Unlike earlier build systems, Pants v2 automatically infers your code's internal and external dependencies. And it does this at the file level, so that you get optimal invalidation, caching, and concurrency performance without having to manually create and maintain mountains of BUILD file metadata.

Highlights include: less boilerplate via hierarchical defaults for target field values, better Golang monorepo support, with multiple go.mods, do more of your workflows in Pants with the experimental deploy goal (with initial support for Helm), and much more…

How we worked around some quirks and limitations of GitHub Actions to skip CI jobs that aren't necessary in certain scenarios, without breaking branch protection rules that normally require those CI jobs to succeed.

To make it easier to understand the value and power of dependency inference, Toolchain (the lead sponsor of Pants) has built a new site: Graph My Repo. As its name suggests, Graph My Repo shows you an interactive graph of a public GitHub repo of your choice…

I was born in the early 80's in a small fishing town in the Spanish Atlantic Coast, far away from the big urban sprawls and common traits of miles-long beaches, year-round summertime and chill out vibes normally identified with life in Spain. This is the autonomous region named Galicia…

We're pleased to announce Pants 2.13.0. Highlights include better command line arguments for file sets, improved JVM support, easier access to parallel execution in CI, and lower barriers to adoption for Python projects that currently use existing distribution and build tools.

"Code development at Astranis has been migrating towards a monorepo structure. Astranis has grown rapidly since this migration started and, along with it, so has the volume of Python hosted in our monorepo. We went looking for new tooling to bring us into the future."

Pantsbuild provides a common interface to run all code quality tools in parallel. This post explores how Pants augments excellent linters such as bandit, flake8, shellcheck, etc. by offering its own linting mechanisms, too, including regex matches, dependency analysis, and metadata checks.

Pants can build a PEX file, an executable zip file containing your Python code and all transitive dependencies. Deploying your application is as simple as copying the file. This post elaborates on how to get best performance out of the powerful combination of Pants+PEX+Docker.