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What is Context Manager in Python? How to use it?

2月21日 17:10

Python Context Managers Explained

Basic Concepts of Context Managers

Context managers are objects in Python used to manage resources, defining operations that should be performed when entering and exiting a context. The most common usage is the with statement.

Why Context Managers are Needed

python
# Bad practice - Manual resource management file = open('example.txt', 'r') try: content = file.read() process(content) finally: file.close() # Good practice - Use context manager with open('example.txt', 'r') as file: content = file.read() process(content) # File automatically closed

Context Manager Protocol

Context managers need to implement two methods:

  • __enter__(self): Called when entering context
  • __exit__(self, exc_type, exc_val, exc_tb): Called when exiting context

Basic Implementation

python
class MyContextManager: def __init__(self, resource): self.resource = resource def __enter__(self): print("Entering context") return self.resource def __exit__(self, exc_type, exc_val, exc_tb): print("Exiting context") # Return True to suppress exception, False to propagate exception return False # Use context manager with MyContextManager("resource") as resource: print(f"Using resource: {resource}") # Output: # Entering context # Using resource: resource # Exiting context

Exception Handling

python
class SafeContextManager: def __enter__(self): print("Entering safe context") return self def __exit__(self, exc_type, exc_val, exc_tb): print("Exiting safe context") if exc_type is not None: print(f"Caught exception: {exc_type.__name__}: {exc_val}") # Return True to suppress exception return True return False # Test exception handling with SafeContextManager(): print("Executing operation") raise ValueError("Test exception") print("Program continues") # Output: # Entering safe context # Executing operation # Exiting safe context # Caught exception: ValueError: Test exception # Program continues

contextlib Module

@contextmanager Decorator

The @contextmanager decorator simplifies creating context managers.

python
from contextlib import contextmanager @contextmanager def simple_context(): print("Entering context") try: yield "resource" finally: print("Exiting context") # Use with simple_context() as resource: print(f"Using resource: {resource}")

Context Manager with Exception Handling

python
from contextlib import contextmanager @contextmanager def error_handling_context(): print("Entering error handling context") try: yield except ValueError as e: print(f"Handling ValueError: {e}") raise # Re-raise exception finally: print("Cleaning up resources") # Use try: with error_handling_context(): print("Executing operation") raise ValueError("Test exception") except ValueError: print("Caught re-raised exception")

closing Function

The closing function creates a context manager for objects without context manager protocol.

python
from contextlib import closing class Resource: def __init__(self, name): self.name = name def close(self): print(f"Closing resource: {self.name}") # Use closing with closing(Resource("database connection")) as resource: print(f"Using resource: {resource.name}") # Resource automatically closed

suppress Function

The suppress function is used to ignore specified exceptions.

python
from contextlib import suppress # Ignore FileNotFoundError with suppress(FileNotFoundError): with open('nonexistent.txt', 'r') as f: content = f.read() print("Program continues") # Ignore multiple exceptions with suppress(FileNotFoundError, PermissionError): with open('protected.txt', 'r') as f: content = f.read()

redirect_stdout and redirect_stderr

python
from contextlib import redirect_stdout, redirect_stderr import io # Redirect standard output output = io.StringIO() with redirect_stdout(output): print("This message is redirected") print(f"Captured output: {output.getvalue()}") # Redirect standard error error_output = io.StringIO() with redirect_stderr(error_output): print("Error message", file=sys.stderr) print(f"Captured error: {error_output.getvalue()}")

Practical Application Scenarios

1. File Operations

python
# Automatically close files with open('input.txt', 'r') as input_file: with open('output.txt', 'w') as output_file: for line in input_file: output_file.write(line.upper()) # Both files automatically closed

2. Database Connections

python
import sqlite3 from contextlib import contextmanager @contextmanager def database_connection(db_path): conn = sqlite3.connect(db_path) try: yield conn finally: conn.close() # Use with database_connection('example.db') as conn: cursor = conn.cursor() cursor.execute("SELECT * FROM users") results = cursor.fetchall() # Connection automatically closed

3. Lock Management

python
import threading from contextlib import contextmanager class LockManager: def __init__(self): self.lock = threading.Lock() @contextmanager def acquire(self): self.lock.acquire() try: yield finally: self.lock.release() # Use lock_manager = LockManager() with lock_manager.acquire(): # Critical section code print("Executing critical section operation") # Lock automatically released

4. Temporary Directory

python
import tempfile import os # Create temporary directory with tempfile.TemporaryDirectory() as temp_dir: print(f"Temporary directory: {temp_dir}") temp_file = os.path.join(temp_dir, 'temp.txt') with open(temp_file, 'w') as f: f.write("Temporary data") # Temporary directory and contents automatically deleted on exit # Temporary directory has been deleted

5. Timer

python
import time from contextlib import contextmanager @contextmanager def timer(name): start_time = time.time() yield end_time = time.time() print(f"{name} took: {end_time - start_time:.4f} seconds") # Use with timer("Data processing"): data = [i ** 2 for i in range(1000000)] sum(data) # Output: Data processing took: 0.1234 seconds

