Daphnis Labs

Python Development

Python services, APIs and automation for business products, with explicit data contracts, background work and operational handover.

catalogue_import.py
for row in catalogue:
result = validate(row)
if result.valid:
queue.upsert(row)
else:
report.add(result.errors)
Valid rowsCorrection report
Python import worker illustration

Tools & technologies

  • Python
  • Django or FastAPI
  • PostgreSQL
  • Task queue

Import a supplier catalogue

Capability Example

A supplier uploads a CSV with valid rows, duplicates and missing prices.

Illustrative data. Nothing is sent to an external system.

Example workspace1 / 3

CSV validation

row 1: valid
row 2: duplicate SKU
row 3: price missing

Check the file schema and collect row-level errors.

Follow the record through the next step

Services and jobs with explicit data contracts.

Backend services

Implement application rules and integrate data from existing systems.

Processing jobs

Validate files, transform records and schedule repeatable operations.

Existing Python systems

Maintain frameworks, improve test coverage and untangle slow or fragile jobs.

Code your team can run and change.

  1. Python service source
  2. API and data schemas
  3. Worker and failure-path tests
  4. Deployment and operations guide
  • Python service source
  • API and data schemas
  • Worker and failure-path tests
  • Deployment and operations guide

Separate the request from the long-running work.

Workload shape

Separate interactive API latency from long-running processing needs.

Data ownership

Define validation and conflict rules before allowing imported data to overwrite records.

Questions before we start.

Do we need Django or FastAPI?

Choose from the product's needs: administration, authentication, API contracts and existing code matter more than framework preference.

Can Python connect to an existing frontend?

Yes. It can expose an API for React, Vue, Angular or mobile clients without replacing those interfaces.

Bring your starting point.

Share the data flow, existing integrations and examples of successful and failed inputs.

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