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You might want to use an iterator chain to do multiple instances of anoperation that can fail, but would like to ignore failures whilecontinuing to process the successful results. In this example, we takeadvantage of the iterable nature of Result to select only theOk values using flatten.

Unlike unwrap, this method is known to never panic on theresult types it is implemented for. Therefore, it can be usedinstead of unwrap as a maintainability safeguard that will failto compile if the error type of the Result is later changedto an error that can actually occur.

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Unlike unwrap_err, this method is known to never panic on theresult types it is implemented for. Therefore, it can be usedinstead of unwrap_err as a maintainability safeguard that will failto compile if the ok type of the Result is later changedto a type that can actually occur.

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Once the result of an operation is available, it is stored and is returned immediately on subsequent calls to the Result property. Note that, if an exception occurred during the operation of the task, or if the task has been cancelled, the Result property does not return a value. Instead, attempting to access the property value throws an AggregateException exception.

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The object returned is known as CursorResult, whichreferences a DBAPI cursor and provides methods for fetching rowssimilar to that of the DBAPI cursor. The DBAPI cursor will be closedby the CursorResult when all of its result rows (if any) areexhausted. A CursorResult that returns no rows, such as that ofan UPDATE statement (without any returned rows),releases cursor resources immediately upon construction.

New in version 1.4.40: Connection.execution_options.yield_per as aCore-only option is new as of SQLAlchemy 1.4.40; for prior 1.4 versions,use Connection.execution_options.stream_resultsdirectly in combination with Result.yield_per().

Using this option is equivalent to manually setting theConnection.execution_options.stream_results option,described in the next section, and then invoking theResult.yield_per() method on the Resultobject with the given integer value. In both cases, the effect thiscombination has includes:

as result rows are fetched, they will be buffered in batches, where thesize of each batch up until the last batch will be equal to the integerargument passed to theConnection.execution_options.yield_per option or theResult.yield_per() method; the last batch is then sized againstthe remaining rows fewer than this size

To enable server side cursors without a specific partition size, theConnection.execution_options.stream_results option may beused, which like Connection.execution_options.yield_per maybe called on the Connection object or the statement object.

When a Result object delivered using theConnection.execution_options.stream_results optionis iterated directly, rows are fetched internallyusing a default buffering scheme that buffers first a small set of rows,then a larger and larger buffer on each fetch up to a pre-configured limitof 1000 rows. The maximum size of this buffer can be affected using theConnection.execution_options.max_row_buffer execution option:

While the Connection.execution_options.stream_resultsoption may be combined with use of the Result.partitions()method, a specific partition size should be passed toResult.partitions() so that the entire result is not fetched.It is usually more straightforward to use theConnection.execution_options.yield_per option when settingup to use the Result.partitions() method.

it is important to note that the SQL compilation cache is cachingthe SQL string that is passed to the database only, and not the datareturned by a query. It is in no way a data cache and does notimpact the results returned for a particular SQL statement nor does itimply any memory use linked to fetching of result rows.

For the above two SQLite PRAGMA statements, the badge reads [raw sql],which indicates the driver is sending a Python string directly to thedatabase using Connection.exec_driver_sql(). Caching does not applyto such statements because they already exist in string form, and thereis nothing known about what kinds of result rows will be returned sinceSQLAlchemy does not parse SQL strings ahead of time.

It is extremely difficult to measure how much memory is occupied by Pythondata structures, however using a process to measure growth in memory via top as asuccessive series of 250 new statements are added to the cache suggest amoderate Core statement takes up about 12K while a small ORM statement takes about20K, including result-fetching structures which for the ORM will be much greater.

Above, the three lambda callables that are used to define the structureof a SELECT statement are invoked exactly once, and the resulting SQLstring cached in the compilation cache of the engine. From that pointforward, the run_my_statement() function may be invoked any numberof times and the lambda callables within it will not be called, onlyused as cache keys to retrieve the already-compiled SQL.

The introduction on using Connection.execute() made use of thetext() construct in order to illustrate how textual SQL statementsmay be invoked. When working with SQLAlchemy, textual SQL is actually moreof the exception rather than the norm, as the Core expression languageand the ORM both abstract away the textual representation of SQL. However, thetext() construct itself also provides some abstraction of textualSQL in that it normalizes how bound parameters are passed, as well as thatit supports datatyping behavior for parameters and result set rows.

The usage ofConnection.execution_options.stream_results isusually combined with setting a fixed number of rows to to be fetchedin batches, to allow for efficient iteration of database rows whileat the same time not loading all result rows into memory at once;this can be configured on a Result object using theResult.yield_per() method, after execution hasreturned a new Result. IfResult.yield_per() is not used,the Connection.execution_options.stream_resultsmode of operation will instead use a dynamically sized bufferwhich buffers sets of rows at a time, growing on each batchbased on a fixed growth size up until a limit which maybe configured using theConnection.execution_options.max_row_bufferparameter.

When using the ORM to fetch ORM mapped objects from a result,Result.yield_per() should always be used withConnection.execution_options.stream_results,so that the ORM does not fetch all rows into new ORM objects at once.

For typical use, theConnection.execution_options.yield_per executionoption should be preferred, which sets up bothConnection.execution_options.stream_results andResult.yield_per() at once. This option is supportedboth at a core level by Connection as well as by theORM Session; the latter is described atFetching Large Result Sets with Yield Per.

A dictionary mapping schema names to schema names, that will beapplied to the Table.schema element of eachTableencountered when SQL or DDL expression elementsare compiled into strings; the resulting schema name will beconverted based on presence in the map of the original name.

The returned object is a proxied version of the DBAPIconnection object used by the underlying driver in use.The object will have all the same behavior as the real DBAPIconnection, except that its close() method will result in theconnection being returned to the pool, rather than being closedfor real.

This impacts the underlying behavior of the result when iterating overthe result object, or otherwise making use of methods such asResult.fetchone() that return one row at a time. Datafrom the underlying cursor or other data source will be buffered up tothis many rows in memory, and the buffered collection will then beyielded out one row at a time or as many rows are requested. Each timethe buffer clears, it will be refreshed to this many rows or as manyrows remain if fewer remain.

Consider using theConnection.execution_options.yield_perexecution option, which will simultaneously setConnection.execution_options.stream_resultsto ensure the use of server side cursors, as well as automaticallyinvoke the Result.yield_per() method to establisha fixed row buffer size at once.

Additionally, in contrast to the behavior of the legacy ORMQuery.first() method, no limit is applied to theSQL query which was invoked to produce thisResult;for a DBAPI driver that buffers results in memory before yieldingrows, all rows will be sent to the Python process and all butthe first row will be discarded.

This is used for result set caching. The method must be calledon the result when it has been unconsumed, and calling the methodwill consume the result fully. When the FrozenResultis retrieved from a cache, it can be called any number of times whereit will produce a new Result object each timeagainst its stored set of rows.

Note that the backend driver will usually buffer the entire resultahead of time unless theConnection.execution_options.stream_results executionoption is used indicating that the driver should not pre-bufferresults, if possible. Not all drivers support this option andthe option is silently ignored for those who do not. 2351a5e196