You will get Paper-Safe Python Trading Automation Reliability Sprint
Project details
You will get a practical reliability review and fix pass for a Python trading bot, execution script, or broker/API automation. I focus on the parts that actually break live systems: order flow, retries, rate limits, logging, state tracking, config mistakes, exception handling, and unsafe edge cases.
My goal is not to promise profits or redesign your strategy. It is to make the bot easier to run, debug, monitor, and trust. You’ll receive clear notes on what was changed, what was tested, and any remaining risks or next-step recommendations.
My goal is not to promise profits or redesign your strategy. It is to make the bot easier to run, debug, monitor, and trust. You’ll receive clear notes on what was changed, what was tested, and any remaining risks or next-step recommendations.
Programming Languages
PythonCoding Expertise
Performance Optimization, SecurityWhat's included $1,800
These options are included with the project scope.
$1,800
- Delivery Time 4 days
- Number of Revisions 1
- Install Script
- Test Script
- Task Automation
Optional add-ons
You can add these on the next page.
Fast 2 Days Delivery
+$100
Additional Revision
+$100About Tim
AI Automation + QA Evidence Reports | Shopify, RAG, Python, Workflows
Brunswick, United States - 11:08 am local time
My best-fit work is fixed-scope evidence: screenshot-backed QA reports, Shopify launch checks, AI automation failure maps, and RAG/document AI diagnostics.
You get clear issue logs, severity ratings, reproduction steps, short walkthrough videos, and practical next fixes. I’m strongest where QA meets systems: Python, automation reliability, document retrieval, source-grounded AI, and operational debugging.
If you need a vague audit, I’m probably not the fit. If you need proof, ranked fixes, and a clean handoff your developer can act on, that is the lane.
Services I can package cleanly:
- Shopify launch QA evidence packs
- Website bug hunts with screenshots and reproduction steps
- AI automation workflow audits
- RAG and document AI accuracy diagnostics
- AI dataset cleanup and labeling QA
- Python workflow reliability fixes
Steps for completing your project
After purchasing the project, send requirements so Tim can start the project.
Delivery time starts when Tim receives requirements from you.
Tim works on your project following the steps below.
Revisions may occur after the delivery date.
Review system logs and failure points
I review the codebase, broker/API flow, logs, configs, and current reliability issues, then identify the safest fixes before making production changes.
Implement reliability and execution files
I fix bot crashes, API edge cases, order handling problems, retry logic, state tracking, logging gaps, and other reliability issues found during review.