Writing JSON column to Postgres using Pandas .to_sql

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半阙折子戏
半阙折子戏 2021-02-07 05:51

During an ETL process I needed to extract and load a JSON column from one Postgres database to another. We use Pandas for this since it has so many ways to read and write data f

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  • 2021-02-07 06:05

    I am unable to comment peralmq's answer, but in case of postgresql JSONB you can use

    from sqlalchemy import dialects
    dataframe.to_sql(..., dtype={"json_column":dialects.postgresql.JSONB})
    
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  • 2021-02-07 06:14

    I've been searching the web for a solution but couldn't find any so here is what we came up with (there might be better ways but at least this is a start if someone else runs into this).

    Specify the dtype parameter in to_sql.

    We went from:df.to_sql(table_name, analytics_db) to df.to_sql(table_name, analytics_db, dtype={'name_of_json_column_in_source_table': sqlalchemy.types.JSON}) and it just works.

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  • 2021-02-07 06:18

    If you (re-)create the JSON column using json.dumps(), you're all set. This way the data can be written using pandas' .to_sql() method, but also the much faster COPY method of PostgreSQL (via copy_expert() of psycopg2 or sqlalchemy's raw_connection()) can be employed.

    For the sake of simplicity, let's assume that we have a column of dictionaries that should be written into a JSON(B) column:

    import json
    import pandas as pd
    
    df = pd.DataFrame([['row1',{'a':1, 'b':2}],
                       ['row2',{'a':3,'b':4,'c':'some text'}]],
                      columns=['r','kv'])
    
    # conversion function:
    def dict2json(dictionary):
        return json.dumps(dictionary, ensure_ascii=False)
    
    # overwrite the dict column with json-strings
    df['kv'] = df.kv.map(dict2json)
    
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