Python 实用宝典

Question 1

When it comes to constructors, and assignments, and method calls, the PyCharm IDE is pretty good at analyzing my source code and figuring out what type each variable should be. I like it when it’s right, because it gives me good code-completion and parameter info, and it gives me warnings if I try to access an attribute that doesn’t exist.

But when it comes to parameters, it knows nothing. The code-completion dropdowns can’t show anything, because they don’t know what type the parameter will be. The code analysis can’t look for warnings.

class Person:
    def __init__(self, name, age):
        self.name = name
        self.age = age

peasant = Person("Dennis", 37)
# PyCharm knows that the "peasant" variable is of type Person
peasant.dig_filth()   # shows warning -- Person doesn't have a dig_filth method

class King:
    def repress(self, peasant):
        # PyCharm has no idea what type the "peasant" parameter should be
        peasant.knock_over()   # no warning even though knock_over doesn't exist

King().repress(peasant)
# Even if I call the method once with a Person instance, PyCharm doesn't
# consider that to mean that the "peasant" parameter should always be a Person

This makes a certain amount of sense. Other call sites could pass anything for that parameter. But if my method expects a parameter to be of type, say, pygame.Surface, I’d like to be able to indicate that to PyCharm somehow, so it can show me all of Surface‘s attributes in its code-completion dropdown, and highlight warnings if I call the wrong method, and so on.

Is there a way I can give PyCharm a hint, and say “psst, this parameter is supposed to be of type X”? (Or perhaps, in the spirit of dynamic languages, “this parameter is supposed to quack like an X”? I’d be fine with that.)

EDIT: CrazyCoder’s answer, below, does the trick. For any newcomers like me who want the quick summary, here it is:

class King:
    def repress(self, peasant):
        """
        Exploit the workers by hanging on to outdated imperialist dogma which
        perpetuates the economic and social differences in our society.

        @type peasant: Person
        @param peasant: Person to repress.
        """
        peasant.knock_over()   # Shows a warning. And there was much rejoicing.

The relevant part is the @type peasant: Person line of the docstring.

If you also go to File > Settings > Python Integrated Tools and set “Docstring format” to “Epytext”, then PyCharm’s View > Quick Documentation Lookup will pretty-print the parameter information instead of just printing all the @-lines as-is.

Question 2

Yes, you can use special documentation format for methods and their parameters so that PyCharm can know the type. Recent PyCharm version supports most common doc formats.

For example, PyCharm extracts types from @param style comments.

See also reStructuredText and docstring conventions (PEP 257).

Another option is Python 3 annotations.

Please refer to the PyCharm documentation section for more details and samples.

Question 3

If you are using Python 3.0 or later, you can also use annotations on functions and parameters. PyCharm will interpret these as the type the arguments or return values are expected to have:

class King:
    def repress(self, peasant: Person) -> bool:
        peasant.knock_over() # Shows a warning. And there was much rejoicing.

        return peasant.badly_hurt() # Lets say, its not known from here that this method will always return a bool

Sometimes this is useful for non-public methods, that do not need a docstring. As an added benefit, those annotations can be accessed by code:

>>> King.repress.__annotations__
{'peasant': <class '__main__.Person'>, 'return': <class 'bool'>}

Update: As of PEP 484, which has been accepted for Python 3.5, it is also the official convention to specify argument and return types using annotations.

Question 4

PyCharm extracts types from a @type pydoc string. See PyCharm docs here and here, and Epydoc docs. It’s in the ‘legacy’ section of PyCharm, perhaps it lacks some functionality.

class King:
    def repress(self, peasant):
        """
        Exploit the workers by hanging on to outdated imperialist dogma which
        perpetuates the economic and social differences in our society.

        @type peasant: Person
        @param peasant: Person to repress.
        """
        peasant.knock_over()   # Shows a warning. And there was much rejoicing.

The relevant part is the @type peasant: Person line of the docstring.

My intention is not to steal points from CrazyCoder or the original questioner, by all means give them their points. I just thought the simple answer should be in an ‘answer’ slot.

Question 5

I’m using PyCharm Professional 2016.1 writing py2.6-2.7 code, and I found that using reStructuredText I can express types in a more succint way:

class Replicant(object):
    pass


class Hunter(object):
    def retire(self, replicant):
        """ Retire the rogue or non-functional replicant.
        :param Replicant replicant: the replicant to retire.
        """
        replicant.knock_over()  # Shows a warning.

See: https://www.jetbrains.com/help/pycharm/2016.1/type-hinting-in-pycharm.html#legacy

Question 6

You can also assert for a type and Pycharm will infer it:

def my_function(an_int):
    assert isinstance(an_int, int)
    # Pycharm now knows that an_int is of type int
    pass

Question 7

Is there a generally accepted way to comment functions in Python? Is the following acceptable?

#########################################################
# Create a new user
#########################################################
def add(self):

Question 8

The correct way to do it is to provide a docstring. That way, help(add) will also spit out your comment.

def add(self):
    """Create a new user.
    Line 2 of comment...
    And so on... 
    """

That’s three double quotes to open the comment and another three double quotes to end it. You can also use any valid Python string. It doesn’t need to be multiline and double quotes can be replaced by single quotes.

See: PEP 257

Question 9

Use a docstring, as others have already written.

