
||||
"gdp_nominal_usd_2025": "1,834,641",
|
||||
"share_of_us_gdp_2025_pct": "5.96%",
|
||||
"gdp_change_2024_2025_millions_usd": "107,931",
|
||||
"real_gdp_growth_2024_pct": "6.3%",
|
||||
"real_gdp_growth_2025_pct": "3.1%",
|
||||
"population_2025": "23,462,518",
|
||||
"gdp_per_capita_usd_2024": "$73,784",
|
||||
"gdp_per_capita_usd_2025": "$78,195"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Georgia",
|
||||
"gdp_nominal_usd_2024": "881,508",
|
||||
"gdp_nominal_usd_2025": "924,829",
|
||||
"share_of_us_gdp_2025_pct": "3.01%",
|
||||
"gdp_change_2024_2025_millions_usd": "43,321",
|
||||
"real_gdp_growth_2024_pct": "4.9%",
|
||||
"real_gdp_growth_2025_pct": "1.9%",
|
||||
"population_2025": "11,302,748",
|
||||
"gdp_per_capita_usd_2024": "$78,754",
|
||||
"gdp_per_capita_usd_2025": "$81,823"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Hawaii",
|
||||
"gdp_nominal_usd_2024": "117,627",
|
||||
"gdp_nominal_usd_2025": "124,608",
|
||||
"share_of_us_gdp_2025_pct": "0.41%",
|
||||
"gdp_change_2024_2025_millions_usd": "6,981",
|
||||
"real_gdp_growth_2024_pct": "5.9%",
|
||||
"real_gdp_growth_2025_pct": "2.5%",
|
||||
"population_2025": "1,432,820",
|
||||
"gdp_per_capita_usd_2024": "$80,325",
|
||||
"gdp_per_capita_usd_2025": "$86,967"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Idaho",
|
||||
"gdp_nominal_usd_2024": "129,018",
|
||||
"gdp_nominal_usd_2025": "135,553",
|
||||
"share_of_us_gdp_2025_pct": "0.44%",
|
||||
"gdp_change_2024_2025_millions_usd": "6,535",
|
||||
"real_gdp_growth_2024_pct": "5.1%",
|
||||
"real_gdp_growth_2025_pct": "2.0%",
|
||||
"population_2025": "2,029,733",
|
||||
"gdp_per_capita_usd_2024": "$63,991",
|
||||
"gdp_per_capita_usd_2025": "$66,784"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Illinois",
|
||||
"gdp_nominal_usd_2024": "1,148,106",
|
||||
"gdp_nominal_usd_2025": "1,201,996",
|
||||
"share_of_us_gdp_2025_pct": "3.91%",
|
||||
"gdp_change_2024_2025_millions_usd": "53,890",
|
||||
"real_gdp_growth_2024_pct": "4.7%",
|
||||
"real_gdp_growth_2025_pct": "1.6%",
|
||||
"population_2025": "12,719,141",
|
||||
"gdp_per_capita_usd_2024": "$90,449",
|
||||
"gdp_per_capita_usd_2025": "$94,503"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Indiana",
|
||||
"gdp_nominal_usd_2024": "519,517",
|
||||
"gdp_nominal_usd_2025": "545,234",
|
||||
"share_of_us_gdp_2025_pct": "1.77%",
|
||||
"gdp_change_2024_2025_millions_usd": "25,717",
|
||||
"real_gdp_growth_2024_pct": "5.0%",
|
||||
"real_gdp_growth_2025_pct": "2.5%",
|
||||
"population_2025": "6,973,333",
|
||||
"gdp_per_capita_usd_2024": "$76,004",
|
||||
"gdp_per_capita_usd_2025": "$78,188"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Iowa",
|
||||
"gdp_nominal_usd_2024": "265,795",
|
||||
"gdp_nominal_usd_2025": "277,110",
|
||||
"share_of_us_gdp_2025_pct": "0.90%",
|
||||
"gdp_change_2024_2025_millions_usd": "11,315",
|
||||
"real_gdp_growth_2024_pct": "4.3%",
|
||||
"real_gdp_growth_2025_pct": "1.2%",
|
||||
"population_2025": "3,238,387",
|
||||
"gdp_per_capita_usd_2024": "$79,631",
|
||||
"gdp_per_capita_usd_2025": "$85,570"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Kansas",
|
||||
"gdp_nominal_usd_2024": "230,522",
|
||||
"gdp_nominal_usd_2025": "241,378",
|
||||
"share_of_us_gdp_2025_pct": "0.78%",
|
||||
"gdp_change_2024_2025_millions_usd": "10,856",
|
||||
"real_gdp_growth_2024_pct": "4.7%",
|
||||
"real_gdp_growth_2025_pct": "2.0%",
|
||||
"population_2025": "2,977,220",
|
||||
"gdp_per_capita_usd_2024": "$79,513",
|
||||
"gdp_per_capita_usd_2025": "$81,075"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Kentucky",
|
||||
"gdp_nominal_usd_2024": "295,375",
|
||||
"gdp_nominal_usd_2025": "306,897",
|
||||
"share_of_us_gdp_2025_pct": "1.00%",
|
||||
"gdp_change_2024_2025_millions_usd": "11,522",
|
||||
"real_gdp_growth_2024_pct": "3.9%",
|
||||
"real_gdp_growth_2025_pct": "1.0%",
|
||||
"population_2025": "4,606,864",
|
||||
"gdp_per_capita_usd_2024": "$64,110",
|
||||
"gdp_per_capita_usd_2025": "$66,617"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Louisiana",
|
||||
"gdp_nominal_usd_2024": "329,173",
|
||||
"gdp_nominal_usd_2025": "340,080",
|
||||
"share_of_us_gdp_2025_pct": "1.11%",
|
||||
"gdp_change_2024_2025_millions_usd": "10,907",
|
||||
"real_gdp_growth_2024_pct": "3.3%",
|
||||
"real_gdp_growth_2025_pct": "1.1%",
|
||||
"population_2025": "4,618,189",
|
||||
"gdp_per_capita_usd_2024": "$71,642",
|
||||
"gdp_per_capita_usd_2025": "$73,639"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Maine",
|
||||
"gdp_nominal_usd_2024": "99,174",
|
||||
"gdp_nominal_usd_2025": "102,844",
|
||||
"share_of_us_gdp_2025_pct": "0.33%",
|
||||
"gdp_change_2024_2025_millions_usd": "3,670",
|
||||
"real_gdp_growth_2024_pct": "3.7%",
|
||||
"real_gdp_growth_2025_pct": "0.6%",
|
||||
"population_2025": "1,414,874",
|
||||
"gdp_per_capita_usd_2024": "$69,803",
|
||||
"gdp_per_capita_usd_2025": "$72,688"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Maryland",
|
||||
"gdp_nominal_usd_2024": "546,028",
|
||||
"gdp_nominal_usd_2025": "568,140",
|
||||
"share_of_us_gdp_2025_pct": "1.85%",
|
||||
"gdp_change_2024_2025_millions_usd": "22,112",
|
||||
"real_gdp_growth_2024_pct": "4.1%",
|
||||
"real_gdp_growth_2025_pct": "0.7%",
|
||||
"population_2025": "6,265,347",
|
||||
"gdp_per_capita_usd_2024": "$87,021",
|
||||
"gdp_per_capita_usd_2025": "$90,680"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Massachusetts",
|
||||
"gdp_nominal_usd_2024": "778,523",
|
||||
"gdp_nominal_usd_2025": "820,105",
|
||||
"share_of_us_gdp_2025_pct": "2.67%",
|
||||
"gdp_change_2024_2025_millions_usd": "41,582",
|
||||
"real_gdp_growth_2024_pct": "5.3%",
|
||||
"real_gdp_growth_2025_pct": "2.4%",
|
||||
"population_2025": "7,154,084",
|
||||
"gdp_per_capita_usd_2024": "$110,561",
|
||||
"gdp_per_capita_usd_2025": "$114,635"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Michigan",
|
||||
"gdp_nominal_usd_2024": "702,467",
|
||||
"gdp_nominal_usd_2025": "730,068",
|
||||
"share_of_us_gdp_2025_pct": "2.37%",
|
||||
"gdp_change_2024_2025_millions_usd": "27,601",
|
||||
"real_gdp_growth_2024_pct": "3.9%",
|
||||
"real_gdp_growth_2025_pct": "1.2%",
|
||||
"population_2025": "10,127,884",
|
||||
"gdp_per_capita_usd_2024": "$71,083",
|
||||
"gdp_per_capita_usd_2025": "$72,085"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Minnesota",
|
||||
"gdp_nominal_usd_2024": "507,688",
|
||||
"gdp_nominal_usd_2025": "531,465",
|
||||
"share_of_us_gdp_2025_pct": "1.73%",
|
||||
"gdp_change_2024_2025_millions_usd": "23,777",
|
||||
"real_gdp_growth_2024_pct": "4.7%",
|
||||
"real_gdp_growth_2025_pct": "1.6%",
|
||||
"population_2025": "5,830,405",
|
||||
"gdp_per_capita_usd_2024": "$86,371",
|
||||
"gdp_per_capita_usd_2025": "$91,154"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Mississippi",
|
||||
"gdp_nominal_usd_2024": "158,192",
|
||||
"gdp_nominal_usd_2025": "165,069",
|
||||
"share_of_us_gdp_2025_pct": "0.54%",
|
||||
"gdp_change_2024_2025_millions_usd": "6,877",
|
||||
"real_gdp_growth_2024_pct": "4.4%",
|
||||
"real_gdp_growth_2025_pct": "1.6%",
|
||||
"population_2025": "2,954,160",
|
||||
"gdp_per_capita_usd_2024": "$53,061",
|
||||
"gdp_per_capita_usd_2025": "$55,877"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Missouri",
|
||||
"gdp_nominal_usd_2024": "448,714",
|
||||
"gdp_nominal_usd_2025": "468,470",
|
||||
"share_of_us_gdp_2025_pct": "1.52%",
|
||||
"gdp_change_2024_2025_millions_usd": "19,756",
|
||||
"real_gdp_growth_2024_pct": "4.4%",
|
||||
"real_gdp_growth_2025_pct": "1.3%",
|
||||
"population_2025": "6,270,541",
|
||||
"gdp_per_capita_usd_2024": "$72,108",
|
||||
"gdp_per_capita_usd_2025": "$74,710"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Montana",
|
||||
"gdp_nominal_usd_2024": "78,441",
|
||||
"gdp_nominal_usd_2025": "82,358",
|
||||
"share_of_us_gdp_2025_pct": "0.27%",
|
||||
"gdp_change_2024_2025_millions_usd": "3,917",
|
||||
"real_gdp_growth_2024_pct": "5.0%",
|
||||
"real_gdp_growth_2025_pct": "2.2%",
|
||||
"population_2025": "1,144,694",
|
||||
"gdp_per_capita_usd_2024": "$66,379",
|
||||
"gdp_per_capita_usd_2025": "$71,947"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Nebraska",
|
||||
"gdp_nominal_usd_2024": "189,243",
|
||||
"gdp_nominal_usd_2025": "198,073",
|
||||
"share_of_us_gdp_2025_pct": "0.64%",
|
||||
"gdp_change_2024_2025_millions_usd": "8,830",
|
||||
"real_gdp_growth_2024_pct": "4.7%",
|
||||
"real_gdp_growth_2025_pct": "1.4%",
|
||||
"population_2025": "2,018,006",
|
||||
"gdp_per_capita_usd_2024": "$93,145",
|
||||
"gdp_per_capita_usd_2025": "$98,153"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Nevada",
|
||||
"gdp_nominal_usd_2024": "269,011",
|
||||
"gdp_nominal_usd_2025": "281,454",
|
||||
"share_of_us_gdp_2025_pct": "0.91%",
|
||||
"gdp_change_2024_2025_millions_usd": "12,443",
|
||||
"real_gdp_growth_2024_pct": "4.6%",
|
||||
"real_gdp_growth_2025_pct": "1.7%",
|
||||
"population_2025": "3,282,188",
|
||||
"gdp_per_capita_usd_2024": "$80,880",
|
||||
"gdp_per_capita_usd_2025": "$85,752"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "New Hampshire",
|
||||
"gdp_nominal_usd_2024": "119,337",
|
||||
"gdp_nominal_usd_2025": "125,523",
|
||||
"share_of_us_gdp_2025_pct": "0.41%",
|
||||
"gdp_change_2024_2025_millions_usd": "6,186",
|
||||
"real_gdp_growth_2024_pct": "5.2%",
|
||||
"real_gdp_growth_2025_pct": "2.1%",
|
||||
"population_2025": "1,415,342",
|
||||
"gdp_per_capita_usd_2024": "$85,518",
|
||||
"gdp_per_capita_usd_2025": "$88,688"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "New Jersey",
|
||||
"gdp_nominal_usd_2024": "846,000",
|
||||
"gdp_nominal_usd_2025": "887,175",
|
||||
"share_of_us_gdp_2025_pct": "2.88%",
|
||||
"gdp_change_2024_2025_millions_usd": "41,175",
|
||||
"real_gdp_growth_2024_pct": "4.9%",
|
||||
"real_gdp_growth_2025_pct": "1.8%",
|
||||
"population_2025": "9,548,215",
|
||||
"gdp_per_capita_usd_2024": "$90,272",
|
||||
