In python, if you need a module from a different package you have to import it. Coming from a Java background, that makes sense.
import foo.bar
What doesn't make sense though, is why do I need to use the full name whenever I want to use bar? If I wanted to use the full name, why do I need to import? Doesn't using the full name immediately describe which module I'm addressing?
It just seems a little redundant to have from foo import bar when that's what import foo.bar should be doing. Also a little vague why I had to import when I was going to use the full name.
The thing is, even though Python's import statement is designed to look similar to Java's, they do completely different things under the hood. As you know, in Java an import statement is really little more than a hint to the compiler. It basically sets up an alias for a fully qualified class name. For example, when you write
import java.util.Set;
it tells the compiler that throughout that file, when you write Set, you mean java.util.Set. And if you write s.add(o) where s is an object of type Set, the compiler (or rather, linker) goes out and finds the add method in Set.class and puts in a reference to it.
But in Python,
import util.set
(that is a made-up module, by the way) does something completely different. See, in Python, packages and modules are not just names, they're actual objects, and when you write util.set in your code, that instructs Python to access an object named util and look for an attribute on it named set. The job of Python's import statement is to create that object and attribute. The way it works is that the interpreter looks for a file named util/__init__.py, uses the code in it to define properties of an object, and binds that object to the name util. Similarly, the code in util/set.py is used to initialize an object which is bound to util.set. There's a function called __import__ which takes care of all of this, and in fact the statement import util.set is basically equivalent to
util = __import__('util.set')
The point is, when you import a Python module, what you get is an object corresponding to the top-level package, util. In order to get access to util.set you need to go through that, and that's why it seems like you need to use fully qualified names in Python.
There are ways to get around this, of course. Since all these things are objects, one simple approach is to just bind util.set to a simpler name, i.e. after the import statement, you can have
set = util.set
and from that point on you can just use set where you otherwise would have written util.set. (Of course this obscures the built-in set class, so I don't recommend actually using the name set.) Or, as mentioned in at least one other answer, you could write
from util import set
or
import util.set as set
This still imports the package util with the module set in it, but instead of creating a variable util in the current scope, it creates a variable set that refers to util.set. Behind the scenes, this works kind of like
_util = __import__('util', fromlist='set')
set = _util.set
del _util
in the former case, or
_util = __import__('util.set')
set = _util.set
del _util
in the latter (although both ways do essentially the same thing). This form is semantically more like what Java's import statement does: it defines an alias (set) to something that would ordinarily only be accessible by a fully qualified name (util.set).
You can shorten it, if you would like:
import foo.bar as whateveriwant
Using the full name prevents two packages with the same-named submodules from clobbering each other.
There is a module in the standard library called io:
In [84]: import io
In [85]: io
Out[85]: <module 'io' from '/usr/lib/python2.6/io.pyc'>
There is also a module in scipy called io:
In [95]: import scipy.io
In [96]: scipy.io
Out[96]: <module 'scipy.io' from '/usr/lib/python2.6/dist-packages/scipy/io/__init__.pyc'>
If you wanted to use both modules in the same script, then namespaces are a convenient way to distinguish the two.
In [97]: import this
The Zen of Python, by Tim Peters
...
Namespaces are one honking great idea -- let's do more of those!
in Python, importing doesn't just indicate you might use something. The import actually executes code at the module level. You can think of the import as being the moment where the functions are 'interpreted' and created. Any code that is in the _____init_____.py level or not inside a function or class definition happens then.
The import also makes an inexpensive copy of the whole module's namespace and puts it inside the namespace of the file / module / whatever where it is imported. An IDE then has a list of the functions you might be starting to type for command completion.
Part of the Python philosophy is explicit is better than implicit. Python could automatically import the first time you try to access something from a package, but that's not explicit.
I'm also guessing that package initialization would be much more difficult if the imports were automatic, as it wouldn't be done consistently in the code.
