lab1

backend/__init__.py

@@ -1,52 +0,0 @@
-import importlib
-import os
-import traceback
-
-import matplotlib
-from apiflask import APIBlueprint, APIFlask
-from flask_cors import CORS
-
-matplotlib.use("agg")
-
-cors = CORS()
-api_bp = APIBlueprint("api", __name__, url_prefix="/api/v1")
-dataset_path: str | None = None
-
-
-class Config:
-    SECRET_KEY = "secret!"
-    SEND_FILE_MAX_AGE_DEFAULT = -1
-
-
-def create_app():
-    global dataset_path
-
-    # Create and configure app
-    app = APIFlask(
-        "MAI Service",
-        title="MAI Service API",
-        docs_path="/",
-        version="1.0",
-        static_folder="",
-        template_folder="",
-    )
-    app.config.from_object(Config)
-
-    dataset_path = os.path.join(app.instance_path, "dataset")
-    os.makedirs(dataset_path, exist_ok=True)
-
-    @app.errorhandler(Exception)
-    def my_error_processor(error):
-        traceback.print_exception(error)
-        return {"message": str(error), "detail": "No details"}, 500
-
-    # Import custom REST methods
-    importlib.import_module("backend.api")
-
-    # Enable REST API
-    app.register_blueprint(api_bp)
-
-    # Enable app extensions
-    cors.init_app(app)
-
-    return app

backend/api.py

@@ -1,57 +0,0 @@
-from apiflask import FileSchema, Schema, fields
-from flask import send_file
-
-from backend import api_bp, dataset_path
-from backend.service import Service
-
-
-class FileUpload(Schema):
-    file = fields.File(required=True)
-
-
-class ColumnInfoDto(Schema):
-    datatype = fields.String()
-    items = fields.List(fields.String())
-
-
-class TableColumnDto(Schema):
-    name = fields.String()
-    datatype = fields.String()
-    items = fields.List(fields.String())
-
-
-service = Service(dataset_path)
-
-
-@api_bp.post("/dataset")
-@api_bp.input(FileUpload, location="files")
-def upload_dataset(files_data):
-    uploaded_file = files_data["file"]
-    return service.upload_dataset(uploaded_file)
-
-
-@api_bp.get("/dataset")
-def get_all_datasets():
-    return service.get_all_datasets()
-
-
-@api_bp.get("/dataset/<string:name>")
-@api_bp.output(TableColumnDto(many=True))
-def get_dataset_info(name: str):
-    return service.get_dataset_info(name)
-
-
-@api_bp.get("/dataset/<string:name>/<string:column>")
-@api_bp.output(ColumnInfoDto)
-def get_column_info(name: str, column: str):
-    return service.get_column_info(name, column)
-
-
-@api_bp.get("/dataset/draw/hist/<string:name>/<string:column>")
-@api_bp.output(
-    FileSchema(type="string", format="binary"), content_type="image/png", example=""
-)
-def get_dataset_hist(name: str, column: str):
-    data = service.get_hist(name, column)
-    data.seek(0)
-    return send_file(data, download_name=f"{name}.hist.png", mimetype="image/png")

backend/service.py

@@ -1,59 +0,0 @@
-import io
-import os
-import pathlib
-from typing import BinaryIO, Dict, List
-
-import pandas as pd
-from matplotlib.figure import Figure
-from werkzeug.datastructures import FileStorage
-from werkzeug.utils import secure_filename
-
-
-class Service:
-    def __init__(self, dataset_path: str | None) -> None:
-        if dataset_path is None:
-            raise Exception("Dataset path is not defined")
-        self.__path: str = dataset_path
-
-    def __get_dataset(self, filename: str) -> pd.DataFrame:
-        full_file_name = os.path.join(self.__path, secure_filename(filename))
-        return pd.read_csv(full_file_name)
-
-    def upload_dataset(self, file: FileStorage) -> str:
-        if file.filename is None:
-            raise Exception("Dataset upload error")
-        file_name: str = file.filename
-        full_file_name = os.path.join(self.__path, secure_filename(file_name))
-        file.save(full_file_name)
-        return file_name
-
-    def get_all_datasets(self) -> List[str]:
-        return [file.name for file in pathlib.Path(self.__path).glob("*.csv")]
-
-    def get_dataset_info(self, filename) -> List[Dict]:
-        dataset = self.__get_dataset(filename)
-        dataset_info = []
-        for column in dataset.columns:
-            items = dataset[column].astype(str)
-            column_info = {
-                "name": column,
-                "datatype": dataset.dtypes[column],
-                "items": items,
-            }
-            dataset_info.append(column_info)
-        return dataset_info
-
-    def get_column_info(self, filename, column) -> Dict:
-        dataset = self.__get_dataset(filename)
-        datatype = dataset.dtypes[column]
-        items = sorted(dataset[column].astype(str).unique())
-        return {"datatype": datatype, "items": items}
-
-    def get_hist(self, filename, column) -> BinaryIO:
-        dataset = self.__get_dataset(filename)
-        bytes = io.BytesIO()
-        plot: Figure | None = dataset.plot.hist(column=[column], bins=80).get_figure()
-        if plot is None:
-            raise Exception("Can't create hist plot")
-        plot.savefig(bytes, dpi=300, format="png")
-        return bytes