Convert Figma logo to code with AI

attractivechaos logoklib

A standalone and lightweight C library

4,117
552
4,117
89

Top Related Projects

1,369

Toolkit for processing sequences in FASTA/Q formats

A versatile pairwise aligner for genomic and spliced nucleotide sequences

Quick Overview

Klib is a standalone and lightweight C library that provides efficient implementations of various algorithms and data structures. It focuses on performance and simplicity, offering a collection of useful tools for C programmers without the need for external dependencies.

Pros

  • Lightweight and standalone, with no external dependencies
  • High-performance implementations of common algorithms and data structures
  • Easy to integrate into existing C projects
  • Well-documented and actively maintained

Cons

  • Limited scope compared to more comprehensive libraries
  • Requires manual memory management in some cases
  • May not be as feature-rich as larger, more specialized libraries
  • Primarily focused on C, with limited support for other languages

Code Examples

  1. Using the khash hash table:
#include "khash.h"
KHASH_MAP_INIT_INT(m32, char)

int main() {
    int ret, is_missing;
    khint_t k;
    khash_t(m32) *h = kh_init(m32);
    k = kh_put(m32, h, 5, &ret);
    kh_value(h, k) = 10;
    k = kh_get(m32, h, 10);
    is_missing = (k == kh_end(h));
    k = kh_get(m32, h, 5);
    kh_del(m32, h, k);
    kh_destroy(m32, h);
    return 0;
}
  1. Using the ksort sorting function:
#include "ksort.h"
KSORT_INIT_GENERIC(int)

int main() {
    int arr[] = {3, 1, 4, 1, 5, 9, 2, 6, 5, 3};
    int n = sizeof(arr) / sizeof(arr[0]);
    ks_introsort(int, n, arr);
    return 0;
}
  1. Using the kstring string manipulation functions:
#include "kstring.h"

int main() {
    kstring_t str = {0, 0, 0};
    ksprintf(&str, "Hello, %s!", "world");
    kputs("How are you?", &str);
    printf("%s\n", str.s);
    free(str.s);
    return 0;
}

Getting Started

To use Klib in your project:

  1. Clone the repository:

    git clone https://github.com/attractivechaos/klib.git
    
  2. Include the desired header files in your C source code:

    #include "klib/khash.h"
    #include "klib/ksort.h"
    #include "klib/kstring.h"
    
  3. Compile your program with the Klib headers:

    gcc -I/path/to/klib your_program.c -o your_program
    

Note: Klib is header-only, so you don't need to link against any libraries.

Competitor Comparisons

1,369

Toolkit for processing sequences in FASTA/Q formats

Pros of seqtk

  • Specialized for sequence processing tasks in bioinformatics
  • Includes a wide range of sequence manipulation tools
  • Optimized for handling large genomic datasets efficiently

Cons of seqtk

  • More focused scope compared to the general-purpose klib
  • May have a steeper learning curve for non-bioinformaticians
  • Less suitable for general-purpose programming tasks

Code Comparison

seqtk (sequence processing):

while ((l = kseq_read(seq)) >= 0) {
    if (seq->qual.l) {
        for (i = 0; i < seq->qual.l; ++i)
            seq->qual.s[i] = q_int2char(33 + (seq->qual.s[i] - 33 + q) / 2);
    }
    puts(seq->name.s);
    puts(seq->seq.s);
    if (seq->qual.l) puts(seq->qual.s);
}

klib (general-purpose library):

#include "khash.h"
KHASH_MAP_INIT_STR(str, int)
khash_t(str) *h;
h = kh_init(str);
k = kh_put(str, h, "key", &ret);
kh_value(h, k) = 1;
kh_del(str, h, k);
kh_destroy(str, h);

The code snippets demonstrate the specialized nature of seqtk for sequence processing, while klib provides more general-purpose data structures and algorithms.

