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importing a large dataset into odoo 14

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Adriano Peluso

I have a large dataset to be imported in an Odoo instance

The data will be processed and they will populate several different models

I'm assuming the tool to do this os odoorpc

Is this assumption correct ?

Am I missing anything ?

Thanks

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Josep Anton Belchi Riera

What is the question?

Adriano Peluso
Author

sorry, I just erased it by mistake

I need 500 karma points to remove this one and publisha new one

Adriano Peluso
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ok, I managed to edit it

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Thuy Ngoc
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Hi  Adriano,

I think this video can help you:

https://www.youtube.com/watch?v=etMYrOJyaiU&list=PLSKcWRTtEl5qzvRaI-VTGavfReiHS_EEb&index=2

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shubham shiroya
Best Answer

Yes, your assumption is correct. odoorpc is a popular tool for interacting with an Odoo instance using the RPC (Remote Procedure Call) protocol. It allows you to automate various operations, including data import, in an Odoo instance.

To import a large dataset into an Odoo instance using odoorpc, you can follow these steps:

1. Establish a connection: Connect to your Odoo instance using the odoorpc library. Provide the necessary connection details such as the host, port, database name, username, and password.

2. Identify the target models: Determine which Odoo models you need to populate with your data. These models represent the different entities or tables in the Odoo database where your data will be stored.

3. Prepare your data: Organize your data in a format that can be easily processed and mapped to the target models. This could be in the form of CSV files, Excel spreadsheets, JSON, or any other structured format that can be parsed and transformed into Python objects.

4. Iterate through the data: Iterate through your dataset and use the odoorpc library to create records in the target models. For each record, set the appropriate field values based on your data. You can use the `create()` method provided by odoorpc to create new records.

5. Handle relationships: If your data includes relationships between different models (e.g., foreign keys), make sure to handle those relationships appropriately. You may need to query for existing records or create related records before assigning them to the appropriate fields.

6. Commit the changes: Once you have processed all the data and created the records in the target models, make sure to commit the changes to the Odoo database. You can use the `write()` method provided by odoorpc to update existing records if needed.

7. Close the connection: After completing the data import process, close the connection to the Odoo instance using the odoorpc library.

Additionally, it's good practice to handle error scenarios and perform data validation during the import process. You can use try-except blocks to catch and handle any exceptions that may occur during the data import.

By using odoorpc, you have the flexibility to automate and streamline the data import process into your Odoo instance, making it efficient and manageable for large datasets.

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