feat: add comprehensive environment and trending analysis prompt templates
Environment Analysis Templates:
- analyze_environment_dependencies: Analyze current Python environment and dependencies
- check_outdated_packages: Check for outdated packages with update priorities
- generate_update_plan: Create comprehensive package update plans with strategies
Trending Analysis Templates:
- analyze_daily_trends: Analyze daily PyPI download trends and popular packages
- find_trending_packages: Discover trending packages over different time periods
- track_package_updates: Track recent package updates and releases
Key Features:
- Follow standard MCP workflow with {{parameter}} template variables
- Support environment analysis (uvx pip list integration ready)
- Enable trending package discovery and popularity analysis
- Provide structured update planning with different strategies
- Include comprehensive parameter validation and documentation
- Add usage examples and integration guides
All templates follow the established MCP prompt workflow:
1. User calls tool → MCP client sends request
2. Tool function executes → Collects necessary data and parameters
3. Call Prompt generator → Pass parameters to corresponding generator
4. Load template → Get template with {{parameter}} placeholders
5. Parameter replacement → Replace {{parameter_name}} with actual values
6. Return final prompt → As tool's response back to AI
Updated documentation and README with new template examples and usage patterns.
Signed-off-by: longhao <hal.long@outlook.com>
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longhao
Hal
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291
pypi_query_mcp/prompts/environment_analysis.py
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pypi_query_mcp/prompts/environment_analysis.py
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"""Environment analysis prompt templates for PyPI MCP server."""
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from typing import Annotated
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from fastmcp import Context
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from pydantic import Field
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class Message:
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"""Simple message class for prompt templates."""
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def __init__(self, text: str, role: str = "user"):
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self.text = text
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self.role = role
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async def analyze_environment_dependencies(
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environment_type: Annotated[
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str,
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Field(description="Type of environment (local, virtual, docker, conda)")
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] = "local",
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python_version: Annotated[
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str | None,
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Field(description="Python version in the environment")
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] = None,
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project_path: Annotated[
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str | None,
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Field(description="Path to the project directory")
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] = None,
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ctx: Context | None = None,
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) -> str:
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"""Generate a prompt template for analyzing environment dependencies.
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This prompt template helps analyze the current Python environment dependencies,
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check for outdated packages, and provide upgrade recommendations.
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Returns a template string with {{environment_type}}, {{python_version}}, and {{project_path}} variables.
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"""
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template = """Please analyze the Python environment dependencies {{environment_info}}.
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## 🔍 Environment Analysis Request
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I need to analyze my current Python environment to understand:
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### Current Environment Status
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- List all installed packages and their versions (use `{{command_prefix}}pip list`)
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- Identify the Python version and environment type
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- Check for any conflicting or problematic installations
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### Package Version Analysis
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- Compare installed versions with latest available on PyPI
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- Identify outdated packages that have newer versions
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- Highlight packages with security updates available
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- Check for packages with major version updates
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### Dependency Health Check
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- Analyze dependency relationships and conflicts
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- Identify unused or redundant packages
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- Check for packages with known vulnerabilities
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- Assess overall environment health
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## 📊 Detailed Analysis Framework
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### For Each Package, Provide:
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1. **Current vs Latest Version**
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- Installed version
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- Latest stable version on PyPI
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- Version gap analysis (patch/minor/major updates)
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2. **Update Priority Assessment**
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- Security updates (HIGH priority)
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- Bug fixes and stability improvements (MEDIUM priority)
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- New features and enhancements (LOW priority)
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3. **Compatibility Impact**
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- Breaking changes in newer versions
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- Dependency chain effects
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- Potential conflicts with other packages
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### Environment Optimization Recommendations
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- Packages safe to update immediately
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- Packages requiring careful testing before update
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- Packages to avoid updating (due to breaking changes)
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- Cleanup recommendations for unused packages
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## 🚀 Action Plan
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Provide a prioritized action plan with:
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- Immediate updates (security and critical fixes)
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- Planned updates (with testing requirements)
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- Long-term upgrade strategy
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- Environment maintenance best practices
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Please include specific commands for package management and update procedures."""
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return template
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async def check_outdated_packages(
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package_filter: Annotated[
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str | None,
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Field(description="Filter packages by name pattern (optional)")
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] = None,
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severity_level: Annotated[
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str,
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Field(description="Focus level: all, security, major, minor")
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] = "all",
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include_dev_dependencies: Annotated[
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bool,
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Field(description="Include development dependencies in analysis")
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] = True,
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ctx: Context | None = None,
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) -> str:
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"""Generate a prompt template for checking outdated packages.
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This prompt template helps identify and prioritize outdated packages
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in the current environment with specific focus criteria.
