60 lines
2.1 KiB
Python
60 lines
2.1 KiB
Python
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import io
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import os
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import pathlib
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from typing import BinaryIO, Dict, List
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import pandas as pd
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from matplotlib.figure import Figure
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from werkzeug.datastructures import FileStorage
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from werkzeug.utils import secure_filename
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class Service:
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def __init__(self, dataset_path: str | None) -> None:
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if dataset_path is None:
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raise Exception("Dataset path is not defined")
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self.__path: str = dataset_path
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def __get_dataset(self, filename: str) -> pd.DataFrame:
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full_file_name = os.path.join(self.__path, secure_filename(filename))
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return pd.read_csv(full_file_name)
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def upload_dataset(self, file: FileStorage) -> str:
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if file.filename is None:
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raise Exception("Dataset upload error")
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file_name: str = file.filename
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full_file_name = os.path.join(self.__path, secure_filename(file_name))
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file.save(full_file_name)
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return file_name
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def get_all_datasets(self) -> List[str]:
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return [file.name for file in pathlib.Path(self.__path).glob("*.csv")]
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def get_dataset_info(self, filename) -> List[Dict]:
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dataset = self.__get_dataset(filename)
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dataset_info = []
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for column in dataset.columns:
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items = dataset[column].astype(str)
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column_info = {
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"name": column,
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"datatype": dataset.dtypes[column],
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"items": items,
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}
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dataset_info.append(column_info)
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return dataset_info
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def get_column_info(self, filename, column) -> Dict:
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dataset = self.__get_dataset(filename)
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datatype = dataset.dtypes[column]
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items = sorted(dataset[column].astype(str).unique())
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return {"datatype": datatype, "items": items}
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def get_hist(self, filename, column) -> BinaryIO:
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dataset = self.__get_dataset(filename)
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bytes = io.BytesIO()
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plot: Figure | None = dataset.plot.hist(column=[column], bins=80).get_figure()
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if plot is None:
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raise Exception("Can't create hist plot")
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plot.savefig(bytes, dpi=300, format="png")
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return bytes
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