Tutorial and tips for GitHub Actions workflows
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| ## | |
| ## How to run multiple uvicorn server apps in the same process | |
| ## | |
| import asyncio | |
| from uvicorn import Server, Config | |
| class MyServer(Server): | |
| async def run(self, sockets=None): | |
| self.config.setup_event_loop() | |
| return await self.serve(sockets=sockets) |
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| [tool.poetry.dependencies] | |
| python = "3.7.7" | |
| gdal = {platform = "windows", path = "thirdparty/GDAL-3.1.2-cp37-cp37m-win32.whl"} | |
| fiona = {platform = "windows", path = "thirdparty/Fiona-1.8.13-cp37-cp37m-win32.whl"} | |
| [tool.coverage.paths] | |
| source = ["src", "*/site-packages"] | |
| [tool.coverage.run] | |
| branch = true |
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| #!/bin/sh | |
| echo '' | |
| echo ' __________' | |
| echo ' / ___ ___ \' | |
| echo ' / / @ \/ @ \ \' | |
| echo ' \ \___/\___/ /\' | |
| echo ' \____\/____/||' | |
| echo ' / /\\\\\//' | |
| echo ' | |\\\\\\' |
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| from datetime import datetime | |
| from typing import Optional | |
| import pandas as pd | |
| from rich import box | |
| from rich.console import Console | |
| from rich.table import Table | |
| console = Console() |
Pandas DataFrames are central to Data Analysis in Python. In this post, we introduce the itables Python package that enhances how these DataFrames are displayed, by turning them into interactive HTML DataTables.
Using itables is as simple as
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