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UV scripts for analyzing HuggingFace datasets using streaming mode.
Scripts
finepdfs-stats.py - Temporal Educational Quality Analysis
Analyze educational quality trends across CommonCrawl dumps using Polars streaming. Answers: "Is the web getting more educational over time?"
Features:
- Polars streaming (no download of 300GB+ dataset)
- Temporal analysis across 106 CommonCrawl dumps (2013-2025)
- ASCII chart visualizations
- Uploads results to HF Hub with auto-generated dataset card
- Supports single language or all 70+ languages
Quick Examples:
# Quick test (10K samples)
uv run https://huggingface.co/datasets/uv-scripts/dataset-stats/raw/main/finepdfs-stats.py \
--limit 10000 --show-plan
# Analyze English PDFs
uv run https://huggingface.co/datasets/uv-scripts/dataset-stats/raw/main/finepdfs-stats.py \
--output-repo username/my-stats
# Analyze ALL 70+ languages
uv run https://huggingface.co/datasets/uv-scripts/dataset-stats/raw/main/finepdfs-stats.py \
--all-languages --output-repo username/my-stats
Run on HF Jobs (recommended for full dataset):
hf jobs uv run \
-s HF_TOKEN \
-e HF_XET_HIGH_PERFORMANCE=1 \
https://huggingface.co/datasets/uv-scripts/dataset-stats/raw/main/finepdfs-stats.py \
-- --all-languages --output-repo username/finepdfs-temporal-stats
Example output: davanstrien/finepdfs-temporal-stats-all
Performance:
- 50M docs in
14 minutes (60K docs/sec) - Single scan using Polars HF Hub integration
- Works on HF Jobs CPU instances
Related Scripts
Check out other scripts in the uv-scripts organization:
- dataset-creation: Create datasets from PDFs and other formats
- vllm: GPU-accelerated classification and inference
- ocr: Document OCR using vision-language models
Why UV Scripts?
UV scripts are self-contained Python scripts that:
- Run with a single
uv runcommand (no setup required) - Include all dependencies in PEP 723 inline metadata
- Work seamlessly on both local machines and HF Jobs
Learn more about UV: https://docs.astral.sh/uv/
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