Natural language tokenizer; supports a simple white space tokenizer (preferable for simple tasks), a unicode pattern-matcher, and state function lexer.
There are 2 toplevel functions:
TokenizeStr(string, string) []string *DigestTokenizeBytes([]byte, string) *Digest.
Both functions require you to select which tokenizer type to be used (the second argument). The TokenizeBytes function only supports lex and 'unicodeoptions and will only return aDigeststruct with aBytesfield; it is for use in instances where dealing with strings is not preferred or possible. TheTokenizeStrfunction is for dealing directly with strings and supportslex, unicode, whitespace`; it returns a slice of tokens as well as digest, and depending on the tokenizer used the digest will contain different data fields.
Any kind. During development I often used publicly available corpora with particularly nasty text. For example, the 20 Newsgroups data set has archived news and emails from early internet groups.... Specifically, the comp.windows.x data set is wealth of archived emails or early internet text containing technical manuals, source code, and even full bitmaps. The unicode and lexer parsers can handle these easily, though in nuanced ways. The lexer is more powerful, flexible, and slower. It gathers a lot of metadata and keeps virtually the full text intact. Once you've run the Lexer the Digest should contain enough data that you can chop it up any way you wish. The Unicode tokenizer is more of a sanatizer to clean up nasty text. So usually a combination of these tokenizers is useful.
Or one thing I've often done if I needed the Lexer is to split up my text files into smaller chunks then run the lexer against smaller data sets. Or, I'll run the unicode tokenizer to sanatize large amounts of text, then run the lexer to get the flexibility I need.
Support for streaming data from an input file to an output fill is now supported.
- Stream from one file to another
- Stream a directory of files to one outpur file
- Stream wikipedia dump of one xml file to one output file
These streamers use the byte tokenzizers and so you shouldn't be looking for lots of metatdata or interesting ways to interact with these apis. Mostly the streamers support moving large files or directories with lots of files across some kind of tokenizing sanitization. For example, I've recenlty used the file, directory, and wikipedia streamers to sanatize and aggregate a large data set of around 8 billions words.
go get github.com/jbowles/nlpt_tkzpackage main
import (
"fmt"
tkz "github.com/jbowles/nlpt_tkz"
)
func main() {
s := "From: mathew <mathew@mantis.co.uk> \nSubject: Alt.Atheism FAQ: Atheist Resources\n\nArchive-name: atheism/resources\nAlt-atheism-archive-name: resources\nLast-modified: 11 December 1992\nVersion: 1.0"
b := []byte(s)
digest1 := tkz.TokenizeBytes(b, "lex")
digest2 := tkz.TokenizeBytes(b, "unicode")
_, digest3 := tkz.TokenizeStr(s, "lex")
_, digest4 := tkz.TokenizeStr(s, "unicode")
_, digest5 := tkz.TokenizeStr(s, "whitespace")
fmt.Printf("-----printed digest-----")
fmt.Printf("\n\n")
fmt.Printf("LexBytes \n %+v\n\n", digest1)
fmt.Printf("UnicodeBytes \n %+v\n\n", digest2)
fmt.Printf("LexStr \n %+v\n\n", digest3)
fmt.Printf("UnicodeStr \n %+v\n\n", digest4)
fmt.Printf("WhitespaceStr \n %+v\n\n", digest5)
fmt.Printf("---------------------")
fmt.Printf("\n\n\n")
fmt.Printf("-----printed bytes-----")
fmt.Printf("\n\n")
fmt.Printf("++++++ LexBytes Printed +++++++ \n\n %s\n", digest1.Bytes)
fmt.Printf("++++++ LexBytes Printed +++++++ \n\n %s\n", digest3.Tokens)
fmt.Printf("\n\n")
fmt.Printf("+++++ UnicodeBytes Printed ++++++ \n\n %s\n", digest2.Bytes)
fmt.Printf("+++++ UnicodeStr Printed ++++++ \n\n %s\n", digest4.Tokens)
}The program above will produce this:
-----printed digest-----
LexBytes
