Our tools work well with Jupyter notebooks. Each time you call wandb.init we create a new run and print a link to the run page. If the machine or directory you are running jupyter notebook from isn't configured, you will be prompted to configure the directory interactively in the notebook.
You can call wandb.log as you would normally and metrics will be sent to the run created by wandb.init. If you want to display live results in the notebook, you can decorate the cell that calls wandb.log with %%wandb. If you run this cell multiple times, data will be appended to the run.
{% hint style="info" %} Call wandb.init before you use %%wandb. If you are calling wandb.init inside a model training function, add a line after wandb.init to show graphs in the : display(wandb.jupyter.Run()) {% endhint %}
We have a nice extra integration with Google Colab. The first time you call wandb.init we will automatically pull in your credentials if you're already logged into wandb.
Calling wandb docker --jupyter will launch a docker container, mount your code in it, ensure jupyter is installed and launch it on port 8888.
This is not recommended as you may miss important information. If you'd like to disable info messages you can run the following in one of your cells
import logging
logger = logging.getLogger("wandb")
logger.setLevel(logging.ERROR)
If your project is private, viewers of your notebook will be prompted to login to view results.
If you're seeing the error message "Failed to query for notebook name, you can set it manually with the WANDB_NOTEBOOK_NAME environment variable," you can solve this by setting the environment variable from your script like so: os.environ['WANDB_NOTEBOOK_NAME'] = 'some text here'