imports

app.py

@@ -1,34 +1,34 @@
 import streamlit as st
 ###
-# import os
-# import re
-# import ast
-# import heapq
-# import warnings
-#
-# import pandas as pd
-# from datetime import datetime, timedelta
-# from typing import Dict, List, Tuple, Any
-#
-# import plotly.express as px
-# import plotly.graph_objects as go
-# import ipywidgets as widgets
-# from IPython.display import display
-#
-# from functools import reduce
-# from pyhive import hive
-# from pyspark.sql import SparkSession, DataFrame, functions as F
-# from pyspark.sql.functions import (
-#     lit, to_timestamp, unix_timestamp, hour, dayofweek, when, col, count
-# )
-# from pyspark.sql.types import StructType, StructField, StringType, TimestampType, IntegerType
-# from pyspark.ml import Pipeline, PipelineModel
-# from pyspark.ml.feature import VectorAssembler, StandardScaler
-# from pyspark.ml.classification import LogisticRegression, LogisticRegressionModel
-# from pyspark.ml.evaluation import MulticlassClassificationEvaluator, ClusteringEvaluator
-# from pyspark.ml.clustering import PowerIterationClustering
-#
-# warnings.simplefilter(action='ignore', category=UserWarning)
+import os
+import re
+import ast
+import heapq
+import warnings
+
+import pandas as pd
+from datetime import datetime, timedelta
+from typing import Dict, List, Tuple, Any
+
+import plotly.express as px
+import plotly.graph_objects as go
+import ipywidgets as widgets
+from IPython.display import display
+
+from functools import reduce
+from pyhive import hive
+from pyspark.sql import SparkSession, DataFrame, functions as F
+from pyspark.sql.functions import (
+    lit, to_timestamp, unix_timestamp, hour, dayofweek, when, col, count
+)
+from pyspark.sql.types import StructType, StructField, StringType, TimestampType, IntegerType
+from pyspark.ml import Pipeline, PipelineModel
+from pyspark.ml.feature import VectorAssembler, StandardScaler
+from pyspark.ml.classification import LogisticRegression, LogisticRegressionModel
+from pyspark.ml.evaluation import MulticlassClassificationEvaluator, ClusteringEvaluator
+from pyspark.ml.clustering import PowerIterationClustering
+
+warnings.simplefilter(action='ignore', category=UserWarning)
 ###