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"""
Cannabis Analytes
Copyright (c) 2023 Cannlytics
Authors:
Keegan Skeate <https://github.com/keeganskeate>
Candace O'Sullivan-Sutherland <https://github.com/candy-o>
Created: 10/10/2023
Updated: 10/10/2023
License: <https://huggingface.co/datasets/cannlytics/cannabis_analytes/blob/main/LICENSE>
"""
# External imports:
import datasets
import pandas as pd
# Constants.
_SCRIPT = 'cannabis_analytes.py'
_VERSION = '2023.10.10'
_HOMEPAGE = 'https://huggingface.co/datasets/cannlytics/cannabis_analytes'
_LICENSE = "https://opendatacommons.org/licenses/by/4-0/"
_DESCRIPTION = """\
This dataset consists of analyte data for various analytes that are regularly tested for in cannabis. The dataset consists of sub-datasets for each type of test, as well as a sub-dataset that includes all analytes.
"""
_CITATION = """\
@inproceedings{cannlytics2023cannabis_analytes,
author = {Skeate, Keegan and O'Sullivan-Sutherland, Candace},
title = {Cannabis Analytes},
booktitle = {Cannabis Data Science},
month = {October},
year = {2023},
address = {United States of America},
publisher = {Cannlytics}
}
"""
# Define subsets.
SUBSETS = [
'all',
'cannabinoids',
'terpenes',
]
# Dataset fields.
FIELDS = datasets.Features({
'description': datasets.Value(dtype='string'),
'key': datasets.Value(dtype='string'),
'name': datasets.Value(dtype='string'),
'scientific_name': datasets.Value(dtype='string'),
'type': datasets.Value(dtype='string'),
'wikipedia_url': datasets.Value(dtype='string'),
'degrades_to': datasets.Sequence(datasets.Value(dtype='string')),
'precursors': datasets.Sequence(datasets.Value(dtype='string')),
'subtype': datasets.Value(dtype='string'),
'cas_number': datasets.Value(dtype='string'),
'chemical_formula': datasets.Value(dtype='string'),
'molar_mass': datasets.Value(dtype='string'),
'density': datasets.Value(dtype='string'),
'boiling_point': datasets.Value(dtype='string'),
'image_url': datasets.Value(dtype='string'),
'chemical_formula_image_url': datasets.Value(dtype='string'),
})
class CannabisAnalytesConfig(datasets.BuilderConfig):
"""BuilderConfig for the Cannabis Analytes dataset."""
def __init__(self, name, **kwargs):
"""BuilderConfig for the Cannabis Analytes dataset.
Args:
name (str): Configuration name that determines setup.
**kwargs: Keyword arguments forwarded to super.
"""
description = _DESCRIPTION
description += f'This configuration is for the `{name}` subset.'
super().__init__(
data_dir='data',
description=description,
name=name,
**kwargs,
)
class CannabisLicenses(datasets.GeneratorBasedBuilder):
"""The Cannabis Licenses dataset."""
VERSION = datasets.Version(_VERSION)
BUILDER_CONFIG_CLASS = CannabisAnalytesConfig
BUILDER_CONFIGS = [CannabisAnalytesConfig(s) for s in SUBSETS]
DEFAULT_CONFIG_NAME = 'all'
def _info(self):
"""Returns the dataset metadata."""
return datasets.DatasetInfo(
features=FIELDS,
supervised_keys=None,
homepage=_HOMEPAGE,
citation=_CITATION,
description=_DESCRIPTION,
license=_LICENSE,
version=_VERSION,
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
subset = self.config.name
if subset == 'all':
subset = 'analytes'
data_url = f'data/{subset}.json'
urls = {subset: data_url}
downloaded_files = dl_manager.download_and_extract(urls)
params = {'filepath': downloaded_files[subset]}
return [datasets.SplitGenerator(name='data', gen_kwargs=params)]
def _generate_examples(self, filepath):
"""Returns the examples in raw text form."""
# Read the data.
df = pd.read_json(filepath)
# Add missing columns.
for col in FIELDS.keys():
if col not in df.columns:
df[col] = ''
# Keep only the feature columns.
df = df[list(FIELDS.keys())]
# Fill missing values.
df.fillna('', inplace=True)
# Return the data as a dictionary.
for index, row in df.iterrows():
obs = row.to_dict()
yield index, obs
# === Test ===
# [✓] Tested: 2023-10-10 by Keegan Skeate <keegan@cannlytics>
if __name__ == '__main__':
from datasets import load_dataset
# Load each dataset subset.
for subset in SUBSETS:
dataset = load_dataset(_SCRIPT, subset)
data = dataset['data']
assert len(data) > 0
print('Read %i %s data points.' % (len(data), subset))
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