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# checks module

Utilities for validation during runtime.

## assert_array_equal function

    assert_array_equal(
        arg1,
        arg2
    )

Raise exception if the first argument and the second argument have different metadata or values.

## assert_columns_equal function

    assert_columns_equal(
        arg1,
        arg2,
        check_names=True
    )

Raise exception if the first argument and the second argument have different columns.

## assert_dict_sequence_valid function

    assert_dict_sequence_valid(
        arg,
        lvl_keys
    )

Raise exception if a dict or any dict in a sequence of dicts has keys that are not in `lvl_keys`.

## assert_dict_valid function

    assert_dict_valid(
        arg,
        lvl_keys
    )

Raise exception if dict the argument has keys that are not in `lvl_keys`.

`lvl_keys` must be a list of lists, each corresponding to a level in the dict.

## assert_dtype function

    assert_dtype(
        arg,
        dtype,
        arg_name=None
    )

Raise exception if the argument is not of data type `dtype`.

## assert_dtype_equal function

    assert_dtype_equal(
        arg1,
        arg2
    )

Raise exception if the first argument and the second argument have different data types.

## assert_equal function

    assert_equal(
        arg1,
        arg2,
        deep=False
    )

Raise exception if the first argument and the second argument are different.

## assert_in function

    assert_in(
        arg1,
        arg2,
        arg_name=None
    )

Raise exception if the first argument is not in the second argument.

## assert_index_equal function

    assert_index_equal(
        arg1,
        arg2,
        check_names=True
    )

Raise exception if the first argument and the second argument have different index.

## assert_instance_of function

    assert_instance_of(
        arg,
        types,
        arg_name=None
    )

Raise exception if the argument is none of types `types`.

## assert_iterable function

    assert_iterable(
        arg
    )

Raise exception if the argument is not an iterable.

## assert_len_equal function

    assert_len_equal(
        arg1,
        arg2
    )

Raise exception if the first argument and the second argument have different length.

Does not transform arguments to NumPy arrays.

## assert_level_not_exists function

    assert_level_not_exists(
        arg,
        level_name
    )

Raise exception if index the argument has level `level_name`.

## assert_meta_equal function

    assert_meta_equal(
        arg1,
        arg2,
        axis=None
    )

Raise exception if the first argument and the second argument have different metadata.

## assert_ndim function

    assert_ndim(
        arg,
        ndims
    )

Raise exception if the argument has a different number of dimensions than `ndims`.

## assert_not_instance_of function

    assert_not_instance_of(
        arg,
        types,
        arg_name=None
    )

Raise exception if the argument is one of types `types`.

## assert_not_none function

    assert_not_none(
        arg,
        arg_name=None
    )

Raise exception if the argument is None.

## assert_not_subclass_of function

    assert_not_subclass_of(
        arg,
        classes,
        arg_name=None
    )

Raise exception if the argument is a subclass of classes `classes`.

## assert_numba_func function

    assert_numba_func(
        func
    )

Raise exception if `func` is not Numba-compiled.

## assert_sequence function

    assert_sequence(
        arg
    )

Raise exception if the argument is not a sequence.

## assert_shape_equal function

    assert_shape_equal(
        arg1,
        arg2,
        axis=None
    )

Raise exception if the first argument and the second argument have different shapes along `axis`.

## assert_subclass_of function

    assert_subclass_of(
        arg,
        classes,
        arg_name=None
    )

Raise exception if the argument is not a subclass of classes `classes`.

## assert_subdtype function

    assert_subdtype(
        arg,
        dtype,
        arg_name=None
    )

Raise exception if the argument is not a sub data type of `dtype`.

## assert_type_equal function

    assert_type_equal(
        arg1,
        arg2
    )

Raise exception if the first argument and the second argument have different types.

## iskeyword function

    frozenset.__contains__(
        ...
    )

x.contains(y) <==> y in x.

## func_accepts_arg function

    func_accepts_arg(
        func,
        arg_name,
        arg_kind=None
    )

Check whether `func` accepts a positional or keyword argument with name `arg_name`.

## is_any_array function

    is_any_array(
        arg
    )

Check whether the argument is a NumPy array or a Pandas object.

## is_bool function

    is_bool(
        arg
    )

Check whether the argument is a bool.

## is_class function

    is_class(
        arg,
        types
    )

Check whether the argument is `types`.

`types` can be one or multiple types, strings, or patterns of type Regex.

## is_complex_iterable function

    is_complex_iterable(
        arg
    )

Check whether the argument is iterable but not a string or bytes object.

