PyDoctor doesn't create documentation for one module - python

I set pydoctor loose on my source code:
pydoctor *.py
and the auto-generated code seems nice, except for one of my modules just has a page saying "engine : module documentation - Undocumented". The module itself has a docstring as well as the class in it and several methods in it. It doesn't even list the methods or classes in engine.py. The only thing that stands out about engine.py other than sheer size is the number of modules it imports, but I don't see why that should be a problem.
import pygame, pygame.event, pygame.image, pygame.display
import EntityTypes, threading, main
import sys, time, events, collision, player, traceback
from functools import wraps
Thanks for any help.

somehow I see this a very long time after the question is asked... I can't help without seeing the module though. The only thing I can think of is that engine.py's docstring isn't being recognized as such for some reason.

Related

Pylint gives warnings for centralised imports

In a python project I would like to globber imports into a single file called common_imports.py in order to reduce number of import statements in python files.
Instead of writing
file1.py
import foo
import bar
import baz
[...]
file2.py
import foo
import bar
import baz
[...]
I would like to write
file1.py
from common_imports import *
[...]
file2.py
from common_imports import *
[...]
common_imports.py
import foo
import bar
import baz
However, this gives me a lot of pylint false positives.
I can disable pylint warnings in the common_imports.py file by adding a pylint disable comment. I can disable wildcard imports. Unfortunately, I can disable unused imports only globally but not specific for all imports from common_imports.py.
Somebody has an idea howto get pylint on the track?
Summarising my comments above into a proper answer:
TL;DR:
While the reusable code motive is commendable, it's not fit for purpose here. Listen to the linter, and save your hard-earned respect among your colleagues. :-)
Pythonic Viewpoint:
Don't
Why? Python convention, in all its organisational glory and documented structure, states that if you use a library in a module, import it in the module. Plain and simple.
Imports are always put at the top of the file, just after any module comments and docstrings, and before module globals and constants.
-- PEP8 - Imports
At a lower level, the sys.modules dict, which tracks imports, will only import a library if it hasn’t been imported already. So from an efficiency point of view, there is no gain.
Maintainer's Viewpoint:
Don't
Why? If (when) the code is changed / optimised in a module, thus alleviating the need for a specific import … "remind me where I look to find where that library is imported? Oh ya, here. But this other module needs that import, but not this new library I’m using to optimise this code. Where should I import that? Ugh!!!"
You've lost the hard-earned respect of following maintainers.

Python: After initialising a module, no longer can import functions

I have two files: 'my_main.py' and 'my_functions.py'. I wrote two functions in 'my_functions.py', 'first_function' and 'second_function' and imported this module into 'my_main.py'. However, I then added a third function into 'my_functions.py' called 'third_function':
def first_function():
print("hello1")
def second_function():
print("hello2")
def third_function():
print("hello3")
I found that I could not import 'third_function' into 'my_main.py', getting an error - AttributeError: module 'my_functions' has no attribute 'third_function'.
To understand this, in 'my_main.py' I then ran:
import my_functions
help(my_functions)
and had as my output:
Help on module my_functions:
NAME
my_functions
FUNCTIONS
first_function()
second_function()
For some reason 'my_functions.py' would not recognise any more functions after the initial two, meaning I couldn't then import 'third_function' into 'my_main.py'. How can I fix this?
Make sure you have saved your file my_functions.py before running my_main.py. Unless the file is saved, the update (addition of third_function) won't be recognized. Have been doing this for years, and still make this mistake constantly. Editing not enough. Need to edit and save.
You need to explicitly reload the module if you've made changes since the last import. There is a built-in function for this
You can reload your module as follows:
import importlib
importlib.reload(my_functions)
See this answer for a much more detailed explanation.

Way around Python imports within imports?

