How to get column attributes from a query using PostgreSQL? - python

I need to get the fields attributes from a query, like in this question:How to get column attributes query from table name using PostgreSQL?
but for a query, is there a way of doing this?

Assuming you're using psycopg2 as your database driver, then the cursor.description field is what you want:
import pprint
import psycopg2
conn = psycopg2.connect('');
curs = conn.cursor()
curs.execute("SELECT 1 as col1, 2 as col2, 'text' as colblah");
pprint.pprint(curs.description)
produces:
(Column(name='col1', type_code=23, display_size=None, internal_size=4, precision=None, scale=None, null_ok=None),
Column(name='col2', type_code=23, display_size=None, internal_size=4, precision=None, scale=None, null_ok=None),
Column(name='colblah', type_code=705, display_size=None, internal_size=-2, precision=None, scale=None, null_ok=None))
The type codes are PostgreSQL's internal object IDs.
For more detail see the psycopg2 manual, which explains how to turn the type oids into type names, among other things.

Related

How to specify a dot separated table as a parameter into the sql query

For purposes of this question, let's say there is a table schema foo.bar.baz
And we have created a cursor object using following boilerplate
import snowflake.connector
ctx = snowflake.connector.connect(...)
cur = ctx.cursor()
With that cursor object, we can put the whole dot deliminated schema into a query like so:
cur.execute('''
select * from foo.bar.baz
'''
)
and have no issues, but we wouldn't be able to do:
cur.execute('''
select * from %(tbl)s
''', {'tbl': 'foo.bar.baz'}
)
Doing that throws this type of error: ProgrammingError: 001011 (42601): SQL compilation error: invalid URL prefix found in: foo.bar.baz
I'm guessing this is because the dots are sql identifiers and not strings, but I don't see any workaround in the snowflake documentation. Does anyone know how this could be done without having to change the connection object.
Using TABLE:
In a FROM clause, the syntax TABLE( { string_literal | session_variable | bind_variable } ) can be used
select * from TABLE(%(tbl)s)

ORA-00942 when importing data from Oracle Database to Pandas

I try to import data from a oracle database to a pandas dataframe.
right Now i am using:
import cx_Oracle
import pandas as pd
db_connection_string = '.../A1#server:port/servername'
con = cx_Oracle.connect(db_connection_string)
query = """SELECT*
FROM Salesdata"""
df = pd.read_sql(query, con=con)
and get the following error: DatabaseError: ORA-00942: Table or view doesn't exist
When I run a query to get the list of all tables:
cur = con.cursor()
cur.execute("SELECT table_name FROM dba_tables")
for row in cur:
print (row)
The output looks like this:
('A$',)
('A$BD',)
('Salesdata',)
What I am doing wrong? I used this question to start.
If I use the comment to print(query)I get:
SELECT*
FROM Salesdata
Getting ORA-00942 when running SELECT can have 2 possible causes:
The table does not exist: here you should make sure the table name is prefixed by the table owner (schema name) as in select * from owner_name.table_name. This is generally needed if the current Oracle user connected is not the table owner.
You don't have SELECT privileges on the table. This is also generally needed if the current Oracle user connected is not the table owner.
You need to check both.

Specifying pyODBC options (fast_executemany = True in particular) using SQLAlchemy

I would like to switch on the fast_executemany option for the pyODBC driver while using SQLAlchemy to insert rows to a table. By default it is of and the code runs really slow... Could anyone suggest how to do this?
Edits:
I am using pyODBC 4.0.21 and SQLAlchemy 1.1.13 and a simplified sample of the code I am using are presented below.
import sqlalchemy as sa
def InsertIntoDB(self, tablename, colnames, data, create = False):
"""
Inserts data into given db table
Args:
tablename - name of db table with dbname
colnames - column names to insert to
data - a list of tuples, a tuple per row
"""
# reflect table into a sqlalchemy object
meta = sa.MetaData(bind=self.engine)
reflected_table = sa.Table(tablename, meta, autoload=True)
# prepare an input object for sa.connection.execute
execute_inp = []
for i in data:
execute_inp.append(dict(zip(colnames, i)))
# Insert values
self.connection.execute(reflected_table.insert(),execute_inp)
Try this for pyodbc
crsr = cnxn.cursor()
crsr.fast_executemany = True
Starting with version 1.3, SQLAlchemy has directly supported fast_executemany, e.g.,
engine = create_engine(connection_uri, fast_executemany=True)

