On 24/08/2023 06.11, dn via Python-list wrote:
On 24/08/2023 03.41, Jason Friedman via Python-list wrote:
with Database() as mydb:
conn = mydb.get_connection()
cursor = conn.get_cursor()
cursor.execute("update table1 set x = 1 where y = 2")
cursor.close()
cursor = conn.get_cursor()
cursor.execute("update table2 set a = 1 where b = 2")
cursor.close()
import jaydebeapi as jdbc
class Database:
database_connection = None
def __init__(self, auto_commit: bool = False):
self.database_connection = jdbc.connect(...)
self.database_connection.jconn.setAutoCommit(auto_commit)
def __enter__(self) -> jdbc.Connection:
return self
def __exit__(self, exception_type: Optional[Type[BaseException]],
exception_value: Optional[BaseException],
traceback: Optional[types.TracebackType]) -> bool:
if exception_type:
self.database_connection.rollback()
else:
self.database_connection.commit()
self.database_connection.close()
def get_connection(self) -> jdbc.Connection:
return self.database_connection
Using a context-manager is a good idea: it ensures clean-up with/without
an exception occurring. Accordingly, I (and may I presume, most) like
the idea when working with life-cycle type resources, eg I/O. Absolutely
nothing wrong with the idea!
However, the scope of a c-m is the with-block. If there are a number of
'nested operations' to be performed (which could conceivably involve
other c-ms, loops, or similar code-structures) the code could become
harder to read and the length of the scope unwieldy.
An ease of management tactic is being able to see the start and end of a
construct on the same page/screen. Such would 'limit' the length of a
c-m's scope.
Perhaps drawing an inappropriate parallel, but like a try-except block,
there seems virtue in keeping a c-m's scope short, eg releasing
resources such as a file opened for output, and some basic DBMS-es which
don't offer multi-access.
Accordingly, why I stopped using a c-m for database work. NB YMMV!
There were two other reasons:
1 multiple databases
2 principles (and my shining virtue (?) )
1 came across a (statistics) situation where the client was using two
DBMS-es. They'd used one for some time, but then preferred another. For
their own reasons, they didn't migrate old data to the new DBMS. Thus,
when performing certain analyses, the data-collection part of the script
might have to utilise different DB 'sources'. In at least one case,
comparing data through time, the routine needed to access both DBMS-es.
(oh what a tangled web we weave...)
2 another situation where the script may or may not actually have needed
to access the DB. Odd? In which case, the 'expense' of the 'entry' and
'exit' phases would never be rewarded.
Thus, 'inspired' to realise that had (long) been contravening SOLID's
DSP advice?rule (Dependency Inversion Principle).
Accordingly, these days adopt something like the following (explaining
it 'backwards' to aid comprehension in case you (gentle reader) have not
come-across such thinking before - remember that word, "inversion"!)
- in the mainline, prior to processing, instantiate a database object
database = Database( credentials )
- assume the mainline calls a function which is the substance of the script:
def just_do_it( database_instance, other_args, ):
while "there's work to be done":
database.query( query, data, etc, )
# could be SELECT or UPDATE in and amongst the 'work'
- a basic outline of query() might be:
def query( self, sql, data, etc, ):
cursor = self.get_cursor()
cursor.execute( sql, data, ) # according to DB/connector, etc
# return query results
- a query can't happen without a "cursor", so either use an existing
cursor, or create a fresh one:
def get_cursor( self ):
if not self._cursor:
connection = self.get_connection()
self._cursor = connection.cursor()
return self._cursor
NB assuming the DBMS has restrictions on cursors, I may have multiple
connections with one cursor each, but in some situations it may be
applicable to run multiple cursors through a single connection.
- a cursor can't exist without a "connection", so either ... :
def get_connection( self ):
if not self._connection:
self._connection = # connect to the DB
return self._connection
- to instantiate a DB-object in the first place, the class definition:
class Database:
def __init__(self):
self._connection = None
self._cursor = None
- and the one part of the exposition that's not 'backwards':
def close(self):
if self._connection:
self._connection.close()
It might be a plan to have several query() methods, according to
application. If each is a dedicated query, such avoids the need to pass
SQL around.
Alternately, and because having "SELECT ..." sprinkled throughout one's
code is a 'code smell' ("magic constants"), it's a good idea to have all
such collected into a separate module. This would also facilitate the
corporate situation where a DBA will provide services to the
applications team.
(don't EVER let a DBA into your Python code - you have been warned!)
Just as with all toy-examples, much detail has been omitted.
Specifically the OP's concern for error-checking. The above enables more
thorough checking and more precise error-reporting; because the steps
are discrete (very SRP = Single Responsibility Principle). That said,
from an application point-of-view, all the DB stuff has been centralised
and it either works or the whole thing should probably be drawn to a
grinding-halt.
The one glaring disadvantage is in the situation where a lot of
(expensive) processing is carried-out, and only at the end is the DB
accessed (presumably to persist the results). It could be frustrating to
do 'all the work' and only thereafter find out that the DBMS is
asleep-at-the-wheel, eg that Docker container has been started. Doh!
The OP had a linked-query 'commit or rollback' situation. The structure
of a separate method for that query-pair (perhaps calling individual
methods for each query) with attendant controls (as described
previously) will work nicely.
Should you be foolish-enough to be required to (and capable of) cope
with more than one DBMS, you can likely see that turning the Database
class into an ABC, will enable consistency between multiple concrete and
specific database class implementations. Thereafter a 'factory' to
choose which DB-class to use, and all will be roses...
(yeah right!)
--
Regards,
=dn
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