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import datetime
import pyspark.sql.functions as F
from pyspark.sql.window import Window

def input_event_paths(date, depth):
    dt = datetime.datetime.strptime(date, '%Y-%m-%d')
    return [f"/user/username/data/events/date={(dt-datetime.timedelta(days=x)).strftime('%Y-%m-%d')}" for x in range(depth)]

def tag_tops(date, depth, spark):
		message_paths = input_event_paths(date, depth)
		result = spark.read\
    .option("basePath", "/user/username/data/events")\
    .parquet(*message_paths)\
    .where("event_type = 'message'")\
		.where("event.message_channel_to is not null")\
		.select(F.col("event.message_id").alias("message_id"),
		        F.col("event.message_from").alias("user_id"),
		        F.explode(F.col("event.tags")).alias("tag"))\
		.groupBy("user_id", "tag")\
		.agg(F.count("*").alias("tag_count"))\
		.withColumn("rank", F.row_number().over(Window.partitionBy("user_id")\
        .orderBy(F.desc("tag_count"), F.desc("tag"))))\
		.where("rank <= 3")\
		.groupBy("user_id")\
		.pivot("rank", [1, 2, 3])\
		.agg(F.first("tag"))\
		.withColumnRenamed("1", "tag_top_1")\
		.withColumnRenamed("2", "tag_top_2")\
		.withColumnRenamed("3", "tag_top_3")
	
		return result
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