jiangchenan/python-driver: Teradata SQL Driver for Python · GitHub

This package enables Python applications to connect to the Teradata Database.

This package implements the PEP-249 Python Database API Specification 2.0.

This package requires 64-bit Python 3.4 or later, and runs on Windows, macOS, and Linux. 32-bit Python is not supported.

For community support, please visit Teradata Community.

For Teradata customer support, please visit Teradata Customer Service.

Please note, this driver may contain beta/preview features ("Beta Features"). As such, by downloading and/or using the driver, in addition to agreeing to the licensing terms below, you acknowledge that the Beta Features are experimental in nature and that the Beta Features are provided "AS IS" and may not be functional on any machine or in any environment.

Copyright 2022 Teradata. All Rights Reserved.

• Features
• Limitations
• Installation
• License
• Documentation
• Sample Programs
• Using the Driver
• Connection Parameters
• COP Discovery
• Stored Password Protection
• Client Attributes
• Transaction Mode
• Auto-Commit
• Data Types
• Null Values
• Character Export Width
• Module Constructors
• Module Globals
• Module Exceptions
• Connection Methods
• Cursor Attributes
• Cursor Methods
• Type Objects
• Escape Syntax
• FastLoad
• FastExport
• CSV Batch Inserts
• CSV Export Results
• Change Log

Table of Contents links do not work on PyPI due to a PyPI limitation.

The Teradata SQL Driver for Python is a DBAPI Driver that enables Python applications to connect to the Teradata Database. The driver implements the PEP-249 Python Database API Specification 2.0.

The driver is a young product that offers a basic feature set. We are working diligently to add features to the driver, and our goal is feature parity with the Teradata JDBC Driver.

At the present time, the driver offers the following features.

• Supported for use with Teradata Database 14.10 and later releases. Informally tested to work with Teradata Database 12.0 and later releases.
• COP Discovery.
• Laddered Concurrent Connect.
• HTTPS/TLS connections with Teradata SQL Engine 16.20.53.30 and later.
• Encrypted logon using the TD2, JWT, LDAP, KRB5 (Kerberos), or TDNEGO logon mechanisms.
• Data encryption governed by central administration, or enabled via the encryptdata connection parameter.
• Unicode character data transferred via the UTF8 session character set.
• Auto-commit for ANSI and TERA transaction modes.
• 1 MB rows supported with Teradata Database 16.0 and later.
• Multi-statement requests that return multiple result sets.
• Most JDBC escape syntax.
• Parameterized SQL requests with question-mark parameter markers.
• Parameterized batch SQL requests with multiple rows of data bound to question-mark parameter markers.
• Complex data types such as XML, JSON, DATASET STORAGE FORMAT AVRO, and DATASET STORAGE FORMAT CSV.
• ElicitFile protocol support for DDL commands that create external UDFs or stored procedures and upload a file from client to database.
• CREATE PROCEDURE and REPLACE PROCEDURE commands.
• Stored Procedure Dynamic Result Sets.
• FastLoad and FastExport.

• The UTF8 session character set is always used. The charset connection parameter is not supported.
• No support yet for Recoverable Network Protocol and Redrive.
• Monitor partition support is not available yet.

The driver depends on the pycryptodome package which is available from PyPI.

Use pip install to download and install the driver and its dependencies automatically.

When upgrading to a new version of the driver, you may need to use pip install's --no-cache-dir option to force the download of the new version.

Use of the driver is governed by the License Agreement for the Teradata SQL Driver for Python.

When the driver is installed, the LICENSE and THIRDPARTYLICENSE files are placed in the teradatasql directory under your Python installation directory.

In addition to the license terms, the driver may contain beta/preview features ("Beta Features"). As such, by downloading and/or using the driver, in addition to the licensing terms, you acknowledge that the Beta Features are experimental in nature and that the Beta Features are provided "AS IS" and may not be functional on any machine or in any environment.

When the driver is installed, the README.md file is placed in the teradatasql directory under your Python installation directory. This permits you to view the documentation offline, when you are not connected to the Internet.

The README.md file is a plain text file containing the documentation for the driver. While the file can be viewed with any text file viewer or editor, your viewing experience will be best with an editor that understands Markdown format.

Sample programs are provided to demonstrate how to use the driver. When the driver is installed, the sample programs are placed in the teradatasql/samples directory under your Python installation directory.

The sample programs are coded with a fake database hostname whomooz, username guest, and password please. Substitute your actual database hostname and credentials before running a sample program.

Your Python script must import the teradatasql package in order to use the driver.

import teradatasql

After importing the teradatasql package, your Python script calls the teradatasql.connect function to open a connection to the database.

You may specify connection parameters as a JSON string, as kwargs, or using a combination of the two approaches. The teradatasql.connect function's first argument is an optional JSON string. The teradatasql.connect function's second and subsequent arguments are optional kwargs.

Connection parameters specified only as kwargs:

con = teradatasql.connect(host="whomooz", user="guest", password="please")

Connection parameters specified only as a JSON string:

con = teradatasql.connect('{"host":"whomooz","user":"guest","password":"please"}')

Connection parameters specified using a combination:

con = teradatasql.connect('{"host":"whomooz"}', user="guest", password="please")

When a combination of parameters are specified, connection parameters specified as kwargs take precedence over same-named connection parameters specified in the JSON string.

The following table lists the connection parameters currently offered by the driver. Connection parameter values are case-sensitive unless stated otherwise.

Our goal is consistency for the connection parameters offered by this driver and the Teradata JDBC Driver, with respect to connection parameter names and functionality. For comparison, Teradata JDBC Driver connection parameters are documented here.

The driver provides Communications Processor (COP) discovery behavior when the cop connection parameter is true or omitted. COP Discovery is turned off when the cop connection parameter is false.

A database system can be composed of multiple database nodes. One or more of the database nodes can be configured to run the database Gateway process. Each database node that runs the database Gateway process is termed a Communications Processor, or COP. COP Discovery refers to the procedure of identifying all the available COP hostnames and their IP addresses. COP hostnames can be defined in DNS, or can be defined in the client system's hosts file. Teradata strongly recommends that COP hostnames be defined in DNS, rather than the client system's hosts file. Defining COP hostnames in DNS provides centralized administration, and enables centralized changes to COP hostnames if and when the database is reconfigured.

The coplast connection parameter specifies how COP Discovery determines the last COP hostname.

• When coplast is false or omitted, or COP Discovery is turned off, then the driver will not perform a DNS lookup for the coplast hostname.
• When coplast is true, and COP Discovery is turned on, then the driver will first perform a DNS lookup for a coplast hostname to obtain the IP address of the last COP hostname before performing COP Discovery. Subsequently, during COP Discovery, the driver will stop searching for COP hostnames when either an unknown COP hostname is encountered, or a COP hostname is encountered whose IP address matches the IP address of the coplast hostname.

Specifying coplast as true can improve performance with DNS that is slow to respond for DNS lookup failures, and is necessary for DNS that never returns a DNS lookup failure.

When performing COP Discovery, the driver starts with cop1, which is appended to the database hostname, and then proceeds with cop2, cop3, ..., copN. The driver supports domain-name qualification for COP Discovery and the coplast hostname. Domain-name qualification is recommended, because it can improve performance by avoiding unnecessary DNS lookups for DNS search suffixes.

The following table illustrates the DNS lookups performed for a hypothetical three-node database system named "whomooz".

Round-robin DNS rotates the list of IP addresses automatically to provide load distribution. Round-robin is only possible with DNS, not with the client system hosts file.

The driver supports the definition of multiple IP addresses for COP hostnames and non-COP hostnames.

For the first connection to a particular database system, the driver generates a random number to index into the list of COPs. For each subsequent connection, the driver increments the saved index until it wraps around to the first position. This behavior provides load distribution across all discovered COPs.

