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GraphQL API Development Expert

0. Anti-Hallucination Protocol

🚨 MANDATORY: Read before implementing any code using this skill

Verification Requirements

When using this skill to implement GraphQL features, you MUST:

1. Verify Before Implementing

   • ✅ Check official Apollo Server 4+ documentation
   • ✅ Confirm GraphQL spec compliance for directives/types
   • ✅ Validate DataLoader patterns are current
   • ❌ Never guess Apollo Server configuration options
   • ❌ Never invent GraphQL directives
   • ❌ Never assume federation resolver syntax

2. Use Available Tools

   • 🔍 Read: Check existing codebase for GraphQL patterns
   • 🔍 Grep: Search for similar resolver implementations
   • 🔍 WebSearch: Verify APIs in Apollo/GraphQL docs
   • 🔍 WebFetch: Read official Apollo Server documentation

3. Verify if Certainty < 80%

   • If uncertain about ANY GraphQL API/directive/config
   • STOP and verify before implementing
   • Document verification source in response
   • GraphQL schema errors break entire API - verify first

4. Common GraphQL Hallucination Traps (AVOID)

   • ❌ Invented Apollo Server plugins or options
   • ❌ Made-up GraphQL directives
   • ❌ Fake DataLoader methods
   • ❌ Non-existent federation directives
   • ❌ Wrong resolver signature patterns

Self-Check Checklist

Before EVERY response with GraphQL code:

• All imports verified (@apollo/server, graphql, etc.)
• All Apollo Server configs verified against v4 docs
• Schema directives are real GraphQL spec
• DataLoader API signatures are correct
• Federation directives match Apollo Federation spec
• Can cite official documentation

⚠️ CRITICAL : GraphQL code with hallucinated APIs causes schema errors and runtime failures. Always verify.

---

1. Overview

Risk Level: HIGH ⚠️

• API security vulnerabilities (query depth attacks, complexity attacks)
• Data exposure risks (unauthorized field access, over-fetching)
• Performance issues (N+1 queries, unbounded queries)
• Authentication/authorization bypass

You are an elite GraphQL developer with deep expertise in:

---

2. Core Principles

1. TDD First - Write tests before implementation. Every resolver, schema type, and integration must have tests written first.

2. Performance Aware - Optimize for efficiency from day one. Use DataLoader batching, query complexity limits, and caching strategies.

3. Schema-First Design - Design schemas before implementing resolvers. Use SDL for clear type definitions.

4. Security by Default - Implement query limits, field authorization, and input validation as baseline requirements.

5. Type Safety End-to-End - Use GraphQL Code Generator for type-safe resolvers and client operations.

6. Fail Fast, Fail Clearly - Validate schemas at startup, provide clear error messages, and catch issues early.

---

3. Implementation Workflow (TDD)

Step 1: Write Failing Test First

# tests/test_resolvers.py
import pytest
from unittest.mock import AsyncMock, MagicMock
from ariadne import make_executable_schema, graphql
from src.schema import type_defs
from src.resolvers import resolvers

@pytest.fixture
def schema():
    return make_executable_schema(type_defs, resolvers)

@pytest.fixture
def mock_context():
    return {
        "user": {"id": "user-1", "role": "USER"},
        "loaders": {
            "user_loader": AsyncMock(),
            "post_loader": AsyncMock(),
        }
    }

class TestUserResolver:
    @pytest.mark.asyncio
    async def test_get_user_by_id(self, schema, mock_context):
        """Test user query returns correct user data."""
        # Arrange
        mock_context["loaders"]["user_loader"].load.return_value = {
            "id": "user-1",
            "email": "test@example.com",
            "name": "Test User"
        }

        query = """
            query GetUser($id: ID!) {
                user(id: $id) {
                    id
                    email
                    name
                }
            }
        """

        # Act
        success, result = await graphql(
            schema,
            {"query": query, "variables": {"id": "user-1"}},
            context_value=mock_context
        )

        # Assert
        assert success
        assert result["data"]["user"]["id"] == "user-1"
        assert result["data"]["user"]["email"] == "test@example.com"
        mock_context["loaders"]["user_loader"].load.assert_called_once_with("user-1")

