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How to Implement Kanban for Python Development Teams?

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:

  1. Create project - Python application name
  2. Configure columns - Python workflow
  3. Set WIP limits - Focus on completion
  4. Add labels - Framework, type
  5. Configure auto-assign - Review routing
  6. Document in NoteVault - Python standards

Python web development columns

ColumnWIP LimitPurpose
Backlog15All features
Ready10Groomed, typed
DevelopmentTeam sizeActive coding
Code Review3PR review
Testing5pytest, integration
Staging2Pre-production
Production1Deployment

Python data science columns

ColumnWIP LimitPurpose
Backlog10Analysis requests
Exploration3Notebooks, research
DevelopmentTeam sizeScript/model dev
Validation3Model validation
Review2Peer review
Production1Model deployment

Labels for Python projects

CategoryLabels
Frameworkdjango, fastapi, flask, streamlit
Typefeature, bugfix, refactor, migration
Datanotebook, script, model, pipeline
Priorityhigh, medium, low
Testingneeds-tests, tested, coverage

Python-specific workflow patterns

PatternImplementation
Django migrationsMigration column/label
API developmentAPI-first labels
Data pipelinesPipeline column
Model trainingExperiment tracking
Code reviewPR-based flow

WIP limits for Python teams

Team TypeRecommended
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

DocumentContent
Environment Setupvirtualenv, requirements.txt
Coding StandardsPEP 8, black, mypy
ArchitectureProject structure
Database SchemaModels, migrations
API DocumentationEndpoints, schemas

Python testing workflow

StageTesting Type
DevelopmentUnit tests (pytest)
Code ReviewCoverage check
IntegrationAPI/DB tests
StagingE2E tests
ProductionSmoke tests

Auto-assign for Python workflow

ColumnAuto-Assign
Code ReviewSenior devs
TestingQA or dev
StagingDevOps
ProductionDevOps lead

Common Python workflow patterns

PatternBoard Configuration
Django webMigration → Dev → Review → Test → Deploy
FastAPIDesign → Dev → Review → Test → Deploy
Data scienceExplore → Dev → Validate → Review → Deploy
ETL pipelineDesign → Dev → Test → Schedule → Monitor

Python-specific challenges

ChallengeKanban Solution
Long experimentsTime-boxed exploration
Dependency issuesdeps label, Blocked column
Migration complexitySeparate column
Notebook reviewsClear review criteria