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Class: Minitest::BenchSpec

Relationships & Source Files
Super Chains via Extension / Inclusion / Inheritance
Class Chain:
Instance Chain:
Inherits: Minitest::Benchmark
Defined in: lib/minitest/benchmark.rb

Overview

The spec version of Benchmark.

Constant Summary

Runnable - Inherited

SIGNALS

Assertions - Included

E, UNDEFINED

Test - Inherited

PASSTHROUGH_EXCEPTIONS, TEARDOWN_METHODS

Class Attribute Summary

Spec::DSL - Extended

Test - Inherited

Class Method Summary

Spec::DSL - Extended

after

Define an ‘after’ action.

before

Define a ‘before’ action.

it

Define an expectation with name desc.

let

Essentially, define an accessor for name with block.

register_spec_type

Register a new type of spec that matches the spec’s description.

spec_type

Figure out the spec class to use based on a spec’s description.

specify

Alias for Spec::DSL#it.

subject

Another lazy man’s accessor generator.

children, create, describe_stack, name, nuke_test_methods!, to_s

Benchmark - Inherited

.bench_exp

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

.bench_linear

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

.bench_range

Specifies the ranges used for benchmarking for that class.

.io, .run, .runnable_methods

Test - Inherited

.i_suck_and_my_tests_are_order_dependent!

Call this at the top of your tests when you absolutely positively need to have ordered tests.

.make_my_diffs_pretty!

Make diffs for this Test use #pretty_inspect so that diff in assert_equal can have more details.

.parallelize_me!

Call this at the top of your tests when you want to run your tests in parallel.

.runnable_methods

Returns all instance methods starting with “test_”.

.test_order

Defines the order to run tests (:random by default).

Guard - Extended

jruby?

Is this running on jruby?

maglev?

Is this running on maglev?

mri?

Is this running on mri?

rubinius?

Is this running on rubinius?

windows?

Is this running on windows?

Runnable - Inherited

.methods_matching

Returns all instance methods matching the pattern re.

.run

Responsible for running all runnable methods in a given class, each in its own instance.

.run_one_method

Runs a single method and has the reporter record the result.

.runnable_methods

Each subclass of Runnable is responsible for overriding this method to return all runnable methods.

.runnables

Returns all subclasses of Runnable.

.inherited, .new, .on_signal, .reset, .with_info_handler

Instance Attribute Summary

Reportable - Included

#error?

Did this run error?

#passed?

Did this run pass?

#skipped?

Was this run skipped?

Assertions - Included

#skipped?

Was this testcase skipped? Meant for #teardown.

Runnable - Inherited

#assertions

Number of assertions executed in this run.

#failures

An assertion raised during the run, if any.

#name

Name of the run.

#name=

Set the name of the run.

#passed?

Did this run pass?

#skipped?

Was this run skipped? See #passed? for more information.

#time

The time it took to run.

Instance Method Summary

Benchmark - Inherited

#assert_performance

Runs the given work, gathering the times of each run.

#assert_performance_constant

Runs the given work and asserts that the times gathered fit to match a constant rate (eg, linear slope == 0) within a given threshold.

#assert_performance_exponential

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

#assert_performance_linear

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

#assert_performance_logarithmic

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

#assert_performance_power

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

#fit_error

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

#fit_exponential

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

#fit_linear

Fits the functional form: a + bx.

#fit_logarithmic

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

#fit_power

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

#sigma

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

#validation_for_fit

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

#io

Test - Inherited

#run

Runs a single test with setup/teardown hooks.

#capture_exceptions

LifecycleHooks.

#class_name, #with_info_handler

Guard - Included

#jruby?

Is this running on jruby?

#maglev?

Is this running on maglev?

#mri?

Is this running on mri?

#rubinius?

Is this running on rubinius?

#windows?

Is this running on windows?

Test::LifecycleHooks - Included

#after_setup

Runs before every test, after setup.

#after_teardown

Runs after every test, after teardown.

#before_setup

Runs before every test, before setup.

#before_teardown

Runs after every test, before teardown.

#setup

Runs before every test.

#teardown

Runs after every test.

Reportable - Included

#location

The location identifier of this test.

#result_code

Returns “.”, “F”, or “E” based on the result of the run.

#class_name

Assertions - Included

#assert

Fails unless test is truthy.

#assert_empty

Fails unless obj is empty.

#assert_equal

Fails unless exp == act printing the difference between the two, if possible.

#assert_in_delta

For comparing Floats.

#assert_in_epsilon

For comparing Floats.

#assert_includes

Fails unless collection includes obj.

#assert_instance_of

Fails unless obj is an instance of cls.

#assert_kind_of

Fails unless obj is a kind of cls.

#assert_match

Fails unless matcher =~ obj.

#assert_mock

Assert that the mock verifies correctly.

#assert_nil

Fails unless obj is nil.

#assert_operator

For testing with binary operators.

#assert_output

Fails if stdout or stderr do not output the expected results.

#assert_predicate

For testing with predicates.

