Python os.writev Function
Last modified April 11, 2025
This comprehensive guide explores Python's os.writev
function,
which performs scatter-gather I/O operations. We'll cover buffer management,
performance benefits, and practical file writing examples.
Basic Definitions
The os.writev
function writes data from multiple buffers to a file
descriptor in a single system call. This is known as vectorized I/O or
scatter-gather I/O.
Key parameters: fd (file descriptor), buffers (sequence of bytes-like objects). Returns total bytes written. Available on Unix-like systems (not Windows).
Basic File Writing with writev
This example demonstrates the simplest use of os.writev
to write
multiple buffers to a file. We'll create a file and write three separate chunks.
import os # Create a test file fd = os.open("output.txt", os.O_WRONLY | os.O_CREAT, 0o644) # Prepare multiple buffers buffers = [ b"First line\n", b"Second line\n", b"Third line\n" ] # Write all buffers at once bytes_written = os.writev(fd, buffers) print(f"Total bytes written: {bytes_written}") os.close(fd)
This code opens a file, creates three byte buffers, and writes them in one operation. The function returns the total bytes written across all buffers.
The advantage over multiple write calls is reduced system call overhead, especially beneficial for high-performance applications.
Writing Different Buffer Types
os.writev
accepts various bytes-like objects. This example shows
writing different types: bytes, bytearray, and memoryview objects.
import os fd = os.open("mixed_buffers.bin", os.O_WRONLY | os.O_CREAT, 0o644) buffers = [ b"Static bytes\n", bytearray(b"Bytearray content\n"), memoryview(b"Memoryview content\n") ] bytes_written = os.writev(fd, buffers) print(f"Total bytes written: {bytes_written}") os.close(fd)
This demonstrates os.writev
's flexibility with different bytes-like
objects. All are written efficiently in a single system call.
Memoryview is particularly useful as it avoids copying large buffers while still working with the vectorized write operation.
Performance Comparison
This example compares os.writev
with multiple os.write
calls to demonstrate the performance benefit of vectorized I/O.
import os import time def test_writev(fd, buffers): start = time.perf_counter() os.writev(fd, buffers) return time.perf_counter() - start def test_multiple_writes(fd, buffers): start = time.perf_counter() for buf in buffers: os.write(fd, buf) return time.perf_counter() - start # Prepare test data buffers = [b"x" * 1024 for _ in range(1000)] fd = os.open("perf_test.bin", os.O_WRONLY | os.O_CREAT) # Test writev writev_time = test_writev(fd, buffers) os.ftruncate(fd, 0) # Reset file # Test multiple writes write_time = test_multiple_writes(fd, buffers) os.close(fd) print(f"writev time: {writev_time:.6f}s") print(f"Multiple writes time: {write_time:.6f}s") print(f"Speedup: {write_time/writev_time:.1f}x")
This benchmark creates 1000 buffers and writes them using both methods. On most
systems, os.writev
will be significantly faster.
The performance difference comes from reduced system call overhead - one call instead of many. The advantage grows with more buffers.
Partial Writes with writev
Like regular writes, os.writev
may perform partial writes. This
example shows how to handle such cases by retrying with remaining data.
import os def robust_writev(fd, buffers): total = 0 while buffers: try: written = os.writev(fd, buffers) total += written # Adjust buffers based on what was written while written > 0: if written >= len(buffers[0]): written -= len(buffers[0]) buffers.pop(0) else: buffers[0] = buffers[0][written:] written = 0 except BlockingIOError: # Would block - wait and retry time.sleep(0.1) except InterruptedError: # System call interrupted - retry continue return total fd = os.open("partial_test.txt", os.O_WRONLY | os.O_CREAT | os.O_NONBLOCK) buffers = [b"a" * 10000, b"b" * 20000, b"c" * 30000] bytes_written = robust_writev(fd, buffers) print(f"Successfully wrote {bytes_written} bytes") os.close(fd)
This implementation handles partial writes by tracking how much was written and adjusting the buffers accordingly. It also handles non-blocking scenarios.
The function continues writing until all buffers are exhausted, making it robust against partial writes and interruptions.
