本文へ移動
cccskills
無料GitHub で公開

pulumi-python

Creates Pulumi infrastructure-as-code projects in Python, defines cloud resources (AWS, Azure, GCP), configures ESC environments for secrets management, sets up OIDC authentication for secure deployments, and builds multi-language component resources. Use when creating Pulumi Python projects, writing infrastructure code, configuring cloud providers, managing secrets with Pulumi ESC, setting up OIDC for Pulumi, automating infrastructure deployments with Python, creating reusable Pulumi components in Python, or configuring Python toolchains (pip, poetry, uv) for Pulumi. Also use when the user mentions pyproject.toml with Pulumi, component_provider_host, or Python virtual environments for infrastructure code.

インストール方法を見る

含まれるファイル(8)

  • SKILL.md12.1 KB
  • evals/evals.json3.1 KB
  • references/pulumi-best-practices-aws.md6.6 KB
  • references/pulumi-best-practices-azure.md8.4 KB
  • references/pulumi-best-practices-gcp.md8.7 KB
  • references/pulumi-esc.md3.6 KB
  • references/pulumi-patterns.md8.2 KB
  • references/pulumi-python.md5.4 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Pulumi Python Skill

Development Workflow

1. Project Setup

# Create new Python project
pulumi new python

# Or with a cloud-specific template
pulumi new aws-python
pulumi new azure-python
pulumi new gcp-python

Project structure:

my-project/
├── Pulumi.yaml
├── __main__.py
├── requirements.txt     # or pyproject.toml
└── venv/                # Virtual environment

2. Pulumi ESC Integration

Use Pulumi ESC for centralized secrets and configuration instead of stack config files.

Link ESC environment to stack:

# Create ESC environment
pulumi env init myorg/myproject-dev

# Edit environment
pulumi env edit myorg/myproject-dev

# Link to Pulumi stack
pulumi config env add myorg/myproject-dev

ESC environment definition (YAML):

values:
  # Static configuration
  pulumiConfig:
    aws:region: us-west-2
    myapp:instanceType: t3.medium

  # Dynamic OIDC credentials for AWS
  aws:
    login:
      fn::open::aws-login:
        oidc:
          roleArn: arn:aws:iam::123456789:role/pulumi-oidc
          sessionName: pulumi-deploy

  # Pull secrets from AWS Secrets Manager
  secrets:
    fn::open::aws-secrets:
      region: us-west-2
      login: ${aws.login}
      get:
        dbPassword:
          secretId: prod/database/password

  # Expose to environment variables
  environmentVariables:
    AWS_ACCESS_KEY_ID: ${aws.login.accessKeyId}
    AWS_SECRET_ACCESS_KEY: ${aws.login.secretAccessKey}
    AWS_SESSION_TOKEN: ${aws.login.sessionToken}

Validate ESC environment:

# View resolved values (verify no errors)
pulumi env open myorg/myproject-dev

# Check for missing required values
pulumi env open myorg/myproject-dev --format json | jq .

3. Python Patterns

Basic resource creation:

import pulumi
import pulumi_aws as aws

# Get configuration from ESC
config = pulumi.Config()
instance_type = config.require("instanceType")

# Create resources with proper tagging
bucket = aws.s3.Bucket(
    "my-bucket",
    versioning=aws.s3.BucketVersioningArgs(
        enabled=True,
    ),
    server_side_encryption_configuration=aws.s3.BucketServerSideEncryptionConfigurationArgs(
        rule=aws.s3.BucketServerSideEncryptionConfigurationRuleArgs(
            apply_server_side_encryption_by_default=aws.s3.BucketServerSideEncryptionConfigurationRuleApplyServerSideEncryptionByDefaultArgs(
                sse_algorithm="AES256",
            ),
        ),
    ),
    tags={
        "Environment": pulumi.get_stack(),
        "ManagedBy": "Pulumi",
    },
)

# Export outputs
pulumi.export("bucket_name", bucket.id)
pulumi.export("bucket_arn", bucket.arn)

Using dictionary literals (concise alternative):

import pulumi
import pulumi_aws as aws

bucket = aws.s3.Bucket(
    "my-bucket",
    versioning={"enabled": True},
    server_side_encryption_configuration={
        "rule": {
            "apply_server_side_encryption_by_default": {
                "sse_algorithm": "AES256",
            },
        },
    },
    tags={
        "Environment": pulumi.get_stack(),
        "ManagedBy": "Pulumi",
    },
)

Component resources for reusability:

import pulumi
from pulumi_aws import lb


class WebServiceArgs:
    def __init__(self, port: pulumi.Input[int], image_uri: pulumi.Input[str]):
        self.port = port
        self.image_uri = image_uri


class WebService(pulumi.ComponentResource):
    url: pulumi.Output[str]

    def __init__(self, name: str, args: WebServiceArgs, opts: pulumi.ResourceOptions = None):
        super().__init__("custom:app:WebService", name, {}, opts)

