Skip to main content

A General Use Python Tookit.

Project description

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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pytoolkit928-0.0.13.tar.gz (57.0 kB view details)

Uploaded Source

Built Distribution

pytoolkit928-0.0.13-py3-none-any.whl (48.1 kB view details)

Uploaded Python 3

File details

Details for the file pytoolkit928-0.0.13.tar.gz.

File metadata

  • Download URL: pytoolkit928-0.0.13.tar.gz
  • Upload date:
  • Size: 57.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for pytoolkit928-0.0.13.tar.gz
Algorithm Hash digest
SHA256 5439a7b7d56679d6e755e3ae8e0e5517a3c46fdc3b75affa6c97a83d3e51b00e
MD5 47a53e4a881e18bc43ae17014b090331
BLAKE2b-256 03e17d0b18d7e8761dd7a4ca24f5281c6eeb3506e7b36426adf8a740ec37a249

See more details on using hashes here.

File details

Details for the file pytoolkit928-0.0.13-py3-none-any.whl.

File metadata

File hashes

Hashes for pytoolkit928-0.0.13-py3-none-any.whl
Algorithm Hash digest
SHA256 dc03c835a9351c419e709c57dc228d23d4758766bef743c9a987de60593b4a35
MD5 16e19795efec529f9bfec886f081d097
BLAKE2b-256 ac7531a2f8eabc8492d90c5ac48befc2d8c91d46fd58d4a116f5eac5372b343c

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page