Python Performance Optimization
Profile and optimize Python code — cProfile, memory profilers, line profiling, call graphs, and proven optimization strategies
- What
- Profile and optimize Python code — cProfile, memory profilers, line profiling, call graphs, and proven optimization strategies
- Cost
- Free
- Needs
- Python installed; cProfile ships with the standard library — memory profilers installed as needed
- Install
- Copy the installer prompt below into your Muse — your agent does the rest.
Curated by Skill Harbor — a comprehensive guide to profiling, analyzing, and optimizing Python code: CPU profiling, memory profiling, line-by-line granularity, and call-graph visualization, plus the core metrics (execution time, memory usage, CPU utilization, I/O wait). Covers when to use it — slow code, latency reduction, CPU-intensive operations, memory leaks, database query performance, I/O optimization, data pipelines — and the strategy ladder: algorithmic improvements, more efficient code patterns, parallelization, caching, and native C/Rust extensions for critical paths. By @wshobson, listed here with credit to its creator. Honest caveats: a methodology and reference guide, not a magic optimizer — it won't rewrite your code for you; profiling a production app still requires care about overhead. Skill Harbor never reviews the code, review it yourself before use.
Version:
Install
Prerequisites: Python installed; cProfile ships with the standard library — memory profilers installed as needed Install "Python Performance Optimization" for me. Profile and optimize Python code — cProfile, memory profilers, line profiling, call graphs, and proven optimization strategies Repository: https://github.com/wshobson/agents/blob/main/plugins/python-development/skills/python-performance-optimization/SKILL.md 1. Fetch the SKILL.md file for the wshobson-python-performance-optimization skill from the repository into a temporary folder and summarize what it does in one or two sentences. 2. Safety check: review the SKILL.md and scripts for anything suspicious (unexpected network calls, shell commands, credential harvesting). This repo should contain zero secrets in code, credentials only via the secure vault, allowed hosts declared in the SKILL.md. Verify that holds here; STOP on any red flag and tell me. 3. Install it as a skill: copy SKILL.md and its helper files into the agent's skills directory, in a folder named "wshobson-python-performance-optimization". 4. Verify with no network calls: frontmatter valid, files in place. 5. Report what was installed, where, and what I still need to do myself (e.g. any accounts, API keys, or CLI tools mentioned in the prerequisites above). GitHub is optional: if I have a GitHub account or the gh CLI, you may use it; otherwise public access is fine. Never require it unless it's in the prerequisites above. Rules: don't touch anything outside the temp folder and the install target. Never ask me to paste secrets in chat — credentials go through the secure vault or environment variables. If anything looks off, stop and ask me.
Questions
How do I install a build?
Every product page includes a copy-paste install prompt. Paste it into your Muse and it sets the build up for you — no manual configuration.
Where does my money go?
Straight to the seller. Skill Harbor never processes payments: checkout happens on the seller’s own page, usually Stripe.
What does the ✓ next to a creator’s name mean?
It means we confirmed the identity of the person behind the listing. It says nothing about the code itself — always check a build before installing it.