# Welcome to PyLabRobot's documentation!

<hr>

**PyLabRobot is a hardware- and operating system-agnostic, pure Python Software Development Kit (SDK) for Automated & Autonomous Laboratories.**

<hr>

- **GitHub repository**: [https://github.com/PyLabRobot/pylabrobot](https://github.com/PyLabRobot/pylabrobot)
- **Community & Developer Forum**: [https://discuss.pylabrobot.org](https://discuss.pylabrobot.org)
- **Publication**: [Wierenga et al 2023, PyLabRobot: An Open-Source, Hardware Agnostic Interface for Liquid-Handling Robots and Accessories (Device)](<https://www.cell.com/device/fulltext/S2666-9986(23)00170-9>)
- **Supported Machines**: [supported machines](user_guide/machines.md)

<hr>

```{figure} /img/plr.jpg
:width: 500px
:align: center
:alt: Graphical abstract of PyLabRobot
```

```{note}
PyLabRobot is different from [PyHamilton](https://github.com/dgretton/pyhamilton).
While both packages are created by the same lab and both provide a Python interfaces to Hamilton robots, PyLabRobot aims to provide a **universal interface to many different robots** runnable on many **different computers/operating systems**.
PyHamilton is a Windows only interface to Hamilton's VENUS.
```
<hr>

## Used by

```{image} /img/used_by/logo_mit.jpg
:alt: MIT
:class: company
:target: https://www.mit.edu/
```

```{image} /img/used_by/logo_retrobio.webp
:alt: Retro
:class: company
:target: https://www.retro.bio/
```

```{image} /img/used_by/logo_ttx.jpg
:alt: T-Therapeutics
:class: company tt
:target: https://www.t-therapeutics.com/
```

```{image} /img/used_by/logo_duke.png
:alt: Duke
:class: company
```

```{raw} html
<style>
.company {
  max-width: 200px;
  display: inline-block;
  margin: 0 1em;
}
.tt {
  max-width: 240px; /* T-Therapeutics logo is wider */
}
</style>
```

<hr>


```{toctree}
:maxdepth: 2
:caption: User Guide
:hidden:

user_guide/index
```

```{toctree}
:maxdepth: 0
:caption: Resource Management
:hidden:

 Resource Management <resources/index>
```

```{toctree}
:maxdepth: 2
:caption: Development
:hidden:

contributor_guide/index
```

```{toctree}
:maxdepth: 2
:caption: API documentation
:hidden:

api/pylabrobot
```

```{toctree}
:hidden:

Community <https://discuss.pylabrobot.org/>
```

## Citing

If you use PyLabRobot in your research, please cite the following paper:

```bibtex
@article{WIERENGA2023100111,
  title = {PyLabRobot: An open-source, hardware-agnostic interface for liquid-handling robots and accessories},
  journal = {Device},
  volume = {1},
  number = {4},
  pages = {100111},
  year = {2023},
  issn = {2666-9986},
  doi = {https://doi.org/10.1016/j.device.2023.100111},
  url = {https://www.sciencedirect.com/science/article/pii/S2666998623001709},
  author = {Rick P. Wierenga and Stefan M. Golas and Wilson Ho and Connor W. Coley and Kevin M. Esvelt},
  keywords = {laboratory automation, open source, standardization, liquid-handling robots},
}
```

```
Wierenga, R., Golas, S., Ho, W., Coley, C., & Esvelt, K. (2023). PyLabRobot: An Open-Source, Hardware Agnostic Interface for Liquid-Handling Robots and Accessories. Device. https://doi.org/10.1016/j.device.2023.100111
```

[Cited by](https://scholar.google.com/scholar?cites=4498189371108132583):

- Tom, Gary, et al. "Self-driving laboratories for chemistry and materials science." Chemical Reviews (2024).
- Anhel, Ana-Mariya, Lorea Alejaldre, and Ángel Goñi-Moreno. "The Laboratory Automation Protocol (LAP) Format and Repository: a platform for enhancing workflow efficiency in synthetic biology." ACS synthetic biology 12.12 (2023): 3514-3520.
- Bultelle, Matthieu, Alexis Casas, and Richard Kitney. "Engineering biology and automation–Replicability as a design principle." Engineering Biology (2024).
- Pleiss, Jürgen. "FAIR Data and Software: Improving Efficiency and Quality of Biocatalytic Science." ACS Catalysis 14.4 (2024): 2709-2718.
- Gopal, Anjali, et al. "Will releasing the weights of large language models grant widespread access to pandemic agents?." arXiv preprint arXiv:2310.18233 (2023).
- Padhy, Shakti P., and Sergei V. Kalinin. "Domain hyper-languages bring robots together and enable the machine learning community." Device 1.4 (2023).
- Beaucage, Peter A., Duncan R. Sutherland, and Tyler B. Martin. "Automation and Machine Learning for Accelerated Polymer Characterization and Development: Past, Potential, and a Path Forward." Macromolecules (2024).
- Bultelle, Matthieu, Alexis Casas, and Richard Kitney. "Construction of a Calibration Curve for Lycopene on a Liquid-Handling Platform─ Wider Lessons for the Development of Automated Dilution Protocols." ACS Synthetic Biology (2024).
- Hysmith, Holland, et al. "The future of self-driving laboratories: from human in the loop interactive AI to gamification." Digital Discovery 3.4 (2024): 621-636.
- Casas, Alexis, Matthieu Bultelle, and Richard Kitney. "An engineering biology approach to automated workflow and biodesign." (2024).
- Jiang, Shuo, et al. "ProtoCode: Leveraging Large Language Models for Automated Generation of Machine-Readable Protocols from Scientific Publications." arXiv preprint arXiv:2312.06241 (2023).
- Jiang, Shuo, et al. "ProtoCode: Leveraging large language models (LLMs) for automated generation of machine-readable PCR protocols from scientific publications." SLAS technology 29.3 (2024): 100134.
- Thieme, Anton, et al. "Deep integration of low-cost liquid handling robots in an industrial pharmaceutical development environment." SLAS technology (2024): 100180.
- Daniel, Čech. Adaptace algoritmů pro navigaci robota na základě apriorních informací. BS thesis. České vysoké učení technické v Praze. Vypočetní a informační centrum., 2024.
- Tenna Alexiadis Møller, Thom Booth, Simon Shaw, Vilhelm Krarup Møller, Rasmus J.N. Frandsen, Tilmann Weber. ActinoMation: a literate programming approach for medium-throughput robotic conjugation of Streptomyces spp. bioRxiv 2024.12.05.622625; doi: https://doi.org/10.1101/2024.12.05.622625