def do_work(personal_exemp, exemp_start, phase_out):
global tax_dta
myvars = {}
myvars['_rt4'] = [0.39]
user_mods = json.dumps(myvars)
print "begin work"
cur_path = os.path.abspath(os.path.dirname(__file__))
tax_dta = pd.read_csv(os.path.join(cur_path, "./puf2.csv"))
mY_dec, df_dec, mY_bin, df_bin = dropq.run_models(tax_dta, user_mods=user_mods)
print "end work"
results = (personal_exemp - exemp_start) * phase_out
return results
def get_tax_results_async(mods, inputs_pk):
print "mods is ", mods
user_mods = package_up_vars(mods)
print "user_mods is ", user_mods
print "begin work"
cur_path = os.path.abspath(os.path.dirname(__file__))
tax_dta = pd.read_csv("puf.csv.gz", compression='gzip')
mY_dec, mX_dec, df_dec, mY_bin, mX_bin, df_bin, fiscal_tots = dropq.run_models(tax_dta,
num_years=NUM_BUDGET_YEARS, user_mods={START_YEAR:user_mods})
if DUMP_DEBUG:
with open("mY_dec.txt", "w") as f1:
f1.write(json.dumps(mY_dec, sort_keys=True, indent=4, separators=(',', ': ')) + '\n')
with open("mX_dec.txt", "w") as f1:
f1.write(json.dumps(mX_dec, sort_keys=True, indent=4, separators=(',', ': ')) + '\n')
with open("df_dec.txt", "w") as f1:
f1.write(json.dumps(df_dec, sort_keys=True, indent=4, separators=(',', ': ')) + '\n')
with open("mY_bin.txt", "w") as f1:
f1.write(json.dumps(mY_bin, sort_keys=True, indent=4, separators=(',', ': ')) + '\n')
with open("mX_bin.txt", "w") as f1:
f1.write(json.dumps(mX_bin, sort_keys=True, indent=4, separators=(',', ': ')) + '\n')
with open("df_bin.txt", "w") as f1:
f1.write(json.dumps(df_bin, sort_keys=True, indent=4, separators=(',', ': ')) + '\n')
with open("fiscal_tots.txt", "w") as f1:
f1.write(json.dumps(fiscal_tots, sort_keys=True, indent=4, separators=(',', ': ')) + '\n')
results = {'mY_dec': mY_dec, 'mX_dec': mX_dec, 'df_dec': df_dec,
'mY_bin': mY_bin, 'mX_bin': mX_bin, 'df_bin': df_bin,
'fiscal_tots': fiscal_tots, 'inputs_pk': inputs_pk}
print "end work"
return results
def get_tax_results_async(mods, inputs_pk):
print("mods is ", mods)
user_mods = package_up_vars(mods)
print("user_mods is ", user_mods)
print("begin work")
tax_dta = pd.read_csv("puf.csv.gz", compression='gzip')
(mY_dec, mX_dec, df_dec, mY_bin, mX_bin, df_bin,
fiscal_tots) = dropq.run_models(tax_dta,
num_years=NUM_BUDGET_YEARS,
user_mods={START_YEAR: user_mods})
if DUMP_DEBUG:
with open("mY_dec.txt", "w") as f1:
f1.write(
json.dumps(
mY_dec, sort_keys=True, indent=4, separators=(',', ': ')) +
'\n')
with open("mX_dec.txt", "w") as f1:
f1.write(
json.dumps(
mX_dec, sort_keys=True, indent=4, separators=(',', ': ')) +
'\n')
with open("df_dec.txt", "w") as f1:
f1.write(
json.dumps(
df_dec, sort_keys=True, indent=4, separators=(',', ': ')) +
'\n')
with open("mY_bin.txt", "w") as f1:
f1.write(
json.dumps(
mY_bin, sort_keys=True, indent=4, separators=(',', ': ')) +
'\n')
with open("mX_bin.txt", "w") as f1:
f1.write(
json.dumps(
mX_bin, sort_keys=True, indent=4, separators=(',', ': ')) +
'\n')
with open("df_bin.txt", "w") as f1:
f1.write(
json.dumps(
df_bin, sort_keys=True, indent=4, separators=(',', ': ')) +
'\n')
with open("fiscal_tots.txt", "w") as f1:
f1.write(
json.dumps(fiscal_tots,
sort_keys=True,
indent=4,
separators=(',', ': ')) + '\n')
results = {
'mY_dec': mY_dec,
'mX_dec': mX_dec,
'df_dec': df_dec,
'mY_bin': mY_bin,
'mX_bin': mX_bin,
'df_bin': df_bin,
'fiscal_tots': fiscal_tots,
'inputs_pk': inputs_pk
}
print("end work")
return results