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Returns a template string with {{package_filter}}, {{severity_level}}, and {{dev_deps}} variables.
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"""
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template = """Please check for outdated packages in my Python environment {{filter_info}}.
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## 🔍 Outdated Package Analysis
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Focus on {{severity_level}} updates{{dev_deps_text}}.
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### Analysis Scope
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- Check all installed packages against PyPI latest versions
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- Identify packages with available updates
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- Categorize updates by severity and importance
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- Assess update risks and benefits
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## 📋 Update Categories
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### 🚨 Security Updates (Critical)
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- Packages with known security vulnerabilities
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- CVE fixes and security patches
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- Immediate action required packages
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### 🔧 Bug Fixes & Stability (Important)
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- Critical bug fixes
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- Stability improvements
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- Performance enhancements
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### ✨ Feature Updates (Optional)
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- New features and capabilities
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- API improvements
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- Non-breaking enhancements
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### ⚠️ Major Version Updates (Careful)
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- Breaking changes
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- API modifications
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- Requires thorough testing
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## 📊 For Each Outdated Package, Provide:
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1. **Version Information**
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- Current version installed
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- Latest available version
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- Release date of latest version
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- Version type (patch/minor/major)
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2. **Update Assessment**
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- Change log highlights
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- Breaking changes (if any)
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- Security implications
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- Dependency impact
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3. **Recommendation**
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- Update priority (High/Medium/Low)
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- Testing requirements
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- Rollback considerations
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- Best update timing
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## 🎯 Prioritized Update Plan
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Create a step-by-step update plan:
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1. **Immediate Updates** (security and critical fixes)
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2. **Planned Updates** (important improvements)
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3. **Future Considerations** (major version upgrades)
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4. **Monitoring Setup** (track future updates)
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Include specific pip/uv commands for each update category."""
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return template
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async def generate_update_plan(
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update_strategy: Annotated[
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str,
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Field(description="Update strategy: conservative, balanced, aggressive")
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] = "balanced",
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environment_constraints: Annotated[
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str | None,
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Field(description="Environment constraints or requirements")
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] = None,
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testing_requirements: Annotated[
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str | None,
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Field(description="Testing requirements before updates")
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] = None,
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ctx: Context | None = None,
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) -> str:
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"""Generate a prompt template for creating package update plans.
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This prompt template helps create comprehensive update plans for Python environments
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with specific strategies and constraints.
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Returns a template string with {{strategy}}, {{constraints}}, and {{testing}} variables.
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"""
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template = """Please create a comprehensive package update plan using a {{strategy}} strategy{{constraints_text}}{{testing_text}}.
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## 🎯 Update Strategy: {{strategy}}
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### Strategy Guidelines
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- **Conservative**: Only security and critical bug fixes
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- **Balanced**: Security fixes + stable improvements + selected features
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- **Aggressive**: Latest versions with careful testing
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## 📋 Update Plan Framework
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### Phase 1: Pre-Update Assessment
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1. **Environment Backup**
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- Create requirements.txt snapshot
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- Document current working state
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- Set up rollback procedures
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2. **Dependency Analysis**
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- Map dependency relationships
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- Identify potential conflicts
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- Plan update order
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3. **Risk Assessment**
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- Categorize packages by update risk
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- Identify critical dependencies
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- Plan testing scope
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### Phase 2: Staged Update Execution
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#### Stage 1: Critical Security Updates
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- Packages with known vulnerabilities
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- Zero-day fixes and security patches
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- Immediate deployment candidates
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#### Stage 2: Stability Improvements
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- Bug fixes and performance improvements
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- Compatibility updates
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- Low-risk enhancements
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#### Stage 3: Feature Updates
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- New functionality additions
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- API improvements
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- Non-breaking enhancements
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#### Stage 4: Major Version Updates
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- Breaking changes requiring code updates
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- Comprehensive testing required
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- Gradual rollout recommended
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### Phase 3: Validation & Monitoring
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#### Testing Protocol
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- Unit test execution
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- Integration testing
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- Performance regression testing
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- User acceptance testing
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#### Deployment Strategy
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- Development environment first
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- Staging environment validation
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- Production deployment with monitoring
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- Rollback procedures ready
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## 🔧 Implementation Commands
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Provide specific commands for:
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1. **Environment preparation**
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2. **Package updates by category**
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3. **Testing and validation**
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4. **Rollback procedures**
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## 📊 Success Metrics
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Define success criteria:
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- All tests passing
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- No performance degradation
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- Security vulnerabilities addressed
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- Functionality maintained
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Include monitoring setup for ongoing package management."""
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return template
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