How to Connect to CSV Data in Using Python: 6 Steps

The rich ecosystem of Python modules lets you get to work quicker and integrate your systems more effectively. With the CData Linux/UNIX ODBC Driver for CSV and the pyodbc module, you can easily build CSV-connected Python applications. This article shows how to use the pyodbc built-in functions to connect to CSV data, execute queries, and output the results.

How to Use the CData ODBC Drivers on UNIX/Linux

The CData ODBC Drivers are supported in various Red Hat-based and Debian-based systems, including Ubuntu, Debian, RHEL, CentOS, and Fedora. There are also several libraries and packages that are required, many of which may be installed by default, depending on your system. For more information on the supported versions of Linux operating systems and the required libraries, please refer to the "Getting Started" section in the help documentation (installed and found online).

1. Install the Driver Manager

Before installing the driver, check that your system has a driver manager. For this article, you will use unixODBC, a free and open source ODBC driver manager that is widely supported.

For Debian-based systems like Ubuntu, you can install unixODBC with the APT package manager:

$ sudo apt-get install unixodbc unixodbc-dev

For systems based on Red Hat Linux, you can install unixODBC with yum or dnf:

$ sudo yum install unixODBC unixODBC-devel

The unixODBC driver manager reads information about drivers from an odbcinst.ini file and about data sources from an odbc.ini file. You can determine the location of the configuration files on your system by entering the following command into a terminal:

$ odbcinst -j

The output of the command will display the locations of the configuration files for ODBC data sources and registered ODBC drivers. User data sources can only be accessed by the user account whose home folder the odbc.ini is located in. System data sources can be accessed by all users. Below is an example of the output of this command:

DRIVERS............: /etc/odbcinst.ini
SYSTEM DATA SOURCES: /etc/odbc.ini
FILE DATA SOURCES..: /etc/ODBCDataSources
USER DATA SOURCES..: /home/myuser/.odbc.ini
SQLULEN Size.......: 8
SQLLEN Size........: 8
SQLSETPOSIROW Size.: 8

2. Install the Driver

You can download the driver in standard package formats: the Debian .deb package format or the .rpm file format. Once you have downloaded the file, you can install the driver from the terminal.

The driver installer registers the driver with unixODBC and creates a system DSN, which can be used later in any tools or applications that support ODBC connectivity.

For Debian-based systems like Ubuntu, run the following command with sudo or as root:

$ dpkg -i /path/to/package.deb

For Red Hat systems and other systems that support .rpms, run the following command with sudo or as root:

$ rpm -i /path/to/package.rpm

Once the driver is installed, you can list the registered drivers and defined data sources using the unixODBC driver manager:

List the Registered Driver(s)

$ odbcinst -q -d
CData ODBC Driver for CSV
...

List the Defined Data Source(s)

$ odbcinst -q -s
CData CSV Source
...

To use the CData ODBC Driver for CSV with unixODBC, ensure that the driver is configured to use UTF-16. To do so, edit the INI file for the driver (cdata.odbc.csv.ini), which can be found in the lib folder in the installation location (typically /opt/cdata/cdata-odbc-driver-for-csv), as follows:

cdata.odbc.csv.ini

...

[Driver]
DriverManagerEncoding = UTF-16

3. Modify the DSN

The driver installation predefines a system DSN. You can modify the DSN by editing the system data sources file (/etc/odbc.ini) and defining the required connection properties. Additionally, you can create user-specific DSNs that will not require root access to modify in $HOME/.odbc.ini.

Connecting to Local or Cloud-Stored (Box, Google Drive, Amazon S3, SharePoint) CSV Files

CData Drivers let you work with CSV files stored locally and stored in cloud storage services like Box, Amazon S3, Google Drive, or SharePoint, right where they are.

Setting connection properties for local files

Set the URI property to local folder path.

Setting connection properties for files stored in Amazon S3

To connect to CSV file(s) within Amazon S3, set the URI property to the URI of the Bucket and Folder where the intended CSV files exist. In addition, at least set these properties:

• AWSAccessKey: AWS Access Key (username)
• AWSSecretKey: AWS Secret Key

Setting connection properties for files stored in Box

To connect to CSV file(s) within Box, set the URI property to the URI of the folder that includes the intended CSV file(s). Use the OAuth authentication method to connect to Box.

Dropbox

To connect to CSV file(s) within Dropbox, set the URI proprerty to the URI of the folder that includes the intended CSV file(s). Use the OAuth authentication method to connect to Dropbox. Either User Account or Service Account can be used to authenticate.

SharePoint Online (SOAP)

To connect to CSV file(s) within SharePoint with SOAP Schema, set the URI proprerty to the URI of the document library that includes the intended CSV file. Set User, Password, and StorageBaseURL.

SharePoint Online REST

To connect to CSV file(s) within SharePoint with REST Schema, set the URI proprerty to the URI of the document library that includes the intended CSV file. StorageBaseURL is optional. If not set, the driver will use the root drive. OAuth is used to authenticate.

Google Drive

To connect to CSV file(s) within Google Drive, set the URI property to the URI of the folder that includes the intended CSV file(s). Use the OAuth authentication method to connect and set InitiateOAuth to GETANDREFRESH.

/etc/odbc.ini or $HOME/.odbc.ini

[CData CSV Source]
Driver = CData ODBC Driver for CSV
Description = My Description
URI = /PATH/TO/MyCSVFilesFolder

For specific information on using these configuration files, please refer to the help documentation (installed and found online).

You can follow the procedure below to install pyodbc and start accessing CSV through Python objects.

4. Install pyodbc

You can use the pip utility to install the module:

pip install pyodbc

Be sure to import with the module with the following:

import pyodbc

5. Connect to CSV Data

You can now connect with an ODBC connection string or a DSN. Below is the syntax for a connection string:

cnxn = pyodbc.connect('DRIVER={CData ODBC Driver for CSV};URI=/PATH/TO/MyCSVFilesFolder;')

Below is the syntax for a DSN:

cnxn = pyodbc.connect('DSN=CData CSV Sys;')

6. Execute SQL on CSV

Instantiate a Cursor and use the execute method of the Cursor class to execute any SQL statement.

cursor = cnxn.cursor()

Select

You can use fetchall, fetchone, and fetchmany to retrieve Rows returned from SELECT statements:

import pyodbc

cursor = cnxn.cursor()
cnxn = pyodbc.connect('DSN=CData CSV Source;User=MyUser;Password=MyPassword')
cursor.execute("SELECT City, TotalDue FROM Customer WHERE FirstName = 'Bob'")
rows = cursor.fetchall()
for row in rows:
 print(row.City, row.TotalDue)

You can provide parameterized queries in a sequence or in the argument list:

cursor.execute(
 "SELECT City, TotalDue
 FROM Customer
 WHERE FirstName = ?", 'Bob',1)

Metadata Discovery

You can use the getinfo method to retrieve data such as information about the data source and the capabilities of the driver. The getinfo method passes through input to the ODBC SQLGetInfo method.

cnxn.getinfo(pyodbc.SQL_DATA_SOURCE_NAME)

You are now ready to build Python apps in Linux/UNIX environments with connectivity to CSV data, using the CData ODBC Driver for CSV.