Metadata-Version: 2.1
Name: edsl
Version: 0.1.17.dev1
Summary: Create and analyze LLM-based surveys
Home-page: https://www.expectedparrot.com/
License: MIT
Keywords: LLM,social science,surveys,user research
Author: Apostolos Filippas
Author-email: apostolos@expectedparrot.com
Requires-Python: >=3.9.1,<3.12
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Software Development :: Libraries :: Application Frameworks
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Dist: aiohttp (>=3.9.1,<4.0.0)
Requires-Dist: anthropic (>=0.23.1,<0.24.0)
Requires-Dist: jinja2 (>=3.1.2,<4.0.0)
Requires-Dist: jupyter (>=1.0.0,<2.0.0)
Requires-Dist: markdown2 (>=2.4.11,<3.0.0)
Requires-Dist: matplotlib (>=3.8.4,<4.0.0)
Requires-Dist: nbsphinx (>=0.9.3,<0.10.0)
Requires-Dist: nest-asyncio (>=1.5.9,<2.0.0)
Requires-Dist: numpy (>=1.22,<2.0)
Requires-Dist: openai (>=1.4.0,<2.0.0)
Requires-Dist: pandas (>=2.1.4,<3.0.0)
Requires-Dist: pydot (>=2.0.0,<3.0.0)
Requires-Dist: pygments (>=2.17.2,<3.0.0)
Requires-Dist: pytest-asyncio (>=0.23.5,<0.24.0)
Requires-Dist: pytest-mock (>=3.12.0,<4.0.0)
Requires-Dist: python-docx (>=1.1.0,<2.0.0)
Requires-Dist: python-dotenv (>=1.0.0,<2.0.0)
Requires-Dist: rich (>=13.7.0,<14.0.0)
Requires-Dist: simpleeval (>=0.9.13,<0.10.0)
Requires-Dist: sqlalchemy (>=2.0.23,<3.0.0)
Requires-Dist: tenacity (>=8.2.3,<9.0.0)
Project-URL: Documentation, https://www.expectedparrot.com/getting-started/
Description-Content-Type: text/markdown

# Expected Parrot Domain-Specific Language 
<p align="center">
  <img src="https://github.com/expectedparrot/edsl/blob/main/static/logo.png?raw=true" alt="edsl.png" width="100"/>
</p>

The Expected Parrot Domain-Specific Language (EDSL) package lets you conduct computational social science and market research with AI. Use it to design surveys and experiments, simulate responses with large language models, and perform data labeling and other research tasks. EDSL comes with built-in methods for analyzing, visualizing and sharing your results. 

## 🔗 Links
- PyPI: https://pypi.org/project/edsl/
- Documentation: https://docs.expectedparrot.com
- Getting started: https://www.expectedparrot.com/getting-started/
- Discord: https://discord.com/invite/mxAYkjfy9m


## 💡 Contributions, Feature Requests & Bugs
Interested in contributing? Want us to add a new feature? Found a nasty bug that you would like us to squash? Please send us an email at info@expectedparrot.com or message us at our Discord server.


## 💻 Getting started
EDSL is compatible with Python 3.9 - 3.11.
```
pip install edsl
```

See https://www.expectedparrot.com/getting-started/ for examples and tutorials.
Read the docs at http://docs.expectedparrot.com.

## 🔧 Dependencies
API keys for LLMs that you want to use, stored in a `.env` file

