We are using python on top of Postgresql / PostGIS, for a vehicle tracking system.
THis is quite data intensive, and we have some 'interesting' GIS queries where we see where a vehicle or fleet has stopped within specific areas, where it has traveled, any incidents along the way and much more.
Postgresql functions are used almost exclusively for DML and queries, as running individual SQL statements that will return all the records required to process a complex report was just too slow. For even simple stuff, we are an order of magnitude faster than a similar system using the same data written in Java against Posgresql, but using the java ORM for queries.
All geographic functions are processed in PostGIS, other than the odd reverse geocoding call which is performed against Google Maps or similar
YMMV.
On Fri, 31 Jul 2020 at 12:50, Allan Kamau <kamauallan@xxxxxxxxx> wrote:
You may write stored procedures using PL/pgSQL,alternatively you may write your queries in python.You may use psycopg2 to query the DB from Python.You may have a mix of the two, it will depend on your preference.Ideally you may not want your users running queries against the data by connecting to the database directly using database tools psql or pgadmin3 or pgadmin4.This means that having a database access application written in Python to restrict the and encapsulate data access may be advisable.In this case you may place all the DML statements in python and execute them or you may have much of the data access logic written into several PL/pgSQL functions, then call these functions via Python.Below is python code illustrating the use of psycopg2. This code has not been run so expect some errors.Here I am executing an SQL query on a table, you may modify this code to execute a PL/pgSQL function.
import psycopg2;
from psycopg2 import sql;
import psycopg2.extras;
from psycopg2.extensions import AsIs;
db__pg_conn__str="host='host_name_of_computer_hosting_pg_db_service' port=5432 dbname='your_pg_db_name' user='your_username' password='user_password'";
db__pg_conn=psycopg2.connect(db__pg_conn__str);
query_table(
dataset_name
,some_value_2
,db__pg_conn
);
def query_table(
dataset_name
,some_value_2
,db__pg_conn
):
"""
""";
table__id=-1;
_sql_query1a="""
SELECT {}::TEXT AS some_string,a.id AS table__id,a.*,clock_timestamp() FROM {}.{} a WHERE a.dataset_name={}::TEXT
;
""";
sqlSQL1a=None;
sqlSQL1a=sql.SQL(_sql_query1a);
pg_cursor1a=db__pg_conn.cursor(cursor_factory=psycopg2.extras.DictCursor);
_sql_query1a_processed=pg_cursor1a.mogrify(
sqlSQL1a.format(
sql.SQL(',').join(map(psycopg2.sql.Placeholder,['some_value_1']))
,psycopg2.sql.Identifier("my_schema.my_table".split(".")[0])
,psycopg2.sql.Identifier("my_schema.my_table".split(".")[1])
,sql.SQL(',').join(map(psycopg2.sql.Placeholder,['some_value_2']))
)
,{
'some_value_1':'ABC'
,'some_value_2':dataset_name
}
);
_sql_query1a_processed=_sql_query1a_processed.decode().replace("\\'","'");
#LOGGER.info(" '{0}', -------------- _sql_query1a_processed is:'{1}'.".format(datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S.%f')[:-1],_sql_query1a_processed));
pg_cursor1a.execute(
_sql_query1a_processed
);
rowcount1a=pg_cursor1a.rowcount;
rows=None;
rows=pg_cursor1a.fetchall();
row_cnt=0;
for row in rows:
pass;
row_cnt+=1;
table__id=row["table__id"];//do something with table__id
//do something with rows.
rows=None;
db__pg_conn.commit();
sqlSQL1a=None;
pg_cursor1a=None;On Fri, Jul 31, 2020 at 12:30 PM Shaozhong SHI <shishaozhong@xxxxxxxxx> wrote:Hi,
What is the advantage of querying in Python?
Has anyone got much experience?
What not just use standard query?
What is the rationale for querying in Python?Would the performance be better?
Regards,
Shao
