enry

package module
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 Go to latest Published: Aug 7, 2019 License: Apache-2.0 Imports: 9 Imported by: 15

README

enry GoDoc Build Status codecov

File programming language detector and toolbox to ignore binary or vendored files. enry, started as a port to Go of the original linguist Ruby library, that has an improved 2x performance.

Installation

The recommended way to install enry is to either download a release or

go get github.com/src-d/enry/cmd/enry

This project is now part of source{d} Engine, which provides the simplest way to get started with a single command. Visit sourced.tech/engine for more information.

Examples

lang, safe := enry.GetLanguageByExtension("foo.go")
fmt.Println(lang, safe)
// result: Go true

lang, safe := enry.GetLanguageByContent("foo.m", []byte("<matlab-code>"))
fmt.Println(lang, safe)
// result: Matlab true

lang, safe := enry.GetLanguageByContent("bar.m", []byte("<objective-c-code>"))
fmt.Println(lang, safe)
// result: Objective-C true

// all strategies together
lang := enry.GetLanguage("foo.cpp", []byte("<cpp-code>"))
// result: C++ true

Note that the returned boolean value safe is set either to true, if there is only one possible language detected, or to false otherwise.

To get a list of possible languages for a given file, you can use the plural version of the detecting functions.

langs := enry.GetLanguages("foo.h",  []byte("<cpp-code>"))
// result: []string{"C", "C++", "Objective-C}

langs := enry.GetLanguagesByExtension("foo.asc", []byte("<content>"), nil)
// result: []string{"AGS Script", "AsciiDoc", "Public Key"}

langs := enry.GetLanguagesByFilename("Gemfile", []byte("<content>"), []string{})
// result: []string{"Ruby"}

CLI

You can use enry as a command,

$ enry --help
enry v2.0.0 build: 05-08-2019_20_40_35 commit: 6ccf0b6, based on linguist commit: e456098
enry, A simple (and faster) implementation of github/linguist
usage: enry [-mode=(file|line|byte)] [-prog] <path>
        enry [-mode=(file|line|byte)] [-prog] [-json] [-breakdown] <path>
        enry [-mode=(file|line|byte)] [-prog] [-json] [-breakdown]
        enry [-version]

and on repository root, it'll return an output similar to linguist's output,

$ enry
97.71%	Go
1.60%	C
0.31%	Shell
0.22%	Java
0.07%	Ruby
0.05%	Makefile
0.04%	Scala
0.01%	Gnuplot

but not only the output; its flags are also the same as linguist's ones,

$ enry --breakdown
97.71%	Go
1.60%	C
0.31%	Shell
0.22%	Java
0.07%	Ruby
0.05%	Makefile
0.04%	Scala
0.01%	Gnuplot

Scala
java/build.sbt
java/project/plugins.sbt

Java
java/src/main/java/tech/sourced/enry/Enry.java
java/src/main/java/tech/sourced/enry/GoUtils.java
java/src/main/java/tech/sourced/enry/Guess.java
java/src/test/java/tech/sourced/enry/EnryTest.java

Makefile
Makefile
java/Makefile

Go
benchmark_test.go

even the JSON flag,

$ enry --json | jq .
{
  "C": [
    "internal/tokenizer/flex/lex.linguist_yy.c",
    "internal/tokenizer/flex/lex.linguist_yy.h",
    "internal/tokenizer/flex/linguist.h",
    "python/_c_enry.c",
    "python/enry.c"
  ],
  "Gnuplot": [
    "benchmarks/plot-histogram.gp"
  ],
  "Go": [
    "benchmark_test.go",

Note that enry's CLI doesn't need a git repository to work, which is intentionally different from the linguist.

Java bindings

Generated Java bindings using a C shared library and JNI are available under java and published on Maven at tech.sourced:enry-java for macOS and linux.

Python bindings

Generated Python bindings using a C shared library and cffi are not available yet and are WIP under src-d/enry#154.

Divergences from linguist

The enry library is based on the data from github/linguist version v7.5.1.

As opposed to linguist, enry CLI tool does not require a full Git repository in the filesystem in order to report languages.

