DTLPY – SDK and CLI for Dataloop.ai
📚 Platform Documentation | 📖 SDK Documentation | Developer docs
An open-source SDK and CLI toolkit to interact seamlessly with the Dataloop.ai platform, providing powerful data management, annotation capabilities, and workflow automation.
Table of Contents
Overview
DTLPY provides a robust Python SDK and a powerful CLI, enabling developers and data scientists to automate tasks, manage datasets, annotations, and streamline workflows within the Dataloop platform.
Installation
Install DTLPY directly from PyPI using pip:
pip install dtlpy
Alternatively, for the latest development version, install directly from GitHub:
pip install git+https://github.com/dataloop-ai/dtlpy.git
Usage
SDK Usage
Here's a basic example to get started with the DTLPY SDK:
import dtlpy as dl
# Authenticate
dl.login()
# Access a project
project = dl.projects.get(project_name='your-project-name')
# Access dataset
dataset = project.datasets.get(dataset_name='your-dataset-name')
CLI Usage
DTLPY also provides a convenient command-line interface:
dlp login
dlp projects ls
dlp datasets ls --project-name your-project-name
Python Version Support
DTLPY supports multiple Python versions as follows:
| Python Version | 3.14 | 3.13 | 3.12 | 3.11 | 3.10 | 3.9 | 3.8 | 3.7 |
|---|---|---|---|---|---|---|---|---|
| dtlpy >= 1.118 | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ❌ | ❌ |
| dtlpy 1.99–1.117 | ❌ | ❌ | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ |
| dtlpy 1.76–1.98 | ❌ | ❌ | ❌ | ✅ | ✅ | ✅ | ✅ | ✅ |
| dtlpy >= 1.61 | ❌ | ❌ | ❌ | ❌ | ✅ | ✅ | ✅ | ✅ |
| dtlpy 1.50–1.60 | ❌ | ❌ | ❌ | ❌ | ❌ | ✅ | ✅ | ✅ |
Development
To set up the development environment, clone the repository and install dependencies:
git clone https://github.com/dataloop-ai/dtlpy.git
cd dtlpy
pip install -r requirements.txt
Resources
- Dataloop Platform
- Full SDK Documentation
- Platform Documentation
- SDK Examples and Tutorials
- Developer docs
Contribution Guidelines
We encourage contributions! Please ensure:
- Clear and descriptive commit messages
- Code follows existing formatting and conventions
- Comprehensive tests for new features or bug fixes
- Updates to documentation if relevant
Create pull requests for review. All contributions will be reviewed carefully and integrated accordingly.
Metadata
Release files for dtlpy 1.126.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| dtlpy-1.126.4.tar.gz | 519.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| dtlpy-1.126.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.2 MB
Release files / dtlpy-1.126.4.tar.gz
| Download URL | dtlpy-1.126.4.tar.gz |
|---|---|
| Size | 519.6 kB |
| Tags | Source |
|
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.10.21
|
Release files / dtlpy-1.126.4-py3-none-any.whl
| Download URL | dtlpy-1.126.4-py3-none-any.whl |
|---|---|
| Size | 632.3 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.10.21
|