docs: document how to configure MODULE.bazel for different use cases (#1864)

This largely comes from being regularly tagged on BCR PRs about how a
module should be configured. This info was sort of already in the
getting started docs, but that isn't an obvious place to go and bloated
the what should be simplified steps to getting started.

Author: rickeylev

docs/sphinx/getting-started.md

@@ -1,12 +1,17 @@
 # Getting started
 
-The following two sections cover using `rules_python` with bzlmod and
-the older way of configuring bazel with a `WORKSPACE` file.
+This doc is a simplified guide to help get started started quickly. It provides
+a simplified introduction to having a working Python program for both bzlmod
+and the older way of using `WORKSPACE`.
 
+It assumes you have a `requirements.txt` file with your PyPI dependencies.
 
-## Using bzlmod
+For more details information about configuring `rules_python`, see:
+* [Configuring the runtime](toolchains)
+* [Configuring third party dependencies (pip/pypi)](pypi-dependencies)
+* [API docs](api/index)
 
-**IMPORTANT: bzlmod support is still in Beta; APIs are subject to change.**
+## Using bzlmod
 
 The first step to using rules_python with bzlmod is to add the dependency to
 your MODULE.bazel file:
@@ -15,99 +20,20 @@ your MODULE.bazel file:
 # Update the version "0.0.0" to the release found here:
 # https://github.com/bazelbuild/rules_python/releases.
 bazel_dep(name = "rules_python", version = "0.0.0")
-```
-
-Once added, you can load the rules and use them:
-
-```starlark
-load("@rules_python//python:py_binary.bzl", "py_binary")
-
-py_binary(...)
-```
-
-Depending on what you're doing, you likely want to do some additional
-configuration to control what Python version is used; read the following
-sections for how to do that.
-
-### Toolchain registration with bzlmod
 
-A default toolchain is automatically configured depending on
-`rules_python`. Note, however, the version used tracks the most recent Python
-release and will change often.
-
-If you want to use a specific Python version for your programs, then how
-to do so depends on if you're configuring the root module or not. The root
-module is special because it can set the *default* Python version, which
-is used by the version-unaware rules (e.g. `//python:py_binary.bzl` et al). For
-submodules, it's recommended to use the version-aware rules to pin your programs
-to a specific Python version so they don't accidentally run with a different
-version configured by the root module.
-
-#### Configuring and using the default Python version
-
-To specify what the default Python version is, set `is_default = True` when
-calling `python.toolchain()`. This can only be done by the root module; it is
-silently ignored if a submodule does it. Similarly, using the version-unaware
-rules (which always use the default Python version) should only be done by the
-root module. If submodules use them, then they may run with a different Python
-version than they expect.
-
-```starlark
-python = use_extension("@rules_python//python/extensions:python.bzl", "python")
-
-python.toolchain(
+pip = use_extension("@rules_python//python/extensions:pip.bzl", "pip")
+pip.parse(
+    hub_name = "my_deps",
     python_version = "3.11",
-    is_default = True,
+    requirements_lock = "//:requirements.txt",
 )
+use_repo(pip, "my_deps")
 ```
 
-Then use the base rules from e.g. `//python:py_binary.bzl`.
-
-#### Pinning to a Python version
-
-Pinning to a version allows targets to force that a specific Python version is
-used, even if the root module configures a different version as a default. This
-is most useful for two cases:
-
-1. For submodules to ensure they run with the appropriate Python version
-2. To allow incremental, per-target, upgrading to newer Python versions,
-   typically in a mono-repo situation.
-
-To configure a submodule with the version-aware rules, request the particular
-version you need, then use the `@python_versions` repo to use the rules that
-force specific versions:
-
-```starlark
-python = use_extension("@rules_python//python/extensions:python.bzl", "python")
-
-python.toolchain(
-    python_version = "3.11",
-)
-use_repo(python, "python_versions")
-```
-
-Then use e.g. `load("@python_versions//3.11:defs.bzl", "py_binary")` to use
-the rules that force that particular version. Multiple versions can be specified
-and use within a single build.
-
-For more documentation, see the bzlmod examples under the {gh-path}`examples`
-folder.  Look for the examples that contain a `MODULE.bazel` file.
-
-#### Other toolchain details
-
-The `python.toolchain()` call makes its contents available under a repo named
-`python_X_Y`, where X and Y are the major and minor versions. For example,
-`python.toolchain(python_version="3.11")` creates the repo `@python_3_11`.
-Remember to call `use_repo()` to make repos visible to your module:
-`use_repo(python, "python_3_11")`
-
 ## Using a WORKSPACE file
 
-To import rules_python in your project, you first need to add it to your
-`WORKSPACE` file, using the snippet provided in the
-[release you choose](https://github.com/bazelbuild/rules_python/releases)
-
-To depend on a particular unreleased version, you can do the following:
+Using WORKSPACE is deprecated, but still supported, and a bit more involved than
+using Bzlmod. Here is a simplified setup to download the prebuilt runtimes.
 
 ```starlark
 load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
@@ -130,13 +56,7 @@ http_archive(
 load("@rules_python//python:repositories.bzl", "py_repositories")
 
 py_repositories()
-```
-
-### Toolchain registration
-
-To register a hermetic Python toolchain rather than rely on a system-installed interpreter for runtime execution, you can add to the `WORKSPACE` file:
 
-```starlark
 load("@rules_python//python:repositories.bzl", "python_register_toolchains")
 
 python_register_toolchains(
@@ -157,25 +77,20 @@ pip_parse(
 )
 ```
 
-After registration, your Python targets will use the toolchain's interpreter during execution, but a system-installed interpreter
-is still used to 'bootstrap' Python targets (see https://github.com/bazelbuild/rules_python/issues/691).
-You may also find some quirks while using this toolchain. Please refer to [python-build-standalone documentation's _Quirks_ section](https://gregoryszorc.com/docs/python-build-standalone/main/quirks.html).
-
-## Toolchain usage in other rules
-
-Python toolchains can be utilized in other bazel rules, such as `genrule()`, by adding the `toolchains=["@rules_python//python:current_py_toolchain"]` attribute. You can obtain the path to the Python interpreter using the `$(PYTHON2)` and `$(PYTHON3)` ["Make" Variables](https://bazel.build/reference/be/make-variables). See the
-{gh-path}`test_current_py_toolchain <tests/load_from_macro/BUILD.bazel>` target for an example.
-
 ## "Hello World"
 
-Once you've imported the rule set into your `WORKSPACE` using any of these
-methods, you can then load the core rules in your `BUILD` files with the following:
+Once you've imported the rule set using either Bzlmod or WORKSPACE, you can then
+load the core rules in your `BUILD` files with the following:
 
 ```starlark
 load("@rules_python//python:defs.bzl", "py_binary")
 
 py_binary(
   name = "main",
   srcs = ["main.py"],
+  deps = [
+      "@my_deps//foo",
+      "@my_deps//bar",
+  ]
 )
 ```

docs/sphinx/index.md

@@ -57,6 +57,7 @@ by buildifier.
 self
 getting-started
 pypi-dependencies
+configuring
 pip
 coverage
 gazelle