Merge pull request #58 from jdebacker/cs_updates

Updates for dependency compatibility

.git-blame-ignore-revs

@@ -0,0 +1,3 @@
+# .git-blame-ignore-revs
+# ignore initial move to black formatting
+0c5478bfb211de34346e5b92d5a298e371b8b1bd

.github/workflows/build_and_test.yml

@@ -0,0 +1,44 @@
+name: Build Package and Test Source Code [Python 3.9, 3.10, 3.11]
+
+on: [push, pull_request]
+
+jobs:
+  build:
+    runs-on: ${{ matrix.os }}
+    strategy:
+      matrix:
+        os: [ubuntu-latest, macos-latest]
+        python-version: ["3.9", "3.10", "3.11"]
+
+    steps:
+      - name: Checkout
+        uses: actions/checkout@master
+        with:
+          persist-credentials: false
+      - name: Setup Miniconda using Python ${{ matrix.python-version }}
+        uses: conda-incubator/setup-miniconda@v2
+        with:
+          activate-environment: taxcrunch-env
+          environment-file: environment.yml
+          python-version: ${{ matrix.python-version }}
+          auto-activate-base: false
+      - name: Build
+        shell: bash -l {0}
+        run: |
+          pip install -e .
+          pip install pytest-cov
+          pip install pytest-pycodestyle
+      - name: Test
+        shell: bash -l {0}
+        working-directory: ./
+        run: |
+          pytest --cov=./ --cov-report=xml
+      - name: Upload coverage to Codecov
+        uses: codecov/codecov-action@v3
+        with:
+          token: ${{ secrets.CODECOV_TOKEN }} # not required for public repos
+          file: ./coverage.xml
+          flags: unittests
+          name: codecov-umbrella
+          fail_ci_if_error: true
+          verbose: true

cs-config/cs_config/__init__.py

@@ -1 +1 @@
-from .functions import *
+from .functions import *

cs-config/cs_config/constants.py

@@ -5,43 +5,60 @@
     "labels": {
         "year": {
             "type": "int",
+            "validators": {
+                "choice": {"choices": [yr for yr in range(2013, 2030 + 1)]}
+            },
+        },
+        "MARS": {
+            "type": "str",
             "validators": {
                 "choice": {
                     "choices": [
-                        yr for yr in range(2013, 2030 + 1)
+                        "single",
+                        "mjoint",
+                        "mseparate",
+                        "headhh",
+                        "widow",
                     ]
                 }
-            }
-        },
-        "MARS": {
-            "type": "str",
-            "validators": {"choice": {"choices": ["single", "mjoint",
-                                                  "mseparate", "headhh",
-                                                  "widow"]}}
+            },
         },
         "idedtype": {
             "type": "str",
-            "validators": {"choice": {"choices": ["med", "sltx", "retx", "cas",
-                                                  "misc", "int", "char"]}}
+            "validators": {
+                "choice": {
+                    "choices": [
+                        "med",
+                        "sltx",
+                        "retx",
+                        "cas",
+                        "misc",
+                        "int",
+                        "char",
+                    ]
+                }
+            },
         },
         "EIC": {
             "type": "str",
-            "validators": {"choice": {"choices": ["0kids", "1kid",
-                                                  "2kids", "3+kids"]}}
+            "validators": {
+                "choice": {"choices": ["0kids", "1kid", "2kids", "3+kids"]}
+            },
         },
         "data_source": {
             "type": "str",
-            "validators": {"choice": {"choices": ["PUF", "CPS", "other"]}}
-        }
+            "validators": {"choice": {"choices": ["PUF", "CPS", "other"]}},
+        },
     },
     "additional_members": {
         "section_1": {"type": "str"},
         "section_2": {"type": "str"},
         "start_year": {"type": "int"},
-        "checkbox": {"type": "bool"}
-    }
+        "checkbox": {"type": "bool"},
+    },
 }
 
+
 class MetaParameters(paramtools.Parameters):
     array_first = True
     defaults = {
@@ -51,11 +68,7 @@ class MetaParameters(paramtools.Parameters):
             "type": "int",
             "value": 2019,
             "validators": {
-                "choice": {
-                    "choices": [
-                        yr for yr in range(2013, 2030 + 1)
-                    ]
-                }
-            }
+                "choice": {"choices": [yr for yr in range(2013, 2030 + 1)]}
+            },
         }
     }

cs-config/cs_config/functions.py

@@ -36,6 +36,7 @@ def fix_checkbox(params):
 
     return pol_params
 
+
 def get_version():
     version = taxcrunch.__version__
     return f"Tax-Cruncher v{version}"
@@ -51,14 +52,15 @@ def get_inputs(meta_params_dict):
     params = CruncherParams()
     policy_params = Policy()
 
-    policy_params.set_state(
-        year=metaparams.year.tolist())
+    policy_params.set_state(year=metaparams.year.tolist())
 
     policy_params.array_first = False
     # Hack to work smoothly with convert_policy_defaults since
     # it expects a data_source attribute.
     metaparams.data_source = "CPS"
-    filtered_pol_params = inputs.convert_policy_defaults(metaparams, policy_params)
+    filtered_pol_params = inputs.convert_policy_defaults(
+        metaparams, policy_params
+    )
 
     keep = [
         "mstat",
@@ -88,13 +90,15 @@ def get_inputs(meta_params_dict):
         "w2paid",
         "qualprop",
         "mtr_options",
-        "schema"
+        "schema",
     ]
     cruncher_dict = params.dump()
 
     default_params = {
-        "Tax Information": {k: v for k, v in cruncher_dict.items() if k in keep},
-        "Policy": filtered_pol_params
+        "Tax Information": {
+            k: v for k, v in cruncher_dict.items() if k in keep
+        },
+        "Policy": filtered_pol_params,
     }
 
     meta = metaparams.dump()
@@ -136,52 +140,51 @@ def run_model(meta_params_dict, adjustment):
     increments = pd.DataFrame(list(range(0, 2000000, 200)))
 
