Initial commit: frontend + backend integration
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Ignacio
22
backend/beyond_metrics/io/__init__.py
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22
backend/beyond_metrics/io/__init__.py
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from .base import DataSource, ResultsSink
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from .local import LocalDataSource, LocalResultsSink
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from .s3 import S3DataSource, S3ResultsSink
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from .google_drive import (
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GoogleDriveDataSource,
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GoogleDriveConfig,
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GoogleDriveResultsSink,
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GoogleDriveSinkConfig,
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)
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__all__ = [
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"DataSource",
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"ResultsSink",
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"LocalDataSource",
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"LocalResultsSink",
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"S3DataSource",
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"S3ResultsSink",
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"GoogleDriveDataSource",
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"GoogleDriveConfig",
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"GoogleDriveResultsSink",
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"GoogleDriveSinkConfig",
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]
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36
backend/beyond_metrics/io/base.py
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36
backend/beyond_metrics/io/base.py
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from __future__ import annotations
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from abc import ABC, abstractmethod
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from typing import Any, Dict
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import pandas as pd
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from matplotlib.figure import Figure
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class DataSource(ABC):
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"""Interfaz de lectura de datos (CSV)."""
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@abstractmethod
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def read_csv(self, path: str) -> pd.DataFrame:
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"""
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Lee un CSV y devuelve un DataFrame.
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El significado de 'path' depende de la implementación:
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- LocalDataSource: ruta en el sistema de ficheros
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- S3DataSource: 's3://bucket/key'
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"""
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raise NotImplementedError
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class ResultsSink(ABC):
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"""Interfaz de escritura de resultados (JSON e imágenes)."""
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@abstractmethod
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def write_json(self, path: str, data: Dict[str, Any]) -> None:
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"""Escribe un dict como JSON en 'path'."""
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raise NotImplementedError
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@abstractmethod
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def write_figure(self, path: str, fig: Figure) -> None:
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"""Guarda una figura matplotlib en 'path'."""
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raise NotImplementedError
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160
backend/beyond_metrics/io/google_drive.py
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160
backend/beyond_metrics/io/google_drive.py
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# beyond_metrics/io/google_drive.py
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from __future__ import annotations
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import io
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import json
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import re
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from dataclasses import dataclass
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from pathlib import Path
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from typing import Optional, Dict, Any
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import pandas as pd
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from google.oauth2 import service_account
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from googleapiclient.discovery import build
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from googleapiclient.http import MediaIoBaseDownload, MediaIoBaseUpload
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from .base import DataSource, ResultsSink
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GDRIVE_SCOPES = ["https://www.googleapis.com/auth/drive.readonly",
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"https://www.googleapis.com/auth/drive.file"]
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def _extract_file_id(file_id_or_url: str) -> str:
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"""
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Acepta:
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- un ID directo de Google Drive (ej: '1AbC...')
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- una URL de Google Drive compartida
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y devuelve siempre el file_id.
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"""
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if "http://" not in file_id_or_url and "https://" not in file_id_or_url:
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return file_id_or_url.strip()
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patterns = [
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r"/d/([a-zA-Z0-9_-]{10,})", # https://drive.google.com/file/d/<ID>/view
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r"id=([a-zA-Z0-9_-]{10,})", # https://drive.google.com/open?id=<ID>
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]
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for pattern in patterns:
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m = re.search(pattern, file_id_or_url)
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if m:
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return m.group(1)
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raise ValueError(f"No se pudo extraer un file_id de la URL de Google Drive: {file_id_or_url}")
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# -------- DataSource --------
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@dataclass
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class GoogleDriveConfig:
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credentials_path: str # ruta al JSON de service account
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impersonate_user: Optional[str] = None
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class GoogleDriveDataSource(DataSource):
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"""
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DataSource que lee CSVs desde Google Drive.
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"""
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def __init__(self, config: GoogleDriveConfig) -> None:
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self._config = config
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self._service = self._build_service(readonly=True)
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def _build_service(self, readonly: bool = True):
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scopes = ["https://www.googleapis.com/auth/drive.readonly"] if readonly else GDRIVE_SCOPES
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creds = service_account.Credentials.from_service_account_file(
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self._config.credentials_path,
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scopes=scopes,
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)
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if self._config.impersonate_user:
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creds = creds.with_subject(self._config.impersonate_user)
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service = build("drive", "v3", credentials=creds)
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return service
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def read_csv(self, path: str) -> pd.DataFrame:
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file_id = _extract_file_id(path)
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request = self._service.files().get_media(fileId=file_id)
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fh = io.BytesIO()
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downloader = MediaIoBaseDownload(fh, request)
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done = False
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while not done:
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_, done = downloader.next_chunk()
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fh.seek(0)
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df = pd.read_csv(fh)
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return df
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# -------- ResultsSink --------
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@dataclass
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class GoogleDriveSinkConfig:
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credentials_path: str # ruta al JSON de service account
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base_folder_id: str # ID de la carpeta de Drive donde escribir
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impersonate_user: Optional[str] = None
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class GoogleDriveResultsSink(ResultsSink):
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"""
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ResultsSink que sube JSONs e imágenes a una carpeta de Google Drive.
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Nota: por simplicidad, usamos solo el nombre del fichero (basename de `path`).
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Es decir, si le pasas 'data/output/123/results.json', en Drive se guardará
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como 'results.json' dentro de base_folder_id.
