A few minor changes to make input data testing easier

Makefile

@@ -32,7 +32,7 @@ help:
 clean:
 	@find . -name *pyc -exec rm {} \;
 	@find . -name *cache -maxdepth 1 -exec rm -r {} \;
-	@conda uninstall taxcalc --yes --quiet 2>&1 > /dev/null
+	@pip uninstall taxcalc --yes --quiet 2>&1 > /dev/null
 
 .PHONY=package
 package:
@@ -51,7 +51,7 @@ endef
 .PHONY=pytest-cps
 pytest-cps:
 	@$(pytest-setup)
-	@cd taxcalc ; pytest -n4 -m "not requires_pufcsv and not pre_release"
+	@cd taxcalc ; pytest -n4 --disable-warnings -m "not requires_pufcsv and not pre_release"
 	@$(pytest-cleanup)
 
 .PHONY=pytest

taxcalc.egg-info/PKG-INFO

@@ -16,6 +16,12 @@ Classifier: Programming Language :: Python :: 3.7
 Classifier: Programming Language :: Python :: 3.8
 Classifier: Programming Language :: Python :: 3.9
 Classifier: Topic :: Software Development :: Libraries :: Python Modules
+License-File: LICENSE.md
+Requires-Dist: setuptools
+Requires-Dist: numpy
+Requires-Dist: pandas
+Requires-Dist: bokeh
+Requires-Dist: numba
 
 [![PSL cataloged](https://img.shields.io/badge/PSL-cataloged-a0a0a0.svg)](https://www.PSLmodels.org)
 [![Python 3.6+](https://img.shields.io/badge/python-3.6%2B-blue.svg)](https://www.python.org/downloads/release/python-360/)

taxcalc.egg-info/SOURCES.txt

@@ -1,3 +1,4 @@
+LICENSE.md
 MANIFEST.in
 README.md
 setup.py

taxcalc/calcfunctions.py

@@ -577,7 +577,7 @@ def CapGains(p23250, p22250, sep, ALD_StudentLoan_hc,
 
 
 @iterate_jit(nopython=True)
-def SSBenefits(MARS, ymod, e02400, SS_thd50, SS_thd85,
+def SSBenefits(MARS, ymod, e02400, SS_all_in_agi, SS_thd50, SS_thd85,
                SS_percentage1, SS_percentage2, c02500):
     """
     Calculates OASDI benefits included in AGI, c02500.
@@ -590,6 +590,8 @@ def SSBenefits(MARS, ymod, e02400, SS_thd50, SS_thd85,
         Variable that is used in OASDI benefit taxation logic
     e02400: float
         Total social security (OASDI) benefits
+    SS_all_in_agi: bool
+        Whether all social security benefits are included in AGI
     SS_thd50: list
         Threshold for social security benefit taxability (1)
     SS_thd85: list
@@ -615,6 +617,8 @@ def SSBenefits(MARS, ymod, e02400, SS_thd50, SS_thd85,
                      SS_percentage1 *
                      min(e02400, SS_thd85[MARS - 1] -
                          SS_thd50[MARS - 1]), SS_percentage2 * e02400)
+    if SS_all_in_agi:
+        c02500 = e02400
     return c02500
 
 
@@ -1595,7 +1599,7 @@ def GainsTax(e00650, c01000, c23650, p23250, e01100, e58990, e00200,
              CG_nodiff, PT_EligibleRate_active, PT_EligibleRate_passive,
              PT_wages_active_income, PT_top_stacking,
              CG_rt1, CG_rt2, CG_rt3, CG_rt4, CG_brk1, CG_brk2, CG_brk3,
-             dwks10, dwks13, dwks14, dwks19, c05700, taxbc):
+             dwks10, dwks13, dwks14, dwks19, dwks43, c05700, taxbc):
     """
     GainsTax function implements (2015) Schedule D Tax Worksheet logic for
     the special taxation of long-term capital gains and qualified dividends
@@ -1725,6 +1729,8 @@ def GainsTax(e00650, c01000, c23650, p23250, e01100, e58990, e00200,
         Maximum of 0 and dwks1 - dwks13
     dwks19: float
         Maximum of dwks17 and dwks16
+    dwks43: float
+        separate tax on long-term capital gains and qualified dividends
     c05700: float
         Lump sum distributions
     taxbc: float
@@ -1740,6 +1746,8 @@ def GainsTax(e00650, c01000, c23650, p23250, e01100, e58990, e00200,
         Maximum of 0 and dwks1 - dwks13
     dwks19: float
         Maximum of dwks17 and dwks16
+    dwks43: float
+        separate tax on long-term capital gains and qualified dividends
     c05700: float
         Lump sum distributions
     taxbc: float
@@ -1834,12 +1842,13 @@ def GainsTax(e00650, c01000, c23650, p23250, e01100, e58990, e00200,
         dwks13 = 0.
         dwks14 = 0.
         dwks19 = 0.
+        dwks43 = 0.
 
