Understanding the underscore(

I’m not a native speaker. Sorry for my english. Please understand.

The underscore (_) is special in Python.

While the underscore (_) is used for just snake-case variables and functions in most languages (Of course, not for all), but it has special meanings in Python. If you are python programmer, for _ in range(10) , __init__(self) like syntax may be familiar.

This post will explain the about when and how use the underscore (_) and help you understand it.

There are 5 cases for using the underscore in Python.

For storing the value of last expression in interpreter.
For ignoring the specific values. (so-called “I don’t care”)
To give special meanings and functions to name of vartiables or functions.
To use as ‘Internationalization(i18n)’ or ‘Localization(l10n)’ functions.
To separate the digits of number literal value.

Let’s look at each case.

When used in interpreter

The python interpreter stores the last expression value to the special variable called ‘_’. This feature has been used in standard CPython interpreter first and you could use it in other Python interpreters too.

>>> 1010>>> _10>>> _ * 330>>> _ * 20600

For Ignoring the values

The underscore is also used for ignoring the specific values. If you don’t need the specific values or the values are not used, just assign the values to underscore.

_# Ignore a value when unpacking_x, _, y = (1, 2, 3) # x = 1, y = 3

# Ignore the multiple values. It is called "Extended Unpacking" which is available in only Python 3.xx, *_, y = (1, 2, 3, 4, 5) # x = 1, y = 5

_# Ignore the index_for _ in range(10):do_something()

# Ignore a value of specific locationfor _, val in list_of_tuple:do_something()

Give special meanings to name of variables and functions

The underscore may be most used in ‘naming’. The PEP8 which is Python convention guideline introduces the following 4 naming cases.

**_single_leading_underscore**This convention is used for declaring private variables, functions, methods and classes in a module. Anything with this convention are ignored in from module import *. However, of course, Python does not supports truly private, so we can not force somethings private ones and also can call it directly from other modules. So sometimes we say it “weak internal use indicator”.

_internal_name = 'one_nodule' # private variable_internal_version = '1.0' # private variable

class _Base: # private class_hidden_factor = 2 # private variable

def \_\_init\_\_(self, price):  
    self.\_price = price

def \_double\_price(self): # private method  
    return self.\_price \* self.\_hidden\_factor

def get\_double\_price(self):  
    return self.\_double\_price()

**single_trailing_underscore_**This convention could be used for avoiding conflict with Python keywords or built-ins. You might not use it often.

Tkinter.Toplevel(master, class_='ClassName') # Avoid conflict with 'class' keyword

list_ = List.objects.get(1) # Avoid conflict with 'list' built-in type

**__double_leading_underscore**This is about syntax rather than a convention. double underscore will mangle the attribute names of a class to avoid conflicts of attribute names between classes. (so-called “mangling” that means that the compiler or interpreter modify the variables or function names with some rules, not use as it is) The mangling rule of Python is adding the “_ClassName” to front of attribute names are declared with double underscore. That is, if you write method named “__method” in a class, the name will be mangled in “_ClassName__method” form.

class A:def _single_method(self):pass

def \_\_double\_method(self): # for mangling  
    pass

class B(A):def __double_method(self): # for manglingpass

Because of the attributes named with double underscore will be mangled like above, we can not access it with “ClassName.__method”. Sometimes, some people use it as like real private ones using these features, but it is not for private and not recommended for that. For more details, read Python Naming.

**__double_leading_and_trailing_underscore__**This convention is used for special variables or methods (so-called “magic method”) such as__init__, __len__. These methods provides special syntactic features or does special things. For example, __file__ indicates the location of Python file, __eq__ is executed when a == b expression is excuted. A user of course can make custom special method, it is very rare case, but often might modify the some built-in special methods. (e.g. You should initialize the class with __init__ that will be executed at first when a instance of class is created.)

class A:def __init__(self, a): # use special method '__init__' for initializingself.a = a

def \_\_custom\_\_(self): # custom special method. you might almost do not use it  
    pass

As Internationalization(i18n)/Localization(l10n) functions

It is just convention, does not have any syntactic functions. That is, the underscore does not means i18n/l10n, and it is just a convention that binds the i18n/l10n to underscore variable has been from C convention.The built-in library gettext which is for i18n/l10n uses this convention, and Django which is Python web framework supports i18n/l10n also introduces and uses this convention.

# see official docs : https://docs.python.org/3/library/gettext.htmlimport gettext

gettext.bindtextdomain('myapplication','/path/to/my/language/directory')gettext.textdomain('myapplication')_ = gettext.gettext

# ...

print(_('This is a translatable string.'))

To separate the digits of number literal value

This feature was added in Python 3.6. It is used for separating digits of numbers using underscore for readability.

dec_base = 1_000_000bin_base = 0b_1111_0000hex_base = 0x_1234_abcd

print(dec_base) # 1000000print(bin_base) # 240print(hex_base) # 305441741

Conclusion

So far we’ve covered the underscore of Python. While I’m a Python programmer, I didn’t know some of them till wrote this post. Especially, the i18n/l10n is very new to me.Like me, I hope you gain some useful knowledges about underscore from this post.

Next, I’ll cover more interesting things about Python. Thank you.

_Update_Added the new feature (PEP 515) was added in Python 3.6

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