Database upsert all dataframe data











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having a DataFrame df, how do I best approach upserting it's data into a postgres database?



I use the following code to upload the data - this seems to be super efficient (way more than pd.to_sql):



def to_sql(engine: sqlalchemy.engine, df: pd.DataFrame, table, if_exists='append', sep='t', encoding='utf8'):
# df[:0].to_sql(table, engine, if_exists=if_exists) # Not needed as the table has to exist

output = StringIO()
df.to_csv(output, sep=sep, header=False, encoding=encoding, index=False)
output.seek(0)

connection = engine.raw_connection()
cursor = connection.cursor()
cursor.copy_from(output, table, sep=sep, null='', columns=list(df.columns))
connection.commit()
cursor.close()


When I think about UPSERT the data though, an approach like that does obviously not work.



Thanks!










share|improve this question


























    up vote
    0
    down vote

    favorite












    having a DataFrame df, how do I best approach upserting it's data into a postgres database?



    I use the following code to upload the data - this seems to be super efficient (way more than pd.to_sql):



    def to_sql(engine: sqlalchemy.engine, df: pd.DataFrame, table, if_exists='append', sep='t', encoding='utf8'):
    # df[:0].to_sql(table, engine, if_exists=if_exists) # Not needed as the table has to exist

    output = StringIO()
    df.to_csv(output, sep=sep, header=False, encoding=encoding, index=False)
    output.seek(0)

    connection = engine.raw_connection()
    cursor = connection.cursor()
    cursor.copy_from(output, table, sep=sep, null='', columns=list(df.columns))
    connection.commit()
    cursor.close()


    When I think about UPSERT the data though, an approach like that does obviously not work.



    Thanks!










    share|improve this question
























      up vote
      0
      down vote

      favorite









      up vote
      0
      down vote

      favorite











      having a DataFrame df, how do I best approach upserting it's data into a postgres database?



      I use the following code to upload the data - this seems to be super efficient (way more than pd.to_sql):



      def to_sql(engine: sqlalchemy.engine, df: pd.DataFrame, table, if_exists='append', sep='t', encoding='utf8'):
      # df[:0].to_sql(table, engine, if_exists=if_exists) # Not needed as the table has to exist

      output = StringIO()
      df.to_csv(output, sep=sep, header=False, encoding=encoding, index=False)
      output.seek(0)

      connection = engine.raw_connection()
      cursor = connection.cursor()
      cursor.copy_from(output, table, sep=sep, null='', columns=list(df.columns))
      connection.commit()
      cursor.close()


      When I think about UPSERT the data though, an approach like that does obviously not work.



      Thanks!










      share|improve this question













      having a DataFrame df, how do I best approach upserting it's data into a postgres database?



      I use the following code to upload the data - this seems to be super efficient (way more than pd.to_sql):



      def to_sql(engine: sqlalchemy.engine, df: pd.DataFrame, table, if_exists='append', sep='t', encoding='utf8'):
      # df[:0].to_sql(table, engine, if_exists=if_exists) # Not needed as the table has to exist

      output = StringIO()
      df.to_csv(output, sep=sep, header=False, encoding=encoding, index=False)
      output.seek(0)

      connection = engine.raw_connection()
      cursor = connection.cursor()
      cursor.copy_from(output, table, sep=sep, null='', columns=list(df.columns))
      connection.commit()
      cursor.close()


      When I think about UPSERT the data though, an approach like that does obviously not work.



      Thanks!







      python pandas sqlalchemy






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked Nov 11 at 18:05









      Bishonen_PL

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