def test_integer_col_na_values(self):
"""Test if the loader can load columns with integers and NAs.
This is necessary because NaNs cannot be represented by integers."""
x = map(str, range(20))
x[13] = ""
df = pd.DataFrame.from_dict(dict(a=x, b=x))
tempdir = tempfile.mkdtemp()
outfile = op.join(tempdir, "testdata.csv")
df.to_csv(outfile, index=False)
specfile = op.join(tempdir, "dict.yaml")
specs = dict(delimiter=',', dtypes={'a': int, 'b': int}, path=outfile)
with open(specfile, "w") as fileobj:
yaml.dump({'testdata': specs},
fileobj,
Dumper=yaml.CDumper,
default_flow_style=False)
pr.add_project("wrong_dtype", specfile)
try:
_pr = pr.Project("wrong_dtype")
df = _pr.load_dataset("testdata")
self.assertEqual(df['a'].dtype, float)
self.assertEqual(df['b'].dtype, float)
finally:
pr.remove_project("wrong_dtype")
shutil.rmtree(tempdir)
def test_load_dataset_wrong_dtypes_in_spec(self):
"""Test if the Loader can safely load columns that have a wrongly
specified data type in the schema.
"""
# Make a file with two columns, both specified as integers in the
# dtypes, but one has random string types.
x = np.random.randint(0, 10, size=(100, 2))
dframe = pd.DataFrame(x, columns=['a', 'b'])
tempdir = tempfile.mkdtemp()
outfile = op.join(tempdir, "testdata.csv")
_ix = np.random.randint(0, 100, size=(5,))
dframe['b'][_ix] = "aa"
dframe.to_csv(outfile, index=False)
specs = dict(delimiter=',', dtypes={'a': int, 'b': int}, path=outfile)
specfile = op.join(tempdir, "dict.yaml")
with open(specfile, "w") as fileobj:
yaml.dump({'testdata': specs}, fileobj, Dumper=Dumper,
default_flow_style=False)
pr.add_project("wrong_dtype", specfile)
try:
_pr = pr.Project("wrong_dtype")
with warnings.catch_warnings(record=True) as catcher:
dframe = _pr.load_dataset("testdata")
assert len(catcher) == 1
assert issubclass(catcher[-1].category, UserWarning)
finally:
pr.remove_project("wrong_dtype")
shutil.rmtree(tempdir)
def test_load_dataset_wrong_dtypes_in_spec(self):
"""Test if the loader can safely load columns that have a wrongly
specified data type in the schema.
"""
# Make a file with two columns, both specified as integers in the
# dtypes, but one has random string types.
x = np.random.randint(0, 10, size=(100, 2))
dframe = pd.DataFrame(x, columns=['a', 'b'])
tempdir = tempfile.mkdtemp()
outfile = op.join(tempdir, "testdata.csv")
_ix = np.random.randint(0, 100, size=(5, ))
dframe['b'][_ix] = "aa"
dframe.to_csv(outfile, index=False)
specs = dict(delimiter=',', dtypes={'a': int, 'b': int}, path=outfile)
specfile = op.join(tempdir, "dict.yaml")
with open(specfile, "w") as fileobj:
yaml.dump({'testdata': specs},
fileobj,
Dumper=yaml.CDumper,
default_flow_style=False)
pr.add_project("wrong_dtype", specfile)
try:
_pr = pr.Project("wrong_dtype")
with warnings.catch_warnings(record=True) as catcher:
dframe = _pr.load_dataset("testdata")
assert len(catcher) == 1
assert issubclass(catcher[-1].category, UserWarning)
finally:
pr.remove_project("wrong_dtype")
shutil.rmtree(tempdir)
def test_add(self):
"""Test if the `add` subcommand can add projects to the config file."""
try:
cmd = ['semantic', 'add', 'dummy_added_project', '/tmp/dummy.yaml']
subprocess.check_call(cmd, env=self.testenv)
projects = pr.get_projects()
self.assertIn(("dummy_added_project", "/tmp/dummy.yaml"), projects)
finally:
pr.remove_project("dummy_added_project")
def test_add(self):
"""Test if the `add` subcommand can add projects to the config file."""
