Astrology-Based Date Explorer

Inspiration

Choosing when to start a new venture is a meaningful decision. This project explores how a traditional astrological timing method can be translated into explicit, reproducible computational rules rather than vague recommendations.

The goal was to build a working proof of concept that explains why a particular date meets predefined conditions.

What it does

Astrology-Based Date Explorer is a functional web prototype that evaluates calendar dates for starting a business venture.

It uses a fixed, fictional natal chart and real astronomical calculations from Swiss Ephemeris. Users can select a date range of up to 30 days and explore dates that meet either favorable or unfavorable conditions defined by the prototype.

A date qualifies only when the applicable conditions remain satisfied throughout the entire local calendar day.

The application presents matching dates with explanations. It does not rank dates, use prerecorded results, or claim to predict business success.

How we built it

We used an AI-assisted development workflow to turn the initial concept into a structured product scope, requirements document, technical specification, implementation, and verification process.

The application was developed with Python, FastAPI, and Swiss Ephemeris, with a browser-based interface.

The calculation engine evaluates astronomical positions and relevant transitions within the requested period. The interface communicates the results in accessible language.

AI supported the planning, implementation, debugging, and testing process. The astronomical results themselves are computed by deterministic software, not generated by a language model.

Challenges we faced

The main challenge was ensuring that a condition remained valid throughout an entire day rather than checking only one instant.

We also had to handle transitions near calculation boundaries, numerical uncertainty, historical time-zone interpretation, and reproducibility.

To keep the demonstration technically honest, unresolved numerical ambiguity produces a technical error rather than a potentially misleading recommendation.

Accomplishments

• Built a functional, interactive proof of concept.
• Integrated real Swiss Ephemeris calculations.
• Implemented full-day condition checking.
• Added explanations for matching dates.
• Completed 46 automated tests.
• Verified reproducibility across the supported 61-day evaluation domain.
• Prepared a reproducible installation procedure and published the source code with open-source licensing information.

What we learned

AI-assisted development works best when requirements, assumptions, limitations, and verification criteria are made explicit.

We also learned that a convincing demonstration does not need to pretend to be a finished commercial product. A smaller, testable implementation can communicate an idea more effectively.

What's next

Future work could include user-provided birth data, additional activity categories, broader date ranges, more extensive numerical verification, and clearer multilingual explanations.

This version remains a limited educational and technical proof of concept, not a validated predictive system or a substitute for practical business judgment.

Built With

• codex
• css
• ephemeris
• fastapi
• github
• html
• javascript
• openai
• python
• swiss