Choosing the Right Python Backend Framework for Your Needs

Logs shouldn't just be strings - they should be structured data. I wrote a piece on why Structlog is a game-changer for Python developers, especially those working with FastAPI and distributed tracing. In the post: 👉 Traditional vs. Structured approach. 👉 Production-grade setups. 👉 Why "Event Logging" scales better. Read more here: https://lnkd.in/dFBrMnuM #Coding #Python #ProgrammingTips #TechBlog

oday I explored how backend works and understood how Python connects logic with real-world applications. ✔️ Revised core concepts ✔️ Learned about how servers handle requests ✔️ Strengthened my understanding of problem-solving Slowly moving from just writing code ➝ to understanding how systems actually work. Consistency + Curiosity = Growth 💡 #Python #BackendDevelopment #LearningInPublic #TechJourney 

Day by day. Concept by concept. 💙 Today’s focus: Python Data Types Before writing complex programs, understand how Python stores data. Single value or multiple values — choosing the right type matters! Small concepts → Big confidence 📈 What topic should I post next? 👇 #Python #PythonProgramming #LearnPython #Developers #CodingJourney

Python is great for scripting, but for the heavy lifting, we drop to Rust. We use PyO3 to wrap high-performance Rust kernels directly into our Python trading stack. This allows us to maintain the flexibility of Python for strategy logic while executing the compute-heavy Monte Carlo paths in parallel, GIL-free Rust. Key Implementation Details: • #[pyfunction]: Exposes the Rust function to Python. Just import rust_engine and call it like a native function. • Rayon: Replaces Python's multiprocessing with work-stealing parallelism. The into_par_iter() call automatically distributes the 1M+ paths across all CPU cores. • Type Safety: Rust's compiler guarantees memory safety and thread safety at compile time, eliminating a class of runtime errors common in C++ extensions. Stop optimizing Python loops. Rewrite the bottleneck. #RustLang #QuantitativeTrading #HighFrequencyTrading #Python #SystemArchitecture #RemoveEmotionFromTrading

We'll use st.cache_resource along with another technique to prevent logs from duplicating and eating resources. https://lnkd.in/eHCguX-z #python #streamlit #crossfit #tutorial #datascience #softwaredevelopment #software #fastapi #contextmanager #logging

Two small Python features now supported in Memphis: semicolon separators crossed with single-line blocks. Can't say I've ever written code like this! But it works. https://lnkd.in/e5KmEuZZ

Most Python code I see still counts things manually. Something like this: counts = {} for item in data: counts[item] = counts.get(item, 0) + 1 It works. But Python has had a built-in solution for years: from collections import Counter counts = Counter(data) Cleaner code is nice. But the real advantage is clarity of intent. When someone reads Counter(data), they don’t have to figure out what the code is doing. They immediately know why it exists. Small differences like this scale more than people realize. #Python #DataAnalytics

🔍 Set vs Dictionary in Python — Think Like an Engineer Both use hashing. Both offer average O(1) lookup. But they solve different problems. 🔹 Set → When uniqueness matters. Perfect for tracking unique users, emails, IDs, or attendance. 🔹 Dictionary → When relationships matter. #Python #SoftwareEngineering #DataStructures #DeveloperMindset 🚀

"We'll prototype in Python and then rewrite it in C++." Famous last words. This classic promise often creates a synchronization hell. The research team iterates on the Python prototype for months, adding features and changing logic. By the time the quant dev team starts the "rewrite," it's a moving target. The strategy isn't inherently wrong, but without strict API contracts, shared test suites, and paired programming, you build two different models. The key is to design the Python prototype as if it were the C++ kernel from day one. Has a "rewrite later" strategy ever backfired on you? What was the lesson? #QuantFinance #QuantDev #SoftwareEngineering #Prototyping #KernelDevelopment #FinancialEngineering

I'm going to use a python feature called a context manager combined with a logger to help us to find potential bottlenecks in our application. https://lnkd.in/eMmHq9xY #python #streamlit #crossfit #tutorial #datascience #softwaredevelopment #software #fastapi #contextmanager #logging