Facata

A Python library that provides a simplified alternative to DBAPI 2. It provides a facade in front of DBAPI 2 drivers.

Table of Contents

Installation
Examples For SQLite With SQLite3
Examples For PostgreSQL With pg8000
Examples For PostgreSQL With Psycopg2
Examples For MariaDB With MariaDb Driver
Examples For MySQL With MySQL Connector/Python
API Docs
Diferences From DBAPI 2
Testing
Doing A Release Of Facata
Release Notes

Installation

Create a virtual environment: python3 -m venv venv
Activate the virtual environment: source venv/bin/activate
Install: pip install facata

Examples For SQLite With SQLite3

Basic Example

Here’s an example of how to access an SQLite database. It uses the sqlite3 driver that comes with Python:

>> >>> # Create a temporary table >>> >>> con.run("CREATE TEMPORARY TABLE book (title TEXT)") >>> >>> # Populate the table >>> >>> for title in ("Ender's Game", "The Magus"): ... con.run("INSERT INTO book (title) VALUES (:title)", title=title) >>> >>> # Print all the rows in the table >>> >>> for row in con.run("SELECT * FROM book"): ... print(row) ("Ender's Game",) ('The Magus',)">

>>> import facata
>>>
>>> con = facata.connect("sqlite", "sqlite3", dbname=":memory:")
>>>
>>> # Create a temporary table
>>>
>>> con.run("CREATE TEMPORARY TABLE book (title TEXT)")
>>>
>>> # Populate the table
>>>
>>> for title in ("Ender's Game", "The Magus"):
...     con.run("INSERT INTO book (title) VALUES (:title)", title=title)
>>>
>>> # Print all the rows in the table
>>>
>>> for row in con.run("SELECT * FROM book"):
...     print(row)
("Ender's Game",)
('The Magus',)

Transactions

Here’s how to run groups of SQL statements in a transaction:

>>> import facata
>>>
>>> con = facata.connect("sqlite", "sqlite3", dbname=":memory:")
>>>
>>> con.run("BEGIN TRANSACTION")
>>> con.run("CREATE TEMPORARY TABLE book (title TEXT)")
>>> for title in ("Ender's Game", "The Magus", "Phineas Finn"):
...     con.run("INSERT INTO book (title) VALUES (:title)", title=title)
>>> con.run("COMMIT")
>>>
>>> for row in con.run("SELECT * FROM book"):
...     print(row)
("Ender's Game",)
('The Magus',)
('Phineas Finn',)

Rolling back a transaction:

>>> import facata
>>>
>>> con = facata.connect("sqlite", "sqlite3", dbname=":memory:")
>>>
>>> con.run("BEGIN TRANSACTION")
>>> con.run("CREATE TEMPORARY TABLE book (title TEXT)")
>>> for title in ("Ender's Game", "The Magus", "Phineas Finn"):
...     con.run("INSERT INTO book (title) VALUES (:title)", title=title)
>>> con.run("COMMIT")
>>>
>>> con.run("BEGIN TRANSACTION")
>>> con.run("DELETE FROM book WHERE title = :title", title="Phineas Finn")
>>> con.run("ROLLBACK")
>>>
>>> for row in con.run("SELECT * FROM book"):
...     print(row)
("Ender's Game",)
('The Magus',)
('Phineas Finn',)

Query Using Fuctions

Another query, using an SQLite function:

>> >>> con.run("SELECT datetime(1092941466, 'unixepoch');") [('2004-08-19 18:51:06',)]">

>>> import facata
>>>
>>> con = facata.connect("sqlite", "sqlite3",  dbname=":memory:")
>>>
>>> con.run("SELECT datetime(1092941466, 'unixepoch');")
[('2004-08-19 18:51:06',)]

Retrieve Column Metadata From Results

Find the column metadata returned from a query:

>> >>> con.run("create temporary table quark (spin text)") >>> for spin in ('Up', 'Down'): ... con.run("INSERT INTO quark (spin) VALUES (:spin)", spin=spin) >>> # Now execute the query >>> >>> con.run("SELECT * FROM quark") [('Up',), ('Down',)] >>> >>> # and read the metadata >>> >>> con.columns [{'name': 'spin', 'type_code': None, 'display_size': None, 'internal_size': None, 'precision': None, 'scale': None}] >>> >>> # Show just the column names >>> >>> [c['name'] for c in con.columns] ['spin']">

>>> import facata
>>>
>>> con = facata.connect("sqlite", "sqlite3", dbname=":memory:")
>>>
>>> con.run("create temporary table quark (spin text)")
>>> for spin in ('Up', 'Down'):
...     con.run("INSERT INTO quark (spin) VALUES (:spin)", spin=spin)
>>> # Now execute the query
>>>
>>> con.run("SELECT * FROM quark")
[('Up',), ('Down',)]
>>>
>>> # and read the metadata
>>>
>>> con.columns
[{'name': 'spin', 'type_code': None, 'display_size': None, 'internal_size': None, 'precision': None, 'scale': None}]
>>>
>>> # Show just the column names
>>>
>>> [c['name'] for c in con.columns]
['spin']

Many SQL Statements Can’t Be Parameterized

In SQLite parameters can only be used for data values. Sometimes this might not work as expected, for example the following fails:

>> >>> con.run("SELECT 'silo 1' LIMIT :lim", lim='ALL') Traceback (most recent call last): sqlite3.IntegrityError: datatype mismatch">

>>> import facata
>>>
>>> con = facata.connect("sqlite", "sqlite3", dbname=":memory:")
>>>
>>> con.run("SELECT 'silo 1' LIMIT :lim", lim='ALL')
Traceback (most recent call last):
sqlite3.IntegrityError: datatype mismatch

You might think that the following would work, but in fact the server doesn’t like it:

>> >>> con.run("SELECT 'silo 1' WHERE 'a' IN :v", v=('a', 'b')) Traceback (most recent call last): sqlite3.OperationalError: near ":v": syntax error">

>>> import facata
>>>
>>> con = facata.connect("sqlite", "sqlite3", dbname=":memory:")
>>>
>>> con.run("SELECT 'silo 1' WHERE 'a' IN :v", v=('a', 'b'))
Traceback (most recent call last):
sqlite3.OperationalError: near ":v": syntax error

Execute SQL Scripts

If you want to execute a series of SQL statements (eg. an .sql file), with SQLite you need to access the the underlying connection with and use SQLite3’s executescript() method:

>>
>>> statements = """
...     CREATE TEMPORARY TABLE quark (spin text);
...     INSERT INTO quark (spin) VALUES ('Up');
...     INSERT INTO quark (spin) VALUES ('Down');"""
>>>
>>> con.connection.executescript(statements)

>>> con.run("SELECT * FROM quark")
[('Up',), ('Down',)]">
      >>> import facata
>>>
>>> con = facata.connect("sqlite", "sqlite3", dbname=":memory:")
>>>
>>> statements = """
...     CREATE TEMPORARY TABLE quark (spin text);
...     INSERT INTO quark (spin) VALUES ('Up');
...     INSERT INTO quark (spin) VALUES ('Down');"""
>>>
>>> con.connection.executescript(statements)
<sqlite3.Cursor object at ...>
>>> con.run("SELECT * FROM quark")
[('Up',), ('Down',)]
     

A caveat is that when executing scripts you can’t have any parameters.

Quoted Identifiers in SQL

Say you had a column called My Column. Since it’s case sensitive and contains a space, you’d have to surround it by double quotes. But you can’t do:

>> >>> con.run("select 'hello' as "My Column"") Traceback (most recent call last): SyntaxError: invalid syntax">

>>> import facata
>>>
>>> con = facata.connect("sqlite", "sqlite3", dbname=":memory:")
>>>
>>> con.run("select 'hello' as "My Column"")
Traceback (most recent call last):
SyntaxError: invalid syntax

since Python uses double quotes to delimit string literals, so one solution is to use Python’s triple quotes to delimit the string instead:

>> >>> con.run('''select 'hello' as "My Column"''') [('hello',)]">

>>> import facata
>>>
>>> con = facata.connect("sqlite", "sqlite3", dbname=":memory:")
>>>
>>> con.run('''select 'hello' as "My Column"''')
[('hello',)]

Custom Adapter From A Python Type To An SQLite Type

Sqlite3 has a mapping from Python types to PostgreSQL types for when it needs to send SQL parameters to the server. The default mapping that comes with SQLite is fairly limited, but you can add custom conversions with an adapter.

By default, a Python decimal.Decimal object can’t be used as a parameter but here’s an example of how to register an adapter for it:

>> >>> def decimal_py_to_db(dec): ... return str(dec) # Must return int, float, str or bytes >>> >>> con.register_py_to_db(Decimal, None, decimal_py_to_db) >>> >>> con.run("SELECT :val", val=Decimal('0.1')) [('0.1',)]">

>>> from decimal import Decimal
>>> import facata
>>>
>>> con = facata.connect("sqlite", "sqlite3", dbname=":memory:")
>>>
>>> def decimal_py_to_db(dec):
...     return str(dec)  # Must return int, float, str or bytes
>>>
>>> con.register_py_to_db(Decimal, None, decimal_py_to_db)
>>>
>>> con.run("SELECT :val", val=Decimal('0.1'))
[('0.1',)]

Note that it still came back as a str object because we only changed the mapping from Python to SQLite. See below for an example of how to change the mapping from SQLite to Python.