Sorry if this is a very novice question, I was just wondering one thing.
When in python and your code is split up amongst multiple files, how would you avoid a ton of imports on the same thing?
Say I have 2 files. Main, and Content.
Main:
import pygame
from pygame.locals import *
pygame.display.init()
blah
Content:
import pygame
from pygame.locals import *
pygame.display.init()
load content and stuff
pygame is imported twice and display.init is called twice. This is problematic in other places. Is there anyway to get around this, or must it just import and import and import?
One situation I can think of is this: A script that writes to a file everytime it is imported. That way, if it's imported 3 times, it gets run 3 times, therefore writing to the file 3 times.
Thanks in advance!
You misunderstand what import does. It's not the same as include. Loaded modules are singletons and their corresponding files are not evaluated twice.
That said, a well-constructed module will not have side-effects on import. That's the purpose of the if __name__=='__main__' idiom.
Do not attempt to "clean up" your imports. Import everything you need to use from within a file. You could make less use of import *, but this is purely for code readability and maintainability.
You should avoid having anything happen at import(except, see further down). a python file is a module first, so it can and should be used by other python modules. If something "happens" in the import stage of a python file, then it may happen in an undesirable way when that file is imported by another module.
Each module should just define things to be used: classes, functions, constants, and just wait for something else to use them.
Obviously, if no script ever does at import, then it's not possible for anything to actually get used and make stuff "happen". There is a special idiom for the unusual case that a module was called directly. Each python file has a variable, __name__ automatically created with the module name it was imported as. When you run a script from the command line (or however you have started it), it wasn't imported, and there's no name for it to have, and so the __name__ variable will have a special value "__main__" that indicates that it's the script being executed. You can check for this condition and act accordingly:
# main.py
import pygame
from pygame.locals import *
import content
def init():
pygame.display.init()
def stuff():
content.morestuff()
if __name__ == '__main__':
init()
stuff()
# content.py
import pygame
from pygame.locals import *
def init():
pygame.display.init()
def morestuff():
"do some more stuff"
if __name__ == '__main__':
init()
morestuff()
This way; init() and thus pygame.display.init() are only ever called once, by the script that was run by the user. the code that runs assuming that init() has already been called is broken into another function, and called as needed by the main script (whatever that happens to be)
import statements are supposed to be declarations that you're using something from another module. They shouldn't be used to cause something to happen (like writing to a file). As noted by Francis Avila, Python will try not to execute the code of a module more than once anyway.
This has the consequence that whether a given import statement will cause anything to happen is a global property of the application at runtime; you can't tell just from the import statement and the source code of the module, because it depends on whether any other code anywhere else in the project has already imported that module.
So having a module "do something" when executed is generally a very fragile way to implement your application. There is no hard and fast definition of "do something" though, because obviously the module needs to create all the things that other modules will import from it, and that may involve reading config files, possibly even writing log files, or any number of other things. But anything that seems like the "action" of your program, rather than just "setting up" things to be imported from the module, should usually not be done in module scope.

Python - import error

I've done what I shouldn't have done and written 4 modules (6 hours or so) without running any tests along the way.
I have a method inside of /mydir/__init__.py called get_hash(), and a class inside of /mydir/utils.py called SpamClass.
/mydir/utils.py imports get_hash() from /mydir/__init__.
/mydir/__init__.py imports SpamClass from /mydir/utils.py.
Both the class and the method work fine on their own but for some reason if I try to import /mydir/, I get an import error saying "Cannot import name get_hash" from /mydir/__init__.py.
The only stack trace is the line saying that __init__.py imported SpamClass. The next line is where the error occurs in in SpamClass when trying to import get_hash. Why is this?
This is a pretty easy problem to encounter. What's happening is this that the interpreter evaluates your __init__.py file line-by line. When you have the following code:
import mydir.utils
def get_hash(): return 1
The interpreter will suspend processing __init__.py at the point of import mydir.utils until it has fully executed 'mydir/utils.py' So when utils.py attempts to import get_hash(), it isn't defined because the interpreter hasn't gotten to it's definition yet.
To add to what the others have said, another good approach to avoiding circular import problems is to avoid from module import stuff.
If you just do standard import module at the top of each script, and write module.stuff in your functions, then by the time those functions run, the import will have finished and the module members will all be available.
You then also don't have to worry about situations where some modules can update/change one of their members (or have it monkey-patched by a naughty third party). If you'd imported from the module, you'd still have your old, out-of-date copy of the member.
Personally, I only use from-import for simple, dependency-free members that I'm likely to refer to a lot: in particular, symbolic constants.
In absence of more information, I would say you have a circular import that you aren't working around. The simplest, most obvious fix is to not put anything in mydir/__init__.py that you want to use from any module inside mydir. So, move your get_hash function to another module inside the mydir package, and import that module where you need it.

