chore: add RuboCop for code standardization

Add RuboCop with rubocop-minitest for consistent code style:

- Configure .rubocop.yml with project-specific rules
- Exclude legacy bin/ and install.rb files
- Allow complexity in mathematical algorithms (SVD, LSI)
- Auto-correct 151 style offenses
- Add respond_to_missing? to Bayes class
- Add lint job to CI workflow

Style improvements applied:
- Consistent single quotes for strings
- Proper spacing and indentation
- Modern Ruby idioms (anonymous block forwarding)
- Minitest assertion best practices

Fixes #56

Author: cardmagic

.github/workflows/ruby.yml

@@ -17,8 +17,19 @@ permissions:
   contents: read
 
 jobs:
-  test:
+  lint:
+    runs-on: ubuntu-latest
+    steps:
+    - uses: actions/checkout@v4
+    - name: Set up Ruby
+      uses: ruby/setup-ruby@v1
+      with:
+        ruby-version: '3.3'
+        bundler-cache: true
+    - name: Run RuboCop
+      run: bundle exec rubocop
 
+  test:
     runs-on: ubuntu-latest
     strategy:
       matrix:

.rubocop.yml

@@ -0,0 +1,96 @@
+plugins:
+  - rubocop-minitest
+
+AllCops:
+  TargetRubyVersion: 3.1
+  NewCops: enable
+  Exclude:
+    - 'vendor/**/*'
+    - 'coverage/**/*'
+    - '*.gemspec'
+    - 'bin/**/*'
+    - 'install.rb'
+
+# Existing code lacks documentation, can add incrementally
+Style/Documentation:
+  Enabled: false
+
+# Test files often have long blocks
+Metrics/BlockLength:
+  Exclude:
+    - 'test/**/*'
+    - 'lib/classifier/extensions/vector.rb'
+
+# Allow longer methods in complex algorithms (SVD, etc.)
+Metrics/MethodLength:
+  Max: 25
+  Exclude:
+    - 'test/**/*'
+    - 'lib/classifier/extensions/vector.rb'
+    - 'lib/classifier/lsi/content_node.rb'
+
+# Allow higher complexity for mathematical algorithms
+Metrics/AbcSize:
+  Max: 30
+  Exclude:
+    - 'test/**/*'
+    - 'lib/classifier/extensions/vector.rb'
+    - 'lib/classifier/lsi.rb'
+    - 'lib/classifier/lsi/content_node.rb'
+
+Metrics/CyclomaticComplexity:
+  Max: 10
+  Exclude:
+    - 'lib/classifier/extensions/vector.rb'
+    - 'lib/classifier/lsi/content_node.rb'
+
+Metrics/PerceivedComplexity:
+  Max: 10
+  Exclude:
+    - 'lib/classifier/extensions/vector.rb'
+    - 'lib/classifier/lsi/content_node.rb'
+
+# Class length limits - algorithms and tests can be longer
+Metrics/ClassLength:
+  Max: 250
+  Exclude:
+    - 'test/**/*'
+
+# SV_decomp is a standard algorithm name
+Naming/MethodName:
+  Exclude:
+    - 'lib/classifier/extensions/vector.rb'
+
+# Short parameter names are acceptable for serialization
+Naming/MethodParameterName:
+  Exclude:
+    - 'lib/classifier/extensions/vector_serialize.rb'
+
+# Marshal.load is intentional for deserialization
+Security/MarshalLoad:
+  Exclude:
+    - 'lib/classifier/extensions/vector_serialize.rb'
+    - 'test/**/*'
+
+# CORPUS_SKIP_WORDS is a public constant used externally
+Lint/UselessConstantScoping:
+  Enabled: false
+
+# Frozen string literal is optional for this gem
+Style/FrozenStringLiteralComment:
+  Enabled: false
+
+# Allow compact class/module child definitions
+Style/ClassAndModuleChildren:
+  Enabled: false
+
+# Allow both styles of string literals
+Style/StringLiterals:
+  EnforcedStyle: single_quotes
+
+Style/StringLiteralsInInterpolation:
+  EnforcedStyle: single_quotes
+
+# Minitest assertions
+Minitest/MultipleAssertions:
+  Max: 10

Gemfile

@@ -8,3 +8,8 @@ gem 'mutex_m'
 group :test do
   gem 'simplecov', require: false
 end
+
+group :development do
+  gem 'rubocop', require: false
+  gem 'rubocop-minitest', require: false
+end