Parsing linguist/samples the following enry results are different from linguist:

In all the cases above that have an issue number - we plan to update enry to match Linguist behavior.

Benchmarks

Enry's language detection has been compared with Linguist's one. In order to do that, Linguist's project directory linguist/samples was used as a set of files to run benchmarks against.

We got these results:

histogram

The histogram shows the number of files detected (y-axis) per time interval bucket (x-axis). As one can see, most of the files were detected faster by enry.

We found few cases where enry turns slower than linguist due to Go regexp engine being slower than Ruby's, based on oniguruma library, written in C.

See instructions for running enry with oniguruma.

Why Enry?

In the movie My Fair Lady, Professor Henry Higgins is one of the main characters. Henry is a linguist and at the very beginning of the movie enjoys guessing the origin of people based on their accent.

"Enry Iggins" is how Eliza Doolittle, pronounces the name of the Professor during the first half of the movie.

Development

To build enry's CLI run:

make build

this will generate a binary in the project's root directory called enry.

To run the tests:

make test
Sync with github/linguist upstream

enry re-uses parts of the original github/linguist to generate internal data structures. In order to update to the latest release of linguist do:

$ git clone https://github.com/github/linguist.git .linguist
$ cd .linguist; git checkout <release-tag>; cd ..

# put the new release's commit sha in the generator_test.go (to re-generate .gold test fixtures)
# https://github.com/src-d/enry/blob/13d3d66d37a87f23a013246a1b0678c9ee3d524b/internal/code-generator/generator/generator_test.go#L18

$ make code-generate

To stay in sync, enry needs to be updated when a new release of the linguist includes changes to any of the following files:

There is no automation for detecting the changes in the linguist project, so this process above has to be done manually from time to time.

When submitting a pull request syncing up to a new release, please make sure it only contains the changes in the generated files (in data subdirectory).

Separating all the necessary "manual" code changes to a different PR that includes some background description and an update to the documentation on "divergences from linguist" is very much appreciated as it simplifies the maintenance (review/release notes/etc).

Misc

Benchmark

All benchmark scripts are in benchmarks directory.

Dependencies

As benchmarks depend on Ruby and Github-Linguist gem make sure you have:

  • Ruby (e.g using rbenv), bundler installed
  • Docker
  • native dependencies installed
  • Build the gem cd .linguist && bundle install && rake build_gem && cd -
  • Install it gem install --no-rdoc --no-ri --local .linguist/github-linguist-*.gem
Quick benchmark

To run quicker benchmarks you can either:

make benchmarks

to get average times for the main detection function and strategies for the whole samples set or:

make benchmarks-samples

if you want to see measures per sample file.

Full benchmark

If you want to reproduce the same benchmarks as reported above:

  • Make sure all dependencies are installed
  • Install gnuplot (in order to plot the histogram)
  • Run ENRY_TEST_REPO="$PWD/.linguist" benchmarks/run.sh (takes ~15h)

It will run the benchmarks for enry and linguist, parse the output, create csv files and plot the histogram.

Faster regexp engine (optional)

Oniguruma is CRuby's regular expression engine. It is very fast and performs better than the one built into Go runtime. enry supports swapping between those two engines thanks to rubex project. The typical overall speedup from using Oniguruma is 1.5-2x. However, it requires CGo and the external shared library. On macOS with Homebrew, it is:

brew install oniguruma

On Ubuntu, it is

sudo apt install libonig-dev

To build enry with Oniguruma regexps use the oniguruma build tag

go get -v -t --tags oniguruma ./...

and then rebuild the project.

License

Apache License, Version 2.0. See LICENSE

Documentation

Overview

Package enry implements multiple strategies for programming language identification.

Identification is made based on file name and file content using a seriece of strategies to narrow down possible option. Each strategy is available as a separate API call, as well as a main enty point 

GetLanguage(filename string, content []byte) (language string)

It is a port of the https://github.com/github/linguist from Ruby. Upstream Linguist YAML files are used to generate datastructures for data package.

Index

Constants

View Source 
const OtherLanguage = ""

OtherLanguage is used as a zero value when a function can not return a specific language.

