jsn | A relaxed , user-friendly json-like data format | JSON Processing library

    try:
        p = win32print.OpenPrinter("Dmax4310e")
        win32print.StartDocPrinter(p, 1, ("Python test RAW print", None, "raw"))
        win32print.StartPagePrinter(p)
        win32print.WritePrinter(p, labelString.encode('utf-8')

def str2dict(data):
    data = data.strip(" {}") # get rid of brackets and spaces at the start an end
    key_value_pair_strings = data.split(",") # split data at , into key value pair strings
    key_value_pair_strings_stripped = list(map

import json
str1_dict='{"Sentence": "Frequently Asked Questions AND PRIVACY" ,"Question": "What is the most frequently asked question about privacy?", "Answer0": "Frequently", "Question": "What does Privacy stand for?", "Answer1": "PRIVACY

import json

csv = """Contract_no,sales_date,store_sales_amount,cashier_counter,discount_amount,before_tax_amount,tax_amount,cashier_amount,product,dine_in,take_away,mode,amount
CS,2020-04-12,18.50,C1,0,18.50,0,18.50,18.50,0,0,CASH,1068.50

>>> data = [
        ['Power:',data["PowerS"],'MVA'],
        ['Voltage:',data["Voltage"],'V'],
        ['Impedance:',data["Impedance"],'ohms'],
        ['Current:',data["CurrentS"],'A'],
    ]
>>> print(data[0][0])
'Powe

#sample dataframe
df=spark.createDataFrame([("a",1),("b",2)],["id","name"])

from pyspark.sql.functions import *

df.groupBy(lit("1")).\
agg(collect_list(struct(*[df.columns])).alias("cl")).\
select(to_json("cl").alias("jsn")).\
rdd.\
map(

df.select("doc_id",explode("msp_contracts")).show()
#+------+---+
#|doc_id|col|
#+------+---+
#|     1|[1]|
#+------+---+

jsn='{"doc_id":1,"msp_contracts":[{"_el1":1}]}'
df=spark.read.json(sc.parallelize([(jsn)]))

#sample valid json
jsn='{"feed":{"catalog":{"schema":["somekey","somevalue"], "add":{"items":[{"sku":"10002","status":"Enabled"},{"sku":"10003","status":"Enabled"}]}}}}'

#read the json using spark.read.json
df=spark.read.json(sc.paralleli

#F is  pyspark.sql.functions
#schm in my json Schema sth like  
schm = StructType([
StructField("col1", LongType(), True),
StructField("col2", StringType(), True)])      
df.select(F.from_json(F.col("changes"),
schm
).alias("jsn")).select(

df.show()
#+---------------+----------------------------------------------------------------------------------------------------------------+
#|candidate_email|transactions