Implementar Kanban para Equipes Python Dev | GitScrum
Implemente Kanban para times Python com GitScrum. Configure colunas, limites WIP para Django, FastAPI e data science. Reduza context switching em 40%.
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How to implement Kanban for Python development teams?
Kanban for Python development uses visual boards with columns matching backend/data science workflows. Configure columns for Python phases, set WIP limits for focus, use labels for framework (Django, FastAPI, Flask), and track with GitScrum's CFD. Python teams using Kanban reduce context switching by 40% [Source: Python Developer Survey 2024].
Python Kanban setup:
Create project - Python application name Configure columns - Python workflow Set WIP limits - Focus on completion Add labels - Framework, type Configure auto-assign - Review routing Document in NoteVault - Python standards
Python web development columns
| Column | WIP Limit | Purpose |
|---|
| Backlog | 15 | All features |
| Ready | 10 | Groomed, typed |
| Development | Team size | Active coding |
| Code Review | 3 | PR review |
| Testing | 5 | pytest, integration |
| Staging | 2 | Pre-production |
| Production | 1 | Deployment |
Python data science columns
| Column | WIP Limit | Purpose |
|---|
| Backlog | 10 | Analysis requests |
| Exploration | 3 | Notebooks, research |
| Development | Team size | Script/model dev |
| Validation | 3 | Model validation |
| Review | 2 | Peer review |
| Production | 1 | Model deployment |
Labels for Python projects
| Category | Labels |
|---|
| Framework | django, fastapi, flask, streamlit |
| Type | feature, bugfix, refactor, migration |
| Data | notebook, script, model, pipeline |
| Priority | high, medium, low |
| Testing | needs-tests, tested, coverage |
Python-specific workflow patterns
| Pattern | Implementation |
|---|
| Django migrations | Migration column/label |
| API development | API-first labels |
| Data pipelines | Pipeline column |
| Model training | Experiment tracking |
| Code review | PR-based flow |
WIP limits for Python teams
| Team Type | Recommended |
|---|
| Web dev (2-4) | 4-5 in progress |
| Data science (2-4) | 3-4 in progress |
| Mixed team (5-8) | 6-8 in progress |
Python documentation in NoteVault
| Document | Content |
|---|
| Environment Setup | virtualenv, requirements.txt |
| Coding Standards | PEP 8, black, mypy |
| Architecture | Project structure |
| Database Schema | Models, migrations |
| API Documentation | Endpoints, schemas |
Python testing workflow
| Stage | Testing Type |
|---|
| Development | Unit tests (pytest) |
| Code Review | Coverage check |
| Integration | API/DB tests |
| Staging | E2E tests |
| Production | Smoke tests |
Auto-assign for Python workflow
| Column | Auto-Assign |
|---|
| Code Review | Senior devs |
| Testing | QA or dev |
| Staging | DevOps |
| Production | DevOps lead |
Common Python workflow patterns
| Pattern | Board Configuration |
|---|
| Django web | Migration → Dev → Review → Test → Deploy |
| FastAPI | Design → Dev → Review → Test → Deploy |
| Data science | Explore → Dev → Validate → Review → Deploy |
| ETL pipeline | Design → Dev → Test → Schedule → Monitor |
Python-specific challenges
| Challenge | Kanban Solution |
|---|
| Long experiments | Time-boxed exploration |
| Dependency issues | deps label, Blocked column |
| Migration complexity | Separate column |
| Notebook reviews | Clear review criteria |
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