SShortSingh.
Back to feed

Overusing useState Is Slowing Your React Apps, Developers Warned

0
·8 views

A developer guide published on DEV Community highlights a common React anti-pattern where too many component values are stored in useState, causing unnecessary re-renders. The article identifies three main culprits: derived values that should be computed with useMemo, values only used in event handlers that belong in a useRef, and form fields that rarely need to be controlled inputs. The author argues that useState should only hold values React genuinely needs to track for rendering, not every variable in a component. Alternatives like useRef, closure variables, and reading form data on submit are recommended for cases where re-renders add no benefit. The core takeaway is that avoiding unnecessary state is a more effective performance strategy than memoizing expensive renders after the fact.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Log in to join the discussion and vote.

Log in

Related stories

0
ProgrammingDEV Community ·

Developer argues deterministic code, not LLMs, should drive AI observability decisions

A developer running a managed monitoring service found that letting large language models classify and judge infrastructure alerts produced inconsistent, unreliable results — with the same alert generating different root-cause categories across multiple runs. To fix this, they redesigned the pipeline so that deterministic Python code handles all classification, validation, and aggregation, while the LLM is restricted solely to narrating the outcome in plain English. The approach also incorporates a pre-call metrics lookup to give the model historical baseline context, preventing misleading narratives such as false disk-fill urgency on a stable host. The author notes this design keeps aggregation reliable, prevents hallucinated classifications, and ensures the monitoring pipeline remains functional even if the model fails. The system runs intentionally on modest CPU-only hardware with no GPU, reflecting a deliberate choice to keep all data on-premise rather than sending it to external services.

0
ProgrammingDEV Community ·

How Stream Analyzers Help Broadcast Engineers Diagnose and Fix Live TV Issues

Digital TV broadcasters rely on stream analysis tools to diagnose and resolve technical faults before they affect viewers. A common problem involves legacy set-top boxes failing to play streams correctly due to GOP structure issues, particularly excessive B-frame counts in H.264 video. Engineers use file-based analyzers to inspect frame-by-frame structure, detect standard violations, and identify buffer overflow conditions at precise points in a stream. Tools like Elecard StreamEye allow technicians to visualize bitrate fluctuations, confirm whether a stream is truly constant bitrate, and test compatibility with older hardware before going live. This diagnostic workflow — capturing a problematic stream and examining it offline — serves as a core quality-control practice in professional broadcast operations.

0
ProgrammingDEV Community ·

No, ChatGPT Cannot Predict Stocks: What LLMs Actually Do Explained

A viral YouTube ad has been selling a ₹199 'secret prompt' claiming ChatGPT and Claude can predict stock trades with 90% accuracy, requiring no technical or fundamental analysis. Experts and educators warn this is misleading, as large language models like ChatGPT, Claude, and Gemini are fundamentally next-word prediction systems trained on text patterns — not financial or mathematical forecasting engines. While some specialized AI models can perform numerical stock trend analysis, general-purpose LLMs are architecturally unsuited for that task. The confusion largely stems from users and sellers treating these models as all-purpose 'magic black boxes' without understanding how they actually process information. Such misconceptions, whether deliberate or not, can lead retail investors to make poorly informed financial decisions.