I have a sqlite db in my home dir.
stephen#stephen-AO725:~$ pwd
/home/stephen
stephen#stephen-AO725:~$ sqlite db1
SQLite version 2.8.17
Enter ".help" for instructions
sqlite> select * from test
...> ;
3|4
5|6
sqlite> .quit
when I try to connect from a jupiter notebook with sqlalchemy and pandas, sth does not work.
db=sqla.create_engine('sqlite:////home/stephen/db1')
pd.read_sql('select * from db1.test',db)
~/anaconda3/lib/python3.7/site-packages/sqlalchemy/engine/default.py in do_execute(self, cursor, statement, parameters, context)
578
579 def do_execute(self, cursor, statement, parameters, context=None):
--> 580 cursor.execute(statement, parameters)
581
582 def do_execute_no_params(self, cursor, statement, context=None):
DatabaseError: (sqlite3.DatabaseError) file is not a database
[SQL: select * from db1.test]
(Background on this error at: http://sqlalche.me/e/4xp6)
I also tried:
db=sqla.create_engine('sqlite:///~/db1')
same result
Personally, just to complete the code of #Stephen with the modules required:
# 1.-Load module
import sqlalchemy
import pandas as pd
#2.-Turn on database engine
dbEngine=sqlalchemy.create_engine('sqlite:////home/stephen/db1.db') # ensure this is the correct path for the sqlite file.
#3.- Read data with pandas
pd.read_sql('select * from test',dbEngine)
#4.- I also want to add a new table from a dataframe in sqlite (a small one)
df_todb.to_sql(name = 'newTable',con= dbEngine, index=False, if_exists='replace')
Another way to read is using sqlite3 library, which may be more straighforward:
#1. - Load libraries
import sqlite3
import pandas as pd
# 2.- Create your connection.
cnx = sqlite3.connect('sqlite:////home/stephen/db1.db')
cursor = cnx.cursor()
# 3.- Query and print all the tables in the database engine
cursor.execute("SELECT name FROM sqlite_master WHERE type='table';")
print(cursor.fetchall())
# 4.- READ TABLE OF SQLITE CALLED test
dfN_check = pd.read_sql_query("SELECT * FROM test", cnx) # we need real name of table
# 5.- Now I want to delete all rows of this table
cnx.execute("DELETE FROM test;")
# 6. -COMMIT CHANGES! (mandatory if you want to save these changes in the database)
cnx.commit()
# 7.- Close the connection with the database
cnx.close()
Please let me know if this helps!
import sqlalchemy
engine=sqlalchemy.create_engine(f'sqlite:///db1.db')
Note: that you need three slashes in sqlite:/// in order to use a relative path for the DB. If you want an absolute path, use four slashes: sqlite:////
Source: Link
The issue is no backward compatibility as noted by Everila. anaconda installs its own sqlite, which is sqlite3.x and that sqlite cannot load databases created by sqlite 2.x
after creating a db with sqlite 3 the code works fine
db=sqla.create_engine('sqlite:////home/stephen/db1')
pd.read_sql('select * from test',db)
which confirms the 4 slashes are needed.
None of the sqlalchemy solutions worked for me with python 3.10.6 and sqlalchemy 2.0.0b4, it could be a beta issue or version 2.0.0 changed things. #corina-roca's solution was close, but not right as you need to pass a connection object, not an engine object. That's what the documentation says, but it didn't actually work. After a bit of experimentation, I discovered that engine.raw_connect() works, although you get a warning on the CLI. Here are my working examples
The sqlite one works out of the box - but it's not ideal if you are thinking of changing databases later
import sqlite3
conn = sqlite3.connect("sqlite:////home/stephen/db1")
df = pd.read_sql_query('SELECT * FROM test', conn)
df.head()
# works, no problem
sqlalchemy lets you abstract your db away
from sqlalchemy import create_engine, text
engine = create_engine("sqlite:////home/stephen/db1")
conn = engine.connect() # <- this is also what you are supposed to
# pass to pandas... it doesn't work
result = conn.execute(text("select * from test"))
for row in result:
print(row) # outside pands, this works - proving that
# connection is established
conn = engine.raw_connection() # with this workaround, it works; but you
# get a warning UserWarning: pandas only
# supports SQLAlchemy connectable ...
df = pd.read_sql_query(sql='SELECT * FROM test', con=conn)
df.head()
Related
I'm trying to get a table from Denodo using Python and sqlalchemy library. That's my code
from sqlalchemy import create_engine
import os
sql = """SELECT * FROM test_table LIMIT 10 """
engine = create_engine('mssql+pyodbc://DenodoODBC', encoding='utf-8')
con = engine.connect().connection
cursor = con.cursor()
cursor.execute(sql)
df = cursor.fetchall()
cursor.close()
con.close()
When I'm trying to run it for the first time I get the following error.
