rapids-dependency-file-generator

rapids-dependency-file-generator is a Python CLI tool that generates conda environment.yaml files and requirements.txt files from a single YAML file, typically named dependencies.yaml.

When installed, it makes the rapids-dependency-file-generator CLI command available which is responsible for parsing a dependencies.yaml configuration file and generating the appropriate conda environment.yaml and requirements.txt dependency files.

Table of Contents

• Installation
• Usage
• dependencies.yaml Format
  • files key
  • channels key
  • dependencies key
• How Dependency Lists Are Merged
• Additional CLI Notes
• Examples

Installation

rapids-dependency-file-generator is available on PyPI. To install, run:

pip install rapids-dependency-file-generator

Usage

When rapids-dependency-file-generator is invoked, it will read a dependencies.yaml file from the current directory and generate children dependency files.

The dependencies.yaml file has the following characteristics:

• it is intended to be committed to the root directory of repositories
• it can define matrices that enable the output dependency files to vary according to any arbitrary specification (or combination of specifications), including CUDA version, machine architecture, Python version, etc.
• it contains bifurcated lists of dependencies based on the dependency's purpose (i.e. build, runtime, test, etc.). The bifurcated dependency lists are merged according to the description in the How Dependency Lists Are Merged section below.

dependencies.yaml Format

The Examples section below has instructions on where example dependency.yaml files and their corresponding output can be viewed.

The dependencies.yaml file has three relevant top-level keys: files, channels, and dependencies. These keys are described in detail below.

files Key

The top-level files key is responsible for determining the following:

• which types of dependency files should be generated (i.e. conda environment.yaml files and/or requirements.txt files)
• where the generated files should be written to (relative to the dependencies.yaml file)
• which variant files should be generated (based on the provided matrix)
• which of the dependency lists from the top-level dependencies key should be included in the generated files

Here is an example of what the files key might look like:

files:
  all: # used as the prefix for the generated dependency file names for conda or requirements files (has no effect on pyproject.toml files)
    output: [conda, requirements] # which dependency file types to generate. required, can be "conda", "requirements", "pyproject", "none" or a list of non-"none" values
    conda_dir: conda/environments # where to put conda environment.yaml files. optional, defaults to "conda/environments"
    requirements_dir: python/cudf # where to put requirements.txt files. optional, but recommended. defaults to "python"
    pyproject_dir: python/cudf # where to put pyproject.toml files. optional, but recommended. defaults to "python"
    matrix: # (optional) contains an arbitrary set of key/value pairs to determine which dependency files that should be generated. These values are included in the output filename.
      cuda: ["11.5", "11.6"] # which CUDA version variant files to generate.
      arch: [x86_64] # which architecture version variant files to generate. This value should be the result of running the `arch` command on a given machine.
    includes: # a list of keys from the `dependencies` section which should be included in the generated files
      - build
      - test
      - runtime
  build: # multiple `files` children keys can be specified
    output: requirements
    conda_dir: conda/environments
    requirements_dir: python/cudf
    matrix:
      cuda: ["11.5"]
      arch: [x86_64]
      py: ["3.8"]
    includes:
      - build

The result of the above configuration is that the following dependency files would be generated:

• conda/environments/all_cuda-115_arch-x86_64.yaml
• conda/environments/all_cuda-116_arch-x86_64.yaml
• python/cudf/requirements_all_cuda-115_arch-x86_64.txt
• python/cudf/requirements_all_cuda-116_arch-x86_64.txt
• python/cudf/requirements_build_cuda-115_arch-x86_64_py-38.txt

The all*.yaml and requirements_all*.txt files would include the contents of the build, test, and runtime dependency lists from the top-level dependency key. The requirements_build*.txt file would only include the contents of the build dependency list from the top-level dependency key.

