CSV DataSource
The CSV (comma separated values) are most widely used legacy data format.
The CSV data transform requires csv-config
files which are xml based data
mapping rules.
Data Mapping
The CSV data mapping definitions are defined using XML syntax. A typical config file looks like this:
<?xml version="1.0"?>
<csv-inputs xmlns="http://axelor.com/xml/ns/data-import"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://axelor.com/xml/ns/data-import
http://axelor.com/xml/ns/data-import/data-import_5.4.xsd">
<input file="titles.csv" type="com.axelor.contact.db.Title"/>
<input file="circles.csv" type="com.axelor.contact.db.Circle"/>
<input file="company.csv" type="com.axelor.contact.db.Company"/>
<input file="contacts.csv" type="com.axelor.contact.db.Contact"/>
<input file="titles.csv" type="com.axelor.contact.db.Title"
search="self.code = :code" update="true">
<bind to="code" column="code"></bind>
<bind to="name" column="name" if-empty="true"></bind>
</input>
<input file="titles-no-header.csv" type="com.axelor.contact.db.Title"
search="self.code = :code" update="true">
<header>code,name</header>
<bind to="code" column="code"></bind>
<bind to="name" column="name" if-empty="true"></bind>
</input>
<input file="contacts-update.csv" type="com.axelor.contact.db.Contact"
separator="\t"
search="self.firstName = :firstName AND self.lastName = :lastName"
update="true"/>
<input file="taxes.csv" type="com.axelor.sale.db.Tax"/>
<input file="sale-orders.csv" type="com.axelor.sale.db.Order"
call="com.axelor.data.tests.Validators:validateSaleOrder">
<!-- transform boolean value into 'true' or 'false' -->
<bind column="confirmed" to="confirmed"
eval="confirmed ==~ /^(T|Y|1)$/ ? 'true' : 'false'"/>
<bind column="date" to="orderDate"/>
<bind column="date" to="createDate"/>
<!-- default value provided with eval expression -->
<bind to="confirmDate" eval="java.time.LocalDate.now()"/>
<bind to="customer" search="self.email = :email" if="!email.empty">
<bind column="firstName" to="firstName"/>
<bind column="lastName" to="lastName"/>
<bind column="email" to="email"/>
</bind>
<bind to="customer" if="email.empty">
<bind column="firstName" to="firstName"/>
<bind column="lastName" to="lastName"/>
<bind to="email" eval='"${firstName}.${lastName}@gmail.com".toLowerCase()'/>
</bind>
<bind to="items">
<bind column="q1" to="quantity"/>
<bind column="r1" to="price"/>
<bind to="product" search="self.name = :p1">
<bind column="p1" to="name"/>
<bind column="p1" to="code"/>
</bind>
<bind column="t11" to="taxes" search="self.code = :t11"/>
<bind column="t12" to="taxes" search="self.code = :t12"/>
</bind>
<bind to="items">
<bind column="q2" to="quantity"/>
<bind column="r2" to="price"/>
<bind to="product" search="self.name = :p2">
<bind column="p2" to="name"/>
<bind column="p2" to="code"/>
</bind>
<bind column="t2" to="taxes" search="self.code in :t2"
eval="t2.split('\\|') as List"/>
</bind>
</input>
</csv-input>
As you can see, a mapping file maps input files to target objects and binds csv columns to target object fields. The syntax is self-explanatory and easy to understand.
Let’s see the binding in details:
The <input>
tag is used to map a source csv file to a target model type.
Attribute | Description |
---|---|
|
the source input file name |
|
the target model name |
|
the separator character (default is comma |
|
JPQL where clause search for existing record |
|
|
|
call a method on the transformed object before saving it to database |
|
call a method to prepare context before transforming the csv row |
The <input>
can be used in many ways. You can see the first four inputs in the
example are very simple. This is because of automatic import as the csv header
column names matches to the target model field names. Otherwise, we need to
specify binding manually using the <bind>
tag.
The <bind>
tag can be used to map CSV columns to a target object field.
Attribute | Description |
---|---|
|
the CSV column name |
|
the target model field name |
|
type adapter, followed by an optional string argument separated by |
|
jpql where clause search for existing record |
|
if search returns an existing record whether to update it |
|
groovy expression, to transform the value |
|
boolean groovy expression, only bind if condition passed |
|
only update the target value if target field is empty (or null) |
The <bind>
tag can again have nested <bind>
tags in case of binding
relational fields.
Automatic Import
If the CSV data files have identical columns with the field names of the target domain model class, it can be imported automatically with minimal configuration.
title.code,firstName,lastName,email,phone,dateOfBirth,group.code,company.code
mr,Peter,Parker,peter.parker@gmail.com,,1988-11-11,friends,
mr,John,Smith,jsmith@gmail.com,,1979-11-01,friends,my
The first line of the CSV file gives fields information.
The dotted fields title.code
, group.code
and company.code
can be used to
related records directly.
One of the major concern of importing data from external source is to manage relationship (data integration). As primary keys are often auto-generated values it’s not easy to map the source keys with the target key. In order to overcome with this issue, instead of referencing the relations with primary key, we are using one or more keys of the related object that results in unique constraint to locate referenced record.
