Python Oracle Drivereverdownloads

This page provides resources for people looking for ODBC drivers which they can then use with one of the available Python ODBC interfaces.

We group drivers by database backend. Where available, please add the database vendor drivers as first entry in each section.

This time we covered several core areas of the Oracle-Python bridge including PL/SQL stored procedure calls and handling PL/SQL function results. When it comes to Python, you should now be familiar with the essentials of the multiprocessing module which is one of the most important recent additions to the language. Finally, Oracle Berkeley DB. As a first step, get familiar with the basic concepts of Oracle-Python connectivity. Among the core principles of Python's way of doing things there is a rule about having high-level interfaces to APIs. The Database API (in this case the Oracle API) is one example. Python is a popular general purpose dynamic scripting language. With the rise of Frameworks, Python is also becoming common for Web application development. If you want to use Python and an Oracle database, this tutorial helps you get started by giving examples. It is recommended that you complete this OBE first. This time we covered several core areas of the Oracle-Python bridge including PL/SQL stored procedure calls and handling PL/SQL function results. When it comes to Python, you should now be familiar with the essentials of the multiprocessing module which is one of the most important recent additions to the language. Devart Oracle ODBC Driver Works on Windows, Linux, Mac OS X 32/64 bits. Supports Oracle servers: 12c, 11g, 10g, 9i, 8i, 8.0, including Oracle Express Edition 11g and 10g. Supports both x86 and x64 versions of the following Oracle Clients: 12c, 11g, 10g, 9i, 8i, 8.0. EasySoft ODBC Driver for Oracle. OpenLink ODBC Driver for Oracle.

Contents

  1. ODBC Drivers
    1. Drivers by Data Source

Generic Lists

  • SQL Summit list of ODBC drivers and vendors
    This was once the most comprehensive listing of ODBC drivers. Unfortunately, the site stopped working in 2014, so the above is a link to the last archive.org version. Even though it is not updated anymore, it still provides a good overview of where to look for drivers.

  • ODBC Drivers on databasedrivers.comListing of available ODBC drivers. This is also available as list based on database backend.

ODBC Driver Vendors

There are a couple of companies which focus on creating commercial quality ODBC drivers for various backends:

  • Actual Technologies (specialized on Mac OS X)

  • CData Software ODBC Drivers for more than 60 data sources.

  • Devart (Windows, Linux, Mac OS X)

  • DataDirect

  • EasySoft

  • OpenLink

  • Simba Technologies Drivers and driver development tools for Windows, Linux, Mac OS X: SQL Server, Couchbase, MongoDB, Hive, DynamoDB, Redshift, Cassandra, Spark, Impala, BigQuery, HBase, Salesforce.

Drivers by Data Source

Amazon DynamoDB

  • CData ODBC Driver for Amazon DynamoDB

  • Please add new entries here

Amazon SimpleDB

  • CData ODBC Driver for Amazon SimpleDB

  • Please add new entries here

Apache Cassandra

  • CData ODBC Driver for Apache Cassandra

  • Simba Cassandra ODBC driver with SQL connector

  • Please add new entries here

Apache HBase

  • CData ODBC Driver for Apache HBase

  • Please add new entries here

Apache Hive

  • Simba Hive ODBC driver with SQL connector

  • Please add new entries here

Authorize.Net

  • CData ODBC Driver for Authorize.Net

  • Please add new entries here

Azure Management

  • CData ODBC Driver for Azure Management

  • Please add new entries here

Azure Table

  • CData ODBC Driver for Azure Table

  • Please add new entries here

Couchbase

  • CData ODBC Driver for Couchbase Server

  • Simba Couchbase ODBC driver with SQL connector

  • Please add new entries here

CSV/TSV Files

  • CData ODBC Driver for CSV/TSV Files

  • Please add new entries here

E*TRADE

  • CData ODBC Driver for E*TRADE

  • Please add new entries here

Email

  • CData ODBC Driver for Email

  • Please add new entries here

Exact Online

  • CData ODBC Driver for Exact Online

  • Please add new entries here

Facebook

  • CData ODBC Driver for Facebook

  • Please add new entries here

FreshBooks Accounting

  • CData ODBC Driver for FreshBooks Accounting

  • Please add new entries here

Firebird (and Interbase)

  • Devart Firebird ODBC Driver
    Works on Windows, Linux, Mac OS X 32/64 bits.
    Supports Firebird server and client versions 2.x, 1.x.

