Stefan Thoss stefanthoss

Dictionaries

d.items() returns an iterable with key-value pairs as tuples
d.keys() returns an iterable with all keys
d.values() returns an iterable with all values
dict(sorted(d.items())) returns a dict sorted by keys
dict(sorted(d.items(), key=lambda x: x[1])) returns a dict sorted by values
d.get(key, default=None) returns the value for a key
d.pop(key, default=None) removes the key and returns the value for key
d.popitem() removes the last item added and returns it as (key, value) (LIFO)

PostgreSQL syntax

SELECT [DISTINCT] column_name
  FROM table_name
  WHERE condition
  GROUP BY grouping_element
  HAVING condition
  ORDER BY expression [ ASC | DESC ]
  LIMIT count

	ARG NVIDIA_DRIVER_VERSION=570.153.02
	ARG NVIDIA_DRIVER_FILENAME="NVIDIA-Linux-aarch64-${NVIDIA_DRIVER_VERSION}.run"

	RUN apt-get update \
	&& apt-get install -y --no-install-recommends \
	ca-certificates \
	kmod \
	wget \
	&& rm -rf /var/lib/apt/lists/*

	#!/usr/bin/env bash

	DEVICES=$(camcontrol devlist \| sed 's/.,\(.\)).*/\1/')

	for DEV in $DEVICES; do
	printf "%s: " "$DEV"
	camcontrol epc "$DEV" -c status -P
	done

	import pandas as pd

	# Input:
	# a b c d e
	# 0 Text Text NaN 0.0 5
	# 1 Text NaN 1.1.1.1 0.0 55
	# 2 Text.Text Text Text 0.4 555

	data = [
	{"a": "Text", "b": "Text", "d": 0, "e": 5},

	SELECT
	t.table_schema,
	t.table_name,
	c.column_name
	FROM
	information_schema.tables t
	INNER JOIN information_schema.columns c ON c.table_name = t.table_name
	AND c.table_schema = t.table_schema
	WHERE
	c.column_name ~ 'regex'

	def advanced_dataframe_union(df1, df2):
	df1_fields = set((f.name, f.dataType) for f in df1.schema)
	df2_fields = set((f.name, f.dataType) for f in df2.schema)

	df2 = df2.select(
	df2.columns
	+ [
	F.lit(None).cast(datatype).alias(name)
	for name, datatype in df1_fields.difference(df2_fields)
	]

	FROM alpine:3.10

	RUN apk add --no-cache \
	bzip2-dev \
	g++ \
	make

	RUN cd /tmp/ && \
	wget -q https://launchpad.net/pbzip2/1.1/1.1.13/+download/pbzip2-1.1.13.tar.gz && \
	tar -xzf pbzip2-1.1.13.tar.gz && \

	import json
	from pyspark.sql.types import *

	# Define the schema
	schema = StructType(
	[StructField("name", StringType(), True), StructField("age", IntegerType(), True)]
	)

	# Write the schema
	with open("schema.json", "w") as f: