How to display a streaming DataFrame (as show fails with AnalysisException)?

So I have some data I'm stream in a Kafka topic, I'm taking this streaming data and placing it into a DataFrame. I want to display the data inside of the DataFrame:

import os
from kafka import KafkaProducer
from pyspark.sql import SparkSession, DataFrame
import time
from datetime import datetime, timedelta

os.environ['PYSPARK_SUBMIT_ARGS'] = '--packages org.apache.spark:spark-sql-kafka-0-10_2.11:2.2.0,org.apache.spark:spark-streaming-kafka-0-8_2.11:2.2.0 pyspark-shell'

topic_name = "my-topic"
kafka_broker = "localhost:9092"

producer = KafkaProducer(bootstrap_servers = kafka_broker)
spark = SparkSession.builder.getOrCreate()
terminate = datetime.now() + timedelta(seconds=30)

while datetime.now() < terminate:
    producer.send(topic = topic_name, value = str(datetime.now()).encode('utf-8'))
    time.sleep(1)

readDF = spark \
    .readStream \
    .format("kafka") \
    .option("kafka.bootstrap.servers", kafka_broker) \
    .option("subscribe", topic_name) \
    .load()
readDF = readDF.selectExpr("CAST(key AS STRING)","CAST(value AS STRING)")

readDF.writeStream.format("console").start()
readDF.show()

producer.close()

However I keep on getting this error:

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/spark/spark/python/pyspark/sql/utils.py", line 63, in deco
    return f(*a, **kw)
  File "/home/spark/spark/python/lib/py4j-0.10.4-src.zip/py4j/protocol.py", line 319, in get_return_value
py4j.protocol.Py4JJavaError: An error occurred while calling o30.showString.
: org.apache.spark.sql.AnalysisException: Queries with streaming sources must be executed with writeStream.start();;
kafka
    at org.apache.spark.sql.catalyst.analysis.UnsupportedOperationChecker$.org$apache$spark$sql$catalyst$analysis$UnsupportedOperationChecker$$throwError(UnsupportedOperationChecker.scala:297)
    at org.apache.spark.sql.catalyst.analysis.UnsupportedOperationChecker$$anonfun$checkForBatch$1.apply(UnsupportedOperationChecker.scala:36)
    at org.apache.spark.sql.catalyst.analysis.UnsupportedOperationChecker$$anonfun$checkForBatch$1.apply(UnsupportedOperationChecker.scala:34)
    at org.apache.spark.sql.catalyst.trees.TreeNode.foreachUp(TreeNode.scala:127)
...
Traceback (most recent call last):
      File "test2.py", line 30, in <module>
        readDF.show()
      File "/home/spark/spark/python/pyspark/sql/dataframe.py", line 336, in show
        print(self._jdf.showString(n, 20))
      File "/home/spark/spark/python/lib/py4j-0.10.4-src.zip/py4j/java_gateway.py", line 1133, in __call__
      File "/home/spark/spark/python/pyspark/sql/utils.py", line 69, in deco
        raise AnalysisException(s.split(': ', 1)[1], stackTrace)
    pyspark.sql.utils.AnalysisException: 'Queries with streaming sources must be executed with writeStream.start();;\nkafka'

I don't understand why the exception is happening, I'm calling writeStream.start() right before show(). I tried getting rid of selectExpr() but that made no difference. Does anyone know how to display a stream sourced DataFrame? I'm using Python 3.6.1, Kafka 0.10.2.1, and Spark 2.2.0