The driver masks connection failures to down COPs, thereby hiding most connection failures from the client application. An exception is thrown to the application only when all the COPs are down for that database. If a COP is down, the next COP in the sequence (including a wrap-around to the first COP) receives extra connections that were originally destined for the down COP. When multiple IP addresses are defined in DNS for a COP, the driver will attempt to connect to each of the COP's IP addresses, and the COP is considered down only when connection attempts fail to all of the COP's IP addresses.

If COP Discovery is turned off, or no COP hostnames are defined in DNS, the driver connects directly to the hostname specified in the host connection parameter. This permits load distribution schemes other than the COP Discovery approach. For example, round-robin DNS or a TCP/IP load distribution product can be used. COP Discovery takes precedence over simple database hostname lookup. To use an alternative load distribution scheme, either ensure that no COP hostnames are defined in DNS, or turn off COP Discovery with cop as false.

Stored Password Protection enables an application to provide a connection password in encrypted form to the driver.

An encrypted password may be specified in the following contexts:

• A login password specified as the password connection parameter.
• A login password specified within the logdata connection parameter.

If the password, however specified, begins with the prefix ENCRYPTED_PASSWORD( then the specified password must follow this format:

ENCRYPTED_PASSWORD(file:PasswordEncryptionKeyFileName,file:EncryptedPasswordFileName)

Each filename must be preceded by the file: prefix. The PasswordEncryptionKeyFileName must be separated from the EncryptedPasswordFileName by a single comma.

The PasswordEncryptionKeyFileName specifies the name of a file that contains the password encryption key and associated information. The EncryptedPasswordFileName specifies the name of a file that contains the encrypted password and associated information. The two files are described below.

Stored Password Protection is offered by this driver, the Teradata JDBC Driver, and the Teradata SQL Driver for R. These drivers use the same file format.

TJEncryptPassword.py is a sample program to create encrypted password files for use with Stored Password Protection. When the driver is installed, the sample programs are placed in the teradatasql/samples directory under your Python installation directory.

This program works in conjunction with Stored Password Protection offered by the driver. This program creates the files containing the password encryption key and encrypted password, which can be subsequently specified via the ENCRYPTED_PASSWORD( syntax.

You are not required to use this program to create the files containing the password encryption key and encrypted password. You can develop your own software to create the necessary files. You may also use the TJEncryptPassword.java sample program that is available with the Teradata JDBC Driver Reference. The only requirement is that the files must match the format expected by the driver, which is documented below.

This program encrypts the password and then immediately decrypts the password, in order to verify that the password can be successfully decrypted. This program mimics the password decryption of the driver, and is intended to openly illustrate its operation and enable scrutiny by the community.

The encrypted password is only as safe as the two files. You are responsible for restricting access to the files containing the password encryption key and encrypted password. If an attacker obtains both files, the password can be decrypted. The operating system file permissions for the two files should be as limited and restrictive as possible, to ensure that only the intended operating system userid has access to the files.

The two files can be kept on separate physical volumes, to reduce the risk that both files might be lost at the same time. If either or both of the files are located on a network volume, then an encrypted wire protocol can be used to access the network volume, such as sshfs, encrypted NFSv4, or encrypted SMB 3.0.

This program accepts eight command-line arguments:

The TJEncryptPassword program uses the driver to log on to the specified database using the encrypted password, so the driver must have been installed with the pip install teradatasql command.

The following commands assume that the TJEncryptPassword.py program file is located in the current directory. When the driver is installed, the sample programs are placed in the teradatasql/samples directory under your Python installation directory. Change your current directory to the teradatasql/samples directory under your Python installation directory.

The following example commands illustrate using a 256-bit AES key, and using the HmacSHA256 algorithm.

You are not required to use the TJEncryptPassword program to create the files containing the password encryption key and encrypted password. You can develop your own software to create the necessary files, but the files must match the format expected by the driver.

The password encryption key file is a text file in Java Properties file format, using the ISO 8859-1 character encoding.

The file must contain the following string properties:

The TJEncryptPassword program uses a timestamp as a shared match value, but a timestamp is not required. Any shared string can serve as a match value. The timestamp is not related in any way to the encryption of the password, and the timestamp cannot be used to decrypt the password.

The encrypted password file is a text file in Java Properties file format, using the ISO 8859-1 character encoding.

The file must contain the following string properties:

While params is technically optional, an initialization vector is required by all three block cipher modes CBC, CFB, and OFB that are supported by the driver. ECB (Electronic Codebook) does not require params, but ECB is not supported by the driver.

A transformation is a string that describes the set of operations to be performed on the given input, to produce transformed output. A transformation specifies the name of a cryptographic algorithm such as DES or AES, followed by a feedback mode and padding scheme.

The driver supports the following transformations and key sizes.

Stored Password Protection uses a symmetric encryption algorithm such as DES or AES, in which the same secret key is used for encryption and decryption of the password. Stored Password Protection does not use an asymmetric encryption algorithm such as RSA, with separate public and private keys.

CBC (Cipher Block Chaining) is a block cipher encryption mode. With CBC, each ciphertext block is dependent on all plaintext blocks processed up to that point. CBC is suitable for encrypting data whose total byte count exceeds the algorithm's block size, and is therefore suitable for use with Stored Password Protection.

Stored Password Protection hides the password length in the encrypted password file by extending the length of the UTF8-encoded password with trailing null bytes. The length is extended to the next 512-byte boundary.

• A block cipher with no padding, such as AES/CBC/NoPadding, may only be used to encrypt data whose byte count after extension is a multiple of the algorithm's block size. The 512-byte boundary is compatible with many block ciphers. AES, for example, has a block size of 128 bits (16 bytes), and is therefore compatible with the 512-byte boundary.
• A block cipher with padding, such as AES/CBC/PKCS5Padding, can be used to encrypt data of any length. However, CBC with padding is vulnerable to a "padding oracle attack", so Stored Password Protection performs Encrypt-then-MAC for protection from a padding oracle attack. MAC algorithms HmacSHA1 and HmacSHA256 are supported.
• The driver does not support block ciphers used as byte-oriented ciphers via modes such as CFB8 or OFB8.

The strength of the encryption depends on your choice of cipher algorithm and key size.

• AES uses a 128-bit (16 byte), 192-bit (24 byte), or 256-bit (32 byte) key.
• DESede uses a 192-bit (24 byte) key. The driver does not support a 128-bit (16 byte) key for DESede.
• DES uses a 64-bit (8 byte) key.

This driver and the Teradata JDBC Driver can share the files containing the password encryption key and encrypted password, if you use a transformation, key size, and MAC algorithm that is supported by both drivers.

• Recommended choices for compatibility are AES/CBC/NoPadding and HmacSHA256.
• Use a 256-bit key if your Java environment has the Java Cryptography Extension (JCE) Unlimited Strength Jurisdiction Policy Files from Oracle.
• Use a 128-bit key if your Java environment does not have the Unlimited Strength Jurisdiction Policy Files.
• Use HmacSHA1 for compatibility with JDK 1.4.2.

For the ENCRYPTED_PASSWORD( syntax of the driver, each filename must be preceded by the file: prefix. The PasswordEncryptionKeyFileName must be separated from the EncryptedPasswordFileName by a single comma. The files can be located in the current directory, specified with a relative path, or specified with an absolute path.

Example for files in the current directory:

ENCRYPTED_PASSWORD(file:JohnDoeKey.properties,file:JohnDoePass.properties)

Example with relative paths:

ENCRYPTED_PASSWORD(file:../dir1/JohnDoeKey.properties,file:../dir2/JohnDoePass.properties)

Example with absolute paths on Windows:

ENCRYPTED_PASSWORD(file:c:/dir1/JohnDoeKey.properties,file:c:/dir2/JohnDoePass.properties)

Example with absolute paths on Linux:

ENCRYPTED_PASSWORD(file:/dir1/JohnDoeKey.properties,file:/dir2/JohnDoePass.properties)

The two filenames specified for an encrypted password must be accessible to the driver and must conform to the properties file formats described above. The driver raises an exception if the file is not accessible, or the file does not conform to the required file format.

