Metadata-Version: 2.1
Name: pickydict
Version: 0.4.0
Summary: More picky version of Python dictionary.
Home-page: https://github.com/florian-huber/pickydict
Author: Florian Huber
Author-email: 
License: MIT
Platform: UNKNOWN
Requires-Python: >=3.6
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Requires-Dist: pytest ; extra == 'dev'
Requires-Dist: pytest-cov ; extra == 'dev'

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# pickydict - the more picky version of Python dictionary

`PickyDict` objects will behave just like Python dictionaries, with a few
notable exceptions:

1. PickyDict has a `force_lower_case` attribute.   
If set to True (default) then dictionary keys will all be treated as lower-case.

2. PickyDict can contain two additional dictionaries named `key_replacements`
    and `key_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

```python
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:

```python
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:

```python

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:

```python

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:

```python

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.


