pytoolkit928 0.0.15

A General Use Python Tookit.

PyToolkit

Python General tools

Utilities

string_or_list function allows you to interpret a string and return a list. Provides you the option of adding a delimeter using an OR function to return a possible string that you may be expecting possible commond delimeters. Such as: ",|:|\|, ".

Example:

>>> from pytoolkit.utils import string_or_list

>>> test = 'string1,string2 string3|string4'
>>> string_or_list(test)
['string1,string2 string3|string4']
>>> string_or_list(test,delimeters=',| ')
['string1', 'string2', 'string3|string4']
>>> string_or_list(test,delimeters=',| |\|')
['string1', 'string2', 'string3', 'string4']

Dataclass Base

Used for basic extended functionality for dataclass declerations. Includes the ability to create a dataclass from a dictionary or from **kwargs. Also, includes a conversion from Dataclass to a Python dictionary.

Usage:

from typing import Optional
from dataclasses import dataclass

from pytoolkit.utilities import BaseMonitor, NONETYPE

@dataclass
class Sample(BaseMonitor):
    key1: str
    key2: str
    key3: int
    key5: Optional[str] = NONETYPE

# create a sample module
_dict = {"key1": "value1", "key2": "value2", "key3": 3}

sample1 = Sample.create_from_dict(_dict)
sample2 = Sample.create_from_kwargs(**_dict)

print(sample1)
print(sample2)
print(sample1.to_dict())

OUTPUT:

>>> print(sample1)
Sample(key1='value1', key2='value2', key3=3, key5=<object object at 0x10c8e8b70>)
>>> print(sample2)
Sample(key1='value1', key2='value2', key3=3, key5=<object object at 0x10c8e8b70>)
>>> print(sample1.to_dict())
{'key1': 'value1', 'key2': 'value2', 'key3': 3}

Maniuplating Dictionaries

Flatten a Dictionary:

import json
from pytoolkit import utilities

sample_dict = {"key1":"value","key2": "value2", "metadata": {"key1": "meta_value1","key2":"meta_value2"}}

# Convert dictionary into a flat dictionary
flat_dict = utilities.flatten_dict(sample_dict)

# Convert dictionary back into a nested ditionary
nest_dict = utilities.nested_dict(flat_dict)

print(f"This is a Flattened Dictionary:\n{json.dumps(flat_dict,indent=1)}")
print(f"This is a Nested Dictionary:\n{json.dumps(nest_dict,indent=1)}")

OUTPUT:

This is a Flattened Dictionary:
{
 "key1": "value",
 "key2": "value2",
 "metadata.key1": "meta_value1",
 "metadata.key2": "meta_value2"
}

This is a Nested Dictionary:
{
 "key1": "value",
 "key2": "value2",
 "metadata": {
  "key1": "meta_value1",
  "key2": "meta_value2"
 }
}

The above is using the default '.' seperator value. There is a mix of commands that can be passed to adjust how the dictionary is expressed. This is useful for expressing data in otherformats that do not allow for nested dictionaries, but need a way to recreate the original formated datastructure.

Nested Dictionary:

TOOD: Create a way to extract a CSV or XCEL file and turn it into a proper dictionary based on the type. Integrate with Splunk

TODO: Add splunk HEC fromatter with proper chunck

TODO: KVSTORE configuration tool.

Utilities

Sanatize dictionary data

from pytoolkit.utils import sanatize_data

test_dict = {
    "value1": "one",
    "value2": "two",
    "subvalue01": {
        "password": "welcome123",
        "username": "testuser",
    }
}

sanatized_dict = sanatize_data(data=test_dict)
print(sanatize_dict)
# {"value1": "one", "value2": "two", "subvalue01": { "password": "[MASKED]", "username": "testuser"}}