colab_or_not Python Package Documentation

colab_or_not is Python package to help make Jupyter notebooks easily runnable in Google Colab or local environments.

Installation

Install the latest version with pip:

pip install colab-or-not

Overview

If you want to create a Jupyter notebook that can run in Google Colab as well as a local or other environment, there are several annoying things you need to worry about:

1. Installing required Python packages

2. Installing required system packages

3. Installing required Python modules

4. Loading settings

5. Prompting for input files

This package helps you with all of that.

Example usage:

%pip install colab-or-not

from colab_or_not import NotebookBridge

# Set up our notebook environment
notebook_env = NotebookBridge(
    github_repo="higherbar-ai/colab-or-not",
    requirements_path="example-requirements.txt",
    system_packages=[],
    module_paths=[
        "src/example_module.py",
    ],
    config_path="~/.hbai/colab-or-not.env",
    config_template={
        "SETTING_1": "setting 1 value",
        "SETTING_2": "setting 2 value",
    }
)
notebook_env.setup_environment()

# Read and output settings
setting_1 = notebook_env.get_setting("SETTING_1")
setting_2 = notebook_env.get_setting("SETTING_2")
print()
print(f"Setting 1: {setting_1}")
print(f"Setting 2: {setting_2}")

# Use a function in a custom module (adding a type hint to ignore an import warning in Google Colab)
import example_module   # type: ignore[import]
example_module.example_function()

# Prompt user for one or more input files
input_files = notebook_env.get_input_files(prompt="Please select one or more input files")

# Output the list of selected or uploaded input files
print()
if not input_files:
    print("No input files selected or uploaded.")
for input_file in input_files:
    print(f"Input file: {input_file}")

# Output the output directory (here, just the user home directory or Colab content root)
output_dir = notebook_env.get_output_dir(not_colab_dir="~", colab_subdir="")
print()
print(f"Output directory: {output_dir}")

For a runnable version of the above, see the example.ipynb notebook.

Technical details

Loading settings

To load settings from either a configuration file or Google Colab secrets, initialize a NotebookBridge object with a config_path for the configuration file and, optionally, a config_template that contains name-value pairs for default settings. Call the setup_environment() method and then get_setting() for each setting you’d like to read. For example:

from colab_or_not import NotebookBridge

notebook_env = NotebookBridge(
    config_path="~/.hbai/colab-or-not.env",
    config_template={
        "SETTING_1": "setting 1 value",
        "SETTING_2": "setting 2 value",
    }
)

notebook_env.setup_environment()

setting_1 = notebook_env.get_setting("SETTING_1")
setting_2 = notebook_env.get_setting("SETTING_2")

If in Google Colab, the settings will always come from secrets (click the key button in the left sidebar, create each secret, and be sure to click the toggle to give the notebook access to each secret).

If not in Google Colab, setup_environment() will look for the configuration file and, if it’s there, load its settings into the local environment (which is where get_setting() will find them). If the configuration file doesn’t exist, setup_environment() will raise an exception that tells the user they need to configure settings in that configuration file before trying again; if you had specified a config_template, a default configuration file will be written out for the user, based on your template.

Installing Python packages

To install Python packages, you can explicitly add %pip install packagename lines to your notebook, or you can use the NotebookBridge class to automatically install requirements from a requirements.txt file in your GitHub repo. For example:

from colab_or_not import NotebookBridge

notebook_env = NotebookBridge(
    github_repo="higherbar-ai/colab-or-not",
    requirements_path="example-requirements.txt"
)
notebook_env.setup_environment()

Your file can be named anything you like, but it should be in the format of a requirements.txt file. It also doesn’t have to be in the root of your repo; you can specify a path to it, like src/requirements.txt.

Installing system packages

To install system packages, you can explicitly add apt-get, brew, or choco commands, depending on the system, or you can use the NotebookBridge class to automatically install system packages. For example:

from colab_or_not import NotebookBridge

notebook_env = NotebookBridge(
    system_packages=[
        "libreoffice",
    ]
)
notebook_env.setup_environment()

Each system package will be installed using the appropriate package manager for the current system.

Importing custom modules from your GitHub repo

If you need access to one or more .py modules from your GitHub repo, you can use the NotebookBridge class to automatically download and install them locally when running in Google Colab. For example:

from colab_or_not import NotebookBridge

notebook_env = NotebookBridge(
    github_repo="higherbar-ai/colab-or-not",
    module_paths=[
        "src/example_module.py",
    ]
)
notebook_env.setup_environment()

import example_module   # type: ignore[import]
example_module.example_function()

Each module will be downloaded into the Google Colab content folder and that will be added into the Python system path so that import statements will work as expected. (Unfortunately, Google Colab will still show a warning in the text editor about dynamically-loaded modules, which is why we have a # type: ignore[import] comment in our examples.)

Prompting for input files

If you want to read user files in your notebook, you can call the get_input_files() method. For example:

from colab_or_not import NotebookBridge

notebook_env = NotebookBridge()

input_files = notebook_env.get_input_files(prompt="Please select one or more input files")
if not input_files:
    print("No input files selected or uploaded.")
for input_file in input_files:
    print(f"Input file: {input_file}")

When running in Google Colab, the user will be prompted to upload one or more files.

When running locally, the user will be prompted to select one or more files.

Choosing an output directory

If you want to write output files in your notebook, you can call the get_output_dir() method. For example:

from colab_or_not import NotebookBridge

notebook_env = NotebookBridge()

output_dir = notebook_env.get_output_dir(not_colab_dir="~/ai-workflows", colab_subdir="")
print(f"Output directory: {output_dir}")

Your not-colab directory can be any path you like, though you might want to include ~ to start at the current user’s home directory. For Colab, you can optionally specify a subdirectory within the main content folder. Either way, if the directory doesn’t exist, it will be created automatically.

Adding an Open in Colab badge

To add a handy Open in Colab button to the top of your Jupyter notebook, add HTML text like this to the beginning of a Markdown cell at the top:

<a href="https://colab.research.google.com/github/higherbar-ai/colab-or-not/blob/main/src/example.ipynb" target="_parent">
<img alt="Open In Colab" src="https://colab.research.google.com/assets/colab-badge.svg"/>
</a>

Just be sure to update the https://colab.research.google.com/github/higherbar-ai/colab-or-not/blob/main/src/example.ipynb part to point to your own GitHub repo and notebook.

Known issues

(None yet!)

Credits

This toolkit was originally developed by Higher Bar AI, PBC, a public benefit corporation. To contact us, email us at info@higherbar.ai.

Reference

• colab_or_not
  • colab_or_not package
    • Submodules
      • colab_or_not.core module
        • NotebookBridge
    • Module contents

Indices and tables

• Index

• Module Index

• Search Page