You're a bit confused about how Python imports work. (I was too when I first started.) In Python, you can't simply refer to something within a module by the full name, unlike in Java; you HAVE to import the module first, regardless of how you plan on referring to the imported item. Try typing math.sqrt(5) in the interpreter without importing math or math.sqrt first and see what happens.
Anyway... the reason import foo.bar has you required to use foo.bar instead of just bar is to prevent accidental namespace conflicts. For example, what if you do import foo.bar, and then import baz.bar?
You could, of course, choose to do import foo.bar as bar (i.e. aliasing), but if you're doing that you may as well just use from foo import bar. (EDIT: except when you want to import methods and variables. Then you have to use the from ... import ... syntax. This includes instances where you want to import a method or variable without aliasing, i.e. you can't simply do import foo.bar if bar is a method or variable.)
Other than in Java, in Python import foo.bar declares, that you are going to use the thing referred to by foo.bar.
This matches with Python's philosophy that explicit is better than implicit. There are more programming languages that make inter-module dependencies more explicit than Java, for example Ada.
Using the full name makes it possible to disambiguate definitions with the same name coming from different modules.
You don't have to use the full name. Try one of these
from foo import bar
import foo.bar as bar
import foo.bar
bar = foo.bar
from foo import *
A few reasons why explicit imports are good:
They help signal to humans and tools what packages your module depends on.
They avoid the overhead of dynamically determining which packages have to be loaded (and possibly compiled) at run time.
They (along with sys.path) unambiguously distinguish symbols with conflicting names from different namespaces.
They give the programmer some control of what enters the namespace within which he is working.
Related
In Python, when we import something:
import Module
when we later want to use functions created in the module we have to say
Module.foo()
Is there any way to "attach" the module so that if I simply call
foo()
It knows that I mean to use the foo defined in Module, as long as the name does not conflict with any name in the current file?
from Module import *
This imports all symbols in Module unless overriden by __all__.
You can also explicitly import (which is better) only the symbols you actually need.
from Module import foo
It's typically preferred to use the later. Even better is to use the module as namespacing. There's nothing wrong with Module.foo() vs. foo(). Once your program gets fairly large, this will help you quite a bit with refactoring.
You can just do from module import foo, and then refer to foo() directly.
From the perspective of an external user of the module, are both necessary?
From my understanding, by correctly prefix hidden functions with an underscore it essentially does the same thing as explicitly define __all__, but I keep seeing developers doing both in their code. Why is that?
When importing from a module with from modulename import * names starting with underscores are indeed skipped.
However, a module rarely contains only public API objects. Usually you've made imports to support the code as well, and those names are global in the module as well. Without __all__, those names would be part of the import too.
In other words, unless you want to 'export' os in the following example you should use __all__:
import os
from .implementation import some_other_api_call
_module_path = os.path.dirname(os.path.abspath(__file__))
_template = open(os.path.join(_module_path, 'templates/foo_template.txt')).read()
VERSION = '1.0.0'
def make_bar(baz, ham, spam):
return _template.format(baz, ham, spam)
__all__ = ['some_other_api_call', 'make_bar']
because without the __all__ list, Python cannot distinguish between some_other_api_call and os here and divine which one should not be imported when using from ... import *.
You could work around this by renaming all your imports, so import os as _os, but that'd just make your code less readable.
And an explicit export list is always nice. Explicit is better than implicit, as the Zen of Python tells you.
I also use __all__: that explictly tells module users what you intend to export. Searching the module for names is tedious, even if you are careful to do, e.g., import os as _os, etc. A wise man once wrote "explicit is better than implicit" ;-)
Defining all will overide the default behaviour. There is actually might be one reason to define __all__
When importing a module, you might want that doing from mod import * will import only a minimal amount of things. Even if you prefix everything correctly, there could be reasons not to import everything.
The other problem that I had once was defining a gettext shortcut. The translation function was _ which would not get imported. Even if it is prefixed "in theory" I still wanted it to get exported.
