clearml-docs/docs/clearml_data.md

---
title: ClearML Data
---

In Machine Learning, you are very likely dealing with a gargantuan amount of data that you need to put in a dataset,
which you then need to be able to share, reproduce, and track.

ClearML Data Management solves two important challenges:
- Accessibility - Making data easily accessible from every machine,
- Versioning - Linking data and experiments for better **traceability**.

**We believe Data is not code**. It should not be stored in a git tree, because progress on datasets is not always linear. 
Moreover, it can be difficult and inefficient to find on a git tree the commit associated with a certain version of a dataset. 

A `clearml-data` dataset is a collection of files, stored on a central storage location (S3 \ GS \ Azure \ Network Storage).
Datasets can be set up to inherit from other datasets, so data lineages can be created, 
and users can track when and how their data changes.<br/>
Dataset changes are stored using differentiable storage, meaning a version will store the change-set from its previous dataset parents

Local copies of datasets are always cached, so the same data never needs to be downloaded twice.
When a dataset is pulled it will automatically pull all parent datasets and merge them into one output folder for you to work with

ClearML-data offers two interfaces:
- `clearml-data` - CLI utility for creating, uploading, and managing datasets.  
- `clearml.Dataset` - A python interface for creating, retrieving, managing, and using datasets.

## Creating a Dataset 

Using the `clearml-data` CLI, users can create datasets using the following commands:
```bash
clearml-data create --project dataset_example --name initial_version
clearml-data add --files data_folder 
```

The commands will do the following:

1. Start a Data Processing Task called "initial_version" in the "dataset_example" project
   
1. The CLI will return a unique ID for the dataset
   
1. All the files from the "data_folder" folder will be added to the dataset and uploaded 
by default to the [ClearML server](deploying_clearml/clearml_server.md). 

:::note
`clearml-data` is stateful and remembers the last created dataset so there's no need to specify a specific dataset ID unless 
we want to work on another dataset.
:::

## Using a Dataset
Now in our python code, we can access and use the created dataset from anywhere:

```python
from clearml import Dataset

local_path = Dataset.get(dataset_id='dataset_id_from_previous_command').get_local_copy()
```

We have all our files in the same folder structure under `local_path`, it is that simple!<br/>

The next step is to set the dataset_id as a parameter for our code and voilà! We can now train on any dataset we have in 
the system.

## Setup

`clearml-data` comes built-in with our `clearml` python package! Just check out the [getting started](getting_started/ds/ds_first_steps.md) guide for more info!

## Usage

### CLI

It's possible to manage datasets (create \ modify \ upload \ delete) with the `clearml-data` command line tool.

#### Creating a Dataset
```bash
clearml-data create --project <project_name> --name <dataset_name> --parents <existing_dataset_id>`
```
Creates a new dataset. <br/>

**Parameters**

|Name|Description|Optional|
|---|---|---|
|name |Dataset's name| <img src="/icons/ico-optional-no.svg" className="icon size-md center-md" /> |
|project|Dataset's project| <img src="/icons/ico-optional-no.svg" className="icon size-md center-md" /> | 
|parents|IDs of the dataset's parents. The dataset inherits all of its parents' content. Multiple parents can be entered, but they are merged in the order they were entered| <img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" /> |
|tags |Dataset user tags. The dataset can be labeled, which can be useful for organizing datasets| <img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|

:::important
clearml-data works in a stateful mode so once a new dataset is created, the following commands 
do not require the `--id` flag.
:::
 
<br/>

#### Add Files to Dataset
```bash
clearml-data add --id <dataset_id> --files <filenames/folders_to_add>
```
It's possible to add individual files or complete folders.<br/>

**Parameters**

|Name|Description|Optional|
|---|---|---|
|id | Dataset's ID. Default: previously created / accessed dataset| <img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" /> |
|files|Files / folders to add. Wildcard selection is supported, for example: `~/data/*.jpg ~/data/json` | <img src="/icons/ico-optional-no.svg" className="icon size-md center-md" /> |
|dataset-folder | Dataset base folder to add the files to in the dataset. Default: dataset root| <img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" /> |
|non-recursive | Disable recursive scan of files | <img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" /> |
|verbose | Verbose reporting | <img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|

