Python/pip - Revision history

Jan-steiner-c1cc@uni-bonn.de at 08:37, 12 December 2024

2024-12-12T08:37:43Z

Jan-steiner-c1cc@uni-bonn.de at 12:34, 21 August 2024

2024-08-21T12:34:37Z

Jan-steiner-c1cc@uni-bonn.de: Import from https://git-ce.rwth-aachen.de/hpc.nrw/ag-schulung/hpc-wiki/-/tags/python-page-export-2024-08-21

2024-08-21T12:07:57Z

Import from https://git-ce.rwth-aachen.de/hpc.nrw/ag-schulung/hpc-wiki/-/tags/python-page-export-2024-08-21

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Daniel-schurhoff-de23@rwth-aachen.de at 13:52, 3 September 2019

2019-09-03T13:52:13Z

Daniel-schurhoff-de23@rwth-aachen.de at 14:44, 25 February 2019

2019-02-25T14:44:33Z

Daniel-schurhoff-de23@rwth-aachen.de at 14:43, 25 February 2019

2019-02-25T14:43:45Z

Daniel-schurhoff-de23@rwth-aachen.de at 14:41, 25 February 2019

2019-02-25T14:41:37Z

Jennifer-witham-0957@rwth-aachen.de at 11:34, 30 January 2019

2019-01-30T11:34:23Z

Nina-loseke-fd7a@rwth-aachen.de at 15:06, 19 December 2018

2018-12-19T15:06:41Z

Nina-loseke-fd7a@rwth-aachen.de: /* Pip */

2018-12-19T14:47:26Z

Pip

@@ Line 428: / Line 428: @@
 * Anaconda blog on [https://www.anaconda.com/blog/using-pip-in-a-conda-environment using pip in a Conda environment]
 * In-depth [https://wynton.ucsf.edu/hpc/howto/conda.html Conda how-to] including advanced topics like [https://wynton.ucsf.edu/hpc/howto/conda.html#conda-revisions revisions and environment rollback]
 == References ==

@@ Line 48: / Line 48: @@
 == Arrays ==
-[https://en.wikipedia.org/wiki/Array_(data_structure) Arrays] are a particularly important datatype to master for scientific programmers. Python has a default [https://docs.python.org/3/library/array.html#module-array built-in array] datatype that is rarely used. The much more common way, particularly in scientific software, is to use the [https://numpy.org/ NuPy package] with its [https://numpy.org/doc/stable/user/absolute_beginners.html#what-is-an-array array] type. The array syntax used in NumPy is commonly used by other software too. For example [https://www.tensorflow.org/guide/tensor TensorFlow] and [https://pytorch.org/tutorials/beginner/introyt/tensors_deeper_tutorial.html PyTorch tensors] are functionally very similar to NumPy arrays. [https://pandas.pydata.org/pandas-docs/stable/getting_started/intro_tutorials/01_table_oriented.html Pandas dataframes] are also similar in some respects.
+[https://en.wikipedia.org/wiki/Array_(data_structure) Arrays] are a particularly important datatype to master for scientific programmers. Python has a default [https://docs.python.org/3/library/array.html#module-array built-in array] datatype that is rarely used. The much more common way, particularly in scientific software, is to use the [https://numpy.org/ NumPy package] with its [https://numpy.org/doc/stable/user/absolute_beginners.html#what-is-an-array array] type. The array syntax used in NumPy is commonly used by other software too. For example [https://www.tensorflow.org/guide/tensor TensorFlow] and [https://pytorch.org/tutorials/beginner/introyt/tensors_deeper_tutorial.html PyTorch tensors] are functionally very similar to NumPy arrays. [https://pandas.pydata.org/pandas-docs/stable/getting_started/intro_tutorials/01_table_oriented.html Pandas dataframes] are also similar in some respects.
 An array is a container datatype that contains many entries of the same datatype (e.g. floating-point numbers). The entries are also called array ''elements''. The main advantages of arrays are:

← Older revision		Revision as of 13:52, 3 September 2019
Line 1:		Line 1:
		+	[[Category:Basics]][[Category:HPC-User]]
	== General ==		== General ==
	Python is an Open Source, interpreted high-level programming language which is popular for prototyping high end simulations and data science applications. In addition to a large standard library there are many thirdparty libraries available (e.g. Numpy, Scipy). However, it is a single threaded environment and therefore may not be most suitable for very large simulations.		Python is an Open Source, interpreted high-level programming language which is popular for prototyping high end simulations and data science applications. In addition to a large standard library there are many thirdparty libraries available (e.g. Numpy, Scipy). However, it is a single threaded environment and therefore may not be most suitable for very large simulations.