  • Devart Interbase ODBC Driver
    Works on Windows, Linux, Mac OS X 32/64 bits.
    Supports all the InterBase server and client versions.

  • Please add new entries here

Gmail

  • CData ODBC Driver for Gmail

  • Please add new entries here

Google AdWords

  • CData ODBC Driver for Google AdWords

  • Please add new entries here

Google Analytics

  • CData ODBC Driver for Google Analytics

  • Please add new entries here

Google Apps

  • CData ODBC Driver for Google Apps

  • Please add new entries here

Google BigQuery

  • CData ODBC Driver for Google BigQuery

  • Please add new entries here

Google Sheets

  • CData ODBC Driver for Google Sheets

  • Please add new entries here

HPCC ECL Queries

  • CData ODBC Driver for HPCC ECL Queries

  • Please add new entries here

HubSpot

  • CData ODBC Driver for HubSpot

  • Please add new entries here

IBM DB2

  • IBM DB2 ODBC driver for Windows and Unix
    Come with IBM DB2, but can also be downloaded separately. Supports Windows and Unix.

  • IBM ODBC Driver for Linux on iSeries / AS/400 DB2 servers

  • DataDirect ODBC Driver for IBM DB2

  • OpenLink ODBC Driver for IBM DB2

  • Please add new entries here

IBM Informix

  • Please add new entries here

IBM Netezza

  • Netezza ODBC driver

    Since IBM acquired Netezza, the ODBC drivers are only available to customers with active support contracts. If you have one, you can download the driver as part of the software bundles from IBM FixCentral (search for 'Netezza').

  • Please add new entries here

Ingres

  • Please add new entries here

Intacct

  • CData ODBC Driver for Intacct

  • Please add new entries here

JSON Services

  • CData ODBC Driver for JSON Services

  • Please add new entries here

LDAP Directory Services

  • CData ODBC Driver for LDAP Directory Services

  • Please add new entries here

MailChimp

  • CData ODBC Driver for MailChimp

  • Please add new entries here

MariaDB

MariaDB is a fork of MySQL.

  • MariaDB ODBC Driver

  • Devart MariaDB ODBC Driver
    Works on Windows, Linux, Mac OS X 32/64 bits.
    Supports MariaDB 5.x. LGPLed ODBC driver for Windows.

  • Please add new entries here

Marketo

  • CData ODBC Driver for Marketo

  • Please add new entries here

Microsoft Access

  • Please add new entries here

Microsoft Active Directory

  • CData ODBC Driver for Microsoft Active Directory

  • Please add new entries here

Microsoft Dynamics CRM

  • CData ODBC Driver for Microsoft Dynamics CRM Antares autotune mac crack download.

  • Please add new entries here

Microsoft Dynamics GP

  • CData ODBC Driver for Microsoft Dynamics GP

  • Please add new entries here

Microsoft Dynamics NAV

  • CData ODBC Driver for Microsoft Dynamics NAV

  • Please add new entries here

Microsoft Exchange

  • CData ODBC Driver for Microsoft Exchange

  • Please add new entries here

Microsoft Project

  • CData ODBC Driver for Microsoft Project

  • Please add new entries here

Microsoft SharePoint

  • CData ODBC Driver for Microsoft SharePoint

  • Please add new entries here

Oracle Drivers Free Download

Microsoft SQL Server

  • MS SQL Server Native Client for SQL Server 2005, 2008 and later
    Free, supported by Microsoft and available for Windows and 64-bit Linux.

