Replace repetitive business tasks with a Python workflow built around your actual inputs, outputs and operating needs. I help turn a manual process into a repeatable script or API integration with a clear scope and practical handover.

Web scraping and structured data collection from agreed sources.

API integrations and data transfers between systems.

Data cleanup, file processing and repeatable reports.

Fixes and improvements to existing Python scripts.

1. Map the task: Review the current process, sample inputs, desired output and run frequency.

2. Check feasibility: Validate the source or API and identify access requirements, data gaps and operating constraints.

3. Build the workflow: Implement the agreed transformations, integrations and output format, with validation and error handling appropriate to the task.

4. Test and hand over: Compare results against agreed sample cases and document how to run the workflow.

Python source code for the agreed workflow.

Sample output in the agreed format and checks against the supplied examples.

Setup instructions covering dependencies and configuration.

Usage notes, error-handling guidance and known limitations.

Scheduling or deployment support when included in the proposal.

We agree on the sources, required fields, output format and validation examples before work starts. For recurring workflows, we also define when the job runs, where it runs and how failures should be handled.

Price and timing depend on the sources, data volume, run frequency and integrations. API fees, hosting, subscriptions and ongoing maintenance are separate unless included in the proposal.

Describe the task, share a non-sensitive example input and desired output, and say how often it should run. For scraping, include the source URLs and fields you need. For an API integration, include the systems to connect and the data that should move between them.