<br/>

#### Remove Files From Dataset
```bash
clearml-data remove --id <dataset_id_to_remove_from> --files <filenames/folders_to_remove>  
```    

**Parameters**

|Name|Description|Optional|
|---|---|---|
|id | Dataset's ID. Default: previously created / accessed dataset| <img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" /> |
|files |  Files / folders to remove (wildcard selection is supported, for example: `~/data/*.jpg ~/data/json`). Notice: file path is the path within the dataset, not the local path.| <img src="/icons/ico-optional-no.svg" className="icon size-md center-md" /> | 
|non-recursive | Disable recursive scan of files | <img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" /> |
|verbose | Verbose reporting | <img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|

<br/>

#### Finalize Dataset
```bash
clearml-data close --id <dataset_id>
```  
Finalizes the dataset and makes it ready to be consumed. 
It automatically uploads all files that were not previously uploaded. 
Once a dataset is finalized, it can no longer be modified. 

**Parameters**

|Name|Description|Optional|
|---|---|---|
|id| Dataset's ID. Default: previously created / accessed dataset| <img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" /> |
|storage| Remote storage to use for the dataset files. Default: files_server | <img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" /> |
|disable-upload | Disable automatic upload when closing the dataset | <img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" /> |
|verbose | Verbose reporting | <img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|

<br/>

#### Upload Dataset' Content  
```bash
clearml-data upload [--id <dataset_id>] [--storage <upload_destination>]
```
Uploads added files to [ClearML Server](deploying_clearml/clearml_server.md) by default. It's possible to specify a different storage 
medium by entering an upload destination, such as `s3://bucket`, `gs://`, `azure://`, `/mnt/shared/`.


**Parameters**
     
|Name|Description|Optional|
|---|---|---|
|id| Dataset's ID. Default: previously created / accessed dataset| <img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" /> |
|storage| Remote storage to use for the dataset files. Default: files_server | <img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" /> |
|verbose | Verbose reporting | <img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|

<br/>

#### Sync Local Folder
```
clearml-data sync [--id <dataset_id] --folder <folder_location>  [--parents '<parent_id>']`
```
This option syncs a folder's content with ClearML. It is useful in case a user has a single point of truth (i.e. a folder) which
updates from time to time.


Once an update should be reflected into ClearML's system, users can call `clearml-data sync`, create a new dataset, enter the folder, 
and the changes (either file addition, modification and removal) will be reflected in ClearML.

This command also uploads the data and finalizes the dataset automatically.

**Parameters**

|Name|Description|Optional|
|---|---|---|
|id| Dataset's ID. Default: previously created / accessed dataset| <img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" /> |
|folder|Local folder to sync. Wildcard selection is supported, for example: `~/data/*.jpg ~/data/json`|<img src="/icons/ico-optional-no.svg" className="icon size-md center-md" />|
|storage|Remote storage to use for the dataset files. Default: files_server |<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|parents|IDs of the dataset's parents (i.e. merge all parents). All modifications made to the folder since the parents were synced will be reflected in the dataset|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|project|If creating a new dataset, specify the dataset's project name|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|name|If creating a new dataset, specify the dataset's name|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|tags|Dataset user tags|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|skip-close|Do not auto close dataset after syncing folders|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|verbose | Verbose reporting |<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|

<br/>

#### List Dataset Content 
```bash
clearml-data list [--id <dataset_id>] 
```

**Parameters**

|Name|Description|Optional|
|---|---|---|
|id|Dataset ID whose contents will be shown (alternatively, use project / name combination). Default: previously accessed dataset|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|project|Specify dataset project name (if used instead of ID, dataset name is also required)|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|name|Specify dataset name (if used instead of ID, dataset project is also required)|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|filter|Filter files based on folder / wildcard. Multiple filters are supported. Example: `folder/date_*.json folder/sub-folder`|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|modified|Only list file changes (add / remove / modify) introduced in this version|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|

<br/>

####  Delete a Dataset
```
clearml-data delete [--id <dataset_id_to_delete>]
```  
Deletes an entire dataset from ClearML. This can also be used to delete a newly created dataset.

This does not work on datasets with children.