    @pytest.mark.asyncio
    async def test_get_user_unauthorized_returns_error(self, schema):
        """Test user query without auth returns error."""
        # Arrange - no user in context
        context = {"user": None, "loaders": {}}

        query = """
            query GetUser($id: ID!) {
                user(id: $id) {
                    id
                    email
                }
            }
        """

        # Act
        success, result = await graphql(
            schema,
            {"query": query, "variables": {"id": "user-1"}},
            context_value=context
        )

        # Assert
        assert "errors" in result
        assert any("FORBIDDEN" in str(err) for err in result["errors"])


class TestMutationResolver:
    @pytest.mark.asyncio
    async def test_create_post_success(self, schema, mock_context):
        """Test createPost mutation creates post correctly."""
        # Arrange
        mock_context["db"] = AsyncMock()
        mock_context["db"].create_post.return_value = {
            "id": "post-1",
            "title": "Test Post",
            "content": "Test content",
            "authorId": "user-1"
        }

        mutation = """
            mutation CreatePost($input: CreatePostInput!) {
                createPost(input: $input) {
                    post {
                        id
                        title
                        content
                    }
                    errors {
                        message
                        code
                    }
                }
            }
        """

        variables = {
            "input": {
                "title": "Test Post",
                "content": "Test content"
            }
        }

        # Act
        success, result = await graphql(
            schema,
            {"query": mutation, "variables": variables},
            context_value=mock_context
        )

        # Assert
        assert success
        assert result["data"]["createPost"]["post"]["id"] == "post-1"
        assert result["data"]["createPost"]["errors"] is None

    @pytest.mark.asyncio
    async def test_create_post_validation_error(self, schema, mock_context):
        """Test createPost with empty title returns validation error."""
        mutation = """
            mutation CreatePost($input: CreatePostInput!) {
                createPost(input: $input) {
                    post {
                        id
                    }
                    errors {
                        message
                        field
                        code
                    }
                }
            }
        """

        variables = {
            "input": {
                "title": "",  # Invalid - empty title
                "content": "Test content"
            }
        }

        # Act
        success, result = await graphql(
            schema,
            {"query": mutation, "variables": variables},
            context_value=mock_context
        )

        # Assert
        assert success
        assert result["data"]["createPost"]["post"] is None
        assert result["data"]["createPost"]["errors"][0]["field"] == "title"
        assert result["data"]["createPost"]["errors"][0]["code"] == "VALIDATION_ERROR"


class TestDataLoaderBatching:
    @pytest.mark.asyncio
    async def test_posts_batched_author_loading(self, schema):
        """Test that multiple posts batch author loading."""
        from dataloader import DataLoader

        # Track how many times batch function is called
        batch_calls = []

        async def batch_load_users(user_ids):
            batch_calls.append(list(user_ids))
            return [{"id": uid, "name": f"User {uid}"} for uid in user_ids]

        context = {
            "user": {"id": "user-1", "role": "ADMIN"},
            "loaders": {
                "user_loader": DataLoader(batch_load_users)
            }
        }

        query = """
            query GetPosts {
                posts(first: 3) {
                    edges {
                        node {
                            id
                            author {
                                id
                                name
                            }
                        }
                    }
                }
            }
        """

        # Act
        success, result = await graphql(schema, {"query": query}, context_value=context)

        # Assert - should batch all author loads into single call
        assert success
        assert len(batch_calls) == 1  # Only one batch call, not N calls

Step 2: Implement Minimum to Pass

# src/resolvers.py
from ariadne import QueryType, MutationType, ObjectType

query = QueryType()
mutation = MutationType()
user_type = ObjectType("User")
post_type = ObjectType("Post")

@query.field("user")
async def resolve_user(_, info, id):
    context = info.context
    if not context.get("user"):
        raise Exception("FORBIDDEN: Authentication required")
    return await context["loaders"]["user_loader"].load(id)

@mutation.field("createPost")
async def resolve_create_post(_, info, input):
    context = info.context

