More picky version of Python dictionary.
Project description
pickydict - the more picky version of Python dictionary
PickyDict
objects will behave just like Python dictionaries, with a few
notable exceptions:
-
PickyDict has a
force_lower_case
attribute.
If set to True (default) then dictionary keys will all be treated as lower-case. -
PickyDict can contain two additional dictionaries named
key_replacements
andkey_regex_replacements
with mappings to enforce translating specific key words.
Installation
PickyDict can simply be installed with:
pip install pickydict
It has no further dependencies and should run fine with Python >= 3.6 (probably also lower versions, but that is not tested).
Code examples
from pickydict import PickyDict
# per default force_lower_case is set to True:
my_dict = PickyDict({"A": 1, "B": 2})
print(my_dict) # => {'a': 1, 'b': 2}
# now also using a replacements dictionary
my_dict = PickyDict({"A": 1, "B": 2},
key_replacements={"a": "abc", "b": "bcd", "c": "cde"})
print(my_dict) # => {'abc': 1, 'bcd': 2}
# When adding a value using an undesired key, the key will automatically be fixed
my_dict["c"] = 100
print(my_dict) # => {'abc': 1, 'bcd': 2, 'cde': 100}
# Trying to add a value using an undesired key while the proper key already exists,
# will raise an exception.
my_dict["b"] = 5 # => ValueError: Key 'b' will be interpreted as 'bcd'...
It is also possible to add a dictionary with regex expression to replace parts of
key strings. This is done using the key_regex_replacements
attribute. In the following example the dictionary will replace all spaces in keys with underscores.
Important to note is that regex based replacements will be carried out before the more specific key_replacements. This is to reduce the number of possible variations and make things simpler for the user.
Example:
from pickydict import PickyDict
my_dict = PickyDict({"First Name": "Peter", "Last Name": "Petersson"},
key_replacements={"last_name": "surname"},
key_regex_replacements={r"\s": "_"})
print(my_dict) # => {'first_name': 'Peter', 'surname': 'Petersson'}
Whenever the pickyness is updated, no matter if the force_lower_case
, key_replacements
,
or key_regex_replacements
, the entire dictionary will be updated accordingly.
Example:
from pickydict import PickyDict
my_dict = PickyDict({"First Name": "Peter", "Last Name": "Petersson"})
print(my_dict) # => {'first name': 'Peter', 'last name': 'Petersson'}
my_dict.set_pickyness(key_replacements={"last_name": "surname"},
key_regex_replacements={r"\s": "_"})
print(my_dict) # => {'first_name': 'Peter', 'surname': 'Petersson'}
Handling of key duplicates
PickyDict converts key names as described above. This can obviously lead to cases of having key duplicates. This is handled in two different ways. When passing a dictionary to PickyDict in the beginning, only the entries for the desired keys will be kept.
Example:
from pickydict import PickyDict
my_dict = PickyDict({"My Name": "Peter", "name": "Peter Petersson"},
key_replacements={"my_name": "name"},
key_regex_replacements={r"\s": "_"})
print(my_dict) # => {"name": "Peter Petersson"}
Later adding values using an improper key, however, will raise an exception when it leads to a duplicate.
Example:
from pickydict import PickyDict
my_dict = PickyDict({"first_name": "Peter Petersson"},
key_regex_replacements={r"\s": "_"})
my_dict["First Name"] = Peter P. Petersson # => ValueError:Key 'First name' will be interpreted as 'first_name'
For the rest it's just a dict
All other operation should work as you are used to from Python dictionaries.
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