Please note: if you are attempting to download one of our installers using a Chrome browser and receive a malicious software warning, this is because we are in the process of Google-verifying these installers; until that process is complete you will likely encounter this warning.These files are not malicious and have not been compromised.
If you have any additional concerns, we encourage you to verify the MD5 sums of these installers against our repository. We apologize for the inconvenience.
Anaconda is a completely free Python distribution (including for commercial use and redistribution). It includes over 195 of the most popular Python packages for science, math, engineering, data analysis.
Choose Your Installer:
*Anaconda comes with installers for Python 2.7 and 3.4. You can use Python 2.6 and 3.3 by installing either the 2.7 or 3.4 version of Anaconda and using the conda command. You can also create a 3.4 environment with the conda command if you've downloaded 2.7 and vice versa.
If you do not want to download the entire distribution, Miniconda is also available. Miniconda contains only conda and Python, so that you can install only the individual packages you want through the conda command. You can download Miniconda here.
For older versions of Anaconda installers, visit the installer archive or the Anaconda 3.4 installer archive. For long-term support of the packages found in the Anaconda archives, please visit the Anaconda Server page or contact email@example.com.
Looking for more?
Getting started with Anaconda Anaconda Quick Start Guide
Free Community Support for Anaconda Anaconda mailing list
Information on Installation and Use online documentation
Issues or Feature Requests Anaconda Issue Tracker
Install or Technical Support Support page
Anaconda Behind Your Firewall Anaconda Server
NumFOCUS is a charitable organization with the purpose of supporting and promoting world-class, innovative, open-source scientific software. It provides the critical service of helping to remove the financial burden of continual development for many projects, including NumPy, SciPy, IPython, PyTables, pandas, Matplotlib, scikit-learn, and more. Donate to NumFOCUS.