effect-patterns-error-handling

Effect-TS Patterns: Error Handling

This skill provides 3 curated Effect-TS patterns for error handling. Use this skill when working on tasks related to:

• error handling
• Best practices in Effect-TS applications
• Real-world patterns and solutions

🟡 Intermediate Patterns

Error Handling Pattern 1: Accumulating Multiple Errors

Rule: Use error accumulation to report all problems at once rather than failing early, critical for validation and batch operations.

Good Example:

This example demonstrates error accumulation patterns.

import { Effect, Data, Cause } from "effect";

interface ValidationError {
  field: string;
  message: string;
  value?: unknown;
}

interface ProcessingResult<T> {
  successes: T[];
  errors: ValidationError[];
}

// Example 1: Form validation with error accumulation
const program = Effect.gen(function* () {
  console.log(`\n[ERROR ACCUMULATION] Collecting multiple errors\n`);

  // Form data
  interface FormData {
    name: string;
    email: string;
    age: number;
    phone: string;
  }

  const validateForm = (data: FormData): ValidationError[] => {
    const errors: ValidationError[] = [];

    // Validation 1: Name
    if (!data.name || data.name.trim().length === 0) {
      errors.push({
        field: "name",
        message: "Name is required",
        value: data.name,
      });
    } else if (data.name.length < 2) {
      errors.push({
        field: "name",
        message: "Name must be at least 2 characters",
        value: data.name,
      });
    }

    // Validation 2: Email
    if (!data.email) {
      errors.push({
        field: "email",
        message: "Email is required",
        value: data.email,
      });
    } else if (!/^[^\s@]+@[^\s@]+\.[^\s@]+$/.test(data.email)) {
      errors.push({
        field: "email",
        message: "Email format invalid",
        value: data.email,
      });
    }

    // Validation 3: Age
    if (data.age < 0 || data.age > 150) {
      errors.push({
        field: "age",
        message: "Age must be between 0 and 150",
        value: data.age,
      });
    }

    // Validation 4: Phone
    if (data.phone && !/^\d{3}-\d{3}-\d{4}$/.test(data.phone)) {
      errors.push({
        field: "phone",
        message: "Phone must be in format XXX-XXX-XXXX",
        value: data.phone,
      });
    }

    return errors;
  };

  // Example 1: Form with multiple errors
  console.log(`[1] Form validation with multiple errors:\n`);

  const invalidForm: FormData = {
    name: "",
    email: "not-an-email",
    age: 200,
    phone: "invalid",
  };

  const validationErrors = validateForm(invalidForm);

  yield* Effect.log(`[VALIDATION] Found ${validationErrors.length} errors:\n`);

  for (const error of validationErrors) {
    yield* Effect.log(`  ✗ ${error.field}: ${error.message}`);
  }

  // Example 2: Batch processing with partial success
  console.log(`\n[2] Batch processing (accumulate successes and failures):\n`);

  interface Record {
    id: string;
    data: string;
  }

  const processRecord = (record: Record): Result<string> => {
    if (record.id.length === 0) {
      return { success: false, error: "Missing ID" };
    }

    if (record.data.includes("ERROR")) {
      return { success: false, error: "Invalid data" };
    }

    return { success: true, value: `processed-${record.id}` };
  };

  interface Result<T> {
    success: boolean;
    value?: T;
    error?: string;
  }

  const records: Record[] = [
    { id: "rec1", data: "ok" },
    { id: "", data: "ok" }, // Error: missing ID
    { id: "rec3", data: "ok" },
    { id: "rec4", data: "ERROR" }, // Error: invalid data
    { id: "rec5", data: "ok" },
  ];

  const results: ProcessingResult<string> = {
    successes: [],
    errors: [],
  };

  for (const record of records) {
    const result = processRecord(record);

    if (result.success) {
      results.successes.push(result.value!);
    } else {
      results.errors.push({
        field: record.id || "unknown",
        message: result.error!,
      });
    }
  }

  yield* Effect.log(
    `[BATCH] Processed ${records.length} records`
  );
  yield* Effect.log(`[BATCH] ✓ ${results.successes.length} succeeded`);
  yield* Effect.log(`[BATCH] ✗ ${results.errors.length} failed\n`);

  for (const success of results.successes) {
    yield* Effect.log(`  ✓ ${success}`);
  }

  for (const error of results.errors) {
    yield* Effect.log(`  ✗ [${error.field}] ${error.message}`);
  }

  // Example 3: Multi-step validation with error accumulation
  console.log(`\n[3] Multi-step validation (all checks run):\n`);

  interface ServiceHealth {
    diskSpace: boolean;
    memory: boolean;
    network: boolean;
    database: boolean;
  }

  const diagnostics: ValidationError[] = [];

  // Check 1: Disk space
  const diskFree = 50; // MB

  if (diskFree < 100) {
    diagnostics.push({
      field: "disk-space",
      message: `Only ${diskFree}MB free (need 100MB)`,
      value: diskFree,
    });
  }

