When installing Python packages via pip, you may occasionally encounter the frustrating error:
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error: metadata-generation-failed
This error prevents the package from being installed properly. But don’t worry – in most cases, this error can be easily fixed.
In this guide, we’ll cover:
- What causes the “metadata-generation-failed” error
- Common fixes and workarounds
- How to prevent it from happening in the future
Knowing the right troubleshooting steps can save you significant headaches and effort when encountering this error during Python package installation.
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What Causes the “Metadata-Generation-Failed” Error?
The “metadata-generation-failed” error appears during the wheel-building process. Wheels are a built archive format that contains Python packages in a pre-compiled, optimized format.
When pip tries to build a wheel for a package, metadata generation extracts info from the package into a metadata folder. If this process fails, it results in the “metadata-generation-failed” error.
Some common triggers for this error include:
- Issues with the source package code itself
- Incompatibility with the current Python version
- Missing compilers or dependencies on your system
Later sections cover specific fixes for these causes. Understanding the root of the problem makes troubleshooting much easier.
Now let’s look at solutions to try when faced with the metadata generation failure error.
Fixes for the “Metadata-Generation-Failed” Error
Several methods can resolve the dreaded “metadata-generation-failed” message. Try these top fixes to get past the error and successfully install your Python packages.
Fix 1: Check Your Python Version
One of the most common causes of metadata generation errors is incompatibility with your Python version.
For example, a wheel meant for Python 3.7 may fail to build properly when pip tries to install it into a Python 3.9 environment.
To check your active Python version, run:
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python --version
Or for version inside a virtual environment:
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python -m virtualenv --version
Make sure you’re using the latest minor version of Python for your major release. For example, use Python 3.8 or 3.9 instead of 3.7.
Upgrading your Python installation to the newest available minor version often resolves metadata issues.
Fix 2: Reinstall Package with –no-binary Flag
Some packages rely on pre-built binary wheels. When these fail metadata generation, reinstalling from source without binaries can help.
First, uninstall the package causing issues:
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pip uninstall pkgname
Next, reinstall using the –no-binary flag:
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pip install --no-binary :all: pkgname
This forces Pip to build the package from its source instead of downloading a pre-compiled wheel. Avoiding the wheel skips the metadata generation step entirely.
Fix 3: Clear the pip Cache
An outdated or corrupt pip download cache can also trigger metadata failures.
To erase the pip cache:
- Locate your pip cache directory:
<!—->
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pip cache dir
- Delete all files inside the cache folder. 3. Reinstall the package that was failing:
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pip install pkgname
With the corrupted cache cleared, pip may now build the wheel successfully.
Fix 4: Upgrade pip and setup tools
Making sure you have the latest versions of pip and setup tools can help avoid issues during wheel creation.
Upgrade both using:
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pip install -U pip setuptools
Then try installing the package again. The most recent pip and setuptools sometimes resolve dependencies that previous versions missed.
Fix 5: Check Compile Requirements
Some Python packages require additional compilers or libraries to build properly.
Carefully read the error output – it may indicate missing C compilers like gcc/g++, or lacking libraries like Python. h headers.
Install any missing build tools needed for your system:
- Ubuntu/Debian: sudo apt-get install build-essential
- Fedora: sudo dnf group install “Development Tools”
- MacOS: Install XCode command line tools
Meeting all required build dependencies allows metadata generation to be completed successfully.
With the right tools present, reattempt installing the Python package.
Resolving “Metadata-Generation-Failed” for psycopg2
The popular psycopg2 library for connecting to PostgreSQL databases commonly suffers metadata generation errors.
Here are two specific methods for fixing psycopg2 installation issues.
Use Conda to Install psycopg2
If you have the Anaconda Python distribution, use its conda package manager:
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conda install psycopg2
This often builds psycopg2 properly when pip fails.
Make sure to run the conda command for your specific environment if using a virtual or conda env.
Compile psycopg2 from Source Without Binaries
As covered earlier, forcing source compilation avoids metadata problems:
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pip install --no-binary :all: psycopg2
Or on Linux, install build dependencies before compiling from source:
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sudo apt-get build-dep python-psycopg2
pip install --no-binary psycopg2 psycopg2
This approach reliably builds psycopg2 from scratch, sidestepping metadata issues.
