Handling Data Transformation

1. Transforming Request Data

Transformation	Example
Trim whitespace	`" alice "` → `"alice"`
Lowercase emails	`"Alice@X.COM"` → `"alice@x.com"`
Normalize phone	`"(555) 123-4567"` → `"+15551234567"`
Parse dates	String → LocalDateTime/Instant
Decode base64	String → byte[]

2. Transforming Response Data

Transformation	Purpose
Entity → DTO	Hide internal fields, shape response
Enum → String	Serialize as readable name
BigDecimal → String	Avoid float precision loss
Lazy → eager loading	Avoid N+1 queries

3. Implementing Data Mapping

Tool	Language	Approach
MapStruct	Java	Compile-time annotation processor
ModelMapper	Java	Runtime reflection
AutoMapper	.NET	Convention-based
class-transformer	TypeScript	Decorator-based

4. Converting Date Formats

Format	Example	Use
ISO 8601	`2026-05-15T10:30:00Z`	Standard for APIs
Unix timestamp	`1747304400`	Compact, no TZ ambiguity
Unix millis	`1747304400000`	JS Date compatibility
RFC 1123 (HTTP)	`Sat, 15 May 2026 10:30:00 GMT`	HTTP headers only

5. Handling Time Zones

Warning: Always store timestamps in UTC. Convert to user's TZ only at presentation layer.

Strategy	Notes
UTC in API	Suffix `Z` in ISO 8601
Include offset	`2026-05-15T10:30:00-05:00`
IANA TZ name	`"timezone": "America/New_York"` (separate field)
Avoid	Local time without offset, abbreviations (EST, PST)

6. Sanitizing User Input

Threat	Mitigation
XSS	HTML-escape before rendering; use CSP
SQL Injection	Parameterized queries / ORMs
NoSQL Injection	Validate object shapes; reject operators
Command Injection	Whitelist; never pass to shell
Path Traversal	Reject `../`, canonicalize paths
Mass Assignment	Allowlist fields (DTO pattern)

7. Implementing Case Conversion

Conversion	Use
snake_case ↔ camelCase	Java backend ↔ JS frontend
Jackson `PropertyNamingStrategy.SNAKE_CASE`	Auto-convert Java fields
JSON.parse with reviver	JS-side conversion

8. Removing Sensitive Fields

Field	Action
Password hashes	Never serialize (Jackson `@JsonIgnore`)
Internal IDs	Strip in DTOs
PII (SSN, DOB)	Mask or omit per role
Tokens / secrets	Never log or return

Example: Field-Level Filtering (Java/Jackson)

public class User {
    private Long id;
    private String email;

    @JsonIgnore
    private String passwordHash;

    @JsonProperty(access = Access.WRITE_ONLY)
    private String currentPassword;
}

9. Implementing Data Enrichment

Enrichment	Source
Computed fields	Server calculation (totals, age from DOB)
Resolved references	Embed related resources (`?expand=author`)
Localized labels	i18n service per Accept-Language
Geocoded addresses	External lookup added to response

10. Using Transformation Libraries

Library	Language	Purpose
Jackson	Java	JSON serialization, custom serializers
MapStruct	Java	DTO ↔ Entity mapping
Lombok	Java	Boilerplate reduction
class-transformer	TS/Node	Plain ↔ class instance
Marshmallow	Python	Schema-based serialization
Pydantic	Python	Model validation + serialization

Related Cheat Sheets

GRPC

Handling Data Transformation

1. Transforming Request Data

2. Transforming Response Data

3. Implementing Data Mapping

4. Converting Date Formats

5. Handling Time Zones

6. Sanitizing User Input

7. Implementing Case Conversion

8. Removing Sensitive Fields

Example: Field-Level Filtering (Java/Jackson)

9. Implementing Data Enrichment

10. Using Transformation Libraries

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