qsprpred.utils package

Subpackages

Submodules

qsprpred.utils.inspect module

qsprpred.utils.inspect.dynamic_import(object_path: str)[source]

Import an object from an import path dynamically.

Parameters:

object_path (str) – fully classified path to the object to be imported

qsprpred.utils.parallel module

class qsprpred.utils.parallel.JITParallelGenerator(n_workers: int | None = None, worker_type: Literal['cpu', 'gpu'] = 'cpu', use_gpus: list[int] | None = None, jobs_per_gpu: int = 1)[source]

Bases: ParallelGenerator, ABC

An abstract class to facilitate JIT (Just In Time) parallel processing of an arbitrary generator. This is meant for situations where the result of the generator is too large to fit into memory or not yet known. Parallelization can be done over a pool of CPU or GPU workers. The generator will yield the results of the function applied in parallel to each item of a supplied generator.

Configures the multiprocessing pool generator.

Parameters:

  • n_workers (int) – Number of workers to use.

  • worker_type (Literal["cpu", "gpu"]) – The type of worker to use.

  • use_gpus (list[int] | None) – A list of GPU indices to use. Only applicable if worker_type is ‘gpu’. If None, all available GPUs will be used.

  • jobs_per_gpu (int) – Number of jobs to run on each GPU.

abstract checkProcess(process: Any)[source]

A simple check of a process or future before a result is attempted to be retrieved.

Parameters:

process (Any) – The process object or a future to check.

Returns:

None if the process is OK, otherwise raises an exception.

Raises:

Exception – If the process has a problem.

abstract checkResultAvailable(process: Any) → bool[source]

Check if the result of a process is available.

Parameters:

process (Any) – The process object or a future to check for a result.

Returns:

True if the result is available, otherwise False.

abstract createJob(pool: Any, process_func: Callable, *args, **kwargs) → Any[source]

Submit a job to the pool that applies the function to a generator item.

Parameters:

  • pool (Any) – The pool object to submit the job to.

  • process_func (Callable) – The function to apply to the input arguments.

  • args (tuple) – Positional arguments to pass to the function. The first argument should be the item from the generator.

  • kwargs (dict) – Additional keyword arguments to pass to the function.

Returns:

The process object or future that was submitted to the pool.

abstract getPool() → Any[source]

Create the pool of workers consuming the generator.

Returns:

A pool object that can be used to apply the function to the generator items in parallel.

abstract getResult(process: Any) → Any[source]

Get the result of a process.

Parameters:

process (Any) – The process object or a future to get the result from.

Returns:

The result of the process.

abstract handleException(process: Any, exception: Exception) → Any[source]

Handle an exception raised by a process. This is executed when the process raises an unexpected exception or the checkProcess method raises an exception.

Parameters:

  • process (Any) – The process object or a future that raised the exception.

  • exception (Exception) – The exception raised by the process.

Returns:

The result to yield instead of the result of the process.

make(generator: Generator, process_func: Callable, *args, **kwargs) → Generator[source]

A parallel “JIT (Just In Time)” generator that yields the results of a function applied in parallel to each item of a supplied generator. The advantage of this JIT implementation is that it only evaluates the next item in the input generator as soon as it is needed for the calculation. This means that only one item from the iterable is loaded into memory at a time.

The generator also supports timeout for each job. The “pebble” pool_type can be used to support this feature. In all other cases, the “multiprocessing” pool_type is sufficient.

Parameters:

  • generator (SupportsNext) – An iterable object to apply the function to.

  • process_func (Callable) – The function to apply to each item in the iterable.

  • args (tuple | None) – Additional positional arguments to pass to the function.

  • kwargs (dict | None) – Additional keyword arguments to pass to the function.

Returns:

A generator that yields the results of the function applied to each item in the iterable. If a timeout is specified, a TimeoutError will be returned instead.

class qsprpred.utils.parallel.MultiprocessingJITGenerator(n_workers: int | None = None, worker_type: Literal['cpu', 'gpu'] = 'cpu', use_gpus: list[int] | None = None, jobs_per_gpu: int = 1)[source]

Bases: JITParallelGenerator

A parallel generator that uses the multiprocessing module to parallelize the processing of an input generator. This is useful when the input generator is too large to fit into memory and needs to be processed in parallel over a pool of workers.

Configures the multiprocessing pool generator.

Parameters:

  • n_workers (int) – Number of workers to use.

  • worker_type (Literal["cpu", "gpu"]) – The type of worker to use.

  • use_gpus (list[int] | None) – A list of GPU indices to use. Only applicable if worker_type is ‘gpu’. If None, all available GPUs will be used.

  • jobs_per_gpu (int) – Number of jobs to run on each GPU.

checkProcess(process)[source]

A simple check of a process or future before a result is attempted to be retrieved.

Parameters:

process (Any) – The process object or a future to check.

Returns:

None if the process is OK, otherwise raises an exception.

