title: PySpark equivalent of function "typedLit" from Scala API
body: <p>We have a function <code>typedLit</code> in <a href="https://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.sql.functions$" rel="nofollow noreferrer">Scala API for Spark</a> to add the Array or Map as column value.</p>
  <pre><code>import org.apache.spark.sql.functions.typedLit
  val df1 = Seq((1, 0), (2, 3)).toDF(&quot;a&quot;, &quot;b&quot;)
  
  df1.withColumn(&quot;seq&quot;, typedLit(Seq(1,2,3)))
      .show(truncate=false)
  
  +---+---+---------+
  |a  |b  |seq      |
  +---+---+---------+
  |1  |0  |[1, 2, 3]|
  |2  |3  |[1, 2, 3]|
  +---+---+---------+
  </code></pre>
  <p>I couldn't find the equivalent in PySpark. How can we create a column in PySpark with Array as a column value?</p>