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Regular tips about Python and programming in general Owner — @pushtaev The current season is run by @orsinium Tips are appreciated: https://ko-fi.com/pythonetc / https://sobe.ru/na/pythonetc © CC BY-SA 4.0 — mention if repost

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6 179

Every method can be treated as a plain function and called with a custom self:

In : class A:
   ...:     def foo(self):
   ...:         return self
   ...:

In : A().foo
Out: <bound method A.foo of <...>>

In : A.foo
Out: <function __main__.A.foo>

In : A.foo(A())
Out: <__main__.A at 0x7f55ddd32898>

You can even convert a function back to the bound method. Any function is a descriptor, so it can be abused by calling __get__:

In [8]: b = A()

In [9]: A.foo.__get__(b, A)
Out[9]: <bound method A.foo of <...>>

6 179

In Python 3 keys, values and items methods of dicts return view objects. They returned lists back in Python 2. The main difference is views don't store all items in memory, but yield them as long as they are requested. It works just fine as long as you are trying to iterate over keys (which you usually are), but you can't access elements by index anymore.

TypeError: 'dict_keys' object does not support indexing

You can argue that you don't really need indexing keys since their order is random, but it's not completely true. First of all, d.keys()[0] can be a proper way to get any key (use next(d.keys()) in Python 3). Second, since Python 3.7 dicts are insertion ordered.

6 179

If you want a context manager to make asynchronous operations upon entering or exiting context, you should use asynchronous context managers. Instead of calling m.__enter__() and m.__exit__() Python does await m.__aenter__() and await m.__aexit__() respectively. Asynchronous context managers are used with async with syntax:

import asyncio

class Slow:
    def __init__(self, delay):
        self._delay = delay

    async def __aenter__(self):
        await asyncio.sleep(self._delay / 2)

    async def __aexit__(self, *exception):
        await asyncio.sleep(self._delay / 2)

async def main():
    async with Slow(1):
        print('slow')

loop = asyncio.get_event_loop()
loop.run_until_complete(main())

6 179

__getattribute__ is a powerful tool that allow you to easily use delegation pattern when it’s appropriate. Here is how you add an ability to be comparable to a non-comparable object:

class CustomEq:
    def __init__(self, orig, *, key):
        self._orig = orig
        self._key = key

    def __lt__(self, other):
        return self._key(self) < self._key(other)

    def __getattribute__(self, name):
        if name in {'_key', '_orig', '__lt__'}:
            return super().__getattribute__(name)

        return getattr(self._orig, name)


class User:
    def __init__(self, user_id):
        self._user_id = user_id

    def get_user_id(self):
        return self._user_id


def comparable(obj, *, key):
    return CustomEq(obj, key=key)


user1 = comparable(User(1), key=lambda u: u.get_user_id())
user2 = comparable(User(2), key=lambda u: u.get_user_id())

print(user2 > user1)  # True
print(user2 < user1)  # False
print(user2.get_user_id())  # 2

6 179

Hi. The weekend task section doesn't welcome you today. I believe It's time for it to go.

6 179

a : b : c notation can be used to define slice(a, b, c) only within brackets:

>>> [1, 2, 3, 4, 5][0:4:2]
[1, 3]
>>> [1, 2, 3, 4, 5][slice(0, 4, 2)]
[1, 3]

If you want to pass the slice object as an argument to a function, you have to define it explicitly:

def multislice(slc, *iterables):
    return [i[slc] for i in iterables]


print(multislice(
    slice(2, 6, 2),
    [1, 2, 3, 4, 5, 6, 7],
    [2, 4, 2, 4, 2, 4, 2],
))

Here is how you can convert such a function to an object that supports [a : b : c]:

from functools import partial


class SliceArgDecorator:
    def __init__(self, f):
        self._f = f

    def __getitem__(self, slc):
        return partial(self._f, slc)

slice_arg = SliceArgDecorator


@slice_arg
def multislice(slc, *iterables):
    return [i[slc] for i in iterables]


print(multislice[2:6:2](
    [1, 2, 3, 4, 5, 6, 7],
    [2, 4, 2, 4, 2, 4, 2],
))

6 179

The in operator can be used with generators: x in g. Python will iterate over g until x is found or g is exhausted.

