Artifician
Artifician is an event driven library developed to simplify and speed up the process of preparation of the datasets for Artificial Intelligence models.
Getting Started
Pre-requisites
- python v3.6 or later
Installation
Binary installers for the latest released version are available at the Python Package Index (PyPI) and on Conda
# or PyPI
pip install artifician
# conda
conda install -c plato_solutions artifician
Documentation
Please visit Aritfician Docs
Usage
from artifician.dataset import *
from artifician.feature_definition import *
from artifician.processors.normalizer import *
def extract_domain_name(sample):
"""function for extracting the path from the given URL"""
domain_name = sample.split("//")[-1].split('/')[0]
return domain_name
input_data = ['https://www.google.com/', 'https://www.youtube.com/']
dataset = Dataset() # initializing dataset object
url_domain = FeatureDefinition(extract_domain_name, dataset) # initializing feature_definition and passing extractor function name as a parameter and subscribing it to dataset
normalizer = Normalizer(PropertiesNormalizer(), url_domain delimiter = {'delimiter': ["."]}) # Initializing normalizer (processor) and passing properties normalizer as a parameter and subscribing it to url_domain
""" Now we are all set to go, all we have to do is call add_samples method on the dataset object and pass the input data
after calling the add_samples, url_domain will start its execution and extract the data using extract_domain_name function, as soon url_domain
feature is processed normalizer will start it execution and furthur is will process the data extracted by url_domain. The processed data is then
passed back to the dataset. Following diagram will make it more clear for you. """
prepared_data = dataset.add_samples(input_data)
print(prepared_data)
Output
| 0 | 1 | |
|---|---|---|
| 0 | https://www.google.com/ | [(www, 0), (google, 1), (com, 2)] |
| 1 | https://www.youtube.com/ | [(www, 0), (youtube, 1), (com, 2)] |
1 maintainer
Metadata
1 maintainer
Release files for artifician 0.6.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| artifician-0.6.4.tar.gz | 312.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| artifician-0.6.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 347.5 kB
Release files / artifician-0.6.4.tar.gz
| Download URL | artifician-0.6.4.tar.gz |
|---|---|
| Size | 312.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
2647ebea2b877cb6c637d2d0f34a6c97fd2e427a015566e00b0a64b77155775d
|
|
BLAKE2b-256 checksum How to use checksums |
5de43dc9169d5af93995e6c922acdef0906813e86d64989f97ab4e37cf77389c
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.12.1
|
Release files / artifician-0.6.4-py3-none-any.whl
| Download URL | artifician-0.6.4-py3-none-any.whl |
|---|---|
| Size | 34.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
0ea37cbf5d61af9649cc3352198424ea259c1a0ac4e17ab9f3a9ea643ef18967
|
|
BLAKE2b-256 checksum How to use checksums |
0adc6e91208e5425463e936db1d7f42a09ed7cb98facb54be459f1dbd47d45c7
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.12.1
|