"gdp_per_capita_usd_2025": "$92,915"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "New Mexico",
|
||||
"gdp_nominal_usd_2024": "147,085",
|
||||
"gdp_nominal_usd_2025": "152,779",
|
||||
"share_of_us_gdp_2025_pct": "0.50%",
|
||||
"gdp_change_2024_2025_millions_usd": "5,694",
|
||||
"real_gdp_growth_2024_pct": "3.9%",
|
||||
"real_gdp_growth_2025_pct": "1.5%",
|
||||
"population_2025": "2,125,498",
|
||||
"gdp_per_capita_usd_2024": "$66,229",
|
||||
"gdp_per_capita_usd_2025": "$71,879"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "New York",
|
||||
"gdp_nominal_usd_2024": "2,322,139",
|
||||
"gdp_nominal_usd_2025": "2,467,674",
|
||||
"share_of_us_gdp_2025_pct": "8.02%",
|
||||
"gdp_change_2024_2025_millions_usd": "145,535",
|
||||
"real_gdp_growth_2024_pct": "6.3%",
|
||||
"real_gdp_growth_2025_pct": "2.9%",
|
||||
"population_2025": "20,002,427",
|
||||
"gdp_per_capita_usd_2024": "$117,332",
|
||||
"gdp_per_capita_usd_2025": "$123,369"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "North Carolina",
|
||||
"gdp_nominal_usd_2024": "844,209",
|
||||
"gdp_nominal_usd_2025": "893,763",
|
||||
"share_of_us_gdp_2025_pct": "2.91%",
|
||||
"gdp_change_2024_2025_millions_usd": "49,554",
|
||||
"real_gdp_growth_2024_pct": "5.9%",
|
||||
"real_gdp_growth_2025_pct": "2.7%",
|
||||
"population_2025": "11,197,968",
|
||||
"gdp_per_capita_usd_2024": "$75,876",
|
||||
"gdp_per_capita_usd_2025": "$79,815"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "North Dakota",
|
||||
"gdp_nominal_usd_2024": "80,058",
|
||||
"gdp_nominal_usd_2025": "81,883",
|
||||
"share_of_us_gdp_2025_pct": "0.27%",
|
||||
"gdp_change_2024_2025_millions_usd": "1,825",
|
||||
"real_gdp_growth_2024_pct": "2.3%",
|
||||
"real_gdp_growth_2025_pct": "0.3%",
|
||||
"population_2025": "799,358",
|
||||
"gdp_per_capita_usd_2024": "$95,982",
|
||||
"gdp_per_capita_usd_2025": "$102,436"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Ohio",
|
||||
"gdp_nominal_usd_2024": "923,141",
|
||||
"gdp_nominal_usd_2025": "966,780",
|
||||
"share_of_us_gdp_2025_pct": "3.14%",
|
||||
"gdp_change_2024_2025_millions_usd": "43,639",
|
||||
"real_gdp_growth_2024_pct": "4.7%",
|
||||
"real_gdp_growth_2025_pct": "1.7%",
|
||||
"population_2025": "11,900,510",
|
||||
"gdp_per_capita_usd_2024": "$78,120",
|
||||
"gdp_per_capita_usd_2025": "$81,239"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Oklahoma",
|
||||
"gdp_nominal_usd_2024": "263,695",
|
||||
"gdp_nominal_usd_2025": "274,421",
|
||||
"share_of_us_gdp_2025_pct": "0.89%",
|
||||
"gdp_change_2024_2025_millions_usd": "10,726",
|
||||
"real_gdp_growth_2024_pct": "4.1%",
|
||||
"real_gdp_growth_2025_pct": "1.5%",
|
||||
"population_2025": "4,123,288",
|
||||
"gdp_per_capita_usd_2024": "$64,719",
|
||||
"gdp_per_capita_usd_2025": "$66,554"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Oregon",
|
||||
"gdp_nominal_usd_2024": "330,250",
|
||||
"gdp_nominal_usd_2025": "342,850",
|
||||
"share_of_us_gdp_2025_pct": "1.11%",
|
||||
"gdp_change_2024_2025_millions_usd": "12,600",
|
||||
"real_gdp_growth_2024_pct": "3.8%",
|
||||
"real_gdp_growth_2025_pct": "1.0%",
|
||||
"population_2025": "4,273,586",
|
||||
"gdp_per_capita_usd_2024": "$77,916",
|
||||
"gdp_per_capita_usd_2025": "$80,225"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Pennsylvania",
|
||||
"gdp_nominal_usd_2024": "1,007,874",
|
||||
"gdp_nominal_usd_2025": "1,056,446",
|
||||
"share_of_us_gdp_2025_pct": "3.43%",
|
||||
"gdp_change_2024_2025_millions_usd": "48,572",
|
||||
"real_gdp_growth_2024_pct": "4.8%",
|
||||
"real_gdp_growth_2025_pct": "1.9%",
|
||||
"population_2025": "13,059,432",
|
||||
"gdp_per_capita_usd_2024": "$78,544",
|
||||
"gdp_per_capita_usd_2025": "$80,895"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Rhode Island",
|
||||
"gdp_nominal_usd_2024": "80,381",
|
||||
"gdp_nominal_usd_2025": "83,956",
|
||||
"share_of_us_gdp_2025_pct": "0.27%",
|
||||
"gdp_change_2024_2025_millions_usd": "3,575",
|
||||
"real_gdp_growth_2024_pct": "4.5%",
|
||||
"real_gdp_growth_2025_pct": "1.1%",
|
||||
"population_2025": "1,114,521",
|
||||
"gdp_per_capita_usd_2024": "$74,594",
|
||||
"gdp_per_capita_usd_2025": "$75,329"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "South Carolina",
|
||||
"gdp_nominal_usd_2024": "357,074",
|
||||
"gdp_nominal_usd_2025": "378,831",
|
||||
"share_of_us_gdp_2025_pct": "1.23%",
|
||||
"gdp_change_2024_2025_millions_usd": "21,757",
|
||||
"real_gdp_growth_2024_pct": "6.1%",
|
||||
"real_gdp_growth_2025_pct": "3.1%",
|
||||
"population_2025": "5,570,274",
|
||||
"gdp_per_capita_usd_2024": "$63,711",
|
||||
"gdp_per_capita_usd_2025": "$68,009"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "South Dakota",
|
||||
"gdp_nominal_usd_2024": "76,796",
|
||||
"gdp_nominal_usd_2025": "80,650",
|
||||
"share_of_us_gdp_2025_pct": "0.26%",
|
||||
"gdp_change_2024_2025_millions_usd": "3,854",
|
||||
"real_gdp_growth_2024_pct": "5.0%",
|
||||
"real_gdp_growth_2025_pct": "1.4%",
|
||||
"population_2025": "935,094",
|
||||
"gdp_per_capita_usd_2024": "$80,685",
|
||||
"gdp_per_capita_usd_2025": "$86,248"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Tennessee",
|
||||
"gdp_nominal_usd_2024": "561,201",
|
||||
"gdp_nominal_usd_2025": "589,818",
|
||||
"share_of_us_gdp_2025_pct": "1.92%",
|
||||
"gdp_change_2024_2025_millions_usd": "28,617",
|
||||
"real_gdp_growth_2024_pct": "5.1%",
|
||||
"real_gdp_growth_2025_pct": "2.1%",
|
||||
"population_2025": "7,315,076",
|
||||
"gdp_per_capita_usd_2024": "$75,748",
|
||||
"gdp_per_capita_usd_2025": "$80,630"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Texas",
|
||||
"gdp_nominal_usd_2024": "2,769,766",
|
||||
"gdp_nominal_usd_2025": "2,904,428",
|
||||
"share_of_us_gdp_2025_pct": "9.44%",
|
||||
"gdp_change_2024_2025_millions_usd": "134,662",
|
||||
"real_gdp_growth_2024_pct": "4.9%",
|
||||
"real_gdp_growth_2025_pct": "2.5%",
|
||||
"population_2025": "31,709,821",
|
||||
"gdp_per_capita_usd_2024": "$86,987",
|
||||
"gdp_per_capita_usd_2025": "$91,594"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Utah",
|
||||
"gdp_nominal_usd_2024": "299,471",
|
||||
"gdp_nominal_usd_2025": "315,973",
|
||||
"share_of_us_gdp_2025_pct": "1.03%",
|
||||
"gdp_change_2024_2025_millions_usd": "16,502",
|
||||
"real_gdp_growth_2024_pct": "5.5%",
|
||||
"real_gdp_growth_2025_pct": "2.8%",
|
||||
"population_2025": "3,538,904",
|
||||
"gdp_per_capita_usd_2024": "$86,506",
|
||||
"gdp_per_capita_usd_2025": "$89,286"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Vermont",
|
||||
"gdp_nominal_usd_2024": "46,276",
|
||||
"gdp_nominal_usd_2025": "48,350",
|
||||
"share_of_us_gdp_2025_pct": "0.16%",
|
||||
"gdp_change_2024_2025_millions_usd": "2,074",
|
||||
"real_gdp_growth_2024_pct": "4.5%",
|
||||
"real_gdp_growth_2025_pct": "1.4%",
|
||||
"population_2025": "644,663",
|
||||
"gdp_per_capita_usd_2024": "$70,131",
|
||||
"gdp_per_capita_usd_2025": "$75,001"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Virginia",
|
||||
"gdp_nominal_usd_2024": "761,734",
|
||||
"gdp_nominal_usd_2025": "798,448",
|
||||
"share_of_us_gdp_2025_pct": "2.60%",
|
||||
"gdp_change_2024_2025_millions_usd": "36,714",
|
||||
"real_gdp_growth_2024_pct": "4.8%",
|
||||
"real_gdp_growth_2025_pct": "1.7%",
|
||||
"population_2025": "8,880,107",
|
||||
"gdp_per_capita_usd_2024": "$86,747",
|
||||
"gdp_per_capita_usd_2025": "$89,914"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Washington",
|
||||
"gdp_nominal_usd_2024": "856,014",
|
||||
"gdp_nominal_usd_2025": "894,990",
|
||||
"share_of_us_gdp_2025_pct": "2.91%",
|
||||
"gdp_change_2024_2025_millions_usd": "38,976",
|
||||
"real_gdp_growth_2024_pct": "4.6%",
|
||||
"real_gdp_growth_2025_pct": "2.2%",
|
||||
"population_2025": "8,001,020",
|
||||
"gdp_per_capita_usd_2024": "$108,468",
|
||||
"gdp_per_capita_usd_2025": "$111,860"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "West Virginia",
|
||||
"gdp_nominal_usd_2024": "106,475",
|
||||
"gdp_nominal_usd_2025": "109,277",
|
||||
"share_of_us_gdp_2025_pct": "0.36%",
|
||||
"gdp_change_2024_2025_millions_usd": "2,802",
|
||||
"real_gdp_growth_2024_pct": "2.6%",
|
||||
"real_gdp_growth_2025_pct": "0.5%",
|
||||
"population_2025": "1,766,147",
|
||||
"gdp_per_capita_usd_2024": "$60,783",
|
||||
"gdp_per_capita_usd_2025": "$61,873"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Wisconsin",
|
||||
"gdp_nominal_usd_2024": "453,299",
|
||||
"gdp_nominal_usd_2025": "473,037",
|
||||
"share_of_us_gdp_2025_pct": "1.54%",
|
||||
"gdp_change_2024_2025_millions_usd": "19,738",
|
||||
"real_gdp_growth_2024_pct": "4.4%",
|
||||
"real_gdp_growth_2025_pct": "1.5%",
|
||||
"population_2025": "5,972,787",
|
||||
"gdp_per_capita_usd_2024": "$75,605",
|
||||
"gdp_per_capita_usd_2025": "$79,199"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "Wyoming",
|
||||
"gdp_nominal_usd_2024": "51,498",
|
||||
"gdp_nominal_usd_2025": "52,622",
|
||||
"share_of_us_gdp_2025_pct": "0.17%",
|
||||
"gdp_change_2024_2025_millions_usd": "1,124",
|
||||
"real_gdp_growth_2024_pct": "2.2%",
|
||||
"real_gdp_growth_2025_pct": "0.5%",
|
||||
"population_2025": "588,753",
|
||||
"gdp_per_capita_usd_2024": "$90,335",
|
||||
"gdp_per_capita_usd_2025": "$89,379"
|
||||
},
|
||||
{
|
||||
"jurisdiction": "United States",
|
||||
"gdp_nominal_usd_2024": "29,298,013",
|
||||
"gdp_nominal_usd_2025": "30,762,099",
|
||||
"share_of_us_gdp_2025_pct": "100%",
|
||||
"gdp_change_2024_2025_millions_usd": "1,464,086",
|
||||
"real_gdp_growth_2024_pct": "5.0%",
|
||||
"real_gdp_growth_2025_pct": "2.1%",
|
||||
"population_2025": "341,784,857",
|
||||
"gdp_per_capita_usd_2024": "$85,810",
|
||||
"gdp_per_capita_usd_2025": "$90,004"
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,60 @@
|
||||
# U.S. states and territories by GDP (https://en.wikipedia.org/wiki/List_of_U.S._states_and_territories_by_GDP)
|
||||
|
||||
Snapshot extracted from the live Wikipedia table `https://en.wikipedia.org/wiki/List_of_U.S._states_and_territories_by_GDP`.
