| Name | wandb JSON |
| Version |
0.19.7
JSON |
| download |
| home_page | None |
| Summary | A CLI and library for interacting with the Weights & Biases API. |
| upload_time | 2025-02-21 01:40:59 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | MIT License
Copyright (c) 2021 Weights and Biases, Inc.
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE. |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
<div align="center">
<img src="https://i.imgur.com/RUtiVzH.png" width="600" /><br><br>
</div>
# Weights and Biases [](https://pypi.python.org/pypi/wandb) [](https://anaconda.org/conda-forge/wandb) [](https://circleci.com/gh/wandb/wandb) [](https://codecov.io/gh/wandb/wandb)
Use W&B to build better models faster. Track and visualize all the pieces of your machine learning pipeline, from datasets to production machine learning models. Get started with W&B today, [sign up for an account!](https://wandb.com?utm_source=github&utm_medium=code&utm_campaign=wandb&utm_content=readme)
See the [W&B Developer Guide](https://docs.wandb.ai/?utm_source=github&utm_medium=code&utm_campaign=wandb&utm_content=documentation) and [API Reference Guide](https://docs.wandb.ai/ref?utm_source=github&utm_medium=code&utm_campaign=wandb&utm_content=documentation) for a full technical description of the W&B platform.
# Quickstart
Get started with W&B in four steps:
1. First, sign up for a [W&B account](https://wandb.ai/login?utm_source=github&utm_medium=code&utm_campaign=wandb&utm_content=quickstart).
2. Second, install the W&B SDK with [pip](https://pip.pypa.io/en/stable/). Navigate to your terminal and type the following command:
```shell
pip install wandb
```
3. Third, log into W&B:
```python
wandb.login()
```
4. Use the example code snippet below as a template to integrate W&B to your Python script:
```python
import wandb
# Start a W&B Run with wandb.init
run = wandb.init(project="my_first_project")
# Save model inputs and hyperparameters in a wandb.config object
config = run.config
config.learning_rate = 0.01
# Model training code here ...
# Log metrics over time to visualize performance with wandb.log
for i in range(10):
run.log({"loss": ...})
# Mark the run as finished, and finish uploading all data
run.finish()
```
For example, if the preceding code was stored in a script called train.py:
```shell
python train.py
```
You will see a URL in your terminal logs when your script starts and finishes. Data is staged locally in a directory named _wandb_ relative to your script. Navigate to the W&B App to view a dashboard of your first W&B Experiment. Use the W&B App to compare multiple experiments in a unified place, dive into the results of a single run, and much more!
# Integrations
Use your favorite framework with W&B. W&B integrations make it fast and easy to set up experiment tracking and data versioning inside existing projects. For more information on how to integrate W&B with the framework of your choice, see [W&B Integrations](https://docs.wandb.ai/guides/integrations) in the W&B Developer Guide.
# Python Version Support
We are committed to supporting our minimum required Python version for *at least* six months after its official end-of-life (EOL) date, as defined by the Python Software Foundation. You can find a list of Python EOL dates [here](https://devguide.python.org/versions/).
When we discontinue support for a Python version, we will increment the library’s minor version number to reflect this change.
# Contribution guidelines
Weights & Biases ❤️ open source, and we welcome contributions from the community! See the [Contribution guide](https://github.com/wandb/wandb/blob/main/CONTRIBUTING.md) for more information on the development workflow and the internals of the wandb library. For wandb bugs and feature requests, visit [GitHub Issues](https://github.com/wandb/wandb/issues) or contact support@wandb.com.
# Academic Researchers
Reach out to W&B Support at support@wandb.com to get a [free academic license](https://www.wandb.com/academic) for you and your research group.
# W&B Community
Be a part of the growing W&B Community and interact with the W&B team in our [Discord](https://wandb.me/discord). Stay connected with the latest ML updates and tutorials with [W&B Fully Connected](https://wandb.ai/fully-connected).
# License
[MIT License](https://github.com/wandb/wandb/blob/main/LICENSE)
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