mt_metadata.base.helpers

Created on Wed Dec 23 20:37:52 2020

copyright:

Jared Peacock (jpeacock@usgs.gov)

license:

MIT

Attributes

filter_descriptions

Classes

NumpyEncoder

Need to encode numpy ints and floats for json to work

Functions

wrap_description(description, column_width)	split a description into separate lines
validate_c1(attr_dict, c1)	Validate column 1 width based on attribute dictionary
write_lines(field_dict[, c1, c2, c3])	Takes a dictionary of field names to FieldInfo objects and parses it into a table
write_block(key, field_info[, c1, c2, c3])
flatten_dict(meta_dict[, parent_key, sep])
flatten_list(x_list)	Flatten a nested list
recursive_split_dict(key, value, remainder[, sep])	recursively split a dictionary
get_by_alias(model, alias_name)
recursive_split_getattr(base_object, name[, sep])
recursive_split_setattr(base_object, name, value[, ...])	Recursively split a name and set the value of the last key. Recursion splits on the separator present in the name.
structure_dict(meta_dict[, sep])
get_units(name, attr_dict)
get_type(name, attr_dict)
recursive_split_xml(element, item, base, name[, attr_dict])
dict_to_xml(meta_dict[, attr_dict])	Assumes dictionary is structured {class:{attribute_dict}}
element_to_dict(element)
element_to_string(element)
validate_name(name[, pattern])	Validate name
has_numbers(text)	Check if a string contains any numeric characters.
is_numeric_string(text)	Check if a string represents a valid number (int or float).
extract_numbers(text)	Extract all numeric values from a string.
requires(**requirements)	Decorate a function with optional dependencies.
object_to_array(value[, dtype])	Convert a value to a numpy array.

Module Contents

mt_metadata.base.helpers.filter_descriptions

mt_metadata.base.helpers.wrap_description(description, column_width)

split a description into separate lines

mt_metadata.base.helpers.validate_c1(attr_dict, c1)

Validate column 1 width based on attribute dictionary

Parameters:

• attr_dict (dict) – DESCRIPTION

• c1 (int) – DESCRIPTION

Returns:

DESCRIPTION

Return type:

int

mt_metadata.base.helpers.write_lines(field_dict, c1=45, c2=45, c3=15)

Takes a dictionary of field names to FieldInfo objects and parses it into a table Returns a string representation of this table. This overwrites the doc.

Parameters:

• field_dict (dict) – dictionary mapping field names to FieldInfo objects

• c1 (int, optional) – column 1 width, by default 45

• c2 (int, optional) – column 2 width, by default 45

• c3 (int, optional) – column 3 width, by default 15

Returns:

doc string

Return type:

str

mt_metadata.base.helpers.write_block(key, field_info, c1=45, c2=45, c3=15)

Parameters:

• key (string) – key to write from attr dict

• field_info (dict) – field information dictionary

• c1 (int, optional) – column 1 width, defaults to 45

• c2 (int, optional) – column 2 width, defaults to 45

• c3 (int, optional) – column 3 width, defaults to 15

Returns:

list of lines

Return type:

list

mt_metadata.base.helpers.flatten_dict(meta_dict, parent_key=None, sep='.')

Parameters:

• meta_dict (TYPE) – DESCRIPTION

• parent_key (TYPE, optional) – DESCRIPTION, defaults to None

• sep (TYPE, optional) – DESCRIPTION, defaults to ‘.’

Returns:

DESCRIPTION

Return type:

TYPE

mt_metadata.base.helpers.flatten_list(x_list)

Flatten a nested list flatten = lambda l: [item for sublist in l for item in sublist]

Return type:

None.

mt_metadata.base.helpers.recursive_split_dict(key, value, remainder, sep='.')

recursively split a dictionary

Parameters:

• key (TYPE) – DESCRIPTION

• value (TYPE) – DESCRIPTION

• remainder (TYPE) – DESCRIPTION

Returns:

DESCRIPTION

Return type:

TYPE

mt_metadata.base.helpers.get_by_alias(model, alias_name)

mt_metadata.base.helpers.recursive_split_getattr(base_object, name, sep='.')

mt_metadata.base.helpers.recursive_split_setattr(base_object, name, value, sep='.', skip_validation=False)

Recursively split a name and set the value of the last key. Recursion splits on the separator present in the name.