Custom Adapter From An SQLite Type To A Python Type

SQLite3 has a mapping from SQLite types to Python types for when it receives SQL results from the server. With a custom adapter you can add a new mapping or replace the default mapping. Here’s an example:

>> >>> def decimal_db_to_py(data): # The parameter is of type bytes ... return Decimal(data.decode('ascii')) >>> >>> con.register_db_to_py('decimal', decimal_db_to_py) >>> >>> con.run("CREATE TEMPORARY TABLE book (title TEXT, price decimal)") >>> con.run( ... "INSERT INTO book (title, price) VALUES (:title, :price)", ... title="The Island", price='7.99') >>> >>> con.run("SELECT * FROM book") [('The Island', Decimal('7.99'))]">

>>> from decimal import Decimal
>>> import sqlite3
>>> import facata
>>>
>>> con = facata.connect(
...     "sqlite", "sqlite3", dbname=":memory:", detect_types=sqlite3.PARSE_DECLTYPES)
>>>
>>> def decimal_db_to_py(data):  # The parameter is of type bytes
...     return Decimal(data.decode('ascii'))
>>>
>>> con.register_db_to_py('decimal', decimal_db_to_py)
>>>
>>> con.run("CREATE TEMPORARY TABLE book (title TEXT, price decimal)")
>>> con.run(
...     "INSERT INTO book (title, price) VALUES (:title, :price)",
...     title="The Island", price='7.99')
>>>
>>> con.run("SELECT * FROM book")
[('The Island', Decimal('7.99'))]

Note that registering the 'db to py' adapter only afected the mapping from the SQLite type to the Python type. See above for an example of how to change the mapping from Python to SQLite.

Examples For PostgreSQL With pg8000

Connecting To A Database

Connecting to PostgreSQL with the pg8000 driver requires the dependency pg8000 to be installed by doing pip install facata[pg8000]. Then connect to a database as follows:

>>> import facata
>>>
>>> with facata.connect("postgresql", "pg8000", user="postgres", password="pw") as con:
...     con.run("SELECT 'Hello'")
[['Hello']]

Basic Example

Import facacta, connect to the database, create a table, add some rows and then query the table:

>> >>> # Create a temporary table >>> >>> con.run("CREATE TEMPORARY TABLE book (id SERIAL, title TEXT)") >>> >>> # Populate the table >>> >>> for title in ("Ender's Game", "The Magus"): ... con.run("INSERT INTO book (title) VALUES (:title)", title=title) >>> >>> # Print all the rows in the table >>> >>> for row in con.run("SELECT * FROM book"): ... print(row) [1, "Ender's Game"] [2, 'The Magus']">

>>> import facata
>>>
>>> # Connect to the database with user name postgres
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> # Create a temporary table
>>>
>>> con.run("CREATE TEMPORARY TABLE book (id SERIAL, title TEXT)")
>>>
>>> # Populate the table
>>>
>>> for title in ("Ender's Game", "The Magus"):
...     con.run("INSERT INTO book (title) VALUES (:title)", title=title)
>>>
>>> # Print all the rows in the table
>>>
>>> for row in con.run("SELECT * FROM book"):
...     print(row)
[1, "Ender's Game"]
[2, 'The Magus']

Transactions

Here’s how to run groups of SQL statements in a transaction:

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> con.run("START TRANSACTION")
>>>
>>> # Create a temporary table
>>> con.run("CREATE TEMPORARY TABLE book (id SERIAL, title TEXT)")
>>>
>>> for title in ("Ender's Game", "The Magus", "Phineas Finn"):
...     con.run("INSERT INTO book (title) VALUES (:title)", title=title)
>>>
>>> con.run("COMMIT")
>>>
>>> for row in con.run("SELECT * FROM book"):
...     print(row)
[1, "Ender's Game"]
[2, 'The Magus']
[3, 'Phineas Finn']

rolling back a transaction:

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> # Create a temporary table
>>> con.run("CREATE TEMPORARY TABLE book (id SERIAL, title TEXT)")
>>>
>>> for title in ("Ender's Game", "The Magus", "Phineas Finn"):
...     con.run("INSERT INTO book (title) VALUES (:title)", title=title)
>>>
>>> con.run("START TRANSACTION")
>>>
>>> con.run("DELETE FROM book WHERE title = :title", title="Phineas Finn")
>>>
>>> con.run("ROLLBACK")
>>>
>>> for row in con.run("SELECT * FROM book"):
...     print(row)
[1, "Ender's Game"]
[2, 'The Magus']
[3, 'Phineas Finn']

Query Using Fuctions

Another query, using some PostgreSQL functions:

>> >>> con.run("SELECT extract(millennium from now())") [[3.0]]">

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> con.run("SELECT extract(millennium from now())")
[[3.0]]

Interval Type

A query that returns the PostgreSQL interval type:

>> >>> ts = datetime.date(1980, 4, 27) >>> con.run("SELECT timestamp '2013-12-01 16:06' - :ts", ts=ts) [[datetime.timedelta(days=12271, seconds=57960)]]">

>>> import datetime
>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> ts = datetime.date(1980, 4, 27)
>>> con.run("SELECT timestamp '2013-12-01 16:06' - :ts", ts=ts)
[[datetime.timedelta(days=12271, seconds=57960)]]

Point Type

A round-trip with a PostgreSQL point type:

>> >>> con.run("SELECT CAST(:pt as point)", pt='(2.3,1)') [['(2.3,1)']]">

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> con.run("SELECT CAST(:pt as point)", pt='(2.3,1)')
[['(2.3,1)']]

Client Encoding

When communicating with the server, pg8000 uses the character set that the server asks it to use (the client encoding). By default the client encoding is the database’s character set (chosen when the database is created), but the client encoding can be changed in a number of ways (eg. setting CLIENT_ENCODING in postgresql.conf). Another way of changing the client encoding is by using an SQL command. For example:

>> >>> con.run("SET CLIENT_ENCODING TO 'UTF8'") >>> >>> con.run("SHOW CLIENT_ENCODING") [['UTF8']]">

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> con.run("SET CLIENT_ENCODING TO 'UTF8'")
>>>
>>> con.run("SHOW CLIENT_ENCODING")
[['UTF8']]

JSON

JSON always comes back from the server de-serialized. If the JSON you want to send is a dict then you can just do:

>> >>> val = {'name': 'Apollo 11 Cave', 'zebra': True, 'age': 26.003} >>> con.run("SELECT :apollo", apollo=val) [[{'age': 26.003, 'name': 'Apollo 11 Cave', 'zebra': True}]]">

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> val = {'name': 'Apollo 11 Cave', 'zebra': True, 'age': 26.003}
>>> con.run("SELECT :apollo", apollo=val)
[[{'age': 26.003, 'name': 'Apollo 11 Cave', 'zebra': True}]]

JSON can always be sent in serialized form to the server:

>> >>> val = ['Apollo 11 Cave', True, 26.003] >>> con.run("SELECT CAST(:apollo as jsonb)", apollo=json.dumps(val)) [[['Apollo 11 Cave', True, 26.003]]]">

>>> import json
>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> val = ['Apollo 11 Cave', True, 26.003]
>>> con.run("SELECT CAST(:apollo as jsonb)", apollo=json.dumps(val))
[[['Apollo 11 Cave', True, 26.003]]]

Retrieve Column Metadata From Results

Find the column metadata returned from a query:

>> >>> con.run("create temporary table quark (id serial, name text)") >>> >>> for name in ('Up', 'Down'): ... con.run("INSERT INTO quark (name) VALUES (:name)", name=name) >>> >>> # Now execute the query >>> >>> con.run("SELECT * FROM quark") [[1, 'Up'], [2, 'Down']] >>> >>> # and retried the metadata >>> >>> con.columns [{'table_oid': ..., 'column_attrnum': 1, 'type_oid': 23, 'type_size': 4, 'type_modifier': -1, 'format': 0, 'name': 'id'}, {'table_oid': ..., 'column_attrnum': 2, 'type_oid': 25, 'type_size': -1, 'type_modifier': -1, 'format': 0, 'name': 'name'}] >>> >>> # Show just the column names >>> >>> [c['name'] for c in con.columns] ['id', 'name']">

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> con.run("create temporary table quark (id serial, name text)")
>>>
>>> for name in ('Up', 'Down'):
...     con.run("INSERT INTO quark (name) VALUES (:name)", name=name)
>>>
>>> # Now execute the query
>>>
>>> con.run("SELECT * FROM quark")
[[1, 'Up'], [2, 'Down']]
>>>
>>> # and retried the metadata
>>>
>>> con.columns
[{'table_oid': ..., 'column_attrnum': 1, 'type_oid': 23, 'type_size': 4, 'type_modifier': -1, 'format': 0, 'name': 'id'}, {'table_oid': ..., 'column_attrnum': 2, 'type_oid': 25, 'type_size': -1, 'type_modifier': -1, 'format': 0, 'name': 'name'}]
>>>
>>> # Show just the column names
>>>
>>> [c['name'] for c in con.columns]
['id', 'name']

Notices, Notifications And Parameter Statuses

To access the PostgreSQL notices you need to obtain the underlying pg8000 connection. The notices are stored in a deque called Connection.notices and added using the append() method. Similarly there are Connection.notifications for notifications and Connection.parameter_statuses for changes to the server configuration. Here’s an example:

>> >>> con.run("LISTEN aliens_landed") >>> con.run("NOTIFY aliens_landed") >>> >>> # A notification is a tuple containing (backend_pid, channel, payload) >>> >>> con.connection.notifications[0] (..., 'aliens_landed', '')">

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> con.run("LISTEN aliens_landed")
>>> con.run("NOTIFY aliens_landed")
>>>
>>> # A notification is a tuple containing (backend_pid, channel, payload)
>>>
>>> con.connection.notifications[0]
(..., 'aliens_landed', '')

LIMIT ALL

You might think that the following would work, but in fact it fails:

>> >>> con.run("SELECT 'silo 1' LIMIT :lim", lim='ALL') Traceback (most recent call last): pg8000.exceptions.DatabaseError: ...">

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> con.run("SELECT 'silo 1' LIMIT :lim", lim='ALL')
Traceback (most recent call last):
pg8000.exceptions.DatabaseError: ...

