Image Processing in Python for 3D image stacks, or imppy3d, is a softwarerepository comprising mostly Python scripts that simplify post-processing and3D shape characterization of grayscale image stacks, otherwise known asvolume-based images, 3D images, or voxel models. imppy3d was originally createdfor post-processing image stacks generated from X-ray computed tomographymeasurements. However, imppy3d also contains a functions to aid inpost-processing general 2D/3D images.Python was chosen for this library because of it is a productive, easy-to-uselanguage.

The main goal of `pyproject2conda` is to provide a means to keep all basicdependency information, for both `pip` based and `conda` based environments, in`pyproject.toml`. I often use a mix of pip and conda when developing packages,and in my everyday workflow. Some packages just aren't available on both. The application provides a simple comment based syntax to add information to dependencies when creating `environment.yaml`. This package is actively used by the author, but is still very much a work inprogress.

Contains Artificial Intelligence Patent Landscape data classifying 13,244,037 granted patents and PGPubs published from 1976 through 2021 in eight AI component technologies using state-of-the art machine learning based models.

The Bulk Data Storage System (BDSS) API allows the public to discover, search by date, and download patent and trademark data within BDSS in bulk form.

The Bulk Search and Download API allows searching published patent applications (pre-grant publications, pgpubs) and issued patents (patent grants) across various fields from 2001 to present, and to request a custom zip package for the given patent application or patent ids. Download up to 100 document numbers at a time. Wait time can vary based on the number of requests being processed.

This curated dataset consists of 269,353 patent documents (published patent applications and granted patents) spanning the 1976 to 2016 period and is intended to help identify promising R&D on the horizon in diagnostics, therapeutics, data analytics, and model biological systems.

The Cancer Moonshot Patent Data Set API allows the public to discover and search USPTO Cancer Moonshot Patent Data.

Contains Cooperative Patent Classification (CPC) classification information for all Utility patent applications published by the U.S. Patent and Trademark Office (USPTO) from 2001 to present. It is available as XML with schemas or text monthly (usually by the 15th of the month).

Contains Cooperative Patent Classification (CPC) classification information for all Utility patent grants issued by the U.S. Patent and Trademark Office (USPTO) from 1790 to present. It is available as XML with schemas or text monthly (usually by the 15th of the month).

Contains selected bibliographic (selected front page data fields) patent data for utility patents granted since 1963 and for other patent documents granted since 1977. The bibliographic data are extracted from the USPTO's Technology Assessment and Forecast (TAF) database and are presented in a form that facilitates loading into database software (e.g., for analysis).