Gemfile.lock

@@ -10,23 +10,57 @@ PATH
 GEM
   remote: https://rubygems.org/
   specs:
+    ast (2.4.3)
     docile (1.4.1)
     fast-stemmer (1.0.2)
+    json (2.18.0)
+    language_server-protocol (3.17.0.5)
+    lint_roller (1.1.0)
     matrix (0.4.2)
     minitest (5.18.1)
     mutex_m (0.2.0)
+    parallel (1.27.0)
+    parser (3.3.10.0)
+      ast (~> 2.4.1)
+      racc
+    prism (1.7.0)
     psych (5.1.2)
       stringio
+    racc (1.8.1)
+    rainbow (3.1.1)
     rake (13.0.6)
     rdoc (6.5.1.1)
       psych (>= 4.0.0)
+    regexp_parser (2.11.3)
+    rubocop (1.82.1)
+      json (~> 2.3)
+      language_server-protocol (~> 3.17.0.2)
+      lint_roller (~> 1.1.0)
+      parallel (~> 1.10)
+      parser (>= 3.3.0.2)
+      rainbow (>= 2.2.2, < 4.0)
+      regexp_parser (>= 2.9.3, < 3.0)
+      rubocop-ast (>= 1.48.0, < 2.0)
+      ruby-progressbar (~> 1.7)
+      unicode-display_width (>= 2.4.0, < 4.0)
+    rubocop-ast (1.48.0)
+      parser (>= 3.3.7.2)
+      prism (~> 1.4)
+    rubocop-minitest (0.38.2)
+      lint_roller (~> 1.1)
+      rubocop (>= 1.75.0, < 2.0)
+      rubocop-ast (>= 1.38.0, < 2.0)
+    ruby-progressbar (1.13.0)
     simplecov (0.22.0)
       docile (~> 1.1)
       simplecov-html (~> 0.11)
       simplecov_json_formatter (~> 0.1)
     simplecov-html (0.13.2)
     simplecov_json_formatter (0.1.4)
     stringio (3.1.0)
+    unicode-display_width (3.2.0)
+      unicode-emoji (~> 4.1)
+    unicode-emoji (4.2.0)
 
 PLATFORMS
   arm64-darwin-22
@@ -41,6 +75,8 @@ DEPENDENCIES
   minitest
   mutex_m
   rdoc
+  rubocop
+  rubocop-minitest
   simplecov
 
 BUNDLED WITH

lib/classifier/bayes.rb

@@ -88,7 +88,7 @@ def classifications(text)
     #    b.classify "I hate bad words and you"
     #    =>  'Uninteresting'
     def classify(text)
-      (classifications(text).sort_by { |a| -a[1] })[0][0]
+      classifications(text).min_by { |a| -a[1] }[0]
     end
 
     #
@@ -109,6 +109,10 @@ def method_missing(name, *args)
       args.each { |text| send(method, category, text) }
     end
 
+    def respond_to_missing?(name, include_private = false)
+      name.to_s =~ /(un)?train_(\w+)/ || super
+    end
+
     #
     # Provides a list of category names
     # For example:

lib/classifier/extensions/vector.rb

@@ -6,11 +6,11 @@
 require 'matrix'
 
 class Array
-  def sum_with_identity(identity = 0.0, &block)
+  def sum_with_identity(identity = 0.0, &)
     return identity unless size.to_i.positive?
-    return map(&block).sum_with_identity(identity) if block_given?
+    return map(&).sum_with_identity(identity) if block_given?
 
-    compact.reduce(:+).to_f || identity.to_f
+    compact.reduce(:+).to_f
   end
 end
 
@@ -58,8 +58,8 @@ def SV_decomp(max_sweeps = 20)
 
     loop do
       iteration_count += 1
-      (0...q_rotation_matrix.row_size - 1).each do |row|
-        (1..q_rotation_matrix.row_size - 1).each do |col|
+      (0...(q_rotation_matrix.row_size - 1)).each do |row|
+        (1..(q_rotation_matrix.row_size - 1)).each do |col|
           next if row == col
 
           angle = Math.atan((2.to_r * q_rotation_matrix[row,

lib/classifier/extensions/word_hash.rb

@@ -12,7 +12,7 @@ class String
   #   "Hello (greeting's), with {braces} < >...?".without_punctuation
   #   => "Hello  greetings   with  braces         "
   def without_punctuation
-    tr(',?.!;:"@#$%^&*()_=+[]{}\|<>/`~', ' ').tr("'\-", '')
+    tr(',?.!;:"@#$%^&*()_=+[]{}|<>/`~', ' ').tr("'-", '')
   end
 
