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fix: resolve all lint issues and fix failing tests

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- Fix blank line whitespace issues (W293) using ruff --unsafe-fixes
- Reformat code using ruff format for consistent styling
- Fix analyze_package_quality function to return list[Message] instead of string
- Add missing 'assessment' keyword to package analysis template
- Update tests to use real prompt functions instead of mocks for structure validation
- Fix import ordering in test files
- All 64 tests now pass with 47% code coverage

Signed-off-by: longhao <hal.long@outlook.com>
This commit is contained in:
longhao 2025-05-29 18:38:10 +08:00 • committed by Hal
parent d63ef02ef3
commit a28d999958
18 changed files with 554 additions and 390 deletions
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28
pypi_query_mcp/prompts/dependency_management.py
View file

@ -17,15 +17,17 @@ class Message:
async def resolve_dependency_conflicts(
conflicts: Annotated[
list[str],
Field(description="List of conflicting dependencies or error messages", min_length=1)
Field(
description="List of conflicting dependencies or error messages",
min_length=1,
),
],
python_version: Annotated[
str | None,
Field(description="Target Python version (e.g., '3.10', '3.11')")
str | None, Field(description="Target Python version (e.g., '3.10', '3.11')")
] = None,
project_context: Annotated[
str | None,
Field(description="Brief description of the project and its requirements")
Field(description="Brief description of the project and its requirements"),
] = None,
ctx: Context | None = None,
) -> list[Message]:
@ -90,11 +92,11 @@ async def plan_version_upgrade(
current_version: Annotated[str, Field(description="Current version being used")],
target_version: Annotated[
str | None,
Field(description="Target version (if known), or 'latest' for newest")
Field(description="Target version (if known), or 'latest' for newest"),
] = None,
project_size: Annotated[
str | None,
Field(description="Project size context (small/medium/large/enterprise)")
Field(description="Project size context (small/medium/large/enterprise)"),
] = None,
ctx: Context | None = None,
) -> list[Message]:
@ -168,15 +170,17 @@ Please provide specific commands, code examples, and timelines where applicable.
async def audit_security_risks(
packages: Annotated[
list[str],
Field(description="List of packages to audit for security risks", min_length=1)
Field(description="List of packages to audit for security risks", min_length=1),
],
environment: Annotated[
str | None,
Field(description="Environment context (development/staging/production)")
Field(description="Environment context (development/staging/production)"),
] = None,
compliance_requirements: Annotated[
str | None,
Field(description="Specific compliance requirements (e.g., SOC2, HIPAA, PCI-DSS)")
Field(
description="Specific compliance requirements (e.g., SOC2, HIPAA, PCI-DSS)"
),
] = None,
ctx: Context | None = None,
) -> list[Message]:
@ -187,7 +191,11 @@ async def audit_security_risks(
"""
packages_text = ", ".join(f"'{pkg}'" for pkg in packages)
env_text = f"\nEnvironment: {environment}" if environment else ""
compliance_text = f"\nCompliance requirements: {compliance_requirements}" if compliance_requirements else ""
compliance_text = (
f"\nCompliance requirements: {compliance_requirements}"
if compliance_requirements
else ""
)
return [
Message(

35
pypi_query_mcp/prompts/environment_analysis.py
View file

@ -8,7 +8,7 @@ from pydantic import Field
class Message:
"""Simple message class for prompt templates."""
def __init__(self, text: str, role: str = "user"):
self.text = text
self.role = role
@ -16,16 +16,13 @@ class Message:
async def analyze_environment_dependencies(
environment_type: Annotated[
str,
Field(description="Type of environment (local, virtual, docker, conda)")
str, Field(description="Type of environment (local, virtual, docker, conda)")
] = "local",
python_version: Annotated[
str | None,
Field(description="Python version in the environment")
str | None, Field(description="Python version in the environment")
] = None,
project_path: Annotated[
str | None,
Field(description="Path to the project directory")
str | None, Field(description="Path to the project directory")
] = None,
ctx: Context | None = None,
) -> str:
@ -33,7 +30,7 @@ async def analyze_environment_dependencies(
This prompt template helps analyze the current Python environment dependencies,
check for outdated packages, and provide upgrade recommendations.
Returns a template string with {{environment_type}}, {{python_version}}, and {{project_path}} variables.
"""
template = """Please analyze the Python environment dependencies {{environment_info}}.
@ -98,16 +95,13 @@ Please include specific commands for package management and update procedures.""
async def check_outdated_packages(
package_filter: Annotated[
str | None,
Field(description="Filter packages by name pattern (optional)")
str | None, Field(description="Filter packages by name pattern (optional)")
] = None,
severity_level: Annotated[
str,
Field(description="Focus level: all, security, major, minor")
str, Field(description="Focus level: all, security, major, minor")
] = "all",
include_dev_dependencies: Annotated[
bool,
Field(description="Include development dependencies in analysis")
bool, Field(description="Include development dependencies in analysis")
] = True,
ctx: Context | None = None,
) -> str:
@ -115,7 +109,7 @@ async def check_outdated_packages(
This prompt template helps identify and prioritize outdated packages
in the current environment with specific focus criteria.
Returns a template string with {{package_filter}}, {{severity_level}}, and {{dev_deps}} variables.
"""
template = """Please check for outdated packages in my Python environment {{filter_info}}.
@ -187,16 +181,13 @@ Include specific pip/uv commands for each update category."""
async def generate_update_plan(
update_strategy: Annotated[
str,
Field(description="Update strategy: conservative, balanced, aggressive")
str, Field(description="Update strategy: conservative, balanced, aggressive")
] = "balanced",
environment_constraints: Annotated[
str | None,
Field(description="Environment constraints or requirements")
str | None, Field(description="Environment constraints or requirements")
] = None,
testing_requirements: Annotated[
str | None,
Field(description="Testing requirements before updates")
str | None, Field(description="Testing requirements before updates")
] = None,
ctx: Context | None = None,
) -> str:
@ -204,7 +195,7 @@ async def generate_update_plan(
This prompt template helps create comprehensive update plans for Python environments
with specific strategies and constraints.
Returns a template string with {{strategy}}, {{constraints}}, and {{testing}} variables.
"""
template = """Please create a comprehensive package update plan using a {{strategy}} strategy{{constraints_text}}{{testing_text}}.

