more-itertools/more-itertools

Features

• Itertools Extensions - Extends the Python itertools module with advanced routines for data transformation and state management.
• Standard Library Extensions - Serves as a comprehensive extension library for the standard Python itertools module.
• Collection Element Transformations - Implements higher-order functions for mapping, filtering, and reducing iterable elements.
• Iterable Transformation Utilities - Provides utilities to map, filter, group, and combine iterables for data processing.
• Iterator State Wrappers - Wraps iterators in stateful classes to provide advanced capabilities like peeking, seeking, and consumption tracking.
• Iterable Chunking - Transforms flat collections into different structures such as sliding windows, chunks, or matrices.
• Iterator State Analysis Tools - Inspects iterator state and performs lookaheads or lookbacks without consuming the underlying data stream.
• Iterator Peek and Seek - Provides mechanisms for looking ahead at upcoming elements without consuming the iterator.
• Lazy Evaluation - Extensively utilizes Python generators to implement lazy evaluation for memory-efficient data processing.
• Iterable Flatteners - Recursively collapses nested sequences or iterators into a single flat stream of elements.
• Iterable Lookahead and Lookback Managers - Provides the ability to access preceding or succeeding elements in a sequence without consuming the entire iterator.
• Combinatorial Generators - Provides efficient algorithms for generating all possible permutations and combinations of a set.
• Unique Subset Generation - Generates unique subsets of a specific length from collections that may contain duplicate elements.
• Permutation Generation Algorithms - Produces unique permutations of elements while correctly handling and avoiding duplicates from repeated values.
• Iterable Grouping - Provides a wide array of utilities to partition standard iterables into groups based on size or content.
• Iterable Splitting - Divides collections into multiple parts based on markers, predicates, or fixed lengths.
• First and Last Element Accessors - Provides utilities to retrieve the first or last element of a collection.
• Sequence Pattern Replacements - Implements a mechanism to substitute items or subsequences that match a predicate with elements from another collection.
• Iterable Interleaving and Zipping - Merges multiple collections by interleaving elements, broadcasting values, or pairing them with offsets.
• Multi-Iterable Interleaver - Combines several collections by yielding one element from each in turn using sequential, even, or random distributions.
• Adjacent Match Identification - Marks items that satisfy a predicate or are within a specified distance of a matching item.
• Element Shifting - Implements circular shifting (rolling) of sequence elements with wrap-around behavior.
• Matrix Multiplication Utilities - Multiplies two matrices using numeric types including complex numbers and fractions.
• Indexed Cycle Generation - Repeats a collection for a set number of cycles while yielding the current cycle index.
• Balanced Splitting - Implements logic to break collections into smaller sub-collections of a specified or balanced size.
• Consecutive Item Grouping - Produces groups of items that are considered adjacent based on a custom ordering function.
• Element Staggering - Produces tuples where elements are offset from the original sequence by specified distances.
• Item Index Location - Produces the indices of items that satisfy a predicate using forward or reverse searches.
• Item Search and Location - Finds the index, position, or first occurrence of specific values within a collection.
• Iterable Neighborhood Analyzers - Extracts overlapping or non-overlapping contiguous subsequences to analyze local neighborhoods of elements.
• Iterable Padding - Appends fill values to a sequence until it reaches a minimum length or a specific size multiple.
• Iterable Property Analyzers - Provides utilities to analyze properties of sequences, such as whether they are sorted or contain unique elements.
• Iterable Reversal - Caches elements of a non-reversible collection to allow yielding them in reverse order.
• Iterable Selection - Extracts specific items or subsets from a sequence based on custom value or position criteria.
• Iterable Summaries - Calculates counts, identifies extremes, and checks for sorting or equality across iterables.
• Iterator Consumption Tracking - Wraps collections to maintain a running tally of how many items have been consumed.
• Sequence Augmentations - Adds padding, inserts separators, or repeats elements to modify the structure of a data stream.
• Sliding Window Generators - Produces overlapping or non-overlapping sequences of a fixed size to analyze neighboring elements.
• Unique Element Identification - Identifies elements that appear exclusively in only one of several input collections.
• Caching Iterators - Provides the ability to traverse forward-only iterators in reverse by caching elements in an internal buffer.
• Iterator Lookahead Buffers - Implements buffering mechanisms to allow peeking at future elements in a sequence without consuming them.
• Partial Products - Generates partial products to explore combinations across multiple collections without producing every possible pair.
• Contiguous Subsequence Generators - Generates every possible contiguous subsequence and their corresponding positions from a sliceable collection.
• Signal Convolutions - Performs discrete linear convolution of a signal and a kernel for tasks like moving averages.
• Fourier Transforms - Computes the Discrete Fourier Transform and its inverse for sequences of complex numbers.
• Mathematical Sequence Processors - Performs discrete linear convolutions, Fourier transforms, and matrix multiplication on sequences of numeric or complex data.
• Non-Indexable Iterable Sampling - Returns a random subset of elements from generators or sets using weights and repetitions.
• Online Running Statistics - Produces cumulative minimums, maximums, means, or medians from a sequence or sliding window.
• Numerical Sequence Processors - Implements specialized routines for matrix multiplication, discrete linear convolution, and Fourier transforms.
• Set Partitions - Produces all possible ways to partition a collection into a fixed number of non-empty subsets.
• Stream Merging - Interleaves elements from multiple streams in fixed or non-deterministic orders.
• Stream Element Interspersing - Inserts fixed values or sequences at regular intervals between elements of an iterable.
• Collection Element Counters - Calculates the total number of elements in an iterable by fully consuming the stream.
• Thread-Safe Iterator Wrappers - Synchronizes access to non-concurrent iterators to ensure safe sequential processing across multiple threads.
• Functional Programming - Extends standard library iteration tools with additional routines.
• General Utilities - Extended routines for operating on iterables.

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