Class: MiniTest::Unit::TestCase

Inherits:
Object
  • Object
show all
Extended by:
Guard
Includes:
Assertions, Guard, LifecycleHooks
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


Instance Attribute Summary collapse




Class Method Summary
collapse





Instance Method Summary
collapse




Methods included from Guard


jruby?, maglev?, mri?, rubinius?, windows?


Methods included from Assertions


#_assertions, #_assertions=, #assert, #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, #capture_subprocess_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, #skipped?, #synchronize


Methods included from LifecycleHooks


#after_setup, #after_teardown, #before_setup, #before_teardown




Constructor Details





#initialize(name) ⇒ TestCase







:nodoc:















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# File 'lib/minitest/unit.rb', line 1268

def initialize name # :nodoc:
  @__name__ = name
  @__io__ = nil
  @passed = nil
  @@current = self # FIX: make thread local
end













Instance Attribute Details






#__name__ ⇒ Object (readonly)







:nodoc:















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# File 'lib/minitest/unit.rb', line 1208

def __name__
  @__name__
end













Class Method Details





.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 20

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 33

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 61

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 43

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 50

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












.current ⇒ Object







:nodoc:















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# File 'lib/minitest/unit.rb', line 1275

def self.current # :nodoc:
  @@current # FIX: make thread local
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 1305

def self.i_suck_and_my_tests_are_order_dependent!
  class << self
    undef_method :test_order if method_defined? :test_order
    define_method :test_order do :alpha end
  end
end












.inherited(klass) ⇒ Object







:nodoc:















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# File 'lib/minitest/unit.rb', line 1340

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












.make_my_diffs_pretty! ⇒ Object







Make diffs for this TestCase use #pretty_inspect so that diff in assert_equal can be more details. NOTE: this is much slower than the regular inspect but much more usable for complex objects.















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# File 'lib/minitest/unit.rb', line 1318

def self.make_my_diffs_pretty!
  require 'pp'

  define_method :mu_pp do |o|
    o.pretty_inspect
  end
end












.parallelize_me! ⇒ Object







Call this at the top of your tests when you want to run your tests in parallel. In doing so, you’re admitting that you rule and your tests are awesome.















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# File 'lib/minitest/unit.rb', line 1331

def self.parallelize_me!
  require "minitest/parallel_each"

  class << self
    undef_method :test_order if method_defined? :test_order
    define_method :test_order do :parallel end
  end
end












.reset ⇒ Object







:nodoc:















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# File 'lib/minitest/unit.rb', line 1294

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












.test_methods ⇒ Object







:nodoc:















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# File 'lib/minitest/unit.rb', line 1353

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

  case self.test_order
  when :parallel
    max = methods.size
    ParallelEach.new methods.sort.sort_by { rand max }
  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 1345

def self.test_order # :nodoc:
  :random
end












.test_suites ⇒ Object







:nodoc:















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# File 'lib/minitest/unit.rb', line 1349

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 |n|
    @obj.algorithm(n)
  end
end
















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# File 'lib/minitest/benchmark.rb', line 83

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 |n|
    @obj.algorithm(n)
  end
end
















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# File 'lib/minitest/benchmark.rb', line 127

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 |n|
    @obj.algorithm(n)
  end
end
















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# File 'lib/minitest/benchmark.rb', line 153

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 |n|
    @obj.algorithm(n)
  end
end
















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# File 'lib/minitest/benchmark.rb', line 193

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












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







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


Fit is calculated by #fit_logarithmic.


Ranges are specified by ::bench_range.


Eg:


def bench_algorithm
  assert_performance_logarithmic 0.9999 do |n|
    @obj.algorithm(n)
  end
end
















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# File 'lib/minitest/benchmark.rb', line 173

def assert_performance_logarithmic threshold = 0.99, &work
  assert_performance validation_for_fit(:logarithmic, 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 213

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 222

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 237

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 282

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_logarithmic(xs, ys) ⇒ Object







To fit a functional form: y = a + b*ln(x).


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


See: mathworld.wolfram.com/LeastSquaresFittingLogarithmic.html















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# File 'lib/minitest/benchmark.rb', line 259

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

  c = n * slnx2 - slnx ** 2
  b = ( n * sylnx - sy * slnx ) / c
  a = (sy - b * slnx) / n

  return a, b, fit_error(xys) { |x| a + b * Math.log(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 304

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







Return the output IO object















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# File 'lib/minitest/unit.rb', line 1282

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












#io? ⇒ Boolean







Have we hooked up the IO yet?








Returns:


    

  • 
(Boolean)

    • 










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# File 'lib/minitest/unit.rb', line 1290

def io?
  @__io__
end












#passed? ⇒ Boolean







Returns true if the test passed.








Returns:


    

  • 
(Boolean)

    • 










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# File 'lib/minitest/unit.rb', line 1373

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 1218

def run runner
  trap "INFO" do
    runner.report.each_with_index do |msg, i|
      warn "\n%3d) %s" % [i + 1, msg]
    end
    warn ''
    time = runner.start_time ? Time.now - runner.start_time : 0
    warn "Current Test: %s#%s %.2fs" % [self.class, self.__name__, time]
    runner.status $stderr
  end if SUPPORTS_INFO_SIGNAL

  start_time = Time.now

  result = ""
  begin
    @passed = nil
    self.before_setup
    self.setup
    self.after_setup
    self.run_test self.__name__
    result = "." unless io?
    time = Time.now - start_time
    runner.record self.class, self.__name__, self._assertions, time, nil
    @passed = true
  rescue *PASSTHROUGH_EXCEPTIONS
    raise
  rescue Exception => e
    @passed = Skip === e
    time = Time.now - start_time
    runner.record self.class, self.__name__, self._assertions, time, e
    result = runner.puke self.class, self.__name__, e
  ensure
    %w{ before_teardown teardown after_teardown }.each do |hook|
      begin
        self.send hook
      rescue *PASSTHROUGH_EXCEPTIONS
        raise
      rescue Exception => e
        @passed = false
        runner.record self.class, self.__name__, self._assertions, time, e
        result = runner.puke self.class, self.__name__, e
      end
    end
    trap 'INFO', 'DEFAULT' if SUPPORTS_INFO_SIGNAL
  end
  result
end












#setup ⇒ Object







Runs before every test. Use this to set up before each test run.















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# File 'lib/minitest/unit.rb', line 1381

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 325

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 clean up after each test run.















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# File 'lib/minitest/unit.rb', line 1387

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 334

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