You can even go one step further and add a doctest to your docstring, making automated testing of your functions a snap.

Question 10

Use a docstring:

A string literal that occurs as the first statement in a module, function, class, or method definition. Such a docstring becomes the __doc__ special attribute of that object.

All modules should normally have docstrings, and all functions and classes exported by a module should also have docstrings. Public methods (including the __init__ constructor) should also have docstrings. A package may be documented in the module docstring of the __init__.py file in the package directory.

String literals occurring elsewhere in Python code may also act as documentation. They are not recognized by the Python bytecode compiler and are not accessible as runtime object attributes (i.e. not assigned to __doc__ ), but two types of extra docstrings may be extracted by software tools:

String literals occurring immediately after a simple assignment at the top level of a module, class, or __init__ method are called “attribute docstrings”.

String literals occurring immediately after another docstring are called “additional docstrings”.

Please see PEP 258 , “Docutils Design Specification” [2] , for a detailed description of attribute and additional docstrings…

Question 11

The principles of good commenting are fairly subjective, but here are some guidelines:

Function comments should describe the intent of a function, not the implementation
Outline any assumptions that your function makes with regards to system state. If it uses any global variables (tsk, tsk), list those.
Watch out for excessive ASCII art. Having long strings of hashes may seem to make the comments easier to read, but they can be annoying to deal with when comments change
Take advantage of language features that provide ‘auto documentation’, i.e., docstrings in Python, POD in Perl, and Javadoc in Java

Question 12

Read about using docstrings in your Python code.

As per the Python docstring conventions:

The docstring for a function or method should summarize its behavior and document its arguments, return value(s), side effects, exceptions raised, and restrictions on when it can be called (all if applicable). Optional arguments should be indicated. It should be documented whether keyword arguments are part of the interface.

There will be no golden rule, but rather provide comments that mean something to the other developers on your team (if you have one) or even to yourself when you come back to it six months down the road.

Question 13

I would go for a documentation practice that integrates with a documentation tool such as Sphinx.

The first step is to use a docstring:

def add(self):
 """ Method which adds stuff
 """

Question 14

I would go a step further than just saying “use a docstring”. Pick a documentation generation tool, such as pydoc or epydoc (I use epydoc in pyparsing), and use the markup syntax recognized by that tool. Run that tool often while you are doing your development, to identify holes in your documentation. In fact, you might even benefit from writing the docstrings for the members of a class before implementing the class.

Question 15

Use docstrings.

This is the built-in suggested convention in PyCharm for describing function using docstring comments:

def test_function(p1, p2, p3):
    """
    test_function does blah blah blah.

    :param p1: describe about parameter p1
    :param p2: describe about parameter p2
    :param p3: describe about parameter p3
    :return: describe what it returns
    """ 
    pass

Question 16

While I agree that this should not be a comment, but a docstring as most (all?) answers suggest, I want to add numpydoc (a docstring style guide).

If you do it like this, you can (1) automatically generate documentation and (2) people recognize this and have an easier time to read your code.

Question 17

You can use three quotes to do it.

You can use single quotes:

def myfunction(para1,para2):
  '''
  The stuff inside the function
  '''

Or double quotes:

def myfunction(para1,para2):
  """
  The stuff inside the function
  """

Question 18

I saw that g will move from the request context to the app context in Flask 0.10, which made me confused about the intended use of g.

My understanding (for Flask 0.9) is that:

g lives in the request context, i.e., created afresh when the requests starts, and available until it ends
g is intended to be used as a “request blackboard”, where I can put stuff relevant for the duration of the request (i.e., set a flag at the beginning of the request and handle it at the end, possibly from a before_request/after_request pair)
in addition to holding request-level-state, g can and should be used for resource management, i.e., holding database connections, etc.

Which of these sentences are no longer true in Flask 0.10? Can someone point me to a resource discussing the reasons for the change? What should I use as a “request blackboard” in Flask 0.10 – should I create my own app/extension specific thread-local proxy and push it to the context stack before_request? What’s the point of resource management at the application context, if my application lives for a long while (not like a request) and thus the resources are never freed?

Question 19

Advanced Flask Patterns, as linked by Markus, explains some of the changes to g in 0.10:

g now lives in the application context.
Every request pushes a new application context, wiping the old one, so g can still be used to set flags per-request without change to code.
The application context is popped after teardown_request is called. (Armin’s presentation explains this is because things like creating DB connections are tasks which setup the environment for the request, and should not be handled inside before_request and after_request)

Question 20

As an addendum to the information in this thread: I’ve been a bit confused by the behavior of flask.g too, but some quick testing has helped me to clarify it. Here’s what I tried out:

from flask import Flask, g
app = Flask(__name__)

with app.app_context():
    print('in app context, before first request context')
    print('setting g.foo to abc')
    g.foo = 'abc'
    print('g.foo should be abc, is: {0}'.format(g.foo))

    with app.test_request_context():
        print('in first request context')
        print('g.foo should be abc, is: {0}'.format(g.foo))
        print('setting g.foo to xyz')
        g.foo = 'xyz'
        print('g.foo should be xyz, is: {0}'.format(g.foo))

    print('in app context, after first request context')
    print('g.foo should be abc, is: {0}'.format(g.foo))

    with app.test_request_context():
        print('in second request context')
        print('g.foo should be abc, is: {0}'.format(g.foo))
        print('setting g.foo to pqr')
        g.foo = 'pqr'
        print('g.foo should be pqr, is: {0}'.format(g.foo))

    print('in app context, after second request context')
    print('g.foo should be abc, is: {0}'.format(g.foo))

