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PYTHON CONNECT TO ORACLE DATABASE INSTALL
The basiclite version of the client is more than enough, no need to install any other “bigger” client (except if you need some of the TNS tools or SQL*Plus). Installing the Oracle Client is pretty easy as it’s available in YUM.
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“Cannot locate Oracle Client” is all I read from this error at first …. cx_Oracle still needs an Oracle Client to be available on the same server where Python is running. Once the package is installed, I’m ready to go again, except that now the error is at the connection step. I can use the terminal available inside JupyterLab to run PIP and install cx_Oracle. Still it has to be installed!Īll it takes is: pip install cx_Oracle into my Python virtual environment where JupyterLab is installed (installing on the system Python wouldn’t make it available inside the virtual environment). It’s well documented and widely used with many blog posts and tutorials about it. To connect Python to an Oracle Database cx_Oracle is the official package to use. A missing package is a typical error as I don’t pre-install by default tons of packages.
PYTHON CONNECT TO ORACLE DATABASE PASSWORD
I don’t expect any issue: the username and password for the database work in SQL Developer, the hostname, port and service name come directly from the DBaaS page where I manage the service. Simple test: connect, query, get results, disconnect. To test my connection, I have an extremely simple code: connect, run a query, get the result, disconnect. The compute instance running Python (in JupyterLab) is in the same exact VCN and subnet. The DBaaS instance is connected to the VCN datalysisvcn1 and the subnet Public Subnet bBBw:EU-ZURICH-1-AD-1. Just like 2 servers being next to each other and connected to the same dumb switch. To keep things simple, I’m using a Compute Instance running in the same exact Virtual Cloud Network and subnet as my database, to avoid any networking issue: the 2 instances are connected to the same network with nothing supposed to block the communication. But patched and maintained not by me manually via SSH but via the cloud web interface.Ĭlassic was the original, older kind of cloud infrastructure, and isn’t available for new instances anymore (at least for me clicking it send me to some generic content). This is what I’m using: just a database running in a VM. The not autonomous part is either named Database or Bare Metal, VM, and Exadata depending which page you look at. It works well for many things but still doesn’t support property graphs (work in progress…) and that’s why I use something else. The autonomous is split into Autonomous Data Warehouse and Autonomous Transaction Processing. To me it’s like there are 2 types mainly: autonomous and not autonomous. There are various different database products in the Oracle Cloud offer, and sometime they also use different names to link to the same thing (depending which page you are on). How can I connect from Python (my JupyterLab notebook) to an Oracle DBaaS database? Must be easy using cx_Oracle, the Python interface for Oracle database. For that I often use an Oracle database as source for my data, and it’s also a cloud service. Now that I have it, I obviously want to use it for some experiments with Machine Learning and graphs.
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I wrote about setting up a JupyterLab sandbox in an Oracle Cloud Compute Instance not long ago.