mirror of https://github.com/python/cpython
504 lines
20 KiB
TeX
504 lines
20 KiB
TeX
\section{\module{sqlite3} ---
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DB-API 2.0 interface for SQLite databases}
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\declaremodule{builtin}{sqlite3}
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\modulesynopsis{A DB-API 2.0 implementation using SQLite 3.x.}
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\sectionauthor{Gerhard Häring}{gh@ghaering.de}
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\versionadded{2.5}
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\subsection{Module functions and constants\label{sqlite3-Module-Contents}}
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\begin{datadesc}{PARSE_DECLTYPES}
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This constant is meant to be used with the \var{detect_types} parameter of the
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\function{connect} function.
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Setting it makes the \module{sqlite3} module parse the declared type for each column it
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returns. It will parse out the first word of the declared type, i. e. for
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"integer primary key", it will parse out "integer". Then for that column, it
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will look into the converters dictionary and use the converter function
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registered for that type there. Converter names are case-sensitive!
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\end{datadesc}
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\begin{datadesc}{PARSE_COLNAMES}
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This constant is meant to be used with the \var{detect_types} parameter of the
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\function{connect} function.
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Setting this makes the SQLite interface parse the column name for each column
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it returns. It will look for a string formed [mytype] in there, and then
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decide that 'mytype' is the type of the column. It will try to find an entry of
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'mytype' in the converters dictionary and then use the converter function found
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there to return the value. The column name found in \member{cursor.description} is only
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the first word of the column name, i. e. if you use something like
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\code{'as "x [datetime]"'} in your SQL, then we will parse out everything until the
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first blank for the column name: the column name would simply be "x".
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\end{datadesc}
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\begin{funcdesc}{connect}{database\optional{, timeout, isolation_level, detect_types, factory}}
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Opens a connection to the SQLite database file \var{database}. You can use
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\code{":memory:"} to open a database connection to a database that resides in
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RAM instead of on disk.
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When a database is accessed by multiple connections, and one of the processes
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modifies the database, the SQLite database is locked until that transaction is
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committed. The \var{timeout} parameter specifies how long the connection should
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wait for the lock to go away until raising an exception. The default for the
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timeout parameter is 5.0 (five seconds).
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For the \var{isolation_level} parameter, please see \member{isolation_level}
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\ref{sqlite3-Connection-IsolationLevel} property of \class{Connection} objects.
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SQLite natively supports only the types TEXT, INTEGER, FLOAT, BLOB and NULL. If
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you want to use other types, like you have to add support for them yourself.
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The \var{detect_types} parameter and the using custom \strong{converters} registered with
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the module-level \function{register_converter} function allow you to easily do that.
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\var{detect_types} defaults to 0 (i. e. off, no type detection), you can set it
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to any combination of \constant{PARSE_DECLTYPES} and \constant{PARSE_COLNAMES} to turn type
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detection on.
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By default, the \module{sqlite3} module uses its \class{Connection} class for the
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connect call. You can, however, subclass the \class{Connection} class and make
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\function{connect} use your class instead by providing your class for the
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\var{factory} parameter.
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Consult the section \ref{sqlite3-Types} of this manual for details.
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The \module{sqlite3} module internally uses a statement cache to avoid SQL parsing
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overhead. If you want to explicitly set the number of statements that are
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cached for the connection, you can set the \var{cached_statements} parameter.
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The currently implemented default is to cache 100 statements.
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\end{funcdesc}
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\begin{funcdesc}{register_converter}{typename, callable}
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Registers a callable to convert a bytestring from the database into a custom
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Python type. The callable will be invoked for all database values that are of
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the type \var{typename}. Confer the parameter \var{detect_types} of the
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\function{connect} function for how the type detection works. Note that the case of
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\var{typename} and the name of the type in your query must match!