Raises:

Exception – If the process has a problem.

checkResultAvailable(process)[source]

Check if the result of a process is available.

Parameters:

process (Any) – The process object or a future to check for a result.

Returns:

True if the result is available, otherwise False.

createJob(pool, process_func, *args, **kwargs)[source]

Submit a job to the pool that applies the function to a generator item.

Parameters:

  • pool (Any) – The pool object to submit the job to.

  • process_func (Callable) – The function to apply to the input arguments.

  • args (tuple) – Positional arguments to pass to the function. The first argument should be the item from the generator.

  • kwargs (dict) – Additional keyword arguments to pass to the function.

Returns:

The process object or future that was submitted to the pool.

getPool()[source]

Create the pool of workers consuming the generator.

Returns:

A pool object that can be used to apply the function to the generator items in parallel.

getResult(process)[source]

Get the result of a process.

Parameters:

process (Any) – The process object or a future to get the result from.

Returns:

The result of the process.

handleException(process, exception)[source]

Handle an exception raised by a process. This is executed when the process raises an unexpected exception or the checkProcess method raises an exception.

Parameters:

  • process (Any) – The process object or a future that raised the exception.

  • exception (Exception) – The exception raised by the process.

Returns:

The result to yield instead of the result of the process.

make(generator: Generator, process_func: Callable, *args, **kwargs) → Generator

A parallel “JIT (Just In Time)” generator that yields the results of a function applied in parallel to each item of a supplied generator. The advantage of this JIT implementation is that it only evaluates the next item in the input generator as soon as it is needed for the calculation. This means that only one item from the iterable is loaded into memory at a time.

The generator also supports timeout for each job. The “pebble” pool_type can be used to support this feature. In all other cases, the “multiprocessing” pool_type is sufficient.

Parameters:

  • generator (SupportsNext) – An iterable object to apply the function to.

  • process_func (Callable) – The function to apply to each item in the iterable.

  • args (tuple | None) – Additional positional arguments to pass to the function.

  • kwargs (dict | None) – Additional keyword arguments to pass to the function.

Returns:

A generator that yields the results of the function applied to each item in the iterable. If a timeout is specified, a TimeoutError will be returned instead.

class qsprpred.utils.parallel.ParallelGenerator[source]

Bases: ABC

An abstract class to facilitate parallel processing of an arbitrary generator.

abstract make(generator: Generator, process_func: Callable, *args, **kwargs) → Generator[source]

This method is used to wrap an input generator or an iterable (needs to support next()). The method should evaluate one item of the generator at a time and apply the process_func to it. This is done in parallel over a pool of workers. The method should return a generator that yields the results of the function applied in parallel as soon as the results are available. Therefore, the user can simply iterate over the generator to get the results.

Parameters:

  • generator – An iterable object to apply the function to.

  • process_func – The function to apply to each item in the iterable.

Returns:

A generator that yields the results of the function applied to each item in the iterable in parallel.

class qsprpred.utils.parallel.PebbleJITGenerator(n_workers: int | None = None, worker_type: Literal['cpu', 'gpu'] = 'cpu', use_gpus: list[int] | None = None, jobs_per_gpu: int = 1, timeout: int | None = None)[source]

Bases: JITParallelGenerator

Uses the pebble library to parallelize the processing of an input generator. The main benefit of using pebble is that it supports timeouts for each job, which makes it easy to handle jobs that take too long to process.

Configures the multiprocessing pool generator.

Parameters:

  • n_workers (int) – Number of workers to use.

  • worker_type (Literal["cpu", "gpu"]) – The type of worker to use.

  • use_gpus (list[int] | None) – A list of GPU indices to use. Only applicable if worker_type is ‘gpu’. If None, all available GPUs will be used.

  • jobs_per_gpu (int) – Number of jobs to run on each GPU.

  • timeout (int | None) – A timeout threshold in seconds. Processes that exceed this threshold will be terminated and a TimeoutError will be returned.

checkProcess(process: Any)[source]

A simple check of a process or future before a result is attempted to be retrieved.

Parameters:

process (Any) – The process object or a future to check.

Returns:

None if the process is OK, otherwise raises an exception.

Raises:

Exception – If the process has a problem.

checkResultAvailable(process: ProcessFuture)[source]

Check if the result of a process is available.

Parameters:

process (Any) – The process object or a future to check for a result.

Returns:

True if the result is available, otherwise False.

createJob(pool: Any, process_func: Callable, *args, **kwargs) → Any[source]

Submit a job to the pool that applies the function to a generator item.

Parameters:

  • pool (Any) – The pool object to submit the job to.

  • process_func (Callable) – The function to apply to the input arguments.

  • args (tuple) – Positional arguments to pass to the function. The first argument should be the item from the generator.

  • kwargs (dict) – Additional keyword arguments to pass to the function.

