What is This?
Juriscraper is a scraper library started several years ago that gathers judicial opinions, oral arguments, and PACER data in the American court system. It is currently able to scrape:
- a variety of pages and reports within the PACER system
- opinions from all major appellate Federal courts
- opinions from all state courts of last resort except for Georgia (typically their "Supreme Court")
- oral arguments from all appellate federal courts that offer them
Juriscraper is part of a two-part system. The second part is your code, which calls Juriscraper. Your code is responsible for calling a scraper, downloading and saving its results. A reference implementation of the caller has been developed and is in use at CourtListener.com. The code for that caller can be found here. There is also a basic sample caller included in Juriscraper that can be used for testing or as a starting point when developing your own.
Some of the design goals for this project are:
- extensibility to support video, oral argument audio, etc.
- extensibility to support geographies (US, Cuba, Mexico, California)
- Mime type identification through magic numbers
- Generalized architecture with minimal code repetition
- XPath-based scraping powered by lxml's html parser
- return all meta data available on court websites (caller can pick what it needs)
- no need for a database
- clear log levels (DEBUG, INFO, WARN, CRITICAL)
- friendly as possible to court websites
Installation & Dependencies
First step: Install Python 2.7.x, then:
# -- Install the dependencies # On Ubuntu/Debian Linux: sudo apt-get install libxml2-dev libxslt-dev libyaml-dev # On macOS with Homebrew <https://brew.sh>: brew install libyaml # -- Install PhantomJS # On Ubuntu/Debian Linux wget https://bitbucket.org/ariya/phantomjs/downloads/phantomjs-1.9.7-linux-x86_64.tar.bz2 tar -x -f phantomjs-1.9.7-linux-x86_64.tar.bz2 sudo mkdir -p /usr/local/phantomjs sudo mv phantomjs-1.9.7-linux-x86_64/bin/phantomjs /usr/local/phantomjs rm -r phantomjs-1.9.7* # Cleanup # On macOS with Homebrew: brew install phantomjs # Finally, install the code. pip install juriscraper # create a directory for logs (this can be skipped, and no logs will be created) sudo mkdir -p /var/log/juriscraper
Joining the Project as a Developer
For scrapers to be merged:
- Running tests via
toxmust pass, listing the results for any new scrapers. The test suite will be run automatically by Travis-CI. If changes are being made to the pacer code, the pacer tests must also pass when run. These tests are skipped by default. To run them, set environment variables for PACER_USERNAME and PACER_PASSWORD.
- A *_example* file must be included in the
tests/examplesdirectory (this is needed for the tests to run your code).
- Your code should be PEP8 compliant with no major Pylint problems or Intellij inspection issues.
- Your code should efficiently parse a page, returning no exceptions or speed warnings during tests on a modern machine.
When you're ready to develop a scraper, get in touch, and we'll find you a scraper that makes sense and that nobody else is working on. We have a wiki list of courts that you can browse yourself. There are templates for new scrapers here (for opinions) and here (for oral arguments).
When you're done with your scraper, fork this repository, push your
changes into your fork, and then send a pull request for your changes.
Be sure to remember to update the
__init__.py file as well, since it
contains a list of completed scrapers.
Before we can accept any changes from any contributor, we need a signed and completed Contributor License Agreement. You can find this agreement in the root of the repository. While an annoying bit of paperwork, this license is for your protection as a Contributor as well as the protection of Free Law Project and our users; it does not change your rights to use your own Contributions for any other purpose.
Getting Set Up as a Developer
To get set up as a developer of Juriscraper, you'll want to install the code from git. To do that, install the dependencies and phantomjs as described above. Instead of installing Juriscraper via pip, do the following:
git clone https://github.com/freelawproject/juriscraper.git . pip install -r requirements.txt python setup.py test
You may need to also install Juriscraper locally with:
pip install .
If you've not installed juriscraper, you can run sample_caller.py as:
PYTHONPATH=`pwd` python juriscraper/sample_caller.py
The scrapers are written in Python, and can can scrape a court as follows:
from juriscraper.opinions.united_states.federal_appellate import ca1 # Create a site object site = ca1.Site() # Populate it with data, downloading the page if necessary site.parse() # Print out the object print str(site) # Print it out as JSON print site.to_json() # Iterate over the item for opinion in site: print opinion
That will print out all the current meta data for a site, including
links to the objects you wish to download (typically opinions or oral
arguments). If you download those opinions, we also recommend running the
_cleanup_content() method against the items that you download (PDFs,
HTML, etc.). See the
sample_caller.py for an example and see
_cleanup_content() for an explanation of what it does.