  • Actual Technologies Mac OS X ODBC Driver for SQL Server

  • DataDirect ODBC Driver for SQL Server

  • Devart SQL Server ODBC Driver
    Works on Windows, Linux, Mac OS X 32/64 bits.
    Compatible with SQL Server 2014, SQL Server 2012, SQL Server 2008 R2, SQL Server 2008, SQL Server 2005, SQL Server 2000 (including MSDE), SQL Server 7, SQL Server Compact 4.0, 3.5, 3.1

  • EasySoft ODBC Driver for SQL Server

  • FreeTDS Unix ODBC Driver for SQL Server
    Open-source TDS protocol client library, which comes with an ODBC driver. The TDS protocol is used by SQL Server and Sybase ASE.

  • OpenLink ODBC Driver for SQL Server

  • Simba SQL Server ODBC drivers Supports Linux, Mac and Windows. Available in client and server (two-tier) versions.

  • Please add new entries here

Python

MongoDB

  • CData ODBC Driver for MongoDB

  • Simba MongoDB ODBC driver with SQL connector

  • Please add new entries here

MySQL

  • MySQL ODBC Driver GPLed ODBC driver for Windows, Linux, Mac OS X, and Unix platforms.

  • Actual Technologies Mac OS X ODBC Driver for MySQL

  • CData ODBC Driver for MySQL

  • DataDirect ODBC Driver for MySQL

  • Devart MySQL ODBC Driver
    Works on Windows, Linux, Mac OS X 32/64 bits.
    Supports MySQL servers: 6.0, 5.6, 5.5, 5.1, 5.0, 4.1, 4.0, and 3.23

  • OpenLink ODBC Driver for MySQL

  • Please add new entries here

NetSuite CRM & ERP

  • CData ODBC Driver for NetSuite CRM & ERP

  • Please add new entries here

OData Services

  • CData ODBC Driver for OData Services

  • Please add new entries here

Office 365

  • CData ODBC Driver for Office 365

  • Please add new entries here

OFX Financial Accounts

  • CData ODBC Driver for OFX Financial Accounts

  • Please add new entries here

Oracle

  • Oracle Instant Client ODBC driver
    Free, supported by Oracle. Works on Windows, Linux, Mac OS X, AIX, z/Linux, Solaris, HP-UX.

  • Actual Technologies Mac OS X ODBC Driver for Oracle

  • DataDirect ODBC Driver for Oracle

  • Devart Oracle ODBC Driver
    Works on Windows, Linux, Mac OS X 32/64 bits.
    Supports Oracle servers: 12c, 11g, 10g, 9i, 8i, 8.0, including Oracle Express Edition 11g and 10g.
    Supports both x86 and x64 versions of the following Oracle Clients: 12c, 11g, 10g, 9i, 8i, 8.0.

  • EasySoft ODBC Driver for Oracle

  • OpenLink ODBC Driver for Oracle

  • Please add new entries here

Oracle Eloqua

  • CData ODBC Driver for Oracle Eloqua

  • Please add new entries here

PayPal

  • CData ODBC Driver for PayPal

  • Please add new entries here

PowerShell

  • CData ODBC Driver for PowerShell

  • Please add new entries here

PreEmptive Analytics

  • CData ODBC Driver for PreEmptive Analytics

  • Please add new entries here

PostgreSQL

  • PostgreSQL ODBC Driver]
    Open-source driver developed as part of the PostgreSQL project.

  • Actual Technologies Mac OS X ODBC Driver for PostgreSQL

  • DataDirect ODBC Driver for PostgreSQL

  • Devart PostgreSQL ODBC Driver
    Works on Windows, Linux, Mac OS X 32/64 bits.
    Supports PostgreSQL server versions since 7.1 up to 9.4.

