clearml-docs/docs/getting_started/ds/ds_first_steps.md

title
First Steps

Install ClearML

First, sign up for free.

Install the clearml python package:

pip install clearml

Connect ClearML SDK to the Server

Local Python

1. Execute the following command to run the ClearML setup wizard:

   clearml-init
   

   :::note The wizard does not edit or overwrite existing configuration files, so the above command will not work if a clearml.conf file already exists. :::

   Additional ClearML configuration files can be created, for example, to use inside Docker containers when executing a Task.

   Use the --file option for clearml-init.

   clearml-init --file MyOtherClearML.conf
   

   and then specify it using the CLEARML_CONFIG_FILE environment variable inside the container:

   CLEARML_CONFIG_FILE = MyOtherClearML.conf
   

   For more information about running experiments inside Docker containers, see ClearML Agent Deployment and ClearML Agent Reference.

2. The setup wizard prompts for ClearML credentials.

   Please create new clearml credentials through the settings page in your `clearml-server` web app (e.g. http://localhost:8080//settings/workspace-configuration), 
   or create a free account at https://app.clear.ml/settings/workspace-configuration
   
   In the settings page, press "Create new credentials", then press "Copy to clipboard".
   
   Paste copied configuration here:
   

3. Get ClearML credentials. Open the ClearML Web UI in a browser. On the SETTINGS > WORKSPACE page, click Create new credentials.

   The LOCAL PYTHON tab shows the data required by the setup wizard (a copy to clipboard action is available on hover).

4. At the command prompt Paste copied configuration here:, copy and paste the ClearML credentials. The setup wizard verifies the credentials.

   Detected credentials key="********************" secret="*******"
   
   CLEARML Hosts configuration:
   Web App: https://app.<your-domain>
   API: https://api.<your-domain>
   File Store: https://files.<your-domain>
   
   Verifying credentials ...
   Credentials verified!
   
   New configuration stored in /home/<username>/clearml.conf
   CLEARML setup completed successfully.
   

Now you can integrate ClearML into your code! Continue here.

Jupyter Notebook

To use ClearML with Jupyter Notebook, you need to configure ClearML Server access credentials for your notebook.

1. Get ClearML credentials. Open the ClearML Web UI in a browser. On the SETTINGS > WORKSPACE page, click Create new credentials. The JUPYTER NOTEBOOK tab shows the commands required to configure your notebook (a copy to clipboard action is available on hover)
2. Add these commands to your notebook

Now you can use ClearML in your notebook!

Auto-log Experiment

In ClearML, experiments are organized as Tasks.

ClearML automatically logs your experiment and code, including outputs and parameters from popular ML frameworks, once you integrate the ClearML SDK with your code. To control what ClearML automatically logs, see this FAQ.

At the beginning of your code, import the clearml package:

from clearml import Task

:::tip Full Automatic Logging To ensure full automatic logging, it is recommended to import the clearml package at the top of your entry script. :::

Then initialize the Task object in your main() function, or the beginning of the script.

task = Task.init(project_name='great project', task_name='best experiment')

If the project does not already exist, a new one is created automatically.

The console should display the following output:

ClearML Task: created new task id=1ca59ef1f86d44bd81cb517d529d9e5a
2021-07-25 13:59:09
ClearML results page: https://app.clear.ml/projects/4043a1657f374e9298649c6ba72ad233/experiments/1ca59ef1f86d44bd81cb517d529d9e5a/output/log
2021-07-25 13:59:16

That's it! You are done integrating ClearML with your code :)

Now, command-line arguments, console output as well as Tensorboard and Matplotlib will automatically be logged in the UI under the created Task.

Sit back, relax, and watch your models converge :) or continue to see what else can be done with ClearML here.

YouTube Playlist

Or watch the Getting Started playlist on ClearML's YouTube Channel!