The driver verifies that the match values in the two files are present, and match each other. The driver raises an exception if the match values differ from each other. The match values are compared to ensure that the two specified files are related to each other, serving as a "sanity check" to help avoid configuration errors. The TJEncryptPassword program uses a timestamp as a shared match value, but a timestamp is not required. Any shared string can serve as a match value. The timestamp is not related in any way to the encryption of the password, and the timestamp cannot be used to decrypt the password.

Before decryption, the driver calculates the MAC using the ciphertext, transformation name, and algorithm parameters if any, and verifies that the calculated MAC matches the expected MAC. The driver raises an exception if the calculated MAC differs from the expected MAC, to indicate that either or both of the files may have been tampered with.

Finally, the driver uses the decrypted password to log on to the database.

Client Attributes record a variety of information about the client system and client software in the system tables DBC.SessionTbl and DBC.EventLog. Client Attributes are intended to be a replacement for the information recorded in the LogonSource column of the system tables DBC.SessionTbl and DBC.EventLog.

The Client Attributes are recorded at session logon time. Subsequently, the system views DBC.SessionInfoV and DBC.LogOnOffV can be queried to obtain information about the client system and client software on a per-session basis. Client Attribute values may be recorded in the database in either mixed-case or in uppercase, depending on the session character set and other factors. Analysis of recorded Client Attributes must flexibly accommodate either mixed-case or uppercase values.

Warning: The information in this section is subject to change in future releases of the driver. Client Attributes can be "mined" for information about client system demographics; however, any applications that parse Client Attribute values must be changed if Client Attribute formats are changed in the future.

Client Attributes are not intended to be used for workload management. Instead, query bands are intended for workload management. Any use of Client Attributes for workload management may break if Client Attributes are changed, or augmented, in the future.

The LogonSource column is obsolete and has been superseded by Client Attributes. The LogonSource column may be deprecated and subsequently removed in future releases of the database.

When the driver establishes a connection to the database, the driver composes a string value that is stored in the LogonSource column of the system tables DBC.SessionTbl and DBC.EventLog. The LogonSource column is included in system views such as DBC.SessionInfoV and DBC.LogOnOffV. All LogonSource values are recorded in the database in uppercase.

The driver follows the format documented in the Teradata Data Dictionary, section "System Views Columns Reference", for network-attached LogonSource values. Network-attached LogonSource values have eight fields, separated by whitespace. The database composes fields 1 through 3, and the driver composes fields 4 through 8.

The tmode connection parameter enables an application to specify the transaction mode for the connection.

• "tmode":"ANSI" provides American National Standards Institute (ANSI) transaction semantics. This mode is recommended.
• "tmode":"TERA" provides legacy Teradata transaction semantics. This mode is only recommended for legacy applications that require Teradata transaction semantics.
• "tmode":"DEFAULT" provides the default transaction mode configured for the database, which may be either ANSI or TERA mode. "tmode":"DEFAULT" is the default when the tmode connection parameter is omitted.

While ANSI mode is generally recommended, please note that every application is different, and some applications may need to use TERA mode. The following differences between ANSI and TERA mode might affect a typical user or application:

1. Silent truncation of inserted data occurs in TERA mode, but not ANSI mode. In ANSI mode, the database returns an error instead of truncating data.
2. Tables created in ANSI mode are MULTISET by default. Tables created in TERA mode are SET tables by default.
3. For tables created in ANSI mode, character columns are CASESPECIFIC by default. For tables created in TERA mode, character columns are NOT CASESPECIFIC by default.
4. In ANSI mode, character literals are CASESPECIFIC. In TERA mode, character literals are NOT CASESPECIFIC.

The last two behavior differences, taken together, may cause character data comparisons (such as in WHERE clause conditions) to be case-insensitive in TERA mode, but case-sensitive in ANSI mode. This, in turn, can produce different query results in ANSI mode versus TERA mode. Comparing two NOT CASESPECIFIC expressions is case-insensitive regardless of mode, and comparing a CASESPECIFIC expression to another expression of any kind is case-sensitive regardless of mode. You may explicitly CAST an expression to be CASESPECIFIC or NOT CASESPECIFIC to obtain the character data comparison required by your application.

The Teradata Reference / SQL Request and Transaction Processing recommends that ANSI mode be used for all new applications. The primary benefit of using ANSI mode is that inadvertent data truncation is avoided. In contrast, when using TERA mode, silent data truncation can occur when data is inserted, because silent data truncation is a feature of TERA mode.

A drawback of using ANSI mode is that you can only call stored procedures that were created using ANSI mode, and you cannot call stored procedures that were created using TERA mode. It may not be possible to switch over to ANSI mode exclusively, because you may have some legacy applications that require TERA mode to work properly. You can work around this drawback by creating your stored procedures twice, in two different users/databases, once using ANSI mode, and once using TERA mode.

Refer to the Teradata Reference / SQL Request and Transaction Processing for complete information regarding the differences between ANSI and TERA transaction modes.

The driver provides auto-commit on and off functionality for both ANSI and TERA mode.

When a connection is first established, it begins with the default auto-commit setting, which is on. When auto-commit is on, the driver is solely responsible for managing transactions, and the driver commits each SQL request that is successfully executed. An application should not execute any transaction management SQL commands when auto-commit is on. An application should not call the commit method or the rollback method when auto-commit is on.

An application can manage transactions itself by calling the execute method with the teradata_nativesql and teradata_autocommit_off escape functions to turn off auto-commit.

cur.execute("{fn teradata_nativesql}{fn teradata_autocommit_off}")

When auto-commit is off, the driver leaves the current transaction open after each SQL request is executed, and the application is responsible for committing or rolling back the transaction by calling the commit or the rollback method, respectively.

Auto-commit remains turned off until the application turns it back on.

cur.execute("{fn teradata_nativesql}{fn teradata_autocommit_on}")

Best practices recommend that an application avoid executing database-vendor-specific transaction management commands such as BT, ET, ABORT, COMMIT, or ROLLBACK, because such commands differ from one vendor to another. (They even differ between Teradata's two modes ANSI and TERA.) Instead, best practices recommend that an application only call the standard methods commit and rollback for transaction management.

1. When auto-commit is on in ANSI mode, the driver automatically executes COMMIT after every successful SQL request.
2. When auto-commit is off in ANSI mode, the driver does not automatically execute COMMIT. When the application calls the commit method, then the driver executes COMMIT.
3. When auto-commit is on in TERA mode, the driver does not execute BT or ET, unless the application explicitly executes BT or ET commands itself, which is not recommended.
4. When auto-commit is off in TERA mode, the driver executes BT before submitting the application's first SQL request of a new transaction. When the application calls the commit method, then the driver executes ET until the transaction is complete.

As part of the wire protocol between the database and Teradata client interface software (such as this driver), each message transmitted from the database to the client has a bit designated to indicate whether the session has a transaction in progress or not. Thus, the client interface software is kept informed as to whether the session has a transaction in progress or not.

In TERA mode with auto-commit off, when the application uses the driver to execute a SQL request, if the session does not have a transaction in progress, then the driver automatically executes BT before executing the application's SQL request. Subsequently, in TERA mode with auto-commit off, when the application uses the driver to execute another SQL request, and the session already has a transaction in progress, then the driver has no need to execute BT before executing the application's SQL request.

In TERA mode, BT and ET pairs can be nested, and the database keeps track of the nesting level. The outermost BT/ET pair defines the transaction scope; inner BT/ET pairs have no effect on the transaction because the database does not provide actual transaction nesting. To commit the transaction, ET commands must be repeatedly executed until the nesting is unwound. The Teradata wire protocol bit (mentioned earlier) indicates when the nesting is unwound and the transaction is complete. When the application calls the commit method in TERA mode, the driver repeatedly executes ET commands until the nesting is unwound and the transaction is complete.