What are good rules of thumb for Python imports?

I am a little confused by the multitude of ways in which you can import modules in Python.
import X
import X as Y
from A import B
I have been reading up about scoping and namespaces, but I would like some practical advice on what is the best strategy, under which circumstances and why. Should imports happen at a module level or a method/function level? In the __init__.py or in the module code itself?
My question is not really answered by "Python packages - import by class, not file" although it is obviously related.
In production code in our company, we try to follow the following rules.
We place imports at the beginning of the file, right after the main file's docstring, e.g.:
"""
Registry related functionality.
"""
import wx
# ...
Now, if we import a class that is one of few in the imported module, we import the name directly, so that in the code we only have to use the last part, e.g.:
from RegistryController import RegistryController
from ui.windows.lists import ListCtrl, DynamicListCtrl
There are modules, however, that contain dozens of classes, e.g. list of all possible exceptions. Then we import the module itself and reference to it in the code:
from main.core import Exceptions
# ...
raise Exceptions.FileNotFound()
We use the import X as Y as rarely as possible, because it makes searching for usage of a particular module or class difficult. Sometimes, however, you have to use it if you wish to import two classes that have the same name, but exist in different modules, e.g.:
from Queue import Queue
from main.core.MessageQueue import Queue as MessageQueue
As a general rule, we don't do imports inside methods -- they simply make code slower and less readable. Some may find this a good way to easily resolve cyclic imports problem, but a better solution is code reorganization.
Let me just paste a part of conversation on django-dev mailing list started by Guido van Rossum:
[...]
For example, it's part of the Google Python style guides[1] that all
imports must import a module, not a class or function from that
module. There are way more classes and functions than there are
modules, so recalling where a particular thing comes from is much
easier if it is prefixed with a module name. Often multiple modules
happen to define things with the same name -- so a reader of the code
doesn't have to go back to the top of the file to see from which
module a given name is imported.
Source: http://groups.google.com/group/django-developers/browse_thread/thread/78975372cdfb7d1a
1: http://code.google.com/p/soc/wiki/PythonStyleGuide#Module_and_package_imports
I would normally use import X on module level. If you only need a single object from a module, use from X import Y.
Only use import X as Y in case you're otherwise confronted with a name clash.
I only use imports on function level to import stuff I need when the module is used as the main module, like:
def main():
import sys
if len(sys.argv) > 1:
pass
HTH
Someone above said that
from X import A,B,C,D,E,F,G,H,I,J,K,L,M,N,O,P
is equivalent to
import X
import X allows direct modifications to A-P, while from X import ... creates copies of A-P. For from X import A..P you do not get updates to variables if they are modified. If you modify them, you only modify your copy, but X does know about your modifications.
If A-P are functions, you won't know the difference.
Others have covered most of the ground here but I just wanted to add one case where I will use import X as Y (temporarily), when I'm trying out a new version of a class or module.
So if we were migrating to a new implementation of a module, but didn't want to cut the code base over all at one time, we might write a xyz_new module and do this in the source files that we had migrated:
import xyz_new as xyz
Then, once we cut over the entire code base, we'd just replace the xyz module with xyz_new and change all of the imports back to
import xyz
DON'T do this:
from X import *
unless you are absolutely sure that you will use each and every thing in that module. And even then, you should probably reconsider using a different approach.
Other than that, it's just a matter of style.
from X import Y
is good and saves you lots of typing. I tend to use that when I'm using something in it fairly frequently But if you're importing a lot from that module, you could end up with an import statement that looks like this:
from X import A,B,C,D,E,F,G,H,I,J,K,L,M,N,O,P
You get the idea. That's when imports like
import X
become useful. Either that or if I'm not really using anything in X very frequently.