**Parameters**

|Name|Description|Optional|
|---|---|---|
|id|ID of dataset to be deleted. Default: previously created / accessed dataset that hasn't been finalized yet|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|force|Force dataset deletion even if other dataset versions depend on it|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />||

<br/>

#### Search for a Dataset
```
clearml-data search [--name <name>] [--project <project_name>] [--tags <tag>]
```  
Lists all datasets in the system that match the search request.

Datasets can be searched by project, name, ID, and tags.
   
**Parameters**

|Name|Description|Optional|
|---|---|---|
|ids|A list of dataset IDs|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|project|The project name of the datasets|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|name|A dataset name or a partial name to filter datasets by|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|tags|A list of dataset user tags|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|

<br/>

### Python API

All API commands should be imported with<br/>
`from clearml import Dataset`


#### `Dataset.get(dataset_id=DS_ID).get_local_copy()`  

Returns a path to dataset in cache, and downloads it if it is not already in cache.

**Parameters**

|Name|Description|Optional|
|---|---|---|
|use_soft_links|If True, use soft links. Default: False on Windows, True on Posix systems|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|raise_on_error|If True, raise exception if dataset merging failed on any file|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|

<br/>

#### `Dataset.get(dataset_id=DS_ID).get_mutable_local_copy()` 

Downloads the dataset to a specific folder (non-cached). If the folder already has contents, specify whether to overwrite 
its contents with the dataset contents.
  
**Parameters**

|Name|Description|Optional|
|---|---|---|
|target_folder|Local target folder for the writable copy of the dataset|<img src="/icons/ico-optional-no.svg" className="icon size-md center-md" />|
|overwrite|If True, recursively delete the contents of the target folder before creating a copy of the dataset. If False (default) and target folder contains files, raise exception or return None|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|raise_on_error|If True, raise exception if dataset merging failed on any file|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|

<br/>

#### `Dataset.create()`

Create a new dataset. 

Parent datasets can be specified, and the new dataset inherits all of its parent's content. Multiple dataset parents can 
be listed. Merging of parent datasets is done based on the list's order, where each parent can override overlapping files 
in the previous parent dataset.
  
**Parameters**

|Name|Description|Optional|
|---|---|---|
|dataset_name|Name of the new dataset|<img src="/icons/ico-optional-no.svg" className="icon size-md center-md" />|
|dataset_project|The project containing the dataset. If not specified, infer project name from parent datasets. If there is no parent dataset, then this value is required|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|parent_datasets|Expand a parent dataset by adding / removing files|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|use_current_task|If True, the dataset is created on the current Task. Default: False|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|

<br/>

#### `Dataset.add_files()` 
  
Add files or folder into the current dataset.

**Parameters**

|Name|Description|Optional|
|---|---|---|
|path|Add a folder / file to the dataset|<img src="/icons/ico-optional-no.svg" className="icon size-md center-md" />|
|wildcard|Add only a specific set of files based on wildcard matching. Wildcard matching can be a single string or a list of wildcards, for example: `~/data/*.jpg`, `~/data/json`|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|local_base_folder|Files will be located based on their relative path from local_base_folder|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|dataset_path|Where in the dataset the folder / files should be located|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|recursive|If True, match all wildcard files recursively|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|verbose| If True, print to console files added / modified|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|

<br/>

#### `Dataset.upload()`
Start file uploading, the function returns when all files are uploaded.
  
**Parameters**

|Name|Description|Optional|
|---|---|---|
|show_progress|If True, show upload progress bar|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|verbose|If True, print verbose progress report|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|output_url|Target storage for the compressed dataset (default: file server). Examples: `s3://bucket/data`, `gs://bucket/data` , `azure://bucket/data`, `/mnt/share/data` |<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|compression|Compression algorithm for the Zipped dataset file (default: ZIP_DEFLATED)|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|

<br/>

#### `Dataset.finalize()`
Closes the dataset and marks it as *Completed*. After a dataset has been closed, it can no longer be modified. 
Before closing a dataset, its files must first be uploaded.

**Parameters**

|Name|Description|Optional|
|---|---|---|
|verbose|If True, print verbose progress report|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|
|raise_on_error|If True, raise exception if dataset finalizing failed|<img src="/icons/ico-optional-yes.svg" className="icon size-md center-md" />|