How to¶
In this tutorial, we will import some datas issue to this csv file
|
City | Contact Name | Country Name | Phone | Street | Street2 | Title | Zip | Partner name | Partner Country Name | Partner City | |||
| default | Paris | Arthur Grosbonnet | France | a.g@wealthyandsons.com | 0268978776 | 1 rue Rockfeller | Sir | 75016 | BML | France | Paris | |||
| invoice | Bruxelles | Carl François | Belgium | carl.françois@bml.be | 0258256545 | 89 Chaussée de Waterloo | 1000 | BML | Belgium | Bruxelles |
Declare your csv file¶
In order to bind csv file and Openerp data models, you have to instanciate a Session, which will read the file and map columns for each data models.
To do this simply do that:
session = Session('file.csv', separator=';', quote='"')
Note
Check for api to have more informations on Session signature.
Declare your models¶
Bind columns with models¶
To configure a Openerp data model, you have to instanciante a Model in order to bind columns with fields:
res_partner = Model('res.partner')
Then you can configure each fields inside the new model, there is 2 ways to do so, First:
res_partner.set_field('name', columns=[1])
...
The second way is to inject fields into the signature of the Model by instanciating Field:
res_partner_address = Model('res.partner.address', fields=[
Field(name='name', columns=[1]),
...
])
Note
Check for api to have more informations on Field signature.
Declare relations¶
csv2oerp also allows you to virtually create the relationship that fields would have between them in Openerp data models.
For example, a res.partner object has a relation to res.partner.address. If these two objects’s field are on the same line (in the CSV file), then you can define a relationship directly into the mapping.
A simple relationship between res.partner to res.partner.address:
+-------------+ +-------------------+
| res.partner | |res.partner.address|
+-------------+ +-------------------+
| | | |
| | partner_id | |
| +-----------------------------+ |
| | 1 | |
| | | |
+-------------+ +-------------------+
partner_model = Model('res.partner', fields=[...])
partner_address = Model('res.partner.address', fields=[
Field('type', default='default'),
# Many2one or One2one
Field(name="partner_id", relation=partner_model),
...
])
The same relationship between res.partner.address to res.partner:
+-------------+ +-------------------+
| res.partner | |res.partner.address|
+-------------+ +-------------------+
| | | |
| | address | |
| +-----------------------------+ |
| | * | |
| | | |
+-------------+ +-------------------+
partner_address_default = Model('res.partner.address', fields=[
Field('type', default='default'),
...
])
partner_address_delivery = Model('res.partner.address', fields=[
Field('type', default='delivery'),
...
])
partner_address_invoice = Model('res.partner.address', fields=[
Field('type', default='invoice'),
...
])
partner_model = Model('res.partner', fields=[
# one2many or many2many
Field(name="addresses", relation=[
partner_address_default, partner_address_delivery, partner_address_invoice
]),
...
])
Setting default values¶
There is two means for this functionnality.
First if a data is missing (as a column) in your csv file. You can then force a value on the field you want to insert without the appropriate binded column.
Model('res.partner.address', fields=[
# this will always have 'invoice' value.
Field("type", default='invoice'),
...
])
Secondly, it can be usefull in case of temporarily missing value on a binded column to define a default. In this example, type must have a value, but in case of null value in a column, the default will be inject instead of it.
Model('res.partner.address', fields=[
# this will have 'default' value only if column have null value.
Field("type", columns=[12], default='default'),
...
])
Setting required value¶
Coming soon ...
Setting unique value¶
Coming soon ...
Column’s value concatenation¶
Coming soon ...
Define custom pre-treatment¶
In order to let you do what you want with values issue from the csv file. A pre-treatment functionnality has been integrated into the fields definition. It’s called a callback. Let’s see with a simple example.
First you have a value on which you want to do some treatment before injecting it into Openerp. To do so, you will create a function which will take as parameter the value you want to modify plus others metadatas. For example, the column associated to the phone and the fax. You want to perform a check of these two phone numbers to determine if its can be injected, reformated or just skipped.
The callback looks like that (You should respect signature):
def phone_check(session, model, value, line_num):
""" Return the phone number reformatted or not if unconsistent
"""
if not value or len(value) != 10: # French length for phone numbers
return None
num_list = [value[:2], value [2:4], value[4:6], value[6:8], value[8:10]]
return ' '.join(num_list)
Field('phone', columns=[2], callbacks=[phone_check]),
Field('fax', columns=[3], callbacks=[phone_check]),
Note
See callback documentation to have more explanation on functionnalities.
For this example, you should also have used the preconfigured callback function too (check_phone):
from csv2oerp.callbacks import get_phones
Field('phone', columns=[2], callbacks=[get_phones('phone')]),
Field('fax', columns=[3], callbacks=[get_phones('fax')]),
Note
Callbacks can be a closure too, with a proper signature usable in the field definition, but only the closure is used by the pre-treatment functionnality.
Note
Callbacks can be used also to dynamically change CRUD actions. See below.
Skip a record (Field level)¶
This functionnality skip a field if the callback return True.
def callback_func_skip(session, model, value, line_num):
""" Check the value and return True or False depending on action you want
Return True = skip field
Return False = allocate field
"""
# Some tests
return True or False
Model('model.name', fields=[
Field(name="field_name", columns=[1], callbacks=[callback_func_skip], skip=True),
])
Skip a record (Model level)¶
This functionnality skip a record if the callback return True.
def callback_func_skip(session, model, value, line_num):
""" Check the value and return True or False depending on action you want
Return True = skip field
Return False = allocate field
"""
# Some tests
return True or False
Model('model.name', fields=[
# All field types
Field(name="field_name1", columns=[0]),
Field(name="field_name3", columns=[2], callbacks=[callback_func_skip], ignore=True),
])
Connection to OpenERP¶
You need an instance of the Openerp class to dialog with an OpenERP server. Let’s pretend that you want to connect as admin on the db_name database of the local OpenERP server (with the XML-RPC service which listens on port 8071). First, prepare the connection:
>>> from csv2oerp import Openerp
>>> oerp = Openerp(
server='localhost',
user='admin',
pwd='admin',
db='db_name',
protocol='xmlrpc',
port=8071)
You can then easily execute some requests with the following CRUD syntaxes.
Launching the importation process¶
Now its time to bind csv files to their appropriated data models. To do so, just link both of them.
session.bind(oerp, models=[
partner_address_default,
partner_address_delivery,
partner_address_invoice,
])
Note
As you could see, the binding between models and oerp is done by the one2many relationship, you bind only higher relations and the link will be automatically created while data processing.
Doing this:
session.bind(oerp, models=[
partner_address_default,
partner_address_delivery,
partner_address_invoice,
partner_model,
])
Will mean the same as the previous example.
Full example¶
See Some examples section.
Getting a resume¶
At the end of your script, you can demand a resume of actions processed during the importation, to do so, just type the following:
csv2oerp.show_stats()
It will show you a resume like this one:
Coming soon ...