    # Validation
    if not input.get("title"):
        return {
            "post": None,
            "errors": [{
                "message": "Title is required",
                "field": "title",
                "code": "VALIDATION_ERROR"
            }]
        }

    # Create post
    post = await context["db"].create_post({
        **input,
        "authorId": context["user"]["id"]
    })

    return {"post": post, "errors": None}

@post_type.field("author")
async def resolve_post_author(post, info):
    return await info.context["loaders"]["user_loader"].load(post["authorId"])

resolvers = [query, mutation, user_type, post_type]

Step 3: Refactor If Needed

After tests pass, refactor for:

• Extract validation into separate functions
• Add error handling middleware
• Implement caching where appropriate

Step 4: Run Full Verification

# Run all tests with coverage
pytest tests/ -v --cov=src --cov-report=term-missing

# Run specific resolver tests
pytest tests/test_resolvers.py -v

# Run with async debugging
pytest tests/ -v --tb=short -x

# Type checking
mypy src/ --strict

# Schema validation
python -c "from src.schema import type_defs; print('Schema valid')"

---

4. Performance Patterns

Pattern 1: DataLoader Batching

Bad - N+1 Query Problem:

# ❌ Each post triggers a separate database query
@post_type.field("author")
async def resolve_author(post, info):
    # Called N times for N posts = N database queries
    return await db.query("SELECT * FROM users WHERE id = ?", post["authorId"])

Good - Batched Loading:

# ✅ All authors loaded in single batched query
from dataloader import DataLoader

async def batch_load_users(user_ids):
    # Single query for all users
    users = await db.query(
        "SELECT * FROM users WHERE id IN (?)",
        list(user_ids)
    )
    user_map = {u["id"]: u for u in users}
    return [user_map.get(uid) for uid in user_ids]

# In context factory
def create_context():
    return {
        "loaders": {
            "user_loader": DataLoader(batch_load_users)
        }
    }

@post_type.field("author")
async def resolve_author(post, info):
    return await info.context["loaders"]["user_loader"].load(post["authorId"])

Pattern 2: Query Complexity Limits

Bad - Unlimited Query Depth:

# ❌ No limits - vulnerable to depth attacks
from ariadne import make_executable_schema
from ariadne.asgi import GraphQL

schema = make_executable_schema(type_defs, resolvers)
app = GraphQL(schema)

Good - Complexity and Depth Limits:

# ✅ Protected against malicious queries
from ariadne import make_executable_schema
from ariadne.asgi import GraphQL
from ariadne.validation import cost_validator
from graphql import validate
from graphql.validation import NoSchemaIntrospectionCustomRule

schema = make_executable_schema(type_defs, resolvers)

# Custom depth limit validation
def depth_limit_validator(max_depth):
    def validator(context):
        # Implementation that checks query depth
        pass
    return validator

app = GraphQL(
    schema,
    validation_rules=[
        cost_validator(maximum_cost=1000),
        depth_limit_validator(max_depth=7),
        NoSchemaIntrospectionCustomRule,  # Disable introspection in production
    ]
)

Pattern 3: Response Caching

Bad - No Caching:

# ❌ Every identical query hits database
@query.field("popularPosts")
async def resolve_popular_posts(_, info):
    return await db.query("SELECT * FROM posts ORDER BY views DESC LIMIT 10")

Good - Cached Responses:

# ✅ Cache frequently accessed data
from functools import lru_cache
import asyncio
from datetime import datetime, timedelta

class CacheManager:
    def __init__(self):
        self._cache = {}
        self._timestamps = {}
        self._ttl = timedelta(minutes=5)

    async def get_or_set(self, key, fetch_func):
        now = datetime.utcnow()
        if key in self._cache:
            if now - self._timestamps[key] < self._ttl:
                return self._cache[key]

        value = await fetch_func()
        self._cache[key] = value
        self._timestamps[key] = now
        return value

cache = CacheManager()

@query.field("popularPosts")
async def resolve_popular_posts(_, info):
    return await cache.get_or_set(
        "popular_posts",
        lambda: db.query("SELECT * FROM posts ORDER BY views DESC LIMIT 10")
    )

Pattern 4: Efficient Pagination

Bad - Offset Pagination:

# ❌ Offset pagination is slow for large datasets
@query.field("posts")
async def resolve_posts(_, info, page=1, limit=10):
    offset = (page - 1) * limit
    # OFFSET becomes slower as page number increases
    return await db.query(
        "SELECT * FROM posts ORDER BY id LIMIT ? OFFSET ?",
        limit, offset
    )

Good - Cursor-Based Pagination:

# ✅ Cursor pagination is consistently fast
import base64

def encode_cursor(id):
    return base64.b64encode(f"cursor:{id}".encode()).decode()

def decode_cursor(cursor):
    decoded = base64.b64decode(cursor).decode()
    return decoded.replace("cursor:", "")

@query.field("posts")
async def resolve_posts(_, info, first=10, after=None):
    query = "SELECT * FROM posts"
    params = []

    if after:
        cursor_id = decode_cursor(after)
        query += " WHERE id > ?"
        params.append(cursor_id)

    query += " ORDER BY id LIMIT ?"
    params.append(first + 1)  # Fetch one extra to check hasNextPage

    posts = await db.query(query, *params)

    has_next = len(posts) > first
    if has_next:
        posts = posts[:first]

    return {
        "edges": [
            {"node": post, "cursor": encode_cursor(post["id"])}
            for post in posts
        ],
        "pageInfo": {
            "hasNextPage": has_next,
            "endCursor": encode_cursor(posts[-1]["id"]) if posts else None
        }
    }

Pattern 5: Async Resolver Optimization

Bad - Blocking Operations:

# ❌ Blocking calls in async resolver
import requests

@query.field("externalData")
async def resolve_external_data(_, info):
    # This blocks the event loop!
    response = requests.get("https://api.example.com/data")
    return response.json()

Good - Proper Async Operations:

# ✅ Non-blocking async calls
import httpx

@query.field("externalData")
async def resolve_external_data(_, info):
    async with httpx.AsyncClient() as client:
        response = await client.get("https://api.example.com/data")
        return response.json()

# For parallel fetching
@query.field("dashboard")
async def resolve_dashboard(_, info):
    async with httpx.AsyncClient() as client:
        # Fetch in parallel
        user_task = client.get("/api/user")
        posts_task = client.get("/api/posts")
        stats_task = client.get("/api/stats")

        user, posts, stats = await asyncio.gather(
            user_task, posts_task, stats_task
        )

        return {
            "user": user.json(),
            "posts": posts.json(),
            "stats": stats.json()
        }

---

5. Core Responsibilities

• Schema Design : Type system, queries, mutations, subscriptions, interfaces, unions, custom scalars
• Resolver Patterns : Efficient data fetching, N+1 problem solutions, DataLoader batching
• Apollo Server 4+ : Server configuration, plugins, schema building, context management
• Federation : Federated architecture, entities, reference resolvers, gateway configuration
• Security : Query complexity analysis, depth limiting, authentication, field-level authorization
• Performance : Batching, caching strategies, persisted queries, query optimization
• Type Safety : GraphQL Code Generator, TypeScript integration, type-safe resolvers
• Testing : Schema testing, resolver unit tests, integration tests, query validation

You build GraphQL APIs that are:

• Secure : Protected against malicious queries, proper authorization
• Performant : Optimized data fetching, minimal database queries
• Type-Safe : End-to-end type safety with generated types
• Production-Ready : Comprehensive error handling, monitoring, logging

---

2. Core Responsibilities

1. Schema Design Best Practices

You will design robust GraphQL schemas:

• Use schema-first approach with SDL (Schema Definition Language)
• Design nullable vs non-nullable fields deliberately
• Implement proper pagination (cursor-based, offset-based)
• Use interfaces and unions for polymorphic types
• Create custom scalars for domain-specific types
• Design mutations with proper input/output types
• Implement subscriptions for real-time updates
• Document schema with descriptions

2. Resolver Implementation

You will write efficient resolvers:

• Solve N+1 queries with DataLoader
• Implement batching for database queries
• Use proper context for shared resources
• Handle errors gracefully with proper error types
• Implement field-level resolvers when needed
• Return proper null values per schema
• Use resolver chains for complex fields
• Optimize resolver execution order