     # final calculations done no matter what the value of hasqdivltcg
     c05100 = c24580  # because foreign earned income exclusion is assumed zero
     c05700 = 0.  # no Form 4972, Lump Sum Distributions
     taxbc = c05700 + c05100
-    return (dwks10, dwks13, dwks14, dwks19, c05700, taxbc)
+    return (dwks10, dwks13, dwks14, dwks19, dwks43, c05700, taxbc)
 
 
 @iterate_jit(nopython=True)

taxcalc/policy_current_law.json

@@ -356,6 +356,32 @@
             "cps": true
         }
     },
+    "SS_all_in_agi": {
+        "title": "Include all social security benefits in AGI",
+        "description": "All social security benefits will be included in AGI.",
+        "notes": "",
+        "section_1": "Social Security Taxability",
+        "section_2": "Social Security Benefit Taxability",
+        "indexable": false,
+        "indexed": false,
+        "type": "bool",
+        "value": [
+            {
+                "year": 2013,
+                "value": false
+            }
+        ],
+        "validators": {
+            "range": {
+                "min": false,
+                "max": true
+            }
+        },
+        "compatible_data": {
+            "puf": true,
+            "cps": true
+        }
+    },
     "SS_thd50": {
         "title": "Threshold for Social Security benefit taxability 1",
         "description": "The first threshold for Social Security benefit taxability: if taxpayers have provisional income greater than this threshold, up to rate 1 of their Social Security benefit will be subject to tax under current law.",
@@ -20666,4 +20692,4 @@
             "cps": true
         }
     }
-}
+}

taxcalc/records_variables.json

@@ -1081,6 +1081,11 @@
       "desc": "search taxcalc/calcfunctions.py for how calculated and used",
       "form": {"2013-20??": "calculated variable"}
     },
+    "dwks43": {
+      "type": "float",
+      "desc": "separate tax on long-term capital gains and qualified dividends",
+      "form": {"2013-20??": "calculated variable"}
+    },
     "fstax": {
       "type": "float",
       "desc": "search taxcalc/calcfunctions.py for how calculated and used",

taxcalc/taxcalcio.py

@@ -565,7 +565,7 @@ def write_decile_table(dfx, tfile, tkind='Totals'):
                                               decile_details=False,
                                               pop_quantiles=False,
                                               weight_by_income_measure=False)
-        gdfx = dfx.groupby('table_row', as_index=False)
+        gdfx = dfx.groupby('table_row', as_index=False, observed=True)
         rtns_series = gdfx.apply(unweighted_sum, 's006').values[:, 1]
         xinc_series = gdfx.apply(weighted_sum, 'expanded_income').values[:, 1]
         itax_series = gdfx.apply(weighted_sum, 'iitax').values[:, 1]

taxcalc/tests/conftest.py

@@ -4,7 +4,6 @@
 import numpy
 import pandas
 import pytest
-
 from pytest_harvest import get_session_results_df
 
 
@@ -143,27 +142,33 @@ def pytest_sessionfinish(session):
     new_stats_df = get_session_results_df(session)
     # move test_id from index into unique column
     new_stats_df.reset_index(inplace=True)
-    old_stats_df = pandas.read_csv(os.path.join(tests_path, 'test_stats_benchmark.csv'))
+    old_stats_df = pandas.read_csv(os.path.join(
+        tests_path, 'test_stats_benchmark.csv')
+    )
 
     merge_df = new_stats_df.merge(old_stats_df, on=['test_id'], how='left')
     # time diff for new tests is set to 0
-    merge_df['time_diff'] = merge_df['duration_ms_x'] - merge_df['duration_ms_y']
+    merge_df['time_diff'] = (
+        merge_df['duration_ms_x'] - merge_df['duration_ms_y']
+    )
     merge_df['time_diff'] = merge_df['time_diff'].fillna(0)
 
     tol = 1.0 # choose tolerance in seconds
     tol *= 1000
 
+    print('\n')
     for ind, row in merge_df.iterrows():
         if row['time_diff'] > tol:
             diff = round(abs(row['time_diff']), 3)
-            print(f"{row['test_id']} is slower than the current benchmark by {diff} ms")
+            print((f"{row['test_id']} is slower than the "
+                   f"current benchmark by {diff} ms"))
 
     print('\n')
-
     for ind, row in merge_df.iterrows():
         if row['time_diff'] < (-1 * tol):
             diff = round(abs(row['time_diff']), 3)
-            print(f"{row['test_id']} is faster than the current benchmark by {diff} ms")
+            print((f"{row['test_id']} is faster than the "
+                   f"current benchmark by {diff} ms"))
 
     # Save new test stats to disk including time diff
     new_stats_df['time_diff'] = merge_df['time_diff'].values