This package implements tools to build python package and tools.
 
>>> from Report import *
>>> data = [
...     {"name": "test0", "level": 5, "id": 0},
...     {"name": "test1", "level": 10, "id": 1},
...     {"name": "test2", "level": 2, "id": 2},
... ]
>>> r = Report(data, "level", "id")
>>> print(r.report_text())
|name         |level        |id           |
|-------------|-------------|-------------|
|test2        |2            |2            |
|test1        |10           |1            |
>>> print(r.report_JSON())
[
    {
        "name": "test2",
        "level": 2,
        "id": 2
    },
    {
        "name": "test1",
        "level": 10,
        "id": 1
    }
]
>>> r.report_CSV()
'name,level,id\r\ntest2,2,2\r\ntest1,10,1\r\n'
>>> print(r.report_HTML())
name	level	id
test2	2	2
test1	10	1
>>> r.statistic()
[{'Name': 'level', 'Sum': 12, 'Max': 10, 'Min': 2, 'Count': 2, 'MaxCount': 1, 'MinCount': 1, 'Average': 6.0, 'Variance': 32, 'Median': 6.0, 'Deviation': 4.0, 'CountGreaterThanAverage': 1, 'CountLessThanAverage': 1, 'CountGreaterThanVariance': 0, 'CountLessThanVariance': 2, 'CountGreaterThanMedian': 1, 'CountLessThanMedian': 1, 'CountGreaterThanDeviation': 1, 'CountLessThanDeviation': 1}, {'Name': 'id', 'Sum': 3, 'Max': 2, 'Min': 1, 'Count': 2, 'MaxCount': 1, 'MinCount': 1, 'Average': 1.5, 'Variance': 0.5, 'Median': 1.5, 'Deviation': 0.5, 'CountGreaterThanAverage': 1, 'CountLessThanAverage': 1, 'CountGreaterThanVariance': 2, 'CountLessThanVariance': 0, 'CountGreaterThanMedian': 1, 'CountLessThanMedian': 1, 'CountGreaterThanDeviation': 2, 'CountLessThanDeviation': 0}]
>>> r2 = Report(r.statistic())
>>> print(r2.report_text(length=26))
|Name                      |Sum                       |Max                       |Min                       |Count                     |MaxCount                  |MinCount                  |Average                   |Variance                  |Median                    |Deviation                 |CountGreaterThanAverage   |CountLessThanAverage      |CountGreaterThanVariance  |CountLessThanVariance     |CountGreaterThanMedian    |CountLessThanMedian       |CountGreaterThanDeviation |CountLessThanDeviation    |
|--------------------------|--------------------------|--------------------------|--------------------------|--------------------------|--------------------------|--------------------------|--------------------------|--------------------------|--------------------------|--------------------------|--------------------------|--------------------------|--------------------------|--------------------------|--------------------------|--------------------------|--------------------------|--------------------------|
|level                     |12                        |10                        |2                         |2                         |1                         |1                         |6.0                       |32                        |6.0                       |4.0                       |1                         |1                         |0                         |2                         |1                         |1                         |1                         |1                         |
|id                        |3                         |2                         |1                         |2                         |1                         |1                         |1.5                       |0.5                       |1.5                       |0.5                       |1                         |1                         |2                         |0                         |1                         |1                         |2                         |0                         |
>>> from dataclasses import dataclass
>>> @dataclass
... class Test:
...     one: int = 1
...     two: int = 2
...
>>> data = [Test(), Test(one=2, two=2)]
>>> r = Report(data)
>>> r.frequence()
>>> r = Report(data, filter_value=lambda x: x["one"] == 1)
>>> r.frequence()
50.0
>>> r = Report(data, filter_value=lambda x: x["two"] == 1)
>>> r.report_text()
>>> r.report_HTML()
>>> r.report_JSON()
>>> r.report_CSV()
>>> r.statistic()
>>>
 
Run tests:
 ~# python -m doctest Report.py
 ~# python Report.py            # Verbose mode
 
1 items passed all tests:
  23 tests in __main__
23 tests in 12 items.
23 passed and 0 failed.
Test passed.
 
~# coverage run Report.py
~# coverage report
Name         Stmts   Miss  Cover
--------------------------------
Report.py      160      1    99%
--------------------------------
TOTAL          160      1    99%
~#

Classes
		builtins.object Report   class Report(builtins.object)     Report(objects: Union[Sequence[dict], Sequence[object]], sort_value: Union[str, collections.abc.Callable] = None, filter_value: Union[str, collections.abc.Callable] = None, reverse: bool = False)   This function reports data in different formats.     Methods defined here: __init__(self, objects: Union[Sequence[dict], Sequence[object]], sort_value: Union[str, collections.abc.Callable] = None, filter_value: Union[str, collections.abc.Callable] = None, reverse: bool = False) Initialize self.  See help(type(self)) for accurate signature. frequence(self, filtered: bool = False, pourcent: bool = True) -> float This function returns the frequence of used/filtered objects for report. report_CSV(self, *args, filtered: bool = False, **kwargs) This function returns a CSV content to report objects.   *args and **kwargs are sent to DictWriter.writerows report_HTML(self, filtered: bool = False) This function returns a text table to report objects. report_JSON(self, *args, filtered: bool = False, indent: int = 4, **kwargs) -> str This function returns a JSON array of dict to report objects.   *args and **kwargs are sent to json.dumps report_text(self, *args, filtered: bool = False, **kwargs) -> str This function returns a text table to report objects.   *args and **kwargs are sent to StringF.strings_tableformat statistic(self, attributes: Sequence[str] = None, filtered: bool = False) -> List[Dict[str, Union[str, int]]] This function returns statistics to report objects statistics. Static methods defined here: get_dicts(objects: Union[Sequence[dict], Sequence[object]]) -> collections.abc.Iterator[dict] This function returns dict from dict or object. Data descriptors defined here: __dict__ dictionary for instance variables (if defined) __weakref__ list of weak references to the object (if defined)

Data
		__all__ = ['Report'] __author_email__ = 'mauricelambert434@gmail.com' __copyright__ = '\nPythonToolsKit Copyright (C) 2022 Maurice Lam...ome to redistribute it\nunder certain conditions.\n' __description__ = '\nThis package implements tools to build python package and tools.\n' __license__ = 'GPL-3.0 License' __maintainer__ = 'Maurice Lambert' __maintainer_email__ = 'mauricelambert434@gmail.com' __url__ = 'https://github.com/mauricelambert/PythonToolsKit'

Author
		Maurice Lambert

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