Instead the docs say that you can send null as an alternative to ALL, which does work:

>> >>> con.run("SELECT 'silo 1' LIMIT :lim", lim=None) [['silo 1']]">

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> con.run("SELECT 'silo 1' LIMIT :lim", lim=None)
[['silo 1']]

IN and NOT IN

You might think that the following would work, but in fact the server doesn’t like it:

>> >>> con.run("SELECT 'silo 1' WHERE 'a' IN :v", v=('a', 'b')) Traceback (most recent call last): pg8000.exceptions.DatabaseError: ...">

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> con.run("SELECT 'silo 1' WHERE 'a' IN :v", v=('a', 'b'))
Traceback (most recent call last):
pg8000.exceptions.DatabaseError: ...

instead you can write it using the unnest function:

>> >>> con.run("SELECT 'silo 1' WHERE 'a' IN (SELECT unnest(:v))", v=('a', 'b')) [['silo 1']]">

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> con.run("SELECT 'silo 1' WHERE 'a' IN (SELECT unnest(:v))", v=('a', 'b'))
[['silo 1']]

and you can do the same for NOT IN.

Many SQL Statements Can’t Be Parameterized

In PostgreSQL parameters can only be used for data values, not identifiers. Sometimes this might not work as expected, for example the following fails:

>> >>> con.run("CREATE USER juan WITH PASSWORD :password", password='quail') Traceback (most recent call last): pg8000.exceptions.DatabaseError: ...">

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> con.run("CREATE USER juan WITH PASSWORD :password", password='quail')
Traceback (most recent call last):
pg8000.exceptions.DatabaseError: ...

It fails because the PostgreSQL server doesn’t allow this statement to have any parameters. There are many SQL statements that one might think would have parameters, but don’t.

COPY From And To A File

The SQL COPY statement can be used to copy from and to a file or file-like object. First we need to obtain the underlying pg8000 connection. Here' an example using the CSV format:

>> connection = con.connection >>> >>> # Create a CSV file in memory >>> >>> stream_in = StringIO() >>> csv_writer = csv.writer(stream_in) >>> csv_writer.writerow([1, "electron"]) 12 >>> csv_writer.writerow([2, "muon"]) 8 >>> csv_writer.writerow([3, "tau"]) 7 >>> stream_in.seek(0) 0 >>> >>> # Create a table and then copy the CSV into it >>> >>> connection.run("CREATE TEMPORARY TABLE lepton (id SERIAL, name TEXT)") >>> >>> connection.run("COPY lepton FROM STDIN WITH (FORMAT CSV)", stream=stream_in) >>> >>> # COPY from a table to a stream >>> >>> stream_out = StringIO() >>> connection.run("COPY lepton TO STDOUT WITH (FORMAT CSV)", stream=stream_out) >>> stream_out.seek(0) 0 >>> for row in csv.reader(stream_out): ... print(row) ['1', 'electron'] ['2', 'muon'] ['3', 'tau']">

>>> from io import StringIO
>>> import csv
>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>> connection = con.connection
>>>
>>> # Create a CSV file in memory
>>>
>>> stream_in = StringIO()
>>> csv_writer = csv.writer(stream_in)
>>> csv_writer.writerow([1, "electron"])
12
>>> csv_writer.writerow([2, "muon"])
8
>>> csv_writer.writerow([3, "tau"])
7
>>> stream_in.seek(0)
0
>>>
>>> # Create a table and then copy the CSV into it
>>>
>>> connection.run("CREATE TEMPORARY TABLE lepton (id SERIAL, name TEXT)")
>>>
>>> connection.run("COPY lepton FROM STDIN WITH (FORMAT CSV)", stream=stream_in)
>>>
>>> # COPY from a table to a stream
>>>
>>> stream_out = StringIO()
>>> connection.run("COPY lepton TO STDOUT WITH (FORMAT CSV)", stream=stream_out)
>>> stream_out.seek(0)
0
>>> for row in csv.reader(stream_out):
...     print(row)
['1', 'electron']
['2', 'muon']
['3', 'tau']

Execute Multiple SQL Statements

If you want to execute a series of SQL statements (eg. an .sql file), you can run them as expected:

>> >>> statements = "SELECT 5; SELECT 'Erich Fromm';" >>> >>> con.run(statements) [[5], ['Erich Fromm']]">

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> statements = "SELECT 5; SELECT 'Erich Fromm';"
>>>
>>> con.run(statements)
[[5], ['Erich Fromm']]

The only caveat is that when executing multiple statements you can’t have any parameters.

Quoted Identifiers in SQL

Say you had a column called My Column. Since it’s case sensitive and contains a space, you’d have to surround it by double quotes. But you can’t do:

>> >>> con.run("select 'hello' as "My Column"") Traceback (most recent call last): SyntaxError: invalid syntax">

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> con.run("select 'hello' as "My Column"")
Traceback (most recent call last):
SyntaxError: invalid syntax

since Python uses double quotes to delimit string literals, so one solution is to use Python’s triple quotes to delimit the string instead:

>> >>> con.run('''select 'hello' as "My Column"''') [['hello']]">

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> con.run('''select 'hello' as "My Column"''')
[['hello']]

Custom Adapter From A Python Type To A PostgreSQL Type

pg8000 has a mapping from Python types to PostgreSQL types for when it needs to send SQL parameters to the server. The default mapping that comes with pg8000 is designed to work well in most cases, but you might want to add or replace the default mapping.

A Python datetime.timedelta object is sent to the server as a PostgreSQL interval type, which has the oid 1186. But let’s say we wanted to create our own Python class to be sent as an interval type. Then we’d have to register an adapter:

>> >>> class MyInterval(str): ... pass >>> >>> def my_interval_py_to_db(my_interval): ... return my_interval # Must return a str >>> >>> con.register_py_to_db(MyInterval, 1186, my_interval_py_to_db) >>> con.run("SELECT :interval", interval=MyInterval("2 hours")) [[datetime.timedelta(seconds=7200)]]">

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> class MyInterval(str):
...     pass
>>>
>>> def my_interval_py_to_db(my_interval):
...     return my_interval  # Must return a str
>>>
>>> con.register_py_to_db(MyInterval, 1186, my_interval_py_to_db)
>>> con.run("SELECT :interval", interval=MyInterval("2 hours"))
[[datetime.timedelta(seconds=7200)]]

Note that it still came back as a datetime.timedelta object because we only changed the mapping from Python to PostgreSQL. See below for an example of how to change the mapping from PostgreSQL to Python.

Custom adapter from a PostgreSQL type to a Python type

pg8000 has a mapping from PostgreSQL types to Python types for when it receives SQL results from the server. The default mapping that comes with pg8000 is designed to work well in most cases, but you might want to add or replace the default mapping.

If pg800 recieves PostgreSQL interval type, which has the oid 1186, it converts it into a Python datetime.timedelta object. But let’s say we wanted to create our own Python class to be used instead of datetime.timedelta. Then we’d have to register an adapter:

>> >>> class MyInterval(str): ... pass >>> >>> def my_interval_db_to_py(my_interval_str): # The parameter is of type str ... return MyInterval(my_interval) >>> >>> con.register_db_to_py(1186, my_interval_db_to_py) >>> con.run("SELECT \'2 years'") [['2 years']]">

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> class MyInterval(str):
...     pass
>>>
>>> def my_interval_db_to_py(my_interval_str):  # The parameter is of type str
...     return MyInterval(my_interval)
>>>
>>> con.register_db_to_py(1186, my_interval_db_to_py)
>>> con.run("SELECT \'2 years'")
[['2 years']]

Note that registering the 'in' adapter only afects the mapping from the PostgreSQL type to the Python type. See above for an example of how to change the mapping from PostgreSQL to Python.

Could Not Determine Data Type Of Parameter

Sometimes you’ll get the 'could not determine data type of parameter' error message from the server:

>> >>> con.run("SELECT :v IS NULL", v=None) Traceback (most recent call last): pg8000.exceptions.DatabaseError: {'S': 'ERROR', 'V': 'ERROR', 'C': '42P18', 'M': 'could not determine data type of parameter $1', 'F': 'postgres.c', 'L': '...', 'R': 'exec_parse_message'}">

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> con.run("SELECT :v IS NULL", v=None)
Traceback (most recent call last):
pg8000.exceptions.DatabaseError: {'S': 'ERROR', 'V': 'ERROR', 'C': '42P18', 'M': 'could not determine data type of parameter $1', 'F': 'postgres.c', 'L': '...', 'R': 'exec_parse_message'}

One way of solving it is to put a cast in the SQL:

>> >>> con.run("SELECT cast(:v as TIMESTAMP) IS NULL", v=None) [[True]]">

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> con.run("SELECT cast(:v as TIMESTAMP) IS NULL", v=None)
[[True]]

Another way is to override the type that pg8000 sends along with each parameter:

>> >>> con.run("SELECT :v IS NULL", v=None, types={'v': pg8000.native.TIMESTAMP}) [[True]]">

>>> import facata
>>> import pg8000.native
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> con.run("SELECT :v IS NULL", v=None, types={'v': pg8000.native.TIMESTAMP})
[[True]]

Prepared Statements

Prepared statements can be useful in improving performance when you have a statement that’s executed repeatedly. Here’s an example:

