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/*
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* Copyright ( c ) Meta Platforms , Inc . and affiliates .
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* All rights reserved .
*
* This source code is licensed under both the BSD - style license ( found in the
* LICENSE file in the root directory of this source tree ) and the GPLv2 ( found
* in the COPYING file in the root directory of this source tree ) .
* You may select , at your option , one of the above - listed licenses .
*/
# if defined (__cplusplus)
extern " C " {
# endif
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# ifndef ZSTD_ZDICT_H
# define ZSTD_ZDICT_H
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/*====== Dependencies ======*/
# include <stddef.h> /* size_t */
/* ===== ZDICTLIB_API : control library symbols visibility ===== */
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# ifndef ZDICTLIB_VISIBLE
/* Backwards compatibility with old macro name */
# ifdef ZDICTLIB_VISIBILITY
# define ZDICTLIB_VISIBLE ZDICTLIB_VISIBILITY
# elif defined(__GNUC__) && (__GNUC__ >= 4) && !defined(__MINGW32__)
# define ZDICTLIB_VISIBLE __attribute__ ((visibility ("default")))
# else
# define ZDICTLIB_VISIBLE
# endif
# endif
# ifndef ZDICTLIB_HIDDEN
# if defined(__GNUC__) && (__GNUC__ >= 4) && !defined(__MINGW32__)
# define ZDICTLIB_HIDDEN __attribute__ ((visibility ("hidden")))
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# else
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# define ZDICTLIB_HIDDEN
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# endif
# endif
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# if defined(ZSTD_DLL_EXPORT) && (ZSTD_DLL_EXPORT==1)
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# define ZDICTLIB_API __declspec(dllexport) ZDICTLIB_VISIBLE
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# elif defined(ZSTD_DLL_IMPORT) && (ZSTD_DLL_IMPORT==1)
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# define ZDICTLIB_API __declspec(dllimport) ZDICTLIB_VISIBLE /* It isn't required but allows to generate better code, saving a function pointer load from the IAT and an indirect jump.*/
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# else
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# define ZDICTLIB_API ZDICTLIB_VISIBLE
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# endif
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/*******************************************************************************
* Zstd dictionary builder
*
* FAQ
* = = =
* Why should I use a dictionary ?
* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
*
* Zstd can use dictionaries to improve compression ratio of small data .
* Traditionally small files don ' t compress well because there is very little
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* repetition in a single sample , since it is small . But , if you are compressing
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* many similar files , like a bunch of JSON records that share the same
* structure , you can train a dictionary on ahead of time on some samples of
* these files . Then , zstd can use the dictionary to find repetitions that are
* present across samples . This can vastly improve compression ratio .
*
* When is a dictionary useful ?
* - - - - - - - - - - - - - - - - - - - - - - - - - - - -
*
* Dictionaries are useful when compressing many small files that are similar .
* The larger a file is , the less benefit a dictionary will have . Generally ,
* we don ' t expect dictionary compression to be effective past 100 KB . And the
* smaller a file is , the more we would expect the dictionary to help .
*
* How do I use a dictionary ?
* - - - - - - - - - - - - - - - - - - - - - - - - - -
*
* Simply pass the dictionary to the zstd compressor with
* ` ZSTD_CCtx_loadDictionary ( ) ` . The same dictionary must then be passed to
* the decompressor , using ` ZSTD_DCtx_loadDictionary ( ) ` . There are other
* more advanced functions that allow selecting some options , see zstd . h for
* complete documentation .
*
* What is a zstd dictionary ?
* - - - - - - - - - - - - - - - - - - - - - - - - - -
*
* A zstd dictionary has two pieces : Its header , and its content . The header
* contains a magic number , the dictionary ID , and entropy tables . These
* entropy tables allow zstd to save on header costs in the compressed file ,
* which really matters for small data . The content is just bytes , which are
* repeated content that is common across many samples .
*
* What is a raw content dictionary ?
* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
*
* A raw content dictionary is just bytes . It doesn ' t have a zstd dictionary
* header , a dictionary ID , or entropy tables . Any buffer is a valid raw
* content dictionary .
*
* How do I train a dictionary ?
* - - - - - - - - - - - - - - - - - - - - - - - - - - - -
*
* Gather samples from your use case . These samples should be similar to each
* other . If you have several use cases , you could try to train one dictionary
* per use case .
