Changelog¶

All notable changes to this project will be documented in this file.

0.0.4¶

Updated to the snickerdoodle 0.4.0 template.
Made ruff ignore boolean default positional arguments (FBT002).
Relaxed pydoclint checks of type hints, class attributes, and raised exceptions.
Excluded uv.lock from the large file check.
Fixed typos in the contributing guide and noted that the project does not use a code formatter.
Fixed the LICENSE link in the README.

merge_district (and the --merge-district option) merges the appellate data with the civil and criminal district records of the appealed cases and saves the result as fjc_idb_appellate_with_district_data_{start_year}_{stop_year}.csv. Appeals are matched by district, docket number, and, for criminal cases, defendant number, and the district columns are added with the prefix district_.
create_folders creates the folders of the data folder, and downloading now creates any that are missing.

The documentation refers to the package by its PyPI name, fjc-idb, when installing it and in prose; it is still imported as fjc_idb.

Parsing for three types of FJC Integrated Database (IDB) files: courts of appeals, civil cases in the district courts, and criminal defendants in the district courts. The parsing follows the current FJC codebooks and has been tested on the files from 2008 through 2026.
run exports a range of years to a CSV file, one yearly file at a time to keep memory use low. import_data, parse_data, and export_data work on the data in memory.
download and list_files get the yearly SAS files and codebooks from the FJC website.
The fjc-idb command (also python -m fjc_idb) with --start-year, --stop-year, --data-folder, --rename-columns, --fix-city-spellings, --download, --download-only, and --overwrite.
Descriptive column names, labels in place of codes (circuits, districts, courthouses, agencies, dispositions, and more), and correct handling of the IDB's missing-value codes.
Pending cases are kept only from the latest yearly file, so combining years does not count a case more than once.
Added columns: indicators for appeal types and for groups of criminal offenses and natures of suit, the days between key dates, counts of concurrences and dissents, whether a decision was published, whether any party was pro se, and a standard appellate docket number.
Documentation: a tutorial, an advanced user guide, recipes, an API reference, and codebooks for the appellate, criminal, and civil CSV files.

Continuous integration: removed Python 3.10 from the test matrix (pandas 3 requires Python 3.11 or later), fixed ruff and mypy errors, removed the ruff-format pre-commit hook, and replaced the outdated release action.

Initial Commit