Get Nested

Get nested value from dictionary.

param d:

Input dictionary.

type d:

dict

param path:

The nested path of keys in a ordered list. Example: [‘level 1’, ‘level 2’]

type path:

list

returns:

value –

value belonging to the key.
None: if the path does not exists.

rtype:

string or numerical

Examples

>>> # Import dicter
>>> import dicter as dt
>>> #
>>> # Example dictionary
>>> d = {'level_a': 1, 'level_b': {'a': 'hello world'}, 'level_c': 3, 'level_d': {'a': 1, 'b': 2, 'c': {'e': 10}}, 'level_e': 2}
>>> # Get the value for the nested path for:
>>> value = dt.get_nested(d, ["level_a"])
>>> print(value)  # 1
>>> #
>>> # Get the value for the nested path for:
>>> value = dt.get_nested(d, ["level_b","a"])
>>> print(value)  # hello world
>>> #
>>> # Get the value for the nested path for:
>>> value = dt.get_nested(d, ["level_d","c", "e"])
>>> print(value)  # 10
>>> #
>>> # Get the value for the nested path for a list:
>>> l = [[[1,2,3],[10,20,30]]]
>>> value = dt.get_nested(l, [0,1,2])    # =>>> 30
>>> print(value)  # 30

Set Nested

Set nested value from dictionary.

Set nested value in dictionary.

param d:: Input dictionary.
type d:: dict
param path:: The nested path of keys in a ordered list.
type path:: list
param value:: The value that needs to be set.
type value:: str
rtype:: Dictionary is updated without a return.

Examples

>>> # Import dicter
>>> import dicter as dt
>>> #
>>> # Example: New path and value in dictionary.
>>> d = {}
>>> path = ['person', 'address', 'city']
>>> dt.set_nested(d, path, 'New York')
>>> # Print updated dictionary
>>> print(d)
>>> # {'person': {'address': {'city': 'New York'}}}
>>> #
>>> # Example: Update value in path.
>>> d = {'person': {'address': {'city': 'New York'}}}
>>> path = ['person', 'address', 'city']
>>> dt.set_nested(d, path, 'Amsterdam')
>>> # Print updated dictionary
>>> print(d)
>>> # {'person': {'address': {'city': 'Amsterdam'}}, 'person_2': {'address': {'city': 'Amsterdam'}}}
>>> #
>>> # Example: New path with value.
>>> d = {'person': {'address': {'city': 'New York'}}}
>>> path = ['person_2', 'address', 'city']
>>> dt.set_nested(d, path, 'Amsterdam')
>>> # Print updated dictionary
>>> print(d)
>>> # {'person': {'address': {'city': 'New York'}}, 'person_2': {'address': {'city': 'Amsterdam'}}}

Update Nested Dictionary

Update a nested dictionary for a specific key with a new value.

param dictionary:: The nested dictionary to update.
type dictionary:: dict
param key_to_update:: The key to update.
type key_to_update:: str
param new_value:: The new value to assign to the specified key.
type new_value:: any

Examples

>>> data_dict_template = {
...     'DEPARTURE': {
...         'SLOPE': 3,
...         'INTERSECTION': 'V4',
...         'TORA': '1234',
...         'CIRCUIT_ALTITUDE': '1000',
...         'TOWER': '122.108',
...         'alignment': 'concrete'
...     }
... }
>>> update(data_dict_template['DEPARTURE'], 'SLOPE', 5)
>>> data_dict_template['DEPARTURE']['SLOPE']
5

>>> update(data_dict_template['DEPARTURE'], 'INTERSECTION', 'V5')
>>> data_dict_template['DEPARTURE']['INTERSECTION']
'V5'

>>> update(data_dict_template['DEPARTURE'], 'TORA', '2000')
>>> data_dict_template['DEPARTURE']['TORA']
'2000'

>>> update(data_dict_template['DEPARTURE'], 'CIRCUIT_ALTITUDE', '1500')
>>> data_dict_template['DEPARTURE']['CIRCUIT_ALTITUDE']
'1500'

>>> update(data_dict_template['DEPARTURE'], 'TOWER', '122.109')
>>> data_dict_template['DEPARTURE']['TOWER']
'122.109'

>>> update(data_dict_template['DEPARTURE'], 'alignment', 'asphalt')
>>> data_dict_template['DEPARTURE']['alignment']
'asphalt'

Traverse

Traverse through all paths in dictionary.

param d:

Input dictionary.

type d:

dict

param sep:

The seperator should be unique and is used to normalize the dictionary. Change the sep in case a string exists with such pattern in the input dictionary.

type sep:

str, default is ‘$->$’

param keys_as_list:

True: Output is structured list with keys. False: Output is list with keys seperated with the “sep” string.

type keys_as_list:

bool, default is True

param verbose:

Set the verbose messages using string or integer values.