>> >>> # Create the prepared statement >>> ps = con.prepare("SELECT cast(:v as varchar)") >>> >>> # Exceute the statement repeatedly >>> ps.run(v="speedy") [['speedy']] >>> ps.run(v="rapid") [['rapid']] >>> ps.run(v="swift") [['swift']] >>> >>> # Close the prepared statement, releasing resources on the server >>> ps.close()">

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> # Create the prepared statement
>>> ps = con.prepare("SELECT cast(:v as varchar)")
>>>
>>> # Exceute the statement repeatedly
>>> ps.run(v="speedy")
[['speedy']]
>>> ps.run(v="rapid")
[['rapid']]
>>> ps.run(v="swift")
[['swift']]
>>>
>>> # Close the prepared statement, releasing resources on the server
>>> ps.close()

Use Environment Variables As Connection Defaults

You might want to use the current user as the database username for example:

import getpass
import facata

# Connect to the database with current user name
user = getpass.getuser()
conection = facata.connect("postgresql", "pg8000", user=user, password="pw")

connection.run("SELECT 'pilau'")

or perhaps you may want to use some of the same environment variables that libpq uses:

>> >>> connection.run("SELECT 'Mr Cairo'") [['Mr Cairo']]">

>>> import facata
>>> from os import environ
>>>
>>> user = environ.get('PGUSER', 'postgres')
>>> password = environ.get('PGPASSWORD', 'pw')
>>> host = environ.get('PGHOST', 'localhost')
>>> port = environ.get('PGPORT', '5432')
>>> dbname = environ.get('PGDATABASE')
>>>
>>> conection = facata.connect(
...    "postgresql", "pg8000", user=user, password=password, host=host, port=port,
...    dbname=dbname)
>>>
>>> connection.run("SELECT 'Mr Cairo'")
[['Mr Cairo']]

It might be asked, why doesn’t Facata have this behaviour built in? The thinking follows the second aphorism of The Zen of Python:

Explicit is better than implicit.

So we’ve taken the approach of only being able to set connection parameters using the facata.connect() function.

Connect To PostgreSQL Over SSL

To connect to the server using SSL defaults do:

from facata import connect


connection = connect(
    "postgresql", "pg8000", user="postgres", password="cpsnow", ssl_context=True)
connection.run("SELECT 'The game is afoot!'")

To connect over SSL with custom settings, set the ssl_context parameter to an ssl.SSLContext object:

from facata import connect
import ssl


ssl_context = ssl.SSLContext()
ssl_context.verify_mode = ssl.CERT_REQUIRED
ssl_context.load_verify_locations('root.pem')
connection = connect(
    "postgresql", "pg8000", user="postgres", password="cpsnow", ssl_context=ssl_context)

It may be that your PostgreSQL server is behind an SSL proxy server in which case you can set a pg8000-specific attribute ssl.SSLContext.request_ssl = False which tells pg8000 to connect using an SSL socket, but not to request SSL from the PostgreSQL server:

from facata import connect
import ssl


ssl_context = ssl.SSLContext()
ssl_context.request_ssl = False
connection = connect(
    "postgresql", "pg8000", user="postgres", password="cpsnow", ssl_context=ssl_context)

Server-Side Cursors

You can use the SQL commands DECLARE, FETCH, MOVE and CLOSE to manipulate server-side cursors. For example:

>> >>> con.run("START TRANSACTION") >>> con.run("DECLARE c SCROLL CURSOR FOR SELECT * FROM generate_series(1, 100)") >>> con.run("FETCH FORWARD 5 FROM c") [[1], [2], [3], [4], [5]] >>> >>> con.run("MOVE FORWARD 50 FROM c") >>> con.run("FETCH BACKWARD 10 FROM c") [[54], [53], [52], [51], [50], [49], [48], [47], [46], [45]] >>> >>> con.run("CLOSE c") >>> con.run("ROLLBACK")">

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> con.run("START TRANSACTION")
>>> con.run("DECLARE c SCROLL CURSOR FOR SELECT * FROM generate_series(1, 100)")
>>> con.run("FETCH FORWARD 5 FROM c")
[[1], [2], [3], [4], [5]]
>>>
>>> con.run("MOVE FORWARD 50 FROM c")
>>> con.run("FETCH BACKWARD 10 FROM c")
[[54], [53], [52], [51], [50], [49], [48], [47], [46], [45]]
>>>
>>> con.run("CLOSE c")
>>> con.run("ROLLBACK")

BLOBs (Binary Large Objects)

There’s a set of SQL functions for manipulating BLOBs. Here’s an example:

>> >>> # Create a BLOB and get its oid >>> data = b'hello' >>> res = con.run("SELECT lo_from_bytea(0, :data)", data=data) >>> oid = res[0][0] >>> >>> # Create a table and store the oid of the BLOB >>> con.run("CREATE TEMPORARY TABLE image (raster oid)") >>> con.run("INSERT INTO image (raster) VALUES (:oid)", oid=oid) >>> # Retrieve the data using the oid >>> con.run("SELECT lo_get(:oid)", oid=oid) [[b'hello']] >>> >>> # Add some data to the end of the BLOB >>> more_data = b' all' >>> offset = len(data) >>> con.run( ... "SELECT lo_put(:oid, :offset, :data)", ... oid=oid, offset=offset, data=more_data) [['']] >>> con.run("SELECT lo_get(:oid)", oid=oid) [[b'hello all']] >>> >>> # Download a part of the data >>> con.run("SELECT lo_get(:oid, 6, 3)", oid=oid) [[b'all']]">

>>> import facata
>>>
>>> con = facata.connect("postgresql", "pg8000", user="postgres", password="pw")
>>>
>>> # Create a BLOB and get its oid
>>> data = b'hello'
>>> res = con.run("SELECT lo_from_bytea(0, :data)", data=data)
>>> oid = res[0][0]
>>>
>>> # Create a table and store the oid of the BLOB
>>> con.run("CREATE TEMPORARY TABLE image (raster oid)")
>>> con.run("INSERT INTO image (raster) VALUES (:oid)", oid=oid)
>>> # Retrieve the data using the oid
>>> con.run("SELECT lo_get(:oid)", oid=oid)
[[b'hello']]
>>>
>>> # Add some data to the end of the BLOB
>>> more_data = b' all'
>>> offset = len(data)
>>> con.run(
...     "SELECT lo_put(:oid, :offset, :data)",
...     oid=oid, offset=offset, data=more_data)
[['']]
>>> con.run("SELECT lo_get(:oid)", oid=oid)
[[b'hello all']]
>>>
>>> # Download a part of the data
>>> con.run("SELECT lo_get(:oid, 6, 3)", oid=oid)
[[b'all']]

Examples For PostgreSQL With Psycopg2

Connecting To A Database

Connecting to PostgreSQL with the psycopg2 driver requires the dependency psycopg2 to be installed by doing pip install facata[psycopg2]. This will install the binary version, but for production use see the psycopg installation docs. Then connect to a database as follows:

>>> import facata
>>>
>>> with facata.connect(
...         "postgresql", "psycopg2", user="postgres", password="pw",
...         host="localhost") as con:
...     con.run("SELECT 'Hello'")
[('Hello',)]

Basic Example

Import facacta, connect to the database, create a table, add some rows and then query the table:

>>> import facata
>>>
>>> # Connect to the database with user name postgres
>>>
>>> con = facata.connect(
...     "postgresql", "psycopg2", user="postgres", password="pw", host="localhost")
>>>
>>> # Create a temporary table
>>>
>>> con.run("CREATE TEMPORARY TABLE book (id SERIAL, title TEXT)")
>>>
>>> # Populate the table
>>>
>>> for title in ("Ender's Game", "The Magus"):
...     con.run("INSERT INTO book (title) VALUES (:title)", title=title)
>>>
>>> # Print all the rows in the table
>>>
>>> for row in con.run("SELECT * FROM book"):
...     print(row)
(1, "Ender's Game")
(2, 'The Magus')

Transactions

Here’s how to run groups of SQL statements in a transaction:

>>> import facata
>>>
>>> con = facata.connect(
...     "postgresql", "psycopg2", user="postgres", password="pw", host="localhost")
>>>
>>> con.run("START TRANSACTION")
>>>
>>> # Create a temporary table
>>> con.run("CREATE TEMPORARY TABLE book (id SERIAL, title TEXT)")
>>>
>>> for title in ("Ender's Game", "The Magus", "Phineas Finn"):
...     con.run("INSERT INTO book (title) VALUES (:title)", title=title)
>>>
>>> con.run("COMMIT")
>>>
>>> for row in con.run("SELECT * FROM book"):
...     print(row)
(1, "Ender's Game")
(2, 'The Magus')
(3, 'Phineas Finn')

rolling back a transaction:

>>> import facata
>>>
>>> con = facata.connect(
...     "postgresql", "psycopg2", user="postgres", password="pw", host="localhost")
>>>
>>> # Create a temporary table
>>> con.run("CREATE TEMPORARY TABLE book (id SERIAL, title TEXT)")
>>>
>>> for title in ("Ender's Game", "The Magus", "Phineas Finn"):
...     con.run("INSERT INTO book (title) VALUES (:title)", title=title)
>>>
>>> con.run("START TRANSACTION")
>>>
>>> con.run("DELETE FROM book WHERE title = :title", title="Phineas Finn")
>>>
>>> con.run("ROLLBACK")
>>>
>>> for row in con.run("SELECT * FROM book"):
...     print(row)
(1, "Ender's Game")
(2, 'The Magus')
(3, 'Phineas Finn')

Query Using Fuctions

Another query, using some PostgreSQL functions:

