I want to connect to two databases using Python and, later on, use tables from both of the databases. How can I do this? Is the following code correct?
con = mdb.connect(host=MY_HOST, user=MY_USER, passwd=MY_PASS, db1=MY_DB1, db2=MY_DB2)
If you don't specify the database in your connect call, you can write queries against multiple databases at once. The documentation says that db is not required.
db = _mysql.connect('localhost', 'user', 'passwd')
then
SELECT u.*, i.* FROM db1.users u LEFT JOIN db2.items i ON u.id = i.user_id
But it'll only work if the two databases are on the same server.
Just make two separate connections
con1 = mdb.connect (host=MY_HOST, user=MY_USER, passwd=MY_PASS, db1=MY_DB1)
con2 = mdb.connect (host=MY_HOST2, user=MY_USER2, passwd=MY_PASS2, db2=MY_DB2)
and use them independently just as you would when using one database.
You have two possibilities:
1) Take the data into a pandas DataFrame and use it to create table in second server.
2) BCP out data from server1 and load it into second server
The two (or more) connections can live in a single variable e.g. a dictionary. This becomes very handy if you want to perform one operation on all the connections at once. For example closing all of them. Here's an example:
connections = {
'conn1': mdb.connect(host, user, passwd, db),
'conn2': mdb.connect(host, user, passwd, db)
}
You can retrieve each connection with its key:
connections['conn1'].execute('SELECT ...')
And you can close all the connections in one line:
[conn.close() for key, conn in connections.items()]
Related
I need to remove any element from a Mongo database when I have two databases:
mydatabase
data-test-second
With the first database this isn't a problem, I use MongoClient:
self.db = self.client.mydatabase
result = self.db.test.delete_one({"name": 'testelement'})
bBt when I use this for a second database I have a problem with:
self.db = self.client.data-test-second
underlining the database name, how I can write this? Or I can't use this solution for the second name?
In the case that your database name is not valid as an object name in Python, you need to address the database differently:
self.db = self.client["data-test-second"]
In general, it is probably advisable to always use this pattern.
For more information, you can refer to the documentation.
I have more than 2 tables in an sqlite3 database. Im trying to INSERT data into one table and update a few columns in another table. Is that possible?
I have tried to user executemany() and executescript() in many shapes and forms. I have recieved a bunch of error messages, and its mostly because execute will not accept my parameters.
with sqlite3.connect('database.db') as conn:
cur = conn.cursor()
cur.executescript("""INSERT INTO prev_users (
imei_prev,
user_id_prev,
start_date,
end_date,
type_prev)
VALUES (?,?,?,?,?);
UPDATE phones
SET owner = (?), date = (?), state = (?)
WHERE imei = (?);
""",(user['imei'], user['user_id'], user['date'], date, user['type'], "None", date, "In Progress", user['imei']))
executescript() will not accept parameters because, well, it doesn't take parameters as an argument, it only takes a "script". From the doc:
executescript(sql_script)
This is a nonstandard convenience method for executing multiple SQL statements at once. It issues a COMMIT statement first, then
executes the SQL script it gets as a parameter.
sql_script can be an instance of str.
For example, it might be used for creating several tables in one script.
executemany() runs one sql against a sequence of parameters.
Neither method is the right tool for the job. You'll likely have to split it into two calls to execute().
I have a MongoDB database that is storing data from ROS topics that my robot is logging. I am trying to print the data in MongoDB by using the following python script:
from pymongo import MongoClient
client = MongoClient('cpr-j100-0101', 62345)
db1 = client.front_scan
db2 = client.cmd_vel
db3 = client.odometry_filtered
print db1
print db2
print db3
but I dont get the result I want when I run this script. I have attached the result of running this script as an image. Instead of this, I would like to actually be able to access the data within mongoDB.enter image description here
You can't print a database before accessing it. First, you need to select what database you need to print. For an example let's think you have 2 collections in db1 as coll1 and coll2. By printing the database means you are going to print the documents of the collections that are in the database.
from pymongo import MongoClient
client = MongoClient('mongodb://localhost:27017/')
db = client.myDatabase
#my dummy database is myDatabase.
coll1 = db.coll1 #selecting the coll1 in myDatabase
for document in coll1.find():
print (document)
so from the above code, you can print all the documents in the coll1 collection of myDatabase. The same manner you can print the databases one by one.
With this script you actually don't do much. You just create three databases and that's basically it. You never insert data, or read data from the database. You're just printing the database object.
I believe, that MongoDB Manual should be useful...
