Class: MiniTest::Unit::TestCase

Inherits:
Object
  • Object
show all
Includes:
Assertions
Defined in:
lib/minitest/unit.rb,
lib/minitest/benchmark.rb

Overview

Subclass TestCase to create your own tests. Typically you’ll want a TestCase subclass per implementation class.

See MiniTest::Assertions

Direct Known Subclasses

Spec

Constant Summary collapse

PASSTHROUGH_EXCEPTIONS = 
[NoMemoryError, SignalException,
Interrupt, SystemExit]
SUPPORTS_INFO_SIGNAL =

:nodoc:





Constants included
from Assertions


Assertions::UNDEFINED, Assertions::WINDOZE


Instance Attribute Summary collapse




Class Method Summary
collapse





Instance Method Summary
collapse




Methods included from Assertions


#_assertions, #_assertions=, #assert, #assert_block, #assert_empty, #assert_equal, #assert_in_delta, #assert_in_epsilon, #assert_includes, #assert_instance_of, #assert_kind_of, #assert_match, #assert_nil, #assert_operator, #assert_output, #assert_predicate, #assert_raises, #assert_respond_to, #assert_same, #assert_send, #assert_silent, #assert_throws, #capture_io, #diff, diff, diff=, #exception_details, #flunk, #message, #mu_pp, #mu_pp_for_diff, #pass, #refute, #refute_empty, #refute_equal, #refute_in_delta, #refute_in_epsilon, #refute_includes, #refute_instance_of, #refute_kind_of, #refute_match, #refute_nil, #refute_operator, #refute_predicate, #refute_respond_to, #refute_same, #skip




Constructor Details





#initialize(name) ⇒ TestCase







:nodoc:















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# File 'lib/minitest/unit.rb', line 996

def initialize name # :nodoc:
  @__name__ = name
  @__io__ = nil
  @passed = nil
end













Instance Attribute Details






#__name__ ⇒ Object (readonly)







:nodoc:















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# File 'lib/minitest/unit.rb', line 952

def __name__
  @__name__
end













Class Method Details





.add_setup_hook(arg = nil, &block) ⇒ Object







Adds a block of code that will be executed before every TestCase is run. Equivalent to setup, but usable multiple times and without re-opening any classes.


All of the setup hooks will run in order after the setup method, if one is defined.


The argument can be any object that responds to #call or a block. That means that this call,


MiniTest::TestCase.add_setup_hook { puts "foo" }



… is equivalent to:


module MyTestSetup
  def call
    puts "foo"
  end
end

MiniTest::TestCase.add_setup_hook MyTestSetup



The blocks passed to add_setup_hook take an optional parameter that will be the TestCase instance that is executing the block.















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# File 'lib/minitest/unit.rb', line 1106

def self.add_setup_hook arg=nil, &block
  hook = arg || block
  @setup_hooks << hook
end












.add_teardown_hook(arg = nil, &block) ⇒ Object







Adds a block of code that will be executed after every TestCase is run. Equivalent to teardown, but usable multiple times and without re-opening any classes.


All of the teardown hooks will run in reverse order after the teardown method, if one is defined.


The argument can be any object that responds to #call or a block. That means that this call,


MiniTest::TestCase.add_teardown_hook { puts "foo" }



… is equivalent to:


module MyTestTeardown
  def call
    puts "foo"
  end
end

MiniTest::TestCase.add_teardown_hook MyTestTeardown



The blocks passed to add_teardown_hook take an optional parameter that will be the TestCase instance that is executing the block.















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# File 'lib/minitest/unit.rb', line 1155

def self.add_teardown_hook arg=nil, &block
  hook = arg || block
  @teardown_hooks << hook
end












.bench_exp(min, max, base = 10) ⇒ Object







Returns a set of ranges stepped exponentially from min to max by powers of base. Eg:


bench_exp(2, 16, 2) # => [2, 4, 8, 16]
















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# File 'lib/minitest/benchmark.rb', line 22

def self.bench_exp min, max, base = 10
  min = (Math.log10(min) / Math.log10(base)).to_i
  max = (Math.log10(max) / Math.log10(base)).to_i

  (min..max).map { |m| base ** m }.to_a
end












.bench_linear(min, max, step = 10) ⇒ Object







Returns a set of ranges stepped linearly from min to max by step. Eg:


bench_linear(20, 40, 10) # => [20, 30, 40]
















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# File 'lib/minitest/benchmark.rb', line 35

def self.bench_linear min, max, step = 10
  (min..max).step(step).to_a
rescue LocalJumpError # 1.8.6
  r = []; (min..max).step(step) { |n| r << n }; r
end












.bench_range ⇒ Object







Specifies the ranges used for benchmarking for that class. Defaults to exponential growth from 1 to 10k by powers of 10. Override if you need different ranges for your benchmarks.


