Redirect standard out to Python’s logging module with contextlib

Python’s built in logging functionality is very nice once you get the hang of it, but many people (including library developers) either disagree or don’t bother to use it. Instead, you often see things like this:

>>> model.fit(X, y, verbose=True)
Epoch 0
Epoch 1
Epoch 2
...

and onwards for 100 lines or whatever.

Printing status messages to standard out is okay, but if you want anything like consistent/parseable logs, log level handling, logging to multiple locations, etc. this can get a bit annoying. How can we redirect standard out to Python’s logging system to get all these juicy benefits?

Another built in module, contextlib, comes to our rescue.

Aside: Context Managers

A context manager in Python is basically an object that implements two methods: __enter__ and __exit__. Usually you enter the context by using the with keyword, which triggers a call to __enter__. You execute some code in an indented block, and (roughly speaking) when you exit the block, the __exit__ method is called with information about any exceptions that occurred. The context manager interface is what makes these two pieces of code more or less equivalent:

h = open("file.txt")
text = h.read()
h.close()

is basically the same as

with open("file.txt") as h:
    text = h.read()

The file handle returned by open implements both __enter__ and __exit__, which is why it can be used in this way. The nice benefit here is that we never forget to close the file, as __exit__ (which closes the file in this case) is called automagically at the end of the block.

Redirecting stdout

So how does this help us? Well, contextlib (which is the library for things related to context managers, in case you didn’t catch that) has a very handy context manager called redirect_stdout (and also the matching redirect_stderr). We can use it to redirect text written to standard out to another file-like object. For example, to write to a file, we could do:

>>> import contextlib
>>> with open("output.txt", "w") as h, contextlib.redirect_stdout(h):
...     print("Hello world!")
...
>>> 

We don’t see any output. If we now look at the newly-created output.txt, we will see

$ cat output.txt
Hello world!

I realize that there are better ways of writing to a file in Python, but writing to a file isn’t the point. The point is that any arbitrary code executed in the context block above would have its output redirected to the file, without having to modify its print statements, including library code that we can’t easily modify.

Now, redirect_stdout requires a file-like object that it can write to, which is why we first had to open our output file above. However, Python’s loggers are not file-like. I think you see where this is going.

A file-like logger

To redirect standard out to logging, we write a simple class that implements the write method, and passes everything that is written to the logger of our choice. We’ll also add a flush method that doesn’t do anything, just to avoid exceptions in case some code tries to use it. We can specify the desired logger by name since Python’s loggers are singletons.

import logging
import contextlib

class OutputLogger:
    def __init__(self, name="root", level="INFO"):
        self.logger = logging.getLogger(name)
        self.name = self.logger.name
        self.level = getattr(logging, level)

    def write(self, msg):
        if msg and not msg.isspace():
            self.logger.log(self.level, msg)

    def flush(self): pass

I added a quick check for empty messages since I don’t want blank lines in my logging.

This is already enough to pass our object to redirect_stdout and thereby redirect standard out to logging:

>>> logging.basicConfig(level=logging.INFO)
>>> with contextlib.redirect_stdout(OutputLogger("my_logger", "INFO")):
...     print("Hello logging!") 
...
INFO:my_logger:Hello logging!

Note that we had to minimally call logging.basicConfig() to get a bit of formatting on the logs and set the log level to at least the level we selected for our redirector (INFO). Since our class is just functioning as a redirector for messages, we leave ourselves free to configure the logger however we want elsewhere in the application (check out the Python logging cookbook for tips).

Baby’s first context manager

This implementation is already functional, but it’s a bit verbose. Since we’re already in the contextlib realm we might as well just make our object into a context manager itself, eliminating the need to call contextlib.redirect_stdout directly every time we want to use it. To do so, we add a new attribute called _redirector to our class, which is an instance of redirect_stdout with self as the redirect destination. Then our __enter__ and __exit__ methods just call the matching methods of our _redirector, ensuring that everything printed in our context will get redirected to our own write method (which in turn passes messages to our logger). Our implementation becomes:

import logging
import contextlib

class OutputLogger:
    def __init__(self, name="root", level="INFO"):
        self.logger = logging.getLogger(name)
        self.name = self.logger.name
        self.level = getattr(logging, level)
        self._redirector = contextlib.redirect_stdout(self)

    def write(self, msg):
        if msg and not msg.isspace():
            self.logger.log(self.level, msg)

    def flush(self): pass

    def __enter__(self):
        self._redirector.__enter__()
        return self

    def __exit__(self, exc_type, exc_value, traceback):
        # let contextlib do any exception handling here
        self._redirector.__exit__(exc_type, exc_value, traceback)

Now we’re cooking! We can use OutputLogger as a context manager, and since we returned self from __enter__ we can even reuse the same instance later by giving it a name using the as keyword:

>>> print("Normal")
Normal
>>> 
>>> with OutputLogger("my_logger", "WARN") as redirector:
...     print("Logged!")
...
WARNING:my_logger:Logged!
>>> 
>>> print("Back to normal")
Back to normal
>>> 
>>> with redirector:
...     print("Logged again!")
...
WARNING:my_logger:Logged again!

There are all sorts of extensions possible here: redirecting standard error to another log level, making sure that changes to OutputLogger.name and OutputLogger.level get applied to the underlying logger properly, input checking on the log level string, etc. But this is enough to get started and will work as a quick and relatively clean way to capture the output from some other code and redirect it to your application’s logging system.

Disclaimer

Though contextlib.redirect_stdout is built in to Python, it does redefine sys.stdout for your whole process while the execution is within its context. For this reason, it can have unintended results for other pieces of code that are trying to do fancier stuff with sys.stdout than just write to it. This is a solution if you are writing an application that just needs to get something done, but if you are writing a library that other people might use, it’s best not do mess with these system properties without being very explicit about it. As always: Just because you can, doesn’t mean you should!

Cover image by Greenpeace Finland - originally posted to Flickr as Logging in Finnish Lapland: ancient trees for pulp and paper, CC BY 2.0, Link