SQLAlchemy select only one column

Try to select one column from pg_shadow table the following way:
role_tbl = Table('pg_shadow', MetaData(engine), autoload=True)
db.query(role_tbl.c.passwd).filter_by(usename='name')
And get an error:
* AttributeError: 'NoneType' object has no attribute 'class_'
The error is the result of having no entity in the query:
The keyword expressions are extracted from the primary entity of the query, or the last entity that was the target of a call to Query.join().
where an entity is a mapped class, or the Table object, but you're querying a single column. The proper way to filter would be:
db.query(role_tbl.c.passwd).filter(role_tbl.c.usename == 'name')
In a more recent version of SQLAlchemy the error is:
NoInspectionAvailable: No inspection system is available for object of type <class 'NoneType'>
Try this one:
role_tbl.select([role_tbl.c.passwd]).where(username=='name').execute().fetchall()
Or probably there is no such column in this table.
You can check it by printing all columns
print role_tbl.columns
P.S.
And also you should use one instance of metadata: MetaData(engine) (it should store information about all tables)
To select only one column you can use Select.with_only_columns:
from sqlalchemy import MetaData, Table, Column, Text
meta = MetaData()
table = Table('user', meta,
Column("name", Text),
Column("full_name", Text))
stmt = (table.select()
.with_only_columns([table.c.name])
)
print(stmt)
# SELECT "user".name
# FROM "user"

