Disable output buffering

When -u isn't enough

What to do when -u switch or PYTHONUNBUFFERED doesn't play nice with your environment, or certain parts of your code? This section examines extra strategies to unbuffer Python's output, providing more control over buffering behavior.

Molding sys stdout properties

Tweak your stream's buffering directly by using the sys module. Example method: tweak sys.stdout to unbuffered mode utilizing the in-built io library:

import io
import sys

# Buffer = zero, for unbuffered output. No more waiting. Clever eh?
sys.stdout = io.TextIOWrapper(sys.stdout.buffer, write_through=True)
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Dynamic stream wrapper

You can creatively construct a custom class to auto-flush after every write task:

import sys

class UnbufferedStream(object):
    def __init__(self, stream):
        self.stream = stream
    
    def write(self, data):
        self.stream.write(data)
        self.stream.flush()  # Like a stream after heavy rain 🌧️
    
    def __getattr__(self, attr):
        return getattr(self.stream, attr)

sys.stdout = UnbufferedStream(sys.stdout)
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This unique setup means that any output sent to sys.stdout gets an automatic flush.

Line buffering with reconfigure (Python 3.7+)

Use sys.stdout.reconfigure for line buffering, this will flush your output right after a newline has been added:

import sys

if hasattr(sys.stdout, 'reconfigure'):
    sys.stdout.reconfigure(line_buffering=True)
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This Python 3.7+ method presents a convenient way to enable buffering on a per-line basis.

Real-world applications and caveats

When and where should you disable output buffering? Here are some use-cases and caveats.

Interactive environments

In shell scripts or automated pipelines with a need for rapid feedback, unbuffered output can immediately show log beacons or error alerts.

Performance trade-offs

While disabling buffering is beneficial for real-time output, expect a dip in performance because of more frequent I/O operations. Tread carefully in high-throughput environments.

Compatibility issues

Bufferless operations may not play well with certain libraries or systems - for instance, Windows consoles or remote sessions. Always rigorously test your solutions across different environments.

Persistence in subprocesses

Ensure that subprocesses invoked from Python also inherit the unbuffered setup. This can be ensured by calling subprocesses with modified environments or passing the -u flag if calling other Python scripts:

import subprocess

# This subprocess got the memo about being unbuffered
subprocess.run(['python', '-u', 'other_script.py'])
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