I got a bunch of queries that should be executed in an Access database as a part of my Python script. Unfortunately, queries that used directly in MS Access are giving some records of output, in Python script return nothing (no error either). Connection with database and general syntax should be fine as simple queries (like select one column from table where something) are working just fine. Here is a code with one of these given queries:
import pyodbc
baza = r"C:\base.mdb"
driver = "{Microsoft Access Driver (*.mdb, *.accdb)}"
access_con_string = r"Driver={};Dbq={};".format(driver, baza)
cnn = pyodbc.connect(access_con_string)
db_cursor = cnn.cursor()
expression = """SELECT F_PARCEL.PARCEL_NR, F_PARCEL_LAND_USE.AREA_USE_CD, F_PARCEL_LAND_USE.SOIL_QUALITY_CD, F_ARODES.TEMP_ADRESS_FOREST, F_SUBAREA.AREA_TYPE_CD, F_AROD_LAND_USE.AROD_LAND_USE_AREA, F_PARCEL.COUNTY_CD, F_PARCEL.DISTRICT_CD, F_PARCEL.MUNICIPALITY_CD, F_PARCEL.COMMUNITY_CD, F_SUBAREA.SUB_AREA
FROM F_PARCEL INNER JOIN (F_PARCEL_LAND_USE INNER JOIN ((F_ARODES INNER JOIN F_AROD_LAND_USE ON F_ARODES.ARODES_INT_NUM = F_AROD_LAND_USE.ARODES_INT_NUM) INNER JOIN F_SUBAREA ON F_ARODES.ARODES_INT_NUM = F_SUBAREA.ARODES_INT_NUM) ON (F_PARCEL_LAND_USE.SHAPE_NR = F_AROD_LAND_USE.SHAPE_NR) AND (F_PARCEL_LAND_USE.PARCEL_INT_NUM = F_AROD_LAND_USE.PARCEL_INT_NUM)) ON F_PARCEL.PARCEL_INT_NUM = F_PARCEL_LAND_USE.PARCEL_INT_NUM
WHERE (((F_ARODES.TEMP_ADRESS_FOREST) Like ?) AND ((F_AROD_LAND_USE.AROD_LAND_USE_AREA)<?) AND ((F_ARODES.TEMP_ACT_ADRESS)= ?))
ORDER BY F_PARCEL.PARCEL_NR, F_PARCEL_LAND_USE.SHAPE_NR;"""
rows = db_cursor.execute(expression, ("14-17-2-03*", 0.0049, True)).fetchall()
for row in rows:
print row
cnn.close()
I know that those queries were generated from query builder in MS Access, so I was wondering that maybe this results in differences, but on the other hand this is still access database.
Anyway it seems, that the problem is in SQL, so I would like to know what elements could possibly result in different output between queries executed directly in MS Access and by pyodbc connection?
You are getting tripped up by the difference in LIKE wildcard characters between queries run in Access itself and queries run from an external application.
When running a query from within Access itself you need to use the asterisk as the wildcard character: "14-17-2-03*".
When running a query from an external application (like your Python app) you need to use the percent sign as the wildcard character: "14-17-2-03%".
Searched the web and this forum without satisfaction. Using Python 2.7 and pyODBC on Windows XP. I can get the code below to run and generate two cursors from two different databases without problems. Ideally, I'd then like to join these result cursors thusly:
SELECT a.state, sum(b.Sales)
FROM cust_curs a
INNER JOIN fin_curs b
ON a.Cust_id = b.Cust_id
GROUP BY a.state
Is there a way to join cursors using SQL statements in python or pyODBC? Would I need to store these cursors in a common DB (SQLite3?) to accomplish this? Is there a pure python data handling approach that would generate this summary from these two cursors?
Thanks for your consideration.
Working code:
import pyodbc
#
# DB2 Financial Data Cursor
#
cnxn = pyodbc.connect('DSN=DB2_Fin;UID=;PWD=')
fin_curs = cnxn.cursor()
fin_curs.execute("""SELECT Cust_id, sum(Sales) as Sales
FROM Finance.Sales_Tbl
GROUP BY Cust_id""")
#
# Oracle Customer Data Cursor
#
cnxn = pyodbc.connect('DSN=Ora_Cust;UID=;PWD=')
cust_curs = cnxn.cursor()
cust_curs.execute("""SELECT Distinct Cust_id, gender, address, state
FROM Customers.Cust_Data""")
Cursors are simply objects used for executing SQL commands and retrieving the results. The data aren't migrated in a new database and thus joins aren't possible. If you would like to join the data you'll need to have the two tables in the same database. Whether that means brining both tables and their data into a SQLite database or doing it some other way depends on the specifics of your use case, but that would theoretically work.