Returns:

The process object or future that was submitted to the pool.

getPool() → Any[source]

Create the pool of workers consuming the generator.

Returns:

A pool object that can be used to apply the function to the generator items in parallel.

getResult(process: Any)[source]

Get the result of a process.

Parameters:

process (Any) – The process object or a future to get the result from.

Returns:

The result of the process.

handleException(process: Any, exception: Exception) → Any[source]

Handle an exception raised by a process. This is executed when the process raises an unexpected exception or the checkProcess method raises an exception.

Parameters:

  • process (Any) – The process object or a future that raised the exception.

  • exception (Exception) – The exception raised by the process.

Returns:

The result to yield instead of the result of the process.

make(generator: Generator, process_func: Callable, *args, **kwargs) → Generator

A parallel “JIT (Just In Time)” generator that yields the results of a function applied in parallel to each item of a supplied generator. The advantage of this JIT implementation is that it only evaluates the next item in the input generator as soon as it is needed for the calculation. This means that only one item from the iterable is loaded into memory at a time.

The generator also supports timeout for each job. The “pebble” pool_type can be used to support this feature. In all other cases, the “multiprocessing” pool_type is sufficient.

Parameters:

  • generator (SupportsNext) – An iterable object to apply the function to.

  • process_func (Callable) – The function to apply to each item in the iterable.

  • args (tuple | None) – Additional positional arguments to pass to the function.

  • kwargs (dict | None) – Additional keyword arguments to pass to the function.

Returns:

A generator that yields the results of the function applied to each item in the iterable. If a timeout is specified, a TimeoutError will be returned instead.

class qsprpred.utils.parallel.ThreadsJITGenerator(n_workers: int | None = None, worker_type: Literal['cpu', 'gpu'] = 'cpu', use_gpus: list[int] | None = None, jobs_per_gpu: int = 1)[source]

Bases: JITParallelGenerator

This class uses the concurrent.futures.ThreadPoolExecutor to parallelize the processing of an input generator. Note that threads in Python are not truly parallel due to the Global Interpreter Lock (GIL). However, this can still be useful for I/O-bound tasks or tasks that are not CPU-bound downstream.

Configures the multiprocessing pool generator.

Parameters:

  • n_workers (int) – Number of workers to use.

  • worker_type (Literal["cpu", "gpu"]) – The type of worker to use.

  • use_gpus (list[int] | None) – A list of GPU indices to use. Only applicable if worker_type is ‘gpu’. If None, all available GPUs will be used.

  • jobs_per_gpu (int) – Number of jobs to run on each GPU.

checkProcess(process: Any)[source]

A simple check of a process or future before a result is attempted to be retrieved.

Parameters:

process (Any) – The process object or a future to check.

Returns:

None if the process is OK, otherwise raises an exception.

Raises:

Exception – If the process has a problem.

checkResultAvailable(process: Future)[source]

Check if the result of a process is available.

Parameters:

process (Any) – The process object or a future to check for a result.

Returns:

True if the result is available, otherwise False.

createJob(pool: Any, process_func: Callable, *args, **kwargs) → Any[source]

Submit a job to the pool that applies the function to a generator item.

Parameters:

  • pool (Any) – The pool object to submit the job to.

  • process_func (Callable) – The function to apply to the input arguments.

  • args (tuple) – Positional arguments to pass to the function. The first argument should be the item from the generator.

  • kwargs (dict) – Additional keyword arguments to pass to the function.

Returns:

The process object or future that was submitted to the pool.

getPool() → Any[source]

Create the pool of workers consuming the generator.

Returns:

A pool object that can be used to apply the function to the generator items in parallel.

getResult(process: Any)[source]

Get the result of a process.

Parameters:

process (Any) – The process object or a future to get the result from.

Returns:

The result of the process.

handleException(process: Any, exception: Exception) → Any[source]

Handle an exception raised by a process. This is executed when the process raises an unexpected exception or the checkProcess method raises an exception.

Parameters:

  • process (Any) – The process object or a future that raised the exception.

  • exception (Exception) – The exception raised by the process.

Returns:

The result to yield instead of the result of the process.

make(generator: Generator, process_func: Callable, *args, **kwargs) → Generator

A parallel “JIT (Just In Time)” generator that yields the results of a function applied in parallel to each item of a supplied generator. The advantage of this JIT implementation is that it only evaluates the next item in the input generator as soon as it is needed for the calculation. This means that only one item from the iterable is loaded into memory at a time.

The generator also supports timeout for each job. The “pebble” pool_type can be used to support this feature. In all other cases, the “multiprocessing” pool_type is sufficient.

Parameters:

  • generator (SupportsNext) – An iterable object to apply the function to.

  • process_func (Callable) – The function to apply to each item in the iterable.

  • args (tuple | None) – Additional positional arguments to pass to the function.

  • kwargs (dict | None) – Additional keyword arguments to pass to the function.

