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https://github.com/hwchase17/langchain
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760632b292
Co-authored-by: Rithwik Ediga Lakhamsani <rithwik.ediga@databricks.com> Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
39 lines
1.0 KiB
Python
39 lines
1.0 KiB
Python
import random
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import string
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from langchain.docstore.document import Document
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from langchain.document_loaders.pyspark_dataframe import PySparkDataFrameLoader
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def test_pyspark_loader_load_valid_data() -> None:
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from pyspark.sql import SparkSession
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# Requires a session to be set up
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spark = SparkSession.builder.getOrCreate()
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data = [
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(random.choice(string.ascii_letters), random.randint(0, 1)) for _ in range(3)
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]
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df = spark.createDataFrame(data, ["text", "label"])
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expected_docs = [
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Document(
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page_content=data[0][0],
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metadata={"label": data[0][1]},
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),
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Document(
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page_content=data[1][0],
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metadata={"label": data[1][1]},
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),
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Document(
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page_content=data[2][0],
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metadata={"label": data[2][1]},
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),
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]
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loader = PySparkDataFrameLoader(
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spark_session=spark, df=df, page_content_column="text"
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)
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result = loader.load()
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assert result == expected_docs
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