Fixing “Metadata-Generation-Failed” in Pipenv
The popular Pipenv tool for managing virtual environments can also suffer metadata generation errors.
Try these tips for fixing pipenv installs.
Set PIPENV_SKIP_LOCK=1
Creating Pipenv lock files can sometimes trigger metadata failures.
Setting this environment variable prevents locking:
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PIPENV_SKIP_LOCK=1 pipenv install
After installation, remove the variable to re-enable locking.
Rebuild Pipenv Environment
Alternatively, completely rebuild your Pipenv environment:
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pipenv --rm pipenv install
This may avoid inconsistencies that cause metadata issues when installing packages.
Preventing Future “Metadata-Generation-Failed” Errors
Once you’ve resolved the immediate error, take steps to prevent metadata failures when installing Python packages in the future.
Use Virtual Environments
Developing Python applications inside virtual environments isolates your dependencies and avoids conflicts.
Tools like virtualenv and Python 3’s built-in venv module make managing virtual environments easy.
Always install packages inside a virtualenv rather than globally.
Pin Package Versions
Freezing package versions in a requirements.txt file prevents unexpected breakage when upstream packages get updated.
Add packages to your requirements file as you install them:
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pip freeze > requirements.txt
Then install from the locked requirements to avoid metadata shocks:
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pip install -r requirements.txt
This pins all packages to versions known to work together.
Frequently Asked Questions (FAQ)
What is metadata generation in Python?
Metadata generation is the process of extracting information from a Python package into a metadata folder when Pip builds a wheel file. This metadata enables proper installation.
Why does this error happen with wheel packages?
Wheels contain pre-built binaries and require metadata generation to install properly. If this process fails, it results in the “metadata-generation-failed” error.
Is the “Metadata-Generation-Failed” error related to the Python version?
Yes, often it indicates an incompatibility between the wheel file and the current Python version, such as using a 3.7 wheel on Python 3.9. Upgrading Python can resolve this.
How can I prevent this error when installing packages?
Use virtual environments, upgrade pip/setuptools regularly, install build tools, and pin package versions in a requirements.txt file to avoid metadata issues.
What’s the best way to troubleshoot “Metadata-Generation-Failed”?
Try cleaning builds without binaries, clearing the pip cache, installing compiler tools, and checking the Python version first. Read the error closely for missing dependency info.
Conclusion
The “metadata-generation-failed” error can certainly be annoying. But as you’ve seen, in most cases it can be quickly resolved.
The key is to:
- Double-check check Python version and virtual environment setup
- Try clean builds from source using –no-binary
- Make sure all compiler tools and dependencies are installed
- Consider conda for psycopg2 and other tricky builds
With these tips, you can breeze past metadata generation errors and continue with Python package installation. Careful dependency management can help avoid the issue altogether.
Now you have the confidence to troubleshoot those cryptic metadata failures!
Mustafa Al Mahmud is the founder and owner of Gizmo Concept, a leading technology news and review site. With over 10 years of experience in the tech industry, Mustafa started Gizmo Concept in 2017 to provide honest, in-depth analysis and insights on the latest gadgets, apps, and tech trends. A self-proclaimed “tech geek,” Mustafa first developed a passion for technology as a computer science student at the Hi-Tech Institute of Engineering & Technology. After graduation, he worked at several top tech firms leading product development teams and honing his skills as both an engineer and innovator. However, he always dreamed of having his own platform to share his perspectives on the tech world. With the launch of Gizmo Concept, Mustafa has built an engaged community of tech enthusiasts who look to the site for trusted, informed takes on everything from smartphones to smart homes. Under his leadership, Gizmo Concept has become a top destination for tech reviews, news, and expert commentary. Outside of running Gizmo Concept, Mustafa is an avid traveler who enjoys experiencing new cultures and tech scenes worldwide. He also serves as a tech advisor and angel investor for several startups. Mustafa holds a B.S. in Computer Science from HIET.