I generally try to use the regular import modulename, unless the module name is long, or used often..
For example, I would do..
from BeautifulSoup import BeautifulStoneSoup as BSS
..so I can do soup = BSS(html) instead of BeautifulSoup.BeautifulStoneSoup(html)
Or..
from xmpp import XmppClientBase
..instead of importing the entire of xmpp when I only use the XmppClientBase
Using import x as y is handy if you want to import either very long method names , or to prevent clobbering an existing import/variable/class/method (something you should try to avoid completely, but it's not always possible)
Say I want to run a main() function from another script, but I already have a main() function..
from my_other_module import main as other_module_main
..wouldn't replace my main function with my_other_module's main
Oh, one thing - don't do from x import * - it makes your code very hard to understand, as you cannot easily see where a method came from (from x import *; from y import *; my_func() - where is my_func defined?)
In all cases, you could just do import modulename and then do modulename.subthing1.subthing2.method("test")...
The from x import y as z stuff is purely for convenience - use it whenever it'll make your code easier to read or write!
When you have a well-written library, which is sometimes case in python, you ought just import it and use it as it. Well-written library tends to take life and language of its own, resulting in pleasant-to-read -code, where you rarely reference the library. When a library is well-written, you ought not need renaming or anything else too often.
import gat
node = gat.Node()
child = node.children()
Sometimes it's not possible to write it this way, or then you want to lift down things from library you imported.
from gat import Node, SubNode
node = Node()
child = SubNode(node)
Sometimes you do this for lot of things, if your import string overflows 80 columns, It's good idea to do this:
from gat import (
Node, SubNode, TopNode, SuperNode, CoolNode,
PowerNode, UpNode
)
The best strategy is to keep all of these imports on the top of the file. Preferrably ordered alphabetically, import -statements first, then from import -statements.
Now I tell you why this is the best convention.
Python could perfectly have had an automatic import, which'd look from the main imports for the value when it can't be found from global namespace. But this is not a good idea. I explain shortly why. Aside it being more complicated to implement than simple import, programmers wouldn't be so much thinking about the depedencies and finding out from where you imported things ought be done some other way than just looking into imports.
Need to find out depedencies is one reason why people hate "from ... import *". Some bad examples where you need to do this exist though, for example opengl -wrappings.
So the import definitions are actually valuable as defining the depedencies of the program. It is the way how you should exploit them. From them you can quickly just check where some weird function is imported from.
The import X as Y is useful if you have different implementations of the same module/class.
With some nested try..import..except ImportError..imports you can hide the implementation from your code. See lxml etree import example:
try:
from lxml import etree
print("running with lxml.etree")
except ImportError:
try:
# Python 2.5
import xml.etree.cElementTree as etree
print("running with cElementTree on Python 2.5+")
except ImportError:
try:
# Python 2.5
import xml.etree.ElementTree as etree
print("running with ElementTree on Python 2.5+")
except ImportError:
try:
# normal cElementTree install
import cElementTree as etree
print("running with cElementTree")
except ImportError:
try:
# normal ElementTree install
import elementtree.ElementTree as etree
print("running with ElementTree")
except ImportError:
print("Failed to import ElementTree from any known place")
I'm with Jason in the fact of not using
from X import *
But in my case (i'm not an expert programmer, so my code does not meet the coding style too well) I usually do in my programs a file with all the constants like program version, authors, error messages and all that stuff, so the file are just definitions, then I make the import
from const import *
That saves me a lot of time. But it's the only file that has that import, and it's because all inside that file are just variable declarations.
Doing that kind of import in a file with classes and definitions might be useful, but when you have to read that code you spend lots of time locating functions and classes.

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