Wednesday, September 2, 2026
2 changes · saas-18.4
Enhancements to existing features
Appointment pages now calculate available booking capacities much more efficiently, especially when many linked resources are involved. This reduces slow page loads from minutes to seconds in affected cases and also corrects some capacity values shown during resource selection.
Original PR description
Before --- - When opening the appointment page, the possible capacities that a user can book needs to be calculated to show the capacity dropdown. - This is currently done by getting all the possible…
Before
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- When opening the appointment page, the possible capacities that a user can book needs to be calculated to show the capacity dropdown.
- This is currently done by getting all the possible combinations that could arise from each resource along with its linked resources (Linked resources are resources that are used to combine with the main resource to allow a bigger capacity)
- The complexity of this approach blows up with the increase in linked resources. For each resource we end up with O(2^m) where m is the number of linked resources it has. If they have the same number of linked resources, and n is the number of resources, we end up with O(n*2^m)
Solution:
- Flipping the algorithm, we create a structure for possible capacities and only keep the best combination for a found capacity.
- We first store all available capacity for relevant resources.
Algorithm
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For a resource:
- We initialize the solution S to {0: []}
- Greedy dynamic programming is then used to get all the possible combinations by building the result dict, adding one resource at a time. We add its capacity to all entries of S -> we use the combination if a new capacity is reached OR update the combination if the number of elements of combination is less than the existing one.
Then, for the global solution:
- We go through S of resources (in the order of self), and add entries to G (the general dict of solutions). Again, on collision, we only keep the lower-cardinal combination.
The complexity of this algorithm is O(n*u) where u is the dynamic programming complexity. u would be quadratic O(m^2) if the sub-sums of capacities overlap heavily, for instance when resources have the same capacity, like tables of a restaurant, but could reach (2^m) in the worst case scenario.
Related changes / side effects
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1. Fixing an issue
2. Cleaning strange logic
3. Cleaning max capacity computation
Benchmark:
- opw-5177932 goes down from 6 mins to less than 2 seconds using the new algorithm.
Also include
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Fix the max capacity on resources when skipping resource selection. It computed the max capa based on values that were not yet emptied in the website_appointment controller.
Task-6233563
Forward-Port-Of: odoo/enterprise#118981Ecuadorian electronic invoicing now lets companies enter their third-party software provider's RUC in settings. This value is automatically included in electronic documents, printed reports, and delivery guides to help meet SRI reporting requirements.
Original PR description
Purpose: SRI Resolution requires taxpayers using 3rd-party billing software in Ecuador to report the software provider's RUC on all electronic documents and printed representations (RIDE). A new system parameter is introduced and displayed in Invoicing > Setting > Ecuadorian Localization > Electronic Invoicing, so users can add their software provider's RUC. This value will be automatically sent to the EDI and displayed on the report. task-6432810 Forward-Port-Of: odoo/enterprise#129456