Context Manager
1. Context Manager简介
"Context managers are a way of allocating and releasing some sort of resource exactly where you need it." Ref[4]
例如:
with file("/tmp/foo", "w") as foo:
print >> foo, "Hello!"
Context Manager是随with一起引入的。
"A context manager is an object that defines the runtime context to be established when executing a with
statement.
The context manager handles the entry into, and the exit from, the desired runtime context for the execution of the
block of code." Ref[11]
"Typical uses of context managers include saving and restoring various kinds of global state, locking and unlocking
resources, closing opened files, etc." Ref[11]
2. 创建Context Manager
2.1 Context Manager Type
with and context manager
"Python’s with
statement supports the concept of a runtime context defined by a context manager. This is implemented
using two separate methods that allow user-defined classes to define a runtime context that is entered before the statement body
is executed and exited when the statement ends. " Ref[6]
context management protocol
"The context management protocol consists of a pair of methods that need to be provided for a context manager
object to define a runtime context:" Ref[6]
contextmanager.__enter__() contextmanager.__exit__(exc_type, exc_val, exc_tb)
contextlib
"Python’s generators and the contextlib.contextmanager
decorator provide a convenient way to implement these protocols.
If a generator function is decorated with the contextlib.contextmanager
decorator, it will return a context manager
implementing the necessary __enter__()
and __exit__()
methods, rather than the iterator produced by an
undecorated generator function." Ref[6]
2.2 使用contextlib模块
"the simplest way is using the contextmanager
decorator from the contextlib
library, and invoking yield
in your context manager
function in between the setup and teardown steps." Ref[4]
Ref[4] 中的例子:
import contextlib
import time @contextlib.contextmanager
def time_print(task_name):
t = time.time()
try:
yield
finally:
print task_name, "took", time.time() - t, "seconds." with time_print("processes"):
[doproc() for _ in range(500)] # processes took 15.236166954 seconds. with time_print("threads"):
[dothread() for _ in range(500)] # threads took 0.11357998848 seconds.
Reference
1. contextlib
— Utilities for with
-statement contexts
https://docs.python.org/2/library/contextlib.html
2. With Statement Context Managers
https://docs.python.org/2/reference/datamodel.html#context-managers
3. with statement
https://docs.python.org/2/reference/compound_stmts.html#with
4. Introduction to Context Managers in Python (Read Again)
http://eigenhombre.com/2013/04/20/introduction-to-context-managers/
5. Fixture functions using “yield” / context manager integration
https://pytest.org/latest/yieldfixture.html
6. Build-in Types (To Read)
https://docs.python.org/2/library/stdtypes.html#typecontextmanager
7. PEP 343 -- The "with" Statement (To Read)
https://www.python.org/dev/peps/pep-0343/
8. Coding with context managers
http://python3porting.com/improving.html
9. Python: Tips, Tricks and Idioms - Part 2 - Decorators and Context Managers
https://codefisher.org/catch/blog/2015/02/10/python-decorators-and-context-managers/
10. Defining Context Managers the Easy Way
https://www.safaribooksonline.com/library/view/python-cookbook-3rd/9781449357337/ch09s22.html
11. With Statement Context Managers
https://docs.python.org/2/reference/datamodel.html#context-managers
Todo:
http://www.rafekettler.com/magicmethods.html