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5 Hidden Python Features You Probably Never Heard Of

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Listed here, I’m going to let you know the tip 5 odd components chances are high you’ll presumably per chance presumably moreover safe in Python. Skilled Python developers could presumably per chance moreover come genuine through about a of them. Nonetheless, others will unruffled be unknown. Regardless, I safe all of them very frigid.

Table of Contents

  1. ...
  2. An Capable Unpacking
  3. Can You Flat This List?
  4. What else?
  5. Evaluating Things Treasure a Boss
  6. Conclusion

...

Sure, you’re reading it favorable, ... is an authority effect in Python. ... is a singleton object called Ellipsis. In case you kind it into the Python interpreter, chances are high you’ll presumably per chance presumably moreover very successfully look it:

>>> ...
Ellipsis

In line with the expert clinical doctors , Ellipsis is a “special tag used mostly alongside with extended cutting back syntax for individual-defined container facts forms.”. There’s two vital exercise cases for it. One is to back as a placeholder physique in an empty device. The diversified is on Numpy, as a prick merchandise, favorable as described in the clinical doctors.

Feature Placeholder

def my_awesome_function(): 
    ...

Here is corresponding to:

def my_awesome_function(): 
    Ellipsis

And this:

def my_awesome_function(): 
    hurry

Beware, I’m no longer pronouncing that hurry == ..., I’m favorable pronouncing that as a device physique, the atomize consequence is the identical. The truth is, chances are high you’ll presumably per chance presumably moreover exercise the rest as placeholder.

def my_awesome_function(): 
    "An empty, but also awesome device"

Numpy

The code below usually plot fabricate an array of matrices. Each matrix is 3×3. Then catch the second column (numpy arrays are 0-primarily based) of all innermost matrix.

>>> import numpy as np
>>> array = np.arange(27).reshape(3, 3, 3)
>>> array
array([[[ 0,  1,  2],
        [ 3,  4,  5],
        [ 6,  7,  8]],

       [[ 9, 10, 11],
        [12, 13, 14],
        [15, 16, 17]],

       [[18, 19, 20],
        [21, 22, 23],
        [24, 25, 26]]])
>>> array[..., 1] 
array([[ 1,  4,  7],
       [10, 13, 16],
       [19, 22, 25]])
>>> 
>>> array[:, :, 1] 
array([[ 1,  4,  7],
       [10, 13, 16],
       [19, 22, 25]])

Beware: Python’s checklist doesn’t work with ....

An Capable Unpacking

Iterable unpacking is a remarkably helpful feature and has been there for a whereas. Most of us exercise it to unpack iterables with plenty of items. As instance, thunder regarding the next exercise cases.

>>> a, *b, c = vary(1, 11)
>>> a
1
>>> c
10
>>> b
[2, 3, 4, 5, 6, 7, 8, 9]

Or favorable:

>>> a, b, c = vary(3)
>>> a
0
>>> b
1
>>> c
2

Nonetheless one tremendous exercise case that many of us enact no longer catch profit of is unpacking a single iterable. Why that is priceless? It makes the code barely bit more neat, IMHO.

In settle on to doing this:

>>> lst = [1]
>>> a = lst[0]
>>> a
1
>>> (a, ) = lst
>>> a
1

You are going to be ready to enact this:

>>> lst = [1]
>>> [a] = lst
>>> a
1

I know that it could presumably per chance moreover fair appear silly, but as a minimum to me, it looks to be like more neat.

Can You Flat This List?

Flattening a checklist could presumably per chance moreover moreover be completed in plenty of how. The most straightforward one is the utilization of checklist comprehension.

>>> l = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
>>> flattened = [elem for sublist in l for elem in sublist]
>>> flattened
[1, 2, 3, 4, 5, 6, 7, 8, 9]

In case chances are high you’ll presumably per chance presumably moreover be more inclined to purposeful programming, chances are high you’ll presumably per chance presumably moreover exercise a reducer.

>>> from functools import lower
>>> lower(lambda x,y: x+y,l)
[1, 2, 3, 4, 5, 6, 7, 8, 9]

Nonetheless, there is but one more plot. You are going to be ready to exercise the sum device!

>>> sum(l, [])
[1, 2, 3, 4, 5, 6, 7, 8, 9]

This works since the sum device iterates through every announce in the checklist and concatenates them with the default tag you hurry as the second argument. Since lists in Python could presumably per chance moreover moreover be concatenated with + operator, then you definately catch one thing admire this:

>>> sum(l, []) ==> [] + [1, 2, 3] + [4, 5, 6] + [7, 8, 9]
[1, 2, 3, 4, 5, 6, 7, 8, 9]

Even supposing this trick is lustrous, it’s by no plot readable. Moreover, it has a dreadful performance.

Raise out we enact this with string?

No, Python forbids doing the identical with strings, even supposing chances are high you’ll presumably per chance presumably moreover concatenated strings with + operator.