One other reason as stated above is importing a module that imports a lot of thing. As python cannot make the difference between symbols created by imports and the one defined in the actual module. It will automatically reexport everything that can be reexported. For that reason, it could be wise to explicitely limit the thing exported to the things you want to export.
With that in mind, you might want to have some prefixed symbols exported by default. Usually, you don't redefine __all__. Whenever you need it to do something unusual then it may make sense to do it.
I am currently doing a python tutorial, but they use IDLE, and I opted to use the interpreter on terminal. So I had to find out how to import a module I created. At first I tried
import my_file
then I tried calling the function inside the module by itself, and it failed. I looked around and doing
my_file.function
works. I am very confused why this needs to be done if it was imported. Also, is there a way around it so that I can just call the function? Can anyone point me in the right direction. Thanks in advance.
If you wanted to use my_file.function by just calling function, try using the from keyword.
Instead of import my_file try from my_file import *.
You can also do this to only import parts of a module like so :
from my_file import function1, function2, class1
To avoid clashes in names, you can import things with a different name:
from my_file import function as awesomePythonFunction
EDIT:
Be careful with this, if you import two modules (myfile, myfile2) that both have the same function inside, function will will point to the function in whatever module you imported last. This could make interesting things happen if you are unaware of it.
This is a central concept to python. It uses namespaces (see the last line of import this). The idea is that with thousands of people writing many different modules, the likelihood of a name collision is reasonably high. For example, I write module foo which provides function baz and Joe Smith writes module bar which provides a function baz. My baz is not the same as Joe Smiths, so in order to differentiate the two, we put them in a namespace (foo and bar) so mine can be called by foo.baz() and Joe's can be called by bar.baz().
Of course, typing foo.baz() all the time gets annoying if you just want baz() and are sure that none of your other modules imported will provide any problems... That is why python provides the from foo import * syntax, or even from foo import baz to only import the function/object/constant baz (as others have already noted).
Note that things can get even more complex:
Assume you have a module foo which provides function bar and baz, below are a few ways to import and then call the functions contained inside foo...
import foo # >>> foo.bar();foo.baz()
import foo as bar # >>> bar.bar();bar.baz()
from foo import bar,baz # >>> bar(); baz()
from foo import * # >>> bar(); baz()
from foo import bar as cow # >>> cow() # This calls bar(), baz() is not available
...
A basic import statement is an assignment of the module object (everything's an object in Python) to the specified name. I mean this literally: you can use an import anywhere in your program you can assign a value to a variable, because they're the same thing. Behind the scenes, Python is calling a built-in function called __import__() to do the import, then returning the result and assigning it to the variable name you provided.
import foo
means "import module foo and assign it the name foo in my namespace. This is the same as:
foo = __import__("foo")
Similarly, you can do:
import foo as f
which means "import module foo and assign it the name f in my namespace." This is the same as:
f = __import__("foo")
Since in this case, you have only a reference to the module object, referring to things contained by the module requires attribute access: foo.bar etc.
You can also do from foo import bar. This creates a variable named bar in your namespace that points to the bar function in the foo module. It's syntactic sugar for:
bar = __import__("foo").bar
I don't really understand your confusion. You've imported the name my_file, not anything underneath it, so that's how you reference it.
If you want to import functions or classes inside a module directly, you can use:
from my_file import function
I'm going to incorporate many of the comments already posted.
To have access to function without having to refer to the module my_file, you can do one of the following:
from my_file import function
or
from my_file import *
For a more in-depth description of how modules work, I would refer to the documentation on python modules.
The first is the preferred solution, and the second is not recommended for many reasons:
It pollutes your namespace
It is not a good practice for maintainability (it becomes more difficult to find where specific names reside.
You typically don't know exactly what is imported
You can't use tools such as pyflakes to statically detect errors in your code
Python imports work differently than the #includes/imports in a static language like C or Java, in that python executes the statements in a module. Thus if two modules need to import a specific name (or *) out of each other, you can run into circular referencing problems, such as an ImportError when importing a specific name, or simply not getting the expected names defined (in the case you from ... import *). When you don't request specific names, you don't run into the, risk of having circular references, as long as the name is defined by the time you actually want to use it.