In rare cases, an application may not follow best practices and may explicitly execute transaction management commands. Such an application must turn off auto-commit before executing transaction management commands such as BT, ET, ABORT, COMMIT, or ROLLBACK. The application is responsible for executing the appropriate commands for the transaction mode in effect. TERA mode commands are BT, ET, and ABORT. ANSI mode commands are COMMIT and ROLLBACK. An application must take special care when opening a transaction in TERA mode with auto-commit off. In TERA mode with auto-commit off, when the application executes a SQL request, if the session does not have a transaction in progress, then the driver automatically executes BT before executing the application's SQL request. Therefore, the application should not begin a transaction by executing BT.

# TERA mode example showing undesirable BT/ET nesting
cur.execute("{fn teradata_nativesql}{fn teradata_autocommit_off}")
cur.execute("BT") # BT automatically executed by the driver before this, and produces a nested BT
cur.execute("insert into mytable1 values(1, 2)")
cur.execute("insert into mytable2 values(3, 4)")
cur.execute("ET") # unwind nesting
cur.execute("ET") # complete transaction

# TERA mode example showing how to avoid BT/ET nesting
cur.execute("{fn teradata_nativesql}{fn teradata_autocommit_off}")
cur.execute("insert into mytable1 values(1, 2)") # BT automatically executed by the driver before this
cur.execute("insert into mytable2 values(3, 4)")
cur.execute("ET") # complete transaction

Please note that neither previous example shows best practices. Best practices recommend that an application only call the standard methods commit and rollback for transaction management.

# Example showing best practice
cur.execute("{fn teradata_nativesql}{fn teradata_autocommit_off}")
cur.execute("insert into mytable1 values(1, 2)")
cur.execute("insert into mytable2 values(3, 4)")
con.commit()

The table below lists the database data types supported by the driver, and indicates the corresponding Python data type returned in result set rows.

The table below lists the parameterized SQL bind-value Python data types supported by the driver, and indicates the corresponding database data type transmitted to the server.

Transforms are used for SQL ARRAY data values, and they can be transferred to and from the database as VARCHAR values.

Transforms are used for structured UDT data values, and they can be transferred to and from the database as VARCHAR values.

SQL NULL values received from the database are returned in result set rows as Python None values.

A Python None value bound to a question-mark parameter marker is transmitted to the database as a NULL VARCHAR value.

The database does not provide automatic or implicit conversion of a NULL VARCHAR value to a different destination data type.

• For NULL column values in a batch, the driver will automatically convert the NULL values to match the data type of the non-NULL values in the same column.
• For solitary NULL values, your application may need to explicitly specify the data type with the teradata_parameter escape function, in order to avoid database error 3532 for non-permitted data type conversion.

Given a table with a destination column of BYTE(4), the database would reject the following SQL with database error 3532 "Conversion between BYTE data and other types is illegal."

cur.execute("update mytable set bytecolumn = ?", [None]) # fails with database error 3532

To avoid database error 3532 in this situation, your application must use the the teradata_parameter escape function to specify the data type for the question-mark parameter marker.

cur.execute("{fn teradata_parameter(1, BYTE(4))}update mytable set bytecolumn = ?", [None])

The driver always uses the UTF8 session character set, and the charset connection parameter is not supported. Be aware of the database's Character Export Width behavior that adds trailing space padding to fixed-width CHAR data type result set column values when using the UTF8 session character set.

The database CHAR(n) data type is a fixed-width data type (holding n characters), and the database reserves a fixed number of bytes for the CHAR(n) data type in response spools and in network message traffic.

UTF8 is a variable-width character encoding scheme that requires a varying number of bytes for each character. When the UTF8 session character set is used, the database reserves the maximum number of bytes that the CHAR(n) data type could occupy in response spools and in network message traffic. When the UTF8 session character set is used, the database appends padding characters to the tail end of CHAR(n) values smaller than the reserved maximum size, so that the CHAR(n) values all occupy the same fixed number of bytes in response spools and in network message traffic.

Work around this drawback by using CAST or TRIM in SQL SELECT statements, or in views, to convert fixed-width CHAR data types to VARCHAR.

Given a table with fixed-width CHAR columns:

CREATE TABLE MyTable (c1 CHAR(10), c2 CHAR(10))

Original query that produces trailing space padding:

SELECT c1, c2 FROM MyTable

Modified query with either CAST or TRIM to avoid trailing space padding:

SELECT CAST(c1 AS VARCHAR(10)), TRIM(TRAILING FROM c2) FROM MyTable

Or wrap query in a view with CAST or TRIM to avoid trailing space padding:

CREATE VIEW MyView (c1, c2) AS SELECT CAST(c1 AS VARCHAR(10)), TRIM(TRAILING FROM c2) FROM MyTable

SELECT c1, c2 FROM MyView

This technique is also demonstrated in sample program CharPadding.py.

teradatasql.connect( JSONConnectionString , Parameters... )

Creates a connection to the database and returns a Connection object.

The first parameter is an optional JSON string that defaults to None. The second and subsequent arguments are optional kwargs. Specify connection parameters as a JSON string, as kwargs, or a combination of the two.

When a combination of parameters are specified, connection parameters specified as kwargs take precedence over same-named connection parameters specified in the JSON string.

teradatasql.Date( Year , Month , Day )

Creates and returns a datetime.date value.

teradatasql.DateFromTicks( Seconds )

Creates and returns a datetime.date value corresponding to the specified number of seconds after 1970-01-01 00:00:00.

teradatasql.Time( Hour , Minute , Second )

Creates and returns a datetime.time value.

teradatasql.TimeFromTicks( Seconds )

Creates and returns a datetime.time value corresponding to the specified number of seconds after 1970-01-01 00:00:00.

teradatasql.Timestamp( Year , Month , Day , Hour , Minute , Second )

Creates and returns a datetime.datetime value.

teradatasql.TimestampFromTicks( Seconds )

Creates and returns a datetime.datetime value corresponding to the specified number of seconds after 1970-01-01 00:00:00.

teradatasql.apilevel

String constant "2.0" indicating that the driver implements the PEP-249 Python Database API Specification 2.0.

teradatasql.threadsafety

Integer constant 2 indicating that threads may share this module, and threads may share connections, but threads must not share cursors.

teradatasql.paramstyle

String constant "qmark" indicating that prepared SQL requests use question-mark parameter markers.

teradatasql.Error is the base class for other exceptions.

• teradatasql.InterfaceError is raised for errors related to the driver. Not supported yet.
• teradatasql.DatabaseError is raised for errors related to the database.
  • teradatasql.DataError is raised for data value errors such as division by zero. Not supported yet.
  • teradatasql.IntegrityError is raised for referential integrity violations. Not supported yet.
  • teradatasql.OperationalError is raised for errors related to the database's operation.
  • teradatasql.ProgrammingError is raised for SQL object existence errors and SQL syntax errors. Not supported yet.

.close()

Closes the Connection.

.commit()

Commits the current transaction.

.cursor()

Creates and returns a new Cursor object for the Connection.

.rollback()

Rolls back the current transaction.

.arraysize

Read/write attribute specifying the number of rows to fetch at a time with the .fetchmany() method. Defaults to 1 meaning fetch a single row at a time.

.connection

Read-only attribute indicating the Cursor's parent Connection object.

.description

Read-only attribute consisting of a sequence of seven-item sequences that each describe a result set column, available after a SQL request is executed.

• .description[Column][0] provides the column name.
• .description[Column][1] provides the column type code as an object comparable to one of the Type Objects listed below.
• .description[Column][2] provides the column display size in characters. Not implemented yet.
• .description[Column][3] provides the column size in bytes.
• .description[Column][4] provides the column precision if applicable, or None otherwise.
• .description[Column][5] provides the column scale if applicable, or None otherwise.
• .description[Column][6] provides the column nullability as True or False.

.rowcount

Read-only attribute indicating the number of rows returned from, or affected by, the current SQL statement.