DBAPIError: (pyodbc.Error) (' \x10#', "[ \x10#] ERROR: Function 'schema_name' with arity 0 not found\njava.sql.SQLException: Function 'schema_name' with arity 0 not found;\nError while executing the query (7) (SQLExecDirectW)")
[SQL: SELECT schema_name()]
I think the problem might be with create_engine because when I'm trying to run the code for the second time without creating an engine again, everything is fine.
I hope somebody can explain me what is going on. Thanks :)
I'm currently trying to query a deltadna database. Their Direct SQL Access guide states that any PostgreSQL ODBC compliant tools should be able to connect without issue. Using the guide, I set up an ODBC data source in windows
I have tried adding Set nocount on, changed various formats for the connection string, changed the table name to be (account).(system).(tablename), all to no avail. The simple query works in Excel and I have cross referenced with how Excel formats everything as well, so it is all the more strange that I get the no query problem.
import pyodbc
conn_str = 'DSN=name'
query1 = 'select eventName from table_name limit 5'
conn = pyodbc.connect(conn_str)
conn.setdecoding(pyodbc.SQL_CHAR,encoding='utf-8')
query1_cursor = conn.cursor().execute(query1)
row = query1_cursor.fetchone()
print(row)
Result is ProgrammingError: No results. Previous SQL was not a query.
Try it like this:
import pyodbc
conn_str = 'DSN=name'
query1 = 'select eventName from table_name limit 5'
conn = pyodbc.connect(conn_str)
conn.setdecoding(pyodbc.SQL_CHAR,encoding='utf-8')
query1_cursor = conn.cursor()
query1_cursor.execute(query1)
row = query1_cursor.fetchone()
print(row)
You can't do the cursor declaration and execution in the same row. Since then your query1_cursor variable will point to a cursor object which hasn't executed any query.
I have a DDL object (create_function_foo) that contains a create function statement. In first line of it I put DROP FUNCTION IF EXISTS foo; but engine.execute(create_function_foo) returns:
sqlalchemy.exc.InterfaceError: (InterfaceError) Use multi=True when executing multiple statements
I put multi=True as parameter for create_engine, engine.execute_options and engine.execute but it doesn't work.
NOTE: engine if my instance of create_engine
NOTE: I'm using python 3.2 + mysql.connector 1.0.12 + sqlalchemy 0.8.2
create_function_foo = DDL("""\
DROP FUNCTION IF EXISTS foo;
CREATE FUNCTION `foo`(
SID INT
) RETURNS double
READS SQL DATA
BEGIN
...
END
""")
Where I should put it?
multi=True is a requirement for MySql connector. You can not set this flag passing it to SQLAlchemy methods. Do this:
conn = session.connection().connection
cursor = conn.cursor() # get mysql db-api cursor
cursor.execute(sql, multi=True)
More info here: http://www.mail-archive.com/sqlalchemy#googlegroups.com/msg30129.html
Yeah... This seems like a bummer to me. I don't want to use the ORM so the accepted answer didn't work for me.
I did this instead:
with open('sql_statements_file.sql') as sql_file:
for statement in sql_file.read().split(';'):
if len(statement.strip()) > 0:
connection.execute(statement + ';')
And then this failed for a CREATE function.... YMMV.
There are some cases where SQLAlchemy does not provide a generic way at accessing some DBAPI functions, such as as dealing with multiple result sets. In these cases, you should deal with the raw DBAPI connection directly.
From SQLAlchemy documentation:
connection = engine.raw_connection()
try:
cursor = connection.cursor()
cursor.execute("select * from table1; select * from table2")
results_one = cursor.fetchall()
cursor.nextset()
results_two = cursor.fetchall()
cursor.close()
finally:
connection.close()
You can also do the same using mysql connector as seen here:
operation = 'SELECT 1; INSERT INTO t1 VALUES (); SELECT 2'
for result in cursor.execute(operation, multi=True):
if result.with_rows:
print("Rows produced by statement '{}':".format(
result.statement))
print(result.fetchall())
else:
print("Number of rows affected by statement '{}': {}".format(
result.statement, result.rowcount))
I am currently connecting to a Sybase 15.7 server using sybpydb. It seems to connect fine:
import sys
sys.path.append('/dba/sybase/ase/15.7/OCS-15_0/python/python26_64r/lib')
sys.path.append('/dba/sybase/ase/15.7/OCS-15_0/lib')
import sybpydb
conn = sybpydb.connect(user='usr', password='pass', servername='serv')
is working fine. Changing any of my connection details results in a connection error.