[0, None, ‘silent’, ‘off’, ‘no’]: No message.
[10, ‘debug’]: Messages from debug level and higher.
[20, ‘info’]: Messages from info level and higher.
[30, ‘warning’]: Messages from warning level and higher.
[40, ‘critical’]: Messages from critical level and higher.

type verbose:

int, default is ‘info’ or 20

returns:

dic – list containing two columns: [[key], value].

rtype:

list

Examples

>>> # Import dicter
>>> import dicter as dt
>>> #
>>> Example dict
>>> d = {'level_a': 1, 'level_b': {'a': 'hello world'}, 'level_c': 3, 'level_d': {'a': 1, 'b': 2, 'c': {'e': 10}}, 'level_e': 2}
>>> # Traverse all paths in dictionary
>>> dlist = dt.traverse(d)
>>> #
>>> print(dlist)
>>> # [[['level_a'], 1],
>>> # [['level_c'], 3],
>>> # [['level_e'], 2],
>>> # [['level_b', 'a'], 'hello world'],
>>> # [['level_d', 'a'], 1],
>>> # [['level_d', 'b'], 2],
>>> # [['level_d', 'c', 'e'], 10]]
>>> #
>>> # Example to retrieve value from a dictionary
>>> value = dt.get_nested(d, dlist[3])
>>> # Look up for ['level_b', 'a']
>>> print(value)  # hello world

Flatten

Flatten dictionary to the deepest level and return key-value.

param d:: Input dictionary.
type d:: dict
returns:: d_flatten – Flattened dictionary containing key and value.
rtype:: list

Examples

>>> # Import dicter
>>> import dicter as dt
>>> #
>>> # Example dict
>>> d = {'level_a': 1, 'level_b': {'a': 'hello world'}, 'level_c': 3, 'level_d': {'a': 1, 'b': 2, 'c': {'e': 10}}, 'level_e': 2}
>>> # Flatten dictionary
>>> dflat = dt.flatten(d)
>>> #
>>> print(d_flat)

Check key exists

Check whether key exists in dictionary.

Check whether the dictionary contains the key.

param d:: Input dictionary.
type d:: dict
param path:: The nested path of keys in a ordered list. Example: [‘level 1’, ‘level 2’]
type path:: list
returns:: True: Key exists. False: Key does not exist.
rtype:: Bool

Examples

>>> # Import dicter
>>> import dicter as dt
>>> #
>>> # Example dictionary
>>> d = {'level_a': 1, 'level_b': {'a': 'hello world'}, 'level_c': 3, 'level_d': {'a': 1, 'b': 2, 'c': {'e': 10}}, 'level_e': 2}
>>> #
>>> # Get the value for the nested path for:
>>> value = dt.is_key(d, ["level_b","a"])

Depth

Depth of dictionary.

param d:: Input dictionary.
type d:: dict
returns:: depth – Depth of dictionary.
rtype:: int

Examples

>>> # Import dicter
>>> import dicter as dt
>>> #
>>> Example dict
>>> d = {'level_a': 1, 'level_b': {'a': 'hello world'}, 'level_c': 3, 'level_d': {'a': 1, 'b': 2, 'c': {'e': 10}}, 'level_e': 2}
>>> n = dt.depth(d)

Compare

Compare two dictionaries.

The second dictionary is compared with the first one, and results are shown accordingly.

param d1:

Dictionary.

type d1:

dict

param d2:

Dictionary.

type d2:

dict

returns:

added (list) – added keys in d1 compared with d2.
removed (list) – Removed keys in d1 compared with d2.
modified (list) – Modified keys in d1 compared with d2.
same (list) – Similar keys in d1 compared with d2.