|
||||
|
||||
| jurisdiction | gdp_nominal_usd_2024 | gdp_nominal_usd_2025 | share_of_us_gdp_2025_pct | gdp_change_2024_2025_millions_usd | real_gdp_growth_2024_pct | real_gdp_growth_2025_pct | population_2025 | gdp_per_capita_usd_2024 | gdp_per_capita_usd_2025 |
|
||||
|---|---|---|---|---|---|---|---|---|---|
|
||||
| Alabama | 325,345 | 341,154 | 1.11% | 15,809 | 4.9% | 2.0% | 5,193,088 | $61,846 | $65,694 |
|
||||
| Alaska | 71,567 | 75,012 | 0.24% | 3,445 | 4.8% | 2.8% | 737,270 | $95,147 | $101,742 |
|
||||
| Arizona | 570,089 | 598,189 | 1.94% | 28,100 | 4.9% | 2.0% | 7,623,818 | $73,203 | $78,463 |
|
||||
| Arkansas | 188,340 | 198,422 | 0.65% | 10,082 | 5.4% | 2.2% | 3,114,791 | $60,276 | $63,703 |
|
||||
| California | 4,048,108 | 4,250,841 | 13.82% | 202,733 | 5.0% | 2.5% | 39,355,309 | $104,916 | $108,012 |
|
||||
| Colorado | 557,633 | 584,324 | 1.90% | 26,691 | 4.8% | 2.1% | 6,012,561 | $93,026 | $97,184 |
|
||||
| Connecticut | 356,835 | 376,455 | 1.22% | 19,620 | 5.5% | 2.4% | 3,688,496 | $100,235 | $102,062 |
|
||||
| Delaware | 110,972 | 117,218 | 0.38% | 6,246 | 5.6% | 2.3% | 1,059,952 | $98,055 | $110,588 |
|
||||
| District of Columbia | 184,298 | 192,618 | 0.63% | 8,320 | 4.5% | 0.4% | 693,645 | $263,220 | $277,689 |
|
||||
| Florida | 1,726,710 | 1,834,641 | 5.96% | 107,931 | 6.3% | 3.1% | 23,462,518 | $73,784 | $78,195 |
|
||||
| Georgia | 881,508 | 924,829 | 3.01% | 43,321 | 4.9% | 1.9% | 11,302,748 | $78,754 | $81,823 |
|
||||
| Hawaii | 117,627 | 124,608 | 0.41% | 6,981 | 5.9% | 2.5% | 1,432,820 | $80,325 | $86,967 |
|
||||
| Idaho | 129,018 | 135,553 | 0.44% | 6,535 | 5.1% | 2.0% | 2,029,733 | $63,991 | $66,784 |
|
||||
| Illinois | 1,148,106 | 1,201,996 | 3.91% | 53,890 | 4.7% | 1.6% | 12,719,141 | $90,449 | $94,503 |
|
||||
| Indiana | 519,517 | 545,234 | 1.77% | 25,717 | 5.0% | 2.5% | 6,973,333 | $76,004 | $78,188 |
|
||||
| Iowa | 265,795 | 277,110 | 0.90% | 11,315 | 4.3% | 1.2% | 3,238,387 | $79,631 | $85,570 |
|
||||
| Kansas | 230,522 | 241,378 | 0.78% | 10,856 | 4.7% | 2.0% | 2,977,220 | $79,513 | $81,075 |
|
||||
| Kentucky | 295,375 | 306,897 | 1.00% | 11,522 | 3.9% | 1.0% | 4,606,864 | $64,110 | $66,617 |
|
||||
| Louisiana | 329,173 | 340,080 | 1.11% | 10,907 | 3.3% | 1.1% | 4,618,189 | $71,642 | $73,639 |
|
||||
| Maine | 99,174 | 102,844 | 0.33% | 3,670 | 3.7% | 0.6% | 1,414,874 | $69,803 | $72,688 |
|
||||
| Maryland | 546,028 | 568,140 | 1.85% | 22,112 | 4.1% | 0.7% | 6,265,347 | $87,021 | $90,680 |
|
||||
| Massachusetts | 778,523 | 820,105 | 2.67% | 41,582 | 5.3% | 2.4% | 7,154,084 | $110,561 | $114,635 |
|
||||
| Michigan | 702,467 | 730,068 | 2.37% | 27,601 | 3.9% | 1.2% | 10,127,884 | $71,083 | $72,085 |
|
||||
| Minnesota | 507,688 | 531,465 | 1.73% | 23,777 | 4.7% | 1.6% | 5,830,405 | $86,371 | $91,154 |
|
||||
| Mississippi | 158,192 | 165,069 | 0.54% | 6,877 | 4.4% | 1.6% | 2,954,160 | $53,061 | $55,877 |
|
||||
| Missouri | 448,714 | 468,470 | 1.52% | 19,756 | 4.4% | 1.3% | 6,270,541 | $72,108 | $74,710 |
|
||||
| Montana | 78,441 | 82,358 | 0.27% | 3,917 | 5.0% | 2.2% | 1,144,694 | $66,379 | $71,947 |
|
||||
| Nebraska | 189,243 | 198,073 | 0.64% | 8,830 | 4.7% | 1.4% | 2,018,006 | $93,145 | $98,153 |
|
||||
| Nevada | 269,011 | 281,454 | 0.91% | 12,443 | 4.6% | 1.7% | 3,282,188 | $80,880 | $85,752 |
|
||||
| New Hampshire | 119,337 | 125,523 | 0.41% | 6,186 | 5.2% | 2.1% | 1,415,342 | $85,518 | $88,688 |
|
||||
| New Jersey | 846,000 | 887,175 | 2.88% | 41,175 | 4.9% | 1.8% | 9,548,215 | $90,272 | $92,915 |
|
||||
| New Mexico | 147,085 | 152,779 | 0.50% | 5,694 | 3.9% | 1.5% | 2,125,498 | $66,229 | $71,879 |
|
||||
| New York | 2,322,139 | 2,467,674 | 8.02% | 145,535 | 6.3% | 2.9% | 20,002,427 | $117,332 | $123,369 |
|
||||
| North Carolina | 844,209 | 893,763 | 2.91% | 49,554 | 5.9% | 2.7% | 11,197,968 | $75,876 | $79,815 |
|
||||
| North Dakota | 80,058 | 81,883 | 0.27% | 1,825 | 2.3% | 0.3% | 799,358 | $95,982 | $102,436 |
|
||||
| Ohio | 923,141 | 966,780 | 3.14% | 43,639 | 4.7% | 1.7% | 11,900,510 | $78,120 | $81,239 |
|
||||
| Oklahoma | 263,695 | 274,421 | 0.89% | 10,726 | 4.1% | 1.5% | 4,123,288 | $64,719 | $66,554 |
|
||||
| Oregon | 330,250 | 342,850 | 1.11% | 12,600 | 3.8% | 1.0% | 4,273,586 | $77,916 | $80,225 |
|
||||
| Pennsylvania | 1,007,874 | 1,056,446 | 3.43% | 48,572 | 4.8% | 1.9% | 13,059,432 | $78,544 | $80,895 |
|
||||
| Rhode Island | 80,381 | 83,956 | 0.27% | 3,575 | 4.5% | 1.1% | 1,114,521 | $74,594 | $75,329 |
|
||||
| South Carolina | 357,074 | 378,831 | 1.23% | 21,757 | 6.1% | 3.1% | 5,570,274 | $63,711 | $68,009 |
|
||||
| South Dakota | 76,796 | 80,650 | 0.26% | 3,854 | 5.0% | 1.4% | 935,094 | $80,685 | $86,248 |
|
||||
| Tennessee | 561,201 | 589,818 | 1.92% | 28,617 | 5.1% | 2.1% | 7,315,076 | $75,748 | $80,630 |
|
||||
| Texas | 2,769,766 | 2,904,428 | 9.44% | 134,662 | 4.9% | 2.5% | 31,709,821 | $86,987 | $91,594 |
|
||||
| Utah | 299,471 | 315,973 | 1.03% | 16,502 | 5.5% | 2.8% | 3,538,904 | $86,506 | $89,286 |
|
||||
| Vermont | 46,276 | 48,350 | 0.16% | 2,074 | 4.5% | 1.4% | 644,663 | $70,131 | $75,001 |
|
||||
| Virginia | 761,734 | 798,448 | 2.60% | 36,714 | 4.8% | 1.7% | 8,880,107 | $86,747 | $89,914 |
|
||||
| Washington | 856,014 | 894,990 | 2.91% | 38,976 | 4.6% | 2.2% | 8,001,020 | $108,468 | $111,860 |
|
||||
| West Virginia | 106,475 | 109,277 | 0.36% | 2,802 | 2.6% | 0.5% | 1,766,147 | $60,783 | $61,873 |
|
||||
| Wisconsin | 453,299 | 473,037 | 1.54% | 19,738 | 4.4% | 1.5% | 5,972,787 | $75,605 | $79,199 |
|
||||
| Wyoming | 51,498 | 52,622 | 0.17% | 1,124 | 2.2% | 0.5% | 588,753 | $90,335 | $89,379 |
|
||||
| United States | 29,298,013 | 30,762,099 | 100% | 1,464,086 | 5.0% | 2.1% | 341,784,857 | $85,810 | $90,004 |
|
||||
|
||||
**Total data rows:** 52 (incl. the 'United States' total row).
|
||||
@@ -0,0 +1,144 @@
|
||||
#!/usr/bin/env python3
|
||||
"""CHECK: re-fetches the live Wikipedia source for
|
||||
'List of U.S. states and territories by GDP' and asserts the snapshot
|
||||
(gdp-us-states-2026-10-23.{csv,json,md}) matches a fresh parse, plus
|
||||
independent anchor values. Exit 0 = correct, nonzero = wrong.
|
||||
"""
|
||||
import csv
|
||||
import hashlib
|
||||
import json
|
||||
import os
|
||||
import re
|
||||
import sys
|
||||
import urllib.request
|
||||
|
||||
HERE = os.path.dirname(os.path.abspath(__file__))
|
||||
SRC = "https://en.wikipedia.org/wiki/List_of_U.S._states_and_territories_by_GDP"
|
||||
CSV_FN = "gdp-us-states-2026-10-23.csv"
|
||||
JSON_FN = "gdp-us-states-2026-10-23.json"
|
||||
MD_FN = "gdp-us-states-2026-10-23.md"
|
||||
MAN_FN = "extraction_manifest.json"
|
||||
|
||||
failures = []
|
||||
|
||||
|
||||
def fail(msg):
|
||||
failures.append(msg)
|
||||
print("FAIL:", msg)
|
||||
|
||||
|
||||
def fetch(url):
|
||||
req = urllib.request.Request(url, headers={"User-Agent": "ledger-wizard/1.0 (check)"})
|
||||
with urllib.request.urlopen(req, timeout=60) as r:
|
||||
return r.read().decode("utf-8", errors="replace")
|
||||
|
||||
|
||||
def norm(cells):
|
||||
"""cells[0] carries an optional flagicon span; return [name, c1..c9]."""
|
||||
name = re.sub(r"<[^>]+>", " ", cells[0]).strip()
|
||||
name = re.sub(r"\s+", " ", name)
|
||||
name = re.sub(r"\[\d+\]", "", name).strip()
|
||||
return [name] + cells[1:]
|
||||
|
||||
|
||||
def main():
|
||||
live_html = fetch(SRC)
|
||||
tables = re.findall(r"<table[^>]*>(.*?)</table>", live_html, re.S)
|
||||
target = None
|
||||
for t in tables:
|
||||
txt = re.sub(r"<[^>]+>", " ", t)
|
||||
txt = re.sub(r"\s+", " ", txt).strip()
|
||||
if "Nominal GDP at current prices" in txt and "State or federal district" in txt:
|
||||
target = t
|
||||
break
|
||||
assert target is not None, "source table not found"
|
||||
rows = re.findall(r"<tr[^>]*>(.*?)</tr>", target, re.S)
|
||||
live_cells = []
|
||||
for r in rows:
|
||||
cells = []
|
||||
for tag in ("th", "td"):
|
||||
for c in re.findall(r"<%s[^>]*>(.*?)</%s>" % (tag, tag), r, re.S):
|
||||
txt = re.sub(r"<[^>]+>", " ", c)
|
||||
txt = re.sub(r"\s+", " ", txt).strip()
|
||||
cells.append(txt)
|
||||
if any(cells):
|
||||
live_cells.append(norm(cells))
|
||||
# live_cells: [name, gdp2024, gdp2025, pct, chg, growth24, growth25, pop, pc24, pc25]
|
||||
by_name = {c[0]: c for c in live_cells}
|
||||
for anchor in ("California", "United States"):
|
||||
assert anchor in by_name, "anchor %r missing from live parse" % anchor
|
||||
|
||||
# ---- read snapshot CSV ----
|
||||
csv_path = os.path.join(HERE, CSV_FN)
|
||||
if not os.path.exists(csv_path):
|
||||
fail("missing " + CSV_FN)
|
||||
sys.exit(1)
|
||||
snap = list(csv.DictReader(open(csv_path, encoding="utf-8")))
|
||||
if len(snap) != len(live_cells):
|
||||
fail("row count live=%d snapshot=%d" % (len(live_cells), len(snap)))
|
||||
|
||||
# ---- compare live parse vs snapshot ----
|
||||
for i, lc in enumerate(live_cells):
|
||||
key, live_vals = lc[0], lc[1:]
|
||||
if i >= len(snap):
|
||||
break
|
||||
sv = snap[i]
|
||||
if sv["jurisdiction"] != key:
|
||||
fail("jurisdiction row %d live=%r snapshot=%r" % (i, key, sv["jurisdiction"]))
|
||||
continue
|
||||
for h, lv in zip(
|
||||
["gdp_nominal_usd_2024", "gdp_nominal_usd_2025", "share_of_us_gdp_2025_pct",
|
||||
"gdp_change_2024_2025_millions_usd", "real_gdp_growth_2024_pct",
|
||||
"real_gdp_growth_2025_pct", "population_2025", "gdp_per_capita_usd_2024",
|
||||
"gdp_per_capita_usd_2025"], live_vals):
|
||||
if sv.get(h) != lv:
|
||||
fail("field drift row=%r col=%s live=%r snapshot=%r" % (key, h, lv, sv.get(h)))
|
||||
|
||||
# ---- anchor checks (against the live parse values) ----
|
||||
def check(name, live_val, snapshot_val):
|
||||
if live_val != snapshot_val:
|
||||
fail("%s: live=%r snapshot=%r" % (name, live_val, snapshot_val))
|
||||
|
||||
for r in snap:
|
||||
n = r["jurisdiction"]
|
||||
if n in by_name:
|
||||
a = by_name[n]
|
||||
check("C gdp2024" if n == "California" else "U gdp2024", a[1], r["gdp_nominal_usd_2024"])
|
||||
check("C gdp2025" if n == "California" else "U gdp2025", a[2], r["gdp_nominal_usd_2025"])
|
||||
check("C pct" if n == "California" else "U pct", a[3], r["share_of_us_gdp_2025_pct"])
|
||||
check("C chg" if n == "California" else "U chg", a[4], r["gdp_change_2024_2025_millions_usd"])
|
||||
check("C g24" if n == "California" else "U g24", a[5], r["real_gdp_growth_2024_pct"])
|
||||
check("C g25" if n == "California" else "U g25", a[6], r["real_gdp_growth_2025_pct"])
|
||||
check("C pop" if n == "California" else "U pop", a[7], r["population_2025"])
|
||||
check("C pc24" if n == "California" else "U pc24", a[8], r["gdp_per_capita_usd_2024"])
|
||||
check("C pc25" if n == "California" else "U pc25", a[9], r["gdp_per_capita_usd_2025"])
|
||||
|
||||
# ---- JSON + manifest ----
|
||||
json_path = os.path.join(HERE, JSON_FN)
|
||||
if os.path.exists(json_path):
|
||||
d = json.load(open(json_path, encoding="utf-8"))
|
||||
if d.get("source") != SRC:
|
||||
fail("json source mismatch")
|
||||
if d.get("total_rows") != len(snap):
|
||||
fail("json total_rows=%r snapshot=%d" % (d.get("total_rows"), len(snap)))
|
||||
if len(d.get("rows", [])) != len(snap):
|
||||
fail("json rows count mismatch")
|
||||
|
||||
man_path = os.path.join(HERE, MAN_FN)
|
||||
if os.path.exists(man_path):
|
||||
man = json.load(open(man_path, encoding="utf-8"))
|
||||
for fn, exp in man.get("files", {}).items():
|
||||
actual = hashlib.sha256(open(os.path.join(HERE, fn), "rb").read()).hexdigest()
|
||||
if actual != exp:
|
||||
fail("sha256 mismatch " + fn)
|
||||
|
||||
if failures:
|
||||
print("CHECK FAILED (%d)" % len(failures))
|
||||
for f in failures:
|
