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Scientific Computing with Python

You're reading from   Scientific Computing with Python High-performance scientific computing with NumPy, SciPy, and pandas

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Product type Paperback
Published in Jul 2021
Publisher Packt
ISBN-13 9781838822323
Length 392 pages
Edition 2nd Edition
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Authors (4):
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Olivier Verdier Olivier Verdier
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Olivier Verdier
Jan Erik Solem Jan Erik Solem
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Jan Erik Solem
Claus Führer Claus Führer
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Claus Führer
Claus Fuhrer Claus Fuhrer
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Claus Fuhrer
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Table of Contents (23) Chapters Close

Preface 1. Getting Started 2. Variables and Basic Types FREE CHAPTER 3. Container Types 4. Linear Algebra - Arrays 5. Advanced Array Concepts 6. Plotting 7. Functions 8. Classes 9. Iterating 10. Series and Dataframes - Working with Pandas 11. Communication by a Graphical User Interface 12. Error and Exception Handling 13. Namespaces, Scopes, and Modules 14. Input and Output 15. Testing 16. Symbolic Computations - SymPy 17. Interacting with the Operating System 18. Python for Parallel Computing 19. Comprehensive Examples 20. About Packt 21. Other Books You May Enjoy 22. References

A complete process: subprocess.run

We demonstrate this tool with the most standard and simple UNIX command, ls—the command for listing the content of a directory. It comes with various optional arguments; for example, ls -l displays the list with extended information.

To execute this command within a Python script, we use subprocess.run. The simplest usage is using only one argument, a list with the Linux command split into several text strings:

import subprocess as sp
res = sp.run(['ls','-l'])

The module shlex provides a special tool for performing this split: 

_import shlex
command_list = shlex.split('ls -l') # returns ['ls', '-l']

It also respects empty spaces in filenames and does not use those as separators.

The command run displays the result of the Linux command and the subprocess.CompletedProcess object res.

To execute UNIX commands in this way is quite useless. Mostly, you want to process the output. Therefore...

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