Returns:

A generator that yields the results of the function applied to each item in the iterable. If a timeout is specified, a TimeoutError will be returned instead.

qsprpred.utils.parallel.batched_generator(iterable: Iterable, batch_size: int) → Generator[source]

A simple helper generator that batches inputs from a supplied Iterable.

Parameters:

  • iterable – An iterable object to batch with the generator.

  • batch_size – Number of items to include in each batch.

Returns:

A generator that yields batches of the input generator one at a time.

qsprpred.utils.serialization module

class qsprpred.utils.serialization.FileSerializable[source]

Bases: ABC

A class that can be serialized to a file and reconstructed from a file.

abstract classmethod fromFile(filename: str) → object[source]

Reconstruct object from a metafile.

Parameters:

filename (str) – filename of the metafile to load object from

Returns:

reconstructed object

Return type:

obj (object)

abstract toFile(filename: str) → str[source]

Serialize object to a metafile. This metafile should contain all data necessary to reconstruct the object.

Parameters:

filename (str) – filename to save object to

Returns:

absolute path to the saved metafile of the object

Return type:

filename (str)

class qsprpred.utils.serialization.JSONSerializable[source]

Bases: FileSerializable

A class that can be serialized to JSON and reconstructed from JSON.

Variables:

_notJSON (list) – list of attributes that should not be serialized to JSON explicitly

classmethod fromFile(filename: str) → Any[source]

Initialize a new instance from a JSON file.

Parameters:

filename (str) – path to the JSON file

Returns:

new instance of the class

Return type:

instance (object)

classmethod fromJSON(json: str) → Any[source]

Reconstruct object from a JSON string.

Parameters:

json (str) – JSON string of the object

Returns:

reconstructed object

Return type:

obj (object)

toFile(filename: str) → str[source]

Serialize object to a JSON file. This JSON file should contain all data necessary to reconstruct the object.

Parameters:

filename (str) – filename to save object to

Returns:

absolute path to the saved JSON file of the object

Return type:

filename (str)

toJSON() → str[source]
Serialize object to a JSON string. This JSON string should

contain all data necessary to reconstruct the object.

Returns:

JSON string of the object

Return type:

json (str)

qsprpred.utils.serialization.function_as_string(func: Callable) → str[source]

Convert a function to a string.

Parameters:

func (Callable) – function to convert

qsprpred.utils.serialization.function_from_string(func_str: str) → Callable[source]

Convert a function from a string. Conversion from encoded bytecode is attempted first. If that fails, the string is assumed to be a fully qualified name of the function.

Parameters:

func_str (str) – string representation of the function

Returns:

function

Return type:

processor (Callable)

qsprpred.utils.stopwatch module

class qsprpred.utils.stopwatch.StopWatch[source]

Bases: object

reset()[source]
stop(msg='Time it took: ')[source]

qsprpred.utils.stringops module

Enumerating a list of items with leading zeros.

qsprpred.utils.stringops.generate_padded_index(items: Sized, prefix: str | None = '') → list[str][source]

Generate zero-padded index strings for a list of items.

Parameters:

  • items (Iterable) – List of items to generate index for.

  • prefix (str, optional) – Prefix to add to each index.

Returns:

List of zero-padded index strings.

Return type:

list[str]

qsprpred.utils.stringops.get_random_string(prefix: str = '', length: int = 10)[source]

Generate a random string of fixed length.

Parameters:

  • prefix (str, optional) – Prefix to add to the random string.

  • length (int, optional) – Length of the random string.

qsprpred.utils.tests module

class qsprpred.utils.tests.TestMultiProcGenerators(methodName='runTest')[source]

Bases: QSPRTestCase

Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

classmethod addClassCleanup(function, /, *args, **kwargs)

Same as addCleanup, except the cleanup items are called even if setUpClass fails (unlike tearDownClass).

addCleanup(function, /, *args, **kwargs)

Add a function, with arguments, to be called when the test is completed. Functions added are called on a LIFO basis and are called after tearDown on test failure or success.

Cleanup items are called even if setUp fails (unlike tearDown).

addTypeEqualityFunc(typeobj, function)

Add a type specific assertEqual style function to compare a type.

This method is for use by TestCase subclasses that need to register their own type equality functions to provide nicer error messages.

Parameters:

  • typeobj – The data type to call this function on when both values are of the same type in assertEqual().

  • function – The callable taking two arguments and an optional msg= argument that raises self.failureException with a useful error message when the two arguments are not equal.

assertAlmostEqual(first, second, places=None, msg=None, delta=None)

Fail if the two objects are unequal as determined by their difference rounded to the given number of decimal places (default 7) and comparing to zero, or by comparing that the difference between the two objects is more than the given delta.

Note that decimal places (from zero) are usually not the same as significant digits (measured from the most significant digit).