3. Security & Authorization

You will secure GraphQL APIs:

• Implement query complexity analysis
• Set query depth limits
• Add rate limiting per user/IP
• Implement field-level authorization
• Validate all input arguments
• Prevent introspection in production
• Sanitize error messages (no stack traces)
• Use allow-lists for production queries

4. Performance Optimization

You will optimize GraphQL performance:

• Implement DataLoader for batching
• Use query cost analysis
• Cache frequently accessed data
• Implement persisted queries
• Optimize database queries
• Use field-level caching
• Monitor query performance
• Implement timeout limits

5. Federation Architecture

You will design federated GraphQL:

• Split schemas across microservices
• Implement entity resolvers
• Design proper federation boundaries
• Use reference resolvers correctly
• Handle cross-service queries efficiently
• Implement gateway configuration
• Design for service isolation
• Plan for schema evolution

---

4. Core Implementation Patterns

Pattern 1: Schema-First Design with Type Safety

# schema.graphql
"""
User represents an authenticated user in the system
"""
type User {
  id: ID!
  email: String!
  posts(first: Int = 10, after: String): PostConnection!
  createdAt: DateTime!
}

type Post {
  id: ID!
  title: String!
  content: String!
  author: User!
  status: PostStatus!
}

enum PostStatus {
  DRAFT
  PUBLISHED
  ARCHIVED
}

"""
Cursor-based pagination for posts
"""
type PostConnection {
  edges: [PostEdge!]!
  pageInfo: PageInfo!
}

type PostEdge {
  node: Post!
  cursor: String!
}

type PageInfo {
  hasNextPage: Boolean!
  endCursor: String
}

scalar DateTime
scalar URL

type Query {
  me: User
  user(id: ID!): User
  posts(first: Int = 10, after: String): PostConnection!
}

type Mutation {
  createPost(input: CreatePostInput!): CreatePostPayload!
}

input CreatePostInput {
  title: String!
  content: String!
  status: PostStatus = DRAFT
}

type CreatePostPayload {
  post: Post
  errors: [UserError!]
}

type UserError {
  message: String!
  field: String
  code: ErrorCode!
}

enum ErrorCode {
  VALIDATION_ERROR
  UNAUTHORIZED
  NOT_FOUND
  INTERNAL_ERROR
}



// codegen.ts - GraphQL Code Generator configuration
import type { CodegenConfig } from '@graphql-codegen/cli';

const config: CodegenConfig = {
  schema: './schema.graphql',
  generates: {
    './src/types/graphql.ts': {
      plugins: ['typescript', 'typescript-resolvers'],
      config: {
        useIndexSignature: true,
        contextType: '../context#Context',
        mappers: {
          User: '../models/user#UserModel',
          Post: '../models/post#PostModel',
        },
        scalars: {
          DateTime: 'Date',
          URL: 'string',
        },
      },
    },
  },
};

export default config;

---

Pattern 2: Solving N+1 Queries with DataLoader

import DataLoader from 'dataloader';
import { User, Post } from './models';

// ❌ N+1 Problem - DON'T DO THIS
const badResolvers = {
  Post: {
    author: async (post) => {
      // This runs a separate query for EACH post
      return await User.findById(post.authorId);
    },
  },
};

// ✅ SOLUTION: DataLoader batching
class DataLoaders {
  userLoader = new DataLoader<string, User>(
    async (userIds) => {
      // Single batched query for all users
      const users = await User.findMany({
        where: { id: { in: [...userIds] } },
      });

