![]() ![]() NVIDIA has released alternate graphics drivers for OS X El Capitan 10.11.6. NOTE: These drivers are currently the only method to get full acceleration for NVIDIA GeForce GTX 750, 750 Ti, 950, 960, 970, 980, 980 Ti, and TITAN X 'Maxwell' graphics cards. ![]() ![]() These are separate from the drivers Apple ships as standard, and should be considered experimental. There are no current Macs with these cards, so support is absent natively in OS X. I do have others installed, not all of which might be 64bit, but in your case if Actual is the only one installed and you are on the latest release it should be 64bit capable. $ lipo -info 'Actual Open Source Databases' Hp printer drivers for mac.Īrchitectures in the fat file: Actual Open Source Databases are: i386 ppc7400 x86_64 ppc64 I just downloaded and installed v4.0 of the Actual Open Source Database drivers, and they appear to BE 64bit. I am not sure this is the whole source of the problem, despite Microsoft's articles. ![]() I don't get it, it sure doesn't seem that it should be expected, and shouldn't even be tolerated. Their articles I linked to actually tell you Excel will crash, this seems to be 'Expected behavior' in this case. execute ( "update Test set class=? where someField=1234", prediction ) connection. Unfortunately though, it’s not as easy as doing a DataFrame.to_sql because there is no SQLAlchemy support for FileMaker.įor my use case I only needed to write single values back, so I ended up building the SQL query “by hand”: cursor. Of course you can also write data back to FileMaker via ODBC. read_sql ( "select field1,field2 from Test", connection ) print df #=> Should print something like this: # field1 field2 #0 5.1 3.5 #1 4.9 3.0 #. But what is even easier is to use Pandas’ read_sql, which you can feed a SQL statement and a connection and get a DataFrame back, like this: df = pd. At first I wrote a function to process the cursor and map the data to a DataFrame myself. Now that we have access to our data, we want to work with it. Transform the data into a Pandas DataFrame execute ( "select field1,field2 from Test" ) for row in rows : print row #=> Should print something like this: #(5.1, 3.5) #(4.9, 3.0) #. connect ( connectionString ) cursor = connection. import pyodbc connectionString = "DSN=TestDSN UID=python PWD=python" connection = pyodbc. We will import pyodbc, setup our connection string with the DSN name, FileMaker account name and password (just like we defined it in ODBC Manager and FileMaker), execute our SQL statement, print the result, and – important – close the connection. Let’s switch to our editor and write some code. If you have trouble, here’s a pre-built package provided by Actual Technologies. Watch out: when you compile it, you need to link it with the iODBC libraries instead of the unixODBC libraries. Either install it via pip install pyodbc or build it yourself. To connect to our FileMaker database we need the open source Python module pyodbc. We give it a name, set the host (in our case localhost) and choose the database we want to connect to (before finishing the wizard, click on “Test” to verify the connection is OK). The process of configuring the DSN is straight forward. Click on “Add” in either the User DSN or System DSN section and select FileMaker ODBC as the driver. In the ODBC Manager we can now create our data source name (DSN). For that we open the menu under File -> Sharing -> Enable ODBC/JDBC…, switch ODBC/JDBC Sharing on and then allow all users or the users of the privilege set that we have created in the previous step. It is important that we check the fmxdbc extended privilege for the chosen privilege set. Create a new user account (we will use that for our connection string later on) in FileMaker and assign it a privilege set (if you’re just testing, choose the to prevent access rights issues). Now that the driver is installed we need to prepare the actual FileMaker file for being accessed via ODBC. After a successful installation, we should be able to see it in our ODBC Manager. FileMaker Pro 15 Advanced/Extras/xDBC/ODBC Client Driver Installer/FileMaker ODBC.pkg To connect to FileMaker via ODBC we need the FileMaker ODBC driver.
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