![]() How much space values take up, and whether the values are fixed-length (all values of the type taking the same amount of space) or variable-length (the amount of space depending on the particular value being stored) Each column type has several characteristics: For example, if you have numeric values, you can store them using a numeric or a string column type, but MySQL will treat the values somewhat differently depending on how you store them. MySQL's column types are the means by which you describe what kinds of values a table's columns contain, which in turn determines how MySQL treats those values. A column type is more specific than a data type, which is just a general category, such as "number" or "string." A column type precisely characterizes the kind of values a given table column can contain, such as SMALLINT or VARCHAR(32). When you create a table using a CREATE TABLE statement, you specify a type for each column. SQL Standard and Multiple Vendor “UPPERCASE” Types.Each table in a database is made up of one or more columns. Reference for the general set of “UPPERCASE” datatypes is below at SQL types that typically expect to be available on at least two backends The “UPPERCASE” datatypes that are part of sqlalchemy.types are common INTEGER, and TIMESTAMP, which inherit directlyįrom the previously mentioned “CamelCase” types ![]() Of UPPERCASE types include VARCHAR, NUMERIC, Of “UPPERCASE” types in a SQLAlchemy application indicates that specificĭatatypes are required, which then implies that the application would normally,īe limited to those backends which use the type exactly as given. Whether or not the current backend supports it. The name of the type is always rendered exactly as given, without regard for Theseĭatatypes are always inherited from a particular “CamelCase” datatype, andĪlways represent an exact datatype. In contrast to the “CamelCase” types are the “UPPERCASE” datatypes. Reference for the general set of “CamelCase” datatypes is below at “CamelCase” types in the general case, as they will generally provide the bestīasic behavior and be automatically portable to all backends. The typical SQLAlchemy application will likely wish to use primarily Interpreting Python numeric or boolean values. As data is sent and receivedįrom the database using this type, based on the dialect in use it may be May render BOOLEAN on a backend such as PostgreSQL, BIT on the ![]() Or BIT values 0 and 1, some have boolean literal constants true andįalse while others dont. Not every backend has a real “boolean” datatype some make use of integers Which represents a string datatype that all databases have, If arguments are needed, such as the lengthĪrgument of 60 in the "email_address" column above, the type may beĪnother “CamelCase” datatype that expresses more backend-specific behavior Table definition or in any SQL expression overall, if noĪrguments are required it may be passed as the class itself, that is, without ![]() When using a particular TypeEngine class in a _processor()įrom sqlalchemy import MetaData from sqlalchemy import Table, Column, Integer, String metadata_obj = MetaData () user = Table ( "user", metadata_obj, Column ( "user_name", String, primary_key = True ), Column ( "email_address", String ( 60 )), ).SQL Standard and Multiple Vendor “UPPERCASE” Types.Using “UPPERCASE” and Backend-specific types for multiple backends. ![]()
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