liquidgenius

#! /bin/bash

# License:    MIT; https://opensource.org/licenses/MIT
# Version:    0.0.1
# Maintainer: https://gist.github.com/liquidgenius

#*******************************************************************************
# Pycharmer; A Pycharm Python project creator
#*******************************************************************************

liquidgenius

#! /bin/bash

# License:    MIT; https://opensource.org/licenses/MIT
# Version:    0.0.1
# Maintainer: https://gist.github.com/liquidgenius
# Gist:       https://gist.github.com/liquidgenius/56167cfedc7270752d207377cf618fcf


#*******************************************************************************
# Masonite 3 Project Scaffolding

liquidgenius

#!/usr/bin/env python
# -*- coding: utf-8 -*-
# https://orm.masoniteproject.com/
# app.helpers.columns.py

from config.database import DB
from masoniteorm.collection import Collection


def columns(model):

michaelbrewer

# Ensure we have the latest pip and pipenv
pip3 install --upgrade pip pipenv
# Setup new Python 3.8 project
pipenv --python 3.8
# Install aws-lambda-powertools
pipenv install boto3 aws-lambda-powertools
# Install dev dependencies
pipenv install black pytest isort mypy --dev --pre

liquidgenius

#!/usr/bin/env python
# -*- coding: utf-8 -*-

from random import choice

import httpx
import fake_useragent


def Proxymesh(url, proxy_choices=None, headers=None, country='US'):

liquidgenius

from dataclasses import dataclass, fields as datafields
from ujson import dumps, loads
# Note: ujson seamlessly serializes dataclasses, unlike stdlib's json

@dataclass
class Point:
    x: float
    y: float

# Shallow dataclass can be rebuilt from dict/json:

liquidgenius

#!/usr/bin/env python
# -*- coding: utf-8 -*-
__license__ = "MIT"
__version__ = "0.0.1"
__maintainer__ = "https://github.com/liquidgenius"
__status__ = "Development"


from pathlib import Path
from pyngrok import ngrok

wshayes

# https://github.com/tiangolo/fastapi/issues/883#issuecomment-575913215
# You can probably use an async queue so your MQTT client will push messages to the queue and the WS server will get from the queue and send them to the WS client.

    from asyncio import Queue

    queue: Queue = None

    @app.websocket("/ws")
    async def websocket_endpoint(websocket: WebSocket):
        await websocket.accept()

wshayes

# https://stackoverflow.com/a/13530258/886938

import multiprocessing as mp
import time

fn = 'c:/temp/temp.txt'

def worker(arg, q):
    '''stupidly simulates long running process'''
    start = time.clock()

liquidgenius

import pymysql
import pandas as pd
from snowflake.sqlalchemy import URL as SFURL
from sqlalchemy import create_engine
from sqlalchemy.engine.url import URL


class OmniDB:
    """ A minimal Python class for uniform API to both Snowflake and MySQL databases. 
    TODO: Error handling