def test_01_create_file(self):
fle2 = cl.DataTable(fname2, 'file')
# test edge case first
fle2.save(fname2, 9)
fle2.save(fname2, ['test data', 'another line', 'final line'])
fle3 = cl.DataTable(fname3, 'file')
file_contents = fle2.load(fname)
self.assertEqual(len(file_contents), 157)
fle3.drop(fname)
# try to drop non existant file
fle3.drop('no such file.bla')
def test_06_create_blank_data_structure(self):
dat = cl.DataTable('sales.csv',
',',
col_names=['date', 'amount', 'details'])
self.assertEqual(dat.col_names[0], 'date')
self.assertEqual(dat.col_names[1], 'amount')
self.assertEqual(dat.col_names[2], 'details')
def TEST():
root_folder = os.path.abspath(
os.path.dirname(os.path.abspath(__file__)) + os.sep + '..' + os.sep +
'..' + os.sep + 'data')
fname = root_folder + os.sep + 'core' + os.sep + 'OBJECT_INFO-COURSE.csv'
print('wrapper for redis databases')
host = '127.0.0.1'
port = 6379
db = 0
d = redis_server(host, port, db)
d.connect()
print(d.server)
d.set('test123', 'this is a test')
print(d.get('test123'))
dt = cls_datatable.DataTable(fname, ',')
dt.load_to_array()
d.import_datatable(dt, 'aikif', 1)
print(
d.get(
"aikif:OBJECT_INFO-COURSE.csv:categories:Artificial Intelligence Planning"
))
def main():
"""
test for rawdata module to create test files
"""
print('Initialising rawdata for AIKIF...')
# setup project for logging
name = 'rawdata_gen'
type = 'Data'
desc = 'Creates raw data tables for aikif'
desc += '\n Last updated ' + mod_dt.TodayAsString()
fldr = os.getcwd()
p = mod_prj.Project(name, type, desc, fldr)
p.add_detail('source', 'pip install rawdata')
# create the rawdata
col_names = ['Year', 'name', 'Purchase', 'Location']
col_types = ['DATE', 'PEOPLE', 'CURRENCY', 'PLACE']
t = generate.TableGenerator(10, col_types, col_names)
# save the table (you can save it via rawdata class, but demonstrates other use
test_data = mod_dt.DataTable('random.csv', ',', col_names=col_names)
p.log_table(test_data)
for row in t.tbl:
#print(row)
p.record(test_data, '', row)
p.build_report('test_raw_data.html', 'html')
p.build_report('test_raw_data.rst', 'rst')
p.build_report('test_raw_data.md', 'md')
print(test_data)
def test_04_add_cols(self):
fle = cl.DataTable(fname, ',')
fle.load_to_array()
fle.add_cols(['NEW1', 'NEW2'])
#fle.describe_contents()
self.assertEqual(
fle.get_header(),
['TERM', 'GENDER', 'ID', 'tot1', 'tot2', 'NEW1', 'NEW2'])
def test_02_percentile(self):
fl3 = cl.DataTable('', '"')
self.assertEqual(fl3.percentile([1, 2, 3, 4, 5, 6], .25), 2.25)
self.assertEqual(fl3.percentile([1, 2, 3, 4, 5, 6], .5), 3.5)
self.assertEqual(fl3.percentile([1, 2, 3, 4, 5, 6], .75), 4.75)
self.assertEqual(fl3.percentile([1, 2, 3, 4, 5, 6, 7, 8, 9, 10], .25),
3.25)
self.assertEqual(fl3.percentile([1, 1, 2], .5), 1)
self.assertEqual(fl3.percentile([1, 1, 2], .25), 1)
self.assertEqual(fl3.percentile([1, 1, 2], .75), 1.5)
def test_09_force_to_string(self):
dat = cl.DataTable('dud.csv', ',', col_names=['date'])
self.assertEqual(dat.force_to_string("hi"), 'hi')
self.assertEqual(dat.force_to_string(123), '123')
self.assertEqual(dat.force_to_string(0.554554523), '0.554554523')
self.assertEqual(dat.force_to_string({"a": 5}), '{a=5,}')
self.assertEqual(dat.force_to_string(['asda', 'ddd']), '[asda,ddd]')
self.assertEqual(dat.force_to_string(['asda', 213123, 0.55, 'HI']),
'[asda,213123,0.55,HI]')
self.assertEqual(dat.force_to_string(['a', ['b', 'c'], 'd']),
'[a,[b,c],d]')
def test_02_record(self):
proj2 = project.Project(name='Sales Log', type='business', desc='Record list of sales', fldr='')
proj2.add_detail('Note', 'List of sales taken from manual entries in test program')
self.assertEqual(proj2.details[0][0],'Note')
self.assertEqual(proj2.details[0][1],'List of sales taken from manual entries in test program')
tbl_exp = cls_datatable.DataTable('expenses.csv', ',', col_names=['date', 'amount', 'details'])
proj2.record(tbl_exp, 'Expense', ['2015-02-13', 49.94, 'restaurant'])
proj2.record(tbl_exp, 'Expense', ['2015-02-15', 29.00, 'petrol'])
proj2.record(tbl_exp, 'Expense', ['2015-02-17', 89.95, 'fringe tickets'])
self.assertEqual(len(tbl_exp.arr), 3)
self.assertEqual(tbl_exp.arr[1][2], 'petrol')
def main():
