updating readme.md

.flake8

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+[flake8]
+max-line-length = 120

.vscode/extensions.json

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+{
+    "recommendations": [
+        "ms-python.black-formatter",
+        "ms-python.flake8",
+        "ms-python.isort",
+        "ms-toolsai.jupyter",
+        "ms-toolsai.datawrangler",
+        "ms-python.python",
+        "donjayamanne.python-environment-manager",
+        // optional
+        "usernamehw.errorlens"
+    ]
+}

.vscode/launch.json

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+{
+    // Use IntelliSense to learn about possible attributes.
+    // Hover to view descriptions of existing attributes.
+    // For more information, visit: https://go.microsoft.com/fwlink/?linkid=830387
+    "version": "0.2.0",
+    "configurations": [
+        {
+            "name": "mai-service",
+            "type": "debugpy",
+            "request": "launch",
+            "program": "run.py",
+            "console": "integratedTerminal",
+            "justMyCode": true
+        }
+    ]
+}

.vscode/settings.json

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+{
+    "files.autoSave": "onFocusChange",
+    "files.exclude": {
+        "**/__pycache__": true
+    },
+    "editor.detectIndentation": false,
+    "editor.formatOnType": false,
+    "editor.formatOnPaste": true,
+    "editor.formatOnSave": true,
+    "editor.tabSize": 4,
+    "editor.insertSpaces": true,
+    "editor.codeActionsOnSave": {
+        "source.organizeImports": "explicit",
+        "source.sortImports": "explicit"
+    },
+    "editor.stickyScroll.enabled": false,
+    "diffEditor.ignoreTrimWhitespace": false,
+    "debug.showVariableTypes": true,
+    "workbench.editor.highlightModifiedTabs": true,
+    "git.suggestSmartCommit": false,
+    "git.autofetch": true,
+    "git.openRepositoryInParentFolders": "always",
+    "git.confirmSync": false,
+    "errorLens.gutterIconsEnabled": true,
+    "errorLens.messageEnabled": false,
+    "[python]": {
+        "editor.defaultFormatter": "ms-python.black-formatter",
+    },
+    "python.languageServer": "Pylance",
+    "python.analysis.typeCheckingMode": "basic",
+    "python.analysis.autoImportCompletions": true,
+    "isort.args": [
+        "--profile",
+        "black"
+    ],
+    "notebook.lineNumbers": "on",
+    "notebook.output.minimalErrorRendering": true,
+}

README.md

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-# MAI_PIbd-33_Volkov_N.A.
+# Репозиторий по дисциплине "Методы ИИ" студента группы ПИбд-33 Волкова Никиты
+## Вариант 4. Данные по инсультам
+## Окружение для выполнения лабораторных работ
 
+### Python
+
+Используется Python версии 3.12
+
+Установщик https://www.python.org/ftp/python/3.12.5/python-3.12.5-amd64.exe
+
+### Poetry
+
+Для создания и настройки окружения проекта необходимо установить poetry
+
+**Для Windows (Powershell)**
+
+```
+(Invoke-WebRequest -Uri https://install.python-poetry.org -UseBasicParsing).Content | python -
+```
+
+**Linux, macOS, Windows (WSL)**
+
+```
+curl -sSL https://install.python-poetry.org | python3 -
+```
+
+**Добавление poetry в PATH**
+
+1. Открыть настройки переменных среды \
+    \
+   <img src="docs/path1.png" width="300"> \
+    \
+   <img src="docs/path2.png" width="400"> \
+2. Изменить переменную Path текущего пользователя \
+    \
+   <img src="docs/path3.png" width="500"> \
+3. Добавление пути `%APPDATA%\Python\Scripts` до исполняемого файла poetry \
+    \
+   <img src="docs/path4.png" width="400">
+
+### Создание окружения
+
+```
+poetry install
+```
+
+### Запуск тестового сервиса
+
+Запустить тестовый сервис можно с помощью VSCode (см. launch.json в каталоге .vscode).
+
+Также запустить тестовый сервис можно с помощью командной строки:
+
+1. Активация виртуального окружения -- `poetry shell`
+
+2. Запуск сервиса -- `python run.py`
+
+Для выходы из виртуального окружения используется команду `exit`

backend/__init__.py

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+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

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+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

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+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

poetry.toml

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+[virtualenvs]
+in-project = true

pyproject.toml

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+[tool.poetry]
+name = "mai"
+version = "1.0.0"
+description = "MAI Examples"
+authors = ["Aleksey Filippov <al.filippov@ulstu.ru>"]
+readme = "readme.md"
+package-mode = false
+
+[tool.poetry.dependencies]
+python = "^3.12"
+jupyter = "^1.1.1"
+numpy = "^2.1.0"
+pandas = "^2.2.2"
+matplotlib = "^3.9.2"
+flask = "^3.0.3"
+apiflask = "^2.2.0"
+flask-cors = "^5.0.0"
+
+
+[tool.poetry.group.dev.dependencies]
+ipykernel = "^6.29.5"
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"

run.py

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+from backend import create_app
+
+app = create_app()
+
+
+def __main():
+    app.run(
+        host="127.0.0.1",
+        port=8080,
+        debug=True,
+        use_reloader=False,
+    )
+
+
+if __name__ == "__main__":
+    __main()