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@samplics-org

svy

samplics-org
United States of America

Sponsor svy

svy is the open-source Python ecosystem for complex survey design, weighting, estimation, and small area estimation.

While Python is the standard language for data science, it has historically lacked the rigorous tooling required for survey methodology. svy closes that gap.

svy is built for practitioners working with real survey data — in public health, national statistics, development, and applied research — where correct inference matters.

Why Sponsor svy?

Survey statistics inform funding decisions, policy design, and public health action.
Incorrect variance estimates or modeling shortcuts are not acceptable.

Your sponsorship helps ensure that svy remains:

  • Statistically correct
  • Transparent and inspectable
  • Production-ready
  • Sustainable over the long term

This project prioritizes trust over hype.

What Your Sponsorship Supports

Validation & Correctness

  • Rigorous benchmarking against reference implementations
    (R survey, Stata)
  • Reproducible validation notebooks
  • Public consistency and correctness reports

Goal: svy results can be trusted in research, policy, and production.

Maintenance & Stability

  • Long-term support for modern Python versions
  • Compatibility with evolving ecosystems (NumPy, Polars, SciPy, JAX)
  • Careful deprecation and API stability

Goal: svy remains reliable as Python evolves.

Documentation & Learning

  • Clear guides for complex survey workflows
  • Applied examples (health, NSOs, development programs)
  • Theory notes bridging statistics and implementation

Goal: lower the barrier to correct survey analysis in Python.

Small Area Estimation (svy-sae)

  • Stabilization of SAE APIs
  • Diagnostics, benchmarking, and calibration workflows
  • Production-grade uncertainty reporting

Goal: bring state-of-the-art SAE into modern Python pipelines.

Who Should Sponsor?

  • Survey statisticians and methodologists
  • Opinion polling and social research organizations
  • Public health and development researchers
  • National statistical offices
  • Data scientists working with complex samples
  • Media, policy, and civic analytics teams
  • Organizations relying on survey-based evidence

If you rely on survey data, svy is built for you.

Project Philosophy

Statistical rigor should survive contact with reality.

No hidden assumptions.
No silent shortcuts.
No black-box inference.

About the Maintainer

svy is led and maintained by Mamadou S. Diallo, statistician and data scientist with extensive experience in:

  • Complex survey design and analysis
  • Public health and development statistics
  • Production data systems and open-source software

svy builds on decades of survey methodology research and modern software engineering practices.

Links

Thank you for supporting correct, transparent, and sustainable survey statistics in Python.

2 sponsors have funded samplics-org’s work.

@samplics-org

This is a longer-term milestone. Reaching 10 sponsors would allow me to dedicate consistent time to validation against reference standards, long-term maintenance, and documentation—ensuring svy remains a reliable foundation for survey analysis and opinion polling in Python.

Private Sponsor
Private Sponsor

Meet the team

Featured work

  1. samplics-org/svy

    Modern Python ecosystem for complex survey design, weighting, estimation, and small area estimation.

    Rust 8

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Select a tier

$ a month

You'll receive any rewards listed in the $5 monthly tier. Additionally, a Public Sponsor achievement will be added to your profile.

$5 a month

Select

🌱 Supporter — $5 / month

For individual users, students, and supporters

Your support helps:

  • Keep svy free and open-source
  • Maintain compatibility with modern Python versions
  • Fix bugs and improve reliability

Benefits:

  • Optional name listed in the Sponsors section
  • Early visibility into roadmap updates
  • Sponsor-only notes on design decisions and internals

This tier is about sustaining the project and signaling support for rigorous survey statistics in Python.

$15 a month

Select

📊 Practitioner — $15 / month

For researchers and practitioners actively using svy

Your support helps:

  • Validation against reference standards (R survey, Stata svy)
  • Numerical accuracy and performance benchmarking
  • Improving documentation with real-world examples

Benefits:

  • Priority consideration for bug reports
  • Early access to validation and comparison notes
  • Optional sponsor acknowledgment in documentation

This tier supports correctness, reproducibility, and trust in results.

$50 a month

Select

🧪 Methodology Backer — $50 / month

For methodologists, teams, and institutions

Your support helps:

  • Development of advanced estimators and variance methods
  • Small Area Estimation workflows
  • Long-term API stability and architectural decisions

Benefits:

  • Input on roadmap priorities
  • Acknowledgment in releases and major documentation
  • Optional logo or name listed in a “Supported by” section

This tier directly supports the long-term scientific integrity of the ecosystem.