Datasets:
Download code/harvest.py from kavyabhand/spacerot: direct link, hf CLI and curl.
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- Download file 1.65 kB
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https://huggingface.co/datasets/kavyabhand/spacerot/resolve/main/code/harvest.py
- Command line
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hf download hf://datasets/kavyabhand/spacerot/code/harvest.py
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curl -L -o harvest.py https://huggingface.co/datasets/kavyabhand/spacerot/resolve/main/code/harvest.py
1.65 kB
| """Census of the most-liked Hugging Face Spaces: which are broken, and why (public runtime error).""" | |
| import json, sys, time, concurrent.futures as cf | |
| import requests | |
| N = int(sys.argv[1]) if len(sys.argv) > 1 else 10000 | |
| OUT = sys.argv[2] if len(sys.argv) > 2 else "/data/census.json" | |
| BROKEN = {"RUNTIME_ERROR", "BUILD_ERROR", "CONFIG_ERROR"} | |
| S = requests.Session() | |
| url = ("https://huggingface.co/api/spaces?limit=1000&sort=likes&direction=-1" | |
| "&expand[]=runtime&expand[]=sdk&expand[]=likes&expand[]=lastModified") | |
| rows = [] | |
| while url and len(rows) < N: | |
| r = S.get(url, timeout=60) | |
| r.raise_for_status() | |
| for s in r.json(): | |
| rt = s.get("runtime") or {} | |
| rows.append({"id": s["id"], "likes": s.get("likes", 0), "sdk": s.get("sdk"), | |
| "stage": rt.get("stage"), "hw": (rt.get("hardware") or {}).get("requested"), | |
| "err": rt.get("errorMessage"), "lastModified": s.get("lastModified")}) | |
| url = r.links.get("next", {}).get("url") | |
| rows = rows[:N] | |
| def err_for(row): | |
| for attempt in range(5): | |
| r = S.get(f"https://huggingface.co/api/spaces/{row['id']}/runtime", timeout=30) | |
| if r.status_code == 429: | |
| time.sleep(2 + attempt * 3) | |
| continue | |
| if r.ok: | |
| row["err"] = r.json().get("errorMessage") | |
| return row | |
| row["err"] = "FETCHFAIL" | |
| return row | |
| need = [r for r in rows if r["stage"] in BROKEN and not r["err"]] | |
| with cf.ThreadPoolExecutor(4) as ex: | |
| list(ex.map(err_for, need)) | |
| json.dump(rows, open(OUT, "w")) | |
| from collections import Counter | |
| print(len(rows), Counter(r["stage"] for r in rows).most_common()) | |