  • EasySoft ODBC Driver for PostgreSQL

  • OpenLink ODBC Driver for PostgreSQL

  • Please add new entries here

Quandl

  • CData ODBC Driver for Quandl

  • Please add new entries here

Reckon

  • CData ODBC Driver for Reckon

  • Please add new entries here

RSS Feeds

  • CData ODBC Driver for RSS Feeds

  • Please add new entries here

SAP ASE / Sybase ASE

  • SAP/Sybase ASE ODBC driver
    The ASE ODBC driver comes as part of the ASE installer. Simply select the ODBC driver when running the installer on a client.

  • Actual Technologies Mac OS X ODBC Driver for SQL Server

  • DataDirect ODBC Driver for SQL Server

  • EasySoft ODBC Driver for SQL Server

  • FreeTDS Unix ODBC Driver for SQL Server
    Open-source TDS protocol client library, which comes with an ODBC driver. ASE talks TDS on the wire and the FreeTDS driver also supports ASE.

  • OpenLink ODBC Driver for SQL Server

  • Please add new entries here

SAP DB / MaxDB

  • MaxDB ODBC Driver
    The driver comes as part of the MaxDB downloads.

  • Please add new entries here

SAP NetWeaver

  • CData ODBC Driver for SAP NetWeaver

  • Please add new entries here

Sage 50 UK

  • CData ODBC Driver for Sage 50 UK

  • Please add new entries here

Salesforce & Force.com

  • CData ODBC Driver for Salesforce & Force.com

  • Please add new entries here

SharePoint Excel Services

  • CData ODBC Driver for SharePoint Excel Services

  • Please add new entries here

Smartsheet.com

  • CData ODBC Driver for Smartsheet.com

  • Please add new entries here

Spark

  • Simba Spark ODBC driver with SQL connector

  • Please add new entries here

Square

  • CData ODBC Driver for Square

  • Please add new entries here

Sugar

  • CData ODBC Driver for Sugar

  • Please add new entries here

Teradata

  • Teradata ODBC Driver
    ODBC driver is available for Windows, Linux, Solaris, AIX, HP-UX and Mac.

  • DataDirect ODBC Driver for Teradata

  • Please add new entries here

Twilio

  • CData ODBC Driver for Twilio

  • Please add new entries here

Twitter

  • CData ODBC Driver for Twitter

  • Please add new entries here

xBase

  • CData ODBC Driver for xBase

  • Please add new entries here

XML Files

  • CData ODBC Driver for XML Files

  • Please add new entries here

Xero Accounting

  • CData ODBC Driver for Xero Accounting

  • Please add new entries here

YouTube

  • CData ODBC Driver for YouTube

  • Please add new entries here

YouTube Analytics

  • CData ODBC Driver for YouTube Analytics

  • Please add new entries here

Zoho CRM

  • CData ODBC Driver for Zoho CRM

  • Please add new entries here

Oracle offers some very powerful utilities for loading, processing, and unloading data. SQL*Loader, Data Pump, external tables, Oracle Text, regular expressions—it's all there. Yet there is often a need to do things outside the database (or, trivially, perhaps you just weren't granted the necessary database privileges).

Python delivers possibilities for efficient data parsing at a high level. The extensive standard library and many modules available for free on the Internet make it possible to work with data logic rather than dissecting bytes by hand.

String Theory

At the lowest level of text parsing are strings. Python doesn't differentiate characters as separate datatypes but distinguishes between regular and Unicode string types. They can be enclosed in single, double, or triple quotes and are one of Python's immutable objects—consequently you cannot change them once they are created. Each operation creates a new string object in-place. For programmers with statically-typed language experience this may sound really odd at first, but there are certain reasons for such an implementation, mostly concerning performance.

As Python fully supports Unicode, processing multi-language information is not a problem. When creating Unicode strings manually either use the u prefix directly before the string like (as in u'Unicode text') or use the built-in unicode() function. Strings can be encoded in any supported character set using the unicode() or encode() methods. For a list of supported encodings please consult the Standard Encodings section of the Python Library Reference or use import encodings; print encodings._aliases.keys().

