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>

1 files changed, 4 insertions, 4 deletions

diff --git a/README.md b/README.md
index 84df69d..37b72fe 100644
--- a/README.md
+++ b/README.md
@@ -120,7 +120,7 @@ re-executed in order to pick up a non-hermetic change to your environment (e.g.,
 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 @@ file of all your python dependencies `pip_parse` will translate each requirement
 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.