>> >>> con.run("SELECT extract(millennium from now())") [(3.0,)]">

>>> import facata
>>>
>>> con = facata.connect(
...     "postgresql", "psycopg2", user="postgres", password="pw", host="localhost")
>>>
>>> con.run("SELECT extract(millennium from now())")
[(3.0,)]

Interval Type

A query that returns the PostgreSQL interval type:

>> >>> ts = datetime.date(1980, 4, 27) >>> con.run("SELECT timestamp '2013-12-01 16:06' - :ts", ts=ts) [(datetime.timedelta(days=12271, seconds=57960),)]">

>>> import datetime
>>> import facata
>>>
>>> con = facata.connect(
...     "postgresql", "psycopg2", user="postgres", password="pw", host="localhost")
>>>
>>> ts = datetime.date(1980, 4, 27)
>>> con.run("SELECT timestamp '2013-12-01 16:06' - :ts", ts=ts)
[(datetime.timedelta(days=12271, seconds=57960),)]

Point Type

A round-trip with a PostgreSQL point type:

>> >>> con.run("SELECT CAST(:pt as point)", pt='(2.3,1)') [('(2.3,1)',)]">

>>> import facata
>>>
>>> con = facata.connect(
...     "postgresql", "psycopg2", user="postgres", password="pw", host="localhost")
>>>
>>> con.run("SELECT CAST(:pt as point)", pt='(2.3,1)')
[('(2.3,1)',)]

Client Encoding

When communicating with the server, psycopg2 uses the character set that the server asks it to use (the client encoding). By default the client encoding is the database’s character set (chosen when the database is created), but the client encoding can be changed in a number of ways (eg. setting CLIENT_ENCODING in postgresql.conf). Another way of changing the client encoding is by using an SQL command. For example:

>> >>> con.run("SET CLIENT_ENCODING TO 'UTF8'") >>> >>> con.run("SHOW CLIENT_ENCODING") [('UTF8',)]">

>>> import facata
>>>
>>> con = facata.connect(
...     "postgresql", "psycopg2", user="postgres", password="pw", host="localhost")
>>>
>>> con.run("SET CLIENT_ENCODING TO 'UTF8'")
>>>
>>> con.run("SHOW CLIENT_ENCODING")
[('UTF8',)]

Retrieve Column Metadata From Results

Find the column metadata returned from a query:

>> >>> con.run("create temporary table quark (id serial, name text)") >>> >>> for name in ('Up', 'Down'): ... con.run("INSERT INTO quark (name) VALUES (:name)", name=name) >>> >>> # Now execute the query >>> >>> con.run("SELECT * FROM quark") [(1, 'Up'), (2, 'Down')] >>> >>> # and retried the metadata >>> >>> con.columns [{'name': 'id', 'type_code': 23, 'display_size': None, 'internal_size': 4, 'precision': None, 'scale': None}, {'name': 'name', 'type_code': 25, 'display_size': None, 'internal_size': -1, 'precision': None, 'scale': None}] >>> >>> # Show just the column names >>> >>> [c['name'] for c in con.columns] ['id', 'name']">

>>> import facata
>>>
>>> con = facata.connect(
...     "postgresql", "psycopg2", user="postgres", password="pw", host="localhost")
>>>
>>> con.run("create temporary table quark (id serial, name text)")
>>>
>>> for name in ('Up', 'Down'):
...     con.run("INSERT INTO quark (name) VALUES (:name)", name=name)
>>>
>>> # Now execute the query
>>>
>>> con.run("SELECT * FROM quark")
[(1, 'Up'), (2, 'Down')]
>>>
>>> # and retried the metadata
>>>
>>> con.columns
[{'name': 'id', 'type_code': 23, 'display_size': None, 'internal_size': 4, 'precision': None, 'scale': None}, {'name': 'name', 'type_code': 25, 'display_size': None, 'internal_size': -1, 'precision': None, 'scale': None}]
>>>
>>> # Show just the column names
>>>
>>> [c['name'] for c in con.columns]
['id', 'name']

Notices, Notifications And Parameter Statuses

>> >>> con.run("LISTEN aliens_landed") >>> con.run("NOTIFY aliens_landed") >>> >>> # A notification is a tuple containing (backend_pid, channel, payload) >>> >>> connection = con.connection >>> connection.notifies[0] Notify(..., 'aliens_landed', '')">

>>> import facata
>>>
>>> con = facata.connect(
...     "postgresql", "psycopg2", user="postgres", password="pw", host="localhost")
>>>
>>> con.run("LISTEN aliens_landed")
>>> con.run("NOTIFY aliens_landed")
>>>
>>> # A notification is a tuple containing (backend_pid, channel, payload)
>>>
>>> connection = con.connection
>>> connection.notifies[0]
Notify(..., 'aliens_landed', '')

LIMIT ALL

You might think that the following would work, but in fact it fails:

>> >>> con.run("SELECT 'silo 1' LIMIT :lim", lim='ALL') Traceback (most recent call last): psycopg2.errors.InvalidTextRepresentation: ...">

>>> import facata
>>>
>>> con = facata.connect(
...     "postgresql", "psycopg2", user="postgres", password="pw", host="localhost")
>>>
>>> con.run("SELECT 'silo 1' LIMIT :lim", lim='ALL')
Traceback (most recent call last):
psycopg2.errors.InvalidTextRepresentation: ...

Instead the docs say that you can send null as an alternative to ALL, which does work:

>> >>> con.run("SELECT 'silo 1' LIMIT :lim", lim=None) [('silo 1',)]">

>>> import facata
>>>
>>> con = facata.connect(
...     "postgresql", "psycopg2", user="postgres", password="pw", host="localhost")
>>>
>>> con.run("SELECT 'silo 1' LIMIT :lim", lim=None)
[('silo 1',)]

COPY From And To A File

The SQL COPY statement can be used to copy from and to a file or file-like object. First we need to obtain the underlying Psycopg2 connection. Here' an example using the CSV format:

>> >>> # Create a CSV file in memory >>> >>> stream_in = StringIO() >>> csv_writer = csv.writer(stream_in) >>> csv_writer.writerow([1, "electron"]) 12 >>> csv_writer.writerow([2, "muon"]) 8 >>> csv_writer.writerow([3, "tau"]) 7 >>> stream_in.seek(0) 0 >>> >>> # Create a table and then copy the CSV into it >>> >>> con.run("CREATE TEMPORARY TABLE lepton (id SERIAL, name TEXT)") >>> >>> cur = con.connection.cursor() >>> cur.copy_expert("COPY lepton FROM STDIN WITH (FORMAT CSV)", stream_in) >>> >>> # COPY from a table to a stream >>> >>> stream_out = StringIO() >>> cur.copy_expert("COPY lepton TO STDOUT WITH (FORMAT CSV)", stream_out) >>> stream_out.seek(0) 0 >>> for row in csv.reader(stream_out): ... print(row) ['1', 'electron'] ['2', 'muon'] ['3', 'tau']">

>>> from io import StringIO
>>> import csv
>>> import facata
>>>
>>> con = facata.connect(
...     "postgresql", "psycopg2", user="postgres", password="pw", host="localhost")
>>>
>>> # Create a CSV file in memory
>>>
>>> stream_in = StringIO()
>>> csv_writer = csv.writer(stream_in)
>>> csv_writer.writerow([1, "electron"])
12
>>> csv_writer.writerow([2, "muon"])
8
>>> csv_writer.writerow([3, "tau"])
7
>>> stream_in.seek(0)
0
>>>
>>> # Create a table and then copy the CSV into it
>>>
>>> con.run("CREATE TEMPORARY TABLE lepton (id SERIAL, name TEXT)")
>>>
>>> cur = con.connection.cursor()
>>> cur.copy_expert("COPY lepton FROM STDIN WITH (FORMAT CSV)", stream_in)
>>>
>>> # COPY from a table to a stream
>>>
>>> stream_out = StringIO()
>>> cur.copy_expert("COPY lepton TO STDOUT WITH (FORMAT CSV)", stream_out)
>>> stream_out.seek(0)
0
>>> for row in csv.reader(stream_out):
...     print(row)
['1', 'electron']
['2', 'muon']
['3', 'tau']

Execute Multiple SQL Statements

If you want to execute a series of SQL statements (eg. an .sql file), you can run them as expected:

>> >>> statements = "SELECT 5; SELECT 'Erich Fromm';" >>> >>> con.run(statements) [('Erich Fromm',)]">

>>> import facata
>>>
>>> con = facata.connect(
...     "postgresql", "psycopg2", user="postgres", password="pw", host="localhost")
>>>
>>> statements = "SELECT 5; SELECT 'Erich Fromm';"
>>>
>>> con.run(statements)
[('Erich Fromm',)]

The only caveat is that when executing multiple statements you can’t have any parameters.

Quoted Identifiers in SQL

Say you had a column called My Column. Since it’s case sensitive and contains a space, you’d have to surround it by double quotes. But you can’t do:

>> >>> con.run("select 'hello' as "My Column"") Traceback (most recent call last): SyntaxError: invalid syntax">

>>> import facata
>>>
>>> con = facata.connect(
...     "postgresql", "psycopg2", user="postgres", password="pw", host="localhost")
>>>
>>> con.run("select 'hello' as "My Column"")
Traceback (most recent call last):
SyntaxError: invalid syntax

since Python uses double quotes to delimit string literals, so one solution is to use Python’s triple quotes to delimit the string instead:

>> >>> con.run('''select 'hello' as "My Column"''') [('hello',)]">

>>> import facata
>>>
>>> con = facata.connect(
...     "postgresql", "psycopg2", user="postgres", password="pw", host="localhost")
>>>
>>> con.run('''select 'hello' as "My Column"''')
[('hello',)]

Custom Adapter From A Python Type To A PostgreSQL Type

Psycopg2 has a mapping from Python types to PostgreSQL types for when it needs to send SQL parameters to the server. The default mapping that comes with Psycopg2 is designed to work well in most cases, but you might want to add or replace the default mapping.

