Calling Conda Source Activate from Bash Script: A Guide

In this blog, we will learn about the challenges data scientists face while handling diverse Python environments across different projects. A key solution to this is Anaconda, with its widely-used conda command-line tool for environment management. The focus of this post will be on optimizing workflow efficiency by delving into the technique of invoking ‘conda source activate’ from a bash script, enhancing the ease of Python environment management.

As data scientists, we often find ourselves working with various Python environments for different projects. One of the most popular tools for managing these environments is Anaconda, and specifically, the conda command-line tool. In this blog post, we’ll explore how to call conda source activate from a bash script, a technique that can streamline your workflow and make managing your Python environments easier.

Table of Contents:

  1. What is Conda?
  2. Why Use a Bash Script?
  3. How to Call Conda Source Activate from a Bash Script
  4. Potential Issues and Solutions
  5. Pros and Cons of Calling conda activate from Bash Script
  6. Conclusion

What is Conda?

Conda is an open-source package management system and environment management system that runs on Windows, macOS, and Linux. It allows you to create, save, load, and switch between environments on your local computer. It was created for Python programs but can package and distribute software for any language.

Why Use a Bash Script?

Bash scripts prove invaluable for automating repetitive tasks. By incorporating conda source activate within a bash script, data scientists can automate environment activation, execute commands, and deactivate the environment seamlessly.

How to Call Conda Source Activate from a Bash Script

Let’s dive into the process of calling conda source activate from a bash script.

Step 1: Create a Conda Environment

First, you need to create a conda environment. You can do this with the conda create command. For example, to create an environment named my_env, you would use the following command:

conda create --name my_env

Step 2: Write the Bash Script

Compose a bash script that calls conda source activate. Here is an example:


source activate my_env

# Your commands here

conda deactivate

In this script, the source activate my_env command activates the my_env conda environment. You can replace my_env with the name of any conda environment you’ve created.

The conda deactivate command at the end of the script deactivates the environment when you’re done.

Step 3: Run the Bash Script

Finally, you can run the bash script with the bash command:


Replace with the name of your bash script.

Potential Issues and Solutions

While calling conda source activate from a bash script is generally straightforward, you may encounter a few issues.

Issue: Conda Command Not Found

If you get a “conda: command not found” error, it means your bash script can’t find the conda command. This is usually because the conda command isn’t in your PATH.

Solution: You can add the conda command to your PATH by adding the following line to your bash script:

export PATH=/path/to/conda:$PATH

Replace /path/to/conda with the actual path to your conda command.

Issue: Conda Environment Not Activating

If your conda environment isn’t activating, it could be because the source activate command isn’t working.

Solution: Try using the conda activate command instead:

conda activate my_env

Issue: Script Not Activating Conda Environment:


# Incorrect way
conda activate my_environment

# Correct way
source activate my_environment

Ensure you use source activate instead of conda activate to activate the environment within the script.

Issue: Environment Activation Failures:


# Activate environment
source activate my_environment || { echo "Failed to activate Conda environment"; exit 1; }

# Rest of the script

Handle activation failures gracefully by checking the return status and displaying an appropriate error message.

Issue: Conflicts with Active Environments:

Copy code

# Deactivate any existing environment
source deactivate

# Activate desired environment
source activate my_environment

Deactivate any existing environment before activating the desired one to avoid conflicts.

Pros and Cons of Calling conda activate from Bash Script


1. Environment Management: Isolation: Conda environments allow for the isolation of dependencies, ensuring that the script runs with the required packages and versions. Reproducibility: Including environment activation in the script ensures that others can replicate the exact environment, promoting reproducibility.

2. Automation: Simplified Workflow: Automating the activation process in a script streamlines development and deployment workflows. Ease of Integration: Bash scripts are widely used and can be easily integrated into various continuous integration (CI) and continuous deployment (CD) pipelines.

3. Portability: Cross-Platform Compatibility: The script can be shared across different platforms, and as long as Conda is installed, it will work seamlessly.


1. Activation Overhead: Performance Impact: Activating a Conda environment can introduce overhead, especially in large projects, impacting script execution time. Resource Utilization: The activated environment consumes additional resources, which may be undesirable in resource-constrained environments.

2. Potential Conflicts: User Environment: If the script is run in an environment with an active Conda environment, conflicts may arise. It’s essential to handle such scenarios gracefully.


Calling conda source activate from a bash script is a powerful technique that can help you automate your Python environment management. By understanding how to create a conda environment, write a bash script, and troubleshoot potential issues, you can streamline your data science workflow and make your projects more efficient.

About Saturn Cloud

Saturn Cloud is your all-in-one solution for data science & ML development, deployment, and data pipelines in the cloud. Spin up a notebook with 4TB of RAM, add a GPU, connect to a distributed cluster of workers, and more. Join today and get 150 hours of free compute per month.