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"""
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def __init__(self, config: GoogleDriveSinkConfig) -> None:
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self._config = config
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self._service = self._build_service()
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def _build_service(self):
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creds = service_account.Credentials.from_service_account_file(
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self._config.credentials_path,
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scopes=GDRIVE_SCOPES,
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)
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if self._config.impersonate_user:
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creds = creds.with_subject(self._config.impersonate_user)
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service = build("drive", "v3", credentials=creds)
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return service
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def _upload_bytes(self, data: bytes, mime_type: str, target_path: str) -> str:
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"""
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Sube un fichero en memoria a Drive y devuelve el file_id.
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"""
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filename = Path(target_path).name
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media = MediaIoBaseUpload(io.BytesIO(data), mimetype=mime_type, resumable=False)
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file_metadata = {
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"name": filename,
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"parents": [self._config.base_folder_id],
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}
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created = self._service.files().create(
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body=file_metadata,
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media_body=media,
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fields="id",
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).execute()
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return created["id"]
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def write_json(self, path: str, data: Dict[str, Any]) -> None:
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payload = json.dumps(data, ensure_ascii=False, indent=2).encode("utf-8")
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self._upload_bytes(payload, "application/json", path)
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def write_figure(self, path: str, fig) -> None:
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from matplotlib.figure import Figure
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if not isinstance(fig, Figure):
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raise TypeError("write_figure espera un matplotlib.figure.Figure")
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buf = io.BytesIO()
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fig.savefig(buf, format="png", bbox_inches="tight")
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buf.seek(0)
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self._upload_bytes(buf.read(), "image/png", path)
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57
backend/beyond_metrics/io/local.py
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57
backend/beyond_metrics/io/local.py
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from __future__ import annotations
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import json
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import os
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from typing import Any, Dict
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import pandas as pd
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from matplotlib.figure import Figure
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from .base import DataSource, ResultsSink
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class LocalDataSource(DataSource):
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"""
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DataSource que lee CSV desde el sistema de ficheros local.
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- base_dir: se prefiere que todos los paths sean relativos a esta carpeta.
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"""
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def __init__(self, base_dir: str = ".") -> None:
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self.base_dir = base_dir
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def _full_path(self, path: str) -> str:
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if os.path.isabs(path):
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return path
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return os.path.join(self.base_dir, path)
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def read_csv(self, path: str) -> pd.DataFrame:
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full = self._full_path(path)
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return pd.read_csv(full)
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class LocalResultsSink(ResultsSink):
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"""
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ResultsSink que escribe JSON e imágenes en el sistema de ficheros local.
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"""
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def __init__(self, base_dir: str = ".") -> None:
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self.base_dir = base_dir
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def _full_path(self, path: str) -> str:
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if os.path.isabs(path):
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full = path
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else:
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full = os.path.join(self.base_dir, path)
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# Crear carpetas si no existen
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os.makedirs(os.path.dirname(full), exist_ok=True)
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return full
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def write_json(self, path: str, data: Dict[str, Any]) -> None:
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full = self._full_path(path)
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with open(full, "w", encoding="utf-8") as f:
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json.dump(data, f, ensure_ascii=False, indent=2)
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def write_figure(self, path: str, fig: Figure) -> None:
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full = self._full_path(path)
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fig.savefig(full, bbox_inches="tight")
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62
backend/beyond_metrics/io/s3.py
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62
backend/beyond_metrics/io/s3.py
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from __future__ import annotations
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import io
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import json
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from typing import Any, Dict, Tuple
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import boto3
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import pandas as pd
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from matplotlib.figure import Figure
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from .base import DataSource, ResultsSink
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def _split_s3_path(path: str) -> Tuple[str, str]:
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"""
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Convierte 's3://bucket/key' en (bucket, key).
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"""
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if not path.startswith("s3://"):
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raise ValueError(f"Ruta S3 inválida: {path}")
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without_scheme = path[len("s3://") :]
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parts = without_scheme.split("/", 1)
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if len(parts) != 2:
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raise ValueError(f"Ruta S3 inválida: {path}")
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return parts[0], parts[1]
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class S3DataSource(DataSource):
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"""
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DataSource que lee CSV desde S3 usando boto3.
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"""
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def __init__(self, boto3_client: Any | None = None) -> None:
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self.s3 = boto3_client or boto3.client("s3")
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def read_csv(self, path: str) -> pd.DataFrame:
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bucket, key = _split_s3_path(path)
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obj = self.s3.get_object(Bucket=bucket, Key=key)
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body = obj["Body"].read()
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buffer = io.BytesIO(body)
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return pd.read_csv(buffer)
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class S3ResultsSink(ResultsSink):
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"""
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ResultsSink que escribe JSON e imágenes en S3.
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"""
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def __init__(self, boto3_client: Any | None = None) -> None:
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self.s3 = boto3_client or boto3.client("s3")
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def write_json(self, path: str, data: Dict[str, Any]) -> None:
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bucket, key = _split_s3_path(path)
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body = json.dumps(data, ensure_ascii=False, indent=2).encode("utf-8")
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self.s3.put_object(Bucket=bucket, Key=key, Body=body)
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def write_figure(self, path: str, fig: Figure) -> None:
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bucket, key = _split_s3_path(path)
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buf = io.BytesIO()
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fig.savefig(buf, format="png", bbox_inches="tight")
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buf.seek(0)
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self.s3.put_object(Bucket=bucket, Key=key, Body=buf.getvalue(), ContentType="image/png")
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