You can safely write Python programs in UTF-8, remembering that only variable names must be valid ASCII strings. Comments can be Greek, strings Chinese, or whatever. There is however a requirement that such a file should be either saved with an editor that prepends a Byte Order Mark (BOM), or alternatively you can make the very first code line:

# -*- coding: utf-8 -*-

Strings come with a set of methods for most useful text operations such as find(), split(), rjust() or upper(). They are implemented on the built-in str type which represents both regular and raw strings. (Raw strings interpret backslashes differently to regular strings.)

One of the greatest features of Python iterable types is the method of indexing. Regular indexes starts with zero while negative indexes count backwards, so [-1] denotes the last character, [:5] the first five characters and [5:-5] means strip five leading and five trailing characters.

Regular Expressions

Regular expressions, of course, are supported in Python. In fact Python's regular expression re module supports Unicode, matching, searching, splitting, replacing and grouping. If you are familiar with Oracle's implementation of regular expressions you will be right at home with Python's functions.

When evaluating the Python and Oracle implementations of regular expressions head-to-head, the noticeable differences include:

  • re.search() can be used in place of Oracle's REGEXP_LIKE, REGEXP_INSTR and REGEXP_SUBSTR, the case is that relational design requires a different approach from programming language one.
  • re.sub() and REGEXP_REPLACE are equivalent to the point that Python syntax can be adapted to be used in the exact same manner as REGEXP_REPLACE. Notice however that Oracle's position parameter starts at 1 whereas Python indexes everything from 0.
  • Oracle's match_parameter represents a set of flags for a regular expression in the same manner Python uses the (?iLmsux) syntax inside search patterns or pattern object compilation attributes. For a list of valid flags please compare the 4.2.3 section of Python Library Reference with a list of valid values for the match_parameter in the Oracle Database SQL Language Reference.

Python's re.search() function is very flexible due to the fundamental concepts of regular expressions. At the lowest level of the re module there is an object that represents matched patterns in a manner that allows dissecting the source string in many different ways. The re.compile() function returns a compiled pattern object taking a pattern and optional flags such as re.I, which represents case-insensitive matching.

You are not required to compile regular expressions explicitly. Functions in the re module do this transparently. It's good to have compiled patterns when they are to be used in several places in the code but those that are used only once don't require such coding overhead.

There are six regular expression compilation flags in Python:

  • I (IGNORECASE) for case-insensitive matching
  • L (LOCALE) makes special sequences such as words and white-space locale-dependent
  • M (MULTILINE) means searching for the pattern in multiple lines so that ˆ matches the start of the string and after each newline, and $ matches before each newline and the end of the string
  • S (DOTALL) forces dot special character (.) to match any character, including newline
  • U (UNICODE) makes special sequences Unicode-aware
  • X (VERBOSE) lets you write regular expressions in a more readable form.
Oracle

To use several flags at once, simply sum them—e.g. re.compile('Oracle', re.I+re.S+re.M). Another way to use flags is to prefix the search pattern with (?iLmsux) using the desired number of options. The previous expression can be rewritten as re.compile('(?ism)Oracle').

The best advice for using regular expressions is to avoid them if possible. Before embedding them in your code, please make sure that there are no string methods that do the same job, because string methods are faster and bring no extra overhead of the import and regular expression processing. Just use dir() on a string object to see what's available.

The following example illustrates the way to think about regular expressions in a such dynamic language as Python. Consider parsing a tnsnames.ora file to create Easy Connect strings for each network alias (point the file() function to the location of your tnsnames.ora file):

The output of this program on Oracle Database XE's default tnsnames.ora file is:

{'XE': 'localhost:1521/XE'}

Please note that this regular expression is dumb enough to choke on IPC entries so they need to be placed at the end of the file. Parsing matching parenthesis is one of the NP-complete problems.

Python match objects are very powerful because of the exposed methods including span(), which returns the matched range; group(), which returns a matched group by a given index; and groupdict(), which returns matched groups as a dictionary when the pattern contains named groups.