>> >>> class MyInterval(str): ... pass >>> >>> def my_interval_py_to_db(my_interval): ... return AsIs(f"'{my_interval}'") # Must return a str >>> >>> con.register_py_to_db(MyInterval, None, my_interval_py_to_db) >>> con.run("SELECT cast(:interval as interval)", interval=MyInterval("2 hours")) [(datetime.timedelta(seconds=7200),)]">

>>> import facata
>>> from psycopg2.extensions import AsIs
>>>
>>> con = facata.connect(
...     "postgresql", "psycopg2", user="postgres", password="pw", host="localhost")
>>>
>>> class MyInterval(str):
...     pass
>>>
>>> def my_interval_py_to_db(my_interval):
...     return AsIs(f"'{my_interval}'")  # Must return a str
>>>
>>> con.register_py_to_db(MyInterval, None, my_interval_py_to_db)
>>> con.run("SELECT cast(:interval as interval)", interval=MyInterval("2 hours"))
[(datetime.timedelta(seconds=7200),)]

Custom adapter from a PostgreSQL type to a Python type

Psycopg2 has a mapping from PostgreSQL types to Python types for when it receives SQL results from the server. The default mapping that comes with Psycopg2 is designed to work well in most cases, but you might want to add or replace the default mapping.

If Psycopg2 recieves PostgreSQL interval type, which has the oid 1186, it converts it into a Python datetime.timedelta object. But let’s say we wanted to create our own Python class to be used instead of datetime.timedelta. Then we’d have to register an adapter:

>> >>> class MyInterval(str): ... pass >>> >>> def my_interval_db_to_py(my_interval_str, cur): # The parameter is of type str ... return MyInterval(my_interval_str) >>> >>> con.register_db_to_py(1186, my_interval_db_to_py) >>> con.run("SELECT cast('2 years' as interval)") [('2 years',)]">

>>> import facata
>>>
>>> con = facata.connect(
...     "postgresql", "psycopg2", user="postgres", password="pw", host="localhost")
>>>
>>> class MyInterval(str):
...     pass
>>>
>>> def my_interval_db_to_py(my_interval_str, cur):  # The parameter is of type str
...     return MyInterval(my_interval_str)
>>>
>>> con.register_db_to_py(1186, my_interval_db_to_py)
>>> con.run("SELECT cast('2 years' as interval)")
[('2 years',)]

Note that registering the 'in' adapter only afects the mapping from the PostgreSQL type to the Python type. See above for an example of how to change the mapping from PostgreSQL to Python.

Prepared Statements

Prepared statements aren’t currently supported by Psycopg2, so the Facata just defaults to standard execution behind the scenes:

>> >>> # Create the prepared statement >>> ps = con.prepare("SELECT cast(:v as varchar)") >>> >>> # Exceute the statement repeatedly >>> ps.run(v="speedy") [('speedy',)] >>> ps.run(v="rapid") [('rapid',)] >>> ps.run(v="swift") [('swift',)] >>> >>> # Close the prepared statement, releasing resources on the server >>> ps.close()">

>>> import facata
>>>
>>> con = facata.connect(
...     "postgresql", "psycopg2", user="postgres", password="pw", host="localhost")
>>>
>>> # Create the prepared statement
>>> ps = con.prepare("SELECT cast(:v as varchar)")
>>>
>>> # Exceute the statement repeatedly
>>> ps.run(v="speedy")
[('speedy',)]
>>> ps.run(v="rapid")
[('rapid',)]
>>> ps.run(v="swift")
[('swift',)]
>>>
>>> # Close the prepared statement, releasing resources on the server
>>> ps.close()

Use Environment Variables As Connection Defaults

You might want to use the current user as the database username for example:

import getpass
import facata

# Connect to the database with current user name
user = getpass.getuser()
con = facata.connect(
    "postgresql", "psycopg2", user="postgres", password="pw", host="localhost")

con.run("SELECT 'pilau'")

or perhaps you may want to use some of the same environment variables that libpq uses:

>> >>> connection.run("SELECT 'Mr Cairo'") [('Mr Cairo',)]">

>>> import facata
>>> from os import environ
>>>
>>> user = environ.get('PGUSER', 'postgres')
>>> password = environ.get('PGPASSWORD', 'pw')
>>> host = environ.get('PGHOST', 'localhost')
>>> port = environ.get('PGPORT', '5432')
>>> dbname = environ.get('PGDATABASE')
>>>
>>> connection = facata.connect(
...    "postgresql", "psycopg2", user=user, password=password, host=host, port=port,
...    dbname=dbname)
>>>
>>> connection.run("SELECT 'Mr Cairo'")
[('Mr Cairo',)]

It might be asked, why doesn’t Facata have this behaviour built in? The thinking follows the second aphorism of The Zen of Python:

Explicit is better than implicit.

So we’ve taken the approach of only being able to set connection parameters using the facata.connect() function.

Connect To PostgreSQL Over SSL

To connect to the server using SSL defaults do:

from facata import connect


connection = connect(
    "postgresql", "psycopg2", user="postgres", password="cpsnow", sslmode='require')
connection.run("SELECT 'The game is afoot!'")

To connect over SSL with custom settings, use the libpq parameters:

from facata import connect
import ssl


connection = connect(
    "postgresql", "psycopg2", user="postgres", password="cpsnow",
    sslmode="verify-full", sslrootcert="root.pem")

Server-Side Cursors

You can use the SQL commands DECLARE, FETCH, MOVE and CLOSE to manipulate server-side cursors. For example:

>> >>> con.run("START TRANSACTION") >>> con.run("DECLARE c SCROLL CURSOR FOR SELECT * FROM generate_series(1, 100)") >>> con.run("FETCH FORWARD 5 FROM c") [(1,), (2,), (3,), (4,), (5,)] >>> >>> con.run("MOVE FORWARD 50 FROM c") >>> con.run("FETCH BACKWARD 10 FROM c") [(54,), (53,), (52,), (51,), (50,), (49,), (48,), (47,), (46,), (45,)] >>> >>> con.run("CLOSE c") >>> con.run("ROLLBACK")">

>>> import facata
>>>
>>> con = facata.connect(
...     "postgresql", "psycopg2", user="postgres", password="pw", host="localhost")
>>>
>>> con.run("START TRANSACTION")
>>> con.run("DECLARE c SCROLL CURSOR FOR SELECT * FROM generate_series(1, 100)")
>>> con.run("FETCH FORWARD 5 FROM c")
[(1,), (2,), (3,), (4,), (5,)]
>>>
>>> con.run("MOVE FORWARD 50 FROM c")
>>> con.run("FETCH BACKWARD 10 FROM c")
[(54,), (53,), (52,), (51,), (50,), (49,), (48,), (47,), (46,), (45,)]
>>>
>>> con.run("CLOSE c")
>>> con.run("ROLLBACK")

BLOBs (Binary Large Objects)

There’s a set of SQL functions for manipulating BLOBs. Here’s an example:

>> >>> # Create a BLOB and get its oid >>> data = b'hello' >>> res = con.run("SELECT lo_from_bytea(0, :data)", data=data) >>> oid = res[0][0] >>> >>> # Create a table and store the oid of the BLOB >>> con.run("CREATE TEMPORARY TABLE image (raster oid)") >>> con.run("INSERT INTO image (raster) VALUES (:oid)", oid=oid) >>> # Retrieve the data using the oid >>> result = con.run("SELECT lo_get(:oid)", oid=oid) >>> bytes(result[0][0]) b'hello' >>> >>> # Add some data to the end of the BLOB >>> more_data = b' all' >>> offset = len(data) >>> con.run( ... "SELECT lo_put(:oid, :offset, :data)", ... oid=oid, offset=offset, data=more_data) [('',)] >>> result = con.run("SELECT lo_get(:oid)", oid=oid) >>> bytes(result[0][0]) b'hello all' >>> >>> # Download a part of the data >>> result = con.run("SELECT lo_get(:oid, 6, 3)", oid=oid) >>> bytes(result[0][0]) b'all'">

>>> import facata
>>>
>>> con = facata.connect(
...     "postgresql", "psycopg2", user="postgres", password="pw", host="localhost")
>>>
>>> # Create a BLOB and get its oid
>>> data = b'hello'
>>> res = con.run("SELECT lo_from_bytea(0, :data)", data=data)
>>> oid = res[0][0]
>>>
>>> # Create a table and store the oid of the BLOB
>>> con.run("CREATE TEMPORARY TABLE image (raster oid)")
>>> con.run("INSERT INTO image (raster) VALUES (:oid)", oid=oid)
>>> # Retrieve the data using the oid
>>> result = con.run("SELECT lo_get(:oid)", oid=oid)
>>> bytes(result[0][0])
b'hello'
>>>
>>> # Add some data to the end of the BLOB
>>> more_data = b' all'
>>> offset = len(data)
>>> con.run(
...     "SELECT lo_put(:oid, :offset, :data)",
...     oid=oid, offset=offset, data=more_data)
[('',)]
>>> result = con.run("SELECT lo_get(:oid)", oid=oid)
>>> bytes(result[0][0])
b'hello all'
>>>
>>> # Download a part of the data
>>> result = con.run("SELECT lo_get(:oid, 6, 3)", oid=oid)
>>> bytes(result[0][0])
b'all'

Examples For MariaDB With MariaDb Driver

Connecting To A Database

Connecting to MariaDB with the mariadb driver requires the Connector/C to be installed, and then the dependency mariadb can be installed by doing pip install facata[mariadb].