     # use Calculation Option to determine what var to increment
-    if mtr_opt == 'Taxpayer Earnings':
-        span = int(ivar[9])
+    if mtr_opt == "Taxpayer Earnings":
+        span = int(ivar[9].values[0])
         df[9] = increments
-    elif mtr_opt == 'Spouse Earnings':
-        span = int(ivar[10])
+    elif mtr_opt == "Spouse Earnings":
+        span = int(ivar[10].values[0])
         df[10] = increments
-    elif mtr_opt == 'Qualified Dividends':
-        span = int(ivar[11])
+    elif mtr_opt == "Qualified Dividends":
+        span = int(ivar[11].values[0])
         df[11] = increments
-    elif mtr_opt == 'Interest Received':
-        span = int(ivar[12])
+    elif mtr_opt == "Interest Received":
+        span = int(ivar[12].values[0])
         df[12] = increments
-    elif mtr_opt == 'Short Term Gains':
-        span = int(ivar[13])
+    elif mtr_opt == "Short Term Gains":
+        span = int(ivar[13].values[0])
         df[13] = increments
-    elif mtr_opt == 'Long Term Gains':
-        span = int(ivar[14])
+    elif mtr_opt == "Long Term Gains":
+        span = int(ivar[14].values[0])
         df[14] = increments
-    elif mtr_opt == 'Business Income':
-        span = int(ivar[15])
+    elif mtr_opt == "Business Income":
+        span = int(ivar[15].values[0])
         df[15] = increments
-    elif mtr_opt == 'Pensions':
-        span = int(ivar[21])
+    elif mtr_opt == "Pensions":
+        span = int(ivar[21].values[0])
         df[21] = increments
-    elif mtr_opt == 'Gross Social Security Benefits':
-        span = int(ivar[22])
+    elif mtr_opt == "Gross Social Security Benefits":
+        span = int(ivar[22].values[0])
         df[22] = increments
-    elif mtr_opt == 'Real Estate Taxes Paid':
-        span = int(ivar[24])
+    elif mtr_opt == "Real Estate Taxes Paid":
+        span = int(ivar[24].values[0])
         df[24] = increments
-    elif mtr_opt == 'Mortgage':
-        span = int(ivar[27])
+    elif mtr_opt == "Mortgage":
+        span = int(ivar[27].values[0])
         df[27] = increments
 
-
     b = Batch(df)
     df_base = b.create_table()
     df_reform = b.create_table(policy_mods)
 
     # compute average tax rates
-    df_base['IATR'] = df_base['Individual Income Tax'] / df_base['AGI']
-    df_base['PATR'] = df_base['Payroll Tax'] / df_base['AGI']
-    df_reform['IATR'] = df_reform['Individual Income Tax'] / df_reform['AGI']
-    df_reform['PATR'] = df_reform['Payroll Tax'] / df_reform['AGI']
-    df_base['Axis'] = increments
-    df_reform['Axis'] = increments
+    df_base["IATR"] = df_base["Individual Income Tax"] / df_base["AGI"]
+    df_base["PATR"] = df_base["Payroll Tax"] / df_base["AGI"]
+    df_reform["IATR"] = df_reform["Individual Income Tax"] / df_reform["AGI"]
+    df_reform["PATR"] = df_reform["Payroll Tax"] / df_reform["AGI"]
+    df_base["Axis"] = increments
+    df_reform["Axis"] = increments
 
     return comp_output(crunch, df_base, df_reform, span, mtr_opt)
 
@@ -204,8 +207,14 @@ def comp_output(crunch, df_base, df_reform, span, mtr_opt):
 
     comp_dict = {
         "renderable": [
-            {"media_type": "table", "title": "Basic Liabilities", "data": table_basic},
-            liabilities, rates, credits,
+            {
+                "media_type": "table",
+                "title": "Basic Liabilities",
+                "data": table_basic,
+            },
+            liabilities,
+            rates,
+            credits,
             {
                 "media_type": "table",
                 "title": "Calculation of Liabilities",

cs-config/cs_config/inputs.py

@@ -3,7 +3,9 @@
 from paramtools import Parameters
 
 
-def convert_policy_defaults(meta_params: Parameters, policy_params: Parameters):
+def convert_policy_defaults(
+    meta_params: Parameters, policy_params: Parameters
+):
     """
     Convert defaults for taxcalc's Policy class to work with C/S.
     """
@@ -82,7 +84,7 @@ def convert_indexed_to_checkbox(defaults: dict):
             new_defaults["schema"] = data
 
         elif data["indexable"] and data.get("indexed", None) is True:
-            new_defaults[param] = dict(data, checkbox= True)
+            new_defaults[param] = dict(data, checkbox=True)
 
         elif data["indexable"] and not data.get("indexed", None) is False:
             new_defaults[param] = dict(data, checkbox=False)