*
* Pass those samples to ` ZDICT_trainFromBuffer ( ) ` and that will train your
* dictionary . There are a few advanced versions of this function , but this
* is a great starting point . If you want to further tune your dictionary
* you could try ` ZDICT_optimizeTrainFromBuffer_cover ( ) ` . If that is too slow
* you can try ` ZDICT_optimizeTrainFromBuffer_fastCover ( ) ` .
*
* If the dictionary training function fails , that is likely because you
* either passed too few samples , or a dictionary would not be effective
* for your data . Look at the messages that the dictionary trainer printed ,
* if it doesn ' t say too few samples , then a dictionary would not be effective .
*
* How large should my dictionary be ?
* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
*
* A reasonable dictionary size , the ` dictBufferCapacity ` , is about 100 KB .
* The zstd CLI defaults to a 110 KB dictionary . You likely don ' t need a
* dictionary larger than that . But , most use cases can get away with a
* smaller dictionary . The advanced dictionary builders can automatically
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* shrink the dictionary for you , and select the smallest size that doesn ' t
* hurt compression ratio too much . See the ` shrinkDict ` parameter .
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* A smaller dictionary can save memory , and potentially speed up
* compression .
*
* How many samples should I provide to the dictionary builder ?
* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
*
* We generally recommend passing ~ 100 x the size of the dictionary
* in samples . A few thousand should suffice . Having too few samples
* can hurt the dictionaries effectiveness . Having more samples will
* only improve the dictionaries effectiveness . But having too many
* samples can slow down the dictionary builder .
*
* How do I determine if a dictionary will be effective ?
* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
*
* Simply train a dictionary and try it out . You can use zstd ' s built in
* benchmarking tool to test the dictionary effectiveness .
*
* # Benchmark levels 1 - 3 without a dictionary
* zstd - b1e3 - r / path / to / my / files
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* # Benchmark levels 1 - 3 with a dictionary
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* zstd - b1e3 - r / path / to / my / files - D / path / to / my / dictionary
*
* When should I retrain a dictionary ?
* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
*
* You should retrain a dictionary when its effectiveness drops . Dictionary
* effectiveness drops as the data you are compressing changes . Generally , we do
* expect dictionaries to " decay " over time , as your data changes , but the rate
* at which they decay depends on your use case . Internally , we regularly
* retrain dictionaries , and if the new dictionary performs significantly
* better than the old dictionary , we will ship the new dictionary .
*
* I have a raw content dictionary , how do I turn it into a zstd dictionary ?
* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
*
* If you have a raw content dictionary , e . g . by manually constructing it , or
* using a third - party dictionary builder , you can turn it into a zstd
* dictionary by using ` ZDICT_finalizeDictionary ( ) ` . You ' ll also have to
* provide some samples of the data . It will add the zstd header to the
* raw content , which contains a dictionary ID and entropy tables , which
* will improve compression ratio , and allow zstd to write the dictionary ID
* into the frame , if you so choose .
*
* Do I have to use zstd ' s dictionary builder ?
* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
*
* No ! You can construct dictionary content however you please , it is just
* bytes . It will always be valid as a raw content dictionary . If you want
* a zstd dictionary , which can improve compression ratio , use
* ` ZDICT_finalizeDictionary ( ) ` .
*
* What is the attack surface of a zstd dictionary ?
* - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -
*
* Zstd is heavily fuzz tested , including loading fuzzed dictionaries , so
* zstd should never crash , or access out - of - bounds memory no matter what
* the dictionary is . However , if an attacker can control the dictionary
* during decompression , they can cause zstd to generate arbitrary bytes ,
* just like if they controlled the compressed data .
*
* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
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/*! ZDICT_trainFromBuffer():
* Train a dictionary from an array of samples .
* Redirect towards ZDICT_optimizeTrainFromBuffer_fastCover ( ) single - threaded , with d = 8 , steps = 4 ,
* f = 20 , and accel = 1.
* Samples must be stored concatenated in a single flat buffer ` samplesBuffer ` ,
* supplied with an array of sizes ` samplesSizes ` , providing the size of each sample , in order .
* The resulting dictionary will be saved into ` dictBuffer ` .
* @ return : size of dictionary stored into ` dictBuffer ` ( < = ` dictBufferCapacity ` )
* or an error code , which can be tested with ZDICT_isError ( ) .
* Note : Dictionary training will fail if there are not enough samples to construct a
* dictionary , or if most of the samples are too small ( < 8 bytes being the lower limit ) .
