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Languages & runtimes · #python
Learn how AlmaLinux’s dnf module streams let you install and switch between different versions of the same software, such as Python 3.9 and 3.11, without package conflicts.
Implement Dijkstra’s algorithm in Python using heapq: understand the O((V+E) log V) complexity, handle non‑negative edge weights, and learn practical trade‑offs for sparse graphs. Includes a worked example and testing tips.
Learn how to mount Google Drive in Google Colab to persist datasets and model weights across sessions, including implementation code and performance tips.
Move Flask app creation into a factory function to enable multiple configurations, cleaner testing, and a project structure that grows without circular imports.
Learn how to use Streamlit’s st.cache_data decorator to avoid re‑loading large datasets on every interaction, with a concrete CSV‑loading example, version notes, and cache‑staleness mitigation.
Hand-tuning subplot margins in Matplotlib is a guess-and-check loop you can skip. tight_layout() measures your labels and computes spacing automatically — here's how to use it, tune it, and recognize its limits.
Learn when to use SVG vs WebGL rendering in Plotly. This guide covers performance thresholds, implementation via render_mode, and how to diagnose rendering bottlenecks.
Offset pagination breaks on live Facebook data. Here's how cursor-based pagination in the Graph API keeps results consistent, with a working Python loop and the rate-limit traps to avoid.
Learn how to identify and resolve N+1 query patterns in Django using select_related and prefetch_related to reduce database load and improve page response times.
googlecolab
streamlit
matplotlib
plotly
facebook
django