← Older revision		Revision as of 14:44, 25 February 2019
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	to execute your code.		to execute your code.

−	Often on a single system there are two environments available simultaneously: Python 2.x.x (callable with ~~'''~~python~~'''~~) and Python 3.x.x (callable as shown above). If not otherwise necessary, it is advisable to use and program in 3.x.x	+	Often on a single system there are two environments available simultaneously: Python 2.x.x (callable with <code>python</code>) and Python 3.x.x (callable as shown above). If not otherwise necessary, it is advisable to use and program in 3.x.x

@@ Line 9: / Line 9: @@
 You can check the used Version with:
 <syntaxhighlight lang="bash">
-$ python --version
+$ python3 --version
 </syntaxhighlight>
 and the corresponding install directory with
 <syntaxhighlight lang="bash">
-$ which python
+$ which python3
 </syntaxhighlight>
 and then use
 <syntaxhighlight lang="bash">
-$ python my_program.py
+$ python3 my_program.py
 </syntaxhighlight>
 to execute your code.

@@ Line 5: / Line 5: @@
 == Usage ==
-Python and its most commonly used libraries (NumPy, SciPy, Matplotlib) are usually available as a module. Please notice that an older version may be set as default. If the version you need is not available, you can install it in your directory by using 'pip' or 'easy_install'.
+Python and its most commonly used libraries (NumPy, SciPy, Matplotlib) are usually available as a module. Please notice that an older version may be set as default and there might be modules for different versions. If the version you need is not available, you can install it in your directory by using 'pip' or 'easy_install'.
-Examples:
+and the corresponding install directory with
 <syntaxhighlight lang="bash">
-$ export MYPY=$HOME/SomeDirForPythonInstall
+$ which python
 </syntaxhighlight>
 <syntaxhighlight lang="bash">
-$ pip install --user theano
+$ python my_program.py
 </syntaxhighlight>
 == Pip ==
 Pip is a package management system for Python and is automatically included since Python 2.7.9/3.4. It enables managing lists of packages and their versions. If you aim to install packages for Python3, use <code>pip3</code> instead of <code>pip</code> with the commands below.
 Getting the list of the installed packages:

← Older revision		Revision as of 11:34, 30 January 2019
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	== Usage ==		== Usage ==
−	Python and its most commonly used libraries (NumPy, SciPy, Matplotlib) are usually available as a module. Please notice that an older version may be set as default. If the version you need is not available, you can install it in your directory by using 'pip' or 'easy_install'. For RWTH CLAIX, you might want to consider loading a GCC compiler when using Python as Intel compilers oftentimes do not work with Python. So please make sure to load the GCC module before adding any Python modules.	+	Python and its most commonly used libraries (NumPy, SciPy, Matplotlib) are usually available as a module. Please notice that an older version may be set as default. If the version you need is not available, you can install it in your directory by using 'pip' or 'easy_install'.

← Older revision		Revision as of 15:06, 19 December 2018
Line 5:		Line 5:

	== Usage ==		== Usage ==
−	Python and its most commonly used libraries (NumPy, SciPy, Matplotlib) are usually available as a module. Please notice that an older version may be set as default. If the version you need is not available, you can install it in your directory by using 'pip' or 'easy_install'. For RWTH CLAIX, you might want to consider ~~using~~ a GCC compiler when ~~setting up~~ Python ~~in your environment, i. e~~. make sure to load the GCC module before adding any Python modules.	+	Python and its most commonly used libraries (NumPy, SciPy, Matplotlib) are usually available as a module. Please notice that an older version may be set as default. If the version you need is not available, you can install it in your directory by using 'pip' or 'easy_install'. For RWTH CLAIX, you might want to consider loading a GCC compiler when using Python as Intel compilers oftentimes do not work with Python. So please make sure to load the GCC module before adding any Python modules.