   # Return a Hash of strings => ints. Each word in the string is stemmed,

lib/classifier/lsi.rb

@@ -165,7 +165,7 @@ def highest_relative_content(max_chunks = 10)
       avg_density = {}
       @items.each_key { |x| avg_density[x] = proximity_array_for_content(x).inject(0.0) { |i, j| i + j[1] } }
 
-      avg_density.keys.sort_by { |x| avg_density[x] }.reverse[0..max_chunks - 1].map
+      avg_density.keys.sort_by { |x| avg_density[x] }.reverse[0..(max_chunks - 1)].map
     end
 
     # This function is the primitive that find_related and classify
@@ -180,10 +180,10 @@ def highest_relative_content(max_chunks = 10)
     # The parameter doc is the content to compare. If that content is not
     # indexed, you can pass an optional block to define how to create the
     # text data. See add_item for examples of how this works.
-    def proximity_array_for_content(doc, &block)
+    def proximity_array_for_content(doc, &)
       return [] if needs_rebuild?
 
-      content_node = node_for_content(doc, &block)
+      content_node = node_for_content(doc, &)
       result =
         @items.keys.collect do |item|
           val = if self.class.gsl_available
@@ -201,10 +201,10 @@ def proximity_array_for_content(doc, &block)
     # calculated vectors instead of their full versions. This is useful when
     # you're trying to perform operations on content that is much smaller than
     # the text you're working with. search uses this primitive.
-    def proximity_norms_for_content(doc, &block)
+    def proximity_norms_for_content(doc, &)
       return [] if needs_rebuild?
 
-      content_node = node_for_content(doc, &block)
+      content_node = node_for_content(doc, &)
       result =
         @items.keys.collect do |item|
           val = if self.class.gsl_available
@@ -229,7 +229,7 @@ def search(string, max_nearest = 3)
 
       carry = proximity_norms_for_content(string)
       result = carry.collect { |x| x[0] }
-      result[0..max_nearest - 1]
+      result[0..(max_nearest - 1)]
     end
 
     # This function takes content and finds other documents
@@ -245,7 +245,7 @@ def find_related(doc, max_nearest = 3, &block)
       carry =
         proximity_array_for_content(doc, &block).reject { |pair| pair[0] == doc }
       result = carry.collect { |x| x[0] }
-      result[0..max_nearest - 1]
+      result[0..(max_nearest - 1)]
     end
 
     # This function uses a voting system to categorize documents, based on
@@ -257,17 +257,17 @@ def find_related(doc, max_nearest = 3, &block)
     # text. A cutoff of 1 means that every document in the index votes on
     # what category the document is in. This may not always make sense.
     #
-    def classify(doc, cutoff = 0.30, &block)
-      votes = vote(doc, cutoff, &block)
+    def classify(doc, cutoff = 0.30, &)
+      votes = vote(doc, cutoff, &)
 
       ranking = votes.keys.sort_by { |x| votes[x] }
       ranking[-1]
     end
 
-    def vote(doc, cutoff = 0.30, &block)
+    def vote(doc, cutoff = 0.30, &)
       icutoff = (@items.size * cutoff).round
-      carry = proximity_array_for_content(doc, &block)
-      carry = carry[0..icutoff - 1]
+      carry = proximity_array_for_content(doc, &)
+      carry = carry[0..(icutoff - 1)]
       votes = {}
       carry.each do |pair|
         categories = @items[pair[0]].categories
@@ -291,8 +291,8 @@ def vote(doc, cutoff = 0.30, &block)
     #
     #
     # See classify() for argument docs
-    def classify_with_confidence(doc, cutoff = 0.30, &block)
-      votes = vote(doc, cutoff, &block)
+    def classify_with_confidence(doc, cutoff = 0.30, &)
+      votes = vote(doc, cutoff, &)
       votes_sum = votes.values.inject(0.0) { |sum, v| sum + v }
       return [nil, nil] if votes_sum.zero?
 
@@ -309,7 +309,7 @@ def highest_ranked_stems(doc, count = 3)
       raise 'Requested stem ranking on non-indexed content!' unless @items[doc]
 
       arr = node_for_content(doc).lsi_vector.to_a
-      top_n = arr.sort.reverse[0..count - 1]
+      top_n = arr.sort.reverse[0..(count - 1)]
       top_n.collect { |x| @word_list.word_for_index(arr.index(x)) }
     end