Merge pull request #1663 from github/strategies

Refactor detection into strategies
This commit is contained in:
Brandon Keepers
2014-11-28 17:40:12 -06:00
5 changed files with 87 additions and 51 deletions

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@@ -3,6 +3,25 @@ require 'linguist/tokenizer'
module Linguist
# Language bayesian classifier.
class Classifier
# Public: Use the classifier to detect language of the blob.
#
# blob - An object that quacks like a blob.
# possible_languages - Array of Language objects
#
# Examples
#
# Classifier.call(FileBlob.new("path/to/file"), [
# Language["Ruby"], Language["Python"]
# ])
#
# Returns an Array of Language objects, most probable first.
def self.call(blob, possible_languages)
language_names = possible_languages.map(&:name)
classify(Samples.cache, blob.data, language_names).map do |name, _|
Language[name] # Return the actual Language objects
end
end
# Public: Train classifier that data is a certain language.
#
# db - Hash classifier database object

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@@ -3,6 +3,23 @@ module Linguist
class Heuristics
ACTIVE = true
# Public: Use heuristics to detect language of the blob.
#
# blob - An object that quacks like a blob.
# possible_languages - Array of Language objects
#
# Examples
#
# Heuristics.call(FileBlob.new("path/to/file"), [
# Language["Ruby"], Language["Python"]
# ])
#
# Returns an Array with one Language if a heuristic matched, or empty if
# none matched or were inconclusive.
def self.call(blob, languages)
find_by_heuristics(blob.data, languages.map(&:name))
end
# Public: Given an array of String language names,
# apply heuristics against the given data and return an array
# of matching languages, or nil.

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@@ -10,6 +10,8 @@ require 'linguist/heuristics'
require 'linguist/samples'
require 'linguist/file_blob'
require 'linguist/blob_helper'
require 'linguist/strategy/filename'
require 'linguist/strategy/shebang'
module Linguist
# Language names that are recognizable by GitHub. Defined languages
@@ -91,6 +93,13 @@ module Linguist
language
end
STRATEGIES = [
Linguist::Strategy::Filename,
Linguist::Strategy::Shebang,
Linguist::Heuristics,
Linguist::Classifier
]
# Public: Detects the Language of the blob.
#
# blob - an object that includes the Linguist `BlobHelper` interface;
@@ -98,61 +107,22 @@ module Linguist
#
# Returns Language or nil.
def self.detect(blob)
name = blob.name.to_s
# Bail early if the blob is binary or empty.
return nil if blob.likely_binary? || blob.binary? || blob.empty?
# A bit of an elegant hack. If the file is executable but extensionless,
# append a "magic" extension so it can be classified with other
# languages that have shebang scripts.
extensions = FileBlob.new(name).extensions
if extensions.empty? && blob.mode && (blob.mode.to_i(8) & 05) == 05
name += ".script!"
end
# Find languages that match based on filename.
possible_languages = find_by_filename(name)
if possible_languages.length == 1
# Simplest and most common case, we can just return the one match based
# on extension
possible_languages.first
# If there is more than one possible language with that extension (or no
# extension at all, in the case of extensionless scripts), we need to
# continue our detection work
else
# Matches possible_languages.length == 0 || possible_languages.length > 0
data = blob.data
# Check if there's a shebang line and use that as authoritative
if (result = find_by_shebang(data)) && !result.empty?
return result.first
# More than one language with that extension. We need to make a choice.
elsif possible_languages.length > 1
# First try heuristics
possible_language_names = possible_languages.map(&:name)
heuristic_languages = Heuristics.find_by_heuristics(data, possible_language_names)
# If there are multiple possible languages returned from heuristics
# then reduce language candidates for Bayesian classifier here.
if heuristic_languages.size > 1
possible_language_names = heuristic_languages.map(&:name)
end
if heuristic_languages.size == 1
return heuristic_languages.first
# Lastly, fall back to the probabilistic classifier.
elsif classified = Classifier.classify(Samples.cache, data, possible_language_names).first
# Return the actual Language object based of the string language name (i.e., first element of `#classify`)
return Language[classified[0]]
end
# Call each strategy until one candidate is returned.
STRATEGIES.reduce([]) do |languages, strategy|
candidates = strategy.call(blob, languages)
if candidates.size == 1
return candidates.first
elsif candidates.size > 1
# More than one candidate was found, pass them to the next strategy.
candidates
else
# No candiates were found, pass on languages from the previous strategy.
languages
end
end
end.first
end
# Public: Get all Languages

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@@ -0,0 +1,20 @@
module Linguist
module Strategy
# Detects language based on filename and/or extension
class Filename
def self.call(blob, _)
name = blob.name.to_s
# A bit of an elegant hack. If the file is executable but extensionless,
# append a "magic" extension so it can be classified with other
# languages that have shebang scripts.
extensions = FileBlob.new(name).extensions
if extensions.empty? && blob.mode && (blob.mode.to_i(8) & 05) == 05
name += ".script!"
end
Language.find_by_filename(name)
end
end
end
end

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@@ -0,0 +1,10 @@
module Linguist
module Strategy
# Check if there's a shebang line and use that as authoritative
class Shebang
def self.call(blob, _)
Language.find_by_shebang(blob.data)
end
end
end
end