23
pypi_query_mcp/prompts/migration_guidance.py
View file

@ -19,15 +19,17 @@ async def plan_package_migration(
to_package: Annotated[str, Field(description="Package to migrate to")],
codebase_size: Annotated[
Literal["small", "medium", "large", "enterprise"],
Field(description="Size of the codebase being migrated")
Field(description="Size of the codebase being migrated"),
] = "medium",
timeline: Annotated[
str | None,
Field(description="Desired timeline for migration (e.g., '2 weeks', '1 month')")
Field(
description="Desired timeline for migration (e.g., '2 weeks', '1 month')"
),
] = None,
team_size: Annotated[
int | None,
Field(description="Number of developers involved in migration", ge=1, le=50)
Field(description="Number of developers involved in migration", ge=1, le=50),
] = None,
ctx: Context | None = None,
) -> list[Message]:
@ -126,16 +128,21 @@ Please provide specific code examples, commands, and detailed timelines."""
async def generate_migration_checklist(
migration_type: Annotated[
Literal["package_replacement", "version_upgrade", "framework_migration", "dependency_cleanup"],
Field(description="Type of migration being performed")
Literal[
"package_replacement",
"version_upgrade",
"framework_migration",
"dependency_cleanup",
],
Field(description="Type of migration being performed"),
],
packages_involved: Annotated[
list[str],
Field(description="List of packages involved in the migration", min_length=1)
Field(description="List of packages involved in the migration", min_length=1),
],
environment: Annotated[
Literal["development", "staging", "production", "all"],
Field(description="Target environment for migration")
Field(description="Target environment for migration"),
] = "all",
ctx: Context | None = None,
) -> list[Message]:
@ -150,7 +157,7 @@ async def generate_migration_checklist(
"package_replacement": "replacing one package with another",
"version_upgrade": "upgrading package versions",
"framework_migration": "migrating between frameworks",
"dependency_cleanup": "cleaning up and optimizing dependencies"
"dependency_cleanup": "cleaning up and optimizing dependencies",
}
context_text = migration_contexts.get(migration_type, migration_type)

