How to read a SQLite database file using polars package in Python

You can read a SQLite database file using the "polars" package in Python as follows:

Install the "polars" package using pip:

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pip install polars

Import the required libraries:

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import polars

import pandas as pd

Load the SQLite database file using polars.load_dataset:

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df = polars.load_dataset('path/to/your/sqlite_file.db')

Convert the data to a Pandas dataframe:

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df = pd.DataFrame(df)

You can now interact with the data as you would with any other Pandas dataframe. For example, you can view the first 5 rows of the data using df.head().

Note: The "polars" package can also be used to read other file formats, such as Parquet and Avro. It's a fast, memory-efficient data processing library for large datasets.

To query the data in the SQLite database, you can use the polars.select_data method. For example, to retrieve all rows where a specific column has a certain value, you can use the following code:

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query = polars.select_data(df, where="column_name='value'")

You can also aggregate the data using the polars.aggregate method. For example, to calculate the average value of a specific column, you can use the following code:

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aggregate = polars.aggregate(df, by=['column_name'], agg={'column_name': 'mean'})

Finally, to save the query or aggregate results back to the SQLite database, you can use the polars.to_dataset method. For example:

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polars.to_dataset(query, 'path/to/your/sqlite_file.db')

With these basic steps, you should be able to read, query, and write to a SQLite database using the "polars" package in Python.