--- title: ClearML Task Tutorial --- In this tutorial, you will use `clearml-task` to execute [a script](https://github.com/allegroai/events/blob/master/webinar-0620/keras_mnist.py) on a remote or local machine, from a remote repository and your local machine. ### Prerequisites - `clearml` Python package installed - `clearml-agent` running on at least one machine (to execute the experiment), configured to listen to default queue ### Executing Code from a Remote Repository ``` bash clearml-task --project keras_examples --name remote_test --repo https://github.com/allegroai/events.git --script /webinar-0620/keras_mnist.py --args batch_size=64 epochs=1 --queue default ``` This sets the following arguments: * `--project keras_examples --name remote_test` - The project and experiment names * `--repo https://github.com/allegroai/events.git` - The repository's URL. By default, `clearml-task` uses the latest commit from the master branch * `--script /webinar-0620/keras_mnist.py` - The script to be executed * `--args batch_size=64 epochs=1` - Arguments passed to the script. This uses the `argparse` object to get CLI parameters * `--queue default` - Selected queue to send the experiment to :::note Adding Requirements `clearml-task` automatically finds the requirements.txt file in remote repositories. If a remote repo does not have such a file, make sure to either add one with all the required Python packages, or add the `--packages ""` option to the command (for example: `--packages "tqdm>=2.1" "scikit-learn"`). ::: Now `clearml-task` does all the heavy-lifting! 1. It creates a new Task on the [ClearML Server](../../deploying_clearml/clearml_server.md). 1. `clearml-task` enqueues the task in the selected execution queue, where a [ClearML Agent](../../clearml_agent.md) assigned to that queue executes the task. Your output should look something like this: ```console New task created id=2f96ee95b05d4693b360d0fcbb26b727 Task id=2f96ee95b05d4693b360d0fcbb26b727 sent for execution on queue default Execution log at: https://app.community.clear.ml/projects/552d5399112d47029c146d5248570295/experiments/2f96ee95b05d4693b360d0fcbb26b727/output/log ``` ### Executing a Local Script For this example, use a local version of [this script](https://github.com/allegroai/events/blob/master/webinar-0620/keras_mnist.py). 1. Clone the [allegroai/events](https://github.com/allegroai/events) repository 1. Go to the root folder of the cloned repository 1. Run the following command: ```bash clearml-task --project keras --name local_test --script webinar-0620/keras_mnist.py --requirements webinar-0620/requirements.txt --args epochs=1 --queue default ``` This sets the following arguments: * `--project keras --name local_test` - The project and experiment names * `--script /webinar-0620/keras_mnist.py` - The local script to be executed * `-requirements webinar-0620/requirements.txt` - The local python package requirements file * `--args batch_size=64 epochs=1` - Arguments passed to the script. This uses the argparse object to capture CLI parameters * `--queue default` - Selected queue to send the experiment to `clearml-task` creates a task according to the input parameters, and sends the task to the `default` queue for execution.