カーソルの型#
Psycopg can manage kinds of "cursors" which differ in where the state of a query being processed is stored: Client-side cursors and Server-side cursors.
Client-side cursors#
Client-side cursors are what Psycopg uses in its normal querying process.
They are implemented by the Cursor
and AsyncCursor
classes. In such
querying pattern, after a cursor sends a query to the server (usually calling
execute()
), the server replies transferring to the client the whole
set of results requested, which is stored in the state of the same cursor and
from where it can be read from Python code (using methods such as
fetchone()
and siblings).
This querying process is very scalable because, after a query result has been transmitted to the client, the server doesn't keep any state. Because the results are already in the client memory, iterating its rows is very quick.
The downside of this querying method is that the entire result has to be transmitted completely to the client (with a time proportional to its size) and the client needs enough memory to hold it, so it is only suitable for reasonably small result sets.
Client-side-binding cursors#
バージョン 3.1 で追加.
The previously described client-side cursors send the query and the parameters separately to the server. This is the most efficient way to process parametrised queries and allows to build several features and optimizations. However, not all types of queries can be bound server-side; in particular no Data Definition Language query can. See サーバーサイド バインディング for the description of these problems.
The ClientCursor
(and its AsyncClientCursor
async counterpart) merge the
query on the client and send the query and the parameters merged together to
the server. This allows to parametrize any type of PostgreSQL statement, not
only queries (SELECT
) and Data Manipulation statements (INSERT
,
UPDATE
, DELETE
).
Using ClientCursor
, Psycopg 3 behaviour will be more similar to psycopg2
(which only implements client-side binding) and could be useful to port
Psycopg 2 programs more easily to Psycopg 3. The objects in the sql
module
allow for greater flexibility (for instance to parametrize a table name too,
not only values); however, for simple cases, a ClientCursor
could be the
right object.
In order to obtain ClientCursor
from a connection, you can set its
cursor_factory
(at init time or changing its attribute
afterwards):
from psycopg import connect, ClientCursor
conn = psycopg.connect(DSN, cursor_factory=ClientCursor)
cur = conn.cursor()
# <psycopg.ClientCursor [no result] [IDLE] (database=piro) at 0x7fd977ae2880>
If you need to create a one-off client-side-binding cursor out of a normal
connection, you can just use the ClientCursor
class passing the connection
as argument.
conn = psycopg.connect(DSN)
cur = psycopg.ClientCursor(conn)
警告
Client-side cursors don't support binary parameters and return values and don't support prepared statements.
Tip
The best use for client-side binding cursors is probably to port large Psycopg 2 code to Psycopg 3, especially for programs making wide use of Data Definition Language statements.
The psycopg.sql
module allows for more generic client-side query
composition, to mix client- and server-side parameters binding, and allows
to parametrize tables and fields names too, or entirely generic SQL
snippets.
Server-side cursors#
PostgreSQL has its own concept of cursor too (sometimes also called portal). When a database cursor is created, the query is not necessarily completely processed: the server might be able to produce results only as they are needed. Only the results requested are transmitted to the client: if the query result is very large but the client only needs the first few records it is possible to transmit only them.
The downside is that the server needs to keep track of the partially processed results, so it uses more memory and resources on the server.
Psycopg allows the use of server-side cursors using the classes ServerCursor
and AsyncServerCursor
. They are usually created by passing the name
parameter to the cursor()
method (reason for which, in
psycopg2
, they are usually called named cursors). The use of these classes
is similar to their client-side counterparts: their interface is the same, but
behind the scene they send commands to control the state of the cursor on the
server (for instance when fetching new records or when moving using
scroll()
).
Using a server-side cursor it is possible to process datasets larger than what would fit in the client's memory. However for small queries they are less efficient because it takes more commands to receive their result, so you should use them only if you need to process huge results or if only a partial result is needed.
参考
Server-side cursors are created and managed by ServerCursor
using SQL
commands such as DECLARE, FETCH, MOVE. The PostgreSQL documentation
gives a good idea of what is possible to do with them.
"Stealing" an existing cursor#
A Psycopg ServerCursor
can be also used to consume a cursor which was
created in other ways than the DECLARE
that ServerCursor.execute()
runs behind the scene.
For instance if you have a PL/pgSQL function returning a cursor:
CREATE FUNCTION reffunc(refcursor) RETURNS refcursor AS $$
BEGIN
OPEN $1 FOR SELECT col FROM test;
RETURN $1;
END;
$$ LANGUAGE plpgsql;
you can run a one-off command in the same connection to call it (e.g. using
Connection.execute()
) in order to create the cursor on the server:
conn.execute("SELECT reffunc('curname')")
after which you can create a server-side cursor declared by the same name, and
directly call the fetch methods, skipping the execute()
call:
cur = conn.cursor('curname')
# no cur.execute()
for record in cur: # or cur.fetchone(), cur.fetchmany()...
# do something with record
Raw Query Cursors#
バージョン 3.2 で追加.
The RawCursor
and AsyncRawCursor
classes allow users to use PostgreSQL
native placeholders ($1
, $2
, etc.) in their queries instead of the
standard %s
placeholder. This can be useful when it's desirable to pass
the query unmodified to PostgreSQL and rely on PostgreSQL's placeholder
functionality, such as when dealing with a very complex query containing
%s
inside strings, dollar-quoted strings or elsewhere.
One important note is that raw query cursors only accept positional arguments in the form of a list or tuple. This means you cannot use named arguments (i.e., dictionaries).
There are two ways to use raw query cursors:
Using the cursor factory:
from psycopg import connect, RawCursor
with connect(dsn, cursor_factory=RawCursor) as conn:
with conn.cursor() as cur:
cur.execute("SELECT $1, $2", [1, "Hello"])
assert cur.fetchone() == (1, "Hello")
Instantiating a cursor:
from psycopg import connect, RawCursor
with connect(dsn) as conn:
with RawCursor(conn) as cur:
cur.execute("SELECT $1, $2", [1, "Hello"])
assert cur.fetchone() == (1, "Hello")