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Version 5.0.1 (25 October 2017): https://docs.anaconda.com/anaconda/release-notes
It would be great if you actually looked at the article before contending to edit it. Mind you, infobox URLs must visible in print.
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| developer = Anaconda, Inc. (former name: Continuum Analytics)
| developer = Anaconda, Inc. (neé Continuum analytics)
| released = <!-- {{Start date and age|YYYY|MM|DD|df=yes/no}} -->
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| genre = [[Programming language]]
| genre = [[Programming language]]
| license = [[BSD licenses#3-clause license ("Revised BSD License", "New BSD License", or "Modified BSD License")|New BSD License]]<ref name="newBSD">{{cite web|title=Anaconda End User License Agreement|url=https://docs.continuum.io/anaconda/eula|website=continuum.io|publisher=Continuum Analytics|accessdate=May 30, 2016}}</ref>
| license = [[BSD licenses#3-clause license ("Revised BSD License", "New BSD License", or "Modified BSD License")|New BSD License]]<ref name="newBSD">{{cite web|title=Anaconda End User License Agreement|url=https://docs.continuum.io/anaconda/eula|website=continuum.io|publisher=Continuum Analytics|accessdate=May 30, 2016}}</ref>
| website = {{Official website|https://www.anaconda.com/|name=Anaconda}}
| alexa =
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== External links ==
== External links ==
* {{Official website|https://www.anaconda.com/}}
* {{Official website}}


[[Category:Proprietary package management systems]]
[[Category:Proprietary package management systems]]

Version vom 26. Oktober 2017, 20:33 Uhr

Vorlage:Infobox software

Anaconda is a freemium[1] open source[2] distribution of the Python and R programming languages for large-scale data processing, predictive analytics, and scientific computing, that aims to simplify package management and deployment.[3][4][5][6][7] Package versions are managed by the package management system conda.[8]

References

Vorlage:Reflist

Vorlage:Comp-sci-stub

  1. ↑ Anaconda Subscriptions. In: continuum.io. Continuum Analytics, abgerufen am 30. September 2015.
  2. ↑ Open Source is at the Core of Modern Software. In: continuum.io. Continuum Analytics, abgerufen am 30. Mai 2016.
  3. ↑ Luiz Felipe Martins: IPython Notebook Essentials. 1st Auflage. Packt, 2014, ISBN 978-1-78398-834-1, S. 190.
  4. ↑ Micha Gorelick, Ian Ozsvald: High Performance Python: Practical Performant Programming for Humans. 1st Auflage. O'Reilly Media, 2014, ISBN 978-1-4493-6159-4, S. 370.
  5. ↑ Joab Jackson: Python gets a big data boost from DARPA. In: Network World. IDG, 5. Februar 2013, abgerufen am 30. Oktober 2014.
  6. ↑ Ben Lorica: Python data tools just keep getting better. In: O'Reilly Radar. O'Reilly Media, 24. März 2013, abgerufen am 30. Oktober 2014.
  7. ↑ Christine Doig: Anaconda for R users: SparkR and rBokeh. In: Developer Blog. Continuum Analytics, 1. Februar 2016;.
  8. ↑ Conda – Conda documentation. Abgerufen am 25. Februar 2016.
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