dead

How to use

First you will need to change the testcicd to the name of your project. In the deployment.json you will also need to change the pkg-testcicd to pkg-{your-project-name}. (This was a small hack to avoid dbx to upload the entire project folder)

Then you can run the normal deploy/launch commands to run the integration test.

dbx deploy --jobs=cov-sample-integration-test --files-only
dbx launch --job=cov-sample-integration-test --as-run-submit --trace
databricks fs cp dbfs:/tmp/coverage.xml .

davideicardi

Alpakka Kafka connector (akka-stream-kafka) example

Simple solution to use Alpakka Kafka connector to produce and consume kafka messages.

I assume that you have 2 scala apps, a producer and a consumer.

Producer

Add the following dependencies:

loilo

This is about how to split a GitHub pull request, following a real in-the-wild example.

So it happened that I once wanted to fix a bug (#832) on the shelljs repository.

I forked the repository, cloned it and created a new branch called ln-directory-dest. I fixed the bug, created a pull request, and implemented initial review feedback.

At this point, I had added the commits A, B, C, D, E and [F](https://github.com/Loilo/shelljs/commit/946ab48bf5cf9c8aac03407

480

MacOS X + oh my zsh + powerline fonts + visual studio code (vscode) terminal settings

Thank you everybody, Your comments makes it better

Install oh my zsh

http://ohmyz.sh/

sh -c "$(curl -fsSL https://raw.github.com/ohmyzsh/ohmyzsh/master/tools/install.sh)"

dmyersturnbull

import pandas as pd
import itertools
import time
import multiprocessing
from typing import Callable, Tuple, Union

def groupby_parallel(
  groupby_df: pd.core.groupby.DataFrameGroupBy,
  func: Callable[[Tuple[str, pd.DataFrame]], Union[pd.DataFrame, pd.Series]],
  num_cpus: int = multiprocessing.cpu_count() - 1,

didip

worker_processes 2;

error_log /var/log/nginx/error.log;
pid /var/run/nginx.pid;

events {
    worker_connections 1024;
    use epoll;
}