And here’s the output that it gives:

in app context, before first request context
setting g.foo to abc
g.foo should be abc, is: abc  

in first request context
g.foo should be abc, is: abc
setting g.foo to xyz
g.foo should be xyz, is: xyz  

in app context, after first request context
g.foo should be abc, is: xyz  

in second request context
g.foo should be abc, is: xyz
setting g.foo to pqr
g.foo should be pqr, is: pqr  

in app context, after second request context
g.foo should be abc, is: pqr

As theY4Kman said above, “Every request pushes a new application context”. And as the Flask docs say, the application context “will not be shared between requests”. Now, what hasn’t been explicitly stated (although I guess it’s implied from these statements), and what my testing clearly shows, is that you should never explicitly create multiple request contexts nested inside one application context, because flask.g (and co) doesn’t have any magic whereby it functions in the two different “levels” of context, with different states existing independently at the application and request levels.

The reality is that “application context” is potentially quite a misleading name, because app.app_context() is a per-request context, exactly the same as the “request context”. Think of it as a “request context lite”, only required in the case where you need some of the variables that normally require a request context, but you don’t need access to any request object (e.g. when running batch DB operations in a shell script). If you try and extend the application context to encompass more than one request context, you’re asking for trouble. So, rather than my test above, you should instead write code like this with Flask’s contexts:

from flask import Flask, g
app = Flask(__name__)

with app.app_context():
    print('in app context, before first request context')
    print('setting g.foo to abc')
    g.foo = 'abc'
    print('g.foo should be abc, is: {0}'.format(g.foo))

with app.test_request_context():
    print('in first request context')
    print('g.foo should be None, is: {0}'.format(g.get('foo')))
    print('setting g.foo to xyz')
    g.foo = 'xyz'
    print('g.foo should be xyz, is: {0}'.format(g.foo))

with app.test_request_context():
    print('in second request context')
    print('g.foo should be None, is: {0}'.format(g.get('foo')))
    print('setting g.foo to pqr')
    g.foo = 'pqr'
    print('g.foo should be pqr, is: {0}'.format(g.foo))

Which will give the expected results:

in app context, before first request context
setting g.foo to abc
g.foo should be abc, is: abc  

in first request context
g.foo should be None, is: None
setting g.foo to xyz
g.foo should be xyz, is: xyz  

in second request context
g.foo should be None, is: None
setting g.foo to pqr
g.foo should be pqr, is: pqr

Question 21

What’s the easiest way to do a case-insensitive string replacement in Python?

Question 22

The string type doesn’t support this. You’re probably best off using the regular expression sub method with the re.IGNORECASE option.

>>> import re
>>> insensitive_hippo = re.compile(re.escape('hippo'), re.IGNORECASE)
>>> insensitive_hippo.sub('giraffe', 'I want a hIPpo for my birthday')
'I want a giraffe for my birthday'

Question 23

import re
pattern = re.compile("hello", re.IGNORECASE)
pattern.sub("bye", "hello HeLLo HELLO")
# 'bye bye bye'

Question 24

In a single line:

import re
re.sub("(?i)hello","bye", "hello HeLLo HELLO") #'bye bye bye'
re.sub("(?i)he\.llo","bye", "he.llo He.LLo HE.LLO") #'bye bye bye'

Or, use the optional “flags” argument:

import re
re.sub("hello", "bye", "hello HeLLo HELLO", flags=re.I) #'bye bye bye'
re.sub("he\.llo", "bye", "he.llo He.LLo HE.LLO", flags=re.I) #'bye bye bye'

Question 25

Continuing on bFloch’s answer, this function will change not one, but all occurrences of old with new – in a case insensitive fashion.

def ireplace(old, new, text):
    idx = 0
    while idx < len(text):
        index_l = text.lower().find(old.lower(), idx)
        if index_l == -1:
            return text
        text = text[:index_l] + new + text[index_l + len(old):]
        idx = index_l + len(new) 
    return text

Question 26

Like Blair Conrad says string.replace doesn’t support this.

Use the regex re.sub, but remember to escape the replacement string first. Note that there’s no flags-option in 2.6 for re.sub, so you’ll have to use the embedded modifier '(?i)' (or a RE-object, see Blair Conrad’s answer). Also, another pitfall is that sub will process backslash escapes in the replacement text, if a string is given. To avoid this one can instead pass in a lambda.