The from ... import * also doesn't guarantee you get everything. As stated in the documentation on python modules, a module can defined the __all__ name, and cause from ... import * statements to miss importing all of the subpackages, except those listed by __all__.
I am developing a Python package for dealing with some scientific data. There are multiple frequently-used classes and functions from other modules and packages, including numpy, that I need in virtually every function defined in any module of the package.
What would be the Pythonic way to deal with them? I have considered multiple variants, but every has its own drawbacks.
Import the classes at module-level with from foreignmodule import Class1, Class2, function1, function2
Then the imported functions and classes are easily accessible from every function. On the other hand, they pollute the module namespace making dir(package.module) and help(package.module) cluttered with imported functions
Import the classes at function-level with from foreignmodule import Class1, Class2, function1, function2
The functions and classes are easily accessible and do not pollute the module, but imports from up to a dozen modules in every function look as a lot of duplicate code.
Import the modules at module-level with import foreignmodule
Not too much pollution is compensated by the need to prepend the module name to every function or class call.
Use some artificial workaround like using a function body for all these manipulations and returning only the objects to be exported... like this
def _export():
from foreignmodule import Class1, Class2, function1, function2
def myfunc(x):
return function1(x, function2(x))
return myfunc
myfunc = _export()
del _export
This manages to solve both problems, module namespace pollution and ease of use for functions... but it seems to be not Pythonic at all.
So what solution is the most Pythonic? Is there another good solution I overlooked?
Go ahead and do your usual from W import X, Y, Z and then use the __all__ special symbol to define what actual symbols you intend people to import from your module:
__all__ = ('MyClass1', 'MyClass2', 'myvar1', …)
This defines the symbols that will be imported into a user's module if they import * from your module.
In general, Python programmers should not be using dir() to figure out how to use your module, and if they are doing so it might indicate a problem somewhere else. They should be reading your documentation or typing help(yourmodule) to figure out how to use your library. Or they could browse the source code yourself, in which case (a) the difference between things you import and things you define is quite clear, and (b) they will see the __all__ declaration and know which toys they should be playing with.
If you try to support dir() in a situation like this for a task for which it was not designed, you will have to place annoying limitations on your own code, as I hope is clear from the other answers here. My advice: don't do it! Take a look at the Standard Library for guidance: it does from … import … whenever code clarity and conciseness require it, and provides (1) informative docstrings, (2) full documentation, and (3) readable code, so that no one ever has to run dir() on a module and try to tell the imports apart from the stuff actually defined in the module.
One technique I've seen used, including in the standard library, is to use import module as _module or from module import var as _var, i.e. assigning imported modules/variables to names starting with an underscore.
The effect is that other code, following the usual Python convention, treats those members as private. This applies even for code that doesn't look at __all__, such as IPython's autocomplete function.
An example from Python 3.3's random module:
from warnings import warn as _warn
from types import MethodType as _MethodType, BuiltinMethodType as _BuiltinMethodType
from math import log as _log, exp as _exp, pi as _pi, e as _e, ceil as _ceil
from math import sqrt as _sqrt, acos as _acos, cos as _cos, sin as _sin
from os import urandom as _urandom
from collections.abc import Set as _Set, Sequence as _Sequence
from hashlib import sha512 as _sha512
Another technique is to perform imports in function scope, so that they become local variables:
"""Some module"""
# imports conventionally go here
def some_function(arg):
"Do something with arg."
import re # Regular expressions solve everything
...
The main rationale for doing this is that it is effectively lazy, delaying the importing of a module's dependencies until they are actually used. Suppose one function in the module depends on a particular huge library. Importing the library at the top of the file would mean that importing the module would load the entire library. This way, importing the module can be quick, and only client code that actually calls that function incurs the cost of loading the library. Further, if the dependency library is not available, client code that doesn't need the dependent feature can still import the module and call the other functions. The disadvantage is that using function-level imports obscures what your code's dependencies are.
