[NEWS] Software and required libraries

andrea.sterbini (167420 points)
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asked Oct 14, 2020 in News by andrea.sterbini (167,420 points)
edited Oct 15, 2020 by Claudio.DiCiccio

Python distribution used in this course: Anaconda

We use the Anaconda Python distribution. It is available at www.anaconda.com/download and contains:

  • Python 3.7 or 3.8;
  • many standard and useful libraries;
  • the Spyder IDE (Integrated Development Environment), which we use in class and during the exam.

For more details on how to install Anaconda see https://docs.anaconda.com/anaconda/install

NOTICE: when installing Anaconda in Windows, choose the “Only for me” option.

Required/useful libraries

Once you have installed Anaconda, you must/could install these other Anaconda packages

Library Needed for Anaconda Prompt command How to use it
ddt Run tests read from a JSON file conda install -c conda-forge ddt It's imported by the test machinery
pytest-timeout Apply a timeout to each test execution conda install pytest-timeout Adds the new parameter --timeout=<seconds> to the pytest command
stopit Apply a timeout only to your function execution conda install -c conda-forge stopit It's imported by the test machinery
pytest-profiling Examine the time spent in each called function conda install -c conda-forge pytest-profiling Adds the new parameter --profile to the pytest command
Spyder IDE (editor+debugger) conda install spyder
spyder-unittest Run tests from inside Spider conda install -c conda-forge spyder-unittest Adds a new tab to Spyder to run/show tests (choose pytest and the directory)
spyder-line-profiler Examine the execution times from inside Spyder conda install -c conda-forge spyder-line-profiler Adds a new menu command to Spyder to profile the execution times of all functions
radon Compute the “intricacy” of your code
(maximum  cyclomatic complexity)
conda install -c conda-forge radon radon cc -a -s --show-closures program.py
Notepad Delete it!

DO NOT USE IT: it does not properly handle the Unix newline character in text files ('\n')

Notepad++ Text editor https://notepad-plus-plus.org
Wordpad OK
Beyond Compare Very useful file comparator for both text and pictures https://www.scootersoftware.com/download.php

To update all Anaconda libraries use the following command from an "Anaconda Prompt" window:

  • conda update --all

Other useful commands

The homework tests are contained in the test_01.py file. Each one is a method that begins with 'test_' and is automatically discovered and run by pytest.

To run all tests:

  • pytest test_01.py
  • pytest test_01.py -v --durations 0                                  # this one lists all the slowest tests

To run a specific test:

  • pytest -v test_01.py -k <substring of the text name>

For example, pytest test_01.py -k 2_values -v.

To compute the code “intricacy” (maximum cyclomatic complexity):

  • radon cc -a -s --show-closures program01.py.

To compute the average test running time (by taking the best of 3 runs and by averaging on 5 executions for each run):

  • python -u -m timeit -v -v -v -v -n 5  -r 3  -s 'from test_01 import Test' 'Test.main()'

To profile your code and understand which part is slower (if you have installed pytest-profiling):

  • pytest -rA -v --profile test_01.py

NOTICE: to get the 20 slowest times you should modify pytest-profiling as follows:
Change file .../Anaconda/lib/python3.*/site-packages/pytest_profiling.py such that line 64 is changed to

pstats.Stats(self.combined, stream=terminalreporter).strip_dirs().sort_stats('tottime').print_stats(20)

instead than

pstats.Stats(self.combined, stream=terminalreporter).strip_dirs().sort_stats('cumulative').print_stats(20)


To interactively explore the profiling results you can use snakeviz:

  • install snakeviz (a .prof files visualizer): conda install snakeviz;
  • execute your test with the profiler: pytest --profile test_01.py;
  • show the execution times with snakeviz: snakeviz prof/combined.prof;
  • your browser opens on a page that allows you to find where most time has been spent;
  • look for your implemented function (normally named ex1) and click on its header line: the visualization will zoom on it.

Python 4 Android

Choose Python version 3

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