6. Temporarily Change Configuration

python
from contextlib import contextmanager class Config: def __init__(self): self.debug = False self.verbose = False config = Config() @contextmanager def temporary_config(config_obj, **kwargs): """Temporarily modify configuration""" original_values = {} # Save original values for key, value in kwargs.items(): original_values[key] = getattr(config_obj, key) setattr(config_obj, key, value) try: yield finally: # Restore original values for key, value in original_values.items(): setattr(config_obj, key, value) # Use print(f"Debug mode: {config.debug}") # False with temporary_config(config, debug=True, verbose=True): print(f"Debug mode: {config.debug}") # True print(f"Verbose mode: {config.verbose}") # True print(f"Debug mode: {config.debug}") # False

7. Transaction Management

python
from contextlib import contextmanager class Database: def __init__(self): self.in_transaction = False self.data = {} def begin_transaction(self): self.in_transaction = True self.transaction_data = self.data.copy() def commit(self): self.in_transaction = False print("Transaction committed") def rollback(self): self.in_transaction = False self.data = self.transaction_data print("Transaction rolled back") @contextmanager def transaction(db): db.begin_transaction() try: yield db db.commit() except Exception as e: db.rollback() raise # Use db = Database() try: with transaction(db): db.data['key1'] = 'value1' db.data['key2'] = 'value2' # raise Exception("Test exception") # Will trigger rollback except Exception as e: print(f"Transaction failed: {e}") print(db.data)

Nested Context Managers

Using Multiple with Statements

python
# Nested usage with open('file1.txt', 'r') as f1: with open('file2.txt', 'r') as f2: content1 = f1.read() content2 = f2.read() # Process both files

Using contextlib.ExitStack

ExitStack allows dynamically managing multiple context managers.

python
from contextlib import ExitStack files = ['file1.txt', 'file2.txt', 'file3.txt'] with ExitStack() as stack: file_handles = [stack.enter_context(open(f, 'r')) for f in files] contents = [f.read() for f in file_handles] # All files automatically closed on exit

Conditional Context Managers

python
from contextlib import ExitStack, nullcontext def get_context(use_context): if use_context: return MyContextManager("resource") else: return nullcontext() # Conditionally use context manager with get_context(True) as resource: if resource is not None: print(f"Using resource: {resource}") else: print("Not using context manager")

Asynchronous Context Managers

Asynchronous Context Manager Protocol

Asynchronous context managers implement:

  • __aenter__(self): Asynchronously enter context
  • __aexit__(self, exc_type, exc_val, exc_tb): Asynchronously exit context
python
class AsyncContextManager: def __init__(self, resource): self.resource = resource async def __aenter__(self): print("Asynchronously entering context") await self.connect() return self.resource async def __aexit__(self, exc_type, exc_val, exc_tb): print("Asynchronously exiting context") await self.disconnect() async def connect(self): print("Connecting to resource...") async def disconnect(self): print("Disconnecting...") # Use asynchronous context manager async def use_async_context(): async with AsyncContextManager("async resource") as resource: print(f"Using resource: {resource}") # Run import asyncio asyncio.run(use_async_context())

asynccontextmanager Decorator

python
from contextlib import asynccontextmanager @asynccontextmanager async def async_resource(): print("Acquiring async resource") try: yield "async resource" finally: print("Releasing async resource") async def use_async_resource(): async with async_resource() as resource: print(f"Using resource: {resource}") asyncio.run(use_async_resource())

Best Practices

1. Ensure Resource Cleanup

python
# Good practice - Use finally to ensure cleanup class ResourceManager: def __enter__(self): self.resource = acquire_resource() return self.resource def __exit__(self, exc_type, exc_val, exc_tb): release_resource(self.resource) return False

2. Handle Exceptions Correctly

python
# Good practice - Distinguish exception types class SafeContextManager: def __exit__(self, exc_type, exc_val, exc_tb): if exc_type is None: print("Normal exit") elif issubclass(exc_type, (ValueError, TypeError)): print(f"Handling expected exception: {exc_val}") return True # Suppress expected exceptions else: print(f"Unhandled exception: {exc_val}") return False # Propagate unhandled exceptions

3. Provide Useful Error Messages

python
class DatabaseContextManager: def __enter__(self): try: self.connection = connect_to_database() return self.connection except ConnectionError as e: raise RuntimeError(f"Cannot connect to database: {e}") def __exit__(self, exc_type, exc_val, exc_tb): if self.connection: try: self.connection.close() except Exception as e: print(f"Error closing connection: {e}")

4. Support Context Manager Chaining

python
class ChainedContextManager: def __init__(self, *managers): self.managers = managers def __enter__(self): self.entered_managers = [] try: for manager in self.managers: self.entered_managers.append(manager.__enter__()) return self.entered_managers[-1] except: # If failed, clean up entered contexts self.__exit__(None, None, None) raise def __exit__(self, exc_type, exc_val, exc_tb): # Exit contexts in reverse order for manager in reversed(self.entered_managers): manager.__exit__(exc_type, exc_val, exc_tb) return False

Summary

Core concepts of Python context managers:

  1. Basic Protocol: Implement __enter__ and __exit__ methods
  2. with Statement: Automatically manage resource entry and exit
  3. Exception Handling: Handle exceptions in __exit__
  4. contextlib Module: Simplify creating context managers
  5. Practical Applications: File operations, database connections, lock management, etc.
  6. Nested Management: Use multiple with statements or ExitStack
  7. Async Support: Asynchronous context managers for async code

Advantages of context managers:

  • Automatic resource management, avoid resource leaks
  • Cleaner, more readable code
  • Exception-safe, ensures resource cleanup
  • Support nesting and chaining

Mastering context managers enables writing safer and more elegant Python code.

标签:Python