Summary
Sometimes when converting a Pandas DataFrame to a Spark DataFrame variables are not interpreted correctly
which can lead a programmer to have to type many lines of code and then provide the schema when building the
Spark DataFrame.
Additionally this is true for defining a Delta Table before loading your parquet files. This package contains
two functions aimed at creating these definitions which will hopefully cut down on a lot of typing and speed
up development time for the user.
Installation
pip install SparkSchemafy
Usage
from schemafy import make_spark_schema, make_delta_schema
Make a Spark DataFrame Schema from a Pandas DataFrame
make_spark_schema(str(spark.sql.DataFram().schema))
Make a delta table schema from parquet file
make_delta_schema('.parquet')
Metadata
Release files for SparkSchemafy 0.1.4
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
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| SparkSchemafy-0.1.4.tar.gz | 5.1 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| SparkSchemafy-0.1.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 8.4 kB
Release files / SparkSchemafy-0.1.4.tar.gz
| Download URL | SparkSchemafy-0.1.4.tar.gz |
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| Size | 5.1 kB |
| Tags | Source |
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Release files / SparkSchemafy-0.1.4-py3-none-any.whl
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| Tags | Python 3 |
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Security for SparkSchemafy 0.1.4
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