✨ v2024.09.19 🏛️

README.md

@@ -55,10 +55,10 @@ Whether you're conducting legal research, developing AI models, or simply intere
 
 | Jurisdiction | Jurisprudences | Oldest | Latest | Tokens | JSONL (gzipped) | Parquet |
 |--------------|----------------|--------|--------|--------|-----------------|---------|
-| Cour d'Appel | 375,557 | 1996-03-25 | 2024-08-13 | 1,884,212,261 | [Download (1.65 GB)](https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/cour_d_appel.jsonl.gz?download=true) | [Download (2.76 GB)](https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/cour_d_appel.parquet?download=true) |
-| Tribunal Judiciaire | 65,342 | 2023-12-14 | 2024-09-12 | 234,224,355 | [Download (209.11 MB)](https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/tribunal_judiciaire.jsonl.gz?download=true) | [Download (348.84 MB)](https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/tribunal_judiciaire.parquet?download=true) |
-| Cour de Cassation | 534,788 | 1860-08-01 | 2024-09-12 | 1,104,650,024 | [Download (929.61 MB)](https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/cour_de_cassation.jsonl.gz?download=true) | [Download (1.57 GB)](https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/cour_de_cassation.parquet?download=true) |
-| **Total** | **975,687** | **1860-08-01** | **2024-09-12** | **3,223,086,640** | **2.76 GB** | **4.67 GB** |
+| Cour d'Appel | 381,768 | 1996-03-25 | 2024-09-13 | 1,911,897,207 | [Download (1.67 GB)](https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/cour_d_appel.jsonl.gz?download=true) | [Download (2.80 GB)](https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/cour_d_appel.parquet?download=true) |
+| Tribunal Judiciaire | 65,343 | 2023-12-14 | 2024-09-12 | 234,306,537 | [Download (209.21 MB)](https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/tribunal_judiciaire.jsonl.gz?download=true) | [Download (349.09 MB)](https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/tribunal_judiciaire.parquet?download=true) |
+| Cour de Cassation | 534,787 | 1860-08-01 | 2024-09-12 | 1,104,517,382 | [Download (929.35 MB)](https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/cour_de_cassation.jsonl.gz?download=true) | [Download (1.57 GB)](https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/cour_de_cassation.parquet?download=true) |
+| **Total** | **981,898** | **1860-08-01** | **2024-09-13** | **3,250,721,126** | **2.79 GB** | **4.71 GB** |
 
 <i>Latest update date: 2024-09-19</i>
 

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v2024.09.12.md

@@ -0,0 +1,87 @@
+<p align="center"><img src="https://raw.githubusercontent.com/antoinejeannot/jurisprudence/artefacts/jurisprudence.svg" width=650></p>
+
+[![Dataset on HF](https://huggingface.co/datasets/huggingface/badges/resolve/main/dataset-on-hf-md-dark.svg)](https://huggingface.co/datasets/antoinejeannot/jurisprudence) [![GitHub](https://img.shields.io/badge/github-%23121011.svg?style=for-the-badge&logo=github&logoColor=white)](https://github.com/antoinejeannot/jurisprudence)
+
+# ✨ Jurisprudence, release v2024.09.12 🏛️
+
+Jurisprudence is an open-source project that automates the collection and distribution of French legal decisions. It leverages the Judilibre API provided by the Cour de Cassation to:
+
+- Fetch rulings from major French courts (Cour de Cassation, Cour d'Appel, Tribunal Judiciaire)
+- Process and convert the data into easily accessible formats
+- Publish & version updated datasets on Hugging Face every few days.
+
+It aims to democratize access to legal information, enabling researchers, legal professionals and the public to easily access and analyze French court decisions.
+Whether you're conducting legal research, developing AI models, or simply interested in French jurisprudence, this project might provide a valuable, open resource for exploring the French legal landscape.
+
+## 📊 Exported Data
+
+| Jurisdiction | Jurisprudences | Oldest | Latest | Tokens | JSONL (gzipped) | Parquet |
+|--------------|----------------|--------|--------|--------|-----------------|---------|
+| **Total** | **0** | **9999-12-31** | **1-01-01** | **0** | **0.00 B** | **0.00 B** |
+
+<i>Latest update date: 2024-09-12</i>
+
+<i># Tokens are computed using GPT-4 tiktoken and the `text` column.</i>
+
+## 🤗 Hugging Face Dataset
+
+The up-to-date jurisprudences dataset is available at: https://huggingface.co/datasets/antoinejeannot/jurisprudence in JSONL (gzipped) and parquet formats.
+
+This allows you to easily fetch, query, process and index all jurisprudences in the blink of an eye!
+
+### Usage Examples
+#### HuggingFace Datasets
+```python
+# pip install datasets
+import datasets
+
+dataset = load_dataset("antoinejeannot/jurisprudence")
+dataset.shape
+>> {'tribunal_judiciaire': (58986, 33),
+'cour_d_appel': (378392, 33),
+'cour_de_cassation': (534258, 33)}
+
+# alternatively, you can load each jurisdiction separately
+cour_d_appel = load_dataset("antoinejeannot/jurisprudence", "cour_d_appel")
+tribunal_judiciaire = load_dataset("antoinejeannot/jurisprudence", "tribunal_judiciaire")
+cour_de_cassation = load_dataset("antoinejeannot/jurisprudence", "cour_de_cassation") 
+```
+
+Leveraging datasets allows you to easily ingest data to [PyTorch](https://huggingface.co/docs/datasets/use_with_pytorch), [Tensorflow](https://huggingface.co/docs/datasets/use_with_tensorflow), [Jax](https://huggingface.co/docs/datasets/use_with_jax) etc.
+
+#### BYOL: Bring Your Own Lib
+For analysis, using polars, pandas or duckdb is quite common and also possible:
+```python
+url = "https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/cour_de_cassation.parquet"  # or tribunal_judiciaire.parquet, cour_d_appel.parquet
+
+# pip install polars
+import polars as pl
+df = pl.scan_parquet(url)
+
+# pip install pandas
+import pandas as pd
+df = pd.read_parquet(url)
+
+# pip install duckdb
+import duckdb
+table = duckdb.read_parquet(url)
+```
+
+## 🪪 Citing & Authors
+
+If you use this code in your research, please use the following BibTeX entry:
+```bibtex
+@misc{antoinejeannot2024,
+author = {Jeannot Antoine and {Cour de Cassation}},
+title = {Jurisprudence},
+year = {2024},
+howpublished = {\url{https://github.com/antoinejeannot/jurisprudence}},
+note = {Data source: API Judilibre, \url{https://www.data.gouv.fr/en/datasets/api-judilibre/}}
+}
+```
+
+This project relies on the [Judilibre API par la Cour de Cassation](https://www.data.gouv.fr/en/datasets/api-judilibre/), which is made available under the Open License 2.0 (Licence Ouverte 2.0)
+
+It scans the API every 3 days at midnight UTC and exports its data in various formats to Hugging Face, without any fundamental transformation but conversions.
+
+<p align="center"><a href="https://www.etalab.gouv.fr/licence-ouverte-open-licence/"><img src="https://raw.githubusercontent.com/antoinejeannot/jurisprudence/artefacts/license.png" width=50 alt="license ouverte / open license"></a></p>