#assert_raises

Fails unless the block raises one of exp.

#assert_respond_to

Fails unless obj responds to meth.

#assert_same

Fails unless exp and act are #equal?

#assert_send

send_ary is a receiver, message and arguments.

#assert_silent

Fails if the block outputs anything to stderr or stdout.

#assert_throws

Fails unless the block throws sym

#capture_io

Captures $stdout and $stderr into strings:

#capture_subprocess_io

Captures $stdout and $stderr into strings, using Tempfile to ensure that subprocess IO is captured as well.

#diff

Returns a diff between exp and act.

#exception_details

Returns details for exception e

#flunk

Fails with msg

#message

Returns a proc that will output msg along with the default message.

#mu_pp

This returns a human-readable version of obj.

#mu_pp_for_diff

This returns a diff-able human-readable version of obj.

#pass

used for counting assertions.

#refute

Fails if test is truthy.

#refute_empty

Fails if obj is empty.

#refute_equal

Fails if exp == act.

#refute_in_delta

For comparing Floats.

#refute_in_epsilon

For comparing Floats.

#refute_includes

Fails if collection includes obj.

#refute_instance_of

Fails if obj is an instance of cls.

#refute_kind_of

Fails if obj is a kind of cls.

#refute_match

Fails if matcher =~ obj.

#refute_nil

Fails if obj is nil.

#refute_operator

Fails if o1 is not op o2.

#refute_predicate

For testing with predicates.

#refute_respond_to

Fails if obj responds to the message meth.

#refute_same

Fails if exp is the same (by object identity) as act.

#skip

Skips the current run.

#_synchronize

Runnable - Inherited

#result_code

Returns a single character string to print based on the result of the run.

#run

Runs a single method.

#failure, #marshal_dump, #marshal_load, #time_it

Constructor Details

This class inherits a constructor from Minitest::Runnable

Class Method Details

.bench(name, &block)

This is used to define a new benchmark method. You usually don’t use this directly and is intended for those needing to write new performance curve fits (eg: you need a specific polynomial fit).

See .bench_performance_linear for an example of how to use this.

[ GitHub ]

  
# File 'lib/minitest/benchmark.rb', line 357

def self.bench name, &block
  define_method "bench_#{name.gsub(/\W+/, "_")}", &block
end

.bench_performance_constant(name, threshold = 0.99, &work)

Create a benchmark that verifies that the performance is constant.

describe "my class Bench" do
  bench_performance_constant "zoom_algorithm!" do |n|
    @obj.zoom_algorithm!(n)
  end
end
[ GitHub ]

  
# File 'lib/minitest/benchmark.rb', line 401

def self.bench_performance_constant name, threshold = 0.99, &work
  bench name do
    assert_performance_constant threshold, &work
  end
end

.bench_performance_exponential(name, threshold = 0.99, &work)

Create a benchmark that verifies that the performance is exponential.

describe "my class Bench" do
  bench_performance_exponential "algorithm" do |n|
    @obj.algorithm(n)
  end
end
[ GitHub ]

  
# File 'lib/minitest/benchmark.rb', line 416

def self.bench_performance_exponential name, threshold = 0.99, &work
  bench name do
    assert_performance_exponential threshold, &work
  end
end

.bench_performance_linear(name, threshold = 0.99, &work)

Create a benchmark that verifies that the performance is linear.

describe "my class Bench" do
  bench_performance_linear "fast_algorithm", 0.9999 do |n|
    @obj.fast_algorithm(n)
  end
end
[ GitHub ]

  
# File 'lib/minitest/benchmark.rb', line 386

def self.bench_performance_linear name, threshold = 0.99, &work
  bench name do
    assert_performance_linear threshold, &work
  end
end

.bench_performance_logarithmic(name, threshold = 0.99, &work)

Create a benchmark that verifies that the performance is logarithmic.

describe "my class Bench" do
  bench_performance_logarithmic "algorithm" do |n|
    @obj.algorithm(n)
  end
end
[ GitHub ]

  
# File 'lib/minitest/benchmark.rb', line 432

def self.bench_performance_logarithmic name, threshold = 0.99, &work
  bench name do
    assert_performance_logarithmic threshold, &work
  end
end

.bench_performance_power(name, threshold = 0.99, &work)

Create a benchmark that verifies that the performance is power.

describe "my class Bench" do
  bench_performance_power "algorithm" do |n|
    @obj.algorithm(n)
  end
end
[ GitHub ]

  
# File 'lib/minitest/benchmark.rb', line 447

def self.bench_performance_power name, threshold = 0.99, &work
  bench name do
    assert_performance_power threshold, &work
  end
end

.bench_range(&block)

Specifies the ranges used for benchmarking for that class.

bench_range do
  bench_exp(2, 16, 2)
end

See Minitest::Benchmark#bench_range for more details.

[ GitHub ]

  
# File 'lib/minitest/benchmark.rb', line 370

def self.bench_range &block
  return super unless block

  meta = (class << self; self; end)
  meta.send :define_method, "bench_range", &block
end