Variables

View Source 
var DefaultStrategies = []Strategy{
	GetLanguagesByModeline,
	GetLanguagesByFilename,
	GetLanguagesByShebang,
	GetLanguagesByExtension,
	GetLanguagesByContent,
	GetLanguagesByClassifier,
}

DefaultStrategies is a sequence of strategies used by GetLanguage to detect languages.

Functions

func GetColor added in v2.1.0 

func GetColor(language string) string

GetColor returns a HTML color code of a given language.

func GetLanguage 

func GetLanguage(filename string, content []byte) (language string)

GetLanguage applies a sequence of strategies based on the given filename and content to find out the most probably language to return.

func GetLanguageByAlias 

func GetLanguageByAlias(alias string) (lang string, ok bool)

GetLanguageByAlias returns either the language related to the given alias and ok set to true or Otherlanguage and ok set to false if the alias is not recognized.

func GetLanguageByClassifier 

func GetLanguageByClassifier(content []byte, candidates []string) (language string, safe bool)

GetLanguageByClassifier returns the most probably language detected for the given content. It uses DefaultClassifier, if no candidates are provided it returns OtherLanguage.

func GetLanguageByContent 

func GetLanguageByContent(filename string, content []byte) (language string, safe bool)

GetLanguageByContent returns detected language. If there are more than one possibles languages it returns the first language by alphabetically order and safe to false.

func GetLanguageByEmacsModeline 

func GetLanguageByEmacsModeline(content []byte) (language string, safe bool)

GetLanguageByEmacsModeline returns detected language. If there are more than one possibles languages it returns the first language by alphabetically order and safe to false.

func GetLanguageByExtension 

func GetLanguageByExtension(filename string) (language string, safe bool)

GetLanguageByExtension returns detected language. If there are more than one possibles languages it returns the first language by alphabetically order and safe to false.

func GetLanguageByFilename 

func GetLanguageByFilename(filename string) (language string, safe bool)

GetLanguageByFilename returns detected language. If there are more than one possibles languages it returns the first language by alphabetically order and safe to false.

func GetLanguageByModeline 

func GetLanguageByModeline(content []byte) (language string, safe bool)

GetLanguageByModeline returns detected language. If there are more than one possibles languages it returns the first language by alphabetically order and safe to false.

func GetLanguageByShebang 

func GetLanguageByShebang(content []byte) (language string, safe bool)

GetLanguageByShebang returns detected language. If there are more than one possibles languages it returns the first language by alphabetically order and safe to false.

func GetLanguageBySpecificClassifier 

func GetLanguageBySpecificClassifier(content []byte, candidates []string, classifier Classifier) (language string, safe bool)

GetLanguageBySpecificClassifier returns the most probably language for the given content using classifier to detect language.

func GetLanguageByVimModeline 

func GetLanguageByVimModeline(content []byte) (language string, safe bool)

GetLanguageByVimModeline returns detected language. If there are more than one possibles languages it returns the first language by alphabetically order and safe to false.

func GetLanguageExtensions 

func GetLanguageExtensions(language string) []string

GetLanguageExtensions returns the different extensions being used by the language.

func GetLanguages 

func GetLanguages(filename string, content []byte) []string

GetLanguages applies a sequence of strategies based on the given filename and content to find out the most probably languages to return. At least one of arguments should be set. If content is missing, language detection will be based on the filename. The function won't read the file, given an empty content.

func GetLanguagesByClassifier 

func GetLanguagesByClassifier(filename string, content []byte, candidates []string) (languages []string)

GetLanguagesByClassifier uses DefaultClassifier as a Classifier and returns a sorted slice of possible languages ordered by decreasing language's probability. If there are not candidates it returns nil. It complies with the signature to be a Strategy type.

func GetLanguagesByContent 

func GetLanguagesByContent(filename string, content []byte, _ []string) []string

GetLanguagesByContent returns a slice of languages for the given content. It is a Strategy that uses content-based regexp heuristics and a filename extension.

func GetLanguagesByEmacsModeline 

func GetLanguagesByEmacsModeline(_ string, content []byte, _ []string) []string

GetLanguagesByEmacsModeline returns a slice of possible languages for the given content. It complies with the signature to be a Strategy type.

