Security News
PyPI’s New Archival Feature Closes a Major Security Gap
PyPI now allows maintainers to archive projects, improving security and helping users make informed decisions about their dependencies.
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. Results are formatted as specified datasets and come with built-in methods for analyzing, visualizing, and sharing.
A quick example:
# Import a question type
from edsl import QuestionMultipleChoice
# Construct a question using the question type template
q = QuestionMultipleChoice(
question_name="example_question",
question_text="How do you feel today?",
question_options=["Bad", "OK", "Good"]
)
# Run it with the default language model
results = q.run()
# Inspect the results
results.select("example_question")
Output:
┏━━━━━━━━━━━━━━━━━━━━━━━━━┓
┃ answer.example_question ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━┩
│ Good │
└─────────────────────────┘
.env
file.
See instructions on storing API keys and activating remote inference.Interested in contributing? Want us to add a new feature? Found a bug for us to squash? Please send us an email at info@expectedparrot.com or message us at our Discord channel..
FAQs
Create and analyze LLM-based surveys
We found that edsl demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 5 open source maintainers collaborating on the project.
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Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
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PyPI now allows maintainers to archive projects, improving security and helping users make informed decisions about their dependencies.
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