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Python is a programming language and the interpreter that runs it. Anaconda Distribution is an installer that includes Python, so the two are not alternatives at the same level. When people ask about the difference between Python and Anaconda, the practical choice is between installing Python on its own from python.org and managing packages with pip and venv, or installing a bundle that adds conda, Anaconda Navigator and a large set of data science packages.
What it is used for in research
Research code in statistics, bioinformatics and data analysis usually depends on many third-party packages. Both routes below give you the same Python language; they differ in what arrives with the installer and in how you isolate the packages for one project from another. For the analysis libraries themselves, see the guide to pandas and SciPy for data analysis in Python.
What is the difference between Python and Anaconda?
Python is the language and its interpreter. Anaconda Distribution installs conda, Python, and Anaconda Navigator, plus what Anaconda’s documentation calls “hundreds of popular data science and machine learning packages” (Anaconda documentation).
What is the difference between Anaconda and Python?
The same difference, seen from the other direction: Anaconda Distribution is an installer that bundles conda, a Python interpreter, Anaconda Navigator and a large package set. Python from python.org is the interpreter and standard library, with pip included for installing packages from PyPI.
Does Anaconda include Python?
Yes. Python is installed as part of Anaconda Distribution, and so is conda. You do not need to install Python separately first.
Install or access
There are three common starting points. The package counts and disk sizes for the two Anaconda options are the vendor’s own figures from its comparison page; the python.org route is described from the Python documentation.
| Option | What you get | Package manager | Source |
|---|---|---|---|
| Python from python.org, plus venv | The interpreter and standard library; pip is included by default with the Python binary installers; venv creates isolated environments | pip, installing from PyPI | docs.python.org, “Installing Python Modules” |
| Miniconda | conda and Python with their dependencies only; “no extra packages and no graphical interface”; about 130+ packages and about 900 MB | conda | Anaconda documentation, “Anaconda or Miniconda” |
| Anaconda Distribution | conda, Python, Anaconda Navigator and a large bundled package set; more than 600 packages and about 9.7 GB of install space | conda | Anaconda documentation, “Anaconda or Miniconda” |
Anaconda’s documentation describes Miniconda as suited to people who work from the command line, and to containers and CI/CD, because you build each environment yourself. Install links and current installers are on Anaconda’s comparison page and the Python documentation. If your goal is to run notebooks, Anaconda for Jupyter Notebook covers installing and opening it.
Step-by-step: create an environment each way
An environment keeps the packages for one project separate from the rest of your machine. Python’s documentation describes a virtual environment as “a semi-isolated Python environment that allows packages to be installed for use by a particular application, rather than being installed system wide,” and names venv as the standard tool for creating one. Conda’s documentation says conda “allows you to create separate environments, each containing their own files, packages, and package dependencies.”
With Python, venv and pip
- Create the environment:
python -m venv /path/to/new/virtual/environment. On Windows PowerShell the documented form ispython -m venv C:\path\to\new\virtual\environment. - Activate it. On POSIX bash or zsh:
source <venv>/bin/activate. On Windows cmd.exe:<venv>\Scripts\activate.bat. On Windows PowerShell:<venv>\Scripts\Activate.ps1. Replace<venv>with the path to the directory holding the environment. - Install packages with pip while the environment is active. The Python documentation notes that venv installs pip into every environment it creates by default.
- When finished, type
deactivatein the same shell.
With conda (Miniconda or Anaconda)
- Create the environment:
conda create --name <env-name>. - Activate it:
conda activate myenvironment, using your own environment’s name in place of the example name used in the conda documentation. - List your environments:
conda info --envs.
The conda documentation describes conda as a command line tool for package and environment management that runs on Windows, macOS and Linux (conda documentation, “Getting started”).
Output and how to read it
After python -m venv, the target directory contains a pyvenv.cfg file whose home key points to the Python installation the command was run from, a bin subdirectory (Scripts on Windows) with a copy or symlink of the Python executable, and a site-packages subdirectory (lib/pythonX.Y/site-packages, or Lib\site-packages on Windows) where pip installs packages. Reading pyvenv.cfg tells you which base Python an environment was built on.
The venv documentation says a virtual environment is created on top of an existing “base” Python and, by default, is isolated from the packages in that base environment, so only packages installed in the environment are available. The conda route differs in what is stored: each conda environment holds its own packages and dependencies, and conda info --envs is the documented command for listing the environments you have.
For sharing an environment with collaborators, see sharing a reproducible conda environment.
Troubleshooting
- The venv will not move to another machine or folder. The Python documentation states that “environments are inherently non-portable, in the general case” and that you should always have a simple means of recreating an environment. Record your dependencies and rebuild rather than copying the folder.
- A package with compiled dependencies is hard to install with pip. The Python documentation says packages with complex binary dependencies are often easier to install by other means than pip, and points to the scientific software guidance at packaging.python.org.
- Mixing pip and conda in one environment. If a project needs both tools, see conda, pip and mamba in one environment.
- Choosing between conda and mamba. See Mamba vs Conda for how the two tools compare for research environments.
Options compared at a glance
| Question | Python + venv + pip | Miniconda | Anaconda Distribution |
|---|---|---|---|
| Includes Python? | Yes, it is Python | Yes | Yes |
| Includes a graphical interface? | Not given in the Python installation documentation | No | Yes, Anaconda Navigator |
| Bundled packages | Standard library; pip fetches others from PyPI | About 130+ packages | More than 600 packages |
| Approximate install space | Not given in the Python installation documentation | About 900 MB | About 9.7 GB |
| Environment tool | venv | conda | conda |
Free alternatives
If the full Anaconda Distribution is more than you need, these two routes give you Python and an environment manager with less installed.
| Alternative | What it gives you | Source |
|---|---|---|
| Python from python.org with venv and pip | The interpreter and standard library, venv for isolated environments, and pip for installing packages from PyPI | docs.python.org, “Installing Python Modules” and “venv” |
| Miniconda | A minimal install of conda, Python and their dependencies, with no extra packages and no graphical interface; you build each environment yourself | Anaconda documentation, “Anaconda or Miniconda” |
FAQ
Is Anaconda a different programming language from Python?
No. Anaconda Distribution is software that installs Python along with conda, Anaconda Navigator and a package collection. The code you write is Python either way.
Do I need both Python and Anaconda?
No. Anaconda Distribution already installs Python. If both are present on one machine, check which interpreter an activated environment is using.
Which tool does the Python documentation recommend for virtual environments?
It names venv as the standard tool for creating virtual environments and pip as the preferred installer program. The page does not mention conda.
Where can I check the commands on this page?
Every command above comes from the documentation listed under Sources.
Sources
- Anaconda documentation, Anaconda or Miniconda. Checked 2026-10-29.
- Python documentation, Installing Python Modules. Checked 2026-10-29.
- Python documentation, venv: Creation of virtual environments. Checked 2026-10-29.
- conda documentation, Getting started with conda. Checked 2026-10-29.