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\end{funcdesc}
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\begin{funcdesc}{register_adapter}{type, callable}
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Registers a callable to convert the custom Python type \var{type} into one of
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SQLite's supported types. The callable \var{callable} accepts as single
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parameter the Python value, and must return a value of the following types:
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int, long, float, str (UTF-8 encoded), unicode or buffer.
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\end{funcdesc}
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\begin{funcdesc}{complete_statement}{sql}
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Returns \constant{True} if the string \var{sql} one or more complete SQL
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statements terminated by semicolons. It does not verify if the SQL is
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syntactically correct, only if there are no unclosed string literals and if the
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statement is terminated by a semicolon.
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This can be used to build a shell for SQLite, like in the following example:
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\verbatiminput{sqlite3/complete_statement.py}
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\end{funcdesc}
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\subsection{Connection Objects \label{sqlite3-Connection-Objects}}
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A \class{Connection} instance has the following attributes and methods:
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\label{sqlite3-Connection-IsolationLevel}
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\begin{memberdesc}{isolation_level}
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Get or set the current isolation level. None for autocommit mode or one of
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"DEFERRED", "IMMEDIATE" or "EXLUSIVE". See Controlling Transactions
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\ref{sqlite3-Controlling-Transactions} for a more detailed explanation.
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\end{memberdesc}
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\begin{methoddesc}{cursor}{\optional{cursorClass}}
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The cursor method accepts a single optional parameter \var{cursorClass}.
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This is a custom cursor class which must extend \class{sqlite3.Cursor}.
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\end{methoddesc}
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\begin{methoddesc}{execute}{sql, \optional{parameters}}
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This is a nonstandard shortcut that creates an intermediate cursor object by
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calling the cursor method, then calls the cursor's \method{execute} method with the
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parameters given.
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\end{methoddesc}
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\begin{methoddesc}{executemany}{sql, \optional{parameters}}
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This is a nonstandard shortcut that creates an intermediate cursor object by
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calling the cursor method, then calls the cursor's \method{executemany} method with the
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parameters given.
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\end{methoddesc}
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\begin{methoddesc}{executescript}{sql_script}
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This is a nonstandard shortcut that creates an intermediate cursor object by
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calling the cursor method, then calls the cursor's \method{executescript} method with the
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parameters given.
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\end{methoddesc}
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\begin{methoddesc}{create_function}{name, num_params, func}
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Creates a user-defined function that you can later use from within SQL
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statements under the function name \var{name}. \var{num_params} is the number
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of parameters the function accepts, and \var{func} is a Python callable that is
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called as SQL function.
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The function can return any of the types supported by SQLite: unicode, str,
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int, long, float, buffer and None. Exceptions in the function are ignored and
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they are handled as if the function returned None.
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Example:
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\verbatiminput{sqlite3/md5func.py}
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\end{methoddesc}
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\begin{methoddesc}{create_aggregate}{name, num_params, aggregate_class}
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Creates a user-defined aggregate function.
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The aggregate class must implement a \code{step} method, which accepts the
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number of parameters \var{num_params}, and a \code{finalize} method which
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will return the final result of the aggregate.
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The \code{finalize} method can return any of the types supported by SQLite:
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unicode, str, int, long, float, buffer and None. Any exceptions are ignored.
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Example:
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\verbatiminput{sqlite3/mysumaggr.py}
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\end{methoddesc}
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\begin{methoddesc}{create_collation}{name, callable}
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Creates a collation with the specified \var{name} and \var{callable}. The
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callable will be passed two string arguments. It should return -1 if the first
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is ordered lower than the second, 0 if they are ordered equal and 1 and if the
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first is ordered higher than the second. Note that this controls sorting
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(ORDER BY in SQL) so your comparisons don't affect other SQL operations.
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Note that the callable will get its parameters as Python bytestrings, which
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will normally be encoded in UTF-8.
