# The ```senselab``` repo
[](https://github.com/sensein/senselab/actions/workflows/test.yaml?query=branch%3Amain)
[](https://codecov.io/gh/sensein/senselab)
[](https://github.com/astral-sh/ruff)
[](https://pypi.org/project/senselab/)
[](https://pypi.org/project/senselab)
[](https://opensource.org/licenses/Apache-2.0)
[](https://sensein.github.io/senselab)
Welcome to the ```senselab``` repo! This is a Python package for streamlining the processing and analysis of behavioral data, such as voice and speech patterns, with robust and reproducible methodologies.
**Caution:**: this package is still under development and may change rapidly over the next few weeks.
## Features
- **Modular design**: Utilize a variety of task-specific transformations that can be easily integrated or used standalone, allowing for flexible data manipulation and analysis strategies.
- **Pre-built pipelines**: Access pre-configured pipelines combining multiple transformations tailored for common analysis tasks, which help in reducing setup time and effort.
- **Reproducibility**: Ensures consistent outputs through the use of fixed seeds and version-controlled processing steps, making your results verifiable and easily comparable.
- **Easy integration**: Designed to fit into existing workflows with minimal configuration, `senselab` can be used alongside other data analysis tools and frameworks seamlessly.
- **Extensible**: Open to modifications and contributions, the package can be expanded with custom transformations and pipelines to meet specific research needs. <u>Do you want to contribute? Please, reach out!</u>
- **Comprehensive documentation**: Comes with detailed documentation for all features and modules, including examples and guides on how to extend the package for other types of behavioral data analysis.
- **Performance Optimized**: Efficiently processes large datasets with optimized code and algorithms, ensuring quick turnaround times even for complex analyses.
- **Interactive Examples**: Includes Jupyter notebooks that provide practical examples of how `senselab` can be implemented to derive insights from real-world data sets.
Whether you're researching speech disorders, analyzing customer service calls, or studying communication patterns, `senselab` provides the tools and flexibility needed to extract meaningful conclusions from your data.
## Installation
Install this package via:
```sh
pip install senselab
```
Or get the newest development version via:
```sh
pip install git+https://github.com/sensein/senselab.git
```
## Quick start
```Python
from senselab.app import hello_world
hello_world()
```
## Contributing
Please see [CONTRIBUTING.md](CONTRIBUTING.md) before contributing.
## To do
Please see the [Project Board](https://github.com/orgs/sensein/projects/45).
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"description": "# The ```senselab``` repo\n\n[](https://github.com/sensein/senselab/actions/workflows/test.yaml?query=branch%3Amain)\n[](https://codecov.io/gh/sensein/senselab)\n[](https://github.com/astral-sh/ruff)\n\n[](https://pypi.org/project/senselab/)\n[](https://pypi.org/project/senselab)\n[](https://opensource.org/licenses/Apache-2.0)\n\n[](https://sensein.github.io/senselab)\n\nWelcome to the ```senselab``` repo! This is a Python package for streamlining the processing and analysis of behavioral data, such as voice and speech patterns, with robust and reproducible methodologies.\n\n**Caution:**: this package is still under development and may change rapidly over the next few weeks.\n\n## Features\n- **Modular design**: Utilize a variety of task-specific transformations that can be easily integrated or used standalone, allowing for flexible data manipulation and analysis strategies.\n\n- **Pre-built pipelines**: Access pre-configured pipelines combining multiple transformations tailored for common analysis tasks, which help in reducing setup time and effort.\n\n- **Reproducibility**: Ensures consistent outputs through the use of fixed seeds and version-controlled processing steps, making your results verifiable and easily comparable.\n\n- **Easy integration**: Designed to fit into existing workflows with minimal configuration, `senselab` can be used alongside other data analysis tools and frameworks seamlessly.\n\n- **Extensible**: Open to modifications and contributions, the package can be expanded with custom transformations and pipelines to meet specific research needs. <u>Do you want to contribute? Please, reach out!</u>\n\n- **Comprehensive documentation**: Comes with detailed documentation for all features and modules, including examples and guides on how to extend the package for other types of behavioral data analysis.\n\n- **Performance Optimized**: Efficiently processes large datasets with optimized code and algorithms, ensuring quick turnaround times even for complex analyses.\n\n- **Interactive Examples**: Includes Jupyter notebooks that provide practical examples of how `senselab` can be implemented to derive insights from real-world data sets.\n\nWhether you're researching speech disorders, analyzing customer service calls, or studying communication patterns, `senselab` provides the tools and flexibility needed to extract meaningful conclusions from your data.\n\n\n## Installation\nInstall this package via:\n\n```sh\npip install senselab\n```\n\nOr get the newest development version via:\n\n```sh\npip install git+https://github.com/sensein/senselab.git\n```\n\n## Quick start\n```Python\nfrom senselab.app import hello_world\n\nhello_world()\n```\n\n## Contributing\nPlease see [CONTRIBUTING.md](CONTRIBUTING.md) before contributing.\n\n## To do\nPlease see the [Project Board](https://github.com/orgs/sensein/projects/45).\n",
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