Comparisons
Compare better-py with other functional programming libraries in Python
Comparisons
See how better-py compares to other functional programming libraries and approaches in Python.
vs Returns Library
better-py
from better_py import Some, Nothing, Ok, Error
# Maybe for optional values
value = Some(42)
result = value.map(lambda x: x * 2)
# Result for error handling
result = Ok(42)
error = Error("something went wrong")Returns
from returns.maybe import Some, Nothing
from returns.result import Success, Failure
# Maybe for optional values
value = Some(42)
result = value.map(lambda x: x * 2)
# Result for error handling
result = Success(42)
failure = Failure("something went wrong")Key Differences
| Feature | better-py | Returns |
|---|---|---|
| Style | Object-oriented with methods | Functional + object mix |
| Type tracking | Full generic inference | Full generic inference |
| Method chaining | Native | Limited |
| Immutability | Frozen dataclasses | Immutable |
| Learning curve | Gentler, Pythonic | Steeper |
| Philosophy | Pragmatic | Academic |
Info: better-py focuses on feeling like natural Python objects, while Returns follows more traditional functional programming patterns.
vs PyMonad
better-py
from better_py import Some, Nothing
value = Some(42)
result = (
value
.map(lambda x: x * 2)
.filter(lambda x: x > 50)
.or_else(0)
)PyMonad
from pymonad.Maybe import Just, Nothing
value = Just(42)
result = value.amap(lambda x: x * 2)
# No built-in filter, or_else, etc.Key Differences
| Feature | better-py | PyMonad |
|---|---|---|
| API completeness | Rich, practical methods | Minimal, academic |
| Method chaining | Full support | Limited |
| Modern Python | Dataclasses, protocols | Older patterns |
| Type hints | Full support | Partial |
| Documentation | Comprehensive | Basic |
vs Option/Maybe from Other Libraries
better-py
from better_py import Some, Nothing
def get_user(id: int) -> Some[User] | Nothing:
if user := db.find(id):
return Some(user)
return Nothing()
user = get_user(1)
name = user.map(lambda u: u.name).or_else("Guest")Optional[T]
from typing import Optional
def get_user(id: int) -> Optional[User]:
return db.find(id)
user = get_user(1)
if user:
name = user.name
else:
name = "Guest"typing-ext
from typing_ext import Option, Some, Nothing
def get_user(id: int) -> Option[User]:
if user := db.find(id):
return Some(user)
return Nothing
name = get_user(1).map_or("Guest", lambda u: u.name)Key Differences
| Feature | better-py | Optional[T] | typing-ext |
|---|---|---|---|
| Safety | Compile-time + runtime | Runtime only | Runtime only |
| Composability | Excellent | Poor | Good |
| Method chaining | Full | None | Good |
| Type narrowing | Automatic | Manual | Limited |
| Pattern matching | Supported | Supported | Limited |
vs Rust's Option and Result
better-py draws inspiration from Rust's excellent error handling:
better-py
from better_py import Some, Nothing, Ok, Error
# Maybe ≈ Option
value = Some(42)
result = value.map(lambda x: x * 2).or_else(0)
# Result ≈ Result
result = Ok(42)
value = result.unwrap_or(0)Rust
// Option
let value = Some(42);
let result = value.map(|x| x * 2).unwrap_or(0);
// Result
let result: Result<i32, &str> = Ok(42);
let value = result.unwrap_or(0);Key Differences
| Feature | better-py | Rust |
|---|---|---|
| Type system | Generic type hints | Algebraic data types |
| Pattern matching | if/is elif/is else | match expressions |
| Compile-time checks | Mypy optional | Built-in |
| Performance | Overhead of objects | Zero-cost |
| Ergonomics | Pythonic idioms | Rust idioms |
Info: better-py aims to bring Rust-like ergonomics to Python, while accepting the limitations of Python's type system.
Summary
Choose better-py if you want:
- ✅ Natural Python object-oriented style
- ✅ Excellent type safety with mypy
- ✅ Rich, composable APIs
- ✅ Modern Python practices (dataclasses, protocols)
- ✅ Comprehensive documentation
Consider alternatives if you need:
- ⚠️ Pure functional programming (use Returns)
- ⚠️ Zero-cost abstractions (use Rust or C++)
- ⚠️ Haskell-style patterns (use PyMonad)
Best Use Cases for better-py:
- New projects starting with modern Python (3.11+)
- Teams familiar with OOP learning FP concepts
- Codebases that value type safety
- Applications requiring robust error handling
- Developers who want practical FP without academic complexity