mirror of
https://github.com/clearml/clearml-docs
synced 2025-02-01 06:56:56 +00:00
64 lines
3.2 KiB
Markdown
64 lines
3.2 KiB
Markdown
---
|
|
title: Jupyter Notebook Server Service
|
|
---
|
|
|
|
The [execute_jupyter_notebook_server.py](https://github.com/allegroai/clearml/blob/master/examples/services/jupyter-service/execute_jupyter_notebook_server.py)
|
|
example demonstrates executing a Jupyter Notebook server in **ClearML Agent** services mode. The example script creates
|
|
an SSH server, and runs Jupyter Notebook as a subprocess. We integrate **ClearML** into the notebooks running on the Jupyter
|
|
Notebook server by passing environment variables to the subprocess, which point to:
|
|
* A **ClearML** configuration file
|
|
* A **ClearML Server** host configuration (web server, API server, and files server)
|
|
* **ClearML** API credentials.
|
|
|
|
**ClearML** logs the server links and console output, including the notebooks run on the server, in the example script's
|
|
Task. When the script runs, it creates an experiment named `Allocate Jupyter Notebook Instance`, which is associated with
|
|
the `DevOps` project in the **ClearML Web UI**.
|
|
|
|
## Running the Jupyter Notebook server service
|
|
|
|
1. The example script must run at least once before it can execute as a **ClearML Agent** service, because the Task must
|
|
be stored in **ClearML Server** in order to be enqueued for a **ClearML Agent** to fetch and execute.
|
|
|
|
python execute_jupyter_notebook_server.py
|
|
|
|
1. **ClearML Agent** must be running in services mode and listening to the `services` queue.
|
|
|
|
For example:
|
|
|
|
clearml-agent daemon --services-mode --detached --queue services --create-queue --cpu-only
|
|
|
|
1. Enqueue the Jupyter Notebook server Task.
|
|
|
|
1. In the **ClearML Web (UI)**, Project page **>** **examples** project **>** right click the **Remote Jupyter NoteBook**
|
|
experiment.
|
|
1. In the context menu, click **Enqueue** **>** select the **services** queue **>** **ENQUEUE**.
|
|
|
|
The status changes to *Pending* and then to *Running*. Once it is running, the Jupyter Notebook server is ready to
|
|
run notebooks.
|
|
|
|
## Logging the Jupyter Notebook server
|
|
|
|
**ClearML** stores the Jupyter Notebook server links in the `Task.comment` property, which appears in the **ClearML Web UI**
|
|
**>** the experiment's **INFO** tab **>** **DESCRIPTION** section.
|
|
|
|
task.comment += "\n" + "".join(
|
|
line for line in new_lines if "http://" in line or "https://" in line
|
|
)
|
|
|
|
It shows the server links are:
|
|
|
|
[I 12:54:48.940 NotebookApp] http://osboxes:8889/?token=3be82d87e83268934dd086e3b136cc408d4bd12e23409f3a
|
|
[I 12:54:48.940 NotebookApp] or http://127.0.0.1:8889/?token=3be82d87e83268934dd086e3b136cc408d4bd12e23409f3a
|
|
http://osboxes:8889/?token=3be82d87e83268934dd086e3b136cc408d4bd12e23409f3a
|
|
or http://127.0.0.1:8889/?token=3be82d87e83268934dd086e3b136cc408d4bd12e23409f3a
|
|
|
|
|
|
|
|
The Jupyter Note Server console output appears in **RESULTS** **>** **CONSOLE**, including log entries for the notebooks run
|
|
on the server.
|
|
|
|
To test the Jupyter Notebook, we ran a notebook named audio_preprocessing_example.ipynb. The log shows it was saved:
|
|
|
|
[I 17:26:45.925 NotebookApp] Saving file at /Projects/clearml-internal/examples/frameworks/pytorch/notebooks/table/download_and_preprocessing.ipynb
|
|
|
|
 |