Why Use Python Instead of Views?

  1. Flexibility: Python allows dynamic data manipulation based on conditions.
  2. Complex Data Transformations: Perform aggregations, computations, or transformations beyond the capabilities of views.
  3. Performance Optimization: By querying and processing data selectively, Python-based solutions can reduce computation overhead.

Step-by-Step Guide

  1. Define the Report Action In your manifest.py file, define the custom report action:
{
    'name': 'Custom Odoo Report',
    'summary': 'A Python-based custom report with group-by and filter capabilities',
    'depends': ['base', 'report'],
    'data': ['views/report_template.xml'],
    'installable': True,
    'application': False,
}

2. Create a Report Template
Define your report template in an XML file. For example:

<template id="report_custom_template">
    <t t-call="web.html_container">
        <t t-foreach="docs" t-as="doc">
            <p><t t-esc="doc.name"/></p>
            <p><t t-esc="doc.total_amount"/></p>
        </t>
    </t>
</template>

3. Write a Python Function for the Report Logic
Inherit the Odoo models.Model class to define a Python method for your report data:

from odoo import models, fields, api  

class CustomReport(models.AbstractModel):  
    _name = 'report.module_name.report_template'  

    @api.model  
    def _get_report_values(self, docids, data=None):  
        records = self.env['your.model.name'].search([])  

        # Apply filtering  
        filtered_records = records.filtered(lambda r: r.field_name > 100)  

        # Group-by logic  
        grouped_data = {}  
        for record in filtered_records:  
            key = record.group_field  
            grouped_data.setdefault(key, 0)  
            grouped_data[key] += record.amount  

        return {  
            'docs': [{'name': key, 'total_amount': value} for key, value in grouped_data.items()]  
        }  

Benefits of Using Python for Report Development

  • Customizable Filters: You can filter data based on user input or dynamic conditions.
  • Enhanced Group-By Options: Grouping data programmatically allows for nested groupings or multi-dimensional data.
  • Optimized Performance: Handle large datasets efficiently by querying only required data.

Conclusion
Building custom Odoo reports using Python provides unparalleled flexibility for businesses seeking tailored solutions. This approach is particularly valuable for companies offering Odoo development services that aim to deliver advanced reporting capabilities to their clients.

Author Of article : maisie brooke Read full article