.callproc( ProcedureName , OptionalSequenceOfParameterValues )

Calls the stored procedure specified by ProcedureName. Provide the second argument as a sequence of IN and INOUT parameter values to bind the values to question-mark parameter markers in the SQL request. Specifying parameter values as a mapping is not supported. Returns a result set consisting of the INOUT parameter output values, if any, followed by any dynamic result sets.

OUT parameters are not supported by this method. Use .execute to call a stored procedure with OUT parameters.

.close()

Closes the Cursor.

.execute( SQLRequest , OptionalSequenceOfParameterValues , ignoreErrors= OptionalSequenceOfIgnoredErrorCodes )

Executes the SQL request. If a sequence of parameter values is provided as the second argument, the values will be bound to question-mark parameter markers in the SQL request. Specifying parameter values as a mapping is not supported.

The ignoreErrors parameter is optional. The ignored error codes must be specified as a sequence of integers.

.executemany( SQLRequest , SequenceOfSequencesOfParameterValues , ignoreErrors= OptionalSequenceOfIgnoredErrorCodes )

Executes the SQL request as an iterated SQL request for the batch of parameter values. The batch of parameter values must be specified as a sequence of sequences. Specifying parameter values as a mapping is not supported.

The ignoreErrors parameter is optional. The ignored error codes must be specified as a sequence of integers.

.fetchall()

Fetches all remaining rows of the current result set. Returns a sequence of sequences of column values.

.fetchmany( OptionalRowCount )

Fetches the next series of rows of the current result set. The argument specifies the number of rows to fetch. If no argument is provided, then the Cursor's .arraysize attribute will determine the number of rows to fetch. Returns a sequence of sequences of column values, or an empty sequence to indicate that all rows have been fetched.

.fetchone()

Fetches the next row of the current result set. Returns a sequence of column values, or None to indicate that all rows have been fetched.

.nextset()

Advances to the next result set. Returns True if another result set is available, or None to indicate that all result sets have been fetched.

.setinputsizes( SequenceOfTypesOrSizes )

Has no effect.

.setoutputsize( Size , OptionalColumnIndex )

Has no effect.

teradatasql.BINARY

Identifies a SQL BLOB, BYTE, or VARBYTE column as a binary data type when compared with the Cursor's description attribute.

.description[Column][1] == teradatasql.BINARY

teradatasql.DATETIME

Identifies a SQL DATE, TIME, TIME WITH TIME ZONE, TIMESTAMP, or TIMESTAMP WITH TIME ZONE column as a date/time data type when compared with the Cursor's description attribute.

.description[Column][1] == teradatasql.DATETIME

teradatasql.NUMBER

Identifies a SQL BIGINT, BYTEINT, DECIMAL, FLOAT, INTEGER, NUMBER, or SMALLINT column as a numeric data type when compared with the Cursor's description attribute.

.description[Column][1] == teradatasql.NUMBER

teradatasql.STRING

Identifies a SQL CHAR, CLOB, INTERVAL, PERIOD, or VARCHAR column as a character data type when compared with the Cursor's description attribute.

.description[Column][1] == teradatasql.STRING

The driver accepts most of the JDBC escape clauses offered by the Teradata JDBC Driver.

Date and time literal escape clauses are replaced by the corresponding SQL literal before the SQL request text is transmitted to the database.

For timestamp literal escape clauses, the decimal point and fractional digits may be omitted, or 1 to 6 fractional digits f may be specified after a decimal point.

Scalar function escape clauses are replaced by the corresponding SQL expression before the SQL request text is transmitted to the database.

Conversion function escape clauses are replaced by the corresponding SQL expression before the SQL request text is transmitted to the database.

Within a LIKE predicate's pattern argument, the characters % (percent) and _ (underscore) serve as wildcards. To interpret a particular wildcard character literally in a LIKE predicate's pattern argument, the wildcard character must be preceded by an escape character, and the escape character must be indicated in the LIKE predicate's ESCAPE clause.

LIKE predicate escape character escape clauses are replaced by the corresponding SQL clause before the SQL request text is transmitted to the database.

{escape 'EscapeCharacter'}

The escape clause must be specified immediately after the LIKE predicate that it applies to.

Outer join escape clauses are replaced by the corresponding SQL clause before the SQL request text is transmitted to the database.

{oj TableName OptionalCorrelationName LEFT OUTER JOIN TableName OptionalCorrelationName ON JoinCondition}

{oj TableName OptionalCorrelationName RIGHT OUTER JOIN TableName OptionalCorrelationName ON JoinCondition}

{oj TableName OptionalCorrelationName FULL OUTER JOIN TableName OptionalCorrelationName ON JoinCondition}

Stored procedure call escape clauses are replaced by the corresponding SQL clause before the SQL request text is transmitted to the database.

{call ProcedureName}

{call ProcedureName(CommaSeparatedParameterValues...)}

When a SQL request contains the native SQL escape clause, all escape clauses are replaced in the SQL request text, and the modified SQL request text is returned to the application as a result set containing a single row and a single VARCHAR column. The SQL request text is not transmitted to the database, and the SQL request is not executed. The native SQL escape clause mimics the functionality of the JDBC API Connection.nativeSQL method.

{fn teradata_nativesql}

The following table lists connection function escape clauses that are intended for use with the native SQL escape clause {fn teradata_nativesql}.

These functions provide information about the connection, or control the behavior of the connection. Functions that provide information return locally-cached information and avoid a round-trip to the database. Connection function escape clauses are replaced by the returned information before the SQL request text is transmitted to the database.

The following table lists request-scope function escape clauses that are intended for use with the Cursor .execute or .executemany methods.

These functions control the behavior of the corresponding Cursor, and are limited in scope to the particular SQL request in which they are specified. Request-scope function escape clauses are removed before the SQL request text is transmitted to the database.

The teradata_field_sep and teradata_field_quote escape functions have a single-character string argument. The string argument must follow SQL literal syntax. The string argument may be enclosed in single-quote (') characters or double-quote (") characters.

To represent a single-quote character in a string enclosed in single-quote characters, you must repeat the single-quote character.

{fn teradata_field_quote('''')}

To represent a double-quote character in a string enclosed in double-quote characters, you must repeat the double-quote character.

{fn teradata_field_quote("""")}

The driver offers FastLoad, which opens multiple database connections to transfer data in parallel.

Please be aware that this is an early release of the FastLoad feature. Think of it as a beta or preview version. It works, but does not yet offer all the features that JDBC FastLoad offers. FastLoad is still under active development, and we will continue to enhance it in subsequent builds.

FastLoad has limitations and cannot be used in all cases as a substitute for SQL batch insert:

• FastLoad can only load into an empty permanent table.
• FastLoad cannot load additional rows into a table that already contains rows.
• FastLoad cannot load into a volatile table or global temporary table.
• FastLoad cannot load duplicate rows into a MULTISET table with a primary index.
• Do not use FastLoad to load only a few rows, because FastLoad opens extra connections to the database, which is time consuming.
• Only use FastLoad to load many rows (at least 100,000 rows) so that the row-loading performance gain exceeds the overhead of opening additional connections.
• FastLoad does not support all database data types. For example, BLOB and CLOB are not supported.
• FastLoad requires StatementInfo parcel support to be enabled.
• FastLoad locks the destination table.
• If Online Archive encounters a table being loaded with FastLoad, online archiving of that table will be bypassed.

Your application can bind a single row of data for FastLoad, but that is not recommended because the overhead of opening additional connections causes FastLoad to be slower than a regular SQL INSERT for a single row.

How to use FastLoad:

• Auto-commit should be turned off before beginning a FastLoad.
• FastLoad is intended for binding many rows at a time. Each batch of rows must be able to fit into memory.
• When auto-commit is turned off, your application can insert multiple batches in a loop for the same FastLoad.
• Each column's data type must be consistent across every row in every batch over the entire FastLoad.
• The column values of the first row of the first batch dictate what the column data types must be in all subsequent rows and all subsequent batches of the FastLoad.