Here’s a function:

import re
def ireplace(old, repl, text):
    return re.sub('(?i)'+re.escape(old), lambda m: repl, text)

>>> ireplace('hippo?', 'giraffe!?', 'You want a hiPPO?')
'You want a giraffe!?'
>>> ireplace(r'[binfolder]', r'C:\Temp\bin', r'[BinFolder]\test.exe')
'C:\\Temp\\bin\\test.exe'

Question 27

This function uses both the str.replace() and re.findall() functions. It will replace all occurences of pattern in string with repl in a case-insensitive way.

def replace_all(pattern, repl, string) -> str:
   occurences = re.findall(pattern, string, re.IGNORECASE)
   for occurence in occurences:
       string = string.replace(occurence, repl)
       return string

Question 28

This doesn’t require RegularExp

def ireplace(old, new, text):
    """ 
    Replace case insensitive
    Raises ValueError if string not found
    """
    index_l = text.lower().index(old.lower())
    return text[:index_l] + new + text[index_l + len(old):]

Question 29

An interesting observation about syntax details and options:

Python 3.7.2 (tags/v3.7.2:9a3ffc0492, Dec 23 2018, 23:09:28) [MSC v.1916 64 bit (AMD64)] on win32

import re
old = "TREEROOT treeroot TREerOot"
re.sub(r'(?i)treeroot', 'grassroot', old)

‘grassroot grassroot grassroot’

re.sub(r'treeroot', 'grassroot', old)

‘TREEROOT grassroot TREerOot’

re.sub(r'treeroot', 'grassroot', old, flags=re.I)

‘grassroot grassroot grassroot’

re.sub(r'treeroot', 'grassroot', old, re.I)

‘TREEROOT grassroot TREerOot’

So the (?i) prefix in the match expression or adding “flags=re.I” as a fourth argument will result in a case-insensitive match. BUT, using just “re.I” as the fourth argument does not result in case-insensitive match.

For comparison,

re.findall(r'treeroot', old, re.I)

[‘TREEROOT’, ‘treeroot’, ‘TREerOot’]

re.findall(r'treeroot', old)

[‘treeroot’]

Question 30

I was having \t being converted to the escape sequences (scroll a bit down), so I noted that re.sub converts backslashed escaped characters to escape sequences.

To prevent that I wrote the following:

Replace case insensitive.

import re
    def ireplace(findtxt, replacetxt, data):
        return replacetxt.join(  re.compile(findtxt, flags=re.I).split(data)  )

Also, if you want it to replace with the escape characters, like the other answers here that are getting the special meaning bashslash characters converted to escape sequences, just decode your find and, or replace string. In Python 3, might have to do something like .decode(“unicode_escape”) # python3

findtxt = findtxt.decode('string_escape') # python2
replacetxt = replacetxt.decode('string_escape') # python2
data = ireplace(findtxt, replacetxt, data)

Tested in Python 2.7.8

Hope that helps.

Question 31

never posted an answer before and this thread is really old but i came up with another sollution and figured i could get your respons, Im not seasoned in Python programming so if there are appearant drawbacks to it, please point them out since its good learning :)

i='I want a hIPpo for my birthday'
key='hippo'
swp='giraffe'

o=(i.lower().split(key))
c=0
p=0
for w in o:
    o[c]=i[p:p+len(w)]
    p=p+len(key+w)
    c+=1
print(swp.join(o))

Question 32

I am trying to filter a DateTimeField comparing with a date. I mean:

MyObject.objects.filter(datetime_attr=datetime.date(2009,8,22))

I get an empty queryset list as an answer because (I think) I am not considering time, but I want “any time”.

Is there an easy way in Django for doing this?

I have the time in the datetime setted, it is not 00:00.

Question 33

Such lookups are implemented in django.views.generic.date_based as follows:

{'date_time_field__range': (datetime.datetime.combine(date, datetime.time.min),
                            datetime.datetime.combine(date, datetime.time.max))}

Because it is quite verbose there are plans to improve the syntax using __date operator. Check “#9596 Comparing a DateTimeField to a date is too hard” for more details.

Question 34

YourModel.objects.filter(datetime_published__year='2008', 
                         datetime_published__month='03', 
                         datetime_published__day='27')

// edit after comments

YourModel.objects.filter(datetime_published=datetime(2008, 03, 27))

doest not work because it creates a datetime object with time values set to 0, so the time in database doesn’t match.

Question 35

Here are the results I got with ipython’s timeit function:

from datetime import date
today = date.today()

timeit[Model.objects.filter(date_created__year=today.year, date_created__month=today.month, date_created__day=today.day)]
1000 loops, best of 3: 652 us per loop

timeit[Model.objects.filter(date_created__gte=today)]
1000 loops, best of 3: 631 us per loop

timeit[Model.objects.filter(date_created__startswith=today)]
1000 loops, best of 3: 541 us per loop

timeit[Model.objects.filter(date_created__contains=today)]
1000 loops, best of 3: 536 us per loop

contains seems to be faster.

Question 36

Now Django has __date queryset filter to query datetime objects against dates in development version. Thus, it will be available in 1.9 soon.

Question 37

Mymodel.objects.filter(date_time_field__contains=datetime.date(1986, 7, 28))

the above is what I’ve used. Not only does it work, it also has some inherent logical backing.

Question 38

As of Django 1.9, the way to do this is by using __date on a datetime object.