Network Socket Writing
os.writev
is particularly useful for network programming. This
example shows writing HTTP response headers and body to a socket efficiently.
import os import socket def send_response(client_sock, headers, body): # Convert headers to bytes header_bytes = "\r\n".join(headers).encode("utf-8") # Prepare buffers - headers + blank line + body buffers = [ header_bytes, b"\r\n\r\n", body if isinstance(body, (bytes, bytearray, memoryview)) else body.encode("utf-8") ] # Get raw file descriptor from socket fd = client_sock.fileno() # Write all at once try: total = os.writev(fd, buffers) print(f"Sent {total} bytes") except (BrokenPipeError, ConnectionResetError) as e: print(f"Connection error: {e}") # Example usage server_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) server_socket.bind(("localhost", 8080)) server_socket.listen(1) client, addr = server_socket.accept() print(f"Connection from {addr}") headers = [ "HTTP/1.1 200 OK", "Content-Type: text/plain", "Connection: close" ] body = "Hello from writev example!" send_response(client, headers, body) client.close() server_socket.close()
This demonstrates how os.writev
can efficiently send HTTP responses
by combining headers and body in one system call.
The technique reduces latency and CPU overhead compared to multiple send calls, especially important for high-performance servers.
Memory Efficiency with Memoryview
This example shows how to use memoryview
with os.writev
to write large files without copying data.
import os def write_large_file(filename, chunks): fd = os.open(filename, os.O_WRONLY | os.O_CREAT, 0o644) # Convert chunks to memoryviews to avoid copying buffers = [memoryview(chunk) for chunk in chunks] total = 0 while buffers: written = os.writev(fd, buffers) total += written # Adjust buffers based on what was written while written > 0 and buffers: chunk_len = len(buffers[0]) if written >= chunk_len: written -= chunk_len buffers.pop(0) else: buffers[0] = buffers[0][written:] written = 0 os.close(fd) return total # Generate 1MB of data in 10 chunks data_chunks = [os.urandom(100000) for _ in range(10)] bytes_written = write_large_file("large_file.bin", data_chunks) print(f"Wrote {bytes_written} bytes")
This approach is memory efficient because memoryview
allows
slicing without copying the underlying data. It's ideal for large files.
The function handles partial writes and tracks progress through the buffer list, ensuring all data is eventually written.
Error Handling
This example demonstrates comprehensive error handling for os.writev
,
covering common failure scenarios and edge cases.
import os import errno def safe_writev(fd, buffers): if not buffers: raise ValueError("Empty buffer list") for buf in buffers: if not isinstance(buf, (bytes, bytearray, memoryview)): raise TypeError(f"Buffer must be bytes-like, got {type(buf)}") try: return os.writev(fd, buffers) except OSError as e: if e.errno == errno.EBADF: raise ValueError("Invalid file descriptor") from e elif e.errno == errno.EINVAL: raise ValueError("Invalid argument") from e elif e.errno == errno.EFAULT: raise ValueError("Bad buffer address") from e elif e.errno in (errno.EAGAIN, errno.EWOULDBLOCK): raise BlockingIOError("Write would block") from e elif e.errno == errno.EINTR: raise InterruptedError("System call interrupted") from e raise # Re-raise other errors # Example usage try: fd = os.open("error_test.txt", os.O_WRONLY | os.O_CREAT) buffers = [b"test", b"data"] try: written = safe_writev(fd, buffers) print(f"Wrote {written} bytes") finally: os.close(fd) except Exception as e: print(f"Error: {e}")
This implementation provides detailed error checking and meaningful error messages
for various failure scenarios that os.writev
might encounter.
The function validates input buffers and translates system errors into appropriate Python exceptions with clear explanations.
Security Considerations
- File descriptors: Ensure descriptors are valid and properly opened
- Buffer validation: Verify all buffers are bytes-like objects
- Partial writes: Always handle cases where not all data is written
- Resource limits: Large writes may hit system limits
- Platform support: Not available on Windows systems
Best Practices
- Use memoryview: For large buffers to avoid copying
- Handle partial writes: Implement retry logic for robustness
- Benchmark: Compare with alternatives for your use case
- Error handling: Cover all possible failure scenarios
- Document assumptions: Note platform requirements clearly
Source References
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