FastLoad opens multiple data transfer connections to the database. FastLoad evenly distributes each batch of rows across the available data transfer connections, and uses overlapped I/O to send and receive messages in parallel.

To use FastLoad, your application must prepend one of the following escape functions to the INSERT statement:

• {fn teradata_try_fastload} tries to use FastLoad for the INSERT statement, and automatically executes the INSERT as a regular SQL statement when the INSERT is not compatible with FastLoad.
• {fn teradata_require_fastload} requires FastLoad for the INSERT statement, and fails with an error when the INSERT is not compatible with FastLoad.

Your application can prepend other optional escape functions to the INSERT statement:

• {fn teradata_sessions(n)} specifies the number of data transfer connections to be opened, and is capped at the number of AMPs. The default is the smaller of 8 or the number of AMPs. CHECK WORKLOAD is not yet used, meaning that the driver does not ask the database how many data transfer connections should be used.
• {fn teradata_error_table_1_suffix(suffix)} specifies the suffix to append to the name of FastLoad error table 1. The default suffix is _ERR_1.
• {fn teradata_error_table_2_suffix(suffix)} specifies the suffix to append to the name of FastLoad error table 2. The default suffix is _ERR_2.
• {fn teradata_error_table_database(dbname)} specifies the parent database name for FastLoad error tables 1 and 2. By default, the FastLoad error tables reside in the same database as the destination table.

After beginning a FastLoad, your application can obtain the Logon Sequence Number (LSN) assigned to the FastLoad by prepending the following escape functions to the INSERT statement:

• {fn teradata_nativesql}{fn teradata_logon_sequence_number} returns the string form of an integer representing the Logon Sequence Number (LSN) for the FastLoad. Returns an empty string if the request is not a FastLoad.

FastLoad does not stop for data errors such as constraint violations or unique primary index violations. After inserting each batch of rows, your application must obtain warning and error information by prepending the following escape functions to the INSERT statement:

• {fn teradata_nativesql}{fn teradata_get_warnings} returns in one string all warnings generated by FastLoad for the request.
• {fn teradata_nativesql}{fn teradata_get_errors} returns in one string all data errors observed by FastLoad for the most recent batch. The data errors are obtained from FastLoad error table 1, for problems such as constraint violations, data type conversion errors, and unavailable AMP conditions.

Your application ends FastLoad by committing or rolling back the current transaction. After commit or rollback, your application must obtain warning and error information by prepending the following escape functions to the INSERT statement:

• {fn teradata_nativesql}{fn teradata_get_warnings} returns in one string all warnings generated by FastLoad for the commit or rollback. The warnings are obtained from FastLoad error table 2, for problems such as duplicate rows.
• {fn teradata_nativesql}{fn teradata_get_errors} returns in one string all data errors observed by FastLoad for the commit or rollback. The data errors are obtained from FastLoad error table 2, for problems such as unique primary index violations.

Warning and error information remains available until the next batch is inserted or until the commit or rollback. Each batch execution clears the prior warnings and errors. Each commit or rollback clears the prior warnings and errors.

The driver offers FastExport, which opens multiple database connections to transfer data in parallel.

Please be aware that this is an early release of the FastExport feature. Think of it as a beta or preview version. It works, but does not yet offer all the features that JDBC FastExport offers. FastExport is still under active development, and we will continue to enhance it in subsequent builds.

FastExport has limitations and cannot be used in all cases as a substitute for SQL queries:

• FastExport cannot query a volatile table or global temporary table.
• FastExport supports single-statement SQL SELECT, and supports multi-statement requests composed of multiple SQL SELECT statements only.
• FastExport supports question-mark parameter markers in WHERE clause conditions. However, the database does not permit the equal = operator for primary or unique secondary indexes, and will return database error 3695 "A Single AMP Select statement has been issued in FastExport".
• Do not use FastExport to fetch only a few rows, because FastExport opens extra connections to the database, which is time consuming.
• Only use FastExport to fetch many rows (at least 100,000 rows) so that the row-fetching performance gain exceeds the overhead of opening additional connections.
• FastExport does not support all database data types. For example, BLOB and CLOB are not supported.
• For best efficiency, do not use GROUP BY and ORDER BY clauses with FastExport.
• FastExport's result set ordering behavior may differ from a regular SQL query. In particular, a query containing an ordered analytic function may not produce an ordered result set. Use an ORDER BY clause to guarantee result set order.

FastExport opens multiple data transfer connections to the database. FastExport uses overlapped I/O to send and receive messages in parallel.

To use FastExport, your application must prepend one of the following escape functions to the query:

• {fn teradata_try_fastexport} tries to use FastExport for the query, and automatically executes the query as a regular SQL query when the query is not compatible with FastExport.
• {fn teradata_require_fastexport} requires FastExport for the query, and fails with an error when the query is not compatible with FastExport.

Your application can prepend other optional escape functions to the query:

• {fn teradata_sessions(n)} specifies the number of data transfer connections to be opened, and is capped at the number of AMPs. The default is the smaller of 8 or the number of AMPs. CHECK WORKLOAD is not yet used, meaning that the driver does not ask the database how many data transfer connections should be used.

After beginning a FastExport, your application can obtain the Logon Sequence Number (LSN) assigned to the FastExport by prepending the following escape functions to the query:

• {fn teradata_nativesql}{fn teradata_logon_sequence_number} returns the string form of an integer representing the Logon Sequence Number (LSN) for the FastExport. Returns an empty string if the request is not a FastExport.

The driver can read batch insert bind values from a CSV (comma separated values) file. This feature can be used with SQL batch inserts and with FastLoad.

To specify batch insert bind values in a CSV file, the application prepends the escape function {fn teradata_read_csv(CSVFileName)} to the INSERT statement.

The application can specify batch insert bind values in a CSV file, or specify bind parameter values, but not both together. The driver returns an error if both are specified together.

Considerations when using a CSV file:

• Each record is on a separate line of the CSV file. Records are delimited by line breaks (CRLF). The last record in the file may or may not have an ending line break.
• The first line of the CSV file is a header line. The header line lists the column names separated by the field separator (e.g. col1,col2,col3).
• The field separator defaults to the comma character (,). You can specify a different field separator character with the field_sep connection parameter or with the teradata_field_sep escape function. The specified field separator character must match the actual separator character used in the CSV file.
• Each field can optionally be enclosed by the field quote character, which defaults to the double-quote character (e.g. "abc",123,efg). You can specify a different field quote character with the field_quote connection parameter or with the teradata_field_quote escape function. The field quote character must match the actual field quote character used in the CSV file.
• The field separator and field quote characters cannot be set to the same value. The field separator and field quote characters must be legal UTF-8 characters and cannot be line feed (\n) or carriage return (\r).
• Field quote characters are only permitted in fields enclosed by field quote characters. Field quote characters must not appear inside unquoted fields (e.g. not allowed ab"cd"ef,1,abc).
• To include a field quote character in a quoted field, the field quote character must be repeated (e.g. "abc""efg""dh",123,xyz).
• Line breaks, field quote characters, and field separators may be included in a quoted field (e.g. "abc,efg\ndh",123,xyz).
• Specify a NULL value in the CSV file with an empty value between commas (e.g. 1,,456).
• A zero-length quoted string specifies a zero-length non-NULL string, not a NULL value (e.g. 1,"",456).
• Not all data types are supported. For example, BLOB, BYTE, and VARBYTE are not supported.
• A field length greater than 64KB is transmitted to the database as a DEFERRED CLOB for a SQL batch insert. A field length greater than 64KB is not supported with FastLoad.

Limitations when using CSV batch inserts:

• Bound parameter values cannot be specified in the execute method when using the escape function {fn teradata_read_csv(CSVFileName)}.
• The CSV file must contain at least one valid record in addition to the header line containing the column names.
• For FastLoad, the insert operation will fail if the CSV file is improperly formatted and a parser error occurs.
• For SQL batch insert, some records may be inserted before a parsing error occurs. A list of the parser errors will be returned. Each parser error will include the line number (starting at line 1) and the column number (starting at zero).
• Using a CSV file with FastLoad has the same limitations and is used the same way as described in the FastLoad section.