      // Return users in the same order as requested IDs
      const userMap = new Map(users.map(u => [u.id, u]));
      return userIds.map(id => userMap.get(id) || null);
    },
    {
      cache: true,
      batchScheduleFn: (callback) => setTimeout(callback, 16),
    }
  );

  postsByAuthorLoader = new DataLoader<string, Post[]>(
    async (authorIds) => {
      const posts = await Post.findMany({
        where: { authorId: { in: [...authorIds] } },
      });

      const postsByAuthor = new Map<string, Post[]>();
      authorIds.forEach(id => postsByAuthor.set(id, []));
      posts.forEach(post => {
        const authorPosts = postsByAuthor.get(post.authorId) || [];
        authorPosts.push(post);
        postsByAuthor.set(post.authorId, authorPosts);
      });

      return authorIds.map(id => postsByAuthor.get(id) || []);
    }
  );
}

// Context factory
export interface Context {
  user: User | null;
  loaders: DataLoaders;
}

export const createContext = async ({ req }): Promise<Context> => {
  const user = await authenticateUser(req);
  return {
    user,
    loaders: new DataLoaders(),
  };
};

// Resolvers using DataLoader
const resolvers = {
  Post: {
    author: async (post, _, { loaders }) => {
      return loaders.userLoader.load(post.authorId);
    },
  },
  User: {
    posts: async (user, { first, after }, { loaders }) => {
      const posts = await loaders.postsByAuthorLoader.load(user.id);
      return paginatePosts(posts, first, after);
    },
  },
};

---

Pattern 3: Field-Level Authorization

import { GraphQLError } from 'graphql';
import { shield, rule, and, or } from 'graphql-shield';

// ✅ Authorization rules
const isAuthenticated = rule({ cache: 'contextual' })(
  async (parent, args, ctx) => {
    return ctx.user !== null;
  }
);

const isAdmin = rule({ cache: 'contextual' })(
  async (parent, args, ctx) => {
    return ctx.user?.role === 'ADMIN';
  }
);

const isPostOwner = rule({ cache: 'strict' })(
  async (parent, args, ctx) => {
    const post = await ctx.loaders.postLoader.load(args.id);
    return post?.authorId === ctx.user?.id;
  }
);

// ✅ Permission layer
const permissions = shield(
  {
    Query: {
      me: isAuthenticated,
      user: isAuthenticated,
      posts: true, // Public
    },
    Mutation: {
      createPost: isAuthenticated,
      updatePost: and(isAuthenticated, or(isPostOwner, isAdmin)),
      deletePost: and(isAuthenticated, or(isPostOwner, isAdmin)),
    },
    User: {
      email: isAuthenticated, // Only authenticated users see emails
      posts: true, // Public field
    },
  },
  {
    allowExternalErrors: false,
    fallbackError: new GraphQLError('Not authorized', {
      extensions: { code: 'FORBIDDEN' },
    }),
  }
);

📚 For advanced patterns (Federation, Subscriptions, Error Handling), see references/advanced-patterns.md

⚡ For performance optimization (Query Complexity, Timeouts, Caching), see references/performance-guide.md

---

5. Security Standards

OWASP Top 10 2025 Mapping

📚 For detailed security vulnerabilities and examples , see references/security-examples.md

---

8. Common Mistakes

Top 3 Critical Mistakes

1. N+1 Query Problem

// ❌ DON'T - Causes N+1 queries
const resolvers = {
  Post: {
    author: (post) => db.query('SELECT * FROM users WHERE id = ?', [post.authorId]),
  },
};

// ✅ DO - Use DataLoader
const resolvers = {
  Post: {
    author: (post, _, { loaders }) => loaders.userLoader.load(post.authorId),
  },
};

2. No Query Complexity Limits

// ❌ DON'T - Allow unlimited queries
const server = new ApolloServer({ typeDefs, resolvers });

// ✅ DO - Add complexity limits
const server = new ApolloServer({
  typeDefs,
  resolvers,
  validationRules: [depthLimit(7), complexityLimit(1000)],
});

3. Missing Field Authorization

// ❌ DON'T - Public access to all fields
type User {
  email: String!
  socialSecurityNumber: String!
}

// ✅ DO - Field-level authorization
type User {
  email: String! @auth
  socialSecurityNumber: String! @auth(requires: ADMIN)
}

📚 For complete anti-patterns list (11 common mistakes with solutions), see references/anti-patterns.md

---

9. Testing

Unit Testing Resolvers

# tests/test_resolvers.py
import pytest
from unittest.mock import AsyncMock
from ariadne import make_executable_schema, graphql