try:
cmd = ['semantic', 'add', 'dummy_added_project', '/tmp/dummy.yaml']
subprocess.check_call(cmd, env=self.testenv)
projects = pr.get_projects()
self.assertIn(("dummy_added_project", "/tmp/dummy.yaml"), projects)
finally:
pr.remove_project("dummy_added_project")
def test_remove(self):
"""Test if the remove subcommand can remove projects."""
pr.add_project("dummy_project_2", "/foo/baz.yaml")
try:
cmd = ['semantic', 'remove', 'dummy_project_2']
subprocess.check_call(cmd, env=self.testenv)
projects = pr.get_projects()
proj_names = [p[0] for p in projects]
self.assertNotIn("dummy_project_2", proj_names)
finally:
pr.remove_project("dummy_project_2")
def test_remove(self):
"""Test if the remove subcommand can remove projects."""
pr.add_project("dummy_project_2", "/foo/baz.yaml")
try:
cmd = ['semantic', 'remove', 'dummy_project_2']
subprocess.check_call(cmd, env=self.testenv)
projects = pr.get_projects()
proj_names = [p[0] for p in projects]
self.assertNotIn("dummy_project_2", proj_names)
finally:
pr.remove_project("dummy_project_2")
def test_relative_path(self):
"""Check if the set-schema and add subcommands convert relative paths
from the cmdline to absolute paths in the config file.
"""
try:
cmd = ['semantic', 'set-schema', 'dummy_project', './foo.yaml']
subprocess.check_call(cmd, env=self.testenv)
self.assertTrue(op.isabs(pr.get_default_specfile('dummy_project')))
pr.remove_project("dummy_project")
cmd = ['semantic', 'add', 'dummy_project', './foo.yaml']
subprocess.check_call(cmd, env=self.testenv)
self.assertTrue(op.isabs(pr.get_default_specfile('dummy_project')))
finally:
pr.remove_project("dummy_project_1")
def _remove_project(project_name, project_files=None):
pr.remove_project(project_name)
if project_files is not None:
if hasattr(project_files, "__iter__"):
for path in project_files:
if op.isfile(path):
os.unlink(path)
elif op.isdir(path):
shutil.rmtree(path)
else:
if op.isfile(project_files):
os.unlink(project_files)
elif op.isdir(project_files):
shutil.rmtree(project_files)
def test_relative_path(self):
"""Check if the set-schema and add subcommands convert relative paths
from the cmdline to absolute paths in the config file.
"""
try:
cmd = ['semantic', 'set-schema', 'dummy_project', './foo.yaml']
subprocess.check_call(cmd, env=self.testenv)
self.assertTrue(op.isabs(pr.get_default_specfile(
'dummy_project')))
pr.remove_project("dummy_project")
cmd = ['semantic', 'add', 'dummy_project', './foo.yaml']
subprocess.check_call(cmd, env=self.testenv)
self.assertTrue(op.isabs(pr.get_default_specfile(
'dummy_project')))
finally:
pr.remove_project("dummy_project_1")
def test_indexcol_not_in_usecols(self):
"""
Test if the specified index column is added to the usecols
argument."""
schema = {'iris': {'path': self.data_specs['iris']['path'],
'index_col': 'Species',
'use_columns': ['Sepal Length', 'Petal Width']}}
with tempfile.NamedTemporaryFile(delete=False) as f_schema:
yaml.dump(schema, f_schema, Dumper=Dumper, default_flow_style=False)
pr.add_project("testindex_usecols", f_schema.name)
try:
project = pr.Project("testindex_usecols")
df = project.load_dataset("iris")
self.assertEqual(df.index.name, "Species")
self.assertItemsEqual(df.columns, ['Sepal Length', 'Petal Width'])
finally:
pr.remove_project("testindex_usecols")
os.unlink(f_schema.name)
def test_index_column_rules(self):
"""Test if column rules specified for index columns are enforced."""
schema = {'iris': {'path': self.data_specs['iris']['path'],
'index_col': 'Species',
'dataframe_rules': {'drop_duplicates': False},
'column_rules': {'Species': {'regex': '.*e.*'}}}}
with tempfile.NamedTemporaryFile(delete=False) as f_schema:
yaml.dump(schema, f_schema, Dumper=Dumper, default_flow_style=False)
pr.add_project("index_col_rules", f_schema.name)
try:
project = pr.Project("index_col_rules")
df = project.load_dataset("iris")
self.assertEqual(df.index.name.lower(), 'species')
self.assertNotIn("virginica", df.index.unique())
self.assertItemsEqual(df.shape, (100, 4))
finally:
pr.remove_project("index_col_rules")
os.unlink(f_schema.name)
def cli(arguments):
"""cli - The main CLI argument parser.