* If dictionary training fails , you should use zstd without a dictionary , as the dictionary
* would ' ve been ineffective anyways . If you believe your samples would benefit from a dictionary
* please open an issue with details , and we can look into it .
* Note : ZDICT_trainFromBuffer ( ) ' s memory usage is about 6 MB .
* Tips : In general , a reasonable dictionary has a size of ~ 100 KB .
* It ' s possible to select smaller or larger size , just by specifying ` dictBufferCapacity ` .
* In general , it ' s recommended to provide a few thousands samples , though this can vary a lot .
* It ' s recommended that total size of all samples be about ~ x100 times the target size of dictionary .
*/
ZDICTLIB_API size_t ZDICT_trainFromBuffer ( void * dictBuffer , size_t dictBufferCapacity ,
const void * samplesBuffer ,
const size_t * samplesSizes , unsigned nbSamples ) ;
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typedef struct {
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int compressionLevel ; /**< optimize for a specific zstd compression level; 0 means default */
unsigned notificationLevel ; /**< Write log to stderr; 0 = none (default); 1 = errors; 2 = progression; 3 = details; 4 = debug; */
unsigned dictID ; /**< force dictID value; 0 means auto mode (32-bits random value)
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* NOTE : The zstd format reserves some dictionary IDs for future use .
* You may use them in private settings , but be warned that they
* may be used by zstd in a public dictionary registry in the future .
* These dictionary IDs are :
* - low range : < = 32767
* - high range : > = ( 2 ^ 31 )
*/
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} ZDICT_params_t ;
/*! ZDICT_finalizeDictionary():
* Given a custom content as a basis for dictionary , and a set of samples ,
* finalize dictionary by adding headers and statistics according to the zstd
* dictionary format .
*
* Samples must be stored concatenated in a flat buffer ` samplesBuffer ` ,
* supplied with an array of sizes ` samplesSizes ` , providing the size of each
* sample in order . The samples are used to construct the statistics , so they
* should be representative of what you will compress with this dictionary .
*
* The compression level can be set in ` parameters ` . You should pass the
* compression level you expect to use in production . The statistics for each
* compression level differ , so tuning the dictionary for the compression level
* can help quite a bit .
*
* You can set an explicit dictionary ID in ` parameters ` , or allow us to pick
* a random dictionary ID for you , but we can ' t guarantee no collisions .
*
* The dstDictBuffer and the dictContent may overlap , and the content will be
* appended to the end of the header . If the header + the content doesn ' t fit in
* maxDictSize the beginning of the content is truncated to make room , since it
* is presumed that the most profitable content is at the end of the dictionary ,
* since that is the cheapest to reference .
*
* ` maxDictSize ` must be > = max ( dictContentSize , ZSTD_DICTSIZE_MIN ) .
*
* @ return : size of dictionary stored into ` dstDictBuffer ` ( < = ` maxDictSize ` ) ,
* or an error code , which can be tested by ZDICT_isError ( ) .
* Note : ZDICT_finalizeDictionary ( ) will push notifications into stderr if
* instructed to , using notificationLevel > 0.
* NOTE : This function currently may fail in several edge cases including :
* * Not enough samples
* * Samples are uncompressible
* * Samples are all exactly the same
*/
ZDICTLIB_API size_t ZDICT_finalizeDictionary ( void * dstDictBuffer , size_t maxDictSize ,
const void * dictContent , size_t dictContentSize ,
const void * samplesBuffer , const size_t * samplesSizes , unsigned nbSamples ,
ZDICT_params_t parameters ) ;
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/*====== Helper functions ======*/
ZDICTLIB_API unsigned ZDICT_getDictID ( const void * dictBuffer , size_t dictSize ) ; /**< extracts dictID; @return zero if error (not a valid dictionary) */
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ZDICTLIB_API size_t ZDICT_getDictHeaderSize ( const void * dictBuffer , size_t dictSize ) ; /* returns dict header size; returns a ZSTD error code on failure */
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ZDICTLIB_API unsigned ZDICT_isError ( size_t errorCode ) ;
ZDICTLIB_API const char * ZDICT_getErrorName ( size_t errorCode ) ;
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# endif /* ZSTD_ZDICT_H */
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# if defined(ZDICT_STATIC_LINKING_ONLY) && !defined(ZSTD_ZDICT_H_STATIC)
# define ZSTD_ZDICT_H_STATIC
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/* This can be overridden externally to hide static symbols. */
# ifndef ZDICTLIB_STATIC_API
# if defined(ZSTD_DLL_EXPORT) && (ZSTD_DLL_EXPORT==1)
# define ZDICTLIB_STATIC_API __declspec(dllexport) ZDICTLIB_VISIBLE
# elif defined(ZSTD_DLL_IMPORT) && (ZSTD_DLL_IMPORT==1)
# define ZDICTLIB_STATIC_API __declspec(dllimport) ZDICTLIB_VISIBLE
# else
# define ZDICTLIB_STATIC_API ZDICTLIB_VISIBLE
# endif
# endif
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/* ====================================================================================
* The definitions in this section are considered experimental .
