Django for life (sciences)
summary
Shows three concrete projects: an invasive-species daily email alert system that pulls from GBIF, a weather-radar pipeline that aggregates networks to produce continent-scale bird migration maps (peaks show fireworks on Jan 1), and a Belgian butterfly catalogue built with Django admin. Uses PostGIS for thousands of geo points, GitHub Actions for CI, and prioritizes small dependency sets, quick prototypes and plain Python over heavy JS stacks. Argues these survive one-time funding and decades of low-maintenance use.
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chapters (21)
- 0:00Introduction and speaker
- 1:10Biodiversity crisis and software role
- 2:58Bird migration visualization project
- 6:14Tracking invasive species alerts
- 7:19Unique challenges in biodiversity software
- 9:07Open science and funding issues
- 11:14Why Django excels for these projects
- 13:25Balancing speed and stability
- 15:12Admin interface as a productivity tool
- 17:41Python’s explicitness and maintainability
- 18:44PostGIS and geographic data
- 20:11Conservative dependency management
- 21:34Avoiding over-engineering tools
- 23:01Alternatives to SPAs and React
- 24:42Cloud vs Unix skills for longevity
- 25:28Avoiding isolation in solo work
- 26:52Public code and collaboration
- 28:17Writing boring explicit code
- 29:01Testing philosophy and time
- 29:23GeoDjango limitations and admin improvements
- 30:05Easier Django project deployment
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