Examples

>>> # Import dicter
>>> import dicter as dt
>>> #
>>> Example: Add
>>> d1 = {'level_a': 1, 'level_b': {'a': 'hello world'}, 'level_c': 'new in d2'}
>>> d2 = {'level_a': 1, 'level_b': {'a': 'hello world'}}
>>> out = dt.compare(d1, d2)
>>> print(out)
>>> #
>>> Example: Remove
>>> d1 = {'level_a': 1, 'level_b': {'a': 'hello world'}}
>>> d2 = {'level_a': 1, 'level_b': {'a': 'hello world'}, 'level_c': 'new in d2'}
>>> out = dt.compare(d1, d2)
>>> print(out)
>>> #
>>> Example: Modified
>>> d1 = {'level_a': 1, 'level_b': {'a': 'hello world'}}
>>> d2 = {'level_a': 1, 'level_b': {'a': 'modified'}}
>>> out = dt.compare(d1, d2)
>>> print(out['modified'])
>

To DataFrame

Save dictionary to json.

param d:

Dictionary.

type d:

dict

param filepath:

File path to store the dictionary.

type filepath:

str

param overwrite:

True: Overwrite if file exists. False: Do not overwrite existing files.

type overwrite:

bool, default: False

param verbose:

Set the verbose messages using string or integer values.

0, None, ‘silent’, ‘off’, ‘no’: No message.
10,’debug’: Messages from debug level and higher.
20,’info’: Messages from info level and higher.
30,’warning’: Messages from warning level and higher.
40,’critical’: Messages from critical level and higher.

type verbose:

int, default is ‘info’ or 20

returns:

writeok – True: Succesful writing to json on disk. False: Nothing is written to disk.

rtype:

bool

Examples

>>> # Import dicter
>>> import dicter as dt
>
>>> d = {'level_a': None, 'level_b': {'a': 'hello world'}, 'level_c': True, 'level_d': 2.3, 'level_e': [[1,2,3], [1,2]]}
>>> dt.save(d, filepath='c:/temp/test/dicter_save.json', overwrite=True)

Save

Save dictionary to json.

param d:

Dictionary.

type d:

dict

param filepath:

File path to store the dictionary.

type filepath:

str

param overwrite:

True: Overwrite if file exists. False: Do not overwrite existing files.

type overwrite:

bool, default: False

param verbose:

Set the verbose messages using string or integer values.

0, None, ‘silent’, ‘off’, ‘no’: No message.
10,’debug’: Messages from debug level and higher.
20,’info’: Messages from info level and higher.
30,’warning’: Messages from warning level and higher.
40,’critical’: Messages from critical level and higher.

type verbose:

int, default is ‘info’ or 20

returns:

writeok – True: Succesful writing to json on disk. False: Nothing is written to disk.

rtype:

bool

Examples

>>> # Import dicter
>>> import dicter as dt
>
>>> d = {'level_a': None, 'level_b': {'a': 'hello world'}, 'level_c': True, 'level_d': 2.3, 'level_e': [[1,2,3], [1,2]]}
>>> dt.save(d, filepath='c:/temp/test/dicter_save.json', overwrite=True)

Load

Load dictionary from json file.

param filepath:

path location to json.

type filepath:

str

param verbose:

Set the verbose messages using string or integer values.

[0, None, ‘silent’, ‘off’, ‘no’]: No message.
[10, ‘debug’]: Messages from debug level and higher.
[20, ‘info’]: Messages from info level and higher.
[30, ‘warning’]: Messages from warning level and higher.
[40, ‘critical’]: Messages from critical level and higher.

type verbose:

str, optional

returns:

dictionary – None or Dictionary.

rtype:

dict

Examples

>>> # Import dicter
>>> import dicter as dt
>>> #
>>> d = {'level_a': None, 'level_b': {'a': 'hello world'}, 'level_c': True, 'level_d': 2.3, 'level_e': [[1,2,3], [1,2]]}
>>> filepath='c:/temp/test/dicter_save.json'
>>> # First save
>>> dt.save(d, filepath=filepath, overwrite=True)
>>> # Load
>>> d = dt.load(filepath)