>>> s = ["abc", "def", "ghf"]

>>> sum(s, "")
---------------------------------------------------------------------------
TypeError                                 Traceback (most most up-to-date call final)
-3-f60d89b81305> in 
----> 1 sum(s, "")

TypeError: sum() can't sum strings [use ''.join(seq) instead]

If we dig intro CPython source code, we are in a position to safe where this happens:

static PyObject builtin_sum_impl(PyObject *module, PyObject *iterable, PyObject *begin up)

{
    PyObject *consequence = begin up;
    PyObject *temp, *merchandise, *iter;

    iter = PyObject_GetIter(iterable);
    if (iter == NULL)
        return NULL;

    if (consequence == NULL) {
        consequence = PyLong_FromLong(0);
        if (consequence == NULL) {
            Py_DECREF(iter);
            return NULL;
        }
    } else {
        
        if (PyUnicode_Check(consequence)) {
            PyErr_SetString(PyExc_TypeError,
                "sum() can no longer sum strings [use ''.join(seq) instead]");
            Py_DECREF(iter);
            return NULL;
        }
        if (PyBytes_Check(consequence)) {
            PyErr_SetString(PyExc_TypeError,
                "sum() can no longer sum bytes [use b''.join(seq) instead]");
            Py_DECREF(iter);
            return NULL;
        }
        if (PyByteArray_Check(consequence)) {
            PyErr_SetString(PyExc_TypeError,
                "sum() can no longer sum bytearray [use b''.join(seq) instead]");
            Py_DECREF(iter);
            return NULL;
        }
        Py_INCREF(consequence);
    }

github.com/python/cpython/blob/c96d00e88ead..

The _

This one is admittedly attention-grabbing and extremely helpful when working with the REPL. It no longer supreme works with the default Python interpreter, but with IPython as successfully.

Everytime you flee an expression in the REPL, Python binds the output to the _ variable.

>>> nums = [1, 3, 7]
>>> sum(nums)
11
>>> _
11
>>>

Since _ is a variable admire all diversified, chances are high you’ll presumably per chance presumably moreover re-bind it, or enact the rest with it.

>>> 9 + _
20
>>> a = _
>>> a
20

What else?

The else notify in can back plenty of applications. Few of us know, but chances are high you’ll presumably per chance presumably moreover exercise it open air the classical ‘if else` block. Python enable it to be used on loops and also on exception blocks.

Loops

Python has two diversified loops, for and whereas. Each of them could presumably per chance moreover moreover be “broken”. That’s, if a undeniable condition is met, we are in a position to escape of the loop. Shall we announce:

In [7]: whereas a < 10:
   ...:     if a == 3:
   ...:         print("a == 3. exiting loop.")
   ...:         spoil
   ...:     a += 1
   ...: 
a == 3. exiting loop.

Now, as an instance that we are procuring for a specific condition. If that condition is pleased, we build the pause cease in a flag called found. Then, if we do no longer safe it, we print a message.

found = Spurious
a = 0

whereas a < 10:
    if a == 12:
        found = Correct
    a += 1
if no longer found:
    print("a used to be by no plot found")

Since a by no plot turns into 12, the program outputs a used to be by no plot found.

Ok, but how can we exercise else on this context?

The else could presumably per chance moreover moreover be used to replace the flag. Essentially, what we in fact settle on is to flee the loop and, if no longer found, then print a message. Here is how it looks to be like admire with else:

a = 0

whereas a < 10:
    if a == 12:
        break
    a += 1
else:
    print("a was never found")

And since it works with any loop, you can use a for instead of while.

for a in range(10):
    if a == 12:
        break
    a += 1
else:
    print("a was never found")

Exceptions

The else in Python is so versatile that you can even use it in a try ... except block. The idea here is to capture a nonoccurrence of an exception.

In [13]: try:
    ...:     {}['lala']
    ...: except KeyError:
    ...:     print("Key is missing")
    ...: else:
    ...:     print("Else here")
    ...: 
Key is missing

In this example, we try looking up a key named “lala” in an empty dictionary. Since “lala” is not there, the code will raise an KeyError exception. When I run this snippet in IPython, I got an expected result.

What about a case where the program raises no exception?

In [14]: try:
    ...:     {'lala': 'bla'}['lala']
    ...: except KeyError:
    ...:     print("Key is missing")
    ...: else:
    ...:     print("Else here")
    ...: 
Else here

Now we can see it in action. The {’lala’: ‘bla’}[‘lala’] block won’t raise KeyError, so the else comes into play.

Remember, few people know this, so I personally avoid using this feature to not confuse other developers working in the same code base. It’s nice to impress friends, though!

Comparing Things Like a Boss

This is one of my favorites and not so hidden, to be honest. Unlike many programming languages, like Java, C or C++, Python allows you to chain comparison operators. Let’s imagine that you have a variable x that holds the value of 10. Now, let’s say that you want to assert that x is within a range, like 5..20, inclusive. You could do something like this:

In [16]: x = 10
In [17]: if x >= 5 and x <= 20:
    ...:     print("x is inner vary")
    ...: else:
    ...:     print("x is open air vary")
    ...: 
is inner vary

It looks, this is in a position to presumably per chance moreover be simplified by chaining the operators. So, we are in a position to refactor the code to this:

In [18]: if 5 <= x <= 20:
    ...:     print("is within range")
    ...: else:
    ...:     print("x is outside range")
    ...: 
is within range

This code achieves the exact same result, but it’s much more elegant. You can chain using any kind of comparison operator.

>>> x = 10
>>> 20 == x > 1
Spurious
>>> 25 > x <= 15
True
>>> x < 20 < x*10 < 1000
Correct

Very frigid!

Conclusion

That’s the pause of this post. Python is a in fact qualified language and has some tremendous, but no longer essential, components. On this post, I showed you my favorites and I hope you’ve learned one thing fresh. Research you next time!

In case you loved this post, accept as true with sharing it with your mates! Moreover, in fact be at liberty to possess a look at me miguendes.me.

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