Deserialization
Deserialization is the process of reconstructing structured data or in-memory values from a serialized representation.
Kotlin in Action, 2E
Deserialization is the process of reconstructing objects or other in-memory data from a serialized representation.
- How it is used
- Uses JSON input to create Kotlin objects, from small factories to a reflection-based library pipeline.
- How deep it goes
- Traces lexer, parser, object seeds, reflection-based constructor calls, type conversion, validation, and reflection caching.
- Examples
- Uses Person, Author, and Book JSON inputs, plus annotated property names and excluded optional values.
- What you can do after
- Evaluate/understand how a Kotlin JSON deserializer parses input, converts values, and constructs objects through reflection.
Data-Oriented Programming: Reduce software complexity
Deserialization is the conversion of a serialized representation back into structured data, including JSON text in the JSON-specific sense.
- How it is used
- Uses deserialization to turn JSON inputs, captured debugging data, and test fixtures into structures that program logic can inspect.
- How deep it goes
- Defines the conversion and demonstrates JSON.parse, Immutable.fromJS, debugger workflows, and fixture loading, but does not discuss parser internals.
- Examples
- Uses search JSON, Watchmen data, Immutable.js collections, copied nested maps, and captured catalog fixtures as teaching examples.
- What you can do after
- Apply it via JSON.parse to inspect JSON, compare parsed test results, restore immutable collections, and reload captured data.
Read how Data-Oriented Programming: Reduce software complexity explains deserialization →
Go in Practice, Second Edition
Unmarshaling is the process of converting a serialized representation into in-memory data structures.
- How it is used
- Turns persistent JSON configuration and REST payloads into Go values, with a custom INI decoder illustrating the same operation.
- How deep it goes
- Works from JSON file decoding through a reflection-based INI Unmarshal; the custom implementation is limited to structs and supported field kinds.
- Examples
- Uses JSON bytes decoded into a typed value and a tagged Processes struct reconstructed from key-value lines.
- What you can do after
- Build it from scratch for tagged INI structs or apply encoding/json to load configuration into a Go struct.
Read how Go in Practice, Second Edition explains deserialization →
Building User-Friendly DSLs
The reconstruction of structured in-memory data from a stored or transferred representation.
- How it is used
- Restores persisted or HTTP-transferred AST JSON so a frontend can retrieve and use a saved model.
- How deep it goes
- Works through depth-first reconstruction, lookup tables, deferred reference resolution, and observable handling for circular AST references.
- Examples
- Uses saved JSON contents, an Attribute Reference to a Data Attribute, and a circular self-reference AST.
- What you can do after
- Build it from scratch by traversing serialized AST data, indexing objects by ID, and resolving references afterward.
Read how Building User-Friendly DSLs explains deserialization →
Kafka for Architects
Deserialization is the process of converting serialized bytes into structured data according to a schema or agreed data format.
- How it is used
- Turns polled Kafka message bytes into structures a consumer can process.
- How deep it goes
- Explains client configuration, the polling workflow, schema lookup, and failure handling without a low-level deserializer implementation.
- Examples
- Uses matching integer-key and string-value configurations and schema-ID-based decoding to illustrate format agreement.
- What you can do after
- Operate/configure it by matching consumer deserializers to producer formats and planning for malformed messages.
Go in Action, Second Edition
Unmarshaling is the process of reconstructing an in-memory value from a serialized representation.
- How it is used
- Converts structured input into Go values for configuration validation and JSON/XML conversion.
- How deep it goes
- Works through JSON struct mapping, pointer-based unmarshaling, type checks, and custom validation without descending into decoder internals.
- Examples
- Uses a server configuration JSON file, its tagged Go struct, and Host validation through a custom unmarshaler.
- What you can do after
- Apply it via encoding/json to decode configuration bytes into typed values and add domain-specific validation.
Read how Go in Action, Second Edition explains deserialization →
Latency
Deserialization is the conversion of a stored or transmitted representation back into in-memory data structures or objects.
- How it is used
- Uses deserialization to restore networked or stored data for application processing and to identify avoidable latency work.
- How deep it goes
- Explains the transformation, CPU and memory-copy costs, service data flow, and a byte-level Rust example without detailing parser implementation.
- Examples
- Uses an online-store order moving between a Rust struct, JSON, storage, and binary RPC formats.
- What you can do after
- Diagnose deserialization as a latency bottleneck by locating its timing, redundant transformations, CPU use, and memory-copy overhead.
Troubleshooting Java, Second Edition
Deserialization is the process of reconstructing structured data from a serialized byte representation.
- How it is used
- Diagnoses service-communication failures caused by incompatible serialized data and independently evolving contracts.
- How deep it goes
- Explains reconstruction, mismatch symptoms, and compatibility concerns without detailing deserializer internals.
- Examples
- Uses added JSON fields, renamed Protobuf enums, Java version identifiers, and an Order message schema.
- What you can do after
- Diagnose dropped data, default values, and errors by comparing evolving schemas and receiver models.
Read how Troubleshooting Java, Second Edition explains deserialization →
Refactoring to Rust
Deserialization is the conversion of a stored or transmitted representation into in-memory program values.
- How it is used
- Parses JSON objects into typed Rust data structures for subsequent program logic.
- How deep it goes
- Explains generic traits, derived implementations, type inference, dependency setup, successful parsing, and runtime type errors.
- Examples
- Uses name-and-value JSON objects, derived Data structs, compiler errors, runtime type errors, and a Python comparison.
- What you can do after
- Apply it via serde_json to parse JSON strings into typed Rust values and use their fields.
Learn PowerShell in a Month of Lunches: Fourth Edition, Covers Windows, Linux, and macOS
Deserialization is the conversion of a stored or transmitted representation back into an in-memory object or data structure.
- How it is used
- Supports PowerShell remoting by converting remote command output into locally usable data.
- How deep it goes
- Explains XML conversion, snapshots, and action limits, but stops short of internal serialization mechanics.
- Examples
- Demonstrates remote process filtering and contrasts transmitting filtered results with filtering deserialized results locally.
- What you can do after
- Apply it via PowerShell remoting by filtering remote data before transmission and treating received objects as reports or stored data.
Related concepts
- serializationcontrasts with · Serialization is the encoding of structured data or in-memory values into a representation suitable for storage or transmission and later reconstruction.
- JSONuses · JSON is a standardized, language-independent text format for representing structured data using objects, arrays, strings, numbers, Boolean values, and null.
- serdeused by · Serde is a Rust framework for serializing and deserializing data structures across external data formats.
- xmluses · XML is a text-based markup language for encoding structured documents and data using elements, attributes, and nested relationships.
- JSON.parseimplemented by · JSON.parse is a standard JavaScript function that parses a JSON-formatted string into the corresponding JavaScript value.
- clientused by · A client is a person, organization, device, or software component that receives or uses a product, service, resource, or functionality provided by another entity.
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