refactor(spp_mis_demo_v2): remove Faker dependency, use pure seeded RNG for name generation

Replace all Faker usage with deterministic random.Random(seed).choice()
from locale-specific name arrays. This ensures fully reproducible output
across runs with the same seed.

- Remove create_faker import and fake variable from mis_demo_generator
- Delete dead code: _generate_random_groups, _create_random_individual,
  _generate_volume_enrollments
- Remove fake parameter from _create_program_cycles
- Remove faker from external_dependencies in manifest
- Remove tests that called deleted _create_random_individual method
- Update docs and docstrings to reflect seeded RNG approach

Author: emjay0921

spp_mis_demo_v2/__manifest__.py

@@ -24,7 +24,7 @@
         "spp_claim_169",
         # Demo-specific extensions
     ],
-    "external_dependencies": {"python": ["faker", "requests"]},
+    "external_dependencies": {"python": ["requests"]},
     "post_init_hook": "post_init_hook",
     "data": [
         "security/ir.model.access.csv",

spp_mis_demo_v2/docs/USE_CASES.md

@@ -1,7 +1,7 @@
 # OpenSPP MIS Demo V2 - Use Cases Guide
 
-This document describes the different demo use cases available in the `spp_mis_demo_v2` module and how to use them
-effectively for sales demos, training, and testing.
+This document describes the different demo use cases available in the `spp_mis_demo_v2`
+module and how to use them effectively for sales demos, training, and testing.
 
 ## Table of Contents
 
@@ -19,11 +19,13 @@ effectively for sales demos, training, and testing.
 
 ## Overview
 
-The MIS Demo V2 module provides realistic demo data that showcases OpenSPP's capabilities for social protection program
-management. It follows the **Blueprint + Seeded Faker** architecture:
+The MIS Demo V2 module provides realistic demo data that showcases OpenSPP's
+capabilities for social protection program management. It follows the **Blueprint +
+Seeded RNG** architecture:
 
 - **Fixed Stories**: 8 named personas with predefined program journeys (unchanged)
-- **Deterministic Volume**: ~730 households with ~2,500 members from 28 blueprint templates
+- **Deterministic Volume**: ~730 households with ~2,500 members from 28 blueprint
+  templates
 - **Demo Programs**: 6 programs covering different social protection scenarios
 - **100% Reproducible**: Same country selection = identical output every run
 - **Country-aware Names**: Names change by locale (Philippines, Sri Lanka, Togo)
@@ -32,14 +34,17 @@ management. It follows the **Blueprint + Seeded Faker** architecture:
 
 ## Blueprint Architecture
 
-Volume data is generated from **28 household blueprint templates** — deterministic definitions that specify household
-composition (members, ages, genders), income bracket, and program eligibility. Blueprints are multiplied by their
-`count` to reach the target volume.
+Volume data is generated from **28 household blueprint templates** — deterministic
+definitions that specify household composition (members, ages, genders), income bracket,
+and program eligibility. Blueprints are multiplied by their `count` to reach the target
+volume.
 
 **Key properties:**
 
-- All structural choices (ages, incomes, genders for "any" specs) use `random.Random(42)` — deterministic
-- Names are generated by `Faker(locale, seed=42)` — deterministic per locale
+- All structural choices (ages, incomes, genders for "any" specs) use
+  `random.Random(42)` — deterministic
+- Names are generated by `random.Random(42).choice()` from locale-specific arrays —
+  deterministic per locale
 - Reserved story names are never used for volume records
 - Each blueprint defines eligibility flags per program, ensuring consistent enrollment
 
@@ -56,15 +61,17 @@ composition (members, ages, genders), income bracket, and program eligibility. B
 
 ## Country / Locale Support
 
-The wizard lets you choose a country. This determines the locale for name generation and the company currency.
+The wizard lets you choose a country. This determines the locale for name generation and
+the company currency.
 
 | Country     | Locale   | Currency                     | Name Examples                |
 | ----------- | -------- | ---------------------------- | ---------------------------- |
 | Philippines | `fil_PH` | PHP (Philippine Peso)        | Juan Santos, Maria Dela Cruz |
 | Sri Lanka   | `si_LK`  | LKR (Sri Lankan Rupee)       | Kasun Perera, Ishara Silva   |
 | Togo        | `fr_TG`  | XOF (West African CFA Franc) | Koffi Mensah, Ama Dosseh     |
 
-**Reproducibility guarantee**: Selecting the same country always produces the exact same set of records.
+**Reproducibility guarantee**: Selecting the same country always produces the exact same
+set of records.
 