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The following example shows a custom collation that sorts "the wrong way":
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\verbatiminput{sqlite3/collation_reverse.py}
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To remove a collation, call \code{create_collation} with None as callable:
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\begin{verbatim}
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con.create_collation("reverse", None)
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\end{verbatim}
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\end{methoddesc}
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\begin{memberdesc}{row_factory}
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You can change this attribute to a callable that accepts the cursor and
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the original row as tuple and will return the real result row. This
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way, you can implement more advanced ways of returning results, like
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ones that can also access columns by name.
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Example:
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\verbatiminput{sqlite3/row_factory.py}
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If the standard tuple types don't suffice for you, and you want name-based
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access to columns, you should consider setting \member{row_factory} to the
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highly-optimized sqlite3.Row type. It provides both
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index-based and case-insensitive name-based access to columns with almost
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no memory overhead. Much better than your own custom dictionary-based
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approach or even a db_row based solution.
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\end{memberdesc}
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\begin{memberdesc}{text_factory}
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Using this attribute you can control what objects are returned for the
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TEXT data type. By default, this attribute is set to \class{unicode} and
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the \module{sqlite3} module will return Unicode objects for TEXT. If you want to return
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bytestrings instead, you can set it to \class{str}.
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For efficiency reasons, there's also a way to return Unicode objects only
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for non-ASCII data, and bytestrings otherwise. To activate it, set this
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attribute to \constant{sqlite3.OptimizedUnicode}.
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You can also set it to any other callable that accepts a single bytestring
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parameter and returns the result object.
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See the following example code for illustration:
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\verbatiminput{sqlite3/text_factory.py}
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\end{memberdesc}
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\begin{memberdesc}{total_changes}
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Returns the total number of database rows that have be modified, inserted,
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or deleted since the database connection was opened.
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\end{memberdesc}
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\subsection{Cursor Objects \label{sqlite3-Cursor-Objects}}
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A \class{Cursor} instance has the following attributes and methods:
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\begin{methoddesc}{execute}{sql, \optional{parameters}}
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Executes a SQL statement. The SQL statement may be parametrized (i. e.
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placeholders instead of SQL literals). The \module{sqlite3} module supports two kinds of
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placeholders: question marks (qmark style) and named placeholders (named
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style).
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This example shows how to use parameters with qmark style:
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\verbatiminput{sqlite3/execute_1.py}
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This example shows how to use the named style:
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\verbatiminput{sqlite3/execute_2.py}
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\method{execute} will only execute a single SQL statement. If you try to
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execute more than one statement with it, it will raise a Warning. Use
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\method{executescript} if want to execute multiple SQL statements with one
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call.
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\end{methoddesc}
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\begin{methoddesc}{executemany}{sql, seq_of_parameters}
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Executes a SQL command against all parameter sequences or mappings found in the
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sequence \var{sql}. The \module{sqlite3} module also allows
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to use an iterator yielding parameters instead of a sequence.
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\verbatiminput{sqlite3/executemany_1.py}
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Here's a shorter example using a generator:
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\verbatiminput{sqlite3/executemany_2.py}
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\end{methoddesc}
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\begin{methoddesc}{executescript}{sql_script}
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This is a nonstandard convenience method for executing multiple SQL statements
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at once. It issues a COMMIT statement before, then executes the SQL script it
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gets as a parameter.
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\var{sql_script} can be a bytestring or a Unicode string.
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Example:
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\verbatiminput{sqlite3/executescript.py}
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\end{methoddesc}
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\begin{memberdesc}{rowcount}
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Although the \class{Cursor} class of the \module{sqlite3} module implements this
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attribute, the database engine's own support for the determination of "rows
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affected"/"rows selected" is quirky.
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For \code{SELECT} statements, \member{rowcount} is always None because we cannot
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determine the number of rows a query produced until all rows were fetched.
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For \code{DELETE} statements, SQLite reports \member{rowcount} as 0 if you make a
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\code{DELETE FROM table} without any condition.
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For \method{executemany} statements, the number of modifications are summed
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up into \member{rowcount}.
