🦀 Logy — A Rust-Based Log Analysis Prototype

Overview

Logy is a lightweight command-line log analyzer implemented in Rust, developed as a learning-oriented prototype to explore Rust’s core language features and idiomatic programming patterns.

The project focuses on fundamental systems programming concepts such as structured data parsing, iterator-driven pipelines, explicit error handling, trait-based abstractions, and strong type modeling. While minimal in scope, Logy is intentionally designed to serve as a foundation for future experimentation and incremental expansion.

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Motivation

Rust is increasingly adopted in systems and infrastructure software due to its emphasis on memory safety, predictable performance, and compile-time correctness guarantees. Log analysis represents a practical problem domain well-suited for studying these characteristics, as it involves:

• File and stream-based I/O
• Sequential data processing
• Domain modeling with enums and structs
• Aggregation and filtering operations
• Explicit error propagation and validation

Logy was created to study these aspects in isolation, without the complexity of production-scale tooling.

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Learning Objectives

This project is primarily intended to support learning and experimentation. Key objectives include:

• Understanding Rust’s ownership and borrowing model in practice
• Modeling domain concepts using enums and strongly typed structs
• Applying iterator-based data transformation pipelines
• Handling invalid or partial data safely using Option and Result
• Designing APIs around traits instead of concrete types
• Writing clear, maintainable, and idiomatic Rust code

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Current Capabilities

Logy currently supports:

• Reading logs from files or standard input (stdin)
• Unix-style pipeline composition
• Parsing a fixed, structured log format
• Representing log severity using a strongly typed enum
• Optional filtering by log level
• Date-based filtering using inclusive since / until bounds
• Descending or ascending ordering of log entries by timestamp
• Strict validation mode for rejecting malformed log entries
• JSON output for structured downstream consumption
• Basic aggregation utilities, such as counting entries by severity

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Supported Log Format

YYYY-MM-DD LEVEL Message

Example:

2025-03-21 INFO User login succeeded
2025-03-21 WARN Rate limit approaching
2025-03-21 ERROR Database timeout

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Usage

Run with a log file

cargo run -- app.log

Read from stdin

cat app.log | cargo run --

Filter by log level

cargo run -- app.log --level=ERROR

Enable strict mode (fail on malformed logs)

cat app.log | cargo run -- --strict

Output structured JSON

cat app.log | cargo run -- --json

Filter by date range

cargo run -- app.log --since=2025-03-22 --until=2025-03-22

The --since and --until flags accept dates in YYYY-MM-DD format and apply inclusive filtering based on the log entry timestamp.

Control output ordering

cargo run -- app.log --desc

By default, log entries are processed in ascending chronological order. The --desc flag reverses the ordering to show the most recent entries first.

Combine features

cat app.log | cargo run -- \
  --level=ERROR \
  --since=2025-03-22 \
  --until=2025-03-22 \
  --json \
  --strict \
  --desc

Build optimized binary

cargo build --release

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Project Structure

The project is intentionally kept minimal to emphasize clarity and learning:

logy/
├── src/
│   ├── main.rs        # Program entry point and orchestration
│   ├── cli.rs         # Command-line argument parsing
│   ├── log.rs         # Domain models (LogLevel, LogEntry)
│   ├── parser.rs     # Log line parsing logic
│   ├── reader.rs     # Generic log ingestion (BufRead-based)
│   └── analyzer.rs   # Aggregation and analysis routines
└── Cargo.toml

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Design Philosophy

Logy prioritizes:

• Explicitness over convenience
• Strong typing over string-based representations
• Clear separation between CLI concerns and core logic
• Trait-based abstractions over concrete dependencies
• Simplicity over premature abstraction
• Learning value over feature completeness

As such, the project deliberately avoids advanced features (e.g., async I/O, concurrency, external CLI frameworks) until foundational understanding is established.

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Future Work

As a personal hobby and learning project, Logy may be expanded incrementally to explore more advanced Rust concepts, such as:

• Improved CLI ergonomics and help output
• Additional structured output formats
• Streaming and long-running log processing
• Unit and property-based testing
• Performance benchmarking and profiling
• Support for additional log schemas

These enhancements will be guided by continued study and experimentation with Rust.

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Disclaimer

This project is not intended for production use. It is a learning artifact designed to document progress in understanding Rust and systems programming concepts through hands-on implementation.

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Author’s Note

Logy represents an early step in a longer-term exploration of Rust. The project will evolve organically as understanding deepens, and it serves both as a technical exercise and a reference point for future work.