Managing Dependencies

Qwak supports a variety of Python frameworks to manage model dependencies.

Poetry

🚧

Qwak system uses Poetry version 1.5.1.

Poetry Lock Support

Qwak supports poetry.lock files as long as they're under the same scope as the pyproject.toml file.

Given the following model structure:

qwak_based_model/
β”œβ”€β”€ main/
β”œβ”€β”€β”€β”€ pyproject.toml
β”œβ”€β”€β”€β”€ poetry.lock
β”œβ”€β”€ tests/

Both files pyproject.toml and poetry.lock will be used by Poetry while executing poetry install cmd.

Poetry Project Starter

Example of quick project starter

[tool.poetry]
name = "Qwak-environment"
version = "0.1.0"
description = "Qwak virtual environment"
authors = ["no-reply@localhost>"]

[tool.poetry.dependencies]
python = "~3.9"
qwak-sdk = "*"

[build-system]
requires = ["poetry-core>=1.0.0"]
build-backend = "poetry.core.masonry.api"

When specifying dependencies in Poetry, using * as the version for qwak-sdk instructs Poetry to install the latest available version of the qwak-sdk package. This approach ensures that your project always utilizes the most recent features and fixes. However, it's important to consider the implications of automatically adopting new versions, as they may introduce breaking changes or compatibility issues. For more controlled dependency management, consider the following alternatives:

  • qwak-sdk = "^0.5.61": This specifies that Poetry should install a version of qwak-sdk that is at least as new as 0.5.61 but less than the next major version (1.0.0). It allows for updates that include backwards-compatible features and fixes. This approach balances the benefits of receiving updates with the safety of avoiding major changes that could break your project.
  • qwak-sdk = "0.5.61": This pins qwak-sdk to a specific version, ensuring that your project will always use version 0.5.61 of the SDK. This is the safest option if your project depends on the specific behavior of this version, as it eliminates the risk of unexpected changes due to updates. However, it also means that you will not automatically benefit from new features or fixes introduced in later versions.


.qwakignore file

Occasionally, we may want to exclude a file from the Qwak build but keep it in the repository with the model code. In such cases, we should add the .qwakignore file to the root directory of our project.

In the file, we define the patterns to match files to exclude from the model build.

For example, suppose we have the following file structure:

.qwakignore
main/
    __init__.py
    model.py
    README.md
tests/
    test_model.py
research/
    paper_a.pdf
    paper_b.pdf

if we want to exclude the entire research directory and the README.md file from the build, our .qwakignore file may contain:

research
README.md

πŸ“˜

Hidden files

By default, Qwak disregards hidden files. Hidden files are files or directories whose names start with a dot (.) in Unix-like operating systems, or they may have the "Hidden" attribute set in Windows. These files are typically used to store configuration data or hold temporary information.

Suppose you have a directory with files and subdirectories, including a hidden file named .config_file. Qwak, following its default behavior, will exclude this file from processing when triggering a remote build.



Incorporating Python Dependencies from .whl Files

Qwak facilitates the use of Python dependencies packaged as .whl files through requirements.txt and conda.yaml for managing dependencies. It's important to note that Poetry does not support dependencies from .whl files.

  1. Preparing Your .whl Files:

First, ensure your .whl file(s) are either uploaded with your model code or fetched from external storage. For instructions on uploading additional dependencies, refer to the Qwak CLI documentation (qwak models build --help). Below is an example directory structure for your model, where main is uploaded by default and the dep directory, containing the pandas dependency in a .whl file, is included via the --dependency-required-folders dep option in the Qwak command.

/qwak/model_dir/
.
β”œβ”€β”€ main                   # Main directory containing core code
β”‚   β”œβ”€β”€ __init__.py        # An empty file that indicates this directory is a Python package
β”‚   β”œβ”€β”€ model.py           # Defines the Credit Risk Model
β”‚   └── conda.yaml         # Conda environment configurationdata
β”‚ 
β”œβ”€β”€ dep                   # Additional dependency directory added with --dependency-required-folders
β”‚   └── pandas-2.2.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
β”‚ 
β”œβ”€β”€ tests                  # Empty directory reserved for future test 
β”‚   └── ...                # Future tests
|
└── 
  1. Configuring Dependency Management Files:

Conda: Include the .whl file in your conda.yaml as follows:

name: test_model
channels:
  - defaults
  - conda-forge
dependencies:
  - python=3.9
  - pip:
    - "/qwak/model_dir/dep/pandas-2.2.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl"

Requirements.txt: Directly reference the .whl file path:

"/qwak/model_dir/dep/pandas-2.2.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl"

  1. Using the Dependency in Your Code:
    Once the dependency is properly configured, you can import and use it in your Python code as usual:
import pandas as pd


Using OpenCV to build a model

If you add the opencv-python library to your dependencies and import the cv2 module, you will see the following error Exception: Error in importing module libGL.so.1: cannot open shared object file: No such file or directory.

To fix the problem, we need to modify the base Docker image and use qwakai/qwak:0.0.13-opencv-cpu-py39 as the base image. If you use the GPU instance, you should set qwakai/opencv-gpu-py39 as the base image.

We can do it in two ways

We can add the --base-image qwakai/qwak:0.0.13-opencv-cpu-py39 parameter to the qwak models build, or we can use the yaml configuration file. The usage of yaml configuration is described in details in our Build Configurations page.

build_env:
  docker:
    base_image: qwakai/qwak:0.0.13-opencv-cpu-py39