If the two objects compare equal then they will automatically compare almost equal.

assertCountEqual(first, second, msg=None)

Asserts that two iterables have the same elements, the same number of times, without regard to order.

self.assertEqual(Counter(list(first)),

Counter(list(second)))

Example:

  • [0, 1, 1] and [1, 0, 1] compare equal.

  • [0, 0, 1] and [0, 1] compare unequal.

assertDictEqual(d1, d2, msg=None)
assertEqual(first, second, msg=None)

Fail if the two objects are unequal as determined by the ‘==’ operator.

assertFalse(expr, msg=None)

Check that the expression is false.

assertGreater(a, b, msg=None)

Just like self.assertTrue(a > b), but with a nicer default message.

assertGreaterEqual(a, b, msg=None)

Just like self.assertTrue(a >= b), but with a nicer default message.

assertIn(member, container, msg=None)

Just like self.assertTrue(a in b), but with a nicer default message.

assertIs(expr1, expr2, msg=None)

Just like self.assertTrue(a is b), but with a nicer default message.

assertIsInstance(obj, cls, msg=None)

Same as self.assertTrue(isinstance(obj, cls)), with a nicer default message.

assertIsNone(obj, msg=None)

Same as self.assertTrue(obj is None), with a nicer default message.

assertIsNot(expr1, expr2, msg=None)

Just like self.assertTrue(a is not b), but with a nicer default message.

assertIsNotNone(obj, msg=None)

Included for symmetry with assertIsNone.

assertLess(a, b, msg=None)

Just like self.assertTrue(a < b), but with a nicer default message.

assertLessEqual(a, b, msg=None)

Just like self.assertTrue(a <= b), but with a nicer default message.

assertListEqual(list1, list2, msg=None)

A list-specific equality assertion.

Parameters:

  • list1 – The first list to compare.

  • list2 – The second list to compare.

  • msg – Optional message to use on failure instead of a list of differences.

assertLogs(logger=None, level=None)

Fail unless a log message of level level or higher is emitted on logger_name or its children. If omitted, level defaults to INFO and logger defaults to the root logger.

This method must be used as a context manager, and will yield a recording object with two attributes: output and records. At the end of the context manager, the output attribute will be a list of the matching formatted log messages and the records attribute will be a list of the corresponding LogRecord objects.

Example:

with self.assertLogs('foo', level='INFO') as cm:
    logging.getLogger('foo').info('first message')
    logging.getLogger('foo.bar').error('second message')
self.assertEqual(cm.output, ['INFO:foo:first message',
                             'ERROR:foo.bar:second message'])
assertMultiLineEqual(first, second, msg=None)

Assert that two multi-line strings are equal.

assertNoLogs(logger=None, level=None)

Fail unless no log messages of level level or higher are emitted on logger_name or its children.

This method must be used as a context manager.

assertNotAlmostEqual(first, second, places=None, msg=None, delta=None)

Fail if the two objects are equal as determined by their difference rounded to the given number of decimal places (default 7) and comparing to zero, or by comparing that the difference between the two objects is less than the given delta.

Note that decimal places (from zero) are usually not the same as significant digits (measured from the most significant digit).

Objects that are equal automatically fail.

assertNotEqual(first, second, msg=None)

Fail if the two objects are equal as determined by the ‘!=’ operator.

assertNotIn(member, container, msg=None)

Just like self.assertTrue(a not in b), but with a nicer default message.

assertNotIsInstance(obj, cls, msg=None)

Included for symmetry with assertIsInstance.

assertNotRegex(text, unexpected_regex, msg=None)

Fail the test if the text matches the regular expression.

assertRaises(expected_exception, *args, **kwargs)

Fail unless an exception of class expected_exception is raised by the callable when invoked with specified positional and keyword arguments. If a different type of exception is raised, it will not be caught, and the test case will be deemed to have suffered an error, exactly as for an unexpected exception.

If called with the callable and arguments omitted, will return a context object used like this:

with self.assertRaises(SomeException):
    do_something()

An optional keyword argument ‘msg’ can be provided when assertRaises is used as a context object.

The context manager keeps a reference to the exception as the ‘exception’ attribute. This allows you to inspect the exception after the assertion:

with self.assertRaises(SomeException) as cm:
    do_something()
the_exception = cm.exception
self.assertEqual(the_exception.error_code, 3)
assertRaisesRegex(expected_exception, expected_regex, *args, **kwargs)

Asserts that the message in a raised exception matches a regex.

Parameters:

  • expected_exception – Exception class expected to be raised.

  • expected_regex – Regex (re.Pattern object or string) expected to be found in error message.

  • args – Function to be called and extra positional args.

  • kwargs – Extra kwargs.

  • msg – Optional message used in case of failure. Can only be used when assertRaisesRegex is used as a context manager.

assertRegex(text, expected_regex, msg=None)

Fail the test unless the text matches the regular expression.

assertSequenceEqual(seq1, seq2, msg=None, seq_type=None)

An equality assertion for ordered sequences (like lists and tuples).

