Give your app a name, add it to your workspace, then click Create App to finalise it. You can configure your Slack app to post to a shared channel, so everyone in your team can see the message, or use a private channel, to which only you have access.įirst, head over to the Slack website and register a new Slack app using your account. This is really easy to do in Python, and you can add Slack messaging functionality to your application in just a few minutes. In this project, we’ll create a really basic Slack application that you can use to send messages or alerts to specific channels using the webhooks system. Besides being a great tool for quick communications, it’s also perfect for alerting. When using distributed training, a GPU is bound to its process using the local rank variable.Slack is a great tool for data scientists and data engineers and is now being adopted across businesses, so it’s probable that you already use it in your workplace. You can also specify an optional argument to tag specific people: user-mentions= and/or user-mentions-mobile=.
sleep ( 10000 ) return # Optional return value Command-line knockknock wechat \ Python from knockknock import email_sender ( recipient_emails =, sender_email = "" ) def train_your_nicest_model ( your_nicest_parameters ): import time time. I recommend creating a new one (rather than your usual one) since you'll have to modify the account's security settings to allow the Python library to access it by Turning on less secure apps. You'll need a gmail email address to use it (you can setup one here, it's free). Microsoft service relies on Yagmail a GMAIL/SMTP client. There are currently twelve ways to setup notifications: Platform The return value (if there is one) is also reported in the notification. The library is designed to be used in a seamless way, with minimal code modification: you only need to add a decorator on top your main function call. This code has only been tested with Python >= 3.6.
It is also interesting to be notified when your training crashes in the middle of the process for unexpected reasons. Thus, it can be interesting to set up automatic notifications for your training. Apart from a rough estimate, it is difficult to predict when the training will finish. When training deep learning models, it is common to use early stopping. A small library to get a notification when your training is complete or when it crashes during the process with two additional lines of code.
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