pgcopy 1.2.0

Fast db insert with postgresql binary copy

pgcopy is a small system for very fast bulk insertion of data into a PostgreSQL database table using binary copy.

Installation

To install:

$ pip install pgcopy

pgcopy requires pytz and the psycopg2 db adapter. nose is required to run the tests.

Use

pgcopy provides facility for copying data from an iterable of tuple-like objects using a CopyManager, which must be instantiated with a psycopg2 db connection, the table name, and an iterable containing the names of the columns to be inserted in the order in which they will be provided. pgcopy inspects the database to determine the datatypes of the columns.

For example:

from datetime import datetime
from pgcopy import CopyManager
import psycopg2
cols = ('id', 'timestamp', 'location', 'temperature')
now = datetime.now()
records = [
        (0, now, 'Jerusalem', 72.2),
        (1, now, 'New York', 75.6),
        (2, now, 'Moscow', 54.3),
    ]
conn = psycopg2.connect(database='weather_db')
mgr = CopyManager(conn, 'measurements_table', cols)
mgr.copy(records)

By default, a temporary file on disk is used. If there’s enough memory, you can get a slight performance benefit with in-memory storage:

from cStringIO import StringIO
mgr.copy(records, StringIO)

A db schema can be specified in the table name using dot notation:

mgr = CopyManager(conn, 'myschema.measurements', cols)

Supported datatypes

Currently the following PostgreSQL datatypes are supported:

• bool

• smallint

• integer

• bigint

• real

• double precision

• char

• varchar

• text

• bytea

• date

• timestamp

• timestamp with time zone

• numeric (data must be decimal.Decimal)

• json

• jsonb

• uuid

Note

PostgreSQL numeric does not support Decimal('Inf') or Decimal('-Inf'). pgcopy serializes these as NaN.

Testing

For a fast test run using current environment, use nose:

$ nosetests

For more thorough testing, Tox configuration will run tests on python versions 2.7 and 3.3 - 3.6:

$ tox

Additionally, test can be run with no local requirements other than the ubiquitous docker:

$ docker-compose up pgcopy

Benchmarks

Below are simple benchmarks for 100000 records. This gives a general idea of the kind of speedup available with pgcopy:

$ nosetests -c tests/benchmark.cfg
          ExecuteManyBenchmark:   7.75s
               PGCopyBenchmark:   0.54s
----------------------------------------------------------------------
Ran 2 tests in 9.101s

Replacing a Table

When possible, faster insertion may be realized by inserting into an empty table with no indices or constraints. In a case where the entire contents of the table can be reinserted, the Replace context manager automates the process. On entry, it creates a new table like the original, with a temporary name. Default column values are included. It provides the temporary name for populating the table within the context. On exit, it recreates the constraints, indices, triggers, and views on the new table, then replaces the old table with the new. It can be used so:

from pgcopy import CopyManager, Replace
with Replace(conn, 'mytable') as temp_name:
    mgr = CopyManager(conn, temp_name, cols)
    mgr.copy(records)

Replace renames new db objects like the old, where possible. Names of foreign key and check constraints will be mangled. As of v0.6 there is also pgcopy.util.RenameReplace, which instead of dropping the original objects renames them using a transformation function.

Note that on PostgreSQL 9.1 and earlier, concurrent queries on the table will fail once the table is dropped.

See Also

cpgcopy, a Cython implementation, about twice as fast.

Changelog

1.2.0

date:

25 Mar, 2017

• Support db schema (Thanks Marcin Gozdalik)

1.1.0

date:

26 Jan, 2017

• Support uuid, json, and jsonb types (Thanks Igor Mastak)

• Integrate Travis CI

• Add docker test strategy

1.0.0

date:

19 Jan, 2017

• Run tests with tox

• Support Python 3

• Initial release on PyPi

0.7

date:

19 Jan, 2017

• Add support for serializing Python decimal.Decimal to PostgreSQL numeric.

0.6

date:

21 Oct, 2014

• RenameReplace variant

0.5

date:

14 Jul, 2014

• Support default values and sequences

0.4

date:

14 Jul, 2014

• Fix Replace utility class bugs

• Add view support to Replace

0.3

date:

8 Jul, 2014

• Move Cython optimization to separate project

• Add Replace utility class

0.2

date:

7 Jul, 2014

• Cython optimization

0.1

date:

29 Jun, 2014

• Initial version