For the purposes of this function, a valid ordered sequence type is one which can be indexed, has a length, and has an equality operator.

Parameters:

  • seq1 – The first sequence to compare.

  • seq2 – The second sequence to compare.

  • seq_type – The expected datatype of the sequences, or None if no datatype should be enforced.

  • msg – Optional message to use on failure instead of a list of differences.

assertSetEqual(set1, set2, msg=None)

A set-specific equality assertion.

Parameters:

  • set1 – The first set to compare.

  • set2 – The second set to compare.

  • msg – Optional message to use on failure instead of a list of differences.

assertSetEqual uses ducktyping to support different types of sets, and is optimized for sets specifically (parameters must support a difference method).

assertTrue(expr, msg=None)

Check that the expression is true.

assertTupleEqual(tuple1, tuple2, msg=None)

A tuple-specific equality assertion.

Parameters:

  • tuple1 – The first tuple to compare.

  • tuple2 – The second tuple to compare.

  • msg – Optional message to use on failure instead of a list of differences.

assertWarns(expected_warning, *args, **kwargs)

Fail unless a warning of class warnClass is triggered by the callable when invoked with specified positional and keyword arguments. If a different type of warning is triggered, it will not be handled: depending on the other warning filtering rules in effect, it might be silenced, printed out, or raised as an exception.

If called with the callable and arguments omitted, will return a context object used like this:

with self.assertWarns(SomeWarning):
    do_something()

An optional keyword argument ‘msg’ can be provided when assertWarns is used as a context object.

The context manager keeps a reference to the first matching warning as the ‘warning’ attribute; similarly, the ‘filename’ and ‘lineno’ attributes give you information about the line of Python code from which the warning was triggered. This allows you to inspect the warning after the assertion:

with self.assertWarns(SomeWarning) as cm:
    do_something()
the_warning = cm.warning
self.assertEqual(the_warning.some_attribute, 147)
assertWarnsRegex(expected_warning, expected_regex, *args, **kwargs)

Asserts that the message in a triggered warning matches a regexp. Basic functioning is similar to assertWarns() with the addition that only warnings whose messages also match the regular expression are considered successful matches.

Parameters:

  • expected_warning – Warning class expected to be triggered.

  • expected_regex – Regex (re.Pattern object or string) expected to be found in error message.

  • args – Function to be called and extra positional args.

  • kwargs – Extra kwargs.

  • msg – Optional message used in case of failure. Can only be used when assertWarnsRegex is used as a context manager.

countTestCases()
debug()

Run the test without collecting errors in a TestResult

defaultTestResult()
classmethod doClassCleanups()

Execute all class cleanup functions. Normally called for you after tearDownClass.

doCleanups()

Execute all cleanup functions. Normally called for you after tearDown.

classmethod enterClassContext(cm)

Same as enterContext, but class-wide.

enterContext(cm)

Enters the supplied context manager.

If successful, also adds its __exit__ method as a cleanup function and returns the result of the __enter__ method.

fail(msg=None)

Fail immediately, with the given message.

failureException

alias of AssertionError

static func(x)[source]
static func_args(x, *args, **kwargs)[source]
static func_batched(x)[source]
static func_timeout(x)[source]
id()
longMessage = True
maxDiff = 640
run(result=None)
setUp()

Hook method for setting up the test fixture before exercising it.

classmethod setUpClass()

Hook method for setting up class fixture before running tests in the class.

shortDescription()

Returns a one-line description of the test, or None if no description has been provided.

The default implementation of this method returns the first line of the specified test method’s docstring.

skipTest(reason)

Skip this test.

subTest(msg=<object object>, **params)

Return a context manager that will return the enclosed block of code in a subtest identified by the optional message and keyword parameters. A failure in the subtest marks the test case as failed but resumes execution at the end of the enclosed block, allowing further test code to be executed.

tearDown()

Hook method for deconstructing the test fixture after testing it.

classmethod tearDownClass()

Hook method for deconstructing the class fixture after running all tests in the class.

testArgs = None
testArgs_0(**kw)
testArgs_1(**kw)
testArgs_2(**kw)
testBatched = None
testBatched_0(**kw)
testBatched_1(**kw)
testBatched_2(**kw)
testSimple = None
testSimple_0(**kw)
testSimple_1(**kw)
testSimple_2(**kw)
testTimeout()[source]
class qsprpred.utils.tests.TestThreadedGenerators(methodName='runTest')[source]

Bases: QSPRTestCase

Test processing using a pool of threads.

Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

classmethod addClassCleanup(function, /, *args, **kwargs)

Same as addCleanup, except the cleanup items are called even if setUpClass fails (unlike tearDownClass).

addCleanup(function, /, *args, **kwargs)

Add a function, with arguments, to be called when the test is completed. Functions added are called on a LIFO basis and are called after tearDown on test failure or success.