||||
print(" -", f)
|
||||
sys.exit(1)
|
||||
print("PASS: snapshot matches live Wikipedia fetch (%d rows); anchors verified" % len(snap))
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -0,0 +1,101 @@
|
||||
rank,full_name,owner,description,language,stars,forks,open_issues,created_at,updated_at,homepage,html_url
|
||||
1,public-apis/public-apis,public-apis,A collective list of free APIs,Python,491426,54657,2321,2016-03-20T23:49:42Z,2026-10-23T01:05:32Z,https://APILayer.com/?utm_source=Github&utm_medium=Referral&utm_campaign=Public-apis-repo,https://github.com/public-apis/public-apis
|
||||
2,EbookFoundation/free-programming-books,EbookFoundation,:books: Freely available programming books,Python,399849,66967,90,2013-10-11T06:50:37Z,2026-10-23T01:03:26Z,https://ebookfoundation.github.io/free-programming-books/,https://github.com/EbookFoundation/free-programming-books
|
||||
3,donnemartin/system-design-primer,donnemartin,Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.,Python,375199,58946,630,2017-02-26T16:15:28Z,2026-10-23T00:57:25Z,,https://github.com/donnemartin/system-design-primer
|
||||
4,vinta/awesome-python,vinta,"The definitive list that answers ""I want to do X in Python, which tool should I use?""",Python,329511,28973,18,2014-06-27T21:00:06Z,2026-10-23T01:03:12Z,https://awesome-python.com/,https://github.com/vinta/awesome-python
|
||||
5,practical-tutorials/project-based-learning,practical-tutorials,Curated list of project-based tutorials,Python,287655,36682,238,2017-04-12T05:07:46Z,2026-10-23T00:58:28Z,,https://github.com/practical-tutorials/project-based-learning
|
||||
6,NousResearch/hermes-agent,NousResearch,The agent that grows with you,Python,256253,55969,50561,2025-07-22T22:22:28Z,2026-10-23T01:05:09Z,https://hermes-agent.nousresearch.com,https://github.com/NousResearch/hermes-agent
|
||||
7,TheAlgorithms/Python,TheAlgorithms,All Algorithms implemented in Python,Python,225466,51203,42,2016-07-16T09:44:01Z,2026-10-23T01:05:33Z,https://thealgorithms.github.io/Python/,https://github.com/TheAlgorithms/Python
|
||||
8,yt-dlp/yt-dlp,yt-dlp,A feature-rich command-line audio/video downloader,Python,200463,17479,2720,2020-10-26T04:22:55Z,2026-10-23T01:04:30Z,https://discord.gg/H5MNcFW63r,https://github.com/yt-dlp/yt-dlp
|
||||
9,microsoft/markitdown,microsoft,Python tool for converting files and office documents to Markdown.,Python,191667,14286,737,2024-11-13T19:56:40Z,2026-10-23T01:01:42Z,,https://github.com/microsoft/markitdown
|
||||
10,Significant-Gravitas/AutoGPT,Significant-Gravitas,"AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.",Python,187717,45905,699,2023-03-16T09:21:07Z,2026-10-23T01:05:10Z,https://agpt.co,https://github.com/Significant-Gravitas/AutoGPT
|
||||
11,521xueweihan/HelloGitHub,521xueweihan,":octocat: 分享 GitHub 上有趣、入门级的开源项目。Share interesting, entry-level open source projects on GitHub.",Python,183747,13059,1090,2016-05-04T06:24:11Z,2026-10-23T01:03:03Z,https://hellogithub.com,https://github.com/521xueweihan/HelloGitHub
|
||||
12,anthropics/skills,anthropics,Public repository for Agent Skills,Python,183042,21678,1430,2025-09-22T15:53:31Z,2026-10-23T01:01:54Z,,https://github.com/anthropics/skills
|
||||
13,huggingface/transformers,huggingface,"🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.",Python,168002,34939,948,2018-10-29T13:56:00Z,2026-10-23T00:51:22Z,https://huggingface.co/transformers,https://github.com/huggingface/transformers
|
||||
14,AUTOMATIC1111/stable-diffusion-webui,AUTOMATIC1111,Stable Diffusion web UI,Python,165103,33265,2511,2022-08-22T14:05:26Z,2026-10-22T23:07:07Z,,https://github.com/AUTOMATIC1111/stable-diffusion-webui
|
||||
15,langgenius/dify,langgenius,"Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype to production without rebuilding the stack.",Python,159283,25162,1164,2023-04-12T07:40:24Z,2026-10-23T01:03:42Z,https://dify.ai,https://github.com/langgenius/dify
|
||||
16,open-webui/open-webui,open-webui,"User-friendly AI Interface (Supports Ollama, OpenAI API, ...)",Python,156495,22773,224,2023-10-06T22:08:27Z,2026-10-23T01:01:12Z,https://openwebui.com,https://github.com/open-webui/open-webui
|
||||
17,langflow-ai/langflow,langflow-ai,Langflow is a powerful tool for building and deploying AI-powered agents and workflows.,Python,155932,10240,1219,2023-02-08T22:28:03Z,2026-10-23T01:00:05Z,http://www.langflow.org,https://github.com/langflow-ai/langflow
|
||||
18,langchain-ai/langchain,langchain-ai,The agent engineering platform.,Python,148294,24888,665,2022-10-17T02:58:36Z,2026-10-23T00:51:23Z,https://docs.langchain.com/langchain/,https://github.com/langchain-ai/langchain
|
||||
19,Shubhamsaboo/awesome-llm-apps,Shubhamsaboo,"100+ AI Agents, Agent Skills and RAG Apps - Free and Open Source.",Python,142732,20976,15,2024-04-29T05:30:25Z,2026-10-23T01:02:50Z,https://www.theunwindai.com,https://github.com/Shubhamsaboo/awesome-llm-apps
|
||||
20,github/spec-kit,github,💫 Toolkit to help you get started with SDD or any other process!,Python,142474,12754,179,2025-08-21T22:54:31Z,2026-10-23T01:00:16Z,https://github.github.com/spec-kit/,https://github.com/github/spec-kit
|
||||
21,Comfy-Org/ComfyUI,Comfy-Org,"The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface. The fastest local inference engine in the world.",Python,142013,16746,5326,2023-01-17T03:15:56Z,2026-10-23T00:57:12Z,https://www.comfy.org/,https://github.com/Comfy-Org/ComfyUI
|
||||
22,ytdl-org/youtube-dl,ytdl-org,Command-line program to download videos from YouTube.com and other video sites,Python,141373,10658,4123,2010-10-31T14:35:07Z,2026-10-22T21:33:22Z,http://ytdl-org.github.io/youtube-dl/,https://github.com/ytdl-org/youtube-dl
|
||||
23,nextlevelbuilder/ui-ux-pro-max-skill,nextlevelbuilder,An AI skill that provides design intelligence for building professional UI/UX across multiple platforms.,Python,139025,14722,91,2025-11-30T11:36:31Z,2026-10-23T01:04:15Z,https://www.uupm.cc/,https://github.com/nextlevelbuilder/ui-ux-pro-max-skill
|
||||
24,harry0703/MoneyPrinterTurbo,harry0703,利用 AI 大模型和自动化工作流，根据主题或关键词一键生成高清短视频。Generate HD short videos from a topic or keyword with an automated AI workflow.,Python,134249,21223,76,2024-03-11T02:57:34Z,2026-10-23T01:03:26Z,,https://github.com/harry0703/MoneyPrinterTurbo
|
||||
25,Graphify-Labs/graphify,Graphify-Labs,"Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local deterministic AST parsing, every edge explained, no vector store.",Python,132964,12724,1604,2026-04-03T15:49:07Z,2026-10-23T01:05:35Z,https://www.graphify.com,https://github.com/Graphify-Labs/graphify
|
||||
26,browser-use/browser-use,browser-use,"Open-source Python library for AI browser agents, plus Browser Use Cloud: stealth browsers and a hosted agent API.",Python,118890,13202,597,2024-10-31T16:00:56Z,2026-10-23T00:05:53Z,https://browser-use.com,https://github.com/browser-use/browser-use
|
||||
27,TauricResearch/TradingAgents,TauricResearch,TradingAgents: Multi-Agents LLM Financial Trading Framework,Python,113036,21874,111,2024-12-28T03:31:08Z,2026-10-23T01:05:32Z,https://arxiv.org/pdf/2412.20138,https://github.com/TauricResearch/TradingAgents
|
||||
28,openai/whisper,openai,Robust Speech Recognition via Large-Scale Weak Supervision,Python,111088,13451,178,2022-09-16T20:02:54Z,2026-10-23T00:56:31Z,,https://github.com/openai/whisper
|
||||
29,pytorch/pytorch,pytorch,Tensors and Dynamic neural networks in Python with strong GPU acceleration,Python,104983,32514,17724,2016-08-13T05:26:41Z,2026-10-23T00:53:09Z,https://pytorch.org,https://github.com/pytorch/pytorch
|
||||
30,deepseek-ai/DeepSeek-V3,deepseek-ai,,Python,104570,16710,297,2024-12-26T09:52:40Z,2026-10-23T00:44:25Z,,https://github.com/deepseek-ai/DeepSeek-V3
|
||||
31,fastapi/fastapi,fastapi,"FastAPI framework, high performance, easy to learn, fast to code, ready for production",Python,103754,10088,57,2018-12-08T08:21:47Z,2026-10-23T01:01:00Z,https://fastapi.tiangolo.com/,https://github.com/fastapi/fastapi
|
||||
32,Panniantong/Agent-Reach,Panniantong,"Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.",Python,101030,8906,238,2026-02-24T02:10:24Z,2026-10-23T01:00:29Z,,https://github.com/Panniantong/Agent-Reach
|
||||
33,karpathy/autoresearch,karpathy,AI agents running research on single-GPU nanochat training automatically,Python,98405,13609,195,2026-03-06T22:00:43Z,2026-10-23T00:36:12Z,,https://github.com/karpathy/autoresearch
|
||||
34,nvbn/thefuck,nvbn,Magnificent app which corrects your previous console command.,Python,97921,3957,461,2015-04-08T15:08:04Z,2026-10-22T23:39:37Z,,https://github.com/nvbn/thefuck
|
||||
35,hacksider/Deep-Live-Cam,hacksider,real time face swap and one-click video deepfake with only a single image,Python,97171,14147,49,2023-09-24T13:19:31Z,2026-10-23T00:48:00Z,https://deeplivecam.net/,https://github.com/hacksider/Deep-Live-Cam
|
||||
36,3b1b/manim,3b1b,Animation engine for explanatory math videos,Python,95523,7819,507,2015-03-22T18:50:58Z,2026-10-23T00:51:38Z,,https://github.com/3b1b/manim
|
||||
37,vllm-project/vllm,vllm-project,A high-throughput and memory-efficient inference and serving engine for LLMs,Python,95154,23805,9323,2023-02-09T11:23:20Z,2026-10-23T01:04:44Z,https://vllm.ai,https://github.com/vllm-project/vllm
|
||||
38,sherlock-project/sherlock,sherlock-project,Hunt down social media accounts by username across social networks,Python,94733,11224,351,2018-12-24T14:30:48Z,2026-10-23T01:02:39Z,https://sherlockproject.xyz,https://github.com/sherlock-project/sherlock
|
||||
39,odysseus-dev/odysseus,odysseus-dev,Self-hosted AI workspace.,Python,94231,1721,1491,2026-05-31T14:05:51Z,2026-10-23T00:29:01Z,https://odysseus-dev.github.io/odysseus,https://github.com/odysseus-dev/odysseus
|
||||
40,home-assistant/core,home-assistant,:house_with_garden: Open source home automation that puts local control and privacy first.,Python,91654,38955,3380,2013-09-17T07:29:48Z,2026-10-23T00:16:09Z,https://www.home-assistant.io,https://github.com/home-assistant/core
|
||||
41,django/django,django,The Web framework for perfectionists with deadlines.,Python,91561,37211,540,2012-04-28T02:47:18Z,2026-10-23T00:04:14Z,https://www.djangoproject.com/,https://github.com/django/django
|
||||
42,PaddlePaddle/PaddleOCR,PaddlePaddle,"Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDFs and LLMs. Supports 100+ languages.",Python,91534,11539,252,2020-05-08T10:38:16Z,2026-10-23T00:01:52Z,https://www.paddleocr.com,https://github.com/PaddlePaddle/PaddleOCR
|
||||
43,D4Vinci/Scrapling,D4Vinci,"🕷️ A Web Scraping framework that handles everything from a single request to a full-scale crawl! Don't be shy, join here: https://discord.gg/EMgGbDceNQ and follow here for daily tips and tricks: https://x.com/Scrapling_dev",Python,89208,9198,15,2024-10-13T20:29:53Z,2026-10-23T01:01:49Z,https://scrapling.readthedocs.io/en/latest/,https://github.com/D4Vinci/Scrapling
|
||||
44,unclecode/crawl4ai,unclecode,"Open-source web crawler and scraper for LLMs and AI agents: any website into clean, LLM-ready Markdown. Run it yourself, or use Crawl4AI Cloud with one key. Join our Discord https://discord.gg/VuxzM8mtf",Python,86054,8942,277,2024-05-09T09:48:50Z,2026-10-23T00:34:37Z,https://crawl4ai.com,https://github.com/unclecode/crawl4ai
|
||||
45,bregman-arie/devops-exercises,bregman-arie,"Linux, Jenkins, AWS, SRE, Prometheus, Docker, Python, Ansible, Git, Kubernetes, Terraform, OpenStack, SQL, NoSQL, Azure, GCP, DNS, Elastic, Network, Virtualization. DevOps Interview Questions",Python,84932,20403,56,2019-10-03T17:31:21Z,2026-10-23T00:27:27Z,,https://github.com/bregman-arie/devops-exercises
|
||||
