xescuder

from datetime import date, datetime, timedelta
from dateutil.relativedelta import relativedelta


def build_formatted_range(interval: str, range_start: date | datetime = None, range_end: date | datetime = None,
                          period: str = None):
    new_start = range_start
    new_end = range_end

    if range_end is None:

xescuder

version: "3"
services:
  db:
    image: mysql:5.7
    volumes:
      - ./wp-data:/var/lib/mysql
    restart: always
    environment:
      MYSQL_ROOT_PASSWORD: MyR00tMySQLPa$$w0rD
      MYSQL_DATABASE: MyWordPressDatabaseName

xescuder

core:
  i18n:
    language: 'es'
  logging:
    version: 1
    formatters:
      standard:
        format: "%(asctime)s - %(name)s - %(levelname)s - %(message)s"
      error:
        format: "%(asctime)s - %(name)s - %(levelname)s <PID %(process)d:%(processName)s>\

xescuder

import logging
from sqlalchemy import (Table, Column, Integer, Enum, Float, String, Date, Boolean, ForeignKey)
from sqlalchemy.orm import registry, relationship

from bot.domain import model

"""
Imperative mapping with dataclasses (models are dataclasses)
https://docs.sqlalchemy.org/en/14/orm/mapping_styles.html#imperative-mapping-with-dataclasses-and-attrs
"""

xescuder

import os
from os import environ as env
from typing import get_type_hints, Union
from dotenv import load_dotenv

env = os.getenv('ENVIRONMENT')
dotenv_path = f'.env.{env}' if env is not None else '.env'
load_dotenv(dotenv_path=dotenv_path)

xescuder

version: "3"
x-airflow-common: &airflow-common
  # In order to add custom dependencies or upgrade provider packages you can use your extended image.
  # Comment the image line, place your Dockerfile in the directory where you placed the docker-compose.yaml
  # and uncomment the "build" line below, Then run `docker-compose build` to build the images.
  image: trading-airflow #${AIRFLOW_IMAGE_NAME:-apache/airflow}
  # build: .
  environment: &airflow-common-env
    AIRFLOW__CORE__EXECUTOR: LocalExecutor
    AIRFLOW__DATABASE__SQL_ALCHEMY_CONN: postgresql+psycopg2://airflow:airflow@postgres/airflow

xescuder

import os
from pathlib import Path
from sqlalchemy import create_engine
import pandas as pd

from trading_data_pipeline.config import AppConfig

config = AppConfig(os.environ)

connection_url = config.get_postgres_uri()

xescuder

SELECT s.symbol, s.sector, first(close, date) AS first_close, last(close, date) AS last_close,
      MIN(date) AS first_date,
      MAX(date) AS last_date,
      100 * (last(close, date) - first(close, date)) / first(close, date) AS return_change
    FROM
      daily_bars db, stocks s
    WHERE
      db.date >= now() - interval '1 year' AND db.symbol = s.symbol
    GROUP BY
      s.symbol

xescuder

xescuder

import backtrader as bt

from trading_backtesting.stop_trailer import StopTrailer


class GoldenCrossStrategy(bt.Strategy):
    SHORT, NONE, LONG = -1, 0, 1

    params = dict(
        fast_length=50,