analysis = cl.DataTable('Results', ',', col_names=['results'])
if len(sys.argv) != 3:
print('usage:')
print('table_compare.py "TABLE1.CSV" "TABLE2.CSV":')
old_table = 'dummy_table1.csv'
new_table = 'dummy_table2.csv'
else:
old_table = sys.argv[1]
new_table = sys.argv[2]
t_old = cl.DataTable(old_table, ',')
t_old.load_to_array()
t_old.describe_contents()
t_new = cl.DataTable(new_table, ',')
t_new.load_to_array()
t_new.describe_contents()
res, pass_fail = check_col_names(t_old, t_new)
analysis.add([res])
if pass_fail != 'OK':
print('Bypassing exact row test, as columns are different')
else:
print(check_rows(t_old, t_new))
res, pass_fail = compare_values(t_old, t_new)
analysis.add([res])
res = distinct_values(t_old, t_new)
for r in res:
analysis.add(r)
analysis.save_csv('results.csv', write_header_separately=True)
#print(analysis)
print('results of analysis saved to "results.csv"')
def test_07_add_data(self):
dat = cl.DataTable('sales.csv',
',',
col_names=['date', 'amount', 'details'])
dat.add(['2015-01-09', 24.95, 'Timer'])
dat.add(['2015-02-17', 45.00, 'Diary'])
dat.add(['2015-02-19', 24.95, 'Timer'])
self.assertEqual(len(dat.arr), 3)
self.assertEqual(len(dat.count_unique_values(0, 'date')), 3)
self.assertEqual(len(dat.count_unique_values(2, 'details')), 2)
self.assertEqual(str(dat)[0:23], 'date amount details')
op_rst = dat.format_rst()
#print(op_rst)
self.assertEqual(len(op_rst) > 55, True)
self.assertEqual(dat.get_col_width('date'), 10)
def test_03_get_distinct_values_from_cols3(self):
fle = cl.DataTable(fname, ',')
fle.load_to_array()
dist_cols = fle.get_distinct_values_from_cols(['TERM', 'ID'])
self.assertEqual(
sorted(dist_cols),
sorted([('5300', '00016'), ('5300', '00078'), ('7310', '00016'),
('7310', '00078')]))
# test edge cases
empty_cols = fle.get_distinct_values_from_cols([])
self.assertEqual(empty_cols, [])
unimplemented_function = fle.get_distinct_values_from_cols(
['a', 'b', 'c', 'd'])
self.assertEqual(unimplemented_function, -44)
def test_05_update_where1(self):
fle = cl.DataTable(fname, ',')
fle.load_to_array()
dist_cols = fle.get_distinct_values_from_cols(['TERM', 'ID'])
fle.add_cols(['RNK_tot1', 'RNK_tot2'])
for new_col in ['tot1', 'tot2']:
for i in dist_cols:
first, third, median = fle.calc_percentiles(
new_col, ['TERM', 'ID'], [str(i[0]), str(i[1])])
fle.update_where('RNK_' + new_col, first, ['TERM', 'ID'],
[str(i[0]), str(i[1])])
fle.save_csv(fname3)
"""
===========================================================
TERM GENDER ID tot1 tot2 RNK_tot1RNK_tot2
5300 F 00078 18 66 18 66
7310 M 00078 10 12 14.0 7.0
7310 M 00078 18 465 14.0 7.0
7310 F 00078 30 2 14.0 7.0
7310 F 00016 25 12 35.5 227.25
5300 M 00016 31 0 31 0
7310 F 00016 67 873 35.5 227.25
"""
self.assertEqual(
fle.get_header(),
['TERM', 'GENDER', 'ID', 'tot1', 'tot2', 'RNK_tot1', 'RNK_tot2'])
self.assertEqual(fle.arr[0][3], '18')
self.assertEqual(fle.arr[0][4], '66')
self.assertEqual(fle.arr[1][5], 14.0)
self.assertEqual(fle.arr[1][6], 7.0)
self.assertEqual(fle.arr[6][6], 227.25)
# update where using col index (updates same column)
fle.update_where(5, first, ['TERM', 'ID'], [str(i[0]), str(i[1])])
# check edge case for calc_percentiles
first, third, median = fle.calc_percentiles(new_col, ['TERM', 'ID'],
['dummy', 'no_data'])
print(first, third, median)
self.assertEqual(first, 0)
self.assertEqual(third, 0)
self.assertEqual(median, 0)
def test_12_get_arr(self):
fle = cl.DataTable(fname, ',')
fle.load_to_array()
self.assertEqual(fle.arr, fle.get_arr())
def test_03_get_distinct_values_from_cols2(self):
fle = cl.DataTable(fname, ',')
fle.load_to_array()
dist_cols = fle.get_distinct_values_from_cols(['TERM'])
self.assertEqual(sorted(dist_cols), [{'5300', '7310'}])
def test_03_get_distinct_values_from_cols1(self):
fle = cl.DataTable(fname, ',')
fle.load_to_array()
dist_cols = fle.get_distinct_values_from_cols(['GENDER'])
self.assertEqual(sorted(dist_cols), [{'F', 'M'}])
def test_10_dict_2_string(self):
dat = cl.DataTable('dud.csv', ',', col_names=['date'])
self.assertEqual(dat.Dict2String({"a": 5}), 'a=5,')
def test_08_describe_contents(self):
dat = cl.DataTable('sales.csv',
',',
col_names=['date', 'amount', 'details'])
dat.describe_contents()