Here title.code
tells the transformation engine to query the referenced
title
record by code
field. We can also provide multiple lookup fields like:
orderDate,confirmed,...,customer.firstName,customer.lastName,...
In this case the record will be fetched by AND expression like this:
SELECT self FROM Contact self WHERE self.firstName = :firstName AND self.lastName = :lastName
Similarly, many-to-many
fields can be imported with multiple values separated
with |
like this:
...,taxes.code
...,tax1.4|tax0.2|tax0.4
The many-to-many field will be set with the result of following query:
SELECT self FROM Tax self WHERE self.code IN :code
The format of `csv-config.xml
for automatic import looks like this:
<?xml version="1.0"?>
<csv-inputs xmlns="http://axelor.com/xml/ns/data-import"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://axelor.com/xml/ns/data-import
http://axelor.com/xml/ns/data-import/data-import_5.4.xsd">
<input file="titles.csv" type="com.axelor.contact.db.Title"/>
<input file="company.csv" type="com.axelor.contact.db.Company"/>
...
...
...
</csv-inputs>
Advanced Import
Sometimes it’s more convenient to import complex records at once instead of providing different CSV for each object in the object graph.
For example, sale orders, consider the following input:
confirmed,date,firstName,lastName,email,p1,q1,r1,t11,t12,p2,q2,r2,t2
T,2011-12-11,John,Smith,j.smith@gmail.com,PC1,1,200.12,vat0.4,stx,PC2,4,230.23,vat0.4|stx
1,2011-12-12,John,Smith,j.smith@gmail.com,PC1,1,200.12,vat0.4,stx,PC2,4,230.23,vat0.6|stx
F,2011-12-13,John,Smith,j.smith@gmail.com,PC1,10,200.12,vat0.4,stx,PC2,3,230.23,vat0.4|stx
F,2011-12-14,John,Smith,,L1,5,20.12,vat0.4,stx,L2,3,20.23,vat0.4|vat0.6
A confirmed order placed on a particular date by someone with the given items. The columns are not matched with underlying object so can’t be mapped automatically.
The manual data binding should be done from configuration like this:
<?xml version="1.0"?>
<csv-inputs xmlns="http://axelor.com/xml/ns/data-import"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://axelor.com/xml/ns/data-import
http://axelor.com/xml/ns/data-import/data-import_5.4.xsd">
...
...
<input file="sale-orders.csv" type="com.axelor.sale.db.Order"
call="com.axelor.data.tests.Validators:validateSaleOrder">
<!-- transform boolean value into 'true' or 'false' -->
<bind column="confirmed" to="confirmed"
eval="confirmed ==~ /^(T|Y|1)$/ ? 'true' : 'false'"/>
<bind column="date" to="orderDate"/>
<bind column="date" to="createDate"/>
<!-- default value provided with eval expression -->
<bind to="confirmDate" eval="java.time.LocalDate.now()"/>
<bind to="customer" search="self.email = :email" if="!email.empty">
<bind column="firstName" to="firstName"/>
<bind column="lastName" to="lastName"/>
<bind column="email" to="email"/>
</bind>
<bind to="customer" if="email.empty">
<bind column="firstName" to="firstName"/>
<bind column="lastName" to="lastName"/>
<bind to="email" eval='"${firstName}.${lastName}@gmail.com".toLowerCase()'/>
</bind>
<bind to="items">
<bind column="q1" to="quantity"/>
<bind column="r1" to="price"/>
<bind to="product" search="self.name = :p1">
<bind column="p1" to="name"/>
<bind column="p1" to="code"/>
</bind>
<bind column="t11" to="taxes" search="self.code = :t11"/>
<bind column="t12" to="taxes" search="self.code = :t12"/>
</bind>
<bind to="items">
<bind column="q2" to="quantity"/>
<bind column="r2" to="price"/>
<bind to="product" search="self.name = :p2">
<bind column="p2" to="name"/>
<bind column="p2" to="code"/>
</bind>
<bind column="t2" to="taxes" search="self.code in :t2"
eval="t2.split('\\|') as List"/>
</bind>
</input>
</csv-inputs>
The related records can be searched using the given search query. If related object is not found, a new record will be created.
Conditional Binding
This feature allows you to bind columns based on some condition. This can be done like this:
...
<bind to="customer" search="self.email = :email" if="!email.empty">
<bind column="firstName" to="firstName"/>
<bind column="lastName" to="lastName"/>
<bind column="email" to="email"/>
</bind>
<bind to="customer" if="email.empty">
<bind column="firstName" to="firstName"/>
<bind column="lastName" to="lastName"/>
<bind to="email" eval='"${firstName}.${lastName}@gmail.com".toLowerCase()'/>
</bind>
...
The first binding is applied if the given if condition !email.empty
is
evaluated to true. In that case, the record will be searched by the given search
expression and if found will be updated with provided values. If not, a new
record will be created.
The second binding is applied if the given if condition email.empty
is
evaluated to true. In this case, a new record is created with a calculated email address.
The if conditions should be simple groovy expressions.