The driver can export query results to CSV files. This feature can be used with SQL query results, with calls to stored procedures, and with FastExport.

To export a result set to a CSV file, the application prepends the escape function {fn teradata_write_csv(CSVFileName)} to the SQL request text.

If the query returns multiple result sets, each result set will be written to a separate file. The file name is varied by inserting the string "_N" between the specified file name and file type extension (e.g. fileName.csv, fileName_1.csv, fileName_2.csv). If no file type extension is specified, then the suffix "_N" is appended to the end of the file name (e.g. fileName, fileName_1, fileName_2).

A stored procedure call that produces multiple dynamic result sets behaves like other SQL requests that return multiple result sets. The stored procedures's output parameter values are exported as the first CSV file.

Example of a SQL request that returns multiple results:

{fn teradata_write_csv(myFile.csv)}select 'abc' ; select 123

To obtain the metadata for each result set, use the escape function {fn teradata_fake_result_sets}. A fake result set containing the metadata will be written to a file preceding each real result set.

Example of a query that returns multiple result sets with metadata:

{fn teradata_fake_result_sets}{fn teradata_write_csv(myFile.csv)}select 'abc' ; select 123

Exported CSV files have the following characteristics:

• Each record is on a separate line of the CSV file. Records are delimited by line breaks (CRLF).
• Column values are separated by the field separator character, which defaults to the comma character (,). You can specify a different field separator character with the field_sep connection parameter or with the teradata_field_sep escape function.
• The first line of the CSV file is a header line. The header line lists the column names separated by the field separator (e.g. col1,col2,col3).
• When necessary, column values are enclosed by the field quote character, which defaults to the double-quote character ("). You can specify a different field quote character with the field_quote connection parameter or with the teradata_field_quote escape function.
• The field separator and field quote characters cannot be set to the same value. The field separator and field quote characters must be legal UTF-8 characters and cannot be line feed (\n) or carriage return (\r).
• If a column value contains line breaks, field quote characters, and/or field separators in a field, the value is quoted with the field quote character.
• If a column value contains a field quote character, the value is quoted and the field quote character is repeated. For example, column value abc"def is exported as "abc""def".
• A NULL value is exported to the CSV file as an empty value between field separators (e.g. 123,,456).
• A non-NULL zero-length character value is exported as a zero-length quoted string (e.g. 123,"",456).

Limitations when exporting to CSV files:

• When the application chooses to export results to a CSV file, the results are not available for the application to fetch in memory.
• A warning is returned if the application specifies an export CSV file for a SQL statement that does not produce a result set.
• Exporting a CSV file with FastExport has the same limitations and is used the same way as described in the FastExport section.
• Not all data types are supported. For example, BLOB, BYTE, and VARBYTE are not supported and if one of these column types are present in the result set, an error will be returned.
• CLOB, XML, JSON, and DATASET STORAGE FORMAT CSV data types are supported for SQL query results and are exported as string values, but these data types are not supported by FastExport.

17.20.0.0 - June 16, 2022

• GOSQL-74 FastLoad support for connection parameter fake_result_sets=true

17.10.0.16 - June 6, 2022

• GOSQL-106 indicate unavailable TLS certificate status with ClientAttributesEx CERT=U

17.10.0.15 - June 2, 2022

• Switch to TeraGSS 17.20.00.04 and OpenSSL 1.1.1l
• Requires macOS 10.14 Mojave or later and ends support for older versions of macOS

17.10.0.14 - May 18, 2022

• GOSQL-104 FastExport reports invalid CSV path name for first query but not subsequent
• GOSQL-105 Avoid driver failure when database warning length is invalid

17.10.0.13 - May 16, 2022

• GOSQL-53 browser and logmech=BROWSER connection parameters
• GOSQL-56 Implement Federated Authentication feature in GoSQL Driver
• PYDBAPI-77 Implement Federated Authentication feature in Python driver

17.10.0.12 - April 15, 2022

• GOSQL-71 TLS certificate verification
• GOSQL-98 remove escape function teradata_setloglevel

17.10.0.11 - April 7, 2022

• GOSQL-82 Escape functions teradata_field_sep and teradata_field_quote
• GOSQL-97 FastLoad/FastExport accommodate extra whitespace in SQL request

17.10.0.10 - March 24, 2022

• GOSQL-95 case-insensitive sslmode connection parameter values
• GOSQL-96 avoid CVE security vulnerabilities present in Go 1.17 and earlier
• Build DLL and shared library with Go 1.18
• Requires macOS 10.13 High Sierra or later and ends support for older versions of macOS

17.10.0.9 - March 18, 2022

• GOSQL-94 thread-safe connect failure cache

17.10.0.8 - March 9, 2022

• GOSQL-84 accommodate 64-bit Activity Count
• GOSQL-92 FastLoad returns error 512 when first column value is NULL

17.10.0.7 - February 23, 2022

• GOSQL-91 Avoid Error 8019 by always sending Config Request message

17.10.0.6 - February 4, 2022

• GOSQL-26 provide stored procedure creation errors
• GOSQL-73 Write CSV files
• GOSQL-88 Append streamlined client call stack to ClientProgramName

17.10.0.5 - January 10, 2022

• GOSQL-86 provide UDF compilation errors

17.10.0.4 - December 13, 2021

• GOSQL-20 TLS support
• GOSQL-29 Laddered Concurrent Connect
• PYDBAPI-82 Implement Laddered Concurrent Connect in Python driver

17.10.0.3 - November 30, 2021

• GOSQL-12 Centralized administration for data encryption
• GOSQL-25 Assign Response message error handling
• GOSQL-27 Enhance checks for missing logon parameters
• GOSQL-65 improve terasso error messages
• GOSQL-66 transmit Client Attributes to DBS during logon
• PYDBAPI-58 Centralized administration (from database) of Data Encryption
• Build DLL and shared library with Go 1.15.15

17.10.0.2 - July 2, 2021

• GOSQL-33 CALL to stored procedure INOUT and OUT parameter output values
• GOSQL-35 Statement Independence
• GOSQL-72 Read CSV files
• PYDBAPI-39 JSON, CSV, and Avro data type support
• PYDBAPI-83 Escape Syntax for FLOAT Data Type

17.10.0.1 - June 9, 2021

• Corrected documentation formatting for PyPI

17.10.0.0 - June 8, 2021

• GOSQL-75 trim whitespace from SQL request text

17.0.0.8 - December 18, 2020

• Documentation changes

17.0.0.7 - December 18, 2020

• GOSQL-13 add support for FastExport protocol

17.0.0.6 - October 9, 2020

• GOSQL-68 cross-process COP hostname load distribution

17.0.0.5 - August 26, 2020

• GOSQL-64 improve error checking for FastLoad escape functions

17.0.0.4 - August 18, 2020

• GOSQL-62 prevent nativesql from executing FastLoad
• GOSQL-63 prevent FastLoad panic

17.0.0.3 - July 30, 2020

• Build DLL and shared library with Go 1.14.6

17.0.0.2 - June 10, 2020

• GOSQL-60 CLOBTranslate=Locked workaround for DBS DR 194293

17.0.0.1 - June 4, 2020

• GOSQL-61 FastLoad accommodate encryptdata true

16.20.0.62 - May 12, 2020

• GOSQL-58 support multiple files for Elicit File protocol
• GOSQL-59 FastLoad accommodate dbscontrol change of COUNT(*) return type

16.20.0.61 - Apr 30, 2020

• GOSQL-57 Deferred LOB values larger than 1MB

16.20.0.60 - Mar 27, 2020

• GOSQL-22 enable insert of large LOB values over 64KB
• GOSQL-52 teradata_try_fastload consider bind value data types
• GOSQL-54 enforce Decimal value maximum precision 38
• PYDBAPI-37 Teradata Data Types Support up to 14.10 including LOB data