&{Tokens:[] DowncaseTokens:[] TokenBytes:map[] Bytes:[70 114 111 109 58 32 109 97 116 104 101 119 32 60 109 97 116 104 101 119 64 109 97 110 116 105 115 46 99 111 46 117 107 62 32 10 83 117 98 106 101 99 116 58 32 65 108 116 46 65 116 104 101 105 115 109 32 70 65 81 58 32 65 116 104 101 105 115 116 32 82 101 115 111 117 114 99 101 115 10 10 65 114 99 104 105 118 101 45 110 97 109 101 58 32 97 116 104 101 105 115 109 47 114 101 115 111 117 114 99 101 115 10 65 108 116 45 97 116 104 101 105 115 109 45 97 114 99 104 105 118 101 45 110 97 109 101 58 32 114 101 115 111 117 114 99 101 115 10 76 97 115 116 45 109 111 100 105 102 105 101 100 58 32 49 49 32 68 101 99 101 109 98 101 114 32 49 57 57 50 10 86 101 114 115 105 111 110 58 32 49 46 48] SpaceCount:0 CharCount:0 Letter:[] Title:[] Number:[] Punct:[] Space:[] Symbol:[] TokenCount:0 PunctCount:0 LineCount:0 EmptyLine:false LastTokenType:3}
UnicodeBytes
&{Tokens:[] DowncaseTokens:[] TokenBytes:map[] Bytes:[70 114 111 109 32 32 109 97 116 104 101 119 32 32 109 97 116 104 101 119 32 109 97 110 116 105 115 32 99 111 32 117 107 32 32 10 83 117 98 106 101 99 116 32 32 65 108 116 32 65 116 104 101 105 115 109 32 70 65 81 32 32 65 116 104 101 105 115 116 32 82 101 115 111 117 114 99 101 115 10 10 65 114 99 104 105 118 101 32 110 97 109 101 32 32 97 116 104 101 105 115 109 32 114 101 115 111 117 114 99 101 115 10 65 108 116 32 97 116 104 101 105 115 109 32 97 114 99 104 105 118 101 32 110 97 109 101 32 32 114 101 115 111 117 114 99 101 115 10 76 97 115 116 32 109 111 100 105 102 105 101 100 32 32 49 49 32 68 101 99 101 109 98 101 114 32 49 57 57 50 10 86 101 114 115 105 111 110 32 32 49 32 48] SpaceCount:0 CharCount:0 Letter:[] Title:[] Number:[] Punct:[] Space:[] Symbol:[] TokenCount:0 PunctCount:0 LineCount:0 EmptyLine:false LastTokenType:0}
LexStr
&{Tokens:[From mathew <mathew@mantis co uk> Subject Alt Atheism FAQ Atheist Resources Archive-name atheism/resources Alt-atheism-archive-name resources Last-modified 11 December 1992 Version 1 0] DowncaseTokens:[from mathew <mathew@mantis co uk> subject alt atheism faq atheist resources archive-name atheism/resources alt-atheism-archive-name resources last-modified 11 december 1992 version 1 0] TokenBytes:map[Alt-atheism-archive-name:[65 108 116 45 97 116 104 101 105 115 109 45 97 114 99 104 105 118 101 45 110 97 109 101] Version:[86 101 114 115 105 111 110] From:[70 114 111 109] ::[58] co:[99 111] Alt:[65 108 116] Resources:[82 101 115 111 117 114 99 101 115] uk>:[117 107 62] Subject:[83 117 98 106 101 99 116] Atheist:[65 116 104 101 105 115 116] atheism/resources:[97 116 104 101 105 115 109 47 114 101 115 111 117 114 99 101 115] resources:[114 101 115 111 117 114 99 101 115] Archive-name:[65 114 99 104 105 118 101 45 110 97 109 101] Last-modified:[76 97 115 116 45 109 111 100 105 102 105 101 100] 11:[49 49] mathew:[109 97 116 104 101 119] <mathew@mantis:[60 109 97 116 104 101 119 64 109 97 110 116 105 115] .:[46] Atheism:[65 116 104 101 105 115 109] FAQ:[70 65 81] December:[68 101 99 101 109 98 101 114] 1992:[49 57 57 50] 1:[49] 0:[48]] Bytes:[70 114 111 109 58 32 109 97 116 104 101 119 32 60 109 97 116 104 101 119 64 109 97 110 116 105 115 46 99 111 46 117 107 62 32 10 83 117 98 106 101 99 116 58 32 65 108 116 46 65 116 104 101 105 115 109 32 70 65 81 58 32 65 116 104 101 105 115 116 32 82 101 115 111 117 114 99 101 115 10 10 65 114 99 104 105 118 101 45 110 97 109 101 58 32 97 116 104 101 105 115 109 47 114 101 115 111 117 114 99 101 115 10 65 108 116 45 97 116 104 101 105 115 109 45 97 114 99 104 105 118 101 45 110 97 109 101 58 32 114 101 115 111 117 114 99 101 115 10 76 97 115 116 45 109 111 100 105 102 105 101 100 58 32 49 49 32 68 101 99 101 109 98 101 114 32 49 57 57 50 10 86 101 114 115 105 111 110 58 32 49 46 48] SpaceCount:19 CharCount:193 Letter:[] Title:[] Number:[] Punct:[: . . : . : : : : : .] Space:[] Symbol:[] TokenCount:22 PunctCount:11 LineCount:7 EmptyLine:false LastTokenType:3}
UnicodeStr