It's also possible to iterate over all courts in a Python package, even if they're not known before starting the scraper. For example:
# Start with an import path. This will do all federal courts. court_id = 'juriscraper.opinions.united_states.federal' # Import all the scrapers scrapers = __import__( court_id, globals(), locals(), ['*'] ).__all__ for scraper in scrapers: mod = __import__( '%s.%s' % (court_id, scraper), globals(), locals(), [scraper] ) # Create a Site instance, then get the contents site = mod.Site() site.parse() print str(site)
This can be useful if you wish to create a command line scraper that
iterates over all courts of a certain jurisdiction that is provided by a
lib/importer.py for an example that's used in
the sample caller.
District Court Parser
A sample driver to run the PACER District Court parser on an html file is included. It takes HTML file(s) as arguments and outputs JSON to stdout.
PYTHONPATH=`pwd` juriscraper/pacerdocket.py tests/examples/pacer/dockets/district/nysd.html
We got that! You can (and should) run the tests with
tox. This will run
python setup.py test for all supported Python runtimes,
iterating over all of the
*_example* files and run the scrapers against them.
Individual tests can be run with:
python -m unittest tests.test_pacer.DocketParseTest.test_district_court_dockets
Or, to run and drop to the Python debugger if it fails, but you must install nost to have nosetests:
nosetests -v --pdb tests/test_pacer.py:DocketParseTest.test_district_court_dockets
In addition, we use Travis-CI to automatically run the tests whenever code is committed to the repository or whenever a pull request is created. You can make sure that your pull request is good to go by waiting for the automated tests to complete.
The current status of Travis CI on our master branch is:
- 0.1 - Supports opinions from all 13 Federal Circuit courts and the U.S. Supreme Court
- 0.2 - Supports opinions from all federal courts of special jurisdiction (Veterans, Tax, etc.)
- 0.8 - Supports oral arguments for all possible Federal Circuit courts.
- 0.9 - Supports all state courts of last resort (typically the "Supreme" court)
- 1.0 - Support opinions from for all possible federal bankruptcy appellate panels (9th and 10th Cir.)
- 1.1.* - Major code reorganization and first release on the Python Package Index (PyPi)
- 1.2.* - Continued improvements.
- 1.3.* - Adds support for scraping some parts of PACER.
- 1.4.* - Python 3 compatibility (this was later dropped due to dependencies).
- 1.5.* - Adds support for querying and parsing PACER dockets.
- 1.6.* - Adds automatic relogin code to PACER sessions, with reorganization of old login APIs.
- 1.7.* - Adds support for hidden PACER APIs.
- 1.8.* - Standardization of string fields in PACER objects so they return the empty string when they have no value instead of returning None sometimes and the empty string others. (This follows Django conventions.)
- 1.9.* - Re-organization, simplification, and standardization of PACER classes.
- 1.10.* - Better parsing for PACER attachment pages.
- 1.11.* - Adds system for identifying invalid dockets in PACER.
- 1.12.* - Adds new parsers for PACER's show_case_doc URLs
- 1.13.* - Fixes issues with Python build compatibility
- 1.14.* - Adds new parser for PACER's docket history report
- 1.15.* - Adds date termination parsing to parties on PACER dockets.
- 1.16.* - Adds PACER RSS feed parsers.
- 1.17.* - Adds support for criminal data in PACER
- 1.18.* - Adds support for appellate docket parsing!
- 1.19.* - Adds support for NextGen PACER logins, but drops support for the PACER training website. The training website now uses a different login flow than the rest of PACER.
- 1.20.* - Tweaks the API of the query method in the FreeOpinionReport object to consistently return None instead of sometimes returning . Version bumped because of breaking API changes.
Immediate Future Goals
- Support for additional PACER pages and utilities
- Support opinions from for all intermediate appellate state courts
- Support opinions from for all courts of U.S. territories (Guam, American Samoa, etc.)
- Support opinions from for all federal district courts with non-PACER opinion listings
- For every court above where a backscraper is possible, it is implemented.
- Support video, additional oral argument audio, and transcripts everywhere available
Deployment to PyPi should happen automatically by Travis CI whenever a new tag is created in Github on the master branch. It will fail if the version has not been updated or if Travis CI failed.
If you wish to create a new version manually, the process is:
- Update version info in
- Install the requirements in requirements_dev.txt
- Set up a config file at ~/.pypirc
Generate a distribution
python setup.py bdist_wheel
Upload the distribution
twine upload dist/* -r pypi (or pypitest)
Juriscraper is licensed under the permissive BSD license.