✨ v2024.09.10 🏛️

README.md

@@ -36,7 +36,14 @@ configs:
 
 <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)
+<p align="center">
+  <a href="https://huggingface.co/datasets/antoinejeannot/jurisprudence">
+    <img src="https://huggingface.co/datasets/huggingface/badges/resolve/main/dataset-on-hf-md-dark.svg" alt="Dataset on HF">
+  </a>
+  <a href="https://github.com/antoinejeannot/jurisprudence">
+    <img src="https://img.shields.io/badge/github-%23121011.svg?style=for-the-badge&logo=github&logoColor=white" alt="GitHub">
+  </a>
+</p>
 
 # ✨ Jurisprudence, release v2024.09.10 🏛️
 
@@ -44,27 +51,68 @@ Jurisprudence is an open-source project that automates the collection and distri
 
 - 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 3 days
+- Publish & version updated datasets on Hugging Face every few days.
 
-This project 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 provides a valuable, open resource for exploring the French legal landscape.
+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 |
 |--------------|----------------|--------|--------|--------|-----------------|---------|
-| Cour d'Appel | 3,712 | 2024-08-01 | 2024-09-04 | 13,346,838 | [Download (11.50 MB)](https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/cour_d_appel.jsonl.gz?download=true) | [Download (19.45 MB)](https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/cour_d_appel.parquet?download=true) |
-| Cour de Cassation | 467 | 2024-08-01 | 2024-09-05 | 572,237 | [Download (415.92 KB)](https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/cour_de_cassation.jsonl.gz?download=true) | [Download (766.87 KB)](https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/cour_de_cassation.parquet?download=true) |
-| Tribunal Judiciaire | 5,881 | 2024-08-01 | 2024-09-04 | 19,841,126 | [Download (17.69 MB)](https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/tribunal_judiciaire.jsonl.gz?download=true) | [Download (29.61 MB)](https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/tribunal_judiciaire.parquet?download=true) |
-| **Total** | **10,060** | **2024-08-01** | **2024-09-05** | **33,760,201** | **29.60 MB** | **49.81 MB** |
+| Cour d'Appel | 378,392 | 1996-03-25 | 2024-09-04 | 1,895,747,631 | [Download (1.66 GB)](https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/cour_d_appel.jsonl.gz?download=true) | [Download (2.77 GB)](https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/cour_d_appel.parquet?download=true) |
+| Cour de Cassation | 534,258 | 1860-08-01 | 2024-09-10 | 1,103,935,111 | [Download (928.92 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) |
+| Tribunal Judiciaire | 58,986 | 2023-12-14 | 2024-08-13 | 211,665,028 | [Download (189.16 MB)](https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/tribunal_judiciaire.jsonl.gz?download=true) | [Download (315.38 MB)](https://huggingface.co/datasets/antoinejeannot/jurisprudence/resolve/main/tribunal_judiciaire.parquet?download=true) |
+| **Total** | **971,636** | **1860-08-01** | **2024-09-10** | **3,211,347,770** | **2.75 GB** | **4.65 GB** |
 
 <i>Latest update date: 2024-09-10</i>
 
-<i># Tokens are computed using GPT-4 tiktoken </i>
+<i># Tokens are computed using GPT-4 tiktoken and the `text` column</i>
 
 ## 🤗 Hugging Face Dataset
 
-The updated dataset is available at: https://huggingface.co/datasets/antoinejeannot/jurisprudence
+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
 

cour_d_appel.jsonl.gz

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:529e5cb28fc6234b8e9d73d78e53074b285047c290850d1ca65f39d4f070af5d
-size 12061016
+oid sha256:e978dde95d6d4fe448700463b9b1e5355a776aee6df8b67049f14a2a5e6c2095
+size 1782063344

cour_d_appel.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:94b02967b591df918b96579ce57a10d1574559a3512972c9998d26b348f63b49
-size 20397715
+oid sha256:a9e06aec0659c78dacde1a5f634dc4509b9eb590c58a21876cb8e82abad3f38e
+size 2976313141

cour_de_cassation.jsonl.gz

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:771d03c7a06c9831ca940243ea63226b7e470cebde5f7f4f35551b8519ea52ba
-size 425907
+oid sha256:708a247a80f9dedddbef781479ec91611115163b99f6ae42b2f7aa4f06b2a861
+size 974041954

cour_de_cassation.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:96973aa9f6814cec5133610a550be7e66516338090c39270846fb1aaeb07f0f7
-size 785270
+oid sha256:d797738e74f6bb0cd2022b840b747252c506492eddd316685613b2d26bbc8013
+size 1689606885

tribunal_judiciaire.jsonl.gz

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:bad441ed3b89a5f240e5f53127009f9403af9b46797f5a8eb5aa7d7ba7eaa035
-size 18548079
+oid sha256:ef1623f1631ac2534bf5b8b04e70d5465275f906cf4663fbd8dd67e983ba49cc
+size 198347186

tribunal_judiciaire.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:98b003c453510117f7898913445585c3233e5bc5b74a1bb96163457b979ffa3b
-size 31047283
+oid sha256:a17a9279f63330fa1dbb2aef465d346114ba3eb516da0f6049ccc3d337bbd030
+size 330695268