Parameters:

• base_object (object) – The object having its attribute set, or a “parent” object in the recursive/nested scenario

• name (str) – The name of the attribute to set

• value (any) – The value to set the attribute to

• sep (str, optional) – The separator to split the name on, defaults to “.”

• skip_validation (Optional[bool]) – Whether to skip validation/parse of the attribute, defaults to False

Returns:

None

Return type:

NoneType

mt_metadata.base.helpers.structure_dict(meta_dict, sep='.')

Parameters:

• meta_dict (TYPE) – DESCRIPTION

• sep (TYPE, optional) – DESCRIPTION, defaults to ‘.’

Returns:

DESCRIPTION

Return type:

TYPE

mt_metadata.base.helpers.get_units(name, attr_dict)

mt_metadata.base.helpers.get_type(name, attr_dict)

mt_metadata.base.helpers.recursive_split_xml(element, item, base, name, attr_dict=None)

mt_metadata.base.helpers.dict_to_xml(meta_dict, attr_dict=None)

Assumes dictionary is structured {class:{attribute_dict}}

Parameters:

meta_dict (TYPE) – DESCRIPTION

Returns:

DESCRIPTION

Return type:

TYPE

mt_metadata.base.helpers.element_to_dict(element)

Parameters:

element (TYPE) – DESCRIPTION

Returns:

DESCRIPTION

Return type:

TYPE

mt_metadata.base.helpers.element_to_string(element)

class mt_metadata.base.helpers.NumpyEncoder(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, sort_keys=False, indent=None, separators=None, default=None)

Bases: json.JSONEncoder

Need to encode numpy ints and floats for json to work

default(obj)

Parameters:

obj

Returns:

mt_metadata.base.helpers.validate_name(name, pattern=None)

Validate name

Parameters:

• name (TYPE) – DESCRIPTION

• pattern (TYPE, optional) – DESCRIPTION, defaults to None

Returns:

DESCRIPTION

Return type:

TYPE

mt_metadata.base.helpers.has_numbers(text)

Check if a string contains any numeric characters.

Parameters:

text (str) – The string to check for numeric characters.

Returns:

True if the string contains any digits (0-9), False otherwise.

Return type:

bool

Examples

>>> has_numbers("abc123")
True
>>> has_numbers("hello")
False
>>> has_numbers("test1")
True
>>> has_numbers("")
False

mt_metadata.base.helpers.is_numeric_string(text)

Check if a string represents a valid number (int or float).

Parameters:

text (str) – The string to check if it represents a number.

Returns:

True if the string can be converted to a number, False otherwise.

Return type:

bool

Examples

>>> is_numeric_string("123")
True
>>> is_numeric_string("12.34")
True
>>> is_numeric_string("-45.6")
True
>>> is_numeric_string("1.23e-4")
True
>>> is_numeric_string("abc")
False
>>> is_numeric_string("12abc")
False

mt_metadata.base.helpers.extract_numbers(text)

Extract all numeric values from a string.

Parameters:

text (str) – The string to extract numbers from.

Returns:

List of float values found in the string.

Return type:

list

Examples

>>> extract_numbers("abc123def45.6")
[123.0, 45.6]
>>> extract_numbers("no numbers here")
[]
>>> extract_numbers("1.5 and -2.3e4")
[1.5, -23000.0]

mt_metadata.base.helpers.requires(**requirements)

Decorate a function with optional dependencies.

Parameters:

**requirements (obj) – keywords of package name and the required object for a function.

Returns:

decorated_function – Original function if all soft dependencies are met, otherwise it returns an empty function which prints why it is not running.

Return type:

function

Examples

``` try:

import obspy

except ImportError:

obspy = None

@requires(obspy=obspy) def obspy_function():

… # does something using obspy

mt_metadata.base.helpers.object_to_array(value, dtype=float)

Convert a value to a numpy array.

Parameters:

value (any) – The value to convert.

Returns:

The converted numpy array.

Return type:

np.ndarray