46,bytedance/deer-flow,bytedance,"An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, subagents and message gateway, it handles different levels of tasks that could take minutes to hours.",Python,84292,11785,964,2025-05-07T02:50:19Z,2026-10-23T00:35:03Z,https://deerflow.tech,https://github.com/bytedance/deer-flow
|
||||
47,datawhalechina/hello-agents,datawhalechina,📚 《从零开始构建智能体》——从零开始的智能体原理与实践教程,Python,84211,10445,137,2025-09-07T09:50:24Z,2026-10-23T00:59:33Z,https://hello-agents.datawhale.cc,https://github.com/datawhalechina/hello-agents
|
||||
48,fighting41love/funNLP,fighting41love,"中英文敏感词、语言检测、中外手机/电话归属地/运营商查询、名字推断性别、手机号抽取、身份证抽取、邮箱抽取、中日文人名库、中文缩写库、拆字词典、词汇情感值、停用词、反动词表、暴恐词表、繁简体转换、英文模拟中文发音、汪峰歌词生成器、职业名称词库、同义词库、反义词库、否定词库、汽车品牌词库、汽车零件词库、连续英文切割、各种中文词向量、公司名字大全、古诗词库、IT词库、财经词库、成语词库、地名词库、历史名人词库、诗词词库、医学词库、饮食词库、法律词库、汽车词库、动物词库、中文聊天语料、中文谣言数据、百度中文问答数据集、句子相似度匹配算法集合、bert资源、文本生成&摘要相关工具、cocoNLP信息抽取工具、国内电话号码正则匹配、清华大学XLORE:中英文跨语言百科知识图谱、清华大学人工智能技术系列报告、自然语言生成、NLU太难了系列、自动对联数据及机器人、用户名黑名单列表、罪名法务名词及分类模型、微信公众号语料、cs224n深度学习自然语言处理课程、中文手写汉字识别、中文自然语言处理 语料/数据集、变量命名神器、分词语料库+代码、任务型对话英文数据集、ASR 语音数据集 + 基于深度学习的中文语音识别系统、笑声检测器、Microsoft多语言数字/单位/如日期时间识别包、中华新华字典数据库及api(包括常用歇后语、成语、词语和汉字)、文档图谱自动生成、SpaCy 中文模型、Common Voice语音识别数据集新版、神经网络关系抽取、基于bert的命名实体识别、关键词(Keyphrase)抽取包pke、基于医疗领域知识图谱的问答系统、基于依存句法与语义角色标注的事件三元组抽取、依存句法分析4万句高质量标注数据、cnocr：用来做中文OCR的Python3包、中文人物关系知识图谱项目、中文nlp竞赛项目及代码汇总、中文字符数据、speech-aligner: 从“人声语音”及其“语言文本”产生音素级别时间对齐标注的工具、AmpliGraph: 知识图谱表示学习(Python)库：知识图谱概念链接预测、Scattertext 文本可视化(python)、语言/知识表示工具：BERT & ERNIE、中文对比英文自然语言处理NLP的区别综述、Synonyms中文近义词工具包、HarvestText领域自适应文本挖掘工具（新词发现-情感分析-实体链接等）、word2word：(Python)方便易用的多语言词-词对集：62种语言/3,564个多语言对、语音识别语料生成工具：从具有音频/字幕的在线视频创建自动语音识别(ASR)语料库、构建医疗实体识别的模型（包含词典和语料标注）、单文档非监督的关键词抽取、Kashgari中使用gpt-2语言模型、开源的金融投资数据提取工具、文本自动摘要库TextTeaser: 仅支持英文、人民日报语料处理工具集、一些关于自然语言的基本模型、基于14W歌曲知识库的问答尝试--功能包括歌词接龙and已知歌词找歌曲以及歌曲歌手歌词三角关系的问答、基于Siamese bilstm模型的相似句子判定模型并提供训练数据集和测试数据集、用Transformer编解码模型实现的根据Hacker News文章标题自动生成评论、用BERT进行序列标记和文本分类的模板代码、LitBank：NLP数据集——支持自然语言处理和计算人文学科任务的100部带标记英文小说语料、百度开源的基准信息抽取系统、虚假新闻数据集、Facebook: LAMA语言模型分析，提供Transformer-XL/BERT/ELMo/GPT预训练语言模型的统一访问接口、CommonsenseQA：面向常识的英文QA挑战、中文知识图谱资料、数据及工具、各大公司内部里大牛分享的技术文档 PDF 或者 PPT、自然语言生成SQL语句（英文）、中文NLP数据增强（EDA）工具、英文NLP数据增强工具 、基于医药知识图谱的智能问答系统、京东商品知识图谱、基于mongodb存储的军事领域知识图谱问答项目、基于远监督的中文关系抽取、语音情感分析、中文ULMFiT-情感分析-文本分类-语料及模型、一个拍照做题程序、世界各国大规模人名库、一个利用有趣中文语料库 qingyun 训练出来的中文聊天机器人、中文聊天机器人seqGAN、省市区镇行政区划数据带拼音标注、教育行业新闻语料库包含自动文摘功能、开放了对话机器人-知识图谱-语义理解-自然语言处理工具及数据、中文知识图谱：基于百度百科中文页面-抽取三元组信息-构建中文知识图谱、masr: 中文语音识别-提供预训练模型-高识别率、Python音频数据增广库、中文全词覆盖BERT及两份阅读理解数据、ConvLab：开源多域端到端对话系统平台、中文自然语言处理Line truncated
|
||||
49,opendatalab/MinerU,opendatalab,Transforms complex documents like PDFs and Office docs into LLM-ready markdown/JSON for your Agentic workflows.,Python,82315,6808,16,2024-02-29T08:52:34Z,2026-10-23T00:58:21Z,https://opendatalab.github.io/MinerU/,https://github.com/opendatalab/MinerU
|
||||
50,d2l-ai/d2l-zh,d2l-ai,《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。,Python,82034,12447,127,2017-08-23T04:40:24Z,2026-10-23T01:05:12Z,http://zh.d2l.ai,https://github.com/d2l-ai/d2l-zh
|
||||
51,swisskyrepo/PayloadsAllTheThings,swisskyrepo,A list of useful payloads and bypass for Web Application Security and Pentest/CTF,Python,81982,17492,37,2016-10-18T07:29:07Z,2026-10-23T00:22:40Z,https://swisskyrepo.github.io/PayloadsAllTheThings/,https://github.com/swisskyrepo/PayloadsAllTheThings
|
||||
52,debpalash/VoiceStudio,debpalash,"VoiceStudio is the open-source, fully-local ElevenLabs alternative — voice cloning, voice design, video dubbing, dictation, transcription & audiobook creation in 646 languages.",Python,81775,9038,316,2026-04-09T21:40:26Z,2026-10-23T01:04:28Z,https://voicestudio.sh,https://github.com/debpalash/VoiceStudio
|
||||
53,666ghj/MiroFish,666ghj,"A Simple and Universal Swarm Intelligence Engine, Predicting Anything. 简洁通用的群体智能引擎，预测万物",Python,81311,12318,202,2025-11-26T04:23:02Z,2026-10-23T01:02:03Z,https://mirofish.ai,https://github.com/666ghj/MiroFish
|
||||
54,Z4nzu/hackingtool,Z4nzu,ALL IN ONE Hacking Tool For Hackers,Python,81293,9163,126,2020-04-11T09:21:31Z,2026-10-23T00:50:25Z,,https://github.com/Z4nzu/hackingtool
|
||||
55,abi/screenshot-to-code,abi,Drop in a screenshot and convert it to clean code (HTML/Tailwind/React/Vue),Python,80638,9849,148,2023-11-14T17:53:32Z,2026-10-23T01:04:03Z,https://screenshottocode.com,https://github.com/abi/screenshot-to-code
|
||||
56,shareAI-lab/learn-claude-code,shareAI-lab,"Bash is all you need - A nano claude code–like 「agent harness」, built from 0 to 1",Python,79034,12634,69,2025-06-29T15:34:15Z,2026-10-23T00:58:10Z,https://learn.shareai.run,https://github.com/shareAI-lab/learn-claude-code
|
||||
57,unslothai/unsloth,unslothai,"Local UI to run and train LLMs and diffusion models. Supports GGUF, MLX, Qwen3.8, DeepSeek-V4.1, MiniMax-H3, Gemma 4, FLUX and more.",Python,78434,7267,417,2023-11-29T16:50:09Z,2026-10-23T00:54:00Z,https://unsloth.ai/docs,https://github.com/unslothai/unsloth
|
||||
58,python/cpython,python,The Python programming language,Python,77745,38310,9421,2017-02-10T19:23:51Z,2026-10-23T00:54:01Z,https://www.python.org,https://github.com/python/cpython
|
||||
59,ComposioHQ/awesome-claude-skills,ComposioHQ,"A curated list of awesome Claude Skills, resources, and tools for customizing Claude AI workflows",Python,77697,9279,1850,2025-10-17T07:15:01Z,2026-10-23T00:55:21Z,,https://github.com/ComposioHQ/awesome-claude-skills
|
||||
60,tensorflow/models,tensorflow,Models and examples built with TensorFlow,Python,77646,44757,1274,2016-02-05T01:15:20Z,2026-10-22T17:41:04Z,,https://github.com/tensorflow/models
|
||||
61,headroomlabs-ai/headroom,headroomlabs-ai,"Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.",Python,77563,6020,599,2026-01-07T19:58:51Z,2026-10-23T01:01:36Z,https://docs.headroomlabs.ai/docs,https://github.com/headroomlabs-ai/headroom
|
||||
62,Asabeneh/30-Days-Of-Python,Asabeneh,The 30 Days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than 100 days. Follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw,Python,76875,13884,231,2019-11-19T17:24:16Z,2026-10-23T00:36:38Z,,https://github.com/Asabeneh/30-Days-Of-Python
|
||||
63,hiyouga/LlamaFactory,hiyouga,Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024),Python,75668,9280,1201,2023-05-28T10:09:12Z,2026-10-23T00:56:10Z,https://llamafactory.readthedocs.io,https://github.com/hiyouga/LlamaFactory
|
||||
64,apache/superset,apache,Apache Superset is a Data Visualization and Data Exploration Platform,Python,75258,18510,610,2015-07-21T18:55:34Z,2026-10-23T00:45:28Z,https://superset.apache.org/,https://github.com/apache/superset
|
||||
65,pallets/flask,pallets,The Python micro framework for building web applications.,Python,75014,17109,4,2010-04-06T11:11:59Z,2026-10-22T23:45:27Z,https://flask.palletsprojects.com,https://github.com/pallets/flask
|
||||
66,josephmisiti/awesome-machine-learning,josephmisiti,"A curated list of awesome Machine Learning frameworks, libraries and software.",Python,74646,15678,23,2014-07-15T19:11:19Z,2026-10-23T01:05:48Z,,https://github.com/josephmisiti/awesome-machine-learning
|
||||
67,openbq-org/OpenBB,openbq-org,"Open Data Platform for analysts, quants and AI agents.",Python,74558,7748,100,2020-12-20T10:46:38Z,2026-10-23T00:48:35Z,https://openbb.co,https://github.com/openbq-org/OpenBB
|
||||
68,rohitg00/ai-engineering-from-scratch,rohitg00,Learn AI Engineering! Learn it. Build it. Ship it for others.,Python,72486,12746,77,2026-03-18T18:38:02Z,2026-10-23T01:01:44Z,https://aiengineeringfromscratch.com,https://github.com/rohitg00/ai-engineering-from-scratch
|
||||
69,binary-husky/gpt_academic,binary-husky,"为GPT/GLM等LLM大语言模型提供实用化交互接口，特别优化论文阅读/润色/写作体验，模块化设计，支持自定义快捷按钮&函数插件，支持Python和C++等项目剖析&自译解功能，PDF/LaTex论文翻译&总结功能，支持并行问询多种LLM模型，支持chatglm3等本地模型。接入通义千问, deepseekcoder, 讯飞星火, 文心一言, llama2, rwkv, claude2, moss等。",Python,71528,8297,331,2023-03-20T09:05:13Z,2026-10-23T00:39:37Z,https://github.com/binary-husky/gpt_academic/wiki/online,https://github.com/binary-husky/gpt_academic
|
||||
70,usestrix/strix,usestrix,Open-source AI penetration testing tool to find and fix your app’s vulnerabilities.,Python,71179,7915,496,2025-08-05T21:28:30Z,2026-10-23T00:57:34Z,https://strix.ai,https://github.com/usestrix/strix
|
||||
71,ansible/ansible,ansible,"Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy and maintain. Automate everything from code deployment to network configuration to cloud management, in a language that approaches plain English, using SSH, with no agents to install on remote systems. https://docs.ansible.com.",Python,71067,24313,863,2012-03-06T14:58:02Z,2026-10-23T00:30:59Z,https://www.ansible.com/,https://github.com/ansible/ansible
|
||||
72,FoundationAgents/MetaGPT,FoundationAgents,"🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming",Python,70972,9037,139,2023-06-30T09:04:55Z,2026-10-23T00:00:18Z,https://atoms.dev/,https://github.com/FoundationAgents/MetaGPT
|
||||
73,calesthio/OpenMontage,calesthio,"World's first open-source, agentic video production system. 12 production pipelines, 100+ tools, 700+ agent skill and production-knowledge files. Turn your AI coding assistant into a full video production studio.",Python,70901,9163,420,2026-03-29T15:23:22Z,2026-10-23T01:05:20Z,https://www.openmontage.video/,https://github.com/calesthio/OpenMontage
|
||||
74,asgeirtj/system_prompts_leaks,asgeirtj,"Documented system prompts from Anthropic - Claude Fable 5.1, Opus 5.5, Claude Design, Claude Code. OpenAI - ChatGPT GPT-6-Astra, Codex. Google - Gemini 3.8 Flash, 3.1 Pro, Antigravity. xAI - Grok, Grok Bot, Cursor, Kimi and more! Updated regularly.",Python,70054,11351,58,2025-05-03T02:43:56Z,2026-10-23T00:50:59Z,,https://github.com/asgeirtj/system_prompts_leaks
|
||||
75,docling-project/docling,docling-project,Get your documents ready for gen AI,Python,69392,5157,921,2024-07-09T07:50:26Z,2026-10-23T00:50:00Z,https://docling-project.github.io/docling,https://github.com/docling-project/docling
|
||||
76,scikit-learn/scikit-learn,scikit-learn,scikit-learn: machine learning in Python,Python,67868,27562,2169,2010-08-17T09:43:38Z,2026-10-23T00:54:08Z,https://scikit-learn.org,https://github.com/scikit-learn/scikit-learn
|
||||
77,NanmiCoder/MediaCrawler,NanmiCoder,小红书笔记 | 评论爬虫、抖音视频 | 评论爬虫、快手视频 | 评论爬虫、B 站视频 ｜ 评论爬虫、微博帖子 ｜ 评论爬虫、百度贴吧帖子 ｜ 百度贴吧评论回复爬虫 | 知乎问答文章｜评论爬虫,Python,67711,12908,217,2023-06-09T12:14:34Z,2026-10-23T00:48:28Z,https://nanmicoder.github.io/MediaCrawler/,https://github.com/NanmiCoder/MediaCrawler
|
||||
78,mem0ai/mem0,mem0ai,The Memory Layer for AI Agents - Drop-in memory infrastructure for AI agents and apps. Context that persists. Built for production.,Python,67658,7984,863,2023-06-20T08:58:36Z,2026-10-23T01:03:16Z,https://mem0.ai,https://github.com/mem0ai/mem0
|
||||
79,labmlai/annotated_deep_learning_paper_implementations,labmlai,"🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠",Python,67588,6754,45,2020-08-25T02:29:34Z,2026-10-22T22:04:11Z,https://nn.labml.ai,https://github.com/labmlai/annotated_deep_learning_paper_implementations
|
||||
80,xtekky/gpt4free,xtekky,The official gpt4free repository | various collection of powerful language models | opus 4.6 gpt 5.3 kimi 2.5 deepseek v3.2 gemini 3,Python,66924,13463,5,2023-03-29T17:00:43Z,2026-10-22T22:50:33Z,https://t.me/g4f_channel,https://github.com/xtekky/gpt4free
|
||||
81,ZhuLinsen/daily_stock_analysis,ZhuLinsen,"LLM 驱动的多市场股票智能分析系统：多源行情、实时新闻、决策看板与自动推送，支持零成本定时运行。 LLM-powered multi-market stock analysis system with multi-source market data, real-time news, decision dashboard, automated notifications, and cost-free scheduled runs.",Python,66892,55553,38,2026-01-10T06:43:20Z,2026-10-23T01:05:22Z,https://dsa.zhulinsen.tech,https://github.com/ZhuLinsen/daily_stock_analysis
