How to Solve Python ModuleNotFoundError: no module named ‘google’

by | Programming, Python, Tips

A common error you may encounter when using Python is modulenotfounderror: no module named ‘google’.

You can solve this error by installing the product-specific google-cloud-* package

For example, if we want to install google-cloud-bigquery in Python 3 we can use: python3 -m pip install google-cloud-bigquery.

Or conda install -c anaconda google-cloud-bigquery for conda environments.

This tutorial goes through the exact steps to troubleshoot this error for the Windows, Mac, and Linux operating systems.


How to Solve Python ModuleNotFoundError: no module named ‘google.cloud’

What is Google Cloud

Google Cloud has a set of Python idiomatic clients for Google Cloud Platform services. The packages are consistently named google-cloud-*, where the asterisk stands in place for the name of the package you want to install.

Example

Let’s look at an example to reproduce the error:

from google.cloud import bigquery

Let’s run the code to see the result:

---------------------------------------------------------------------------
ModuleNotFoundError                       Traceback (most recent call last)
Input In [2], in <cell line: 1>()
----> 1 from google.cloud import bigquery

ModuleNotFoundError: No module named 'google'

The Python interpreter cannot find the google module in the environment. We need to install the relevant package that you want to use in your application. In this case, we need to install google-cloud-bigquery. Every Python API client has the google-cloud- prefix.

The simplest way to install google-cloud-* packages is to use the package manager for Python called pip. The following installation instructions are for the major Python version 3.

Always Use a Virtual Environment to Install Packages

It is always best to install new libraries within a virtual environment. You should not install anything into your global Python interpreter when you develop locally. You may introduce incompatibilities between packages, or you may break your system if you install an incompatible version of a library that your operating system needs. Using a virtual environment helps compartmentalize your projects and their dependencies. Each project will have its environment with everything the code needs to run. Most ImportErrors and ModuleNotFoundErrors occur due to installing a library for one interpreter and trying to use the library with another interpreter. Using a virtual environment avoids this. In Python, you can use virtual environments and conda environments. We will go through how to install google-cloud-* packages with both.

How to Install Google Cloud Big Query API on Windows Operating System

First, you need to download and install Python on your PC. Ensure you select the install launcher for all users and Add Python to PATH checkboxes. The latter ensures the interpreter is in the execution path. Pip is automatically on Windows for Python versions 2.7.9+ and 3.4+.

You can check your Python version with the following command:

python3 --version

You can install pip on Windows by downloading the installation package, opening the command line and launching the installer. You can install pip via the CMD prompt by running the following command.

python get-pip.py

You may need to run the command prompt as administrator. Check whether the installation has been successful by typing.

pip --version
virtualenv env

You can activate the environment by typing the command:

# Activate on Windows

env\Scripts\activate

# Activate on Windows (cmd.exe)

env\Scripts\activate.bat

# Activate on Windows (PowerShell)

env\Scripts\Activate.ps1

You will see “env” in parenthesis next to the command line prompt. You can install google-cloud-storage within the environment by running the following command from the command prompt.

python3 -m pip install google-cloud-bigquery

We use python -m pip to execute pip using the Python interpreter we specify as Python. Doing this helps avoid ImportError when we try to use a package installed with one version of Python interpreter with a different version. You can use the command which python to determine which Python interpreter you are using.

How to Install Google Cloud Big Query API on Mac Operating System using pip

Open a terminal by pressing command (⌘) + Space Bar to open the Spotlight search. Type in terminal and press enter. To get pip, first ensure you have installed Python3:

python3 --version
Python 3.8.8

Download pip by running the following curl command:

curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py

The curl command allows you to specify a direct download link. Using the -o option sets the name of the downloaded file.

Install pip by running:

python3 get-pip.py

To install google-cloud-bigquery, first, create the virtual environment:

python3 -m venv env

Then activate the environment using:

source env/bin/activate 

You will see “env” in parenthesis next to the command line prompt. You can install google-cloud-bigquery within the environment by running the following command from the command prompt.

python3 -m pip install google-cloud-bigquery

How to Install Google Cloud Big Query API on Linux Operating Systems

All major Linux distributions have Python installed by default. However, you will need to install pip. You can install pip from the terminal, but the installation instructions depend on the Linux distribution you are using. You will need root privileges to install pip. Open a terminal and use the commands relevant to your Linux distribution to install pip.

Installing pip for Ubuntu, Debian, and Linux Mint

sudo apt install python-pip3

Installing pip for CentOS 8 (and newer), Fedora, and Red Hat

sudo dnf install python-pip3

Installing pip for CentOS 6 and 7, and older versions of Red Hat

sudo yum install epel-release

sudo yum install python-pip3

Installing pip for Arch Linux and Manjaro

sudo pacman -S python-pip

Installing pip for OpenSUSE

sudo zypper python3-pip

google-cloud-bigquery Installation on Linux with Pip

To install google-cloud-bigquery, first, create the virtual environment:

python3 -m venv env

Then activate the environment using:

source env/bin/activate 

You will see “env” in parenthesis next to the command line prompt.

Once you have activated your virtual environment, you can install google-cloud-bigquery using:

python3 -m pip install google-cloud-bigquery

Installing Google Cloud Big Query API Using Anaconda

Anaconda is a distribution of Python and R for scientific computing and data science. You can install Anaconda by going to the installation instructions. Once you have installed Anaconda, you can create a virtual environment and install google-cloud-bigquery.

To create a conda environment you can use the following command:

conda create -n project python=3.8

You can specify a different Python 3 version if you like. Ideally, choose the latest version of Python. Next, you will activate the project container. You will see “project” in parentheses next to the command line prompt.

source activate project

Now you’re ready to install google-cloud-bigquery using conda.

Once you have installed Anaconda and created your conda environment, you can install google-cloud-bigquery using the following command:

conda install -c conda-forge google-cloud-bigquery

Check Google Cloud Big Query API Version

Once you have successfully installed google-cloud-bigquery, you can check its version. If you used pip to install google-cloud-bigquery, you can use pip show from your terminal.

python3 -m pip show google-cloud-bigquery
Name: google-cloud-bigquery
Version: 3.3.0
Summary: Google BigQuery API client library
Home-page: https://github.com/googleapis/python-bigquery

You can also check the version of google-cloud-bigquery by importing the module and printing the __version__ attribute.

from google.cloud import bigquery
print(bigquery.__version__)
3.3.0

If you used conda to install google-cloud-bigquery, you could check the version using the following command:

conda list -f google-cloud-bigquery
# Name                    Version                   Build  Channel
google-cloud-bigquery     3.2.0              pyhd8ed1ab_0    conda-forge

Summary

Congratulations on reading to the end of this tutorial.

Go to the online courses page on Python to learn more about Python for data science and machine learning.

For further reading on missing modules in Python, go to the articles:

Have fun and happy researching!

Research Scientist at Moogsoft | + posts

Suf is a research scientist at Moogsoft, specializing in Natural Language Processing and Complex Networks. Previously he was a Postdoctoral Research Fellow in Data Science working on adaptations of cutting-edge physics analysis techniques to data-intensive problems in industry. In another life, he was an experimental particle physicist working on the ATLAS Experiment of the Large Hadron Collider. His passion is to share his experience as an academic moving into industry while continuing to pursue research. Find out more about the creator of the Research Scientist Pod here and sign up to the mailing list here!