infiniter 0.2.0

Improved python iterators

Infiniter - Rust-Inspired Iterators for Python

This library provides a rust-inspired improved iterator system to python

Features

• Rust-like method chaining - Fluent API similar to Rust's Iterator trait
• Infinite iterator support - Safe operations on unbounded sequences
• Mathematical sequences - Built-in generators (Fibonacci, primes, triangular numbers, etc.)
• Operator overloading - Use +, -, *, / on iterators
• Lazy evaluation - All operations are lazy until materialization

Quick Start

from infiniter import Iter

# Basic chaining
result = (Iter.range(1, 20)
          .filter(lambda x: x % 2 == 0)
          .map(lambda x: x ** 2)
          .take(5)
          .collect())
# [4, 16, 36, 64, 100]

# Infinite sequences with operators
squares_of_triangles = Iter.triangle_numbers() ** 2
for val in squares_of_triangles.take(5):
    print(val)
# 1, 9, 36, 100, 225

# Element-wise operations on two iterators
result = (Iter.fibonacci() + Iter.primes()).take(5).collect()
# [3, 4, 7, 10, 16]  (1+2, 1+3, 2+5, 3+7, 5+11)

Creating Iterators

From Built-ins

# From ranges
Iter.range(1, 10)           # 1, 2, 3, ..., 9
Iter.range(0, 100, 10)      # 0, 10, 20, ..., 90

# From any iterable
Iter([1, 2, 3])
Iter("hello")
Iter({'a': 1, 'b': 2})

Infinite Iterators

# Counting sequences
Iter.count()                # 0, 1, 2, 3, ...
Iter.count(10)              # 10, 11, 12, 13, ...
Iter.count(0, 2)            # 0, 2, 4, 6, ...

# Cycling
Iter.cycle([1, 2, 3])       # 1, 2, 3, 1, 2, 3, ...

# Repeating
Iter.repeat(5)              # 5, 5, 5, 5, ... (infinite)
Iter.repeat(5, 3)           # 5, 5, 5 (finite)

Mathematical Sequences

# Fibonacci sequence
Iter.fibonacci()            # 1, 1, 2, 3, 5, 8, 13, ...
Iter.fibonacci(0, 1)        # 0, 1, 1, 2, 3, 5, 8, ...

# Prime numbers
Iter.primes()               # 2, 3, 5, 7, 11, 13, 17, ...

# Triangular numbers
Iter.triangle_numbers()     # 1, 3, 6, 10, 15, 21, ...

# Perfect squares
Iter.square()               # 0, 1, 4, 9, 16, 25, ...
Iter.square(1)              # 1, 4, 9, 16, 25, ...

Transformations

All transformations are lazy - they don't execute until you materialize the iterator.

iter = Iter.range(1, 100)

# Map - transform each element
iter.map(lambda x: x * 2)

# Filter - keep matching elements
iter.filter(lambda x: x % 2 == 0)

# Filter and map combined
iter.filter_map(lambda x: x * 2 if x % 3 == 0 else None)

# Enumerate - add indices
iter.enumerate()            # (0, 1), (1, 2), (2, 3), ...
iter.enumerate(start=10)    # (10, 1), (11, 2), (12, 3), ...

# Zip - combine with other iterables
iter.zip([10, 20, 30])      # (1, 10), (2, 20), (3, 30)

Operator Overloading

Scalar Operations (Broadcasting)

Apply operations to each element:

# Addition
Iter.range(1, 5) + 10           # 11, 12, 13, 14

# Multiplication
Iter.range(1, 5) * 2            # 2, 4, 6, 8

# Power
Iter.triangle_numbers() ** 2    # 1, 9, 36, 100, 225, ...

# Division
Iter.range(10, 50, 10) / 10     # 1.0, 2.0, 3.0, 4.0

# Subtraction
Iter.range(10, 15) - 5          # 5, 6, 7, 8, 9

Element-wise Operations (Zipping)

Combine two iterators element by element:

# Add corresponding elements
iter1 = Iter.range(1, 5)
iter2 = Iter.range(10, 14)
(iter1 + iter2).collect()       # [11, 13, 15, 17]

# Multiply corresponding elements
(iter1 * iter2).collect()       # [10, 22, 36, 52]

# Complex combinations
fib = Iter.fibonacci()
primes = Iter.primes()
(fib * 2 + primes).take(5).collect()
# [4, 5, 9, 13, 21]  # (1*2+2, 1*2+3, 2*2+5, 3*2+7, 5*2+11)

Slicing & Limiting

# Take first n elements
Iter.count().take(5)            # 0, 1, 2, 3, 4

# Take while condition holds
Iter.count().take_while(lambda x: x < 10)  # 0, 1, 2, ..., 9

Terminal Operations

Terminal operations consume the iterator and return a value.