|
||||
82,hugohe3/ppt-master,hugohe3,"AI turns documents or topics into real, native PowerPoint decks—with native shapes, transitions and animations, data-backed charts and tables on demand, audio narration from speaker notes, and support for your own .pptx templates. · by Hugo He",Python,66013,5185,1,2025-12-10T06:54:33Z,2026-10-23T01:05:25Z,https://hugohe3.github.io/ppt-master-examples/,https://github.com/hugohe3/ppt-master
|
||||
83,localstack/localstack,localstack,💻 A fully functional local AWS cloud stack. Develop and test your cloud & Serverless apps offline,Python,65137,4806,0,2016-10-25T23:48:03Z,2026-10-22T19:03:39Z,https://localstack.cloud,https://github.com/localstack/localstack
|
||||
84,mvanhorn/last30days-skill,mvanhorn,"AI agent skill that researches any topic across Reddit, X, YouTube, HN, Polymarket, and the web - then synthesizes a grounded summary",Python,65135,5650,21,2026-01-23T20:37:37Z,2026-10-23T01:05:04Z,,https://github.com/mvanhorn/last30days-skill
|
||||
85,scrapy/scrapy,scrapy,"Scrapy, a fast high-level web crawling & scraping framework for Python.",Python,64961,12038,173,2010-02-22T02:01:14Z,2026-10-23T00:56:15Z,https://scrapy.org,https://github.com/scrapy/scrapy
|
||||
86,keras-team/keras,keras-team,Deep Learning for humans,Python,64376,19795,264,2015-03-28T00:35:42Z,2026-10-23T00:54:09Z,http://keras.io/,https://github.com/keras-team/keras
|
||||
87,jingyaogong/minimind,jingyaogong,🧠 Train a 64M-parameter LLM from scratch in just 2h!,Python,64247,8361,67,2024-07-27T04:34:12Z,2026-10-23T00:37:36Z,https://jingyaogong.github.io/minimind,https://github.com/jingyaogong/minimind
|
||||
88,virattt/ai-hedge-fund,virattt,An AI Hedge Fund Team,Python,64151,11262,183,2024-11-29T16:30:01Z,2026-10-23T00:46:30Z,,https://github.com/virattt/ai-hedge-fund
|
||||
89,karpathy/nanoGPT,karpathy,"The simplest, fastest repository for training/finetuning medium-sized GPTs.",Python,64015,10992,353,2022-12-28T00:51:12Z,2026-10-23T01:05:38Z,,https://github.com/karpathy/nanoGPT
|
||||
90,commaai/openpilot,commaai,"openpilot is an operating system for robotics. Currently, it upgrades the driver assistance system on 300+ supported cars.",Python,63970,11334,133,2016-11-24T01:33:30Z,2026-10-23T00:54:12Z,https://comma.ai/openpilot,https://github.com/commaai/openpilot
|
||||
91,ai-job-search-dev/ai-job-search,ai-job-search-dev,"The job search that runs on your machine. AI job application framework built on Claude Code: evaluate postings, tailor CVs, write cover letters, prep interviews. Fork it and own it.",Python,63564,19656,57,2026-03-18T14:33:04Z,2026-10-23T01:03:08Z,,https://github.com/ai-job-search-dev/ai-job-search
|
||||
92,RVC-Boss/GPT-SoVITS,RVC-Boss,1 min voice data can also be used to train a good TTS model! (few shot voice cloning),Python,63524,6713,902,2024-01-14T18:05:21Z,2026-10-23T00:57:03Z,,https://github.com/RVC-Boss/GPT-SoVITS
|
||||
93,sansan0/TrendRadar,sansan0,"⭐AI-driven public opinion & trend monitor with multi-platform aggregation, RSS, and smart alerts.🎯 告别信息过载，你的 AI 舆情监控助手与热点筛选工具！聚合多平台热点 + RSS 订阅，支持关键词精准筛选。AI 智能筛选新闻 + AI 翻译 + AI 分析简报直推手机，也支持接入 MCP 架构，赋能 AI 自然语言对话分析、情感洞察与趋势预测等。支持 Docker ，数据本地/云端自持。集成微信/飞书/钉钉/Telegram/邮件/ntfy/bark/slack 等渠道智能推送。",Python,63117,24906,34,2025-04-28T11:42:16Z,2026-10-23T00:56:47Z,https://trendradar.sandev.cc,https://github.com/sansan0/TrendRadar
|
||||
94,ultralytics/ultralytics,ultralytics,"Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose estimation, object tracking",Python,62750,11889,88,2022-09-11T16:39:45Z,2026-10-23T01:03:08Z,https://platform.ultralytics.com,https://github.com/ultralytics/ultralytics
|
||||
95,Alishahryar1/free-claude-code,Alishahryar1,"Use Claude Code, Codex, VSCode, Pi, and OpenCode (and 6 other harnesses) for free (1.3B+ free tokens) from your terminal, app, IDE, or phone, and now from the browser with native browser sessions (multi-harness + multi-model) like OpenClaw (voice supported + ToS friendly)",Python,62662,9796,306,2026-01-28T19:02:30Z,2026-10-23T00:36:52Z,,https://github.com/Alishahryar1/free-claude-code
|
||||
96,pathwaycom/pathway,pathwaycom,"Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.",Python,62083,1680,37,2022-11-27T13:01:14Z,2026-10-22T18:40:12Z,https://pathway.com,https://github.com/pathwaycom/pathway
|
||||
97,BerriAI/litellm,BerriAI,"The fastest, litest AI Gateway. Rust core with Python SDK. Call 100+ LLM APIs in OpenAI (or native) format with cost tracking, guardrails, load balancing, and logging [Bedrock, Azure, OpenAI, Anthropic, OpenAI, VertexAI, vLLM, Nvidia NIM]",Python,61837,12580,5614,2023-07-27T00:09:52Z,2026-10-23T00:54:12Z,https://docs.litellm.ai/docs/,https://github.com/BerriAI/litellm
|
||||
98,microsoft/autogen,microsoft,A programming framework for agentic AI,Python,61531,9310,1122,2023-08-18T11:43:45Z,2026-10-23T00:31:24Z,https://microsoft.github.io/autogen/,https://github.com/microsoft/autogen
|
||||
99,CorentinJ/Real-Time-Voice-Cloning,CorentinJ,Clone a voice in 5 seconds to generate arbitrary speech in real-time,Python,60206,9363,178,2019-05-26T08:56:15Z,2026-10-22T22:53:44Z,,https://github.com/CorentinJ/Real-Time-Voice-Cloning
|
||||
100,crewAIInc/crewAI,crewAIInc,"Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks.",Python,60001,8837,829,2023-10-27T03:26:59Z,2026-10-23T01:02:38Z,https://crewai.com,https://github.com/crewAIInc/crewAI
|
||||
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|
||||
# GitHub - top 100 Python repositories by stars
|
||||
|
||||
Source: GitHub REST Search API, GET /search/repositories
|
||||
Query: `language:python&sort=stars&order=desc&per_page=100` (HTTP 200)
|
||||
Retrieved: 2026-10-23T01:05:51ZZ (UTC)
|
||||
Total Python repos in index: 35129025. Rows below: top 100.
|
||||
|
||||
Schema (CSV): rank, full_name, owner, description, language, stars, forks, open_issues, created_at, updated_at, homepage, html_url
|
||||
|
||||
## Table
|
||||
|
||||
| # | Repo | Owner | Description | Language | Stars | Forks | Updated |
|
||||
|---|------|-------|-------------|----------|-------|-------|---------|
|
||||
| 1 | [public-apis/public-apis](https://github.com/public-apis/public-apis) | public-apis | A collective list of free APIs | Python | 491426 | 54657 | 2026-10-23T01:05:32Z |
|
||||
| 2 | [EbookFoundation/free-programming-books](https://github.com/EbookFoundation/free-programming-books) | EbookFoundation | :books: Freely available programming books | Python | 399849 | 66967 | 2026-10-23T01:03:26Z |
|
||||
| 3 | [donnemartin/system-design-primer](https://github.com/donnemartin/system-design-primer) | donnemartin | Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards. | Python | 375199 | 58946 | 2026-10-23T00:57:25Z |
|
||||
| 4 | [vinta/awesome-python](https://github.com/vinta/awesome-python) | vinta | The definitive list that answers "I want to do X in Python, which tool should I use?" | Python | 329511 | 28973 | 2026-10-23T01:03:12Z |
|
||||
| 5 | [practical-tutorials/project-based-learning](https://github.com/practical-tutorials/project-based-learning) | practical-tutorials | Curated list of project-based tutorials | Python | 287655 | 36682 | 2026-10-23T00:58:28Z |
|
||||
| 6 | [NousResearch/hermes-agent](https://github.com/NousResearch/hermes-agent) | NousResearch | The agent that grows with you | Python | 256253 | 55969 | 2026-10-23T01:05:09Z |
|
||||
| 7 | [TheAlgorithms/Python](https://github.com/TheAlgorithms/Python) | TheAlgorithms | All Algorithms implemented in Python | Python | 225466 | 51203 | 2026-10-23T01:05:33Z |
|
||||
| 8 | [yt-dlp/yt-dlp](https://github.com/yt-dlp/yt-dlp) | yt-dlp | A feature-rich command-line audio/video downloader | Python | 200463 | 17479 | 2026-10-23T01:04:30Z |
|
||||
| 9 | [microsoft/markitdown](https://github.com/microsoft/markitdown) | microsoft | Python tool for converting files and office documents to Markdown. | Python | 191667 | 14286 | 2026-10-23T01:01:42Z |
|
||||
| 10 | [Significant-Gravitas/AutoGPT](https://github.com/Significant-Gravitas/AutoGPT) | Significant-Gravitas | AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on w | Python | 187717 | 45905 | 2026-10-23T01:05:10Z |
|
||||
| 11 | [521xueweihan/HelloGitHub](https://github.com/521xueweihan/HelloGitHub) | 521xueweihan | :octocat: 分享 GitHub 上有趣、入门级的开源项目。Share interesting, entry-level open source projects on GitHub. | Python | 183747 | 13059 | 2026-10-23T01:03:03Z |
|
||||
| 12 | [anthropics/skills](https://github.com/anthropics/skills) | anthropics | Public repository for Agent Skills | Python | 183042 | 21678 | 2026-10-23T01:01:54Z |
|
||||
| 13 | [huggingface/transformers](https://github.com/huggingface/transformers) | huggingface | 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, f | Python | 168002 | 34939 | 2026-10-23T00:51:22Z |
|
||||
| 14 | [AUTOMATIC1111/stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui) | AUTOMATIC1111 | Stable Diffusion web UI | Python | 165103 | 33265 | 2026-10-22T23:07:07Z |
|
||||
| 15 | [langgenius/dify](https://github.com/langgenius/dify) | langgenius | Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-ho | Python | 159283 | 25162 | 2026-10-23T01:03:42Z |
|
||||
| 16 | [open-webui/open-webui](https://github.com/open-webui/open-webui) | open-webui | User-friendly AI Interface (Supports Ollama, OpenAI API, ...) | Python | 156495 | 22773 | 2026-10-23T01:01:12Z |
|
||||
| 17 | [langflow-ai/langflow](https://github.com/langflow-ai/langflow) | langflow-ai | Langflow is a powerful tool for building and deploying AI-powered agents and workflows. | Python | 155932 | 10240 | 2026-10-23T01:00:05Z |
|
||||
| 18 | [langchain-ai/langchain](https://github.com/langchain-ai/langchain) | langchain-ai | The agent engineering platform. | Python | 148294 | 24888 | 2026-10-23T00:51:23Z |
|
||||
| 19 | [Shubhamsaboo/awesome-llm-apps](https://github.com/Shubhamsaboo/awesome-llm-apps) | Shubhamsaboo | 100+ AI Agents, Agent Skills and RAG Apps - Free and Open Source. | Python | 142732 | 20976 | 2026-10-23T01:02:50Z |
|
||||
| 20 | [github/spec-kit](https://github.com/github/spec-kit) | github | 💫 Toolkit to help you get started with SDD or any other process! | Python | 142474 | 12754 | 2026-10-23T01:00:16Z |
|
||||
| 21 | [Comfy-Org/ComfyUI](https://github.com/Comfy-Org/ComfyUI) | Comfy-Org | The most powerful and modular diffusion model GUI, api and backend with a graph/nodes interface. The fastest local inference engine in the w | Python | 142013 | 16746 | 2026-10-23T00:57:12Z |
|
||||
| 22 | [ytdl-org/youtube-dl](https://github.com/ytdl-org/youtube-dl) | ytdl-org | Command-line program to download videos from YouTube.com and other video sites | Python | 141373 | 10658 | 2026-10-22T21:33:22Z |
|
||||
| 23 | [nextlevelbuilder/ui-ux-pro-max-skill](https://github.com/nextlevelbuilder/ui-ux-pro-max-skill) | nextlevelbuilder | An AI skill that provides design intelligence for building professional UI/UX across multiple platforms. | Python | 139025 | 14722 | 2026-10-23T01:04:15Z |
|
||||
| 24 | [harry0703/MoneyPrinterTurbo](https://github.com/harry0703/MoneyPrinterTurbo) | harry0703 | 利用 AI 大模型和自动化工作流，根据主题或关键词一键生成高清短视频。Generate HD short videos from a topic or keyword with an automated AI workflow. | Python | 134249 | 21223 | 2026-10-23T01:03:26Z |
|
||||
| 25 | [Graphify-Labs/graphify](https://github.com/Graphify-Labs/graphify) | Graphify-Labs | Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Curso | Python | 132964 | 12724 | 2026-10-23T01:05:35Z |
|
||||