* They should never be used with a dynamic library , as they may change in the future .
* They are provided for advanced usages .
* Use them only in association with static linking .
* = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = = */
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# define ZDICT_DICTSIZE_MIN 256
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/* Deprecated: Remove in v1.6.0 */
# define ZDICT_CONTENTSIZE_MIN 128
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/*! ZDICT_cover_params_t:
* k and d are the only required parameters .
* For others , value 0 means default .
*/
typedef struct {
unsigned k ; /* Segment size : constraint: 0 < k : Reasonable range [16, 2048+] */
unsigned d ; /* dmer size : constraint: 0 < d <= k : Reasonable range [6, 16] */
unsigned steps ; /* Number of steps : Only used for optimization : 0 means default (40) : Higher means more parameters checked */
unsigned nbThreads ; /* Number of threads : constraint: 0 < nbThreads : 1 means single-threaded : Only used for optimization : Ignored if ZSTD_MULTITHREAD is not defined */
double splitPoint ; /* Percentage of samples used for training: Only used for optimization : the first nbSamples * splitPoint samples will be used to training, the last nbSamples * (1 - splitPoint) samples will be used for testing, 0 means default (1.0), 1.0 when all samples are used for both training and testing */
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unsigned shrinkDict ; /* Train dictionaries to shrink in size starting from the minimum size and selects the smallest dictionary that is shrinkDictMaxRegression% worse than the largest dictionary. 0 means no shrinking and 1 means shrinking */
unsigned shrinkDictMaxRegression ; /* Sets shrinkDictMaxRegression so that a smaller dictionary can be at worse shrinkDictMaxRegression% worse than the max dict size dictionary. */
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ZDICT_params_t zParams ;
} ZDICT_cover_params_t ;
typedef struct {
unsigned k ; /* Segment size : constraint: 0 < k : Reasonable range [16, 2048+] */
unsigned d ; /* dmer size : constraint: 0 < d <= k : Reasonable range [6, 16] */
unsigned f ; /* log of size of frequency array : constraint: 0 < f <= 31 : 1 means default(20)*/
unsigned steps ; /* Number of steps : Only used for optimization : 0 means default (40) : Higher means more parameters checked */
unsigned nbThreads ; /* Number of threads : constraint: 0 < nbThreads : 1 means single-threaded : Only used for optimization : Ignored if ZSTD_MULTITHREAD is not defined */
double splitPoint ; /* Percentage of samples used for training: Only used for optimization : the first nbSamples * splitPoint samples will be used to training, the last nbSamples * (1 - splitPoint) samples will be used for testing, 0 means default (0.75), 1.0 when all samples are used for both training and testing */
unsigned accel ; /* Acceleration level: constraint: 0 < accel <= 10, higher means faster and less accurate, 0 means default(1) */
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unsigned shrinkDict ; /* Train dictionaries to shrink in size starting from the minimum size and selects the smallest dictionary that is shrinkDictMaxRegression% worse than the largest dictionary. 0 means no shrinking and 1 means shrinking */
unsigned shrinkDictMaxRegression ; /* Sets shrinkDictMaxRegression so that a smaller dictionary can be at worse shrinkDictMaxRegression% worse than the max dict size dictionary. */
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ZDICT_params_t zParams ;
} ZDICT_fastCover_params_t ;
/*! ZDICT_trainFromBuffer_cover():
* Train a dictionary from an array of samples using the COVER algorithm .
* Samples must be stored concatenated in a single flat buffer ` samplesBuffer ` ,
* supplied with an array of sizes ` samplesSizes ` , providing the size of each sample , in order .
* The resulting dictionary will be saved into ` dictBuffer ` .
* @ return : size of dictionary stored into ` dictBuffer ` ( < = ` dictBufferCapacity ` )
* or an error code , which can be tested with ZDICT_isError ( ) .