The value of output can also be none as shown below.

files:
  test:
    output: none
    includes:
      - test

When output: none is used, the conda_dir, requirements_dir and matrix keys can be omitted. The use case for output: none is described in the Additional CLI Notes section below.

extras

A given file may include an extras entry that may be used to provide inputs specific to a particular file type

Here is an example:

files:
  build:
    output: pyproject
    includes: # a list of keys from the `dependencies` section which should be included in the generated files
      - build
    extras:
      table: table_name
      key: key_name

Currently the supported extras by file type are:

• pyproject.toml
  • table: The table in pyproject.toml where the dependencies should be written. Acceptable values are "build-system", "project", and "project.optional-dependencies".
  • key: The key corresponding to the dependency list in table. This may only be provided for the "project.optional-dependencies" table since the key name is fixed for "build-system" ("requires") and "project" ("dependencies"). Note that this implicitly prohibits including optional dependencies via an inline table under the "project" table.

channels Key

The top-level channels key specifies the channels that should be included in any generated conda environment.yaml files.

It might look like this:

channels:
  - rapidsai
  - conda-forge

In the absence of a channels key, some sensible defaults for RAPIDS will be used (see constants.py).

dependencies Key

The top-level dependencies key is where the bifurcated dependency lists should be specified.

Underneath the dependencies key are sets of key-value pairs. For each pair, the key can be arbitarily named, but should match an item from the includes list of any files entry.

The value of each key-value pair can have the following children keys:

• common - contains dependency lists that are the same across all matrix variations
• specific - contains dependency lists that are specific to a particular matrix combination

The values of each of these keys are described in detail below.

common Key

The common key contains a list of objects with the following keys:

• output_types - a list of output types (e.g. "conda" for environment.yaml files or "requirements" for requirements.txt files) for the packages in the packages key
• packages - a list of packages to be included in the generated output file

specific Key

The specific key contains a list of objects with the following keys:

• output_types - same as output_types for the common key above
• matrices - a list of objects (described below) which define packages that are specific to a particular matrix combination

matrices Key

Each list item under the matrices key contains a matrix key and a packages key. The matrix key is used to define which matrix combinations from files.[*].matrix will use the associated packages. The packages key is a list of packages to be included in the generated output file for a matching matrix. This is elaborated on in How Dependency Lists Are Merged.

An example of the above structure is exemplified below:

dependencies:
  build: # dependency list name
    common: # dependencies common among all matrix variations
      - output_types: [conda, requirements] # the output types this list item should apply to
        packages:
          - common_build_dep
      - output_types: conda
        packages:
          - cupy
          - pip: # supports `pip` key for conda environment.yaml files
              - some_random_dep
    specific: # dependencies specific to a particular matrix combination
      - output_types: conda # dependencies specific to conda environment.yaml files
        matrices:
          - matrix:
              cuda: "11.5"
            packages:
              - cudatoolkit=11.5
          - matrix:
              cuda: "11.6"
            packages:
              - cudatoolkit=11.6
          - matrix: # an empty matrix entry serves as a fallback if there are no other matrix matches
            packages:
              - cudatoolkit
      - output_types: [conda, requirements]
        matrices:
          - matrix: # dependencies specific to x86_64 and 11.5
              cuda: "11.5"
              arch: x86_64
            packages:
              - a_random_x86_115_specific_dep
          - matrix: # an empty matrix/package entry to prevent error from being thrown for non 11.5 and x86_64 matches
            packages:
      - output_types: requirements # dependencies specific to requirements.txt files
        matrices:
          - matrix:
              cuda: "11.5"
            packages:
              - another_random_dep=11.5.0
          - matrix:
              cuda: "11.6"
            packages:
              - another_random_dep=11.6.0
  test:
    common:
      - output_types: [conda, requirements]
        packages:
          - pytest

How Dependency Lists Are Merged

The information from the top-level files and dependencies keys are used to determine which dependencies should be included in the final output of the generated dependency files.