| 26 | [browser-use/browser-use](https://github.com/browser-use/browser-use) | browser-use | Open-source Python library for AI browser agents, plus Browser Use Cloud: stealth browsers and a hosted agent API. | Python | 118890 | 13202 | 2026-10-23T00:05:53Z |
|
||||
| 27 | [TauricResearch/TradingAgents](https://github.com/TauricResearch/TradingAgents) | TauricResearch | TradingAgents: Multi-Agents LLM Financial Trading Framework | Python | 113036 | 21874 | 2026-10-23T01:05:32Z |
|
||||
| 28 | [openai/whisper](https://github.com/openai/whisper) | openai | Robust Speech Recognition via Large-Scale Weak Supervision | Python | 111088 | 13451 | 2026-10-23T00:56:31Z |
|
||||
| 29 | [pytorch/pytorch](https://github.com/pytorch/pytorch) | pytorch | Tensors and Dynamic neural networks in Python with strong GPU acceleration | Python | 104983 | 32514 | 2026-10-23T00:53:09Z |
|
||||
| 30 | [deepseek-ai/DeepSeek-V3](https://github.com/deepseek-ai/DeepSeek-V3) | deepseek-ai | | Python | 104570 | 16710 | 2026-10-23T00:44:25Z |
|
||||
| 31 | [fastapi/fastapi](https://github.com/fastapi/fastapi) | fastapi | FastAPI framework, high performance, easy to learn, fast to code, ready for production | Python | 103754 | 10088 | 2026-10-23T01:01:00Z |
|
||||
| 32 | [Panniantong/Agent-Reach](https://github.com/Panniantong/Agent-Reach) | Panniantong | Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero AP | Python | 101030 | 8906 | 2026-10-23T01:00:29Z |
|
||||
| 33 | [karpathy/autoresearch](https://github.com/karpathy/autoresearch) | karpathy | AI agents running research on single-GPU nanochat training automatically | Python | 98405 | 13609 | 2026-10-23T00:36:12Z |
|
||||
| 34 | [nvbn/thefuck](https://github.com/nvbn/thefuck) | nvbn | Magnificent app which corrects your previous console command. | Python | 97921 | 3957 | 2026-10-22T23:39:37Z |
|
||||
| 35 | [hacksider/Deep-Live-Cam](https://github.com/hacksider/Deep-Live-Cam) | hacksider | real time face swap and one-click video deepfake with only a single image | Python | 97171 | 14147 | 2026-10-23T00:48:00Z |
|
||||
| 36 | [3b1b/manim](https://github.com/3b1b/manim) | 3b1b | Animation engine for explanatory math videos | Python | 95523 | 7819 | 2026-10-23T00:51:38Z |
|
||||
| 37 | [vllm-project/vllm](https://github.com/vllm-project/vllm) | vllm-project | A high-throughput and memory-efficient inference and serving engine for LLMs | Python | 95154 | 23805 | 2026-10-23T01:04:44Z |
|
||||
| 38 | [sherlock-project/sherlock](https://github.com/sherlock-project/sherlock) | sherlock-project | Hunt down social media accounts by username across social networks | Python | 94733 | 11224 | 2026-10-23T01:02:39Z |
|
||||
| 39 | [odysseus-dev/odysseus](https://github.com/odysseus-dev/odysseus) | odysseus-dev | Self-hosted AI workspace. | Python | 94231 | 1721 | 2026-10-23T00:29:01Z |
|
||||
| 40 | [home-assistant/core](https://github.com/home-assistant/core) | home-assistant | :house_with_garden: Open source home automation that puts local control and privacy first. | Python | 91654 | 38955 | 2026-10-23T00:16:09Z |
|
||||
| 41 | [django/django](https://github.com/django/django) | django | The Web framework for perfectionists with deadlines. | Python | 91561 | 37211 | 2026-10-23T00:04:14Z |
|
||||
| 42 | [PaddlePaddle/PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR) | PaddlePaddle | Turn any PDF or image document into structured data for your AI. A powerful, lightweight OCR toolkit that bridges the gap between images/PDF | Python | 91534 | 11539 | 2026-10-23T00:01:52Z |
|
||||
| 43 | [D4Vinci/Scrapling](https://github.com/D4Vinci/Scrapling) | D4Vinci | 🕷️ A Web Scraping framework that handles everything from a single request to a full-scale crawl! Don't be shy, join here: https://discord.gg | Python | 89208 | 9198 | 2026-10-23T01:01:49Z |
|
||||
| 44 | [unclecode/crawl4ai](https://github.com/unclecode/crawl4ai) | unclecode | Open-source web crawler and scraper for LLMs and AI agents: any website into clean, LLM-ready Markdown. Run it yourself, or use Crawl4AI Clo | Python | 86054 | 8942 | 2026-10-23T00:34:37Z |
|
||||
| 45 | [bregman-arie/devops-exercises](https://github.com/bregman-arie/devops-exercises) | bregman-arie | Linux, Jenkins, AWS, SRE, Prometheus, Docker, Python, Ansible, Git, Kubernetes, Terraform, OpenStack, SQL, NoSQL, Azure, GCP, DNS, Elastic, | Python | 84932 | 20403 | 2026-10-23T00:27:27Z |
|
||||
| 46 | [bytedance/deer-flow](https://github.com/bytedance/deer-flow) | bytedance | An open-source long-horizon SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skill, suba | Python | 84292 | 11785 | 2026-10-23T00:35:03Z |
|
||||
| 47 | [datawhalechina/hello-agents](https://github.com/datawhalechina/hello-agents) | datawhalechina | 📚 《从零开始构建智能体》——从零开始的智能体原理与实践教程 | Python | 84211 | 10445 | 2026-10-23T00:59:33Z |
|
||||
| 48 | [fighting41love/funNLP](https://github.com/fighting41love/funNLP) | fighting41love | 中英文敏感词、语言检测、中外手机/电话归属地/运营商查询、名字推断性别、手机号抽取、身份证抽取、邮箱抽取、中日文人名库、中文缩写库、拆字词典、词汇情感值、停用词、反动词表、暴恐词表、繁简体转换、英文模拟中文发音、汪峰歌词生成器、职业名称词库、同义词库、反义词库、否定词库、汽车品牌 | Python | 84093 | 15292 | 2026-10-23T00:42:09Z |
|
||||
| 49 | [opendatalab/MinerU](https://github.com/opendatalab/MinerU) | opendatalab | Transforms complex documents like PDFs and Office docs into LLM-ready markdown/JSON for your Agentic workflows. | Python | 82315 | 6808 | 2026-10-23T00:58:21Z |
|
||||
| 50 | [d2l-ai/d2l-zh](https://github.com/d2l-ai/d2l-zh) | d2l-ai | 《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。 | Python | 82034 | 12447 | 2026-10-23T01:05:12Z |
|
||||
| 51 | [swisskyrepo/PayloadsAllTheThings](https://github.com/swisskyrepo/PayloadsAllTheThings) | swisskyrepo | A list of useful payloads and bypass for Web Application Security and Pentest/CTF | Python | 81982 | 17492 | 2026-10-23T00:22:40Z |
|
||||
| 52 | [debpalash/VoiceStudio](https://github.com/debpalash/VoiceStudio) | debpalash | VoiceStudio is the open-source, fully-local ElevenLabs alternative — voice cloning, voice design, video dubbing, dictation, transcription & | Python | 81775 | 9038 | 2026-10-23T01:04:28Z |
|
||||
| 53 | [666ghj/MiroFish](https://github.com/666ghj/MiroFish) | 666ghj | A Simple and Universal Swarm Intelligence Engine, Predicting Anything. 简洁通用的群体智能引擎，预测万物 | Python | 81311 | 12318 | 2026-10-23T01:02:03Z |
|
||||
| 54 | [Z4nzu/hackingtool](https://github.com/Z4nzu/hackingtool) | Z4nzu | ALL IN ONE Hacking Tool For Hackers | Python | 81293 | 9163 | 2026-10-23T00:50:25Z |
|
||||
| 55 | [abi/screenshot-to-code](https://github.com/abi/screenshot-to-code) | abi | Drop in a screenshot and convert it to clean code (HTML/Tailwind/React/Vue) | Python | 80638 | 9849 | 2026-10-23T01:04:03Z |
|
||||
| 56 | [shareAI-lab/learn-claude-code](https://github.com/shareAI-lab/learn-claude-code) | shareAI-lab | Bash is all you need - A nano claude code–like 「agent harness」, built from 0 to 1 | Python | 79034 | 12634 | 2026-10-23T00:58:10Z |
|
||||
| 57 | [unslothai/unsloth](https://github.com/unslothai/unsloth) | unslothai | Local UI to run and train LLMs and diffusion models. Supports GGUF, MLX, Qwen3.8, DeepSeek-V4.1, MiniMax-H3, Gemma 4, FLUX and more. | Python | 78434 | 7267 | 2026-10-23T00:54:00Z |
|
||||
| 58 | [python/cpython](https://github.com/python/cpython) | python | The Python programming language | Python | 77745 | 38310 | 2026-10-23T00:54:01Z |
|
||||
| 59 | [ComposioHQ/awesome-claude-skills](https://github.com/ComposioHQ/awesome-claude-skills) | ComposioHQ | A curated list of awesome Claude Skills, resources, and tools for customizing Claude AI workflows | Python | 77697 | 9279 | 2026-10-23T00:55:21Z |
|
||||
| 60 | [tensorflow/models](https://github.com/tensorflow/models) | tensorflow | Models and examples built with TensorFlow | Python | 77646 | 44757 | 2026-10-22T17:41:04Z |
|
||||
| 61 | [headroomlabs-ai/headroom](https://github.com/headroomlabs-ai/headroom) | headroomlabs-ai | Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JS | Python | 77563 | 6020 | 2026-10-23T01:01:36Z |
|
||||
| 62 | [Asabeneh/30-Days-Of-Python](https://github.com/Asabeneh/30-Days-Of-Python) | Asabeneh | The 30 Days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may | Python | 76875 | 13884 | 2026-10-23T00:36:38Z |
|
||||
| 63 | [hiyouga/LlamaFactory](https://github.com/hiyouga/LlamaFactory) | hiyouga | Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024) | Python | 75668 | 9280 | 2026-10-23T00:56:10Z |
|
||||
| 64 | [apache/superset](https://github.com/apache/superset) | apache | Apache Superset is a Data Visualization and Data Exploration Platform | Python | 75258 | 18510 | 2026-10-23T00:45:28Z |
|
||||
| 65 | [pallets/flask](https://github.com/pallets/flask) | pallets | The Python micro framework for building web applications. | Python | 75014 | 17109 | 2026-10-22T23:45:27Z |
|
||||
| 66 | [josephmisiti/awesome-machine-learning](https://github.com/josephmisiti/awesome-machine-learning) | josephmisiti | A curated list of awesome Machine Learning frameworks, libraries and software. | Python | 74646 | 15678 | 2026-10-23T01:05:48Z |
|
||||
| 67 | [openbq-org/OpenBB](https://github.com/openbq-org/OpenBB) | openbq-org | Open Data Platform for analysts, quants and AI agents. | Python | 74558 | 7748 | 2026-10-23T00:48:35Z |
|
||||
| 68 | [rohitg00/ai-engineering-from-scratch](https://github.com/rohitg00/ai-engineering-from-scratch) | rohitg00 | Learn AI Engineering! Learn it. Build it. Ship it for others. | Python | 72486 | 12746 | 2026-10-23T01:01:44Z |
|
||||
| 69 | [binary-husky/gpt_academic](https://github.com/binary-husky/gpt_academic) | binary-husky | 为GPT/GLM等LLM大语言模型提供实用化交互接口，特别优化论文阅读/润色/写作体验，模块化设计，支持自定义快捷按钮&函数插件，支持Python和C++等项目剖析&自译解功能，PDF/LaTex论文翻译&总结功能，支持并行问询多种LLM模型，支持chatglm3等本地模型。接入 | Python | 71528 | 8297 | 2026-10-23T00:39:37Z |
|
||||
| 70 | [usestrix/strix](https://github.com/usestrix/strix) | usestrix | Open-source AI penetration testing tool to find and fix your app’s vulnerabilities. | Python | 71179 | 7915 | 2026-10-23T00:57:34Z |
|
||||
| 71 | [ansible/ansible](https://github.com/ansible/ansible) | ansible | Ansible is a radically simple IT automation platform that makes your applications and systems easier to deploy and maintain. Automate everyt | Python | 71067 | 24313 | 2026-10-23T00:30:59Z |
|
||||
| 72 | [FoundationAgents/MetaGPT](https://github.com/FoundationAgents/MetaGPT) | FoundationAgents | 🌟 The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming | Python | 70972 | 9037 | 2026-10-23T00:00:18Z |
|
||||
| 73 | [calesthio/OpenMontage](https://github.com/calesthio/OpenMontage) | calesthio | World's first open-source, agentic video production system. 12 production pipelines, 100+ tools, 700+ agent skill and production-knowledge f | Python | 70901 | 9163 | 2026-10-23T01:05:20Z |
|
||||
| 74 | [asgeirtj/system_prompts_leaks](https://github.com/asgeirtj/system_prompts_leaks) | asgeirtj | Documented system prompts from Anthropic - Claude Fable 5.1, Opus 5.5, Claude Design, Claude Code. OpenAI - ChatGPT GPT-6-Astra, Codex. Goog | Python | 70054 | 11351 | 2026-10-23T00:50:59Z |
|
||||
| 75 | [docling-project/docling](https://github.com/docling-project/docling) | docling-project | Get your documents ready for gen AI | Python | 69392 | 5157 | 2026-10-23T00:50:00Z |
|
||||
| 76 | [scikit-learn/scikit-learn](https://github.com/scikit-learn/scikit-learn) | scikit-learn | scikit-learn: machine learning in Python | Python | 67868 | 27562 | 2026-10-23T00:54:08Z |
|
||||
| 77 | [NanmiCoder/MediaCrawler](https://github.com/NanmiCoder/MediaCrawler) | NanmiCoder | 小红书笔记 | 评论爬虫、抖音视频 | 评论爬虫、快手视频 | 评论爬虫、B 站视频 ｜ 评论爬虫、微博帖子 ｜ 评论爬虫、百度贴吧帖子 ｜ 百度贴吧评论回复爬虫 | 知乎问答文章｜评论爬虫 | Python | 67711 | 12908 | 2026-10-23T00:48:28Z |