* See ZDICT_trainFromBuffer ( ) for details on failure modes .
* Note : ZDICT_trainFromBuffer_cover ( ) requires about 9 bytes of memory for each input byte .
* Tips : In general , a reasonable dictionary has a size of ~ 100 KB .
* It ' s possible to select smaller or larger size , just by specifying ` dictBufferCapacity ` .
* In general , it ' s recommended to provide a few thousands samples , though this can vary a lot .
* It ' s recommended that total size of all samples be about ~ x100 times the target size of dictionary .
*/
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ZDICTLIB_STATIC_API size_t ZDICT_trainFromBuffer_cover (
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void * dictBuffer , size_t dictBufferCapacity ,
const void * samplesBuffer , const size_t * samplesSizes , unsigned nbSamples ,
ZDICT_cover_params_t parameters ) ;
/*! ZDICT_optimizeTrainFromBuffer_cover():
* The same requirements as above hold for all the parameters except ` parameters ` .
* This function tries many parameter combinations and picks the best parameters .
* ` * parameters ` is filled with the best parameters found ,
* dictionary constructed with those parameters is stored in ` dictBuffer ` .
*
* All of the parameters d , k , steps are optional .
* If d is non - zero then we don ' t check multiple values of d , otherwise we check d = { 6 , 8 } .
* if steps is zero it defaults to its default value .
* If k is non - zero then we don ' t check multiple values of k , otherwise we check steps values in [ 50 , 2000 ] .
*
* @ return : size of dictionary stored into ` dictBuffer ` ( < = ` dictBufferCapacity ` )
* or an error code , which can be tested with ZDICT_isError ( ) .
* On success ` * parameters ` contains the parameters selected .
* See ZDICT_trainFromBuffer ( ) for details on failure modes .
* Note : ZDICT_optimizeTrainFromBuffer_cover ( ) requires about 8 bytes of memory for each input byte and additionally another 5 bytes of memory for each byte of memory for each thread .
*/
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ZDICTLIB_STATIC_API size_t ZDICT_optimizeTrainFromBuffer_cover (
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void * dictBuffer , size_t dictBufferCapacity ,
const void * samplesBuffer , const size_t * samplesSizes , unsigned nbSamples ,
ZDICT_cover_params_t * parameters ) ;
/*! ZDICT_trainFromBuffer_fastCover():
* Train a dictionary from an array of samples using a modified version of COVER algorithm .
* Samples must be stored concatenated in a single flat buffer ` samplesBuffer ` ,
* supplied with an array of sizes ` samplesSizes ` , providing the size of each sample , in order .
* d and k are required .
* All other parameters are optional , will use default values if not provided
* The resulting dictionary will be saved into ` dictBuffer ` .
* @ return : size of dictionary stored into ` dictBuffer ` ( < = ` dictBufferCapacity ` )
* or an error code , which can be tested with ZDICT_isError ( ) .
* See ZDICT_trainFromBuffer ( ) for details on failure modes .
* Note : ZDICT_trainFromBuffer_fastCover ( ) requires 6 * 2 ^ f bytes of memory .
* Tips : In general , a reasonable dictionary has a size of ~ 100 KB .
* It ' s possible to select smaller or larger size , just by specifying ` dictBufferCapacity ` .
* In general , it ' s recommended to provide a few thousands samples , though this can vary a lot .
* It ' s recommended that total size of all samples be about ~ x100 times the target size of dictionary .
*/
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ZDICTLIB_STATIC_API size_t ZDICT_trainFromBuffer_fastCover ( void * dictBuffer ,
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size_t dictBufferCapacity , const void * samplesBuffer ,
const size_t * samplesSizes , unsigned nbSamples ,
ZDICT_fastCover_params_t parameters ) ;
/*! ZDICT_optimizeTrainFromBuffer_fastCover():
* The same requirements as above hold for all the parameters except ` parameters ` .
* This function tries many parameter combinations ( specifically , k and d combinations )
* and picks the best parameters . ` * parameters ` is filled with the best parameters found ,
* dictionary constructed with those parameters is stored in ` dictBuffer ` .
* All of the parameters d , k , steps , f , and accel are optional .
* If d is non - zero then we don ' t check multiple values of d , otherwise we check d = { 6 , 8 } .
* if steps is zero it defaults to its default value .
* If k is non - zero then we don ' t check multiple values of k , otherwise we check steps values in [ 50 , 2000 ] .