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As required by the Python DB API Spec, the \member{rowcount} attribute "is -1
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in case no executeXX() has been performed on the cursor or the rowcount
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of the last operation is not determinable by the interface".
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\end{memberdesc}
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\subsection{SQLite and Python types\label{sqlite3-Types}}
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\subsubsection{Introduction}
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SQLite natively supports the following types: NULL, INTEGER, REAL, TEXT, BLOB.
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The following Python types can thus be sent to SQLite without any problem:
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\begin{tableii} {c|l}{code}{Python type}{SQLite type}
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\lineii{None}{NULL}
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\lineii{int}{INTEGER}
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\lineii{long}{INTEGER}
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\lineii{float}{REAL}
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\lineii{str (UTF8-encoded)}{TEXT}
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\lineii{unicode}{TEXT}
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\lineii{buffer}{BLOB}
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\end{tableii}
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This is how SQLite types are converted to Python types by default:
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\begin{tableii} {c|l}{code}{SQLite type}{Python type}
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\lineii{NULL}{None}
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\lineii{INTEGER}{int or long, depending on size}
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\lineii{REAL}{float}
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\lineii{TEXT}{depends on text_factory, unicode by default}
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\lineii{BLOB}{buffer}
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\end{tableii}
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The type system of the \module{sqlite3} module is extensible in both ways: you can store
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additional Python types in a SQLite database via object adaptation, and you can
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let the \module{sqlite3} module convert SQLite types to different Python types via
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converters.
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\subsubsection{Using adapters to store additional Python types in SQLite databases}
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Like described before, SQLite supports only a limited set of types natively. To
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use other Python types with SQLite, you must \strong{adapt} them to one of the sqlite3
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module's supported types for SQLite. So, one of NoneType, int, long, float,
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str, unicode, buffer.
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The \module{sqlite3} module uses the Python object adaptation, like described in PEP 246
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for this. The protocol to use is \class{PrepareProtocol}.
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There are two ways to enable the \module{sqlite3} module to adapt a custom Python type
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to one of the supported ones.
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\paragraph{Letting your object adapt itself}
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This is a good approach if you write the class yourself. Let's suppose you have
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a class like this:
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\begin{verbatim}
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class Point(object):
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def __init__(self, x, y):
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self.x, self.y = x, y
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\end{verbatim}
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Now you want to store the point in a single SQLite column. You'll have to
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choose one of the supported types first that you use to represent the point in.
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Let's just use str and separate the coordinates using a semicolon. Then you
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need to give your class a method \code{__conform__(self, protocol)} which must
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return the converted value. The parameter \var{protocol} will be
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\class{PrepareProtocol}.
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\verbatiminput{sqlite3/adapter_point_1.py}
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\paragraph{Registering an adapter callable}
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The other possibility is to create a function that converts the type to the
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string representation and register the function with \method{register_adapter}.
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\verbatiminput{sqlite3/adapter_point_2.py}
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\begin{notice}
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The type/class to adapt must be a new-style class, i. e. it must have
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\class{object} as one of its bases.
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\end{notice}
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The \module{sqlite3} module has two default adapters for Python's builtin
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\class{datetime.date} and \class{datetime.datetime} types. Now let's suppose we
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want to store \class{datetime.datetime} objects not in ISO representation, but
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as Unix timestamp.
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\verbatiminput{sqlite3/adapter_datetime.py}
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\subsubsection{Converting SQLite values to custom Python types}
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Now that's all nice and dandy that you can send custom Python types to SQLite.
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But to make it really useful we need to make the Python to SQLite to Python
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roundtrip work.
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Enter converters.
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Let's go back to the Point class. We stored the x and y coordinates separated
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via semicolons as strings in SQLite.
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Let's first define a converter function that accepts the string as a parameter and constructs a Point object from it.
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\begin{notice}
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Converter functions \strong{always} get called with a string, no matter
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under which data type you sent the value to SQLite.
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\end{notice}
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\begin{notice}
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Converter names are looked up in a case-sensitive manner.