For example: MyObject.objects.filter(datetime_attr__date=datetime.date(2009,8,22))

Question 39

This produces the same results as using __year, __month, and __day and seems to work for me:

YourModel.objects.filter(your_datetime_field__startswith=datetime.date(2009,8,22))

Question 40

assuming active_on is a date object, increment it by 1 day then do range

next_day = active_on + datetime.timedelta(1)
queryset = queryset.filter(date_created__range=(active_on, next_day) )

Question 41

Here is an interesting technique– I leveraged the startswith procedure as implemented with Django on MySQL to achieve the result of only looking up a datetime through only the date. Basically, when Django does the lookup in the database it has to do a string conversion for the DATETIME MySQL storage object, so you can filter on that, leaving out the timestamp portion of the date– that way %LIKE% matches only the date object and you’ll get every timestamp for the given date.

datetime_filter = datetime(2009, 8, 22) 
MyObject.objects.filter(datetime_attr__startswith=datetime_filter.date())

This will perform the following query:

SELECT (values) FROM myapp_my_object \ 
WHERE myapp_my_object.datetime_attr LIKE BINARY 2009-08-22%

The LIKE BINARY in this case will match everything for the date, no matter the timestamp. Including values like:

+---------------------+
| datetime_attr       |
+---------------------+
| 2009-08-22 11:05:08 |
+---------------------+

Hopefully this helps everyone until Django comes out with a solution!

Question 42

There’s a fantastic blogpost that covers this here: Comparing Dates and Datetimes in the Django ORM

The best solution posted for Django>1.7,<1.9 is to register a transform:

from django.db import models

class MySQLDatetimeDate(models.Transform):
    """
    This implements a custom SQL lookup when using `__date` with datetimes.
    To enable filtering on datetimes that fall on a given date, import
    this transform and register it with the DateTimeField.
    """
    lookup_name = 'date'

    def as_sql(self, compiler, connection):
        lhs, params = compiler.compile(self.lhs)
        return 'DATE({})'.format(lhs), params

    @property
    def output_field(self):
        return models.DateField()

Then you can use it in your filters like this:

Foo.objects.filter(created_on__date=date)

EDIT

This solution is definitely back end dependent. From the article:

Of course, this implementation relies on your particular flavor of SQL having a DATE() function. MySQL does. So does SQLite. On the other hand, I haven’t worked with PostgreSQL personally, but some googling leads me to believe that it does not have a DATE() function. So an implementation this simple seems like it will necessarily be somewhat backend-dependent.

Question 43

Hm.. My solution is working:

Mymodel.objects.filter(date_time_field__startswith=datetime.datetime(1986, 7, 28))

Question 44

Model.objects.filter(datetime__year=2011, datetime__month=2, datetime__day=30)

Question 45

In Django 1.7.6 works:

MyObject.objects.filter(datetime_attr__startswith=datetime.date(2009,8,22))

Question 46

See the article Django Documentation

ur_data_model.objects.filter(ur_date_field__gte=datetime(2009, 8, 22), ur_date_field__lt=datetime(2009, 8, 23))

Question 47

I have a class with two class methods (using the classmethod() function) for getting and setting what is essentially a static variable. I tried to use the property() function with these, but it results in an error. I was able to reproduce the error with the following in the interpreter:

class Foo(object):
    _var = 5
    @classmethod
    def getvar(cls):
        return cls._var
    @classmethod
    def setvar(cls, value):
        cls._var = value
    var = property(getvar, setvar)

I can demonstrate the class methods, but they don’t work as properties:

>>> f = Foo()
>>> f.getvar()
5
>>> f.setvar(4)
>>> f.getvar()
4
>>> f.var
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
TypeError: 'classmethod' object is not callable
>>> f.var=5
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
TypeError: 'classmethod' object is not callable

Is it possible to use the property() function with classmethod decorated functions?

Question 48

A property is created on a class but affects an instance. So if you want a classmethod property, create the property on the metaclass.

>>> class foo(object):
...     _var = 5
...     class __metaclass__(type):  # Python 2 syntax for metaclasses
...         pass
...     @classmethod
...     def getvar(cls):
...         return cls._var
...     @classmethod
...     def setvar(cls, value):
...         cls._var = value
...     
>>> foo.__metaclass__.var = property(foo.getvar.im_func, foo.setvar.im_func)
>>> foo.var
5
>>> foo.var = 3
>>> foo.var
3

But since you’re using a metaclass anyway, it will read better if you just move the classmethods in there.

>>> class foo(object):
...     _var = 5
...     class __metaclass__(type):  # Python 2 syntax for metaclasses
...         @property
...         def var(cls):
...             return cls._var
...         @var.setter
...         def var(cls, value):
...             cls._var = value
... 
>>> foo.var
5
>>> foo.var = 3
>>> foo.var
3

or, using Python 3’s metaclass=... syntax, and the metaclass defined outside of the foo class body, and the metaclass responsible for setting the initial value of _var:

>>> class foo_meta(type):
...     def __init__(cls, *args, **kwargs):
...         cls._var = 5
...     @property
...     def var(cls):
...         return cls._var
...     @var.setter
...     def var(cls, value):
...         cls._var = value
...
>>> class foo(metaclass=foo_meta):
...     pass
...
>>> foo.var
5
>>> foo.var = 3
>>> foo.var
3

Question 49

Reading the Python 2.2 release notes, I find the following.

The get method [of a property] won’t be called when the property is accessed as a class attribute (C.x) instead of as an instance attribute (C().x). If you want to override the __get__ operation for properties when used as a class attribute, you can subclass property – it is a new-style type itself – to extend its __get__ method, or you can define a descriptor type from scratch by creating a new-style class that defines __get__, __set__ and __delete__ methods.

NOTE: The below method doesn’t actually work for setters, only getters.

