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