func GetLanguagesByExtension 

func GetLanguagesByExtension(filename string, _ []byte, _ []string) []string

GetLanguagesByExtension returns a slice of possible languages for the given filename. It complies with the signature to be a Strategy type.

func GetLanguagesByFilename 

func GetLanguagesByFilename(filename string, _ []byte, _ []string) []string

GetLanguagesByFilename returns a slice of possible languages for the given filename. It complies with the signature to be a Strategy type.

func GetLanguagesByModeline 

func GetLanguagesByModeline(_ string, content []byte, candidates []string) []string

GetLanguagesByModeline returns a slice of possible languages for the given content. It complies with the signature to be a Strategy type.

func GetLanguagesByShebang 

func GetLanguagesByShebang(_ string, content []byte, _ []string) (languages []string)

GetLanguagesByShebang returns a slice of possible languages for the given content. It complies with the signature to be a Strategy type.

func GetLanguagesBySpecificClassifier 

func GetLanguagesBySpecificClassifier(content []byte, candidates []string, classifier Classifier) (languages []string)

GetLanguagesBySpecificClassifier returns a slice of possible languages. It takes in a Classifier to be used.

func GetLanguagesByVimModeline 

func GetLanguagesByVimModeline(_ string, content []byte, _ []string) []string

GetLanguagesByVimModeline returns a slice of possible languages for the given content. It complies with the signature to be a Strategy type.

func GetMIMEType 

func GetMIMEType(path string, language string) string

GetMIMEType returns a MIME type of a given file based on its languages.

func IsBinary 

func IsBinary(data []byte) bool

IsBinary detects if data is a binary value based on: http://git.kernel.org/cgit/git/git.git/tree/xdiff-interface.c?id=HEAD#n198

func IsConfiguration 

func IsConfiguration(path string) bool

IsConfiguration tells if filename is in one of the configuration languages.

func IsDocumentation 

func IsDocumentation(path string) bool

IsDocumentation returns whether or not path is a documentation path.

func IsDotFile 

func IsDotFile(path string) bool

IsDotFile returns whether or not path has dot as a prefix.

func IsImage 

func IsImage(path string) bool

IsImage tells if a given file is an image (PNG, JPEG or GIF format).

func IsVendor 

func IsVendor(path string) bool

IsVendor returns whether or not path is a vendor path.

Types

type Classifier 

type Classifier interface {
	Classify(content []byte, candidates map[string]float64) (languages []string)
}

Classifier is the interface in charge to detect the possible languages of the given content based on a set of candidates. Candidates is a map which can be used to assign weights to languages dynamically. 

var DefaultClassifier Classifier = &classifier{
	languagesLogProbabilities: data.LanguagesLogProbabilities,
	tokensLogProbabilities:    data.TokensLogProbabilities,
	tokensTotal:               data.TokensTotal,
}

DefaultClassifier is a Naive Bayes classifier trained on Linguist samples.

type Strategy 

type Strategy func(filename string, content []byte, candidates []string) (languages []string)

Strategy type fix the signature for the functions that can be used as a strategy.

type Type 

type Type int

Type represent language's type. Either data, programming, markup, prose, or unknown. 

const (
	Unknown Type = iota
	Data
	Programming
	Markup
	Prose
)

Type's values.

func GetLanguageType 

func GetLanguageType(language string) (langType Type)

GetLanguageType returns the type of the given language.

Source Files

View all Source files

Directories

Path Synopsis
benchmarks
parser
cmd
enry
Package data contains only auto-generated data-structures for all the language identification strategies from the Linguist project sources.
 Package data contains only auto-generated data-structures for all the language identification strategies from the Linguist project sources.
rule
Package rule contains rule-based heuristic implementations.
 Package rule contains rule-based heuristic implementations.
internal
code-generator
code-generator/generator
Package generator provides facilities to generate Go code for the package data in enry from YAML files describing supported languages in Linguist.
 Package generator provides facilities to generate Go code for the package data in enry from YAML files describing supported languages in Linguist.
tokenizer
Package tokenizer implements file tokenization used by the enry content classifier.
 Package tokenizer implements file tokenization used by the enry content classifier.
tokenizer/flex

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