Cleanup items are called even if setUp fails (unlike tearDown).

addTypeEqualityFunc(typeobj, function)

Add a type specific assertEqual style function to compare a type.

This method is for use by TestCase subclasses that need to register their own type equality functions to provide nicer error messages.

Parameters:

  • typeobj – The data type to call this function on when both values are of the same type in assertEqual().

  • function – The callable taking two arguments and an optional msg= argument that raises self.failureException with a useful error message when the two arguments are not equal.

assertAlmostEqual(first, second, places=None, msg=None, delta=None)

Fail if the two objects are unequal as determined by their difference rounded to the given number of decimal places (default 7) and comparing to zero, or by comparing that the difference between the two objects is more than the given delta.

Note that decimal places (from zero) are usually not the same as significant digits (measured from the most significant digit).

If the two objects compare equal then they will automatically compare almost equal.

assertCountEqual(first, second, msg=None)

Asserts that two iterables have the same elements, the same number of times, without regard to order.

self.assertEqual(Counter(list(first)),

Counter(list(second)))

Example:

  • [0, 1, 1] and [1, 0, 1] compare equal.

  • [0, 0, 1] and [0, 1] compare unequal.

assertDictEqual(d1, d2, msg=None)
assertEqual(first, second, msg=None)

Fail if the two objects are unequal as determined by the ‘==’ operator.

assertFalse(expr, msg=None)

Check that the expression is false.

assertGreater(a, b, msg=None)

Just like self.assertTrue(a > b), but with a nicer default message.

assertGreaterEqual(a, b, msg=None)

Just like self.assertTrue(a >= b), but with a nicer default message.

assertIn(member, container, msg=None)

Just like self.assertTrue(a in b), but with a nicer default message.

assertIs(expr1, expr2, msg=None)

Just like self.assertTrue(a is b), but with a nicer default message.

assertIsInstance(obj, cls, msg=None)

Same as self.assertTrue(isinstance(obj, cls)), with a nicer default message.

assertIsNone(obj, msg=None)

Same as self.assertTrue(obj is None), with a nicer default message.

assertIsNot(expr1, expr2, msg=None)

Just like self.assertTrue(a is not b), but with a nicer default message.

assertIsNotNone(obj, msg=None)

Included for symmetry with assertIsNone.

assertLess(a, b, msg=None)

Just like self.assertTrue(a < b), but with a nicer default message.

assertLessEqual(a, b, msg=None)

Just like self.assertTrue(a <= b), but with a nicer default message.

assertListEqual(list1, list2, msg=None)

A list-specific equality assertion.

Parameters:

  • list1 – The first list to compare.

  • list2 – The second list to compare.

  • msg – Optional message to use on failure instead of a list of differences.

assertLogs(logger=None, level=None)

Fail unless a log message of level level or higher is emitted on logger_name or its children. If omitted, level defaults to INFO and logger defaults to the root logger.

This method must be used as a context manager, and will yield a recording object with two attributes: output and records. At the end of the context manager, the output attribute will be a list of the matching formatted log messages and the records attribute will be a list of the corresponding LogRecord objects.

Example:

with self.assertLogs('foo', level='INFO') as cm:
    logging.getLogger('foo').info('first message')
    logging.getLogger('foo.bar').error('second message')
self.assertEqual(cm.output, ['INFO:foo:first message',
                             'ERROR:foo.bar:second message'])
assertMultiLineEqual(first, second, msg=None)

Assert that two multi-line strings are equal.

assertNoLogs(logger=None, level=None)

Fail unless no log messages of level level or higher are emitted on logger_name or its children.

This method must be used as a context manager.

assertNotAlmostEqual(first, second, places=None, msg=None, delta=None)

Fail if the two objects are equal as determined by their difference rounded to the given number of decimal places (default 7) and comparing to zero, or by comparing that the difference between the two objects is less than the given delta.

Note that decimal places (from zero) are usually not the same as significant digits (measured from the most significant digit).

Objects that are equal automatically fail.

assertNotEqual(first, second, msg=None)

Fail if the two objects are equal as determined by the ‘!=’ operator.

assertNotIn(member, container, msg=None)

Just like self.assertTrue(a not in b), but with a nicer default message.

assertNotIsInstance(obj, cls, msg=None)

Included for symmetry with assertIsInstance.

assertNotRegex(text, unexpected_regex, msg=None)

Fail the test if the text matches the regular expression.

assertRaises(expected_exception, *args, **kwargs)

Fail unless an exception of class expected_exception is raised by the callable when invoked with specified positional and keyword arguments. If a different type of exception is raised, it will not be caught, and the test case will be deemed to have suffered an error, exactly as for an unexpected exception.

If called with the callable and arguments omitted, will return a context object used like this:

with self.assertRaises(SomeException):
    do_something()

An optional keyword argument ‘msg’ can be provided when assertRaises is used as a context object.