:param arguments: command line arguments, as parsed by docopt
:type arguments: dict
:return: None
"""
if arguments.get("list", False):
if arguments["--project"] is None:
pr.view_projects()
else:
proj_name = arguments.get("--project")
dataset_names = pr.get_datasets(proj_name)
for name in dataset_names:
print name
elif arguments.get("add", False):
proj_name = arguments.get("PROJECT_NAME")
proj_spec = arguments.get("PROJECT_SPECFILE")
proj_spec = op.abspath(proj_spec)
pr.add_project(proj_name, proj_spec)
elif arguments.get("remove", False):
proj_name = arguments.get("PROJECT_NAME")
if arguments["--dataset"] is None:
if not pr.remove_project(proj_name):
print "Removing the project {0} failed.".format(proj_name)
else:
pr.remove_dataset(proj_name, arguments["--dataset"])
elif arguments.get("set-schema", False):
try:
proj_name = arguments.get("PROJECT_NAME")
proj_spec = arguments.get("SCHEMA_FPATH")
proj_spec = op.abspath(proj_spec)
pr.set_schema_fpath(proj_name, proj_spec)
except MissingProject:
msg = """Project {} not found in the configuration. Please use
$ semantic add
to register the project.""".format(
arguments.get("PROJECT_NAME")
)
print msg
elif arguments.get("set-specs", False):
proj_name = arguments.get("PROJECT_NAME")
dataset_name = arguments.get("--dataset")
newspecs = {}
if arguments.get("--path", False):
newspecs["path"] = arguments.get("--path")
if arguments.get("--dlm", False):
newspecs["delimiter"] = arguments.get("--dlm")
pr.set_schema_specs(proj_name, dataset_name, **newspecs)
elif arguments.get("add-dataset", False):
proj_name = arguments.get("--project")
dataset_name = arguments.get("DATASET_NAME")
specs = dict(path=arguments["--path"], delimiter=arguments["--dlm"])
pr.add_dataset(proj_name, dataset_name, specs)
elif arguments.get("export", False):
project = pr.Project(arguments.get("PROJECT_NAME"))
project.export_dataset(arguments.get("--dataset"), outpath=arguments.get("OUTPATH"))
def test_invalid_literals(self):
"""Test if columns containing invalid literals are parsed safely."""
tempdir = tempfile.mkdtemp()
schema_fpath = op.join(tempdir, "schema.yml")
data_fpath = op.join(tempdir, "data.csv")
data = pd.DataFrame.from_dict(dict(col_a=range(10)))
data['col_b'] = ["x"] * 10
data.to_csv(data_fpath, index=False)
schema = {'dataset': {'path': data_fpath, 'dtypes': {'col_a': int,
'col_b': int}}}
with open(schema_fpath, "w") as fin:
yaml.dump(schema, fin, Dumper=Dumper, default_flow_style=False)
pr.add_project("invalid_literal", schema_fpath)
try:
pr.Project("invalid_literal").load_dataset('dataset')
finally:
shutil.rmtree(tempdir)
pr.remove_project("invalid_literal")
def cli(arguments):
"""cli - The main CLI argument parser.
