Metadata-Version: 2.4
Name: odoo-connect
Version: 0.6.0
Summary: Simple RPC client for Odoo
Author-email: Krzysztof Magusiak <chrmag@poczta.onet.pl>
License:                    GNU LESSER GENERAL PUBLIC LICENSE
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Project-URL: Homepage, https://github.com/kmagusiak/odoo-connect
Keywords: odoo,rpc
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)
Classifier: Programming Language :: Python :: 3
Classifier: Framework :: Odoo
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: requests
Provides-Extra: pinned
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Provides-Extra: test
Requires-Dist: pytest==8.3.2; extra == "test"
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Dynamic: license-file

# Odoo Connect

A simple library to use Odoo RPC.

[![PyPI version](https://badge.fury.io/py/odoo-connect.svg)](https://pypi.org/project/odoo-connect/)

## Usage

```python
import odoo_connect
odoo = env = odoo_connect.connect(url='http://localhost:8069', username='admin', password='admin')
so = env['sale.order']
so.search_read([('create_uid', '=', 1)], [])
```

## /json/2/ support

Since the introduction of `/json/2` in Odoo 19, there is no need to use this
library. You can use any HTTP client and simply send RPC calls.
You could use this library to explore the data more easily. If this is the
case, pass a token instead of user/password when connecting.

```python
import httpx
API_KEY = ...
cli = httpx.Client(base_url=..., headers={'Authorization': f'Bearer {API_KEY}'})
resp = cli.post('/json/2/sale.order/search_read', json={'domain': [], 'limit': 5})
resp.raise_for_status().json()
```

## Rationale

[OdooRPC](https://pypi.org/project/OdooRPC/)
or [Odoo RPC Client](https://pypi.org/project/odoo-rpc-client/)
are both more complete and mimic internal Odoo API.
Then [aio-odoorpc](https://pypi.org/project/aio-odoorpc/) provides
an asynchronous API.

This library provides only a simple API for connecting to the server
and call methods, so the maintenance should be minimal.

Note that each RPC call is executed in a transaction.
So the following code on the server, will add one to every line ordered
quantity or fail and do nothing.
However, RPC client libraries will perform multiple steps, on a failure,
already executed code was committed. You can end with race conditions
where some other code sets product_uom_qty to 0 before you increment it.
A better way of doing this is to implement a function on Odoo side and call it.

```python
lines = env['sale.order.line'].search([
	('order_id.name', '=', 'S00001')
])
# this is fine on the server, but not in RPC (multiple transactions)
for line in lines:
	if line.product_uom_qty > 1:
		line.product_uom_qty += 1
# single transaction
lines.increment_qty([('product_uom_qty', '>', 1)])
```

## Export and import data

A separate package provides utilities to more easily extract data from Odoo.

Since Odoo doesn't accept all kind of values, the `format` package will help
with converting between python values and values returned by Odoo.

The provided function will return a table-like (list of lists) structure
with the requested data.
You can also pass `ir.filters` names or `ir.exports` names instead of,
respectively, domains and fields. Note that this doesn't support groupping.

```python
import odoo_connect.data as odoo_data
so = env['sale.order']

# Read data as usual
data = so.search_read_dict([('state', '=', 'sale')], ['name', 'partner_id.name'])
so.read_group([], ['amount_untaxed'], ['partner_id', 'create_date:month'])
odoo_data.add_url(so, data)

# Exporting flattened data
all_data = odoo_data.export_data(so, [('state', '=', 'sale')], ['name', 'partner_id.name'])
with io.StringIO(newline='') as f:
    w = csv.writer(f, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
    w.writerows(all_data.to_csv())
all_data.to_pandas()  # as a data frame
all_data.to_dbapi(con, 'table_name')  # create a table

# Import data using Odoo's load() function
odoo_data.load_data(so, data)

# Import data using writes and creates (or another custom method)
for batch in odoo_data.make_batches(data):
	# add ids by querying the model using the 'name' field
	# if you remove 'id' from the data, only create() is called
	odoo_data.add_fields(so, batch, 'name', ['id'])
	odoo_data.load_data(so, batch, method='write')
```

## Explore

Provides a simple abstraction for querying data with a local cache.
It may be easier than executing and parsing a `read()`.
Also, auto-completion for fields is provided in jupyter.

```python
from odoo_connect.explore import explore
sale_order = explore(env['sale.order'])
sale_order = sale_order.search([], limit=1)
sale_order.read()
```

## Development

You can use a vscode container and open this repository inside it.
Alternatively, clone and setup the repository manually.

```bash
git clone $url
cd odoo-connect
# Install dev libraries
pip install -e .[pinned,dev,test]
./pre-commit install
# Run some tests
pytest
```