Consider the following top-level files key configuration:

files:
  all:
    output: conda
    conda_dir: conda/environments
    requirements_dir: python/cudf
    matrix:
      cuda: ["11.5", "11.6"]
      arch: [x86_64]
    includes:
      - build
      - test

In this example, rapids-dependency-file-generator will generate two conda environment files: conda/environments/all_cuda-115_arch-x86_64.yaml and conda/environments/all_cuda-116_arch-x86_64.yaml.

Since the output value is conda, rapids-dependency-file-generator will iterate through any dependencies.build.common and dependencies.test.common list entries and use the packages of any entry whose output_types key is conda or [conda, ...].

Further, for the 11.5 and x86_64 matrix combination, any build.specific and test.specific list items whose output includes conda and whose matrices list items matches any of the definitions below would also be merged:

specific:
  - output_types: conda
    matrices:
      - matrix:
          cuda: "11.5"
        packages:
          - some_dep1
          - some_dep2
# or
specific:
  - output_types: conda
    matrices:
      - matrix:
          cuda: "11.5"
          arch: "x86_64"
        packages:
          - some_dep1
          - some_dep2
# or
specific:
  - output_types: conda
    matrices:
      - matrix:
          arch: "x86_64"
        packages:
          - some_dep1
          - some_dep2

Every matrices list must have a match for a given input matrix (only the first matching matrix in the list of matrices will be used). If no matches are found for a particular matrix combination, an error will be thrown. In instances where an error should not be thrown, an empty matrix and packages list item can be used:

- output_types: conda
  matrices:
    - matrix:
        cuda: "11.5"
        arch: x86_64
        py: "3.8"
      packages:
        - a_very_specific_115_x86_38_dep
    - matrix: # an empty matrix entry serves as a fallback if there are no other matrix matches
      packages:

Merged dependency lists are sorted and deduped.

Additional CLI Notes

Invoking rapids-dependency-file-generator without any arguments is meant to be the default behavior for RAPIDS developers. It will generate all of the necessary dependency files as specified in the top-level files configuration.

However, there are CLI arguments that can augment the files configuration values before the files are generated.

Consider the example when output: none is used:

files:
  test:
    output: none
    includes:
      - test

The test file generated by the configuration above is useful for CI, but it might not make sense to necessarily commit those files to a repository. In such a scenario, the following CLI arguments can be used:

ENV_NAME="cudf_test"

rapids-dependency-file-generator \
  --file-key "test" \
  --output "conda" \
  --matrix "cuda=11.5;arch=$(arch)" > env.yaml
mamba env create --file env.yaml
mamba activate "$ENV_NAME"

# install cudf packages built in CI and test them in newly created environment...

The --file-key argument is passed the test key name from the files configuration. Additional flags are used to generate a single dependency file. When the CLI is used in this fashion, it will print to stdout instead of writing the resulting contents to the filesystem.

The --file-key, --output, and --matrix flags must be used together. --matrix may be an empty string if the file that should be generated does not depend on any specific matrix variations.

The --prepend-channel argument accepts additional channels to use, like rapids-dependency-file-generator --prepend-channel my_channel --prepend-channel my_other_channel. If both --output and --prepend-channel are provided, the output format must be conda. Prepending channels can be useful for adding local channels with packages to be tested in CI workflows.

Running rapids-dependency-file-generator -h will show the most up-to-date CLI arguments.

Examples

The tests/examples directory has example dependencies.yaml files along with their corresponding output files.

To create new example tests do the following:

• Create a new directory with a dependencies.yaml file in tests/examples
• Ensure the output directories (e.g. conda_dir, requirements_dir, etc.) are set to write to output/actual
• Run rapids-dependency-file-generator --config tests/examples/<new_folder_name>/dependencies.yaml to generate the initial output files
• Manually inspect the generated files for correctness
• Copy the contents of output/actual to output/expected, so it will be committed to the repository and used as a baseline for future changes
• Add the new folder name to test_examples.py