A versatile pairwise aligner for genomic and spliced nucleotide sequences

Pros of minimap2

  • Specialized for long-read sequence alignment and mapping
  • Optimized for performance with large genomic datasets
  • Actively maintained and widely used in bioinformatics

Cons of minimap2

  • More complex and domain-specific than klib
  • Larger codebase and potentially steeper learning curve
  • Less suitable for general-purpose programming tasks

Code Comparison

minimap2:

int mm_idx_gen(mm_idx_t *mi, int n_threads)
{
    int i, j;
    mm_idx_bucket_t *b;
    if (mi->h == 0) return 0;
    for (i = 0; i < 1<<mi->b; ++i) {
        b = &mi->B[i];

klib:

#define KSORT_INIT(name, type_t, __sort_lt)				\
	KSORT_INIT_GENERIC(name, type_t, __sort_lt, __ks_insertsort_##name, __ks_combsort_##name, __ks_mergesort_##name, __ks_introsort_##name)

#define ks_lt_generic(a, b) ((a) < (b))

minimap2 is tailored for genomic sequence alignment, featuring specialized data structures and algorithms. klib, on the other hand, provides generic macros and functions for broader use cases. The code snippets illustrate this difference, with minimap2 showing a specific indexing function, while klib demonstrates a generic sorting macro.

Convert Figma logo designs to code with AI

Visual Copilot

Introducing Visual Copilot: A new AI model to turn Figma designs to high quality code using your components.

Try Visual Copilot

README

Klib: a Generic Library in C

Overview

Klib is a standalone and lightweight C library distributed under MIT/X11 license. Most components are independent of external libraries, except the standard C library, and independent of each other. To use a component of this library, you only need to copy a couple of files to your source code tree without worrying about library dependencies.

Klib strives for efficiency and a small memory footprint. Some components, such as khash.h, kbtree.h, ksort.h and kvec.h, are among the most efficient implementations of similar algorithms or data structures in all programming languages, in terms of both speed and memory use.

A new documentation is available here which includes most information in this README file.

Common components

Components for more specific use cases

Methodology

For the implementation of generic containers, klib extensively uses C macros. To use these data structures, we usually need to instantiate methods by expanding a long macro. This makes the source code look unusual or even ugly and adds difficulty to debugging. Unfortunately, for efficient generic programming in C that lacks template, using macros is the only solution. Only with macros, we can write a generic container which, once instantiated, compete with a type-specific container in efficiency. Some generic libraries in C, such as Glib, use the void* type to implement containers. These implementations are usually slower and use more memory than klib (see this benchmark).

To effectively use klib, it is important to understand how it achieves generic programming. We will use the hash table library as an example:

#include "khash.h"
KHASH_MAP_INIT_INT(m32, char)        // instantiate structs and methods
int main() {
    int ret, is_missing;
    khint_t k;
    khash_t(m32) *h = kh_init(m32);  // allocate a hash table
    k = kh_put(m32, h, 5, &ret);     // insert a key to the hash table
    if (!ret) kh_del(m32, h, k);
    kh_value(h, k) = 10;             // set the value
    k = kh_get(m32, h, 10);          // query the hash table
    is_missing = (k == kh_end(h));   // test if the key is present
    k = kh_get(m32, h, 5);
    kh_del(m32, h, k);               // remove a key-value pair
    for (k = kh_begin(h); k != kh_end(h); ++k)  // traverse
        if (kh_exist(h, k))          // test if a bucket contains data
			kh_value(h, k) = 1;
    kh_destroy(m32, h);              // deallocate the hash table
    return 0;
}

In this example, the second line instantiates a hash table with unsigned as the key type and char as the value type. m32 names such a type of hash table. All types and functions associated with this name are macros, which will be explained later. Macro kh_init() initiates a hash table and kh_destroy() frees it. kh_put() inserts a key and returns the iterator (or the position) in the hash table. kh_get() and kh_del() get a key and delete an element, respectively. Macro kh_exist() tests if an iterator (or a position) is filled with data.