>>> def g():
...     print(1)
...     yield 1
...     print(2)
...     yield 2
...     print(3)
...     yield 3
...
>>> 2 in g()
1
2
True

However, range() does more than this for you. It has the __contains__ magic method overriden that allows in to work with the O(1) complexity:

In [1]: %timeit 10**20 in range(10**30)
375 ns ± 10.7 ns per loop

Mind that it doesn't work for the Python 2 xrange() function.

6 179

complex is the Python built-in type for complex numbers:

>>> complex(1, 2).real
1.0
>>> abs(complex(3, 4))
5.0
>>> complex(1, 2) == complex(1, -2).conjugate()
True
>>> str(complex(2, -3))
'(2-3j)'

There is not need to use it directly though since Python has literals for complex numbers:

>>> (3 + 4j).imag
4.0
>>> not (3 + 4j)
False
>>> (-3 - 4j) + (2 - 2j)
(-1-6j)

6 179

https://gist.github.com/VadimPushtaev/0507a94c1b8af30533a1c3e74288b85f

6 179

Write a generator that takes any number of iterables as arguments. Those iterables yield values in ascending order. Your generator should yield all values of all iterables in ascending orders.

>>> list(merge([1, 5], [2, 3, 4]))
[1, 2, 3, 4, 5]

6 179

Welcome to the weekend task section. Below is the task the you can solve in Python. My solution will be published in 36 hours.

6 179

To make regular expressions more readable you may use the re.VERBOSE flag. It allows you to use extra spaces wherever you want as well as add comments with the # symbol:

import re

URL_RE = re.compile(r'''
    ^
    (https?)://
    (www[.])?
    (
        (?: [^.]+[.] )+
        (   [^/]+    )  # TLD
    )
    (/.*)
    $
''', re.VERBOSE)

m = URL_RE.match('https://www.pythonetc.com/about/')
schema, www, domain, tld, path = m.groups()

has_www: bool = bool(www)

print(f'schema={schema}, has_www={has_www}')
print(f'domain={domain}, tld={tld}')
print(f'path={path}')

re.X is an alias for re.VERBOSE.

6 179

PATH is an environment variable that stores paths where executables are looked for. When you ask your shell to runls, the sell looks for the ls executable file across all paths that are presented in PATH.

$ echo $PATH
/usr/local/bin:/usr/bin:/usr/local/sbin:/usr/sbin:/home/v.pushtaev/.local/bin:/home/v.pushtaev/bin
$ which ls
/usr/bin/ls

In the example above paths are separated by : in PATH. No escaping is possible: a path that contains : cannot be used inside PATH. However, that is not true for all operating systems. In Python you can get the right separator for the local system with os.pathsep:

Python 3.5.0 [...] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import os
>>> os.pathsep
';'

os.pathsep is not to be mixed up with os.path.sep which is the separator for file paths:

>>> os.path.sep
'/'

6 179

You can use any object as a dictionary key in Python as long as it implements the __hash__ method. This method can return any integer as long as the only requirement is met: equal objects should have equal hashes (not vice versa). You also should avoid using mutable objects as keys, because once the object becomes not equal to the old self, it can't be found in a dictionary anymore. There is also one bizarre thing that might surprise you during debugging or unit testing:

...: class A:
...:     def __init__(self, x):
...:         self.x = x
...:
...:     def __hash__(self):
...:         return self.x
...:
In : hash(A(2))
Out: 2
In : hash(A(1))
Out: 1
In : hash(A(0))
Out: 0
In : hash(A(-1))  # sic!
Out: -2
In : hash(A(-2))
Out: -2

In CPython -1 is internally reserved for error states, so it's implicitly converted to -2.

6 179

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6 179

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6 179

def catalan(n: int):
    result = 1

    for i in range(1, n + 1):
        result = (
            result * 2 * (2 * i - 1)
            // (i + 1)
        )

    return result

6 179

Write a function that returns the nth Catalan number without using explicit recursion.

6 179

Welcome to the weekend task section. Below is the task the you can solve in Python. My solution will be published in 36 hours.