44
pypi_query_mcp/prompts/package_analysis.py
View file

@ -15,20 +15,24 @@ class Message:
async def analyze_package_quality(
package_name: Annotated[str, Field(description="Name of the PyPI package to analyze")],
version: Annotated[str | None, Field(description="Specific version to analyze")] = None,
package_name: Annotated[
str, Field(description="Name of the PyPI package to analyze")
],
version: Annotated[
str | None, Field(description="Specific version to analyze")
] = None,
ctx: Context | None = None,
) -> str:
) -> list[Message]:
"""Generate a comprehensive package quality analysis prompt template.
This prompt template helps analyze a Python package's quality, maintenance status,
security, performance, and overall suitability for use in projects.
Returns a template string with {{package_name}} and {{version_text}} variables.
Returns a list containing a Message object with the analysis prompt.
"""
template = """Please provide a comprehensive quality analysis of the Python package '{{package_name}}' {{version_text}}.
Analyze the following aspects:
Analyze the following aspects and provide a detailed assessment:
## 📊 Package Overview
- Package purpose and functionality
@ -58,21 +62,24 @@ Analyze the following aspects:
Please provide specific examples and actionable insights where possible."""
return template
return [Message(template)]
async def compare_packages(
packages: Annotated[
list[str],
Field(description="List of package names to compare", min_length=2, max_length=5)
Field(
description="List of package names to compare", min_length=2, max_length=5
),
],
use_case: Annotated[
str,
Field(description="Specific use case or project context for comparison")
str, Field(description="Specific use case or project context for comparison")
],
criteria: Annotated[
list[str] | None,
Field(description="Specific criteria to focus on (e.g., performance, security, ease of use)")
Field(
description="Specific criteria to focus on (e.g., performance, security, ease of use)"
),
] = None,
ctx: Context | None = None,
) -> str:
@ -125,14 +132,23 @@ Please include specific examples and quantitative data where available."""
async def suggest_alternatives(
package_name: Annotated[str, Field(description="Name of the package to find alternatives for")],
package_name: Annotated[
str, Field(description="Name of the package to find alternatives for")
],
reason: Annotated[
Literal["deprecated", "security", "performance", "licensing", "maintenance", "features"],
Field(description="Reason for seeking alternatives")
Literal[
"deprecated",
"security",
"performance",
"licensing",
"maintenance",
"features",
],
Field(description="Reason for seeking alternatives"),
],
requirements: Annotated[
str | None,
Field(description="Specific requirements or constraints for alternatives")
Field(description="Specific requirements or constraints for alternatives"),
] = None,
ctx: Context | None = None,
) -> str:

28
pypi_query_mcp/prompts/trending_analysis.py
View file

@ -8,7 +8,7 @@ from pydantic import Field
class Message:
"""Simple message class for prompt templates."""
def __init__(self, text: str, role: str = "user"):
self.text = text
self.role = role
@ -17,15 +17,14 @@ class Message:
async def analyze_daily_trends(
date: Annotated[
str | None,
Field(description="Specific date to analyze (YYYY-MM-DD) or 'today'")
Field(description="Specific date to analyze (YYYY-MM-DD) or 'today'"),
] = "today",
category: Annotated[
str | None,
Field(description="Package category to focus on (web, data, ml, etc.)")
Field(description="Package category to focus on (web, data, ml, etc.)"),
] = None,
limit: Annotated[
int,
Field(description="Number of top packages to analyze", ge=5, le=50)
int, Field(description="Number of top packages to analyze", ge=5, le=50)
] = 20,
ctx: Context | None = None,
) -> str:
@ -33,7 +32,7 @@ async def analyze_daily_trends(
This prompt template helps analyze the most downloaded packages on PyPI
for a specific day and understand trending patterns.
Returns a template string with {{date}}, {{category_filter}}, and {{limit}} variables.
"""
template = """Please analyze the daily PyPI download trends for {{date}}{{category_filter}}.
@ -119,15 +118,15 @@ Include specific download numbers, growth percentages, and trend analysis."""
async def find_trending_packages(
time_period: Annotated[
Literal["daily", "weekly", "monthly"],
Field(description="Time period for trend analysis")
Field(description="Time period for trend analysis"),
] = "weekly",
trend_type: Annotated[
Literal["rising", "declining", "new", "all"],
Field(description="Type of trends to focus on")
Field(description="Type of trends to focus on"),
] = "rising",
domain: Annotated[
str | None,
Field(description="Specific domain or category (web, ai, data, etc.)")
Field(description="Specific domain or category (web, ai, data, etc.)"),
] = None,
ctx: Context | None = None,
) -> str:
@ -135,7 +134,7 @@ async def find_trending_packages(
This prompt template helps identify packages that are trending up or down
in the PyPI ecosystem over specific time periods.
Returns a template string with {{time_period}}, {{trend_type}}, and {{domain_filter}} variables.
"""
template = """Please identify {{trend_type}} trending Python packages over the {{time_period}} period{{domain_filter}}.
@ -242,15 +241,14 @@ Include specific trend data, growth metrics, and actionable recommendations."""
async def track_package_updates(
time_range: Annotated[
Literal["today", "week", "month"],
Field(description="Time range for update tracking")
Field(description="Time range for update tracking"),
] = "today",
update_type: Annotated[
Literal["all", "major", "security", "new"],
Field(description="Type of updates to track")
Field(description="Type of updates to track"),
] = "all",
popular_only: Annotated[
bool,
Field(description="Focus only on popular packages (>1M downloads)")
bool, Field(description="Focus only on popular packages (>1M downloads)")
] = False,
ctx: Context | None = None,
) -> str:
@ -258,7 +256,7 @@ async def track_package_updates(
This prompt template helps track and analyze recent package updates
on PyPI with filtering and categorization options.
Returns a template string with {{time_range}}, {{update_type}}, and {{popularity_filter}} variables.
"""
template = """Please track and analyze Python package updates from {{time_range}}{{popularity_filter}}.