An immediate question is this piece of code does not look like a valid C program (e.g. lacking semicolon, assignment to an apparent function call and apparent undefined m32 'variable'). To understand why the code is correct, let's go a bit further into the source code of khash.h, whose skeleton looks like:

#define KHASH_INIT(name, SCOPE, key_t, val_t, is_map, _hashf, _hasheq) \
  typedef struct { \
    int n_buckets, size, n_occupied, upper_bound; \
    unsigned *flags; \
    key_t *keys; \
    val_t *vals; \
  } kh_##name##_t; \
  SCOPE inline kh_##name##_t *init_##name() { \
    return (kh_##name##_t*)calloc(1, sizeof(kh_##name##_t)); \
  } \
  SCOPE inline int get_##name(kh_##name##_t *h, key_t k) \
  ... \
  SCOPE inline void destroy_##name(kh_##name##_t *h) { \
    if (h) { \
      free(h->keys); free(h->flags); free(h->vals); free(h); \
    } \
  }

#define _int_hf(key) (unsigned)(key)
#define _int_heq(a, b) (a == b)
#define khash_t(name) kh_##name##_t
#define kh_value(h, k) ((h)->vals[k])
#define kh_begin(h, k) 0
#define kh_end(h) ((h)->n_buckets)
#define kh_init(name) init_##name()
#define kh_get(name, h, k) get_##name(h, k)
#define kh_destroy(name, h) destroy_##name(h)
...
#define KHASH_MAP_INIT_INT(name, val_t) \
	KHASH_INIT(name, static, unsigned, val_t, is_map, _int_hf, _int_heq)

KHASH_INIT() is a huge macro defining all the structs and methods. When this macro is called, all the code inside it will be inserted by the C preprocess to the place where it is called. If the macro is called multiple times, multiple copies of the code will be inserted. To avoid naming conflict of hash tables with different key-value types, the library uses token concatenation, which is a preprocessor feature whereby we can substitute part of a symbol based on the parameter of the macro. In the end, the C preprocessor will generate the following code and feed it to the compiler (macro kh_exist(h,k) is a little complex and not expanded for simplicity):

typedef struct {
  int n_buckets, size, n_occupied, upper_bound;
  unsigned *flags;
  unsigned *keys;
  char *vals;
} kh_m32_t;
static inline kh_m32_t *init_m32() {
  return (kh_m32_t*)calloc(1, sizeof(kh_m32_t));
}
static inline int get_m32(kh_m32_t *h, unsigned k)
...
static inline void destroy_m32(kh_m32_t *h) {
  if (h) {
    free(h->keys); free(h->flags); free(h->vals); free(h);
  }
}

int main() {
	int ret, is_missing;
	khint_t k;
	kh_m32_t *h = init_m32();
	k = put_m32(h, 5, &ret);
	if (!ret) del_m32(h, k);
	h->vals[k] = 10;
	k = get_m32(h, 10);
	is_missing = (k == h->n_buckets);
	k = get_m32(h, 5);
	del_m32(h, k);
	for (k = 0; k != h->n_buckets; ++k)
		if (kh_exist(h, k)) h->vals[k] = 1;
	destroy_m32(h);
	return 0;
}

This is the C program we know.

From this example, we can see that macros and the C preprocessor plays a key role in klib. Klib is fast partly because the compiler knows the key-value type at the compile time and is able to optimize the code to the same level as type-specific code. A generic library written with void* will not get such performance boost.

Massively inserting code upon instantiation may remind us of C++'s slow compiling speed and huge binary size when STL/boost is in use. Klib is much better in this respect due to its small code size and component independency. Inserting several hundreds lines of code won't make compiling obviously slower.

Resources

  • Library documentation, if present, is available in the header files. Examples can be found in the test/ directory.
  • Obsolete documentation of the hash table library can be found at SourceForge. This README is partly adapted from the old documentation.
  • Blog post describing the hash table library.
  • Blog post on why using void* for generic programming may be inefficient.
  • Blog post on the generic stream buffer.
  • Blog post evaluating the performance of kvec.h.
  • Blog post arguing B-tree may be a better data structure than a binary search tree.
  • Blog post evaluating the performance of khash.h and kbtree.h among many other implementations. An older version of the benchmark is also available.
  • Blog post benchmarking internal sorting algorithms and implementations.
  • Blog post on the k-small algorithm.
  • Blog post on the Hooke-Jeeve's algorithm for nonlinear programming.