Therefore, I believe the prescribed solution is to create a ClassProperty as a subclass of property.

class ClassProperty(property):
    def __get__(self, cls, owner):
        return self.fget.__get__(None, owner)()

class foo(object):
    _var=5
    def getvar(cls):
        return cls._var
    getvar=classmethod(getvar)
    def setvar(cls,value):
        cls._var=value
    setvar=classmethod(setvar)
    var=ClassProperty(getvar,setvar)

assert foo.getvar() == 5
foo.setvar(4)
assert foo.getvar() == 4
assert foo.var == 4
foo.var = 3
assert foo.var == 3

However, the setters don’t actually work:

foo.var = 4
assert foo.var == foo._var # raises AssertionError

foo._var is unchanged, you’ve simply overwritten the property with a new value.

You can also use ClassProperty as a decorator:

class foo(object):
    _var = 5

    @ClassProperty
    @classmethod
    def var(cls):
        return cls._var

    @var.setter
    @classmethod
    def var(cls, value):
        cls._var = value

assert foo.var == 5

Question 50

I hope this dead-simple read-only @classproperty decorator would help somebody looking for classproperties.

class classproperty(object):

    def __init__(self, fget):
        self.fget = fget

    def __get__(self, owner_self, owner_cls):
        return self.fget(owner_cls)

class C(object):

    @classproperty
    def x(cls):
        return 1

assert C.x == 1
assert C().x == 1

Question 51

Is it possible to use the property() function with classmethod decorated functions?

No.

However, a classmethod is simply a bound method (a partial function) on a class accessible from instances of that class.

Since the instance is a function of the class and you can derive the class from the instance, you can can get whatever desired behavior you might want from a class-property with property:

class Example(object):
    _class_property = None
    @property
    def class_property(self):
        return self._class_property
    @class_property.setter
    def class_property(self, value):
        type(self)._class_property = value
    @class_property.deleter
    def class_property(self):
        del type(self)._class_property

This code can be used to test – it should pass without raising any errors:

ex1 = Example()
ex2 = Example()
ex1.class_property = None
ex2.class_property = 'Example'
assert ex1.class_property is ex2.class_property
del ex2.class_property
assert not hasattr(ex1, 'class_property')

And note that we didn’t need metaclasses at all – and you don’t directly access a metaclass through its classes’ instances anyways.

writing a `@classproperty` decorator

You can actually create a classproperty decorator in just a few lines of code by subclassing property (it’s implemented in C, but you can see equivalent Python here):

class classproperty(property):
    def __get__(self, obj, objtype=None):
        return super(classproperty, self).__get__(objtype)
    def __set__(self, obj, value):
        super(classproperty, self).__set__(type(obj), value)
    def __delete__(self, obj):
        super(classproperty, self).__delete__(type(obj))

Then treat the decorator as if it were a classmethod combined with property:

class Foo(object):
    _bar = 5
    @classproperty
    def bar(cls):
        """this is the bar attribute - each subclass of Foo gets its own.
        Lookups should follow the method resolution order.
        """
        return cls._bar
    @bar.setter
    def bar(cls, value):
        cls._bar = value
    @bar.deleter
    def bar(cls):
        del cls._bar

And this code should work without errors:

def main():
    f = Foo()
    print(f.bar)
    f.bar = 4
    print(f.bar)
    del f.bar
    try:
        f.bar
    except AttributeError:
        pass
    else:
        raise RuntimeError('f.bar must have worked - inconceivable!')
    help(f)  # includes the Foo.bar help.
    f.bar = 5

    class Bar(Foo):
        "a subclass of Foo, nothing more"
    help(Bar) # includes the Foo.bar help!
    b = Bar()
    b.bar = 'baz'
    print(b.bar) # prints baz
    del b.bar
    print(b.bar) # prints 5 - looked up from Foo!

    
if __name__ == '__main__':
    main()

But I’m not sure how well-advised this would be. An old mailing list article suggests it shouldn’t work.

Getting the property to work on the class:

The downside of the above is that the “class property” isn’t accessible from the class, because it would simply overwrite the data descriptor from the class __dict__.

However, we can override this with a property defined in the metaclass __dict__. For example:

class MetaWithFooClassProperty(type):
    @property
    def foo(cls):
        """The foo property is a function of the class -
        in this case, the trivial case of the identity function.
        """
        return cls

And then a class instance of the metaclass could have a property that accesses the class’s property using the principle already demonstrated in the prior sections:

class FooClassProperty(metaclass=MetaWithFooClassProperty):
    @property
    def foo(self):
        """access the class's property"""
        return type(self).foo

And now we see both the instance

>>> FooClassProperty().foo
<class '__main__.FooClassProperty'>

and the class

>>> FooClassProperty.foo
<class '__main__.FooClassProperty'>

have access to the class property.

Question 52

Python 3!

Old question, lots of views, sorely in need of a one-true Python 3 way.

Luckily, it’s easy with the metaclass kwarg:

class FooProperties(type):

    @property
    def var(cls):
        return cls._var

class Foo(object, metaclass=FooProperties):
    _var = 'FOO!'

Then, >>> Foo.var

‘FOO!’

Question 53

There is no reasonable way to make this “class property” system to work in Python.

