Both pip install kedro and conda install -c conda-forge kedro install the core Kedro module, which includes the CLI tool, project template, pipeline abstraction, framework, and support for configuration.

When you create a project, you then introduce additional dependencies for the tasks it performs.

Declare project-specific dependencies

When you create a new Kedro project, Kedro generates a requirements.txt file in the root directory of the project. The file contains the core dependencies and those related to the tools you choose to include in the project. Specifying the project’s exact dependencies in a requirements.txt file makes it easier to run the project in the future, and avoids version conflicts downstream.

Install project-specific dependencies

When someone clones your project, they can install the project-specific dependencies by navigating to the root directory of the project and running the following command:

pip install -r requirements.txt

Reproducible environments

To ensure that the project dependencies and the transitive dependencies are pinned to specific versions, use pip-tools to compile requirements.txt file into a requirements.lock file. To install pip-tools in your virtual environment, run the following command:

pip install pip-tools

To add or remove dependencies to a project, edit the requirements.txt file, then run the following:

pip-compile <project_root>/requirements.txt --output-file <project_root>/requirements.lock

This will pip compile the requirements listed in the requirements.txt file into a requirements.lock that specifies a list of pinned project dependencies(those with a strict version). You can also use this command with additional CLI arguments such as --generate-hashes to use pip’s Hash Checking Mode or --upgrade-package to update specific packages to the latest or specific versions. Check out the pip-tools documentation for more information.


The requirements.txt file contains “source” requirements, while requirements.lock contains the compiled version of those and requires no manual updates. If you need to update the dependencies, update the requirements.txt file and re-run the pip-compile command.