Remove 'experimental' from pip_parse section (#551)
Removes the "Experimental" tag from the `pip_parse` section of the README, and adds a note about the relatively new `compile_pip_requirements` rule.
Co-authored-by: Alex Eagle <eagle@post.harvard.edu>
diff --git a/README.md b/README.md
index 84df69d..37b72fe 100644
--- a/README.md
+++ b/README.md
@@ -120,7 +120,7 @@
updating your system `python` interpreter), you can completely flush out your
repo cache with `bazel clean --expunge`.
-### Fetch `pip` dependencies lazily (experimental)
+### Fetch `pip` dependencies lazily
One pain point with `pip_install` is the need to download all dependencies resolved by
your requirements.txt before the bazel analysis phase can start. For large python monorepos
@@ -131,9 +131,9 @@
Bazel will only fetch/build wheels for the requirements in the subgraph of your build target.
There are API differences between `pip_parse` and `pip_install`:
-1. `pip_parse` requires a fully resolved lock file of your python dependencies. You can generate this using
- `pip-compile`, or a virtualenv and `pip freeze`. `pip_parse` uses a label argument called `requirements_lock` instead of `requirements`
- to make this distinction clear.
+1. `pip_parse` requires a fully resolved lock file of your python dependencies. You can generate this by using the `compile_pip_requirements` rule,
+ running `pip-compile` directly, or using virtualenv and `pip freeze`. `pip_parse` uses a label argument called `requirements_lock` instead of
+ `requirements` to make this distinction clear.
2. `pip_parse` translates your requirements into a starlark macro called `install_deps`. You must call this macro in your WORKSPACE to
declare your dependencies.
