4.8 KiB
4.8 KiB
General Code Style Guide
Universal coding principles that apply across all languages and frameworks.
Readability
Code is Read More Than Written
- Write code for humans first, computers second
- Favor clarity over cleverness
- If code needs a comment to explain what it does, consider rewriting it
Formatting
- Consistent indentation (use project standard)
- Reasonable line length (80-120 characters)
- Logical grouping with whitespace
- One statement per line
Structure
- Keep functions/methods short (ideally < 20 lines)
- One level of abstraction per function
- Early returns to reduce nesting
- Group related code together
Naming Conventions
General Principles
- Names should reveal intent
- Avoid abbreviations (except universally understood ones)
- Be consistent within codebase
- Length proportional to scope
Variables
# Bad
d = 86400 # What is this?
temp = getUserData() # Temp what?
# Good
secondsPerDay = 86400
userData = getUserData()
Functions/Methods
- Use verbs for actions:
calculateTotal(),validateInput() - Use
is/has/canfor booleans:isValid(),hasPermission() - Be specific:
sendEmailNotification()notsend()
Constants
- Use SCREAMING_SNAKE_CASE or language convention
- Group related constants
- Document magic numbers
Classes/Types
- Use nouns:
User,OrderProcessor,ValidationResult - Avoid generic names:
Manager,Handler,Data
Comments
When to Comment
- WHY, not WHAT (code shows what, comments explain why)
- Complex algorithms or business logic
- Non-obvious workarounds with references
- Public API documentation
When NOT to Comment
- Obvious code
- Commented-out code (delete it)
- Change history (use git)
- TODOs without tickets (create tickets instead)
Comment Quality
# Bad
i += 1 # Increment i
# Good
# Retry limit based on SLA requirements (see JIRA-1234)
maxRetries = 3
Error Handling
Principles
- Fail fast and explicitly
- Handle errors at appropriate level
- Preserve error context
- Log for debugging, throw for callers
Patterns
# Bad: Silent failure
try:
result = riskyOperation()
except:
pass
# Good: Explicit handling
try:
result = riskyOperation()
except SpecificError as e:
logger.error(f"Operation failed: {e}")
raise OperationFailed("Unable to complete operation") from e
Error Messages
- Be specific about what failed
- Include relevant context
- Suggest remediation when possible
- Avoid exposing internal details to users
Functions and Methods
Single Responsibility
- One function = one task
- If you need "and" to describe it, split it
- Extract helper functions for clarity
Parameters
- Limit parameters (ideally ≤ 3)
- Use objects/structs for many parameters
- Avoid boolean parameters (use named options)
- Order: required first, optional last
Return Values
- Return early for edge cases
- Consistent return types
- Avoid returning null/nil when possible
- Consider Result/Option types for failures
Code Organization
File Structure
- One primary concept per file
- Related helpers in same file or nearby
- Consistent file naming
- Logical directory structure
Import/Dependency Order
- Standard library
- External dependencies
- Internal dependencies
- Local/relative imports
Coupling and Cohesion
- High cohesion within modules
- Low coupling between modules
- Depend on abstractions, not implementations
- Avoid circular dependencies
Testing Considerations
Testable Code
- Pure functions where possible
- Dependency injection
- Avoid global state
- Small, focused functions
Test Naming
# Describe behavior, not implementation
test_user_can_login_with_valid_credentials()
test_order_total_includes_tax_and_shipping()
Security Basics
Input Validation
- Validate all external input
- Sanitize before use
- Whitelist over blacklist
- Fail closed (deny by default)
Secrets
- Never hardcode secrets
- Use environment variables or secret managers
- Don't log sensitive data
- Rotate credentials regularly
Data Handling
- Minimize data collection
- Encrypt sensitive data
- Secure data in transit and at rest
- Follow principle of least privilege
Performance Mindset
Premature Optimization
- Make it work, then make it fast
- Measure before optimizing
- Optimize bottlenecks, not everything
- Document performance-critical code
Common Pitfalls
- N+1 queries
- Unnecessary allocations in loops
- Missing indexes
- Synchronous operations that could be async
Code Review Checklist
- Does it work correctly?
- Is it readable and maintainable?
- Are edge cases handled?
- Is error handling appropriate?
- Are there security concerns?
- Is it tested adequately?
- Does it follow project conventions?
- Is there unnecessary complexity?