Example from Python 3.3's os.py:
def get_exec_path(env=None):
"""[...]"""
# Use a local import instead of a global import to limit the number of
# modules loaded at startup: the os module is always loaded at startup by
# Python. It may also avoid a bootstrap issue.
import warnings
Import the module as a whole: import foreignmodule. What you claim as a drawback is actually a benefit. Namely, prepending the module name makes your code easier to maintain and makes it more self-documenting.
Six months from now when you look at a line of code like foo = Bar(baz) you may ask yourself which module Bar came from, but with foo = cleverlib.Bar it is much less of a mystery.
Of course, the fewer imports you have, the less of a problem this is. For small programs with few dependencies it really doesn't matter all that much.
When you find yourself asking questions like this, ask yourself what makes the code easier to understand, rather than what makes the code easier to write. You write it once but you read it a lot.
For this situation I would go with an all_imports.py file which had all the
from foreignmodule import .....
from another module import .....
and then in your working modules
import all_imports as fgn # or whatever you want to prepend
...
something = fgn.Class1()
Another thing to be aware of
__all__ = ['func1', 'func2', 'this', 'that']
Now, any functions/classes/variables/etc that are in your module, but not in your modules's __all__ will not show up in help(), and won't be imported by from mymodule import * See Making python imports more structured? for more info.
I would compromise and just pick a short alias for the foreign module:
import foreignmodule as fm
It saves you completely from the pollution (probably the bigger issue) and at least reduces the prepending burden.
I know this is an old question. It may not be 'Pythonic', but the cleanest way I've discovered for exporting only certain module definitions is, really as you've found, to globally wrap the module in a function. But instead of returning them, to export names, you can simply globalize them (global thus in essence becomes a kind of 'export' keyword):
def module():
global MyPublicClass,ExportedModule
import somemodule as ExportedModule
import anothermodule as PrivateModule
class MyPublicClass:
def __init__(self):
pass
class MyPrivateClass:
def __init__(self):
pass
module()
del module
I know it's not much different than your original conclusion, but frankly to me this seems to be the cleanest option. The other advantage is, you can group any number of modules written this way into a single file, and their private terms won't overlap:
def module():
global A
i,j,k = 1,2,3
class A:
pass
module()
del module
def module():
global B
i,j,k = 7,8,9 # doesn't overwrite previous declarations
class B:
pass
module()
del module
Though, keep in mind their public definitions will, of course, overlap.
I want to have a number of files imported in a general python file and then include that file when I need the imported modules in the current module. This of course will lead to errors and re-imports if using the from x import y, however when using the "normal" import statement I end up with long instruction statements, for example:
x = importModule.directoryName1.directoryName2.moduleName.ClassName()
whereas I'd like to do the following:
x = importModule.ClassName()
but as I said before, doing this:
from importModule.directoryName1.directoryName2.moduleNam import ClassName
in a general file doesn't work since I include importModule in ClassName.
So, I'm basically wondering if there's anyway around this (something like an using statement, such as the one in C++, perhaps?)
It sounds like you've got recursive imports (importModule refers to moduleName, and moduleName refers to importModule. If you refactor, you should be able to use
from importModule.directoryName1.directoryName2.moduleName import ClassName
To refactor, you can change the order in which things are imported in moduleName so that the class definition of ClassName occurs before the importModule import; as long as each file defines the references needed by the other module before they try and import the other module, things will work out.
Another way to refactor: you could always import ClassName within the function where it's used; as long as the function isn't called before moduleName is imported, you'll be fine.
The best way to refactor, though, is to move some classes or references into their own module, so you don't have any situation where A imports B and B imports A. That will fix your problem, as well as make it easier to maintain things going forward.
Well, you could do
from importModule.directoryName1.directoryName2 import moduleName as importModule
but that's kind of ugly and very confusing, and won't score you a lot of points with the Python programmers who read your code later.