Add CI, dependabot, issue/PR templates for public repo (#1)

hmgaudecker · claude · web-flow · commit 5f1a4557721b · 2026-04-18T19:10:17.000+02:00
Co-authored-by: Claude Opus 4.7 (1M context) &lt;noreply@anthropic.com&gt;
diff --git a/.github/ISSUE_TEMPLATE/bug_report.md b/.github/ISSUE_TEMPLATE/bug_report.md
@@ -0,0 +1,31 @@
+---
+name: Bug Report
+about: Create a bug report to help us improve aca-model
+title: "BUG:"
+type: "Bug"
+---
+
+- [ ] I have checked that this issue has not already been reported.
+
+- [ ] I have confirmed this bug exists on the latest version of aca-model.
+
+- [ ] (optional) I have confirmed this bug exists on the `main` branch of aca-model.
+
+---
+
+**Note**: Please read [this
+guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing
+how to provide the necessary information for us to reproduce your bug.
+
+#### Code Sample, a copy-pastable example
+
+```python
+# Your code here
+```
+
+#### Problem description
+
+Explain **why** the current behaviour is a problem and why the expected output is a
+better solution.
+
+#### Expected Output
diff --git a/.github/ISSUE_TEMPLATE/enhancement.md b/.github/ISSUE_TEMPLATE/enhancement.md
@@ -0,0 +1,40 @@
+---
+name: Enhancement
+about: Suggest an idea for aca-model
+title: "ENH:"
+---
+
+> [!IMPORTANT]
+> Select **one** of the following types to describe your enhancement:
+> - **Feature**: A new feature or capability
+> - **Task**: A task that needs to be done (e.g., fix typos in the documentation)
+>
+> If your enhancement is related to the documentation, select the label
+> **documentation**.
+
+
+#### Is your feature request related to a problem?
+
+Provide a description of what the problem is, e.g. "I wish I could use aca-model to do
+[...]".
+
+#### Describe the solution you'd like
+
+Provide a description of the feature request and how it might be implemented.
+
+#### API breaking implications
+
+Provide a description of how this feature will affect the API.
+
+#### Describe alternatives you've considered
+
+Provide a description of any alternative solutions or features you've considered.
+
+#### Additional context
+
+Add any other context, code examples, or references to existing implementations about
+the feature request here.
+
+```python
+# Your code here, if applicable
+```
diff --git a/.github/PULL_REQUEST_TEMPLATE/pull_request_template.md b/.github/PULL_REQUEST_TEMPLATE/pull_request_template.md
@@ -0,0 +1,11 @@
+### What problem do you want to solve?
+
+Reference the issue or discussion, if there is any. Provide a description of your
+proposed solution.
+
+### Todo
+
+- [ ] Target the right branch and pick an appropriate title.
+- [ ] Put `Closes #XXXX` in the first PR comment to auto-close the relevant issue once
+  the PR is accepted. This is not applicable if there is no corresponding issue.
+- [ ] Any steps that still need to be done.
diff --git a/.github/dependabot.yml b/.github/dependabot.yml
@@ -0,0 +1,11 @@
+---
+version: 2
+updates:
+  - package-ecosystem: github-actions
+    directory: /
+    schedule:
+      interval: monthly
+    groups:
+      github-actions:
+        patterns:
+          - '*'
diff --git a/.github/workflows/main.yml b/.github/workflows/main.yml
@@ -0,0 +1,36 @@
+---
+name: main
+concurrency:
+  group: ${{ github.head_ref || github.run_id }}
+  cancel-in-progress: true
+on:
+  push:
+    branches:
+      - main
+  pull_request:
+    branches:
+      - '**'
+jobs:
+  run-tests:
+    name: Run tests on ${{ matrix.os }}
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        os:
+          - ubuntu-latest
+        python-version:
+          - '3.14'
+    steps:
+      - uses: actions/checkout@v6
+      - uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Install pylcm (unreleased feature branch required)
+        run: >-
+          pip install "pylcm @
+          git+https://github.com/OpenSourceEconomics/pylcm.git@feature/h-consumes-dag-outputs"
+      - name: Install aca-model with test deps
+        run: pip install -e . pytest pdbp
+      - name: Run pytest
+        run: pytest tests
diff --git a/LICENSE b/LICENSE
@@ -1,4 +1,4 @@
-Copyright (c) 2026 The aca-model Authors
+Copyright (c) 2026 Hans-Martin von Gaudecker
 
                                  Apache License
                            Version 2.0, January 2004
diff --git a/scripts/generate_benchmark_params.py b/scripts/generate_benchmark_params.py
diff --git a/src/aca_model/_benchmark_data/__init__.py b/src/aca_model/_benchmark_data/__init__.py
diff --git a/src/aca_model/_benchmark_data/benchmark_params.pkl b/src/aca_model/_benchmark_data/benchmark_params.pkl
diff --git a/src/aca_model/benchmark.py b/src/aca_model/benchmark.py
@@ -5,11 +5,12 @@
 continuous state). Use for ASV benchmarks and fast end-to-end
 integration tests without requiring the aca-data pipeline.
 