16.20.0.59 - Jan 8, 2020

• GOSQL-51 FastLoad fails when table is dropped and recreated
• PYDBAPI-72 bind value performance improvement
• PYDBAPI-73 DBAPI fails to insert 16383 rows

16.20.0.58 - Dec 11, 2019

• PYDBAPI-71 execute and executemany ignoreErrors parameter

16.20.0.57 - Dec 10, 2019

• GOSQL-50 provide FastLoad duplicate row errors with auto-commit on

16.20.0.56 - Dec 4, 2019

• PYDBAPI-70 raise error for closed cursor usage

16.20.0.55 - Nov 26, 2019

• GOSQL-15 add database connection parameter
• PYDBAPI-66 Better exception when running on 32-bit Python

16.20.0.54 - Nov 21, 2019

• GOSQL-49 FastLoad support for additional connection parameters

16.20.0.53 - Nov 15, 2019

• GOSQL-36 segment and iterate parameter batches per batch row limit
• GOSQL-43 segment and iterate parameter batches per request message size limit for FastLoad

16.20.0.52 - Oct 18, 2019

• Sample programs for fake result sets

16.20.0.51 - Oct 16, 2019

• GOSQL-46 LDAP password special characters

16.20.0.50 - Oct 7, 2019

• PYDBAPI-68 improve performance for batch bind values

16.20.0.49 - Oct 3, 2019

• GOSQL-45 FastLoad interop with Stored Password Protection

16.20.0.48 - Sep 6, 2019

• GOSQL-14 add support for FastLoad protocol
• GOSQL-34 negative scale for Number values
• PYDBAPI-29 Data Transfer - FastLoad Protocol

16.20.0.47 - Aug 27, 2019

• GOSQL-40 Skip executing empty SQL request text
• PYDBAPI-67 teradatasql.connect JSON connection string optional

16.20.0.46 - Aug 16, 2019

• GOSQL-39 COP Discovery interop with Kerberos

16.20.0.45 - Aug 12, 2019

• GOSQL-38 timestamp prefix log messages

16.20.0.44 - Aug 7, 2019

• GOSQL-4 Support COP discovery
• PYDBAPI-36 COP Discovery

16.20.0.43 - Jul 29, 2019

• GOSQL-18 Auto-commit
• PYDBAPI-61 commit and rollback methods

16.20.0.42 - Jun 7, 2019

• PYDBAPI-65 sample program BatchInsert.py

16.20.0.41 - Feb 14, 2019

• PYDBAPI-57 fetchmany may return "rows are closed" instead of empty result set

16.20.0.40 - Feb 8, 2019

• GOSQL-11 JWT authentication method
• GOSQL-16 tmode connection parameter
• GOSQL-17 commit and rollback functions

16.20.0.39 - Oct 26, 2018

• GOSQL-33 CALL to stored procedure INOUT and OUT parameter output values

16.20.0.38 - Oct 25, 2018

• PYDBAPI-56 Stored Procedure Dynamic Result Sets

16.20.0.37 - Oct 22, 2018

• Documentation change

16.20.0.36 - Oct 22, 2018

• GOSQL-5 Create/Replace Procedure MultiTSR protocol

16.20.0.35 - Oct 22, 2018

• GOSQL-10 Stored Password Protection
• PYDBAPI-28 Secure Password at rest
• PYDBAPI-47 Port sample program TJEncryptPassword to Python

16.20.0.34 - Oct 15, 2018

• Fix for sample program TJEncryptPassword.py

16.20.0.33 - Oct 12, 2018

• Installation dependency pycryptodome

16.20.0.32 - Sep 19, 2018

• Sample programs LoadCSVFile.py and MetadataFromPrepare.py
• Escape function teradata_fake_result_sets

16.20.0.31 - Sep 19, 2018

• Added function tracing

16.20.0.30 - Sep 14, 2018

• PYDBAPI-12 Connectivity
• PYDBAPI-33 Pandas library Interoperability
• Moved samples directory

16.20.0.29 - Sep 14, 2018

• Sample program ElicitFile.py

16.20.0.28 - Sep 13, 2018

• Documentation change

16.20.0.27 - Sep 12, 2018

• Documentation change

16.20.0.26 - Sep 11, 2018

• PYDBAPI-8 Documentation
• PYDBAPI-9 User Guide Content

16.20.0.25 - Sep 10, 2018

• Documentation change

16.20.0.24 - Sep 6, 2018

• PYDBAPI-54 Implement cursor rowcount attribute
• PYDBAPI-55 Improved support for Python data types

16.20.0.23 - Aug 31, 2018

• KeepResponse only for LOB locators

16.20.0.22 - Aug 30, 2018

• Fixed NUMBER values

16.20.0.21 - Aug 29, 2018

• Close orphaned rows

16.20.0.20 - Aug 28, 2018

• decimal and datetime values

16.20.0.19 - Aug 22, 2018

• timedelta bind values

16.20.0.18 - Aug 21, 2018

• datetime.datetime bind values

16.20.0.17 - Aug 20, 2018

• Version number in errors

16.20.0.16 - Aug 17, 2018

• SLES 11 SP1 compatibility

16.20.0.15 - Aug 17, 2018

• Documentation change

16.20.0.14 - Aug 10, 2018

• Documentation change

16.20.0.13 - Aug 9, 2018

• Documentation change

16.20.0.12 - Aug 9, 2018

• PYDBAPI-10 User Guide Delivery and Viewability
• PYDBAPI-11 Searchability

16.20.0.11 - Aug 8, 2018

• Documentation change

16.20.0.10 - Aug 8, 2018

• Documentation change

16.20.0.9 - Aug 7, 2018

• Install documentation in teradatasql directory

16.20.0.8 - Aug 7, 2018

• GOSQL-7 TDNEGO authentication method
• PYDBAPI-42 Teradata Logon mechanism - TDNEGO

16.20.0.7 - Jul 30, 2018

• GOSQL-8 Support parameter marker batch insert
• PYDBAPI-45 Parameterized Batch Insertion using executeMany

16.20.0.6 - Jul 25, 2018

• Thread safety for handle maps

16.20.0.5 - Jul 25, 2018

• Removed atexit

16.20.0.4 - Jul 23, 2018

• PYDBAPI-4 Provide Python Driver license file

16.20.0.3 - Jul 19, 2018

• PYDBAPI-46 Accept subclasses of bytes, int, float, str as bind values

16.20.0.2 - Jul 19, 2018

• Package attributes change

16.20.0.1 - Jul 18, 2018

• Version number change

16.20.0.0 - Jul 18, 2018

• GOSQL-1 Encrypted logon
• GOSQL-2 LDAP and Kerberos authentication
• GOSQL-3 Support for 1MB Rows
• GOSQL-6 Elicit File protocol
• PYDBAPI-1 Distribution
• PYDBAPI-5 cursor.execute method return cursor
• PYDBAPI-6 Install and Deployment
• PYDBAPI-7 pip install of python driver package
• PYDBAPI-13 Operating System Platforms
• PYDBAPI-14 Driver must be available for use by Windows OS Users
• PYDBAPI-15 Driver must be available for use by OSX (Mac) Users
• PYDBAPI-16 Driver must be available for use by Linux OS Users
• PYDBAPI-17 Python Language version
• PYDBAPI-18 Python language version 3.4
• PYDBAPI-19 Distribution
• PYDBAPI-23 Teradata Analytics Platform Interoperability/Support
• PYDBAPI-24 Works with Teradata Database 16.10, 16.20
• PYDBAPI-26 Teradata Logon mechanism - Kerberos
• PYDBAPI-32 Downloadable from pypi.org
• PYDBAPI-40 Teradata Logon mechanism - LDAP
• PYDBAPI-41 Teradata Logon mechanism - TD2
• PYDBAPI-43 parameterized single-row inserts
• PYDBAPI-44 parameterized queries