I am trying to automating a long running job, and I want to be able to upload all console outputs to another log like on CloudWatch Logs. For the most part this can be done by making and using a custom function instead of print. But there are functions in MachineLearning like Model.summary() or progress bars while training that outputs to stdout on their own.
I can get all get all console outputs at the very end, via an internal console log. But what I need is real-time uploading of stdout as its called by whomever. So that one can check the progress by taking a look at the logs on Cloudwatch instead of having to log into the machine and check the internal console logs.
Basically what I need is:
From: call_to_stdout -> Console(and probably other stuff)
To: call_to_stdout -> uploadLog() -> Console(and probably other stuff)
pseudocode of what I need
class stdout_PassThru:
def __init__(self, in_old_stdout):
self.old_stdout = in_old_stdout
def write(self, msg):
self.old_stdout.write(msg)
uploadLogToCloudwatch(msg)
def uploadLogToCloudwatch(msg):
# Botocore stuff to upload to Cloudwatch
myPassThru = stdout_PassThru(sys.stdout)
sys.stdout = myPassThru
I've tried googling this, but the best I ever get is stringIO stuff, where I can capture stdout, but I cannot do anything with it until the function I called ends and I can insert code again. I would like to run my upload Log code everytime stdout is used.
Is this even possible? Please and thank you.
EDIT: Someone suggested redirect/output to file. The problem is that, that just streams/writes to the file as things are outputted. I need to call a function that does work on each call to stdout, which is not a stream. If stdout outputs everytime it flushes itself, then having the function call then would be good too.