Import data workflow¶
This document describes the import data workflow in detail, with hooks that enable
customization of the import process. The central aspect of the import process is a resource’s
import_data()
method which is explained below.
-
import_data
(dataset, dry_run=False, raise_errors=False)¶ The
import_data()
method ofResource
is responsible for importing data from a given dataset.dataset
is required and expected to be atablib.Dataset
with a header row.dry_run
is a Boolean which determines if changes to the database are made or if the import is only simulated. It defaults toFalse
.raise_errors
is a Boolean. IfTrue
, import should raise errors. The default isFalse
, which means that eventual errors and traceback will be saved inResult
instance.
This is what happens when the method is invoked:
First, a new
Result
instance, which holds errors and other information gathered during the import, is initialized.Then, an
InstanceLoader
responsible for loading existing instances is intitalized. A differentBaseInstanceLoader
can be specified viaResourceOptions
‘sinstance_loader_class
attribute. ACachedInstanceLoader
can be used to reduce number of database queries. See the source for available implementations.The
before_import()
hook is called. By implementing this method in your resource, you can customize the import process.Each row of the to-be-imported dataset is processed according to the following steps:
The
before_import_row()
hook is called to allow for row data to be modified before it is importedget_or_init_instance()
is called with currentBaseInstanceLoader
and current row of the dataset, returning an object and a Boolean declaring if the object is newly created or not.If no object can be found for the current row,
init_instance()
is invoked to initialize an object.As always, you can override the implementation of
init_instance()
to customized how the new object is created (i.e. set default values).for_delete()
is called to determine if the passedinstance
should be deleted. In this case, the import process for the current row is stopped at this point.If the instance was not deleted in the previous step,
import_obj()
is called with theinstance
as current object,row
as current row anddry run
.import_field()
is called for each field inResource
skipping many- to-many fields. Many-to-many fields are skipped because they require instances to have a primary key and therefore assignment is postponed to when the object has already been saved.import_field()
in turn callssave()
, ifField.attribute
is set andField.column_name
exists in the given row.It then is determined whether the newly imported object is different from the already present object and if therefore the given row should be skipped or not. This is handled by calling
skip_row()
withoriginal
as the original object andinstance
as the current object from the dataset.If the current row is to be skipped,
row_result.import_type
is set toIMPORT_TYPE_SKIP
.If the current row is not to be skipped,
save_instance()
is called and actually saves the instance whendry_run
is not set.There are two hook methods (that by default do nothing) giving you the option to customize the import process:
Both methods receive
instance
anddry_run
arguments.save_m2m()
is called to save many to many fields.RowResult
is assigned with a diff between the original and the imported object fields, as well as andimport_type
attribute which states whether the row is new, updated, skipped or deleted.If an exception is raised during row processing and
import_data()
was invoked withraise_errors=False
(which is the default) the particular traceback is appended toRowResult
as well.If either the row was not skipped or the
Resource
is configured to report skipped rows, theRowResult
is appended to theResult
The
after_import_row()
hook is called
The
Result
is returned.
Transaction support¶
If transaction support is enabled, whole import process is wrapped inside
transaction and rollbacked or committed respectively.
All methods called from inside of import_data
(create / delete / update)
receive False
for dry_run
argument.