>>> import facata
>>>
>>> with facata.connect(
...         "mariadb", "mariadb", user="root", password="pw", host="127.0.0.1",
...         port=3306, dbname="mysql") as con:
...     con.run("SELECT 'Hello'")
[('Hello',)]

Basic Example

Connect to the database, create a table, add some rows and then query the table:

>>> import facata
>>>
>>> con = facata.connect(
...     "mariadb", "mariadb", user="root", password="pw", host="127.0.0.1", port=3306,
...     dbname="mysql")
>>>
>>> # Create a temporary table
>>>
>>> con.run("CREATE TEMPORARY TABLE book (id SERIAL, title TEXT)")
>>>
>>> # Populate the table
>>>
>>> for title in ("Ender's Game", "The Magus"):
...     con.run("INSERT INTO book (title) VALUES (:title)", title=title)
>>>
>>> # Print all the rows in the table
>>>
>>> for row in con.run("SELECT * FROM book"):
...     print(row)
(1, "Ender's Game")
(2, 'The Magus')

Transactions

Here’s how to run groups of SQL statements in a transaction:

>>> import facata
>>>
>>> con = facata.connect(
...     "mariadb", "mariadb", user="root", password="pw", host="127.0.0.1", port=3306,
...     dbname="mysql")
>>>
>>> con.run("START TRANSACTION")
>>>
>>> # Create a temporary table
>>> con.run("CREATE TEMPORARY TABLE book (id SERIAL, title TEXT)")
>>>
>>> for title in ("Ender's Game", "The Magus", "Phineas Finn"):
...     con.run("INSERT INTO book (title) VALUES (:title)", title=title)
>>> con.run("COMMIT")
>>> for row in con.run("SELECT * FROM book"):
...     print(row)
(1, "Ender's Game")
(2, 'The Magus')
(3, 'Phineas Finn')

rolling back a transaction:

>>> import facata
>>>
>>> con = facata.connect(
...     "mariadb", "mariadb", user="root", password="pw", host="127.0.0.1", port=3306,
...     dbname="mysql")
>>>
>>> # Create a temporary table
>>> con.run("CREATE TEMPORARY TABLE book (id SERIAL, title TEXT)")
>>>
>>> for title in ("Ender's Game", "The Magus", "Phineas Finn"):
...     con.run("INSERT INTO book (title) VALUES (:title)", title=title)
>>>
>>> con.run("START TRANSACTION")
>>> con.run("DELETE FROM book WHERE title = :title", title="Phineas Finn")
>>> con.run("ROLLBACK")
>>> for row in con.run("SELECT * FROM book"):
...     print(row)
(1, "Ender's Game")
(2, 'The Magus')
(3, 'Phineas Finn')

Query Using Fuctions

Another query, using a MariaDB function:

>> >>> con.run("SELECT GREATEST(0, -3, 2)") [(2,)]">

>>> import facata
>>>
>>> con = facata.connect(
...     "mariadb", "mariadb", user="root", password="pw", host="127.0.0.1", port=3306)
>>>
>>> con.run("SELECT GREATEST(0, -3, 2)")
[(2,)]

Point Type

A round-trip with a MariaDB point type:

>> >>> con.run("SELECT AsText(PointFromText(:pt))", pt='POINT(2.3 1)') [('POINT(2.3 1)',)]">

>>> import facata
>>>
>>> con = facata.connect(
...     "mariadb", "mariadb", user="root", password="pw", host="127.0.0.1", port=3306,
...     dbname="mysql")
>>>
>>> con.run("SELECT AsText(PointFromText(:pt))", pt='POINT(2.3 1)')
[('POINT(2.3 1)',)]

Retrieve Column Metadata From Results

Find the column metadata returned from a query:

>> >>> con.run("create temporary table quark (id serial, name text)") >>> for name in ('Up', 'Down'): ... con.run("INSERT INTO quark (name) VALUES (:name)", name=name) >>> # Now execute the query >>> >>> con.run("SELECT * FROM quark") [(1, 'Up'), (2, 'Down')] >>> >>> # and retried the metadata >>> >>> con.columns [{'name': 'id', 'type_code': 8, 'display_size': 5, 'internal_size': 20, 'precision': 0, 'scale': 0}, {'name': 'name', 'type_code': 252, 'display_size': 65535, 'internal_size': 262140, 'precision': 0, 'scale': 0}] >>> >>> # Show just the column names >>> >>> [c['name'] for c in con.columns] ['id', 'name']">

>>> import facata
>>>
>>> con = facata.connect(
...     "mariadb", "mariadb", user="root", password="pw", host="127.0.0.1", port=3306,
...     dbname="mysql")
>>>
>>> con.run("create temporary table quark (id serial, name text)")
>>> for name in ('Up', 'Down'):
...     con.run("INSERT INTO quark (name) VALUES (:name)", name=name)
>>> # Now execute the query
>>>
>>> con.run("SELECT * FROM quark")
[(1, 'Up'), (2, 'Down')]
>>>
>>> # and retried the metadata
>>>
>>> con.columns
[{'name': 'id', 'type_code': 8, 'display_size': 5, 'internal_size': 20, 'precision': 0, 'scale': 0}, {'name': 'name', 'type_code': 252, 'display_size': 65535, 'internal_size': 262140, 'precision': 0, 'scale': 0}]
>>>
>>> # Show just the column names
>>>
>>> [c['name'] for c in con.columns]
['id', 'name']

Load Data From A File

The SQL LOAD DATA INFILE statement can be used to copy from a file. Here' an example:

>> >>> # Open and display a pre-prepared file >>> >>> with open('test/mariadb/data.dat') as f: ... f.read() '\telectron\n\tmuon\n\ttau\n' >>> >>> # Create a table and populate it >>> >>> con.run("CREATE TEMPORARY TABLE lepton (id SERIAL, name TEXT)") >>> con.run("LOAD DATA LOCAL INFILE 'test/mariadb/data.dat' INTO TABLE lepton") >>> >>> con.run("SELECT * FROM lepton") [(1, 'electron'), (2, 'muon'), (3, 'tau')]">

>>> import facata
>>>
>>> con = facata.connect(
...     "mariadb", "mariadb", user="root", password="pw", host="127.0.0.1", port=3306,
...     dbname="mysql")
>>>
>>> # Open and display a pre-prepared file
>>>
>>> with open('test/mariadb/data.dat') as f:
...     f.read()
'\telectron\n\tmuon\n\ttau\n'
>>>
>>> # Create a table and populate it
>>>
>>> con.run("CREATE TEMPORARY TABLE lepton (id SERIAL, name TEXT)")
>>> con.run("LOAD DATA LOCAL INFILE 'test/mariadb/data.dat' INTO TABLE lepton")
>>>
>>> con.run("SELECT * FROM lepton")
[(1, 'electron'), (2, 'muon'), (3, 'tau')]

Quoted Identifiers in SQL

Say you had a column called My Column. Since it’s case sensitive and contains a space, you’d have to surround it by backticks. But you can’t do:

>> >>> con.run("select 'hello' as `My Column`") [('hello',)]">

>>> import facata
>>>
>>> con = facata.connect(
...     "mariadb", "mariadb", user="root", password="pw", host="127.0.0.1", port=3306)
>>>
>>> con.run("select 'hello' as `My Column`")
[('hello',)]

Connect To MariaDB Over SSL

To connect to the server using SSL do something like:

import facata

con = facata.connect(
    "mariadb", "mariadb", user="root", password="pw", host="127.0.0.1", port=3306,
    ssl_ca='ca-cert.pem', ssl_cert='client-cert.pem', ssl_key='client-key.pem')

con.run("SELECT 'The game is afoot!'")

Examples For MySQL With MySQL Connector/Python

Connecting to a database

Connecting to MySQL with the MySQL Connector driver requires the dependency mysql-connector to be installed by doing pip install facata[mysql-connector]. Then connect to a database as follows:

>>> import facata
>>>
>>> with facata.connect(
...         "mysql", "mysql-connector", user="root", password="pw", dbname="mysql",
...         host="127.0.0.1", port=3305) as con:
...     con.run("SELECT 'Hello'")
[('Hello',)]

Basic Example

Connect to the database, create a table, add some rows and then query the table:

>>> import facata
>>>
>>> con = facata.connect(
...     "mysql", "mysql-connector", user="root", password="pw", host="127.0.0.1",
...     port=3305, dbname="mysql")
>>>
>>> # Create a temporary table
>>>
>>> con.run("CREATE TEMPORARY TABLE book (id SERIAL, title TEXT)")
>>>
>>> # Populate the table
>>>
>>> for title in ("Ender's Game", "The Magus"):
...     con.run("INSERT INTO book (title) VALUES (:title)", title=title)
>>>
>>> # Print all the rows in the table
>>>
>>> for row in con.run("SELECT * FROM book"):
...     print(row)
(1, "Ender's Game")
(2, 'The Magus')

Transactions

Here’s how to run groups of SQL statements in a transaction:

>>> import facata
>>>
>>> con = facata.connect(
...     "mysql", "mysql-connector", user="root", password="pw", host="127.0.0.1",
...     port=3305, dbname="mysql")
>>>
>>> con.run("START TRANSACTION")
>>>
>>> # Create a temporary table
>>> con.run("CREATE TEMPORARY TABLE book (id SERIAL, title TEXT)")
>>>
>>> for title in ("Ender's Game", "The Magus", "Phineas Finn"):
...     con.run("INSERT INTO book (title) VALUES (:title)", title=title)
>>> con.run("COMMIT")
>>> for row in con.run("SELECT * FROM book"):
...     print(row)
(1, "Ender's Game")
(2, 'The Magus')
(3, 'Phineas Finn')

rolling back a transaction:

>>> import facata
>>>
>>> con = facata.connect(
...     "mysql", "mysql-connector", user="root", password="pw", host="127.0.0.1",
...     port=3305, dbname="mysql")
>>>
>>> # Create a temporary table
>>> con.run("CREATE TEMPORARY TABLE book (id SERIAL, title TEXT)")
>>>
>>> for title in ("Ender's Game", "The Magus", "Phineas Finn"):
...     con.run("INSERT INTO book (title) VALUES (:title)", title=title)
>>>
>>> con.run("START TRANSACTION")
>>> con.run("DELETE FROM book WHERE title = :title", title="Phineas Finn")
>>> con.run("ROLLBACK")
>>> for row in con.run("SELECT * FROM book"):
...     print(row)
(1, "Ender's Game")
(2, 'The Magus')
(3, 'Phineas Finn')

Query Using Fuctions

Another query, using some MySQL functions:

>> >>> con.run("SELECT GREATEST(0, -3, 2)") [(2,)]">

>>> import facata
>>>
>>> con = facata.connect(
...     "mysql", "mysql-connector", user="root", password="pw", host="127.0.0.1",
...     port=3305, dbname="mysql")
>>>
>>> con.run("SELECT GREATEST(0, -3, 2)")
[(2,)]

Point Type

A round-trip with a MySQL point type:

>> >>> con.run("SELECT ST_AsText(ST_GeomFromText(:pt))", pt='POINT(2.3 1)') [('POINT(2.3 1)',)]">

>>> import facata
>>>
>>> con = facata.connect(
...     "mysql", "mysql-connector", user="root", password="pw", host="127.0.0.1",
...     port=3305, dbname="mysql")
>>>
>>> con.run("SELECT ST_AsText(ST_GeomFromText(:pt))", pt='POINT(2.3 1)')
[('POINT(2.3 1)',)]

Retrieve Column Metadata From Results

Find the column metadata returned from a query:

>> >>> con.run("create temporary table quark (id serial, name text)") >>> for name in ('Up', 'Down'): ... con.run("INSERT INTO quark (name) VALUES (:name)", name=name) >>> # Now execute the query >>> >>> con.run("SELECT * FROM quark") [(1, 'Up'), (2, 'Down')] >>> >>> # and retried the metadata >>> >>> con.columns [{'name': 'id', 'type_code': 8, 'display_size': None, 'internal_size': None, 'precision': None, 'scale': None}, {'name': 'name', 'type_code': 252, 'display_size': None, 'internal_size': None, 'precision': None, 'scale': None}] >>> >>> # Show just the column names >>> >>> [c['name'] for c in con.columns] ['id', 'name']">

>>> import facata
>>>
>>> con = facata.connect(
...     "mysql", "mysql-connector", user="root", password="pw", host="127.0.0.1",
...     port=3305, dbname="mysql")
>>>
>>> con.run("create temporary table quark (id serial, name text)")
>>> for name in ('Up', 'Down'):
...     con.run("INSERT INTO quark (name) VALUES (:name)", name=name)
>>> # Now execute the query
>>>
>>> con.run("SELECT * FROM quark")
[(1, 'Up'), (2, 'Down')]
>>>
>>> # and retried the metadata
>>>
>>> con.columns
[{'name': 'id', 'type_code': 8, 'display_size': None, 'internal_size': None, 'precision': None, 'scale': None}, {'name': 'name', 'type_code': 252, 'display_size': None, 'internal_size': None, 'precision': None, 'scale': None}]
>>>
>>> # Show just the column names
>>>
>>> [c['name'] for c in con.columns]
['id', 'name']

Quoted Identifiers in SQL

Say you had a column called My Column. Since it’s case sensitive and contains a space, you’d have to surround it by backticks:

>> >>> con.run("select 'hello' as `My Column`") [('hello',)]">

>>> import facata
>>>
>>> con = facata.connect(
...     "mysql", "mysql-connector", user="root", password="pw", host="127.0.0.1",
...     port=3305, dbname="mysql")
>>>
>>> con.run("select 'hello' as `My Column`")
[('hello',)]

Connect To MySQL Over SSL

To connect to the server using SSL do:

import facata
from mysql.connector.constants import ClientFlag


con = facata.connect(
    "mysql", "mysql-connector", user="root", password="pw", host="127.0.0.1",
    port=3305, dbname="mysql", client_flags=[ClientFlag.SSL],
    ssl_ca='/opt/mysql/ssl/ca.pem', ssl_cert='/opt/mysql/ssl/client-cert.pem',
    ssl_key='/opt/mysql/ssl/client-key.pem')

con.run("SELECT 'The game is afoot!'")

API Docs

facata.connect()

connect(dbms, driver, dbname=None, user=None, password=None, host=None, port=None, **params):: Returns a new facata.Connection representing a connection to the database. Connections aren’t threadsafe.

dbms

Name of DBMS. Can be mariadb, postgresql or sqlite.

driver

The name of a driver for the DBMS. The possible drivers for each DBMS are:

mariadb: (mariadb)
postgresql: (pg80000, psycopg2)
sqlite: (sqlite3)

dbname

Name of the database to connect to.

user

User name.

password

Password of the user.

host

Hostname

port

Port number.

params

Dictionary of parameters to be given as keyword arguments to the underlying driver.

facata.Connection

A facata.Connection object has the following methods and properties:

run(sql, **params)

Returns the result of executing the sql statement as a sequence of sequences (eg. a list of tuple`s) or `None if the statement isn’t one that can return results.

sql: The SQL statement as a str with any parameters written as a : followed by the parameter name.
params: Parameter name / value pairs.

Diferences From DBAPI 2

DBAPI 2 is the Python standard for accessing SQL databases. Facata differs from DBAPI 2 in these ways:

DBAPI 2 has five ways of writing parameters in SQL, but Facata has just one.
In DAPI 2 parameter values can be provided as a sequence or mapping, but in Facata parameter values are provided as keyword arguments.
DBAPI 2 has four levels of threadsafety, but Facata just has one.
DBAPI 2 has a 'cursor' object, but in Facata there is no cursor object and statements are executed using the connection.
DBAPI 2 overrides the autocommit mode of the underlying database by silently sending START TRANSACTION statements if a transaction isn’t already in progress. Facata never silently sends SQL statements.

Testing

Activate the virtual environment: source venv/bin/activate
Install tox: pip install tox
Run tox: tox

Doing A Release Of Facata

Run tox to make sure all tests pass, then update the release notes, then do:

git tag -a x.y.z -m "version x.y.z"
rm -r dist
python setup.py sdist bdist_wheel
for f in dist/*; do gpg --detach-sign -a $f; done
twine upload dist/*

Release Notes

Version 0.0.0, 2021-08-21

First release.

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SQL string composition

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It would be nice to be able to write something like: con.run("SELECT * FROM :table", table="test")

SQLAlchemy seems to be able to manage that too somehow: https://docs.sqlalchemy.org/en/14/core/type_api.html#sqlalchemy.types.TypeEngine.literal_processor

opened by frafra 0

A Python library that provides a simplified alternative to DBAPI 2

Related tags

Overview

Facata

Installation

Examples For SQLite With SQLite3

Basic Example

Transactions

Query Using Fuctions

Retrieve Column Metadata From Results

Many SQL Statements Can’t Be Parameterized

Execute SQL Scripts

Quoted Identifiers in SQL

Custom Adapter From A Python Type To An SQLite Type

Custom Adapter From An SQLite Type To A Python Type

Examples For PostgreSQL With pg8000

Connecting To A Database

Basic Example

Transactions

Query Using Fuctions

Interval Type

Point Type

Client Encoding

JSON

Retrieve Column Metadata From Results

Notices, Notifications And Parameter Statuses

LIMIT ALL

IN and NOT IN

Many SQL Statements Can’t Be Parameterized

COPY From And To A File

Execute Multiple SQL Statements

Quoted Identifiers in SQL

Custom Adapter From A Python Type To A PostgreSQL Type

Custom adapter from a PostgreSQL type to a Python type

Could Not Determine Data Type Of Parameter

Prepared Statements

Use Environment Variables As Connection Defaults

Connect To PostgreSQL Over SSL

Server-Side Cursors

BLOBs (Binary Large Objects)

Examples For PostgreSQL With Psycopg2

Connecting To A Database

Basic Example

Transactions

Query Using Fuctions

Interval Type

Point Type

Client Encoding

Retrieve Column Metadata From Results

Notices, Notifications And Parameter Statuses

LIMIT ALL

COPY From And To A File

Execute Multiple SQL Statements

Quoted Identifiers in SQL

Custom Adapter From A Python Type To A PostgreSQL Type

Custom adapter from a PostgreSQL type to a Python type

Prepared Statements

Use Environment Variables As Connection Defaults

Connect To PostgreSQL Over SSL

Server-Side Cursors

BLOBs (Binary Large Objects)

Examples For MariaDB With MariaDb Driver

Connecting To A Database

Basic Example

Transactions

Query Using Fuctions

Point Type

Retrieve Column Metadata From Results

Load Data From A File

Quoted Identifiers in SQL

Connect To MariaDB Over SSL

Examples For MySQL With MySQL Connector/Python

Connecting to a database

Basic Example

Transactions

Query Using Fuctions

Point Type

Retrieve Column Metadata From Results

Quoted Identifiers in SQL

Connect To MySQL Over SSL