&{Tokens:[From mathew mathewmantiscouk Subject AltAtheism FAQ Atheist Resources Archivename atheismresources Altatheismarchivename resources Lastmodified December Version ] DowncaseTokens:[from mathew mathewmantiscouk subject altatheism faq atheist resources archivename atheismresources altatheismarchivename resources lastmodified december version ] TokenBytes:map[] Bytes:[] SpaceCount:0 CharCount:0 Letter:[F r o m , m a t h e w , m a t h e w m a n t i s c o u k , , S u b j e c t , A l t A t h e i s m , F A Q , A t h e i s t , R e s o u r c e s , , A r c h i v e n a m e , a t h e i s m r e s o u r c e s , A l t a t h e i s m a r c h i v e n a m e , r e s o u r c e s , L a s t m o d i f i e d , , D e c e m b e r , , V e r s i o n , ] Title:[] Number:[1 1 1 9 9 2 1 0] Punct:[: @ . . : . : - : / - - - : - : : .] Space:[] Symbol:[< >] TokenCount:0 PunctCount:0 LineCount:0 EmptyLine:false LastTokenType:0}
WhitespaceStr
&{Tokens:[From: mathew <mathew@mantis.co.uk>
Subject: Alt.Atheism FAQ: Atheist Resources
Archive-name: atheism/resources
Alt-atheism-archive-name: resources
Last-modified: 11 December 1992
Version: 1.0] DowncaseTokens:[] TokenBytes:map[] Bytes:[] SpaceCount:13 CharCount:193 Letter:[] Title:[] Number:[] Punct:[] Space:[] Symbol:[] TokenCount:0 PunctCount:0 LineCount:0 EmptyLine:false LastTokenType:0}
---------------------
-----printed bytes-----
++++++ LexBytes Printed +++++++
From: mathew \<mathew@mantis.co.uk>
Subject: Alt.Atheism FAQ: Atheist Resources
Archive-name: atheism/resources
Alt-atheism-archive-name: resources
Last-modified: 11 December 1992
Version: 1.0
++++++ LexBytes Printed +++++++
[From mathew \<mathew@mantis co uk> Subject Alt Atheism FAQ Atheist Resources Archive-name atheism/resources Alt-atheism-archive-name resources Last-modified 11 December 1992 Version 1 0]
+++++ UnicodeBytes Printed ++++++
From mathew mathew mantis co uk
Subject Alt Atheism FAQ Atheist Resources
Archive name atheism resources
Alt atheism archive name resources
Last modified 11 December 1992
Version 1 0
+++++ UnicodeStr Printed ++++++
[From mathew mathewmantiscouk Subject AltAtheism FAQ Atheist Resources Archivename atheismresources Altatheismarchivename resources Lastmodified December Version ]Only the Lexer for TokenizeStr returns metadata such as line, token, punctation count.
There is no special reason for this, nor is there any rationale behind the different ways metadata is collected. Since nobody I know, including me, is using these tokenizers I've been reluctant to lock down any real consistency between the metatdata collection as the usefulness of metatada shoudl be determined by usage.
The white space tokenizer is merely a wrapper around strings.Split(" ") with some digest content for counts of tokens and such.
The lex (technically a State Function Lexer) and unicode (technically using go's unicode package for matching unicode code points) can and probably will return very differnt tokens sets of tokens (a token is defined as a unique atomic unit). For example, and email subject heading with the Lexer tokenizer will return one token \<mathew@mantis but the Unicode tokenizer will return mathewmantiscouk. For most people or tasks these differences don't matter. The rule of thumb is that if you just need "words", i.e. atomic units, and have a text that is pretty clean use unicode; it is the fastest of the two.
go test -bench .
go test -bench=.
go test -bench Lex
## or use the project go bench ui
gobenchui .
gobenchui github.com/jbowles/nlpt_tkzPASS
BenchmarkStateFnTknzGoodStr-8 10000 126706 ns/op
BenchmarkStateFnTknzBadStr-8 20000 72813 ns/op
BenchmarkStateFnTknzBytesGoodStr-8 20000 97107 ns/op
BenchmarkStateFnTknzBytesBadStr-8 30000 54702 ns/op
BenchmarkLexStrGood-8 10000 129937 ns/op
BenchmarkUnicodeStrGood-8 100000 23280 ns/op
BenchmarkWhitespaceStrGood-8 1000000 1439 ns/op
BenchmarkLexBytesGood-8 20000 98422 ns/op
BenchmarkUnicodeBytesGood-8 300000 5532 ns/op
BenchmarkLexStrBad-8 20000 75062 ns/op
BenchmarkUnicodeStrBad-8 100000 15535 ns/op
BenchmarkWhitespaceStrBad-8 2000000 911 ns/op
BenchmarkLexBytesBad-8 30000 56424 ns/op
BenchmarkUnicodeBytesBad-8 500000 3652 ns/op
BenchmarkUncdMatchTknzGoodStr-8 100000 24598 ns/op
BenchmarkUncdMatchTnkzBadStr-8 100000 15691 ns/op
BenchmarkUncdMatchTknzBytesGoodStr-8 300000 5262 ns/op
BenchmarkUncdMatchTnkzBytesBadStr-8 500000 3292 ns/op
BenchmarkWhiteSpaceTknzGoodStr-8 3000000 587 ns/op
BenchmarkWhiteSpaceTknzBadStr-8 2000000 755 ns/op
ok github.com/jbowles/nlpt_tkz 41.962s