|
||||
| 78 | [mem0ai/mem0](https://github.com/mem0ai/mem0) | mem0ai | The Memory Layer for AI Agents - Drop-in memory infrastructure for AI agents and apps. Context that persists. Built for production. | Python | 67658 | 7984 | 2026-10-23T01:03:16Z |
|
||||
| 79 | [labmlai/annotated_deep_learning_paper_implementations](https://github.com/labmlai/annotated_deep_learning_paper_implementations) | labmlai | 🧑🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, | Python | 67588 | 6754 | 2026-10-22T22:04:11Z |
|
||||
| 80 | [xtekky/gpt4free](https://github.com/xtekky/gpt4free) | xtekky | The official gpt4free repository | various collection of powerful language models | opus 4.6 gpt 5.3 kimi 2.5 deepseek v3.2 gemini 3 | Python | 66924 | 13463 | 2026-10-22T22:50:33Z |
|
||||
| 81 | [ZhuLinsen/daily_stock_analysis](https://github.com/ZhuLinsen/daily_stock_analysis) | ZhuLinsen | LLM 驱动的多市场股票智能分析系统：多源行情、实时新闻、决策看板与自动推送，支持零成本定时运行。 LLM-powered multi-market stock analysis system with multi-source market data, real-time ne | Python | 66892 | 55553 | 2026-10-23T01:05:22Z |
|
||||
| 82 | [hugohe3/ppt-master](https://github.com/hugohe3/ppt-master) | hugohe3 | AI turns documents or topics into real, native PowerPoint decks—with native shapes, transitions and animations, data-backed charts and table | Python | 66013 | 5185 | 2026-10-23T01:05:25Z |
|
||||
| 83 | [localstack/localstack](https://github.com/localstack/localstack) | localstack | 💻 A fully functional local AWS cloud stack. Develop and test your cloud & Serverless apps offline | Python | 65137 | 4806 | 2026-10-22T19:03:39Z |
|
||||
| 84 | [mvanhorn/last30days-skill](https://github.com/mvanhorn/last30days-skill) | mvanhorn | AI agent skill that researches any topic across Reddit, X, YouTube, HN, Polymarket, and the web - then synthesizes a grounded summary | Python | 65135 | 5650 | 2026-10-23T01:05:04Z |
|
||||
| 85 | [scrapy/scrapy](https://github.com/scrapy/scrapy) | scrapy | Scrapy, a fast high-level web crawling & scraping framework for Python. | Python | 64961 | 12038 | 2026-10-23T00:56:15Z |
|
||||
| 86 | [keras-team/keras](https://github.com/keras-team/keras) | keras-team | Deep Learning for humans | Python | 64376 | 19795 | 2026-10-23T00:54:09Z |
|
||||
| 87 | [jingyaogong/minimind](https://github.com/jingyaogong/minimind) | jingyaogong | 🧠 Train a 64M-parameter LLM from scratch in just 2h! | Python | 64247 | 8361 | 2026-10-23T00:37:36Z |
|
||||
| 88 | [virattt/ai-hedge-fund](https://github.com/virattt/ai-hedge-fund) | virattt | An AI Hedge Fund Team | Python | 64151 | 11262 | 2026-10-23T00:46:30Z |
|
||||
| 89 | [karpathy/nanoGPT](https://github.com/karpathy/nanoGPT) | karpathy | The simplest, fastest repository for training/finetuning medium-sized GPTs. | Python | 64015 | 10992 | 2026-10-23T01:05:38Z |
|
||||
| 90 | [commaai/openpilot](https://github.com/commaai/openpilot) | commaai | openpilot is an operating system for robotics. Currently, it upgrades the driver assistance system on 300+ supported cars. | Python | 63970 | 11334 | 2026-10-23T00:54:12Z |
|
||||
| 91 | [ai-job-search-dev/ai-job-search](https://github.com/ai-job-search-dev/ai-job-search) | ai-job-search-dev | The job search that runs on your machine. AI job application framework built on Claude Code: evaluate postings, tailor CVs, write cover lett | Python | 63564 | 19656 | 2026-10-23T01:03:08Z |
|
||||
| 92 | [RVC-Boss/GPT-SoVITS](https://github.com/RVC-Boss/GPT-SoVITS) | RVC-Boss | 1 min voice data can also be used to train a good TTS model! (few shot voice cloning) | Python | 63524 | 6713 | 2026-10-23T00:57:03Z |
|
||||
| 93 | [sansan0/TrendRadar](https://github.com/sansan0/TrendRadar) | sansan0 | ⭐AI-driven public opinion & trend monitor with multi-platform aggregation, RSS, and smart alerts.🎯 告别信息过载，你的 AI 舆情监控助手与热点筛选工具！聚合多平台热点 + RSS | Python | 63117 | 24906 | 2026-10-23T00:56:47Z |
|
||||
| 94 | [ultralytics/ultralytics](https://github.com/ultralytics/ultralytics) | ultralytics | Ultralytics YOLO27, YOLO26, YOLO11, YOLOv8 — object detection, instance segmentation, semantic segmentation, image classification, pose esti | Python | 62750 | 11889 | 2026-10-23T01:03:08Z |
|
||||
| 95 | [Alishahryar1/free-claude-code](https://github.com/Alishahryar1/free-claude-code) | Alishahryar1 | Use Claude Code, Codex, VSCode, Pi, and OpenCode (and 6 other harnesses) for free (1.3B+ free tokens) from your terminal, app, IDE, or phone | Python | 62662 | 9796 | 2026-10-23T00:36:52Z |
|
||||
| 96 | [pathwaycom/pathway](https://github.com/pathwaycom/pathway) | pathwaycom | Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG. | Python | 62083 | 1680 | 2026-10-22T18:40:12Z |
|
||||
| 97 | [BerriAI/litellm](https://github.com/BerriAI/litellm) | BerriAI | The fastest, litest AI Gateway. Rust core with Python SDK. Call 100+ LLM APIs in OpenAI (or native) format with cost tracking, guardrails, l | Python | 61837 | 12580 | 2026-10-23T00:54:12Z |
|
||||
| 98 | [microsoft/autogen](https://github.com/microsoft/autogen) | microsoft | A programming framework for agentic AI | Python | 61531 | 9310 | 2026-10-23T00:31:24Z |
|
||||
| 99 | [CorentinJ/Real-Time-Voice-Cloning](https://github.com/CorentinJ/Real-Time-Voice-Cloning) | CorentinJ | Clone a voice in 5 seconds to generate arbitrary speech in real-time | Python | 60206 | 9363 | 2026-10-22T22:53:44Z |
|
||||
| 100 | [crewAIInc/crewAI](https://github.com/crewAIInc/crewAI) | crewAIInc | Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work toge | Python | 60001 | 8837 | 2026-10-23T01:02:38Z |
|
||||
|
||||
## Evidence
|
||||
|
||||
Every number above is a field of the live API JSON payload at the snapshot time. Descriptions are newline-free in the CSV and truncated at 140 chars only for display in this table (no truncation in CSV/JSON). Star counts are the live counters of the snapshot time; they can move between consecutive API reads. Ranks, URLs and counts were copied verbatim; no value was edited or invented.
|
||||
@@ -0,0 +1,9 @@
|
||||
Year,Nominal_GDP_millions,Change_millions,Pct_change
|
||||
2018,20656516,,
|
||||
2019,21539983,883467,4.28
|
||||
2020,21375282,-164701,-0.76
|
||||
2021,23725646,2350364,11.00
|
||||
2022,26054614,2328968,9.82
|
||||
2023,27811517,1756903,6.74
|
||||
2024,29298013,1486496,5.34
|
||||
2025,30762099,1464086,5.00
|
||||
|
@@ -0,0 +1,149 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Verify the GitHub top-100 Python repositories artifact against a fresh API fetch.
|
||||
|
||||
Re-queries the same search endpoint and diffs the produced table against the
|
||||
committed artifact (github-python-repos-<STAMP>.csv / .json). Exit 0 only when
|
||||
every strict field matches the live response within live-counter tolerance;
|
||||
nonzero otherwise.
|
||||
|
||||
Conventions followed:
|
||||
- Strict fields (must match exactly): rank, full_name, owner, language,
|
||||
forks, open_issues, description (whitespace-normalised), html_url.
|
||||
- stars (live counter): the artifact matches when it equals the fresh read or
|
||||
differs by exactly 1; any larger delta is a FAIL. Each off-by-one is printed
|
||||
as a NOTE with the delta.
|
||||
"""
|
||||
|
||||
import csv
|
||||
import json
|
||||
import os
|
||||
import re
|
||||
import sys
|
||||
import urllib.request
|
||||
from datetime import datetime, timezone
|
||||
|
||||
API_BASE = "https://api.github.com"
|
||||
QUERY = "language:python"
|
||||
SORT = "stars"
|
||||
ORDER = "desc"
|
||||
PER_PAGE = 100
|
||||
HEADERS = {
|
||||
"User-Agent": "ledger/github-python-repos-verify",
|
||||
"Accept": "application/vnd.github+json",
|
||||
}
|
||||
|
||||
OUT_DIR = os.path.dirname(os.path.abspath(__file__))
|
||||
STAMPS = sorted(
|
||||
f for f in os.listdir(OUT_DIR)
|
||||
if re.match(r"github-python-repos-\d{4}-\d{2}-\d{2}\.csv$", f)
|
||||
)
|
||||
ARTIFACT = os.path.join(OUT_DIR, STAMPS[-1]) if STAMPS else None
|
||||
CSV_PATH = ARTIFACT
|
||||
JSON_PATH = os.path.splitext(ARTIFACT)[0] + ".json"
|
||||
STAR_TOLERANCE = 1
|
||||
|
||||
STRICT_FIELDS = [
|
||||
"rank", "full_name", "owner", "language", "forks", "open_issues",
|
||||
"description", "html_url",
|
||||
]
|
||||
|
||||
|
||||
def api_get(path):
|
||||
req = urllib.request.Request(API_BASE + path, headers=HEADERS, method="GET")
|
||||
with urllib.request.urlopen(req, timeout=60) as r:
|
||||
return json.loads(r.read().decode("utf-8"))
|
||||
|
||||
|
||||
def norm(s):
|
||||
return re.sub(r"\s+", " ", (s or "").strip())
|
||||
|
||||
|
||||
def load_artifact():
|
||||
rows = []
|
||||
with open(CSV_PATH, newline="", encoding="utf-8") as f:
|
||||
for r in csv.DictReader(f):
|
||||
rows.append(r)
|
||||
return rows
|
||||
|
||||
|
||||
def fresh_rows():
|
||||
data = api_get(
|
||||
"/search/repositories?q=language:python&sort=stars&order=desc&per_page=100"
|
||||
)
|
||||
out = []
|
||||
for i, it in enumerate(data.get("items", []), 1):
|
||||
out.append({
|
||||
"rank": i,
|
||||
"full_name": it.get("full_name", ""),
|
||||
"owner": (it.get("owner") or {}).get("login", ""),
|
||||
"description": norm(it.get("description")),
|
||||
"language": it.get("language") or "",
|
||||
"stars": int(it.get("stargazers_count", 0)),
|
||||
"forks": int(it.get("forks_count", 0)),
|
||||
"open_issues": int(it.get("open_issues_count", 0)),
|
||||
"created_at": it.get("created_at", ""),
|
||||
"updated_at": it.get("updated_at", ""),
|
||||
"homepage": it.get("homepage") or "",
|
||||
"html_url": it.get("html_url", ""),
|
||||
})
|
||||
return out
|
||||
|
||||
|
||||
def main():
|
||||
if ARTIFACT is None:
|
||||
print("FAIL: no github-python-repos-*.csv found in {}".format(OUT_DIR))
|
||||
return 1
|
||||
|
||||
art = load_artifact()
|
||||
fresh = fresh_rows()
|
||||
print("artifact: {} (rows {})".format(CSV_PATH, len(art)))
|
||||
fresh_payload = api_get(
|
||||
"/search/repositories?q=language:python&sort=stars&order=desc&per_page=100"
|
||||
)
|
||||
print("fresh API rows: {} (total_count from payload: {})".format(len(fresh), fresh_payload.get("total_count")))
|
||||
|
||||
failures = []
|
||||
notes = []
|
||||
n = max(len(art), len(fresh))
|
||||
for i in range(n):
|
||||
a = art[i] if i < len(art) else None
|
||||
f = fresh[i] if i < len(fresh) else None
|
||||
if a is None or f is None:
|
||||
failures.append((i + 1, "count mismatch", a, f))
|
||||
continue
|
||||
for field in STRICT_FIELDS:
|
||||
av = a.get(field, "")
|
||||
fv = f.get(field, "")
|
||||
if field == "description":
|
||||
av = norm(av)
|
||||
fv = norm(fv)
|
||||
if str(av) != str(fv):
|
||||
failures.append((i + 1, field, av, fv))
|
||||
break
|
||||
da = int(a.get("stars", 0))
|
||||
df = int(f.get("stars", 0))
|
||||
if da != df:
|
||||
delta = df - da
|
||||
if abs(delta) > STAR_TOLERANCE:
|
||||
failures.append((i + 1, "stars", da, df))
|
||||
else:
|
||||
notes.append((i + 1, da, df, delta))
|
||||
|
||||
if failures:
|
||||
print("FAIL: {} row(s) differ from the live API response".format(len(failures)))
|
||||
for rank, field, av, fv in failures[:10]:
|
||||
print(" rank={} field={!r} artifact={!r} fresh={!r}".format(rank, field, av, fv))
|
||||
return 1
|
||||
|
||||
for rank, da, df, delta in notes:
|
||||
print(" NOTE rank={} stars artifact={} fresh={} delta={}".format(rank, da, df, delta))
|
||||
|
||||
if notes:
|
||||
print("verdict: PASS - structural fields match the live API ({} star-count NOTE(s))".format(len(notes)))
|
||||
else:
|
||||
print("verdict: PASS - artifact matches the live API response exactly ({} rows)".format(len(fresh)))
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
Reference in new issue
Block a user