add column to SQLAlchemy Table

I made a table using SQLAlchemy and forgot to add a column. I basically want to do this:
users.addColumn('user_id', ForeignKey('users.user_id'))
What's the syntax for this? I couldn't find it in the docs.
I have the same problem, and a thought of using migration library only for this trivial thing makes me
tremble. Anyway, this is my attempt so far:
def add_column(engine, table_name, column):
column_name = column.compile(dialect=engine.dialect)
column_type = column.type.compile(engine.dialect)
engine.execute('ALTER TABLE %s ADD COLUMN %s %s' % (table_name, column_name, column_type))
column = Column('new_column_name', String(100), primary_key=True)
add_column(engine, table_name, column)
Still, I don't know how to insert primary_key=True into raw SQL request.
This is referred to as database migration (SQLAlchemy doesn't support migration out of the box). You can look at using sqlalchemy-migrate to help in these kinds of situations, or you can just ALTER TABLE through your chosen database's command line utility,
See this section of the SQLAlchemy documentation: http://docs.sqlalchemy.org/en/latest/core/metadata.html#altering-schemas-through-migrations
Alembic is the latest software to offer this type of functionality and is made by the same author as SQLAlchemy.
I have a database called "ncaaf.db" built with sqlite3 and a table called "games". So I would CD into the same directory on my linux command prompt and do
sqlite3 ncaaf.db
alter table games add column q4 type float
and that is all it takes! Just make sure you update your definitions in your sqlalchemy code.
from sqlalchemy import create_engine
engine = create_engine('sqlite:///db.sqlite3')
engine.execute('alter table table_name add column column_name String')
I had the same problem, I ended up just writing my own function in raw sql. If you are using SQLITE3 this might be useful.
Then if you add the column to your class definition at the same time it seems to do the trick.
import sqlite3
def add_column(database_name, table_name, column_name, data_type):
connection = sqlite3.connect(database_name)
cursor = connection.cursor()
if data_type == "Integer":
data_type_formatted = "INTEGER"
elif data_type == "String":
data_type_formatted = "VARCHAR(100)"
base_command = ("ALTER TABLE '{table_name}' ADD column '{column_name}' '{data_type}'")
sql_command = base_command.format(table_name=table_name, column_name=column_name, data_type=data_type_formatted)
cursor.execute(sql_command)
connection.commit()
connection.close()
I've recently had this same issue so I took a point from AlexP in an earlier answer. The problem was in getting the new column into my program's metadata. Using sqlAlchemy's append_column functionality had some unexpected downstream effects ('str' object has no attribute 'dialect impl'). I corrected this by adding the column with DDL (MySQL database in this case) and then reflecting the table back from the DB into my metadata.
Code is as roughly as follows (modified slightly from what I have in order to reduce it to its minimal essence. I apologize for any mistakes - if there, they should be minor)...
try:
# Use back quotes as a protection against SQL Injection Attacks. Can we do more?
common.qry_engine.execute('ALTER TABLE %s ADD COLUMN %s %s' %
('`' + self.tbl.schema + '`.`' + self.tbl.name + '`',
'`' + self.outputs[new_col] + '`', 'VARCHAR(50)'))
except exc.SQLAlchemyError as msg:
raise GRError(desc='Unable to physically add derived column to table. Contact support.',
data=str(self.outputs), other_info=str(msg))
try: # Refresh the metadata to show the new column
self.tbl = sqlalchemy.Table(self.tbl.name, self.tbl.metadata, extend_existing=True, autoload=True)
except exc.SQLAlchemyError as msg:
raise GRError(desc='Unable to establish metadata for new column. Contact support.',
data=str(self.outputs), other_info=str(msg))
Yes you can
Install sqlalchemy-migrate (pip install sqlalchemy-migrate) and use it in your script to call Table and Column create() method:
from sqlalchemy import String, MetaData, create_engine
from migrate.versioning.schema import Table, Column
db_engine = create_engine(app.config.get('SQLALCHEMY_DATABASE_URI'))
db_meta = MetaData(bind=db_engine)
table = Table('tabel_name' , db_meta)
col = Column('new_column_name', String(20), default='foo')
col.create(table)
Just continuing the simple way proposed by chasmani, little improvement
'''
# simple migration
# columns to add:
# last_status_change = Column(BigInteger, default=None)
# last_complete_phase = Column(String, default=None)
# complete_percentage = Column(DECIMAL, default=0.0)
'''
import sqlite3
from config import APP_STATUS_DB
from sqlalchemy import types
def add_column(database_name: str, table_name: str, column_name: str, data_type: types, default=None):
ret = False
if default is not None:
try:
float(default)
ddl = ("ALTER TABLE '{table_name}' ADD column '{column_name}' '{data_type}' DEFAULT {default}")
except:
ddl = ("ALTER TABLE '{table_name}' ADD column '{column_name}' '{data_type}' DEFAULT '{default}'")
else:
ddl = ("ALTER TABLE '{table_name}' ADD column '{column_name}' '{data_type}'")
sql_command = ddl.format(table_name=table_name, column_name=column_name, data_type=data_type.__name__,
default=default)
try:
connection = sqlite3.connect(database_name)
cursor = connection.cursor()
cursor.execute(sql_command)
connection.commit()
connection.close()
ret = True
except Exception as e:
print(e)
ret = False
return ret
add_column(APP_STATUS_DB, 'procedures', 'last_status_change', types.BigInteger)
add_column(APP_STATUS_DB, 'procedures', 'last_complete_phase', types.String)
add_column(APP_STATUS_DB, 'procedures', 'complete_percentage', types.DECIMAL, 0.0)
If using docker:
go to the terminal of the container holding your DB
get into the db: psql -U usr [YOUR_DB_NAME]
now you can alter tables using raw SQL: alter table [TABLE_NAME] add column [COLUMN_NAME] [TYPE]
Note you will need to have mounted your DB for the changes to persist between builds.
Adding the column "manually" (not using python or SQLAlchemy) is perhaps the easiest?
Same problem over here. What I will do is iterating over the db and add each entry to a new database with the extra column, then delete the old db and rename the new to this one.

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