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POFast insertion of pandas DataFrame into Postgres DB using psycopg2
 

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  1. POFast insertion of pandas DataFrame into Postgres DB using psycopg2
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    <p>I am trying to insert a <a href="http://pandas.pydata.org" rel="nofollow noreferrer">pandas</a> DataFrame into a Postgresql DB (9.1) in the most efficient way (using Python 2.7).<br> Using "cursor.execute_many" is really slow, so is "DataFrame.to_csv(buffer,...)" together with "copy_from".<br> I found an already much! faster solution on the web (<a href="http://eatthedots.blogspot.de/2008/08/faking-read-support-for-psycopgs.html" rel="nofollow noreferrer">http://eatthedots.blogspot.de/2008/08/faking-read-support-for-psycopgs.html</a>) which I adapted to work with pandas. <br> My code can be found below.<br> My question is whether the method of this related question (using "copy from stdin with binary") can be easily transferred to work with DataFrames and if this would be much faster.<br> <a href="https://stackoverflow.com/questions/8144002/use-binary-copy-table-from-with-psycopg2">Use binary COPY table FROM with psycopg2</a><br> Unfortunately my Python skills aren't sufficient to understand the implementation of this approach.<br> This is my approach:</p> <pre><code> import psycopg2 import connectDB # this is simply a module that returns a connection to the db from datetime import datetime class ReadFaker: """ This could be extended to include the index column optionally. Right now the index is not inserted """ def __init__(self, data): self.iter = data.itertuples() def readline(self, size=None): try: line = self.iter.next()[1:] # element 0 is the index row = '\t'.join(x.encode('utf8') if isinstance(x, unicode) else str(x) for x in line) + '\n' # in my case all strings in line are unicode objects. except StopIteration: return '' else: return row read = readline def insert(df, table, con=None, columns = None): time1 = datetime.now() close_con = False if not con: try: con = connectDB.getCon() ###dbLoader returns a connection with my settings close_con = True except psycopg2.Error, e: print e.pgerror print e.pgcode return "failed" inserted_rows = df.shape[0] data = ReadFaker(df) try: curs = con.cursor() print 'inserting %s entries into %s ...' % (inserted_rows, table) if columns is not None: curs.copy_from(data, table, null='nan', columns=[col for col in columns]) else: curs.copy_from(data, table, null='nan') con.commit() curs.close() if close_con: con.close() except psycopg2.Error, e: print e.pgerror print e.pgcode con.rollback() if close_con: con.close() return "failed" time2 = datetime.now() print time2 - time1 return inserted_rows </code></pre>
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