Conda VS Python Package Index

Compare Conda VS Python Package Index and see what are their differences

TimeLake.io

Improve team performance continuously with time tracking automation. featured

Contents:

» Base Details
» Videos
» Reviews
» Alternatives

Conda

Binary package manager with support for environments.

Python Package Index

A repository of software for the Python programming language

Not present

Landing page //
2023-05-01

Conda

Website: docs.conda.io
$ Details: -

Edit details

Python Package Index

Website: pypi.org
$ Details

Edit details

Conda features and specs

Cross-Platform Package Manager
Conda is a versatile package manager that works across multiple operating systems including Windows, macOS, and Linux, making it a universal solution for environment management.
Environment Management
Conda can create, export, list, remove, and manage environments that contain different versions of Python and/or various packages, enhancing reproducibility and isolation.
Wide Range of Packages
Conda supports a broad spectrum of packages not limited to Python, which means it can install software and their dependencies from the C, C++, FORTRAN, and other ecosystems.
Binary Package Delivery
Packages are delivered as binaries, meaning you don't have to compile anything. This speeds up the installation process and reduces the possibility of errors.
Easy Dependency Resolution
Conda automatically manages dependencies, ensuring that the required packages are installed in the correct versions and reducing compatibility issues.
Version Control
It allows you to manage different versions of software and switch between them seamlessly without conflict, which is crucial for development, testing, and deployment.

Possible disadvantages of Conda

Large Disk Space Requirement
Conda environments can take up a significant amount of disk space due to the inclusion of multiple versions of Python and other binaries.
Complexity
While Conda is powerful, its comprehensive set of features may be overwhelming for beginners who only need simpler package management.
Performance Overhead
The convenience of automated dependency resolution and environment management can sometimes come at the cost of performance, particularly during the first setup.
Slower Package Availability
Newer versions of some packages may take longer to become available on Conda compared to other package managers like pip, leading to potential delays in adopting the latest features.
Third-Party Channels
While Conda has its main channel, many packages are hosted on third-party channels, which can lead to inconsistencies or reliability issues.
Not Limited to Python
Although this is also a strength, for users who are primarily working with Python, Conda might feel over-engineered for their needs.

Python Package Index features and specs

Extensive Library Collection
PyPI hosts a comprehensive collection of Python libraries and packages, enabling developers to find tools and modules for almost any task, from data analysis to web development.
Ease of Use
The PyPI interface is user-friendly, and installation of packages can be quickly done using pip, Python's package installer. This makes it easy for both beginners and advanced users to manage dependencies.
Community Support
Many PyPI packages are well-documented and supported by a large community of developers, which provides reassurance and assistance through forums, tutorials, and user contributions.
Regular Updates
Packages on PyPI are frequently updated by maintainers to include new features, improvements, and security patches, ensuring that developers have access to the latest and most secure versions.
Open Source
PyPI primarily hosts open-source packages, promoting transparency, collaboration, and the ability to modify packages to better suit individual needs.

Possible disadvantages of Python Package Index

Quality Assurance
Not all packages on PyPI are of high quality or well-maintained. Some may have bugs, lack proper documentation, or not adhere to best practices, requiring users to vet packages carefully.
Security Risks
There is a risk of downloading malicious packages since PyPI allows anyone to upload packages. Users need to be cautious and verify the credibility of the package authors and sources.
Dependency Management
Managing dependencies can become complex, especially for large projects, as conflicts between package versions can arise, leading to potential runtime issues.
Overhead
For smaller projects or those with specific needs, the sheer number of available packages can be overwhelming, making it difficult to find the most suitable one without investing a significant amount of time.
Legacy Packages
Some packages on PyPI may no longer be maintained or updated, which can represent a risk if they become incompatible with newer versions of Python or other dependencies.

Conda videos

No Conda videos yet. You could help us improve this page by suggesting one.

Add video

Python Package Index videos

+ Add

Python Django - Create and deploy packages to PyPI - Python Package Index

Category Popularity

0-100% (relative to Conda and Python Package Index)

Python Package Index

Front End Package Manager

73 73%

Front End Package Manager

27% 27

Translation Service

0 0%

Translation Service

100% 100

Package Manager

77 77%

Package Manager

23% 23

Developer Tools

64 64%

Developer Tools

36% 36

User comments

Share your experience with using Conda and Python Package Index. For example, how are they different and which one is better?

Social recommendations and mentions

Based on our record, Python Package Index should be more popular than Conda. It has been mentiond 83 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Conda mentions (32)

Say Hello to UV: A Fast Python Package & Project Manager Written in Rust
If you’ve been managing Python projects long enough, you’ve probably dealt with a mess of tools: pip, pip-tools, poetry, virtualenv, conda, maybe even pdm. - Source: dev.to / 16 days ago
The Simplest Data Architecture
You can use isolated Python environments like venv or conda. If you do this, you'll have to manage your environments yourself, and also constantly switch between them to run your data engineering code vs dbt. - Source: dev.to / 7 months ago
Python's virtual environments
Conda is an open-source package management system and environment management system that runs on Windows, macOS, and Linux. It is a powerful tool that allows you to create and manage virtual environments, install and update packages, and manage dependencies. Conda is particularly popular in the scientific computing community, as it provides access to a wide range of scientific computing libraries and tools. I... - Source: dev.to / 10 months ago
Introducing Flama for Robust Machine Learning APIs
When dealing with software development, reproducibility is key. This is why we encourage you to use Python virtual environments to set up an isolated environment for your project. Virtual environments allow the isolation of dependencies, which plays a crucial role to avoid breaking compatibility between different projects. We cannot cover all the details about virtual environments in this post, but we encourage... - Source: dev.to / over 1 year ago
Ask HN: Package management for multiple modules in C++, Python, Java project?
Conda https://docs.conda.io/en/latest/ ?? I'm not sure, but I used it to download some Python packages. It's an alternative to pip, but I'm not sure about the details. - Source: Hacker News / over 1 year ago

Python Package Index mentions (83)

Solving SSL Certificate Verification Issues with pip on macOS
# Check if Python can connect to pypi.org Python -c "import urllib.request; urllib.request.urlopen('https://pypi.org')" # Test where Python is looking for certificates Python -c "import ssl; print(ssl.get_default_verify_paths())" # Check pip configuration Pip config debug. - Source: dev.to / about 1 month ago
What I wish I knew about Python when I started
But let me back up and start from the perspective of a total Python beginner, as that is who this post is intended for. In Python, there are a lot of built-in libraries available to you via the Python Standard Library. This includes packages like datetime which allows you to manipulate dates and times, or like smtplib which allows you to send emails, or like argparse which helps aid development of command line... - Source: dev.to / about 2 months ago
Python Project Setup With uv – Virtual Environments and Package Management
Virtual Environments are isolated Python environments that have their own site-packages. Basically, it means that each virtual environment has its own set of dependencies to third-party packages usually installed from PyPI. - Source: dev.to / 3 months ago
Getting Started With Pipenv
Where can I find packages available for me to use in my project? At https://pypi.org/ of course! - Source: dev.to / 3 months ago
Create a python package and publish.
To upload your package to PyPI, you need to create an account on PyPI. - Source: dev.to / 4 months ago