        # Create child resources with parent=self
        load_balancer = lb.LoadBalancer(
            f"{name}-lb",
            load_balancer_type="application",
            # ... configuration
            opts=pulumi.ResourceOptions(parent=self),
        )

        self.url = load_balancer.dns_name

        self.register_outputs({
            "url": self.url,
        })

Stack references for cross-stack dependencies:

import pulumi

# Reference outputs from networking stack
networking_stack = pulumi.StackReference("myorg/networking/prod")
vpc_id = networking_stack.get_output("vpc_id")
subnet_ids = networking_stack.get_output("private_subnet_ids")

Working with Outputs:

import pulumi

# Apply transformation
uppercase_name = bucket.id.apply(lambda id: id.upper())

# Combine multiple outputs
combined = pulumi.Output.all(bucket.id, bucket.arn).apply(
    lambda args: f"Bucket {args[0]} has ARN {args[1]}"
)

# Using Output.concat for string interpolation
message = pulumi.Output.concat("Bucket ARN: ", bucket.arn)

# Conditional resources
is_prod = pulumi.get_stack() == "prod"
if is_prod:
    alarm = aws.cloudwatch.MetricAlarm(
        "alarm",
        # ... configuration
    )

4. Using ESC with pulumi env run

Run any command with ESC environment variables injected:

# Run pulumi commands with ESC credentials
pulumi env run myorg/aws-dev -- pulumi up

# Run tests with secrets
pulumi env run myorg/test-env -- pytest

# Open environment and export to shell
pulumi env open myorg/myproject-dev --format shell

5. Multi-Language Components

Create components in Python that can be consumed from any Pulumi language (TypeScript, Go, C#, Java, YAML).

Project structure for multi-language component:

my-component/
├── PulumiPlugin.yaml      # Required for multi-language
├── pyproject.toml         # or requirements.txt
└── __main__.py            # Component + entry point

PulumiPlugin.yaml:

runtime: python

Component with proper Args class (main.py):

from typing import Optional
import pulumi
from pulumi import Input, Output, ResourceOptions
from pulumi.provider.experimental import component_provider_host
import pulumi_aws as aws


class SecureBucketArgs:
    """Args class - use Input types for all properties."""

    def __init__(
        self,
        bucket_name: Input[str],
        enable_versioning: Optional[Input[bool]] = None,
        tags: Optional[Input[dict]] = None,
    ):
        self.bucket_name = bucket_name
        self.enable_versioning = enable_versioning or True
        self.tags = tags


class SecureBucket(pulumi.ComponentResource):
    """A secure S3 bucket with encryption and versioning."""

    bucket_id: Output[str]
    bucket_arn: Output[str]

    # Constructor must have 'args' parameter with type annotation
    def __init__(
        self,
        name: str,
        args: SecureBucketArgs,
        opts: Optional[ResourceOptions] = None,
    ):
        super().__init__("myorg:storage:SecureBucket", name, {}, opts)

        bucket = aws.s3.Bucket(
            f"{name}-bucket",
            bucket=args.bucket_name,
            versioning={"enabled": args.enable_versioning},
            server_side_encryption_configuration={
                "rule": {
                    "apply_server_side_encryption_by_default": {
                        "sse_algorithm": "AES256",
                    },
                },
            },
            tags=args.tags,
            opts=ResourceOptions(parent=self),
        )

        self.bucket_id = bucket.id
        self.bucket_arn = bucket.arn

        self.register_outputs({
            "bucket_id": self.bucket_id,
            "bucket_arn": self.bucket_arn,
        })


# Entry point for multi-language support
if __name__ == "__main__":
    component_provider_host(
        name="python-components",
        components=[SecureBucket],
    )

Publishing for multi-language consumption:

# Consume from git repository
pulumi package add github.com/myorg/my-component

# With version tag
pulumi package add github.com/myorg/my-component@v1.0.0

# Local development
pulumi package add /path/to/local/my-component

Multi-language Args requirements:

  • Use pulumi.Input[T] type hints for all properties
  • Args class must have __init__ with typed parameters
  • Constructor must have args parameter with type annotation
  • Use Optional[Input[T]] for optional properties

Important: Use component_provider_host() (from pulumi.provider.experimental) as the entry point for multi-language components. This is the modern API — the older pulumi.provider.main() with a custom Provider subclass is deprecated for component authoring.

