def __init__(self, pathin=None, list_map=default_map, delim='\t',num_cols=None): from delimited_file_utils import open_delimited_with_sniffer_and_check txt_file_with_list.__init__(self, pathin, list_map=list_map) self.delim = delim self.break_list()#<-- eventually, this could probably be eliminated #self.array = array(self.nested_list) self.array = open_delimited_with_sniffer_and_check(pathin,num_cols=num_cols)#<-- new stuff
def csv_to_xlsx(pathin, pathout=None, **kwargs): if pathout is None: fno, ext = os.path.splitext(pathin) pathout = fno + '.xlsx' array = delimited_file_utils.open_delimited_with_sniffer_and_check(pathin) array_to_xlsx(array, pathout, **kwargs)
def __init__(self, pathin=None, list_map=default_map, delim='\t'): from delimited_file_utils import open_delimited_with_sniffer_and_check txt_file_with_list.__init__(self, pathin, list_map=list_map) self.delim = delim self.break_list()#<-- eventually, this could probably be eliminated #self.array = array(self.nested_list) self.array = open_delimited_with_sniffer_and_check(pathin)#<-- new stuff
def _open_txt_file(pathin, delim='\t'): #import pdb #pdb.set_trace() #myfile = txt_mixin.delimited_txt_file(pathin, delim=delim) #alldata = loadtxt(pathin,dtype=str,delimiter=delim) #alldata = myfile.array alldata = delimited_file_utils.open_delimited_with_sniffer_and_check(pathin) labels = alldata[0,:] data = alldata[1:] return data, labels
def __init__(self, pathin=None, lastnamecol=0, firstnamecol=1, \ delim='\t', **kwargs): txt_mixin.delimited_txt_file.__init__(self, pathin, delim=delim, \ **kwargs) myarray = open_delimited_with_sniffer_and_check(pathin) self.array = myarray self.lastnamecol = lastnamecol self.firstnamecol = firstnamecol self._get_labels_and_data() self._get_student_names() self.clean_firstnames() self.make_keys_and_dict()
def __init__(self, pathin=None, lastnamecol=0, firstnamecol=1, \ delim='\t', **kwargs): txt_mixin.delimited_txt_file.__init__(self, pathin, delim=delim, \ **kwargs) myarray = open_delimited_with_sniffer_and_check(pathin) self.array = myarray ## self.lastnamecol = lastnamecol ## self.firstnamecol = firstnamecol self._get_labels_and_data() self._set_name_cols() self._get_student_names() self.clean_firstnames() self.make_keys_and_dict() #from txt_database.__init__ self.N_cols = len(self.labels) inds = range(self.N_cols) self.col_inds = dict(zip(self.labels, inds)) self._col_labels_to_attr_names() self.map_cols_to_attr()
import glob from numpy import array files = glob.glob('email_update_grades_test*.csv') good_labels = array([ 'Group Name', 'Content/Progress', 'Clarity', 'Writing', 'Apparent Effort', 'Overall Grade', 'Notes' ]) passes = [] failures = [] for curfile in files: curarray = delimited_file_utils.open_delimited_with_sniffer_and_check( curfile) labels = curarray[0, :] data = curarray[1:, :] bool_vect = labels == good_labels test1 = bool_vect.all() test2 = data.shape == (9, 7) if test1 and test2: passes.append(curfile) else: failures.append(curfile) if len(failures) == 0: print('all tests pass') else: print('passes:') for curfile in passes:
import delimited_file_utils import glob from numpy import array files = glob.glob("email_update_grades_test*.csv") good_labels = array( ["Group Name", "Content/Progress", "Clarity", "Writing", "Apparent Effort", "Overall Grade", "Notes"] ) passes = [] failures = [] for curfile in files: curarray = delimited_file_utils.open_delimited_with_sniffer_and_check(curfile) labels = curarray[0, :] data = curarray[1:, :] bool_vect = labels == good_labels test1 = bool_vect.all() test2 = data.shape == (9, 7) if test1 and test2: passes.append(curfile) else: failures.append(curfile) if len(failures) == 0: print("all tests pass") else: print("passes:") for curfile in passes: