Public information is often technically available but practically inaccessible. In many civic contexts, important data is fragmented, difficult to interpret, or published in formats that make it hard for citizens, journalists, and community actors to use effectively. This weakens transparency, limits participation, and reduces public accountability. In this talk, I will show how Python can be used to build civic tech systems that make public information more accessible, understandable, and actionable. Drawing from real-world public-interest technology work, I will explore how APIs, structured data, backend services, and lightweight user-facing tools can be combined to turn complex civic information into practical digital products. The session will cover key technical patterns behind these systems, including data collection and cleaning, API design, backend logic, and building simple services around messy or incomplete public datasets. I will also share practical lessons from working in real-world contexts, such as designing for accessibility, working within local constraints, and prioritizing usefulness over technical complexity. This talk is for Python developers who want to see how their existing skills can be applied beyond conventional product development. Attendees will leave with a clearer understanding of how Python supports civic technology and with practical ideas for building tools that strengthen transparency, accountability, and public good.