## is_complex_sequence function

    is_complex_sequence(
        arg
    )

Check whether the argument is a sequence but not a string or bytes object.

## is_deep_equal function

    is_deep_equal(
        arg1,
        arg2,
        check_exact=False,
        debug=False,
        only_types=False,
        **kwargs
    )

Check whether two objects are equal (deep check).

## is_default_index function

    is_default_index(
        arg,
        check_names=True
    )

Check whether index is a basic range.

## is_dt function

    is_dt(
        arg
    )

Check whether the argument is a datetime object.

## is_dt_like function

    is_dt_like(
        arg
    )

Check whether the argument is a datetime-like object.

## is_equal function

    is_equal(
        arg1,
        arg2,
        equality_func=<function <lambda>>
    )

Check whether two objects are equal.

## is_float function

    is_float(
        arg
    )

Check whether the argument is a float.

## is_frame function

    is_frame(
        arg
    )

Check whether the argument is `pd.DataFrame`.

## is_frequency function

    is_frequency(
        arg
    )

Check whether the argument is a frequency object.

## is_frequency_like function

    is_frequency_like(
        arg
    )

Check whether the argument is a frequency-like object.

## is_hashable function

    is_hashable(
        arg
    )

Check whether the argument can be hashed.

## is_index function

    is_index(
        arg
    )

Check whether the argument is `pd.Index`.

## is_index_equal function

    is_index_equal(
        arg1,
        arg2,
        check_names=True
    )

Check whether indexes are equal.

If `check_names` is True, checks whether names are equal on top of `pd.Index.equals`.

## is_instance_of function

    is_instance_of(
        arg,
        types
    )

Check whether the argument is an instance of `types`.

`types` can be one or multiple types or strings.

## is_int function

    is_int(
        arg
    )

Check whether the argument is an integer (and not a timedelta, for example).

## is_iterable function

    is_iterable(
        arg
    )

Check whether the argument is iterable.

## is_mapping function

    is_mapping(
        arg
    )

Check whether the arguments is a mapping.

## is_mapping_like function

    is_mapping_like(
        arg
    )

Check whether the arguments is a mapping-like object.

## is_multi_index function

    is_multi_index(
        arg
    )

Check whether the argument is `pd.MultiIndex`.

## is_namedtuple function

    is_namedtuple(
        arg
    )

Check whether object is an instance of namedtuple.

## is_notebook function

    is_notebook()

Check whether the code runs in a notebook.

Credit: https://stackoverflow.com/a/39662359

## is_np_array function

    is_np_array(
        arg
    )

Check whether the argument is a NumPy array.

## is_np_scalar function

    is_np_scalar(
        arg
    )

Check whether the argument is a NumPy scalar.

## is_numba_enabled function

    is_numba_enabled()

Check whether Numba is enabled globally.

## is_numba_func function

    is_numba_func(
        arg
    )

Check whether the argument is a Numba-compiled function.

## is_number function

    is_number(
        arg
    )

Check whether the argument is a number.

## is_pandas function

    is_pandas(
        arg
    )

Check whether the argument is `pd.Series`, `pd.Index`, or `pd.DataFrame`.

## is_record function

    is_record(
        arg
    )

Check whether object is a NumPy record.

## is_record_array function

    is_record_array(
        arg
    )

Check whether the argument is a structured NumPy array.

## is_sequence function

    is_sequence(
        arg
    )

Check whether the argument is a sequence.

## is_series function

    is_series(
        arg
    )

Check whether the argument is `pd.Series`.

## is_subclass_of function

    is_subclass_of(
        arg,
        types
    )

Check whether the argument is a subclass of `types`.

`types` can be one or multiple types, strings, or patterns of type Regex.

## is_td function

    is_td(
        arg
    )

Check whether the argument is a timedelta object.

## is_td_like function

    is_td_like(
        arg
    )

Check whether the argument is a timedelta-like object.

## is_time function

    is_time(
        arg
    )

Check whether the argument is a time object.

## is_time_like function

    is_time_like(
        arg
    )

Check whether the argument is a time-like object.

## is_valid_variable_name function

    is_valid_variable_name(
        arg
    )

Check whether the argument is a valid variable name.

## safe_assert function

    safe_assert(
        arg,
        msg=None
    )

## Comparable class

    Comparable()

Class representing an object that can be compared to another object.

Subclasses

- Configured
- pdict

### equals method

    Comparable.equals(
        other,
        *args,
        **kwargs
    )

Check two objects for (deep) equality.

Should accept the keyword arguments accepted by is_deep_equal().

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