We recently made a change to the schema for both Class Action cases and involving Patent Invalidity. Previously, in Class Action cases, the API for a given case returned only the general class action finding, such as “Class Certification: Deny,” and not the specific findings associated with the overall decision of whether to deny or grant class certification. Consequently, the schema was modified so that Class Action cases now return the following specific findings if relevant:

Now that there are three different ways to query the Lex Machina API, knowing what aspects can be queried in each of the three is becoming a more complex task. This post is an attempt to put a lot of data on screen quickly with no real discussion. To see in depth discussions of each, look at the documentation in the developer portal for querying district cases, state and appeals.

As part of our efforts to continuously improve and expand the capabilities of the Lex Machina API, we now have Appeals data available via the API. The in-app documentation has been updated to reflect the changes, new endpoints and the new inputs to some of the list endpoints. Any of the endpoints that previously took “FederalDistrict” or “State” as input now also take “FederalAppeals” as context for the list of resources requested.

Lex Machina now not only has an API to allow automated access to our data but we also have a Sandbox API that allows prospective customers to test out the system with a subset of real data. For those potential users who are testing out the system to see if it meets needs, you can absolutely use the client libraries we have - python and node/JavaScript - to access the Sandbox.

I have written a number of scripts that access the Lex Machina API. Some of these were for testing, some for demo and some for proof of concepts for current and potential customers. As I look at the structure of them, almost of all of them fit into a distinct pattern. The logic I have authored has these phases: Optional search (input text, search for judge, party, etc) or possibly looping over a list (all state or federal district courts) Using either that input and/or hardcoded values, do a query for cases Take the resulting list of cases and look them up one by one Extract values from individual cases for use.

In the world of litigation, data-driven insights have become invaluable tools for legal professionals seeking to gain a competitive edge. As the creator of litigation analytics, Lex Machina has fundamentally altered the way legal research is conducted, providing comprehensive data and sophisticated tools to allow users to make informed decisions. Today we are thrilled to announce the launch of our API Sandbox! This allows potential API customers to experience the capabilities of our API firsthand before committing to a subscription.

The most recent state courts to be added to the Lex Machina data include nine county circuits from Oregon. These nine counties are from the top 11 most populous counties in the state so while 25% of the counties in Oregon, it covers 73% of the population. The goal is to expand to the rest of the counties by the end of the year. (This is an aspiration, not a promise or binding contract.

As of now, the Lex Machina API has client libraries published for both Node and Python. In this article, I will walk through the installation, configuration and use of both. Installation Both libraries are published to their respective package directories. Node The Node package is published to npm. To install it in your project directory use this command: npm install @lexmachina/lexmachina-client Python The Python package is published to PyPi. To install it in your Python environment use this command:

As of general availability, data from both federal district and state cases can be queried via the Lex Machina API. There are full articles on the developer portal about each type of query. Here is the one for federal district queries and one for state queries. For this blog post, I will provide a very quick high level summary of the differences. For details in using either query, see the above articles.

Recently some of the Lex Machina product team went to Las Vegas to exhibit at the CLOC Global Institute conference. It was an interesting event at which we talked to a number of current and potential customers. One idea that was thrown out almost as a joke was the idea of using our API to determine for a given judge how they ruled on the day of the week. Of course, I took this as a challenge.