6. Deployment Workflow

Validate and deploy with error recovery:

# Step 1: Preview changes
pulumi preview

# Step 2: Review output for errors or unexpected changes
# If errors appear, fix code and re-run preview

# Step 3: Deploy only after preview succeeds
pulumi up

# Step 4: Verify outputs
pulumi stack output

For ESC-based deployments:

# Step 1: Validate ESC environment resolves correctly
pulumi env open myorg/myproject-dev

# Step 2: Preview with ESC environment
pulumi env run myorg/myproject-dev -- pulumi preview

# Step 3: Deploy with ESC environment
pulumi env run myorg/myproject-dev -- pulumi up

# Step 4: Check stack outputs
pulumi stack output

Configuration & Security

  • Use Pulumi ESC for all secrets — never commit secrets to stack config files or Pulumi.yaml
  • Enable OIDC authentication instead of static credentials
  • Use dynamic secrets with short TTLs when possible
  • Apply least-privilege IAM policies to OIDC roles
  • Use ComponentResources for reusable infrastructure patterns
  • Leverage Python type hints for better IDE support and error detection

Common Commands

# Environment Commands (pulumi env)
pulumi env init <org>/<project>/<env>        # Create environment
pulumi env edit <org>/<env>                  # Edit environment
pulumi env open <org>/<env>                  # View resolved values
pulumi env run <org>/<env> -- <command>      # Run with env vars
pulumi env version tag <org>/<env> <tag>     # Tag version

# Pulumi Commands
pulumi new python                      # New project
pulumi config env add <org>/<env>     # Link ESC environment
pulumi preview                         # Preview changes
pulumi up                              # Deploy
pulumi stack output                    # View outputs
pulumi destroy                         # Tear down

# Dependency Management
pip install -r requirements.txt        # Install deps (pip)
poetry add pulumi-aws                  # Add dep (poetry)
uv add pulumi-aws                      # Add dep (uv)

Python-Specific Configuration

Using pip (default):

# Pulumi.yaml
runtime:
  name: python
  options:
    toolchain: pip
    virtualenv: venv

Using poetry:

# Pulumi.yaml
runtime:
  name: python
  options:
    toolchain: poetry

Using uv:

# Pulumi.yaml
runtime:
  name: python
  options:
    toolchain: uv
    virtualenv: .venv

Enable type checking:

# Pulumi.yaml
runtime:
  name: python
  options:
    typechecker: mypy  # or pyright

References

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Prepares Go applications to work effectively with AI coding agents. Use when setting up a new Go project or retrofitting an existing one to ensure: structured JSON logging (slog/Zap/ZeroLog/Logrus), machine-readable command output, thorough golangci-lint configuration, non-interactive CLI design with --yes flags, structured error handling with meaningful exit codes, proper context.Context propagation, graceful shutdown, health check endpoints, and a standardized Makefile. Triggers when a user asks to make their Go app "agent-ready," "AI-friendly," wants to improve agent tooling/observability in a Go project, or needs to audit an existing Go project against agent-readiness best practices.

日本語の概要は準備中です。原文の説明を表示しています。

dirien/yet-another-agent-harness202026年5月31日 更新

Use when creating or updating AGENTS.md files, .github/copilot-instructions.md, or other AI agent rule files, onboarding AI agents to a project, standardizing agent documentation, or when anyone mentions AGENTS.md, agent rules, project onboarding, or codebase documentation for AI agents.

日本語の概要は準備中です。原文の説明を表示しています。

dirien/yet-another-agent-harness202026年5月31日 更新

Use when designing new high-level system architecture, reviewing existing designs, or making architectural decisions. Invoke to create architecture diagrams, write Architecture Decision Records (ADRs), evaluate technology trade-offs, design component interactions, and plan for scalability. Use for system design, architecture review, microservices structuring, ADR authoring, scalability planning, and infrastructure pattern selection — distinct from code-level design patterns or database-only design tasks.

日本語の概要は準備中です。原文の説明を表示しています。

dirien/yet-another-agent-harness202026年5月31日 更新

Use when building CLI tools, implementing argument parsing, or adding interactive prompts. Invoke for parsing flags and subcommands, displaying progress bars and spinners, generating bash/zsh/fish completion scripts, CLI design, shell completions, and cross-platform terminal applications using commander, click, typer, or cobra.

日本語の概要は準備中です。原文の説明を表示しています。

dirien/yet-another-agent-harness202026年5月31日 更新

Convert an AWS CloudFormation stack or template to Pulumi. This skill MUST be loaded whenever a user requests migration or conversion of CloudFormation to Pulumi.

日本語の概要は準備中です。原文の説明を表示しています。

dirien/yet-another-agent-harness202026年5月31日 更新

Analyzes code diffs and files to identify bugs, security vulnerabilities (SQL injection, XSS, insecure deserialization), code smells, N+1 queries, naming issues, and architectural concerns, then produces a structured review report with prioritized, actionable feedback. Use when reviewing pull requests, conducting code quality audits, identifying refactoring opportunities, or checking for security issues. Invoke for PR reviews, code quality checks, refactoring suggestions, review code, code quality. Complements specialized skills (security-reviewer, test-master) by providing broad-scope review across correctness, performance, maintainability, and test coverage in a single pass.

日本語の概要は準備中です。原文の説明を表示しています。

dirien/yet-another-agent-harness202026年5月31日 更新

dirien のスキルをすべて見る

このスキルの問題を報告する