  // Check 2: Memory
  const memUsage = 95; // percent

  if (memUsage > 85) {
    diagnostics.push({
      field: "memory",
      message: `Using ${memUsage}% (threshold: 85%)`,
      value: memUsage,
    });
  }

  // Check 3: Network
  const latency = 500; // ms

  if (latency > 200) {
    diagnostics.push({
      field: "network",
      message: `Latency ${latency}ms (threshold: 200ms)`,
      value: latency,
    });
  }

  // Check 4: Database
  const dbConnections = 95;
  const dbMax = 100;

  if (dbConnections > dbMax * 0.8) {
    diagnostics.push({
      field: "database",
      message: `${dbConnections}/${dbMax} connections (80% threshold)`,
      value: dbConnections,
    });
  }

  if (diagnostics.length === 0) {
    yield* Effect.log(`[HEALTH] ✓ All systems normal\n`);
  } else {
    yield* Effect.log(
      `[HEALTH] ✗ ${diagnostics.length} issue(s) detected:\n`
    );

    for (const diag of diagnostics) {
      yield* Effect.log(`  ⚠ ${diag.field}: ${diag.message}`);
    }
  }

  // Example 4: Error collection with retry decisions
  console.log(`\n[4] Error collection for retry strategy:\n`);

  interface ErrorWithContext {
    operation: string;
    error: string;
    retryable: boolean;
    timestamp: Date;
  }

  const operationErrors: ErrorWithContext[] = [];

  const operations = [
    { name: "fetch-config", fail: false },
    { name: "connect-db", fail: true },
    { name: "load-cache", fail: true },
    { name: "start-server", fail: false },
  ];

  for (const op of operations) {
    if (op.fail) {
      operationErrors.push({
        operation: op.name,
        error: "Operation failed",
        retryable: op.name !== "fetch-config",
        timestamp: new Date(),
      });
    }
  }

  yield* Effect.log(`[OPERATIONS] ${operationErrors.length} errors:\n`);

  for (const err of operationErrors) {
    const status = err.retryable ? "🔄 retryable" : "❌ non-retryable";
    yield* Effect.log(`  ${status}: ${err.operation}`);
  }

  if (operationErrors.every((e) => e.retryable)) {
    yield* Effect.log(`\n[DECISION] All errors retryable, will retry\n`);
  } else {
    yield* Effect.log(`\n[DECISION] Some non-retryable errors, manual intervention needed\n`);
  }
});

Effect.runPromise(program);

Rationale:

Error accumulation strategies:

• Collect errors: Gather all failures before reporting
• Fail late: Continue processing despite errors
• Contextual errors: Keep error location/operation info
• Error summary: Aggregate for reporting
• Partial success: Return valid results + errors

Pattern: Use Cause aggregation, Result types, or custom error structures

Failing fast causes problems:

Problem 1: Form validation

• User submits form with 10 field errors
• Fail on first error: "Name required"
• User fixes name, submits again
• New error: "Email invalid"
• User submits 10 times before fixing all errors
• Frustration, reduced productivity

Problem 2: Batch processing

• Process 1000 records, fail on record 5
• 995 records not processed
• User manually retries
• Repeats for each error type
• Inefficient

Problem 3: System diagnostics

• Service health check fails
• Report: "Check 1 failed"
• Fix check 1, service still down
• Hidden problem: checks 2, 3, and 4 also failed
• Time wasted diagnosing

Solutions:

Error accumulation:

• Run all validations
• Collect errors
• Report all problems
• User fixes once, not 10 times

Partial success:

• Process all records
• Track successes and failures
• Return: "950 succeeded, 50 failed"
• No re-processing

Comprehensive diagnostics:

• Run all checks
• Report all failures
• Quick root cause analysis
• Faster resolution

🟠 Advanced Patterns

Error Handling Pattern 2: Error Propagation and Chains

Rule: Use error propagation to preserve context through effect chains, enabling debugging and recovery at the right abstraction level.

Good Example:

This example demonstrates error propagation with context.

import { Effect, Data, Cause } from "effect";

// Domain-specific errors with context
class DatabaseError extends Data.TaggedError("DatabaseError")<{
  query: string;
  parameters: unknown[];
  cause: Error;
}> {}

class NetworkError extends Data.TaggedError("NetworkError")<{
  endpoint: string;
  method: string;
  statusCode?: number;
  cause: Error;
}> {}

class ValidationError extends Data.TaggedError("ValidationError")<{
  field: string;
  value: unknown;
  reason: string;
}> {}

class BusinessLogicError extends Data.TaggedError("BusinessLogicError")<{
  operation: string;
  context: Record<string, unknown>;
  originalError: Error;
}> {}

const program = Effect.gen(function* () {
  console.log(`\n[ERROR PROPAGATION] Error chains with context\n`);

  // Example 1: Simple error propagation
  console.log(`[1] Error propagation through layers:\n`);

  const lowLevelOperation = Effect.gen(function* () {
    yield* Effect.log(`[LAYER 1] Low-level operatio

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