* If f is zero , default value of 20 is used .
* If accel is zero , default value of 1 is used .
*
* @ return : size of dictionary stored into ` dictBuffer ` ( < = ` dictBufferCapacity ` )
* or an error code , which can be tested with ZDICT_isError ( ) .
* On success ` * parameters ` contains the parameters selected .
* See ZDICT_trainFromBuffer ( ) for details on failure modes .
* Note : ZDICT_optimizeTrainFromBuffer_fastCover ( ) requires about 6 * 2 ^ f bytes of memory for each thread .
*/
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ZDICTLIB_STATIC_API size_t ZDICT_optimizeTrainFromBuffer_fastCover ( void * dictBuffer ,
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size_t dictBufferCapacity , const void * samplesBuffer ,
const size_t * samplesSizes , unsigned nbSamples ,
ZDICT_fastCover_params_t * parameters ) ;
typedef struct {
unsigned selectivityLevel ; /* 0 means default; larger => select more => larger dictionary */
ZDICT_params_t zParams ;
} ZDICT_legacy_params_t ;
/*! ZDICT_trainFromBuffer_legacy():
* Train a dictionary from an array of samples .
* Samples must be stored concatenated in a single flat buffer ` samplesBuffer ` ,
* supplied with an array of sizes ` samplesSizes ` , providing the size of each sample , in order .
* The resulting dictionary will be saved into ` dictBuffer ` .
* ` parameters ` is optional and can be provided with values set to 0 to mean " default " .
* @ return : size of dictionary stored into ` dictBuffer ` ( < = ` dictBufferCapacity ` )
* or an error code , which can be tested with ZDICT_isError ( ) .
* See ZDICT_trainFromBuffer ( ) for details on failure modes .
* Tips : In general , a reasonable dictionary has a size of ~ 100 KB .
* It ' s possible to select smaller or larger size , just by specifying ` dictBufferCapacity ` .
* In general , it ' s recommended to provide a few thousands samples , though this can vary a lot .
* It ' s recommended that total size of all samples be about ~ x100 times the target size of dictionary .
* Note : ZDICT_trainFromBuffer_legacy ( ) will send notifications into stderr if instructed to , using notificationLevel > 0.
*/
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ZDICTLIB_STATIC_API size_t ZDICT_trainFromBuffer_legacy (
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void * dictBuffer , size_t dictBufferCapacity ,
const void * samplesBuffer , const size_t * samplesSizes , unsigned nbSamples ,
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ZDICT_legacy_params_t parameters ) ;
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/* Deprecation warnings */
/* It is generally possible to disable deprecation warnings from compiler,
for example with - Wno - deprecated - declarations for gcc
or _CRT_SECURE_NO_WARNINGS in Visual .
Otherwise , it ' s also possible to manually define ZDICT_DISABLE_DEPRECATE_WARNINGS */
# ifdef ZDICT_DISABLE_DEPRECATE_WARNINGS
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# define ZDICT_DEPRECATED(message) /* disable deprecation warnings */
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# else
# define ZDICT_GCC_VERSION (__GNUC__ * 100 + __GNUC_MINOR__)
# if defined (__cplusplus) && (__cplusplus >= 201402) /* C++14 or greater */
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# define ZDICT_DEPRECATED(message) [[deprecated(message)]]
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# elif defined(__clang__) || (ZDICT_GCC_VERSION >= 405)
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# define ZDICT_DEPRECATED(message) __attribute__((deprecated(message)))
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# elif (ZDICT_GCC_VERSION >= 301)
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# define ZDICT_DEPRECATED(message) __attribute__((deprecated))
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# elif defined(_MSC_VER)
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# define ZDICT_DEPRECATED(message) __declspec(deprecated(message))
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# else
# pragma message("WARNING: You need to implement ZDICT_DEPRECATED for this compiler")
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# define ZDICT_DEPRECATED(message)
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# endif
# endif /* ZDICT_DISABLE_DEPRECATE_WARNINGS */
ZDICT_DEPRECATED ( " use ZDICT_finalizeDictionary() instead " )
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ZDICTLIB_STATIC_API
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size_t ZDICT_addEntropyTablesFromBuffer ( void * dictBuffer , size_t dictContentSize , size_t dictBufferCapacity ,
const void * samplesBuffer , const size_t * samplesSizes , unsigned nbSamples ) ;
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# endif /* ZSTD_ZDICT_H_STATIC */
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# if defined (__cplusplus)
}
# endif