7, Classes and Object-Oriented Programming in VS .NET

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7, Classes and Object-Oriented Programming
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contextlib
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The contextlib module provides a decorator and utility functions for creating context managers used in conjunction with the with statement
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contextmanager(func)
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A decorator that creates a context manager from a generator function funcThe way in which you use this decorator is as follows:
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@contextmanager def foo(args): statements try: yield value except Exception as e: error handling (if any) statements
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When the statement with foo(args) as value appears, the generator function is executed with the supplied arguments until the first yield statement is reachedThe value returned by yield is placed into the variable value At this point, the body of the with statement executes Upon completion, the generator function resumes If any kind of exception is raised inside the with-body, that exception is raised inside the generator function where it can be handled as appropriate If the error is to be propagated, the generator should use raise to re-raise the exception An example of using this decorator can be found in the Context Managers section of 5
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nested(mgr1, mgr2, , mgrN)
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A function that invokes more than one context manager mgr1, mgr2, and so on as a single operation Returns a tuple containing the different return values of the with statementsThe statement with nested(m1,m2) as (x,y): statements is the same as
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saying with m1 as x: with m2 as y: statements Be aware that if an inner context manager traps and suppresses an exception, no exception information is passed along to the outer managers
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closing(object)
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Creates a context manager that automatically executes objectclose() when execution leaves the body of the with statementThe value returned by the with statement is the same as object
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functools
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The functools module contains functions and decorators that are useful for creating higher-order functions, functional programming, and decorators
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partial(function [, *args [, **kwargs]])
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Creates a function-like object, partial, that when called, calls function with positional arguments args, keyword arguments kwargs, and any additional positional or keyword arguments that are supplied Additional positional arguments are added to the end of args, and additional keyword arguments are merged into kwargs, overwriting any previously defined values (if any) A typical use of partial() is when making a large number of function calls where many of the arguments are held fixed For example:
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from functools import partial mybutton = partial(Button, root, fg="black",bg="white",font="times",size="12") b1 = mybutton(text="Ok") # Calls Button() with text="Ok" and all of the b2 = mybutton(text="Cancel") # additional arguments supplied to partial() above b3 = mybutton(text="Restart")
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An instance p of the object created by partial has the following attributes:
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Item
pfunc pargs
Description
Function that is called when p is called Tuple containing the leftmost positional arguments supplied to pfunc when called Additional positional arguments are concatenated to the end of this value Dictionary containing the keyword arguments supplied to pfunc when called Additional keyword arguments are merged into this dictionary
pkeywords
Use caution when using a partial object as a stand-in for a regular functionThe result is not exactly the same as a normal function For instance, if you use partial() inside a class definition, it behaves like a static method, not an instance method
reduce(function, items [, initial])
Applies a function, function, cumulatively to the items in the iterable items and returns a single value function must take two arguments and is first applied to the first two items of itemsThis result and subsequent elements of items are then combined one at a time in a similar manner, until all elements of items have been consumed initial is an optional starting value used in the first computation and when items is
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heapq
emptyThis function is the same as the reduce() function that was a built-in in Python 2 For future compatibility, use this version instead
update_wrapper(wrapper, wrapped [, assigned [, updated]])
This is a utility function that is useful when writing decorators Copies attributes from a function wrapped to a wrapper function wrapper in order to make the wrapped function look like the original function assigned is a tuple of attribute names to copy and is set to ('_ _name_ _','_ _module_ _','_ _doc_ _') by default updated is a tuple containing the names of function attributes that are dictionaries and which you want values merged in the wrapper By default, it is a tuple ('_ _dict_ _',)
wraps(function [, assigned [, updated ]])
A decorator carries out the same task as update_wrapper() on the function to which it is applied assigned and updated have the same meaning A typical use of this decorator is when writing other decorators For example:
from functools import wraps def debug(func): @wraps(func) def wrapped(*args,**kwargs): print("Calling %s" % func_ _name_ _) r = func(*args,**kwargs) print("Done calling %s" % func_ _name_ _) return wrapped @debug def add(x,y): return x+y
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