echr-extractor 1.0.11

Library for extracting ECHR data

echr extractor

This library contains functions to get ECHR data.

Version

Python 3.9

Contributors

Benjamin Rodrigues de Miranda

Chloe Crombach

Piotr Lewandowski

Pranav Bapat

running-machin

shashankmc

gijsvd

How to install?

pip install echr-extractor

What are the functions?

1. get_echr
Gets all of the available metadata for echr cases from the HUDOC database. Can be saved in a file or returned in-memory.

2. get_echr_extra
Gets all of the available metadata for echr cases from the HUDOC database. On top of that downloads the full text for each case downloaded. Can be saved in a file or returned in-memory.

What are the parameters?

1. get_echr
skip_missing_dates=False,,fields=None) Parameters:
• start_id: int, optional, default: 0
The id of the first case to be downloaded.
• end_id: int, optional, default: The maximum number of cases available
The id of the last case to be downloaded.
• count: int, optional, default: None
The number of cases to be downloaded, starting from the start_id.
WARNING
If count is provided, the end_id will be set to start_id+count, overwriting any given end_id value.
• start_date: date, optional, default None
The start publication date (yyyy-mm-dd)
• end_date: date, optional, default current date
The end publication date (yyyy-mm-dd)
• verbose: boolean, optional, default False
This option allows for additional printing, showing live progress of the extraction process.
• skip_missing_dates: boolean, optional, default False
This option makes the extraction not collect data for cases where there is no judgement date provided.
• fields: list of strings, optional, default all available fields
This argument can be provided, to limit the metadata to be downloaded. These fields will appear as different columns in the csv file / Dataframe object. The full list of fields is attached in the appendix.
• save_file: ['y', 'n'],optional, default 'y'
Save metadata as a csv file in the data folder, or return as a Pandas DataFrame object in-memory.
2. get_echr_extra
• start_id: int, optional, default: 0
The id of the first case to be downloaded.
• end_id: int, optional, default: The maximum number of cases available
The id of the last case to be downloaded.
• count: int, optional, default: None
The number of cases to be downloaded, starting from the start_id.
WARNING
If count is provided, the end_id will be set to start_id+count, overwriting any given end_id value.
• start_date: date, optional, default None
The start publication date (yyyy-mm-dd)
• end_date: date, optional, default current date
The end publication date (yyyy-mm-dd)
• verbose: boolean, optional, default False
This option allows for additional printing, showing live progress of the extraction process.
• skip_missing_dates: boolean, optional, default False
This option makes the extraction not collect data for cases where there is no judgement date provided.
• fields: list of strings, optional, default all available fields
This argument can be provided, to limit the metadata to be downloaded. These fields will appear as different columns in the csv file / Dataframe object. The full list of fields is attached in the appendix.
• save_file: ['y', 'n'],optional, default 'y'
Save metadata as a csv file in the data folder and the full_text as a json file, or return a Pandas DataFrame object and a list of dictionaries in-memory.
• threads: int, optional, default: 10
The full text download is a parallelizable process. This parameter determines the number of threads to be used in the download.

Examples

import echr_extractor as echr

Below are examples for in-file saving:

df, json = echr.get_echr_extra(count=100,save_file='y',threads=10)
df = echr.get_echr(start_id=1,save_file='y',skip_missing_dates=True)

Below are examples for in-memory saving:

df, json = echr.get_echr_extra(start_id=20,end_id=3000,save_file='n')
    
df = echr.get_echr(start_id=1000,count=2000,save_file='n',verbose=True)

License

Previously under the MIT License, as of 28/10/2022 this work is licensed under a Apache License, Version 2.0.

Apache License, Version 2.0

Copyright (c) 2022 Maastricht Law & Tech Lab

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
    
    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

Appendix

The full list of fields is as follows:

fields = ['itemid','applicability','application','appno','article','conclusion','decisiondate','docname',
'documentcollectionid','documentcollectionid2','doctype','doctypebranch','ecli','externalsources','extractedappno',
'importance','introductiondate','isplaceholder','issue','judgementdate','kpdate','kpdateAsText','kpthesaurus',
'languageisocode','meetingnumber','originatingbody','publishedby','Rank','referencedate','reportdate','representedby',
'resolutiondate',resolutionnumber','respondent','respondentOrderEng','rulesofcourt','separateopinion','scl',
'sharepointid','typedescription','nonviolation','violation']

These fields can take different values, for more information head to https://hudoc.echr.coe.int.