"It is not a matter of fact, but it’s not worth it."
Guido van rossum

Python is a programming language in which it is pleasant to write and which is pleasant to read. We offer thirteen lectures of the fall course of the CS Center to look deep into the language and try to understand how to use all its features. Lectures are given by Sergey Lebedev , a developer at JetBrains and a teacher at the Computer Science Center.

It is not enough to master the syntax to learn a programming language: you need to recognize the idioms of the language and learn how to use them. During the course, Sergey introduces listeners to the idioms and capabilities of the Python language.

_{The photo was taken in the fall of 2014 in Strasbourg, two weeks before the first reading of this course.}

Course Lectures

Videos of all the lectures in the playlist on YouTube.

Start

Who, when and why invented the language Python. Interpreters language. Syntax of a bird's-eye view language. IPython interactive shell.
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Everything you wanted to know about functions in Python

Syntax of the declaration of functions. Packing and unpacking arguments. Key arguments and default arguments. Unpacking and assignment operator. Scopes, LEGB rule, global and nonlocal . Functional programming, anonymous functions. Functions map , filter and zip . Generators lists, sets and dictionaries. A bit about PEP 8.

Decorators and functools module

The syntax of decorators. Decorators with arguments, no arguments. Examples of the use of decorators. Module functools .

Strings, bytes, files, and I / O

String literals and raw strings. Strings and Unicode. The main methods of working with strings. string module. Bytes Encodings Files and file objects. Methods of working with files. Module io .

Built-in collections and collections

And again the built-in collections: a tuple, a list, a set, a dictionary — crawl in depth, an overview of methods, examples. Almost everything about the collections module: named tuples, counters, defaultdict , OrderedDict .

Classes, part 1

Class declaration syntax. Attributes related and unrelated methods, __dict__ , __slots__ . Static methods and class methods. Properties, decorator @property. Inheritance, method overloading and super function. Class decorators. Magical methods.

Exceptions and context managers

Exceptions, why they are needed and how to handle them. Built-in exceptions and base classes BaseException and Exception . Operators try...except..else..finally . Context managers and the contextlib module.

Iterators, generators and itertools module

Two iterator protocols: __next__ + __iter__ and __getitem__ . Iterators and for loops, as well as in and not in operators. Generators, operator expression yield . Generators like: iterators, coroutines, context managers. Module itertools .

Modules, packages and import system

Modules. The import and from ... import statements. Packages. Relative and absolute imports. __init__ -facade. And again the import statement is a detour in depth.

Classes, part 2

Descriptors: what-how-why. Constructor __new__ , class type and metaclasses. Inheritance of built-in types. abc and collections.abc modules.

Testing

Why test? Interpreter Testing and Docs. unittest module. Package py.test - much better. Testing properties and hypothesis package.

Faster, Python, Faster

Measurement of Python code operation time using timeit , cProfile and line_profiler . A little about NumPy. JIT and AOT compile Python code using the example of Numba and Cython.

Multithreading and GIL

The modules are threading , queue and concurrent.futures . Using threads for parallel computing in Python. GIL. Parallelism and competitiveness. asyncio module Module multiprocessing .

What's next

Practical tasks of this course are available only to students of the CS Center, students are recruited once a year, in spring. For those who for some reason cannot study at the center, we recommend not to stop watching the video of the course, but try to solve their everyday tasks in Python, because the main thing in learning a language is practice.

For different languages ​​there are lists of good libraries, for example, Awesome Java , Awesome R and Awesome C ++ . Of course, there is such a list for Python . The next time you need a library for working with a database, logging or analyzing images, feel free to go to the appropriate section of the list for inspiration.