| from sqlalchemy import create_engine, Column, Integer, String | |
| from sqlalchemy.ext.declarative import declarative_base | |
| from sqlalchemy.orm import sessionmaker | |
| from contextlib import contextmanager | |
| Base = declarative_base() | |
| class User(Base): | |
| __tablename__ = "users" | |
| id = Column(Integer, primary_key=True, index=True) |
First, we'll look at the SOAP URL and see what Prefixes, Global Elements, Global Types, Bindings, and Services are provided by the SOAP Service.
You can do this by running zeep as a CLI tool.
export WSDL_URL="http://www.dneonline.com/calculator.asmx?WSDL"
python -m zeep $WSDL_URL
| ## How to hide API keys from github ## | |
| 1. If you have already pushed commits with sensitive data, follow this guide to remove the sensitive info while | |
| retaining your commits: https://help.github.com/articles/remove-sensitive-data/ | |
| 2. In the terminal, create a config.js file and open it up: | |
| touch config.js | |
| atom config.js |
| from datetime import datetime, timedelta | |
| def find_next_biz_day(days_away=1, | |
| start=None, | |
| is_holiday=lambda d: False): | |
| """ | |
| Finds a business day that is N days away | |
| :param days_away: Days away (positive or negative) | |
| :param start: Starting date (today if None) |
| ### Cloudwatch Events ### | |
| # Event rule: Runs at 8pm during working days | |
| resource "aws_cloudwatch_event_rule" "start_instances_event_rule" { | |
| name = "start_instances_event_rule" | |
| description = "Starts stopped EC2 instances" | |
| schedule_expression = "cron(0 8 ? * MON-FRI *)" | |
| depends_on = ["aws_lambda_function.ec2_start_scheduler_lambda"] | |
| } | |
| # Runs at 8am during working days |
| """Extract nested values from a JSON tree.""" | |
| def json_extract(obj, key): | |
| """Recursively fetch values from nested JSON.""" | |
| arr = [] | |
| def extract(obj, arr, key): | |
| """Recursively search for values of key in JSON tree.""" | |
| if isinstance(obj, dict): |
| # vim: set fileencoding=utf-8 : | |
| # | |
| # How to store and retrieve gzip-compressed objects in AWS S3 | |
| ########################################################################### | |
| # | |
| # Copyright 2015 Vince Veselosky and contributors | |
| # | |
| # 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 |
| """ | |
| A sample funtion to perform S3 select operation on a JSON file stored in S3 bucket | |
| The bucket and file names are stored as environment variables | |
| """ | |
| import os | |
| import boto3 | |
| def get_data(): | |
| """ | |
| Using S3 select to query data from S3 |
| from __future__ import unicode_literals | |
| import logging | |
| import json | |
| logger = logging.getLogger(__name__) | |
| logging.getLogger().setLevel(logging.INFO) | |
| class PythonObjectEncoder(json.JSONEncoder): | |
| """Custom JSON Encoder that allows encoding of un-serializable objects |