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Python's Bright Future in Science
--client
pyconau
--show
pycon_au_2016
--room Room_106 11300 --force
Next: 1 Python for bridging between researchers and service operators: from CFFI to Jupyterhub
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Marks
Author(s):
Juan Nunez-Iglesias
Location
Room 106
Date
aug Fri 12
Days Raw Files
Start
09:00
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error-in-template
Duration
1:00:00
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None
End
10:00
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None min.
https://2016.pycon-au.org/schedule/200/view_talk
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Pythons_Bright_Future_in_Science.json
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Over the past five years, Python has skyrocketed in popularity in the scientific world, pushing out proprietary languages such as IDL and Matlab. This rise was powered by simple syntax and efficient numerical libraries. But many operations in Python are still slow, and upstart languages, such as Julia and Go, promise simplicity *and* speed. Can Python cement its place in scientific computing?
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