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Pyton basic datatypes as a references.

Project description

refdatatypes

Pyton basic datatypes as a references. Solve problems with static class immutable datatypes.

Installation

pip3 install refdatatypes

Problem

class A:
    static = 1


class B(A):
    pass


print(f"int {A.static}")  # get 1 correctly
print(f"int {B.static}")  # get 1 correctly

A.static = 5
print(f"int {A.static}")  # get 5 correctly
print(f"int {B.static}")  # get 5 correctly

B.static = 6
print(f"int {A.static}")  # expected 6, but get 5 incorrectly
print(f"int {B.static}")  # get 6 correctly

A.static = 7
print(f"int {A.static}")  # get 7 correctly
print(f"int {B.static}")  # expected 7, but get unchanged 6, incorrectly

Solution

from refdatatypes.refint import RefInt


class AAA:
    static = RefInt(1)


class BBB(AAA):
    pass


print(f"refint {AAA.static.value}")  # get 1 correctly
print(f"refint {BBB.static.value}")  # get 1 correctly

AAA.static.value = 5
print(f"refint {AAA.static.value}")  # get 5 correctly
print(f"refint {BBB.static.value}")  # get 5 correctly

BBB.static.value = 6
print(f"refint {AAA.static.value}")  # get 6 correctly
print(f"refint {BBB.static.value}")  # get 6 correctly

AAA.static.value = 7
print(f"refint {AAA.static.value}")  # get 7 correctly
print(f"refint {BBB.static.value}")  # get 7 correctly

More details you can find in included examples static_class_attribute_problem.py and static_class_attribute_solution.py .

Safe datatypes

safedatatypes is simple set of function and classes which enables you to work safely with base python datatypes without error falls during convert or item access.

example

from refdatatypes.safedatatypes import safe_int

my_int = safe_int("None")  # no error
print(my_int)  # prints: `0`

example 2

from refdatatypes.safedatatypes import SafeDict

my_dict = SafeDict()
my_dict["a"] = 1

print(my_dict["a"])  # prints: `1` 
print(my_dict["b"])  # prints: `None` with no error
print(my_dict)  # prints: `{'a': 1}`

my_dict = SafeDict({"a": 1}, default_value=-1, autoset=True)
print(my_dict["a"])  # prints: `1` 
print(my_dict["b"])  # prints: `-1` with no error
print(my_dict)  # prints: `{'a': 1, 'b': -1}`

example 3

# expected dict structure
my_dict = {"a": 1, "b": {"bb": 2}}
# but structure like this occured
my_dict = {"a": 1, "b": None}
# safe handle of this structure
result = my_dict.get("b") or {}
result = result.get("bb") or 0
print(result)  # prints: `0` with no error

Solution with SafeDict

from refdatatypes.safedatatypes import SafeDict

# expected dict structure
my_dict = SafeDict({"a": 1, "b": {"bb": 2}})
# but structure like this occured
my_dict = SafeDict({"a": 1, "b": None})
# safe handle of this structure
result = my_dict.get("b", SafeDict(), if_none=True).get("bb", 0)
print(result)  # prints: `0` with no error

Utils

dict_item_must_be_list

This utility checks if item in combined structure of lists and dicts is realy list. If not, it converts it to list. This utility is useful when you are working with xmltodict library. You expect list in some dict structure place, but if there is only one item, it is converted to dict not into list, because for xmltodict is not possible know it should be list.

from refdatatypes.utils import dict_item_must_be_list

d = {
    "a": 1,
    "b": {
        "bb": [
            {"ccc": {"ddd": 4}},
            {"ccc": [{"ddd": 4}, {"ddd": 4}]},
            {"ccc": 4},
            {"ccc": None},
            {"ccc": [1, 2, [11, 22]]},
        ]
    },
}
dict_item_must_be_list(d, "b.bb.ccc")
print(d)
{
    'a': 1,
    'b': {
        'bb': [
            {'ccc': [{'ddd': 4}]},
            {'ccc': [{'ddd': 4}, {'ddd': 4}]},
            {'ccc': [4]},
            {'ccc': []},
            {'ccc': [1, 2, [11, 22]]}
        ]
    }
}

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