:param arguments: command line arguments, as parsed by docopt
:type arguments: dict
:return: None
"""
if arguments.get("list", False):
if arguments['--project'] is None:
pr.view_projects()
else:
proj_name = arguments.get('--project')
dataset_names = pr.get_datasets(proj_name)
for name in dataset_names:
print name
elif arguments.get("add", False):
proj_name = arguments.get("PROJECT_NAME")
proj_spec = arguments.get("PROJECT_SPECFILE")
proj_spec = op.abspath(proj_spec)
pr.add_project(proj_name, proj_spec)
elif arguments.get("remove", False):
proj_name = arguments.get("PROJECT_NAME")
if arguments['--dataset'] is None:
if not pr.remove_project(proj_name):
print "The project {0} doesn't exist.".format(proj_name)
else:
pr.remove_dataset(proj_name, arguments['--dataset'])
elif arguments.get("set-schema", False):
try:
proj_name = arguments.get("PROJECT_NAME")
proj_spec = arguments.get("SCHEMA_FPATH")
proj_spec = op.abspath(proj_spec)
pr.set_schema_fpath(proj_name, proj_spec)
except MissingProject:
msg = """Project {} not found in the configuration. Please use
$ semantic add
to register the project.""".format(arguments.get("PROJECT_NAME"))
print msg
elif arguments.get("set-specs", False):
proj_name = arguments.get("PROJECT_NAME")
dataset_name = arguments.get("--dataset")
newspecs = {}
if arguments.get("--path", False):
newspecs['path'] = arguments.get("--path")
if arguments.get("--dlm", False):
newspecs['delimiter'] = arguments.get("--dlm")
pr.set_schema_specs(proj_name, dataset_name, **newspecs)
elif arguments.get("add-dataset", False):
proj_name = arguments.get('--project')
dataset_name = arguments.get("DATASET_NAME")
specs = dict(path=arguments["--path"], delimiter=arguments["--dlm"])
pr.add_dataset(proj_name, dataset_name, specs)
elif arguments.get("export", False):
project = pr.Project(arguments.get("PROJECT_NAME"))
project.export_dataset(arguments.get("--dataset"),
outpath=arguments.get("OUTPATH"))
def test_load_excel_multisheet(self):
"""Test combining multiple sheets into a single dataframe."""
tempdir = tempfile.mkdtemp()
spreadsheet = op.join(tempdir, "multifile_iris.xlsx")
iris = self.project.load_dataset("iris")
with pd.ExcelWriter(spreadsheet) as writer:
iris.to_excel(writer, "iris1", index=False)
iris.to_excel(writer, "iris2", index=False)
schema = {'iris': {'path': spreadsheet, 'sheetname': ['iris1', 'iris2'],
'dataframe_rules': {'drop_duplicates': False}}}
schema_fpath = op.join(tempdir, "multi_iris.yaml")
with open(schema_fpath, "w") as fout:
yaml.dump(schema, fout, Dumper=Dumper, default_flow_style=False)
pr.add_project("multi_iris", schema_fpath)
try:
ideal = pd.concat((iris, iris), axis=0)
actual = pr.Project('multi_iris').load_dataset("iris")
self.assertDataFrameEqual(ideal, actual)
finally:
pr.remove_project("multi_iris")
shutil.rmtree(tempdir)
def test_relpath(self):
"""Test if specifying datapaths relative to schema workds."""
df = pd.DataFrame(np.random.randint(low=1, high=10, size=(10, 2)),
columns="a b".split())
tempdir = tempfile.mkdtemp()
data_dir = op.join(tempdir, "data")
os.mkdir(data_dir)
schema_fpath = op.join(tempdir, "schema.yml")
data_fpath = op.join(data_dir, "data.csv")
df.to_csv(data_fpath, index=False)
schema = {'data': {'path': op.join("data", "data.csv"),
"dataframe_rules": {"drop_duplicates": False}}}
with open(schema_fpath, "w") as fin:
yaml.dump(schema, fin, Dumper=Dumper, default_flow_style=False)
pr.add_project("relpath", schema_fpath)
try:
loaded = pr.Project("relpath").load_dataset("data")
self.assertDataFrameEqual(loaded, df)
finally:
pr.remove_project("relpath")
shutil.rmtree(tempdir)
def test_index_column_exclude(self):
"""Test if values are excluded from index column if so specified."""
tempdir = tempfile.mkdtemp()
schema_fpath = op.join(tempdir, "schema.yml")
data_fpath = op.join(tempdir, "data.csv")
df = pd.DataFrame.from_dict({'index': np.arange(10), 'col_a':
np.arange(10)})
df.to_csv(data_fpath, index=False)
schema = {'data': {'path': data_fpath, 'index_col': 'index',
'column_rules': {'index': {'exclude': [1, 2]}}}}
with open(schema_fpath, "w") as fin:
yaml.dump(schema, fin, Dumper=Dumper, default_flow_style=False)
pr.add_project("index_exclude", schema_fpath)
try:
df = pr.Project("index_exclude").load_dataset("data")
self.assertItemsEqual(df.shape, (8, 1))
self.assertEqual(df.index.name, "index")
self.assertNotIn(1, df.index)
self.assertNotIn(2, df.index)
finally:
pr.remove_project("index_exclude")
shutil.rmtree(tempdir)
def test_error_bad_lines_correction(self):
"""test if the correction for bad lines works."""
