import os import numpy as np import pytest import pandas.util._test_decorators as td import pandas as pd import pandas._testing as tm from pandas.io.sas.sasreader import read_sas # CSV versions of test xpt files were obtained using the R foreign library # Numbers in a SAS xport file are always float64, so need to convert # before making comparisons. def numeric_as_float(data): for v in data.columns: if data[v].dtype is np.dtype("int64"): data[v] = data[v].astype(np.float64) class TestXport: @pytest.fixture(autouse=True) def setup_method(self, datapath): self.dirpath = datapath("io", "sas", "data") self.file01 = os.path.join(self.dirpath, "DEMO_G.xpt") self.file02 = os.path.join(self.dirpath, "SSHSV1_A.xpt") self.file03 = os.path.join(self.dirpath, "DRXFCD_G.xpt") self.file04 = os.path.join(self.dirpath, "paxraw_d_short.xpt") with td.file_leak_context(): yield def test1_basic(self): # Tests with DEMO_G.xpt (all numeric file) # Compare to this data_csv = pd.read_csv(self.file01.replace(".xpt", ".csv")) numeric_as_float(data_csv) # Read full file data = read_sas(self.file01, format="xport") tm.assert_frame_equal(data, data_csv) num_rows = data.shape[0] # Test reading beyond end of file with read_sas(self.file01, format="xport", iterator=True) as reader: data = reader.read(num_rows + 100) assert data.shape[0] == num_rows # Test incremental read with `read` method. with read_sas(self.file01, format="xport", iterator=True) as reader: data = reader.read(10) tm.assert_frame_equal(data, data_csv.iloc[0:10, :]) # Test incremental read with `get_chunk` method. with read_sas(self.file01, format="xport", chunksize=10) as reader: data = reader.get_chunk() tm.assert_frame_equal(data, data_csv.iloc[0:10, :]) # Test read in loop m = 0 with read_sas(self.file01, format="xport", chunksize=100) as reader: for x in reader: m += x.shape[0] assert m == num_rows # Read full file with `read_sas` method data = read_sas(self.file01) tm.assert_frame_equal(data, data_csv) def test1_index(self): # Tests with DEMO_G.xpt using index (all numeric file) # Compare to this data_csv = pd.read_csv(self.file01.replace(".xpt", ".csv")) data_csv = data_csv.set_index("SEQN") numeric_as_float(data_csv) # Read full file data = read_sas(self.file01, index="SEQN", format="xport") tm.assert_frame_equal(data, data_csv, check_index_type=False) # Test incremental read with `read` method. with read_sas( self.file01, index="SEQN", format="xport", iterator=True ) as reader: data = reader.read(10) tm.assert_frame_equal(data, data_csv.iloc[0:10, :], check_index_type=False) # Test incremental read with `get_chunk` method. with read_sas( self.file01, index="SEQN", format="xport", chunksize=10 ) as reader: data = reader.get_chunk() tm.assert_frame_equal(data, data_csv.iloc[0:10, :], check_index_type=False) def test1_incremental(self): # Test with DEMO_G.xpt, reading full file incrementally data_csv = pd.read_csv(self.file01.replace(".xpt", ".csv")) data_csv = data_csv.set_index("SEQN") numeric_as_float(data_csv) with read_sas(self.file01, index="SEQN", chunksize=1000) as reader: all_data = list(reader) data = pd.concat(all_data, axis=0) tm.assert_frame_equal(data, data_csv, check_index_type=False) def test2(self): # Test with SSHSV1_A.xpt # Compare to this data_csv = pd.read_csv(self.file02.replace(".xpt", ".csv")) numeric_as_float(data_csv) data = read_sas(self.file02) tm.assert_frame_equal(data, data_csv) def test2_binary(self): # Test with SSHSV1_A.xpt, read as a binary file # Compare to this data_csv = pd.read_csv(self.file02.replace(".xpt", ".csv")) numeric_as_float(data_csv) with open(self.file02, "rb") as fd: with td.file_leak_context(): # GH#35693 ensure that if we pass an open file, we # dont incorrectly close it in read_sas data = read_sas(fd, format="xport") tm.assert_frame_equal(data, data_csv) def test_multiple_types(self): # Test with DRXFCD_G.xpt (contains text and numeric variables) # Compare to this data_csv = pd.read_csv(self.file03.replace(".xpt", ".csv")) data = read_sas(self.file03, encoding="utf-8") tm.assert_frame_equal(data, data_csv) def test_truncated_float_support(self): # Test with paxraw_d_short.xpt, a shortened version of: # http://wwwn.cdc.gov/Nchs/Nhanes/2005-2006/PAXRAW_D.ZIP # This file has truncated floats (5 bytes in this case). # GH 11713 data_csv = pd.read_csv(self.file04.replace(".xpt", ".csv")) data = read_sas(self.file04, format="xport") tm.assert_frame_equal(data.astype("int64"), data_csv)