DataSpell 2023.3 Help

Create a project

Python projects are intended for managing Jupyter notebooks and Python scripts. A project helps you organize your source code, tests, libraries that you use, and your personal settings in a single unit.

For more information about creating R projects, refer to R plugin support.

Create a Python project

  1. To create a project, do one of the following:

  2. In the New Project dialog, select the desired project type:

    Jupyter

    The project virtual environment has Jupyter pre-installed. By default, a conda virtual environment is used.

    pandas Tables

    The project virtual environment has the following packages pre-installed:

    • pandas

    • matplotlib

    • numpy

    • Jupyter (optional)

    By default, a conda virtual environment is used.

    Polars Tables

    The project virtual environment has the following packages pre-installed:

    • Polars

    • matplotlib

    • Jupyter (optional)

    By default, a virtualenv environment is used.

    Pure Python

    The project virtual environment doesn't contain any pre-installed packages, except for optional Jupyter. By default, a conda virtual environment is used.

    dbt

    The project virtual environment has the dbt® package pre-installed. By default, a virtualenv environment is used.

  3. Specify the project name in the Name field and location in the Location field. DataSpell will create the project directory in the provided location.

    Creating a Pure Python project
  4. Select the Create Git repository checkbox to place the new project under version control.

    You will be able to do it later at any time.

  5. Keep the Create sample Jupyter notebook enabled if you want DataSpell to add sample.ipynb to your project. In this case Jupyter will be installed in the project virtual environment.

    If necessary, enable Create sample Python script to add main.py with a basic Python code sample.

  6. For dbt project type, you will need a profiles.yml file, where database connection settings are stored.

    Specify Profiles location and select Profile to load

    Specify dbt profile
  7. If necessary, expand the Interpreter Settings section and configure the environment options. You can select Conda or Virtualenv:

    Configuring conda environment for a new project
    • Normally, DataSpell will detect conda installation.

      Otherwise, specify the location of the conda executable, or click Conda executable location to browse for it.

    • Specify the environment name.

    Configuring virtuaenv environment for a new project
    • Specify the location of the new virtual environment in the Location field, or click Virtual environment location and browse for the desired location in your file system. The directory for the new virtual environment should be empty.

    • Choose the base interpreter from the list, or click Choose the base interpreter and find the desired Python executable in your file system.

    • Select the Inherit global site-packages checkbox if you want all packages installed in the global Python on your machine to be added to the virtual environment you're going to create. This checkbox corresponds to the --system-site-packages option of the virtualenv tool.

Last modified: 21 February 2024