Conda (package manager)

Conda is an open source,[1] cross-platform,[2] language-agnostic[3] package manager and environment management system[4][5][6] that installs, runs, and updates packages and their dependencies.[1] Conda allows users to easily

Conda is written in the Python programming language, but can manage projects containing code written in other languages (e.g., R[3]), including multi-language projects.[3] Conda can install the Python programming language,[7] while similar Python-based cross-platform package managers (such wheel or pip) cannot.

Continuum Analytics maintains Conda (among other open source tools), which it releases under the Berkeley Software Distribution License.[1][8][9][10][11][12]

References

  1. 1 2 3 "Conda". pydata.org. Retrieved 9 April 2015.
  2. ↑ "Building Conda Packages for Multiple Operating Systems". Pydannt. 29 January 2015. Retrieved 9 April 2015.
  3. 1 2 3 Doig, Christine (21 May 2015). "Conda for Data Science". Archived from the original on 16 Jun 2015. Retrieved 16 Jun 2015. Conda works with Linux, OSX, and Windows, and is language agnostic, which allows us to use it with any programming language or even multi-language projects.
  4. ↑ Gorelick (Author), Micha; Ozsvald, Ian (September 2014). High Performance Python: Practical Performant Programming for Humans (1st ed.). O'Reilly Media. p. 370. ISBN 1449361595.
  5. ↑ Jackson, Joab (Feb 5, 2013). "Python gets a big data boost from DARPA". networkworld. Retrieved October 30, 2014.
  6. ↑ Lorica, Ben (March 24, 2013). "Python data tools just keep getting better". O'Reilly Radar. Retrieved October 30, 2014.
  7. ↑ "3. Managing Python". 2015. Archived from the original on 16 Jun 2015. Retrieved 16 Jun 2015. So now let’s say you need Python 3 to learn programming, but you don’t want to overwrite your Python 2.7 environment by updating Python. You can create and activate a new environment named snakes, and install the latest version of Python 3 as follows:
  8. ↑ "State of Conda, Oct. 2014". Pen and Pants. Retrieved 9 April 2015.
  9. ↑ Tony Ojeda; Sean Patrick Murphy; Benjamin Bengfort; Abhijit Dasgupta (25 September 2014). Practical Data Science Cookbook. Packt Publishing Ltd. ISBN 1783980257. Retrieved 19 March 2015.
  10. ↑ Hans, Petter (2014). A Primer on Scientific Programming with Python. Springer. ISBN 3642549594. Retrieved 19 March 2015.
  11. ↑ Yves Hilpisch (11 December 2014). Python for Finance: Analyze Big Financial Data. O'Reilly Media. Retrieved 19 March 2015.
  12. ↑ "Continuum Analytics Launches Anaconda Server for Enterprise Package Management". Yahoo Finance. 30 January 2014. Retrieved 19 March 2015.
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