See also: ::bench_exp and ::bench_linear.















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# File 'lib/minitest/benchmark.rb', line 63

def self.bench_range
  bench_exp 1, 10_000
end












.benchmark_methods ⇒ Object







Returns the benchmark methods (methods that start with bench_) for that class.















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# File 'lib/minitest/benchmark.rb', line 45

def self.benchmark_methods # :nodoc:
  public_instance_methods(true).grep(/^bench_/).map { |m| m.to_s }.sort
end












.benchmark_suites ⇒ Object







Returns all test suites that have benchmark methods.















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# File 'lib/minitest/benchmark.rb', line 52

def self.benchmark_suites
  TestCase.test_suites.reject { |s| s.benchmark_methods.empty? }
end












.i_suck_and_my_tests_are_order_dependent! ⇒ Object







Call this at the top of your tests when you absolutely positively need to have ordered tests. In doing so, you’re admitting that you suck and your tests are weak.















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# File 'lib/minitest/unit.rb', line 1022

def self.i_suck_and_my_tests_are_order_dependent!
  class << self
    define_method :test_order do :alpha end
  end
end












.inherited(klass) ⇒ Object







:nodoc:















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# File 'lib/minitest/unit.rb', line 1028

def self.inherited klass # :nodoc:
  @@test_suites[klass] = true
  klass.reset_setup_teardown_hooks
  super
end












.reset ⇒ Object







:nodoc:















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# File 'lib/minitest/unit.rb', line 1011

def self.reset # :nodoc:
  @@test_suites = {}
end












.reset_setup_teardown_hooks ⇒ Object







:nodoc:















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# File 'lib/minitest/unit.rb', line 1073

def self.reset_setup_teardown_hooks # :nodoc:
  @setup_hooks = []
  @teardown_hooks = []
end












.setup_hooks ⇒ Object







:nodoc:















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# File 'lib/minitest/unit.rb', line 1111

def self.setup_hooks # :nodoc:
  if superclass.respond_to? :setup_hooks then
    superclass.setup_hooks
  else
    []
  end + @setup_hooks
end












.teardown_hooks ⇒ Object







:nodoc:















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# File 'lib/minitest/unit.rb', line 1160

def self.teardown_hooks # :nodoc:
  if superclass.respond_to? :teardown_hooks then
    superclass.teardown_hooks
  else
    []
  end + @teardown_hooks
end












.test_methods ⇒ Object







:nodoc:















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# File 'lib/minitest/unit.rb', line 1042

def self.test_methods # :nodoc:
  methods = public_instance_methods(true).grep(/^test/).map { |m| m.to_s }

  case self.test_order
  when :random then
    max = methods.size
    methods.sort.sort_by { rand max }
  when :alpha, :sorted then
    methods.sort
  else
    raise "Unknown test_order: #{self.test_order.inspect}"
  end
end












.test_order ⇒ Object







:nodoc:















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# File 'lib/minitest/unit.rb', line 1034

def self.test_order # :nodoc:
  :random
end












.test_suites ⇒ Object







:nodoc:















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# File 'lib/minitest/unit.rb', line 1038

def self.test_suites # :nodoc:
  @@test_suites.keys.sort_by { |ts| ts.name.to_s }
end













Instance Method Details





#assert_performance(validation, &work) ⇒ Object







Runs the given work, gathering the times of each run. Range and times are then passed to a given validation proc. Outputs the benchmark name and times in tab-separated format, making it easy to paste into a spreadsheet for graphing or further analysis.


Ranges are specified by ::bench_range.


Eg:


def bench_algorithm
  validation = proc { |x, y| ... }
  assert_performance validation do |x|
    @obj.algorithm
  end
end
















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# File 'lib/minitest/benchmark.rb', line 85

def assert_performance validation, &work
  range = self.class.bench_range

  io.print "#{__name__}"

  times = []

  range.each do |x|
    GC.start
    t0 = Time.now
    instance_exec(x, &work)
    t = Time.now - t0

    io.print "\t%9.6f" % t
    times << t
  end
  io.puts

  validation[range, times]
end












#assert_performance_constant(threshold = 0.99, &work) ⇒ Object







Runs the given work and asserts that the times gathered fit to match a constant rate (eg, linear slope == 0) within a given threshold. Note: because we’re testing for a slope of 0, R^2 is not a good determining factor for the fit, so the threshold is applied against the slope itself. As such, you probably want to tighten it from the default.