Here is one unreasonable way to make it work. You can certainly make it more seamless with increasing amounts of metaclass magic.

class ClassProperty(object):
    def __init__(self, getter, setter):
        self.getter = getter
        self.setter = setter
    def __get__(self, cls, owner):
        return getattr(cls, self.getter)()
    def __set__(self, cls, value):
        getattr(cls, self.setter)(value)

class MetaFoo(type):
    var = ClassProperty('getvar', 'setvar')

class Foo(object):
    __metaclass__ = MetaFoo
    _var = 5
    @classmethod
    def getvar(cls):
        print "Getting var =", cls._var
        return cls._var
    @classmethod
    def setvar(cls, value):
        print "Setting var =", value
        cls._var = value

x = Foo.var
print "Foo.var = ", x
Foo.var = 42
x = Foo.var
print "Foo.var = ", x

The knot of the issue is that properties are what Python calls “descriptors”. There is no short and easy way to explain how this sort of metaprogramming works, so I must point you to the descriptor howto.

You only ever need to understand this sort of things if you are implementing a fairly advanced framework. Like a transparent object persistence or RPC system, or a kind of domain-specific language.

However, in a comment to a previous answer, you say that you

need to modify an attribute that in such a way that is seen by all instances of a class, and in the scope from which these class methods are called does not have references to all instances of the class.

It seems to me, what you really want is an Observer design pattern.

Question 54

Setting it only on the meta class doesn’t help if you want to access the class property via an instantiated object, in this case you need to install a normal property on the object as well (which dispatches to the class property). I think the following is a bit more clear:

#!/usr/bin/python

class classproperty(property):
    def __get__(self, obj, type_):
        return self.fget.__get__(None, type_)()

    def __set__(self, obj, value):
        cls = type(obj)
        return self.fset.__get__(None, cls)(value)

class A (object):

    _foo = 1

    @classproperty
    @classmethod
    def foo(cls):
        return cls._foo

    @foo.setter
    @classmethod
    def foo(cls, value):
        cls.foo = value

a = A()

print a.foo

b = A()

print b.foo

b.foo = 5

print a.foo

A.foo = 10

print b.foo

print A.foo

Question 55

Half a solution, __set__ on the class does not work, still. The solution is a custom property class implementing both a property and a staticmethod

class ClassProperty(object):
    def __init__(self, fget, fset):
        self.fget = fget
        self.fset = fset

    def __get__(self, instance, owner):
        return self.fget()

    def __set__(self, instance, value):
        self.fset(value)

class Foo(object):
    _bar = 1
    def get_bar():
        print 'getting'
        return Foo._bar

    def set_bar(value):
        print 'setting'
        Foo._bar = value

    bar = ClassProperty(get_bar, set_bar)

f = Foo()
#__get__ works
f.bar
Foo.bar

f.bar = 2
Foo.bar = 3 #__set__ does not

Question 56

Because I need to modify an attribute that in such a way that is seen by all instances of a class, and in the scope from which these class methods are called does not have references to all instances of the class.

Do you have access to at least one instance of the class? I can think of a way to do it then:

class MyClass (object):
    __var = None

    def _set_var (self, value):
        type (self).__var = value

    def _get_var (self):
        return self.__var

    var = property (_get_var, _set_var)

a = MyClass ()
b = MyClass ()
a.var = "foo"
print b.var

Question 57

Give this a try, it gets the job done without having to change/add a lot of existing code.

>>> class foo(object):
...     _var = 5
...     def getvar(cls):
...         return cls._var
...     getvar = classmethod(getvar)
...     def setvar(cls, value):
...         cls._var = value
...     setvar = classmethod(setvar)
...     var = property(lambda self: self.getvar(), lambda self, val: self.setvar(val))
...
>>> f = foo()
>>> f.var
5
>>> f.var = 3
>>> f.var
3

The property function needs two callable arguments. give them lambda wrappers (which it passes the instance as its first argument) and all is well.

Question 58

Here’s a solution which should work for both access via the class and access via an instance which uses a metaclass.

In [1]: class ClassPropertyMeta(type):
   ...:     @property
   ...:     def prop(cls):
   ...:         return cls._prop
   ...:     def __new__(cls, name, parents, dct):
   ...:         # This makes overriding __getattr__ and __setattr__ in the class impossible, but should be fixable
   ...:         dct['__getattr__'] = classmethod(lambda cls, attr: getattr(cls, attr))
   ...:         dct['__setattr__'] = classmethod(lambda cls, attr, val: setattr(cls, attr, val))
   ...:         return super(ClassPropertyMeta, cls).__new__(cls, name, parents, dct)
   ...:

In [2]: class ClassProperty(object):
   ...:     __metaclass__ = ClassPropertyMeta
   ...:     _prop = 42
   ...:     def __getattr__(self, attr):
   ...:         raise Exception('Never gets called')
   ...:

In [3]: ClassProperty.prop
Out[3]: 42

In [4]: ClassProperty.prop = 1
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-4-e2e8b423818a> in <module>()
----> 1 ClassProperty.prop = 1

AttributeError: can't set attribute

In [5]: cp = ClassProperty()

In [6]: cp.prop
Out[6]: 42

In [7]: cp.prop = 1
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-7-e8284a3ee950> in <module>()
----> 1 cp.prop = 1

<ipython-input-1-16b7c320d521> in <lambda>(cls, attr, val)
      6         # This makes overriding __getattr__ and __setattr__ in the class impossible, but should be fixable
      7         dct['__getattr__'] = classmethod(lambda cls, attr: getattr(cls, attr))
----> 8         dct['__setattr__'] = classmethod(lambda cls, attr, val: setattr(cls, attr, val))
      9         return super(ClassPropertyMeta, cls).__new__(cls, name, parents, dct)

AttributeError: can't set attribute

This also works with a setter defined in the metaclass.