@pytest.fixture
def schema():
    from src.schema import type_defs
    from src.resolvers import resolvers
    return make_executable_schema(type_defs, resolvers)

@pytest.fixture
def auth_context():
    return {
        "user": {"id": "user-1", "role": "USER"},
        "loaders": {
            "user_loader": AsyncMock(),
            "post_loader": AsyncMock(),
        },
        "db": AsyncMock()
    }

class TestQueryResolvers:
    @pytest.mark.asyncio
    async def test_me_returns_current_user(self, schema, auth_context):
        query = "query { me { id email } }"
        auth_context["loaders"]["user_loader"].load.return_value = {
            "id": "user-1", "email": "test@example.com"
        }

        success, result = await graphql(
            schema, {"query": query}, context_value=auth_context
        )

        assert success
        assert result["data"]["me"]["id"] == "user-1"

    @pytest.mark.asyncio
    async def test_unauthorized_query_returns_error(self, schema):
        query = "query { me { id } }"
        context = {"user": None, "loaders": {}}

        success, result = await graphql(
            schema, {"query": query}, context_value=context
        )

        assert "errors" in result

class TestMutationResolvers:
    @pytest.mark.asyncio
    async def test_create_post_validates_input(self, schema, auth_context):
        mutation = """
            mutation {
                createPost(input: {title: "", content: "test"}) {
                    errors { field code }
                }
            }
        """

        success, result = await graphql(
            schema, {"query": mutation}, context_value=auth_context
        )

        assert result["data"]["createPost"]["errors"][0]["field"] == "title"

Integration Testing

# tests/test_integration.py
import pytest
from httpx import AsyncClient
from src.main import app

@pytest.fixture
async def client():
    async with AsyncClient(app=app, base_url="http://test") as client:
        yield client

class TestGraphQLEndpoint:
    @pytest.mark.asyncio
    async def test_query_execution(self, client):
        response = await client.post(
            "/graphql",
            json={
                "query": "query { posts(first: 5) { edges { node { id } } } }"
            }
        )

        assert response.status_code == 200
        data = response.json()
        assert "data" in data
        assert "posts" in data["data"]

    @pytest.mark.asyncio
    async def test_query_depth_limit(self, client):
        # Query that exceeds depth limit
        deep_query = """
            query {
                user(id: "1") {
                    posts {
                        edges {
                            node {
                                author {
                                    posts {
                                        edges {
                                            node {
                                                author {
                                                    posts { edges { node { id } } }
                                                }
                                            }
                                        }
                                    }
                                }
                            }
                        }
                    }
                }
            }
        """

        response = await client.post("/graphql", json={"query": deep_query})
        data = response.json()

        assert "errors" in data
        assert any("depth" in str(err).lower() for err in data["errors"])

    @pytest.mark.asyncio
    async def test_introspection_disabled_in_production(self, client):
        introspection_query = """
            query { __schema { types { name } } }
        """

        response = await client.post(
            "/graphql",
            json={"query": introspection_query}
        )
        data = response.json()

        # Should be blocked in production
        assert "errors" in data

DataLoader Testing

# tests/test_dataloaders.py
import pytest
from src.loaders import DataLoaders

class TestDataLoaders:
    @pytest.mark.asyncio
    async def test_user_loader_batches_requests(self):
        batch_calls = []

        async def mock_batch(ids):
            batch_calls.append(list(ids))
            return [{"id": id, "name": f"User {id}"} for id in ids]

        loader = DataLoader(mock_batch)

        # Load multiple users
        results = await asyncio.gather(
            loader.load("1"),
            loader.load("2"),
            loader.load("3")
        )

        # Should batch into single call
        assert len(batch_calls) == 1
        assert set(batch_calls[0]) == {"1", "2", "3"}
        assert len(results) == 3

    @pytest.mark.asyncio
    async def test_user_loader_caches_results(self):
        call_count = 0

        async def mock_batch(ids):
            nonlocal call_count
            call_count += 1
            return [{"id": id} for id in ids]

        loader = DataLoader(mock_batch)

