---
title: Data Management Example
---
In this example we'll create a simple dataset and demonstrate basic actions on it.
## Prerequisites
First, make sure that you have cloned the [clearml](https://github.com/allegroai/clearml) repository. This contains all
the needed files.
1. Open terminal and change directory to the cloned repository's examples folder
`cd clearml/examples/reporting`
## Creating Initial Dataset
1. To create the dataset, run this code:
```bash
clearml-data create --project datasets --name HelloDataset
```
Expected response:
```bash
clearml-data - Dataset Management & Versioning CLI
Creating a new dataset:
New dataset created id=24d05040f3e14fbfbed8edb1bf08a88c
```
1. Now let's add a folder. File addition is recursive, so it's enough to point at the folder
to captures all files and subfolders:
```bash
clearml-data add --files data_samples
```
Expected response:
```bash
clearml-data - Dataset Management & Versioning CLI
Adding files/folder to dataset id 24d05040f3e14fbfbed8edb1bf08a88c
Generating SHA2 hash for 2 files
Hash generation completed
5 files added
```
:::note
After creating a dataset, we don't have to specify its ID when running commands, such as *add*, *remove* or *list*
:::
1. Close the dataset - this command uploads the files. By default, the files are uploaded to the file server, but
this can be configured with the `--storage` flag to any of ClearML's supported storage mediums (see [storage](../../integrations/storage.md)).
The command also finalizes the dataset, making it immutable and ready to be consumed.
```bash
clearml-data close
```
Expected response:
```bash
clearml-data - Dataset Management & Versioning CLI
Finalizing dataset id 24d05040f3e14fbfbed8edb1bf08a88c
Pending uploads, starting dataset upload to https://files.community-master.hosted.allegro.ai
Pending uploads, starting dataset upload to https://files.community.clear.ml
Uploading compressed dataset changes (4 files, total 221.56 KB) to https://files.community.clear.ml
Upload completed (221.56 KB)
2021-05-04 09:32:03,388 - clearml.Task - INFO - Waiting to finish uploads
2021-05-04 09:32:04,067 - clearml.Task - INFO - Finished uploading
Dataset closed and finalized
```
## Listing Dataset Content
To see that all the files were added to the created dataset, use `clearml-data list` and enter the ID of the dataset
that was just closed.
```bash
clearml-data list --id 24d05040f3e14fbfbed8edb1bf08a88c
```
Expected response:
```console
clearml-data - Dataset Management & Versioning CLI
List dataset content: 24d05040f3e14fbfbed8edb1bf08a88c
Listing dataset content
file name | size | hash
------------------------------------------------------------------------------------------------------------------------------------------------
dancing.jpg | 40,484 | 78e804c0c1d54da8d67e9d072c1eec514b91f4d1f296cdf9bf16d6e54d63116a
data.csv | 21,440 | b618696f57b822cd2e9b92564a52b3cc93a2206f41df3f022956bb6cfe4e7ad5
picasso.jpg | 114,573 | 6b3c67ea9ec82b09bd7520dd09dad2f1176347d740fd2042c88720e780691a7c
sample.json | 132 | 9c42a9a978ac7a71873ebd5c65985e613cfaaff1c98f655af0d2ee0246502fd7
sample.mp3 | 72,142 | fbb756ae14005420ff00ccdaff99416bebfcea3adb7e30963a69e68e9fbe361b
Total 5 files, 248771 bytes
```
## Creating a Child Dataset
In Clear Data, it's possible to create datasets that inherit the content of other datasets, there are called child datasets.
1. Create a new dataset, specifying the previously created one as its parent:
```bash
clearml-data create --project datasets --name HelloDataset-improved --parents 24d05040f3e14fbfbed8edb1bf08a88c
```
:::note
You'll need to input the Dataset ID you received when created the dataset above
:::
1. Now, we want to add a new file.
* Create a new file: `echo "data data data" > new_data.txt` (this will create the file `new_data.txt`),
* Now add the file to the dataset:
```bash
clearml-data add --files new_data.txt
```
Which should return this output:
```console
clearml-data - Dataset Management & Versioning CLI
Adding files/folder to dataset id 8b68686a4af040d081027ba3cf6bbca6
1 file added
```
1. Let's also remove a file. We'll need to specify the file's full path (within the dataset, not locally) to remove it.
```bash
clearml-data remove --files data_samples/dancing.jpg
```
Expected response:
```bash
clearml-data - Dataset Management & Versioning CLI
Removing files/folder from dataset id 8b68686a4af040d081027ba3cf6bbca6
1 files removed
```
1. Close and finalize the dataset
```bash
clearml-data close
```
1. Let's take a look again at the files in the dataset:
```
clearml-data list --id 8b68686a4af040d081027ba3cf6bbca6
```
And we see that our changes have been made! `new_data.txt` has been added, and `dancing.jpg` has been removed.
```
file name | size | hash
------------------------------------------------------------------------------------------------------------------------------------------------
data.csv | 21,440 | b618696f57b822cd2e9b92564a52b3cc93a2206f41df3f022956bb6cfe4e7ad5
new_data.txt | 15 | 6df986a2154902260a836febc5a32543f5337eac60560c57db99257a7e012051
picasso.jpg | 114,573 | 6b3c67ea9ec82b09bd7520dd09dad2f1176347d740fd2042c88720e780691a7c
sample.json | 132 | 9c42a9a978ac7a71873ebd5c65985e613cfaaff1c98f655af0d2ee0246502fd7
sample.mp3 | 72,142 | fbb756ae14005420ff00ccdaff99416bebfcea3adb7e30963a69e68e9fbe361b
Total 5 files, 208302 bytes
```
By using `clearml-data`, a clear lineage is created for the data. As seen in this example, when a dataset is closed, the
only way to add or remove data is to create a new dataset, and using the previous dataset as a parent. This way, the data
is not reliant on the code and is reproducible.