| """Utilities for working Amazon Athena. | |
| Example: | |
| To run a query and get the results as a pandas DataFrame: | |
| >>> query = "SELECT * FROM my_table" | |
| >>> df = get_df_from_athena(query) | |
| >>> df.head() | |
Your Raspberry Pi can join The Tor Project network that helps Russians read censored news sites, including Twitter.
These are all the commands necessary to spin up a Snowflake proxy that gives Tor users a way around government attempts to block access.
You can also run a Snowflake proxy from your web browser with Firefox or Chrome. Standing it up on your Raspberry Pi is a way to support the system 24 hours a day. And, unlike other Tor server setups, it doesn't require a static IP address.
| def numoji(number): | |
| """Convert a number into a series of emojis. | |
| Args: | |
| number (int): The number to convert into emoji | |
| Returns: Am emoji string | |
| """ | |
| # Convert the provided number to a string | |
| s = str(number) |
| [ | |
| { | |
| "case_number":"2017-04514", | |
| "slug":"eddie-rosendo-lino", | |
| "first_name":"Eddie", | |
| "middle_name":"Rosendo", | |
| "last_name":"Lino", | |
| "death_date":"2017-06-18T00:00:00.000Z", | |
| "death_year":2017, | |
| "age":23.0, |
This post contains code and commands you can use to deploy Prefect agents to Google Cloud’s Google Kubernetes Engine. The agents stand ready to execute workflows triggered by Prefect projects. One agent can run tasks from multiple projects.
The example here demonstrates how to create a single agent with minimal customization. It is configured with a Dockerfile, which installs necessary dependencies, and a k8s.cfg file, which connects the system to a Prefect account.
Agents are deployed via the gcloud command-line utility and its kubectl extension. Proper permissions within a project on Google Cloud are required.
Here's how I configured a GitHub Action so that a new version issued by GitHub's release interface will build a Dockerfile, tag it with the version number and upload it to Google Artifact Registry.
Before you attempt the steps below, you need the following:
The pandas data-analysis tool can do almost everything. And because it can do almost everything, it's a massive hunk of code. So you might not want to include it in your project if you can avoid taking on the weight.
One of pandas' handiest features is quickly opening Excel spreadsheets. If that's all you need, here's how to accomplish the task with openpyxl, a much lighter dependency.
| # -*- coding: utf-8 -*- | |
| """ | |
| A command-line interface for running Jupyter Notebooks. | |
| Usage: run.py [OPTIONS] [NOTEBOOK_PATHS]... | |
| Executes Jupyter Notebooks from the command line. | |
| Expects one or more file paths input as arguments. |