These will raise InfiniteIteratorError on infinite iterators:

# Collect to list
Iter.range(1, 6).collect()      # [1, 2, 3, 4, 5]

# Sort (requires finite iterator)
Iter([3, 1, 4, 1, 5]).sort().collect()
# [1, 1, 3, 4, 5]

Iter(['apple', 'pie', 'a']).sort(key=len).collect()
# ['a', 'pie', 'apple']

Infinite Iterator Safety

The library prevents accidental infinite loops by tracking which iterators are infinite.

Safe Patterns ✅

# Always use take() with infinite iterators
Iter.fibonacci().take(10).collect()     # ✅ Safe

# take_while terminates naturally
Iter.count().take_while(lambda x: x < 100).collect()  # ✅ Safe

# Zip stops at shortest iterator
Iter.fibonacci().zip(Iter.range(1, 6)).collect()  # ✅ Safe

# Operators preserve safety
(Iter.fibonacci() ** 2).take(5).collect()  # ✅ Safe

Unsafe Patterns ❌

# These will raise InfiniteIteratorError:
Iter.fibonacci().collect()              # ❌ Error!
Iter.count().sort()                     # ❌ Error!
Iter.primes().collect()                 # ❌ Error!

API Reference

Creation Methods

Method	Description
Iter(iterable)	Wrap any iterable
Iter.range(*args)	Create from range
Iter.count(start=0, step=1)	Infinite counting
Iter.cycle(iterable)	Infinite cycling
Iter.repeat(value, times=None)	Repeat value
Iter.fibonacci(a=1, b=1)	Fibonacci sequence
Iter.primes()	Prime numbers
Iter.triangle_numbers()	Triangular numbers
Iter.square(start=0)	Perfect squares

Transformation Methods

Method	Description	Safe for Infinite?
map(func)	Transform elements	✅ Yes
filter(pred)	Keep matching	✅ Yes
filter_map(func)	Map + filter None	✅ Yes
enumerate(start=0)	Add indices	✅ Yes
zip(*iterables)	Combine iterables	✅ Yes*
take(n)	First n elements	✅ Yes
take_while(pred)	Take while true	✅ Yes

*Stops at shortest iterator

Terminal Methods

Method	Description	Safe for Infinite?
collect()	→ list	❌ No
sort(key=None, reverse=False)	→ sorted Iter	❌ No

Operators

Operator	Scalar	Element-wise
+	Add to each	Zip and add
-	Subtract from each	Zip and subtract
*	Multiply each	Zip and multiply
/	Divide each	Zip and divide

Special Methods

Method	Description
__iter__()	Use in for loops
__next__()	Get next element
__getitem__(index)	Access by index
__str__()	Pretty print first 10

Design Philosophy

1. Safety First - Infinite iterators are clearly marked and unsafe operations are blocked
2. Lazy Evaluation - Nothing executes until you call a terminal operation
3. Chainable - Methods return new iterators for fluent composition
4. Pythonic - Uses Python's protocols and conventions
5. Type-Safe - Full type hints for IDE support

Requirements

• Python 3.12+ (uses new generic syntax class Iter[T])

License

MIT

Contributing

Ideas for extensions:

• More mathematical sequences (Catalan, Lucas numbers, etc.)
• More terminal operations (sum(), product(), min(), max())
• Parallel iteration support
• More operators (comparison, bitwise)
• scan() for cumulative operations
• chunk() and window() for grouping

Examples in Action

# Find the 10th Fibonacci number that's also prime
result = (Iter.fibonacci()
          .filter(lambda f: f in Iter.primes().take(1000).collect())
          .take(10)
          .enumerate()
          .collect())

# Generate powers: 2^1, 3^2, 4^3, 5^4, ...
powers = (Iter.count(2) ** Iter.count(1)).take(10).collect()
# [2, 9, 64, 625, 7776, 117649, 2097152, 43046721, 1000000000, 25937424601]

# Complex mathematical pipeline
result = (
    Iter.triangle_numbers()     # 1, 3, 6, 10, 15, ...
    ** 2                         # 1, 9, 36, 100, 225, ...
    .filter(lambda x: x % 2 == 0) # 36, 100, ...
    .map(lambda x: x // 2)       # 18, 50, ...
    .take(5)
    .collect()
)

Enjoy building with infinite possibilities! 🚀