 ---
 
@@ -440,8 +447,8 @@ The wizard lets you choose a country. This determines the locale for name genera
 
 ## Formula Library Demo
 
-The MIS Demo includes comprehensive formula library data demonstrating versioned, auditable business rules for
-eligibility, entitlements, and scoring.
+The MIS Demo includes comprehensive formula library data demonstrating versioned,
+auditable business rules for eligibility, entitlements, and scoring.
 
 ### Formula Categories
 
@@ -472,9 +479,10 @@ eligibility, entitlements, and scoring.
 household.pmt_score < 45.0 && household.member_count > 0
 ```
 
-**Test Cases:** | Persona | PMT Score | Expected | Result | |---------|-----------|----------|--------| | Maria Santos |
-38 | `true` | ✓ Eligible | | Rosa Garcia | 42 | `true` | ✓ Eligible | | Carlos Morales | 48 | `false` | ✗ Not eligible |
-| Ibrahim Hassan | 35 | `true` | ✓ Eligible |
+**Test Cases:** | Persona | PMT Score | Expected | Result |
+|---------|-----------|----------|--------| | Maria Santos | 38 | `true` | ✓ Eligible |
+| Rosa Garcia | 42 | `true` | ✓ Eligible | | Carlos Morales | 48 | `false` | ✗ Not
+eligible | | Ibrahim Hassan | 35 | `true` | ✓ Eligible |
 
 ---
 
@@ -493,8 +501,9 @@ household.pmt_score < 45.0 && household.member_count > 0
 individual.age >= 65 && !individual.receives_other_pension
 ```
 
-**Test Cases:** | Persona | Age | Other Pension | Expected | |---------|-----|---------------|----------| | Rosa Garcia
-| 72 | No | `true` ✓ | | Maria Santos | 45 | No | `false` ✗ | | Pedro Reyes | 55 | No | `false` ✗ |
+**Test Cases:** | Persona | Age | Other Pension | Expected |
+|---------|-----|---------------|----------| | Rosa Garcia | 72 | No | `true` ✓ | |
+Maria Santos | 45 | No | `false` ✗ | | Pedro Reyes | 55 | No | `false` ✗ |
 
 ---
 
@@ -513,8 +522,9 @@ individual.age >= 65 && !individual.receives_other_pension
 150.0 + (household.child_count * 50.0) * (household.is_rural ? 1.2 : 1.0)
 ```
 
-**Test Cases:** | Persona | Children | Rural | Expected Amount | |---------|----------|-------|-----------------| |
-Maria Santos | 2 | Yes | $270 | | Carlos Morales | 3 | No | $300 | | Ana Mendoza | 1 | Yes | $210 |
+**Test Cases:** | Persona | Children | Rural | Expected Amount |
+|---------|----------|-------|-----------------| | Maria Santos | 2 | Yes | $270 | |
+Carlos Morales | 3 | No | $300 | | Ana Mendoza | 1 | Yes | $210 |
 
 ---
 
@@ -537,8 +547,9 @@ min(40, (100 - household.pmt_score) * 0.5)
 ```
 
 **Test Cases:** | Persona | Female-Headed | Disabled | Dep. Ratio | PMT | Score |
-|---------|---------------|----------|------------|-----|-------| | Rosa Garcia | No | No | 0.0 | 42 | 29 | | Maria
-Santos | Yes | No | 0.4 | 38 | 51 | | Ibrahim Hassan | No | Yes | 0.6 | 35 | 72 |
+|---------|---------------|----------|------------|-----|-------| | Rosa Garcia | No |
+No | 0.0 | 42 | 29 | | Maria Santos | Yes | No | 0.4 | 38 | 51 | | Ibrahim Hassan | No |
+Yes | 0.6 | 35 | 72 |
 
 ---
 
@@ -587,7 +598,8 @@ vulnerability_score(household) * 0.6 +
 
 **Objective:** Demonstrate formula versioning for policy changes
 
-**Story:** Government decides to expand Cash Transfer coverage by raising PMT threshold from 45 to 50.
+**Story:** Government decides to expand Cash Transfer coverage by raising PMT threshold
+from 45 to 50.
 
 **Steps:**
 
@@ -817,7 +829,8 @@ vulnerability_score(household) * 0.6 +
 
 ## Event Data
 
-The MIS Demo generates event records that track beneficiary interactions with the system.
+The MIS Demo generates event records that track beneficiary interactions with the
+system.
 
 ### Event Types
 
@@ -914,7 +927,8 @@ This ensures proper integration between modules and complete demo scenarios.
 
 ### GRM Integration
 
-The GRM demo creates specific tickets for story personas that integrate with their MIS journeys:
+The GRM demo creates specific tickets for story personas that integrate with their MIS
+journeys:
 
 | Story            | GRM Ticket           | Links To                   |
 | ---------------- | -------------------- | -------------------------- |