1.4. Python Language

  • Turing complete, general purpose language

  • Multi platform

  • Dynamic typing with automatic memory allocation and GC

  • Code readability and simplicity is important

  • White space are important

  • Everything is an object, but you can write functional code too

  • Standard language in Machine Learning and Data Science

  • Very good standard system library

  • Huge ecosystem of external open source libraries

  • Open Source created by non-profit Python Software Foundation


Figure 1.1. Python Logo

1.4.1. Scripts

  • Python files use .py as an extension

  • Compiled files are in __pycache__ directory

  • Python also uses other extensions

Table 1.2. Python file types and extensions




Compiled source code (bytecode)


Compiled Windows DLL file


Compiled Windows file. Executable with pythonw.exe


cPythona source for C/C++ conversion


zipapp compressed archive

1.4.2. Python Console (REPL)

  • Read–Eval–Print Loop

  • Quickly test and evaluate code

  • Lines starts with >>>

  • Line continuation starts with ...

  • Result is printed below

  • Open REPL with python3 command in terminal

$ python3.10
Python 3.10.0 (default, Oct 13 2021, 06:45:00) [Clang 13.0.0 (clang-1300.0.29.3)] on darwin
Type "help", "copyright", "credits" or "license" for more information.
>>> print('Ehlo World!')
Ehlo World!

In documentation and books you may find >>> and ... at the beginning of code listing lines

>>> if True:
...     print('yes')
... else:
...     print('no')

1.4.3. Jupyter

  • Open Source web application REPL

  • Very popular in Machine Learning and Data Science world

  • Create and share documents that contain live code, equations, visualizations and narrative text

  • Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, machine learning, etc

1.4.4. References

1.4.5. Assignments

Code 1.3. Solution
* Assignment: About Environment
* Complexity: easy
* Lines of code: 0 lines
* Time: 3 min

    1. Create file `about_env.py`
    2. Run file in your IDE
    3. Where Python is installed?
    4. Are you using "venv"?
    5. Make sure, `venv` is not `None`
    6. Run doctests - all must succeed

    1. Stwórz plik `about_env.py`
    2. Uruchom plik w swoim IDE
    3. Gdzie Python jest zainstalowany?
    4. Czy korzystasz z "venv"?
    5. Upewnij się, że `venv` nie jest `None`
    6. Uruchom doctesty - wszystkie muszą się powieść

    >>> import sys; sys.tracebacklimit = 0

    >>> assert python_executable
    >>> assert python_version

import os
import sys

python_executable = sys.executable
python_version = tuple(sys.version_info)
venv = os.getenv("VIRTUAL_ENV")