The context manager keeps a reference to the exception as the ‘exception’ attribute. This allows you to inspect the exception after the assertion:

with self.assertRaises(SomeException) as cm:
    do_something()
the_exception = cm.exception
self.assertEqual(the_exception.error_code, 3)
assertRaisesRegex(expected_exception, expected_regex, *args, **kwargs)

Asserts that the message in a raised exception matches a regex.

Parameters:

  • expected_exception – Exception class expected to be raised.

  • expected_regex – Regex (re.Pattern object or string) expected to be found in error message.

  • args – Function to be called and extra positional args.

  • kwargs – Extra kwargs.

  • msg – Optional message used in case of failure. Can only be used when assertRaisesRegex is used as a context manager.

assertRegex(text, expected_regex, msg=None)

Fail the test unless the text matches the regular expression.

assertSequenceEqual(seq1, seq2, msg=None, seq_type=None)

An equality assertion for ordered sequences (like lists and tuples).

For the purposes of this function, a valid ordered sequence type is one which can be indexed, has a length, and has an equality operator.

Parameters:

  • seq1 – The first sequence to compare.

  • seq2 – The second sequence to compare.

  • seq_type – The expected datatype of the sequences, or None if no datatype should be enforced.

  • msg – Optional message to use on failure instead of a list of differences.

assertSetEqual(set1, set2, msg=None)

A set-specific equality assertion.

Parameters:

  • set1 – The first set to compare.

  • set2 – The second set to compare.

  • msg – Optional message to use on failure instead of a list of differences.

assertSetEqual uses ducktyping to support different types of sets, and is optimized for sets specifically (parameters must support a difference method).

assertTrue(expr, msg=None)

Check that the expression is true.

assertTupleEqual(tuple1, tuple2, msg=None)

A tuple-specific equality assertion.

Parameters:

  • tuple1 – The first tuple to compare.

  • tuple2 – The second tuple to compare.

  • msg – Optional message to use on failure instead of a list of differences.

assertWarns(expected_warning, *args, **kwargs)

Fail unless a warning of class warnClass is triggered by the callable when invoked with specified positional and keyword arguments. If a different type of warning is triggered, it will not be handled: depending on the other warning filtering rules in effect, it might be silenced, printed out, or raised as an exception.

If called with the callable and arguments omitted, will return a context object used like this:

with self.assertWarns(SomeWarning):
    do_something()

An optional keyword argument ‘msg’ can be provided when assertWarns is used as a context object.

The context manager keeps a reference to the first matching warning as the ‘warning’ attribute; similarly, the ‘filename’ and ‘lineno’ attributes give you information about the line of Python code from which the warning was triggered. This allows you to inspect the warning after the assertion:

with self.assertWarns(SomeWarning) as cm:
    do_something()
the_warning = cm.warning
self.assertEqual(the_warning.some_attribute, 147)
assertWarnsRegex(expected_warning, expected_regex, *args, **kwargs)

Asserts that the message in a triggered warning matches a regexp. Basic functioning is similar to assertWarns() with the addition that only warnings whose messages also match the regular expression are considered successful matches.

Parameters:

  • expected_warning – Warning class expected to be triggered.

  • expected_regex – Regex (re.Pattern object or string) expected to be found in error message.

  • args – Function to be called and extra positional args.

  • kwargs – Extra kwargs.

  • msg – Optional message used in case of failure. Can only be used when assertWarnsRegex is used as a context manager.

countTestCases()
debug()

Run the test without collecting errors in a TestResult

defaultTestResult()
classmethod doClassCleanups()

Execute all class cleanup functions. Normally called for you after tearDownClass.

doCleanups()

Execute all cleanup functions. Normally called for you after tearDown.

classmethod enterClassContext(cm)

Same as enterContext, but class-wide.

enterContext(cm)

Enters the supplied context manager.

If successful, also adds its __exit__ method as a cleanup function and returns the result of the __enter__ method.

fail(msg=None)

Fail immediately, with the given message.

failureException

alias of AssertionError

static func(x)[source]
static func_batched(x)[source]
id()
longMessage = True
maxDiff = 640
run(result=None)
setUp()

Hook method for setting up the test fixture before exercising it.

classmethod setUpClass()

Hook method for setting up class fixture before running tests in the class.

shortDescription()

Returns a one-line description of the test, or None if no description has been provided.

The default implementation of this method returns the first line of the specified test method’s docstring.

skipTest(reason)

Skip this test.

subTest(msg=<object object>, **params)

Return a context manager that will return the enclosed block of code in a subtest identified by the optional message and keyword parameters. A failure in the subtest marks the test case as failed but resumes execution at the end of the enclosed block, allowing further test code to be executed.

tearDown()

Hook method for deconstructing the test fixture after testing it.

classmethod tearDownClass()

Hook method for deconstructing the class fixture after running all tests in the class.

testBatched()[source]
testSimple()[source]

Module contents