Question 59

After searching different places, I found a method to define a classproperty valid with Python 2 and 3.

from future.utils import with_metaclass

class BuilderMetaClass(type):
    @property
    def load_namespaces(self):
        return (self.__sourcepath__)

class BuilderMixin(with_metaclass(BuilderMetaClass, object)):
    __sourcepath__ = 'sp'        

print(BuilderMixin.load_namespaces)

Hope this can help somebody :)

Question 60

Here’s my suggestion. Don’t use class methods.

Seriously.

What’s the reason for using class methods in this case? Why not have an ordinary object of an ordinary class?

If you simply want to change the value, a property isn’t really very helpful is it? Just set the attribute value and be done with it.

A property should only be used if there’s something to conceal — something that might change in a future implementation.

Maybe your example is way stripped down, and there is some hellish calculation you’ve left off. But it doesn’t look like the property adds significant value.

The Java-influenced “privacy” techniques (in Python, attribute names that begin with _) aren’t really very helpful. Private from whom? The point of private is a little nebulous when you have the source (as you do in Python.)

The Java-influenced EJB-style getters and setters (often done as properties in Python) are there to facilitate Java’s primitive introspection as well as to pass muster with the static language compiler. All those getters and setters aren’t as helpful in Python.

Question 61

I know @ is for decorators, but what is @= for in Python? Is it just reservation for some future idea?

This is just one of my many questions while reading tokenizer.py.

Question 62

From the documentation:

The @ (at) operator is intended to be used for matrix multiplication. No builtin Python types implement this operator.

The @ operator was introduced in Python 3.5. @= is matrix multiplication followed by assignment, as you would expect. They map to __matmul__, __rmatmul__ or __imatmul__ similar to how + and += map to __add__, __radd__ or __iadd__.

The operator and the rationale behind it are discussed in detail in PEP 465.

Question 63

@= and @ are new operators introduced in Python 3.5 performing matrix multiplication. They are meant to clarify the confusion which existed so far with the operator * which was used either for element-wise multiplication or matrix multiplication depending on the convention employed in that particular library/code. As a result, in the future, the operator * is meant to be used for element-wise multiplication only.

As explained in PEP0465, two operators were introduced:

A new binary operator A @ B, used similarly as A * B
An in-place version A @= B, used similarly as A *= B

Matrix Multiplication vs Element-wise Multiplication

To quickly highlight the difference, for two matrices:

A = [[1, 2],    B = [[11, 12],
     [3, 4]]         [13, 14]]

Element-wise multiplication will yield:

A * B = [[1 * 11,   2 * 12], 
         [3 * 13,   4 * 14]]

Matrix multiplication will yield:

A @ B  =  [[1 * 11 + 2 * 13,   1 * 12 + 2 * 14],
           [3 * 11 + 4 * 13,   3 * 12 + 4 * 14]]

Usage in Numpy

So far, Numpy used the following convention:

the * operator (and arithmetic operators in general) were defined as element-wise operations on ndarrays and as matrix-multiplication on numpy.matrix type.
method/function dot was used for matrix multiplication of ndarrays

Introduction of the @ operator makes the code involving matrix multiplications much easier to read. PEP0465 gives us an example:

# Current implementation of matrix multiplications using dot function
S = np.dot((np.dot(H, beta) - r).T,
            np.dot(inv(np.dot(np.dot(H, V), H.T)), np.dot(H, beta) - r))

# Current implementation of matrix multiplications using dot method
S = (H.dot(beta) - r).T.dot(inv(H.dot(V).dot(H.T))).dot(H.dot(beta) - r)

# Using the @ operator instead
S = (H @ beta - r).T @ inv(H @ V @ H.T) @ (H @ beta - r)

Clearly, the last implementation is much easier to read and interpret as an equation.

Question 64

@ is the new operator for Matrix Multiplication added in Python3.5

Reference: https://docs.python.org/3/whatsnew/3.5.html#whatsnew-pep-465

Example

C = A @ B

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问题：在类方法上使用property（）

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是否可以将property（）函数与装饰有类方法的函数一起使用？

写一个@classproperty装饰

使该属性在类上起作用：

Is it possible to use the property() function with classmethod decorated functions?

writing a @classproperty decorator

Getting the property to work on the class:

回答 4

Python 3！

Python 3!

回答 5

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回答 12

问题：Python中的’@ =’符号是什么？

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矩阵乘法与按元素乘法

在Numpy中使用

Matrix Multiplication vs Element-wise Multiplication

Usage in Numpy

回答 2

问题：为什么在导入模块时Python运行我的模块，以及如何停止它？

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回答 2

写一个`@classproperty`装饰

writing a `@classproperty` decorator

`NotImplementedError`“ 未在基类中实现 ”

`NotImplementedError`“ 预期的实现类型 ”

`NotImplementedError` “not implemented in base class“

`NotImplementedError` “expected implemented type“