See www.graphpad.com/curvefit/goodness_of_fit.htm for more details.


Fit is calculated by #fit_linear.


Ranges are specified by ::bench_range.


Eg:


def bench_algorithm
  assert_performance_constant 0.9999 do |x|
    @obj.algorithm
  end
end
















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# File 'lib/minitest/benchmark.rb', line 129

def assert_performance_constant threshold = 0.99, &work
  validation = proc do |range, times|
    a, b, rr = fit_linear range, times
    assert_in_delta 0, b, 1 - threshold
    [a, b, rr]
  end

  assert_performance validation, &work
end












#assert_performance_exponential(threshold = 0.99, &work) ⇒ Object







Runs the given work and asserts that the times gathered fit to match a exponential curve within a given error threshold.


Fit is calculated by #fit_exponential.


Ranges are specified by ::bench_range.


Eg:


def bench_algorithm
  assert_performance_exponential 0.9999 do |x|
    @obj.algorithm
  end
end
















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# File 'lib/minitest/benchmark.rb', line 155

def assert_performance_exponential threshold = 0.99, &work
  assert_performance validation_for_fit(:exponential, threshold), &work
end












#assert_performance_linear(threshold = 0.99, &work) ⇒ Object







Runs the given work and asserts that the times gathered fit to match a straight line within a given error threshold.


Fit is calculated by #fit_linear.


Ranges are specified by ::bench_range.


Eg:


def bench_algorithm
  assert_performance_linear 0.9999 do |x|
    @obj.algorithm
  end
end
















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# File 'lib/minitest/benchmark.rb', line 175

def assert_performance_linear threshold = 0.99, &work
  assert_performance validation_for_fit(:linear, threshold), &work
end












#assert_performance_power(threshold = 0.99, &work) ⇒ Object







Runs the given work and asserts that the times gathered curve fit to match a power curve within a given error threshold.


Fit is calculated by #fit_power.


Ranges are specified by ::bench_range.


Eg:


def bench_algorithm
  assert_performance_power 0.9999 do |x|
    @obj.algorithm
  end
end
















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# File 'lib/minitest/benchmark.rb', line 195

def assert_performance_power threshold = 0.99, &work
  assert_performance validation_for_fit(:power, threshold), &work
end












#fit_error(xys) ⇒ Object







Takes an array of x/y pairs and calculates the general R^2 value.


See: en.wikipedia.org/wiki/Coefficient_of_determination















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# File 'lib/minitest/benchmark.rb', line 204

def fit_error xys
  y_bar  = sigma(xys) { |x, y| y } / xys.size.to_f
  ss_tot = sigma(xys) { |x, y| (y    - y_bar) ** 2 }
  ss_err = sigma(xys) { |x, y| (yield(x) - y) ** 2 }

  1 - (ss_err / ss_tot)
end












#fit_exponential(xs, ys) ⇒ Object







To fit a functional form: y = ae^(bx).


Takes x and y values and returns [a, b, r^2].


See: mathworld.wolfram.com/LeastSquaresFittingExponential.html















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# File 'lib/minitest/benchmark.rb', line 219

def fit_exponential xs, ys
  n     = xs.size
  xys   = xs.zip(ys)
  sxlny = sigma(xys) { |x,y| x * Math.log(y) }
  slny  = sigma(xys) { |x,y| Math.log(y)     }
  sx2   = sigma(xys) { |x,y| x * x           }
  sx    = sigma xs

  c = n * sx2 - sx ** 2
  a = (slny * sx2 - sx * sxlny) / c
  b = ( n * sxlny - sx * slny ) / c

  return Math.exp(a), b, fit_error(xys) { |x| Math.exp(a + b * x) }
end












#fit_linear(xs, ys) ⇒ Object







Fits the functional form: a + bx.


Takes x and y values and returns [a, b, r^2].


See: mathworld.wolfram.com/LeastSquaresFitting.html















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# File 'lib/minitest/benchmark.rb', line 241

def fit_linear xs, ys
  n   = xs.size
  xys = xs.zip(ys)
  sx  = sigma xs
  sy  = sigma ys
  sx2 = sigma(xs)  { |x|   x ** 2 }
  sxy = sigma(xys) { |x,y| x * y  }

  c = n * sx2 - sx**2
  a = (sy * sx2 - sx * sxy) / c
  b = ( n * sxy - sx * sy ) / c

  return a, b, fit_error(xys) { |x| a + b * x }
end












#fit_power(xs, ys) ⇒ Object







To fit a functional form: y = ax^b.