Comma Separated Values

The CSV format is popular for exchanging information between organizations due to its simplicity and cross-platform design. Comma separated values can often be easily parsed with regular expressions but the task is made even easier with Python's csv module.

Working with the module requires developers to familiarize themselves with the logic behind it. The fundamental information about a CSV file is its 'dialect,' which contains information about delimiters, quote characters, line terminators, etc. The currently available dialects in Python 2.5 are excel and excel-tab. The built-in sniffer always tries to guess the right format. Reader and writer objects enable input and output of CSV data.

For this example I am using data from the JOBS_HISTORY table of the HR schema. It illustrates how to create a CSV file job_history.csv directly from a SQL query.

The file contains:

Alternatively you could export the data in CSV format using Oracle SQL Developer.

The CSV file can be read with:

Note that I didn't have to specify the dialect explicitly above; it was automatically deduced. I only printed the job_id column but what I really could do with such parsed file is insert it into the database. To make sure dates are handled correctly, NLS_DATE_FORMAT is set manually before bulk insertion.

If you used SQL Developer to create the CSV file, you may need to change the date format instead like:

>>> cursor.execute('ALTER SESSION SET NLS_DATE_FORMAT = 'YY/MM/DD')

What takes the csv module a bit imperfect is the lack of native Unicode support. For a solution and more examples of working with CSV files.

Oracle Driver Download

URLs

The urlparse module lets you break Uniform Resource Locator strings into components representing the URL scheme, network location, path, parameters, query string, fragment identifier, username, password, hostname and/or port. Python 2.5 supports as many as 24 of the most popular schemes, including svn+ssh, sftp and mms. This example shows some features of urlparse module:

RSS Feeds

The concept underlying RSS is quite simple: You get the latest news as it happens, not by spotting it accidentally. Consolidating RSS feeds from many different sources is a popular trend in development, especially for news feeds aggregators and Web 2.0 mashups.

RSS is a dialect of XML so it could be easily processed with one of the XML parsers available for Python. The Python standard library doesn't offer a module for parsing feeds natively yet; however, there is a solid, widely-tested Universal Feed Parser available for free at feedparser.org. As it has no external dependencies, this is a good chance to quickly familiarize ourselves with module installation concepts.

After downloading the latest version (4.1 at the time of writing) of the feedparser module, unpack it and change the working directory to feedparser-4.1. At the console/command prompt run python setup.py install. This command will put the module into the Python folder and make it available for instant use. That's it.

How about checking what happened at Oracle lately?

The feedparser module is smart enough to properly parse the date, sanitize HTML markup, normalize content so a consistent API for all supported RSS and ATOM variants can be used, resolve relative links, detect valid character encoding, and much more.

Parse What Next?

Equipped with a regular expression toolbox you can search for nearly any content as long as it is plain text. When it comes to parsing text data, Python has many other features including:

  • email.parse for parsing e-mail messages
  • ConfigParser for parsing INI configuration files known from Windows systems
  • robotparser module for parsing robots.txt of your Web sites
  • optparse module for powerful command line argument parsing
  • HTMLParse class in the HTMLParse module for parsing HTML and XHTML effectively (SAX-like)
  • Several XML parsers (xml.dom, xml.sax, xml.parsers.expat, xml.etree.ElementTree)

For binary data you can leverage the binascii module, which contains a set of functions for converting between binary- and ASCII-encoded data, accompanied by the base64 and uu modules for base64 and uuencode transformations, respectively.

Conclusion

This HowTo introduced some basic and more advanced techniques for parsing data in Python. You should now be aware of the power of the standard library that Python ships with. Before starting cooking your own parser, the first step is to check if the desired functionality is already available for import.

String operations are faster than regular expression operations and sufficient for many programming needs. But the decision whether to use Python or Oracle regular expression functions depends on your application logic and business requirements.

Python Oracle Driver Ever Downloads Windows 7

Przemyslaw Piotrowski is an information technology specialist working with emerging technologies and dynamic, agile development environments. Having a strong IT background that includes administration, development and design, he finds many paths of software interoperability.