| steps: | |
| - uses: actions/checkout@v3 | |
| - uses: docker/setup-qemu-action@v1 | |
| - uses: mr-smithers-excellent/docker-build-push@v5 | |
| with: | |
| image: flask_docker | |
| registry: 940443069190.dkr.ecr.ap-southeast-1.amazonaws.com | |
| tags: ${{ github.sha }} | |
| platform: linux/arm64/v8 | |
| env: |
| db_url = URL.create( | |
| "postgresql+psycopg2", | |
| username="postgres", | |
| password="", | |
| host="", | |
| database="postgres", | |
| ) | |
| engine = create_engine(db_url, connect_args={'connect_timeout': 10}) | |
| metadata = MetaData() | |
| metadata.reflect(engine) |
| /** | |
| * Copyright 2020 Google LLC | |
| * | |
| * Licensed under the Apache License, Version 2.0 (the "License"); | |
| * you may not use this file except in compliance with the License. | |
| * You may obtain a copy of the License at | |
| * | |
| * http://www.apache.org/licenses/LICENSE-2.0 | |
| * | |
| * Unless required by applicable law or agreed to in writing, software |
This guide provides step-by-step instructions on how to backup Elasticache, copy the backup to Amazon S3, create GCP Redis, select network, allocate IP range, create a storage bucket, and upload the backup file. Finally, it explains how to import the backup file after Redis starts.
Before proceeding with the backup and restore process, make sure you have the following:
This doc is a guide for launching a virtual machine (VM) and setting up Airbyte, a data integration platform.
Before getting started, ensure that you have the following:
| from sqlalchemy import MetaData, Table, text | |
| from sqlalchemy.orm import scoped_session | |
| from sqlalchemy import create_engine, URL | |
| from sqlalchemy.ext.declarative import declarative_base | |
| from sqlalchemy.orm import sessionmaker | |
| connection_cred = { | |
| 'username':'postgres', | |
| 'password': '', | |
| 'host':'', |
| import json | |
| from google.cloud import storage | |
| bucket_name = "" | |
| folder_name = "unchecked_checkbox" | |
| def list_items_in_folder(folder_path): | |
| client = storage.Client() |
| def euclidean_distance(point1, point2): | |
| x1, y1 = point1 | |
| x2, y2 = point2 | |
| return math.sqrt((x1 - x2) ** 2 + (y1 - y2) ** 2) | |
| def cal(c_cor, t_cor): | |
| c = c_cor | |
| c_xmid, cy_mid = (c[0][0] + c[2][0]) / 2, (c[0][1] + c[2][1]) / 2 | |
| return t_cor[0][1] <= cy_mid <= t_cor[3][1] |
| def parse_json_from_text(text): | |
| # Removing newline characters and backticks | |
| clean_text = text.replace('\n', '').replace('`', '') | |
| # Extracting JSON part | |
| json_start_index = clean_text.find('{') | |
| json_string = clean_text[json_start_index:] | |
| # Parsing JSON | |
| data = json.loads(json_string) |
