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Siamang
Research-as-code framework for sociological surveys
Siamang offers a straightforward solution to the challenges of survey research by eliminating reliance on GUI builders, messy exports, and disconnected analysis scripts.
With Siamang, you can manage every aspect of your survey research within a single Python codebase. This includes defining your questionnaire, variables, labels, missing values, skip logic, quotas, deployment, data collection, and analysis.
Designed for sociologists, market researchers, UX researchers, data analysts, and anyone interested in making survey research version-controlled, testable, reusable, and transparent, Siamang streamlines the process for better efficiency.
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About Siamang on Product Hunt
“Research-as-code framework for sociological surveys”
Siamang was submitted on Product Hunt and earned 0 upvotes and 1 comments, placing #107 on the daily leaderboard. Research-as-code framework for sociological surveys — define, deploy, and analyze questionnaires in pure Python. - Siamang-Labs/siamang
Siamang was featured in User Experience (366.6k followers), Marketing (465.7k followers), SaaS (43k followers) and GitHub (41.3k followers) on Product Hunt. Together, these topics include over 181k products, making this a competitive space to launch in.
Who hunted Siamang?
Siamang was hunted by Alikhan Bazakov. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Siamang stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Alikhan Bazakov