Takes x and y values and returns [a, b, r^2].


See: mathworld.wolfram.com/LeastSquaresFittingPowerLaw.html















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# File 'lib/minitest/benchmark.rb', line 263

def fit_power xs, ys
  n       = xs.size
  xys     = xs.zip(ys)
  slnxlny = sigma(xys) { |x, y| Math.log(x) * Math.log(y) }
  slnx    = sigma(xs)  { |x   | Math.log(x)               }
  slny    = sigma(ys)  { |   y| Math.log(y)               }
  slnx2   = sigma(xs)  { |x   | Math.log(x) ** 2          }

  b = (n * slnxlny - slnx * slny) / (n * slnx2 - slnx ** 2);
  a = (slny - b * slnx) / n

  return Math.exp(a), b, fit_error(xys) { |x| (Math.exp(a) * (x ** b)) }
end












#io ⇒ Object










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# File 'lib/minitest/unit.rb', line 1002

def io
  @__io__ = true
  MiniTest::Unit.output
end












#io? ⇒ Boolean













Returns:


    

  • 
(Boolean)

    • 










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# File 'lib/minitest/unit.rb', line 1007

def io?
  @__io__
end












#passed? ⇒ Boolean







Returns true if the test passed.








Returns:


    

  • 
(Boolean)

    • 










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# File 'lib/minitest/unit.rb', line 1059

def passed?
  @passed
end












#run(runner) ⇒ Object







Runs the tests reporting the status to runner















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# File 'lib/minitest/unit.rb', line 962

def run runner
  trap "INFO" do
    time = runner.start_time ? Time.now - runner.start_time : 0
    warn "%s#%s %.2fs" % [self.class, self.__name__, time]
    runner.status $stderr
  end if SUPPORTS_INFO_SIGNAL

  result = ""
  begin
    @passed = nil
    self.setup
    self.run_setup_hooks
    self.__send__ self.__name__
    result = "." unless io?
    @passed = true
  rescue *PASSTHROUGH_EXCEPTIONS
    raise
  rescue Exception => e
    @passed = false
    result = runner.puke self.class, self.__name__, e
  ensure
    begin
      self.run_teardown_hooks
      self.teardown
    rescue *PASSTHROUGH_EXCEPTIONS
      raise
    rescue Exception => e
      result = runner.puke self.class, self.__name__, e
    end
    trap 'INFO', 'DEFAULT' if SUPPORTS_INFO_SIGNAL
  end
  result
end












#run_setup_hooks ⇒ Object







:nodoc:















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# File 'lib/minitest/unit.rb', line 1119

def run_setup_hooks # :nodoc:
  self.class.setup_hooks.each do |hook|
    if hook.respond_to?(:arity) && hook.arity == 1
      hook.call(self)
    else
      hook.call
    end
  end
end












#run_teardown_hooks ⇒ Object







:nodoc:















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# File 'lib/minitest/unit.rb', line 1168

def run_teardown_hooks # :nodoc:
  self.class.teardown_hooks.reverse.each do |hook|
    if hook.respond_to?(:arity) && hook.arity == 1
      hook.call(self)
    else
      hook.call
    end
  end
end












#setup ⇒ Object







Runs before every test. Use this to refactor test initialization.















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# File 'lib/minitest/unit.rb', line 1066

def setup; end












#sigma(enum, &block) ⇒ Object







Enumerates over enum mapping block if given, returning the sum of the result. Eg:


sigma([1, 2, 3])                # => 1 + 2 + 3 => 7
sigma([1, 2, 3]) { |n| n ** 2 } # => 1 + 4 + 9 => 14
















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# File 'lib/minitest/benchmark.rb', line 284

def sigma enum, &block
  enum = enum.map(&block) if block
  enum.inject { |sum, n| sum + n }
end












#teardown ⇒ Object







Runs after every test. Use this to refactor test cleanup.















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# File 'lib/minitest/unit.rb', line 1071

def teardown; end












#validation_for_fit(msg, threshold) ⇒ Object







Returns a proc that calls the specified fit method and asserts that the error is within a tolerable threshold.















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# File 'lib/minitest/benchmark.rb', line 293

def validation_for_fit msg, threshold
  proc do |range, times|
    a, b, rr = send "fit_#{msg}", range, times
    assert_operator rr, :>=, threshold
    [a, b, rr]
  end
end