FAQs
Use pip if you are working with pure Python projects and need access to the vast array of libraries available on PyPI. Use conda if you are working with projects that use multiple languages, need different versions of Python, or require complex binary dependencies.
Which Python package manager should you use? ›
The most widely used Python package manager is pip (short for “pip installs packages”). It comes pre-installed with Python versions 3.4 and later. Pip allows developers to easily install packages from the Python Package Index (PyPI) and other repositories.
Is conda a good package manager? ›
There are three advantages to installing Conda and you should install a package management system like Conda if you intend to tackle data science projects.. Package Management: Conda allows you to install, update and manage packages for multiple programming languages like Python.
What is the best Python dependency manager? ›
- venv (virtual environment) and pip (package installer for python) are the most popular tools for managing dependencies due to their ease of use. ...
- Conda is a cross-platform, open-source package and environment management system. ...
- Conda-lock creates a lightweight lockfile for Conda environments.
While Python is a versatile programming language that can be used for a wide range of applications, Anaconda provides a more specialized environment for machine learning and data science, with pre-installed packages and a package manager that make it easier to manage dependencies and resolve conflicts between packages.
Why use Anaconda instead of Python? ›
Environment Setup
Anaconda comes with its own set of pre-installed data science packages and tools, making it convenient for beginners to set up their environment quickly. Python, on the other hand, requires users to manually install the required libraries and tools.
What is the difference between conda and pip package manager? ›
Conda pulls precompiled binaries from its repository, significantly speeding up installations. Pip, on the other hand, fetches from PyPI, compiling packages during installation. Conda's binaries mean fewer compatibility issues, especially on Windows.
Is npm the best package manager? ›
Overall, npm offers a robust and feature-rich package management solution that addresses the needs of developers building Node. js applications. Its extensive package repository, mature ecosystem, comprehensive CLI, and community support make it a preferred choice for JavaScript developers worldwide.
Is PyCharm a package manager? ›
PyCharm provides methods for installing, uninstalling, and upgrading Python packages for a particular Python interpreter. It means that each project has its own set of packages, which is considered a best practice for Python dependency management. By default, PyCharm uses pip to manage project packages.
Should I use Anaconda or conda? ›
If Anaconda doesn't include a package that you need, you use conda to download and install it. If Anaconda doesn't have the version of a package you need, you use conda to update it.
Choosing the right environment management tool depends on your needs. If you need a simple, easy-to-use tool, venv might be the best choice. If you're dealing with complex dependencies, Conda env is the way to go. If you need to switch between different Python versions, consider pyenv or virtualenv.
Can you use both pip and conda? ›
It is possible to have pip installed outside a conda environment or inside a conda environment. To gain the benefits of conda integration, be sure to install pip inside the currently active conda environment and then install packages with that instance of pip.
What tool do most Python developers use? ›
Top Python developer tools
- PyCharm IDE. PyCharm is one of the best Python tools. ...
- Keras. Keras is a deep learning API written in Python language. ...
- Vim. Vim is a text editor that is an enhanced version of the UNIX editor Vi. ...
- Sublime Text. Sublime Text is a lightweight text editor that creates clean Python code.
setuptools is now the recommended way to build and distribute Python packages. It is a package in the Python standard library that provides tools for building and distributing Python packages, and it includes support for many features that are not available in the distutils module.
What is the default Python package manager? ›
Pip: The Standard Package Manager
Pip is built-in into Python and can install packages from many different sources. But PyPI.org is the primary and default package source used. By default, pip installs packages onto a project's global Python environment resulting in packages being accessible by all projects.
Do I need pip if I have conda? ›
Both pip and conda are included in Anaconda and Miniconda, so you do not need to install them separately. Conda environments replace virtualenv, so there is no need to activate a virtualenv before using pip. It is possible to have pip installed outside a conda environment or inside a conda environment.
Should I create virtual environment or Anaconda? ›
The choice between venv and Anaconda depends on your needs: For minimal environments: If you prefer lightweight, minimal environments, venv is the better choice. For data science projects: If you're working on data science projects and need a wide range of pre-installed packages, Anaconda is more suitable.
Is pip the same as conda? ›
In short, pip is a general-purpose manager for Python packages; conda is a language-agnostic cross-platform environment manager. For the user, the most salient distinction is probably this: pip installs python packages within any environment; conda installs any package within conda environments.
Is it better to install Anaconda? ›
On Windows, macOS, and Linux, it is best to install Anaconda for the local user, which does not require administrator permissions and is the most robust type of installation. However, with administrator permissions, you can install Anaconda system wide.