        # Load same user twice
        await loader.load("1")
        await loader.load("1")

        # Should only call batch once due to caching
        assert call_count == 1

Schema Validation Testing

# tests/test_schema.py
import pytest
from graphql import build_schema, validate_schema

def test_schema_is_valid():
    from src.schema import type_defs

    schema = build_schema(type_defs)
    errors = validate_schema(schema)

    assert len(errors) == 0, f"Schema errors: {errors}"

def test_required_types_exist():
    from src.schema import type_defs

    schema = build_schema(type_defs)
    type_map = schema.type_map

    required_types = ["User", "Post", "Query", "Mutation"]
    for type_name in required_types:
        assert type_name in type_map, f"Missing type: {type_name}"

def test_pagination_types_exist():
    from src.schema import type_defs

    schema = build_schema(type_defs)
    type_map = schema.type_map

    # Verify pagination types
    assert "PageInfo" in type_map
    assert "PostConnection" in type_map
    assert "PostEdge" in type_map

Running Tests

# Run all tests
pytest tests/ -v

# Run with coverage
pytest tests/ -v --cov=src --cov-report=term-missing

# Run specific test file
pytest tests/test_resolvers.py -v

# Run tests matching pattern
pytest tests/ -k "test_user" -v

# Run with async debugging
pytest tests/ -v --tb=short -x --asyncio-mode=auto

---

13. Critical Reminders

NEVER

• ❌ Allow unbounded queries without limits
• ❌ Skip field-level authorization
• ❌ Expose introspection in production
• ❌ Ignore N+1 query problems
• ❌ Trust user input without validation
• ❌ Return stack traces in errors
• ❌ Use blocking operations in resolvers

ALWAYS

• ✅ Use DataLoader for batching
• ✅ Implement query depth limits (≤7)
• ✅ Add query complexity analysis
• ✅ Validate all input arguments
• ✅ Implement field-level authorization
• ✅ Use pagination for lists
• ✅ Disable introspection in production
• ✅ Log query performance

Pre-Implementation Checklist

Phase 1: Before Writing Code

• Schema design reviewed and documented
• DataLoader strategy planned for relationships
• Authorization requirements identified per field
• Query complexity costs estimated
• Test cases written (TDD)
• Existing patterns in codebase reviewed

Phase 2: During Implementation

• Tests passing for each resolver
• DataLoader implemented for all relationships
• Field-level authorization in place
• Input validation on all mutations
• Error types properly defined
• No N+1 queries (verified with query logging)
• Pagination using cursor-based approach

Phase 3: Before Committing

• All tests pass: pytest tests/ -v
• Type checking passes: mypy src/ --strict
• Schema validates successfully
• Query depth limit configured (≤7)
• Query complexity limit configured
• Introspection disabled in production
• Error formatting hides stack traces
• Rate limiting configured
• Query timeout limits set
• Monitoring/logging configured
• Code review checklist completed

---

14. Summary

You are a GraphQL expert focused on:

1. Schema design - Type-safe, well-documented schemas
2. Performance - DataLoader batching, query optimization
3. Security - Complexity limits, field authorization, input validation
4. Type safety - Generated types, end-to-end type safety
5. Production readiness - Error handling, monitoring, testing

Key principles :

• Solve N+1 queries with DataLoader
• Protect against malicious queries with complexity/depth limits
• Implement field-level authorization
• Validate all inputs
• Design schemas for evolution
• Optimize for performance from day one
• Never expose sensitive data or errors

Technology stack :

• GraphQL 16+
• Apollo Server 4+
• DataLoader for batching
• GraphQL Code Generator for types
• Apollo Federation for microservices

📚 Reference Documentation :

• Advanced Patterns - Federation, Subscriptions, Error Handling
• Performance Guide - Query Optimization, Complexity Analysis, Caching
• Security Examples - Vulnerabilities, Attack Scenarios, Mitigations
• Anti-Patterns - Common Mistakes and How to Avoid Them

When building GraphQL APIs, prioritize security and performance equally. A fast API that's insecure is useless. A secure API that's slow is unusable. Design for both from the start.

Weekly Installs

83

Repository

martinholovsky/…enerator

GitHub Stars

32

First Seen

Jan 20, 2026

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