I then select a database:
curr = conn.cursor()
curr.execute('use db_1')
however, now when I try to run queries, it always returns None
print curr.execute('select * from table_1')
I have tried running the use and select queries in the same execute, I have tried including go commands after each, I have tried using curr.connection.commit() after each, all with no success. I have confirmed, using dbartisan and isql, that the same queries I am using return entries.
Why am I not getting results from my queries in python?
EDIT:
Just some additional info. In order to get the sybpydb import to work, I had to change two environment variables. I added the lib paths (the same ones that I added to sys.path) to $LD_LIBRARY_PATH, i.e.:
setenv LD_LIBRARY_PATH "$LD_LIBRARY_PATH":dba/sybase/ase/15.7/OCS-15_0/python/python26_64r/lib:/dba/sybase/ase/15.7/OCS-15_0/lib
and I had to change the SYBASE path from 12.5 to 15.7. All this was done in csh.
If I print conn.error(), after every curr.execute(), I get:
("Server message: number(5701) severity(10) state(2) line(0)\n\tChanged database context to 'master'.\n\n", 5701)
I completely understand where you might be confused by the documentation. Its doesn't seem to be on par with other db extensions (e.g. psycopg2).
When connecting with most standard db extensions you can specify a database. Then, when you want to get the data back from a SELECT query, you either use fetch (an ok way to do it) or the iterator (the more pythonic way to do it).
import sybpydb as sybase
conn = sybase.connect(user='usr', password='pass', servername='serv')
cur = conn.cursor()
cur.execute("use db_1")
cur.execute("SELECT * FROM table_1")
print "Query Returned %d row(s)" % cur.rowcount
for row in cur:
print row
# Alternate less-pythonic way to read query results
# for row in cur.fetchall():
# print row
Give that a try and let us know if it works.
Python 3.x working solution:
import sybpydb
try:
conn = sybpydb.connect(dsn="Servername=serv;Username=usr;Password=pass")
cur = conn.cursor()
cur.execute('select * from db_1..table_1')
# table header
header = tuple(col[0] for col in cur.description)
print('\t'.join(header))
print('-' * 60)
res = cur.fetchall()
for row in res:
line = '\t'.join(str(col) for col in row)
print(line)
cur.close()
conn.close()
except sybpydb.Error:
for err in cur.connection.messages:
print(f'Error {err[0]}, Value {err[1]}')
I am using pymssql and the Pandas sql package to load data from SQL into a Pandas dataframe with frame_query.
I would like to send it back to the SQL database using write_frame, but I haven't been able to find much documentation on this. In particular, there is a parameter flavor='sqlite'. Does this mean that so far Pandas can only export to SQLite? My firm is using MS SQL Server 2008 so I need to export to that.
Unfortunately, yes. At the moment sqlite is the only "flavor" supported by write_frame. See https://github.com/pydata/pandas/blob/master/pandas/io/sql.py#L155
def write_frame(frame, name=None, con=None, flavor='sqlite'):
"""
Write records stored in a DataFrame to SQLite. The index will currently be
dropped
"""
if flavor == 'sqlite':
schema = get_sqlite_schema(frame, name)
else:
raise NotImplementedError
Writing a simple write_frame should be fairly easy, though. For example, something like this might work (untested!):
import pymssql
conn = pymssql.connect(host='SQL01', user='user', password='password', database='mydatabase')
cur = conn.cursor()
# frame is your dataframe
wildcards = ','.join(['?'] * len(frame.columns))
data = [tuple(x) for x in frame.values]
table_name = 'Table'
cur.executemany("INSERT INTO %s VALUES(%s)" % (table_name, wildcards), data)
conn.commit()
Just to save someone else who tried to use this some time. It turns out the line:
wildcards = ','.join(['?'] * len(frame.columns))
should be:
wildcards = ','.join(['%s'] * len(frame.columns))
Hope that helps