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\end{notice}
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\begin{verbatim}
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def convert_point(s):
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x, y = map(float, s.split(";"))
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return Point(x, y)
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\end{verbatim}
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Now you need to make the \module{sqlite3} module know that what you select from the
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database is actually a point. There are two ways of doing this:
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\begin{itemize}
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\item Implicitly via the declared type
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\item Explicitly via the column name
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\end{itemize}
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Both ways are described at \ref{sqlite3-Module-Contents} in the text explaining
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the constants \constant{PARSE_DECLTYPES} and \constant{PARSE_COlNAMES}.
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The following example illustrates both ways.
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\verbatiminput{sqlite3/converter_point.py}
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\subsubsection{Default adapters and converters}
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There are default adapters for the date and datetime types in the datetime
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module. They will be sent as ISO dates/ISO timestamps to SQLite.
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The default converters are registered under the name "date" for datetime.date
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and under the name "timestamp" for datetime.datetime.
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This way, you can use date/timestamps from Python without any additional
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fiddling in most cases. The format of the adapters is also compatible with the
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experimental SQLite date/time functions.
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The following example demonstrates this.
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\verbatiminput{sqlite3/pysqlite_datetime.py}
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\subsection{Controlling Transactions \label{sqlite3-Controlling-Transactions}}
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By default, the \module{sqlite3} module opens transactions implicitly before a DML
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statement (INSERT/UPDATE/DELETE/REPLACE), and commits transactions implicitly
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before a non-DML, non-DQL statement (i. e. anything other than
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SELECT/INSERT/UPDATE/DELETE/REPLACE).
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So if you are within a transaction, and issue a command like \code{CREATE TABLE
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...}, \code{VACUUM}, \code{PRAGMA}, the \module{sqlite3} module will commit implicitly
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before executing that command. There are two reasons for doing that. The first
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is that some of these commands don't work within transactions. The other reason
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is that pysqlite needs to keep track of the transaction state (if a transaction
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is active or not).
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You can control which kind of "BEGIN" statements pysqlite implicitly executes
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(or none at all) via the \var{isolation_level} parameter to the
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\function{connect} call, or via the \member{isolation_level} property of
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connections.
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If you want \strong{autocommit mode}, then set \member{isolation_level} to None.
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Otherwise leave it at it's default, which will result in a plain "BEGIN"
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statement, or set it to one of SQLite's supported isolation levels: DEFERRED,
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IMMEDIATE or EXCLUSIVE.
|
|
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|
As the \module{sqlite3} module needs to keep track of the transaction state, you should
|
|
not use \code{OR ROLLBACK} or \code{ON CONFLICT ROLLBACK} in your SQL. Instead,
|
|
catch the \exception{IntegrityError} and call the \method{rollback} method of
|
|
the connection yourself.
|
|
|
|
\subsection{Using pysqlite efficiently}
|
|
|
|
\subsubsection{Using shortcut methods}
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|
|
|
Using the nonstandard \method{execute}, \method{executemany} and
|
|
\method{executescript} methods of the \class{Connection} object, your code can
|
|
be written more concisely, because you don't have to create the - often
|
|
superfluous \class{Cursor} objects explicitly. Instead, the \class{Cursor}
|
|
objects are created implicitly and these shortcut methods return the cursor
|
|
objects. This way, you can for example execute a SELECT statement and iterate
|
|
over it directly using only a single call on the \class{Connection} object.
|
|
|
|
\verbatiminput{sqlite3/shortcut_methods.py}
|
|
|
|
\subsubsection{Accessing columns by name instead of by index}
|
|
|
|
One cool feature of the \module{sqlite3} module is the builtin \class{sqlite3.Row} class
|
|
designed to be used as a row factory.
|
|
|
|
Rows wrapped with this class can be accessed both by index (like tuples) and
|
|
case-insensitively by name:
|
|
|
|
\verbatiminput{sqlite3/rowclass.py}
|
|
|
|
|