-Parameters (`fixed_params` + `params`) are a frozen snapshot of one
-production run, shipped as a pickle in
-`aca-model/tests/data/benchmark_params.pkl`. Regenerate via
-`scripts/generate_benchmark_params.py` after changes to parameter
-assembly.
+Parameters (`fixed_params` + `params`) are a committed stub fixture
+packaged alongside the module at
+`src/aca_model/_benchmark_data/benchmark_params.pkl` — aggregate-level
+values (policy schedules, transition probabilities, fitted
+coefficients) with no runtime dependency on aca-data or any data-prep
+package.
 
 Initial conditions are drawn randomly per call — assets/aime/wage_res
 from their grid ranges, discrete states from their categories, regimes
@@ -33,7 +34,7 @@
 from aca_model.config import BENCHMARK_GRID_CONFIG
 
 _PARAMS_FILE = (
-    Path(__file__).resolve().parents[2] / "tests" / "data" / "benchmark_params.pkl"
+    Path(__file__).resolve().parent / "_benchmark_data" / "benchmark_params.pkl"
 )
 
 _DERIVED_CATEGORICALS = {
diff --git a/tests/helpers/__init__.py b/tests/helpers/__init__.py
diff --git a/tests/helpers/social_security.py b/tests/helpers/social_security.py
@@ -0,0 +1,72 @@
+"""Social Security lookup-table helpers used by tests.
+
+Inlined from the aca-data pipeline so the aca-model test suite has no
+runtime dependency on the data-prep package.
+"""
+
+import numpy as np
+import pandas as pd
+from numpy.typing import NDArray
+
+
+def compute_pia_table(
+    aime_kink_0: float,
+    aime_kink_1: float,
+    pia_conversion_rate_0: float,
+    pia_conversion_rate_1: float,
+    pia_conversion_rate_2: float,
+    max_aime: float,
+) -> tuple[NDArray[np.float64], NDArray[np.float64]]:
+    """Pre-compute PIA lookup table on the minimal 4-point grid.
+
+    PIA is piecewise linear with 2 kinks, so 4 grid points suffice for
+    exact interpolation via `jnp.interp` at any AIME value.
+    """
+    pia_kink_0 = pia_conversion_rate_0 * aime_kink_0
+    pia_kink_1 = pia_kink_0 + pia_conversion_rate_1 * (aime_kink_1 - aime_kink_0)
+
+    aime_grid = np.array([0.0, aime_kink_0, aime_kink_1, max_aime])
+    pia_table = np.array(
+        [
+            0.0,
+            pia_kink_0,
+            pia_kink_1,
+            pia_kink_1 + pia_conversion_rate_2 * (max_aime - aime_kink_1),
+        ]
+    )
+    return aime_grid, pia_table
+
+
+def compute_di_dropout_scale(
+    ratio_lowest_earnings: pd.Series,
+    aime_accrual_factor: float,
+    start_age: int,
+    n_periods: int,
+) -> np.ndarray:
+    """Pre-compute DI dropout-year scale factors for all periods.
+
+    For each period, compute the multiplicative factor by which AIME is
+    scaled up when disregarding years with lowest earnings
+    (CRS Report R43370).
+    """
+    result = np.ones(n_periods)
+
+    for period in range(n_periods):
+        age = start_age + period
+        elapsed = min(age - 22, 35)
+
+        if elapsed <= 0:
+            continue
+
+        years_to_drop = int(min(elapsed // 5, 5))
+
+        if years_to_drop == 0:
+            continue
+
+        product = 1.0
+        for adjust_age in range(age - 1 - years_to_drop, age - 1):
+            product *= 1.0 - ratio_lowest_earnings[adjust_age] * aime_accrual_factor
+
+        result[period] = product * elapsed / (elapsed - years_to_drop)
+
+    return result
diff --git a/tests/test_social_security.py b/tests/test_social_security.py
@@ -5,11 +5,11 @@
 
 import jax.numpy as jnp
 import numpy as np
-from aca_data.social_security import compute_di_dropout_scale, compute_pia_table
 
 from aca_model.agent.labor_market import LaborSupply
 from aca_model.environment import social_security
 from aca_model.environment.social_security import ClaimedSS
+from tests.helpers.social_security import compute_di_dropout_scale, compute_pia_table
 
 ATOL = 0.01
 
diff --git a/tests/test_ss_benefit_integration.py b/tests/test_ss_benefit_integration.py
@@ -5,11 +5,11 @@
 """
 
 import jax.numpy as jnp
-from aca_data.social_security import compute_pia_table
 
 from aca_model.agent.labor_market import LaborSupply
 from aca_model.environment import social_security
 from aca_model.environment.social_security import ClaimedSS
+from tests.helpers.social_security import compute_pia_table
 
 ATOL = 0.01
 

Original file line number	Diff line number	Diff line change
`@@ -1,4 +1,4 @@`
`1`		`-Copyright (c) 2026 The aca-model Authors`
	`1`	`+Copyright (c) 2026 Hans-Martin von Gaudecker`
`2`	`2`
`3`	`3`	`Apache License`
`4`	`4`	`Version 2.0, January 2004`