tempdir = tempfile.mkdtemp()
iris_path = op.join(op.abspath(op.dirname(__file__)), "testdata",
"iris.csv")
with open(iris_path, "r") as fid:
iris_lines = fid.readlines()
outpath = op.join(tempdir, "bad_iris.csv")
iris_lines[50] = iris_lines[50].rstrip() + ",0,23,\n"
with open(outpath, 'w') as fid:
fid.writelines(iris_lines)
data_dict = op.join(tempdir, "dummy_project.yaml")
specs = {'bad_iris': {'path': outpath}}
with open(data_dict, "w") as fid:
yaml.dump(specs, fid, Dumper=Dumper, default_flow_style=False)
pr.add_project('dummy_project', data_dict)
try:
project = pr.Project('dummy_project')
df = project.load_dataset('bad_iris')
self.assertItemsEqual(df.shape, (146, 5))
finally:
shutil.rmtree(tempdir)
pr.remove_project('dummy_project')
def test_nrows_shuffling(self):
"""test_relpath"""
"""Test if the shuffle parameter works with the nrows parameter."""
tempdir = tempfile.mkdtemp()
schema_fpath = op.join(tempdir, "schema.yml")
data_fpath = op.join(tempdir, "data.csv")
X = np.c_[np.arange(10), np.arange(10)]
ix = range(5) + "a b c d e".split()
df = pd.DataFrame(X, index=ix)
df.to_csv(data_fpath, index_label="index")
schema = {'data': {'path': data_fpath, "index_col": "index",
'nrows': {'count': 5, "shuffle": True}}}
with open(schema_fpath, "w") as fin:
yaml.dump(schema, fin, Dumper=Dumper, default_flow_style=False)
pr.add_project("nrows_shuffle", schema_fpath)
try:
df = pr.Project("nrows_shuffle").load_dataset("data")
for row_label in "a b c d e".split():
self.assertNotIn(row_label, df.index)
self.assertFalse(np.all(df.index == range(5)))
finally:
pr.remove_project("nrows_shuffle")
shutil.rmtree(tempdir)
def test_integer_col_na_values(self):
"""Test if the Loader can load columns with integers and NAs.
This is necessary because NaNs cannot be represented by integers."""
x = map(str, range(20))
x[13] = ""
df = pd.DataFrame.from_dict(dict(a=x, b=x))
tempdir = tempfile.mkdtemp()
outfile = op.join(tempdir, "testdata.csv")
df.to_csv(outfile, index=False)
specfile = op.join(tempdir, "dict.yaml")
specs = dict(delimiter=',', dtypes={'a': int, 'b': int}, path=outfile)
with open(specfile, "w") as fileobj:
yaml.dump({'testdata': specs}, fileobj, Dumper=Dumper,
default_flow_style=False)
pr.add_project("wrong_dtype", specfile)
try:
_pr = pr.Project("wrong_dtype")
df = _pr.load_dataset("testdata")
self.assertEqual(df['a'].dtype, float)
self.assertEqual(df['b'].dtype, float)
finally:
pr.remove_project("wrong_dtype")
shutil.rmtree(tempdir)
def test_global_na_reps(self):
"""Test is specifying a global NA value for a dataset works."""
tempdir = tempfile.mkdtemp()
df = pd.DataFrame(np.random.rand(10, 10))
ix = np.random.randint(0, df.shape[0], size=(5,))
ix = np.unique(ix)
for i in xrange(ix.shape[0]):
df.iloc[ix[i], ix[i]] = "foobar"
fpath = op.join(tempdir, "test_na.csv")
df.to_csv(fpath, index=False)
schema = {'path': fpath, 'na_values': "foobar",
'dataframe_rules': {'drop_na': False,
'drop_duplicates': False}}
schema_fpath = op.join(tempdir, "test_na.yaml")
with open(schema_fpath, "w") as fid:
yaml.dump({'test_na': schema}, fid, Dumper=Dumper,
default_flow_style=False)
pr.add_project("test_na", schema_fpath)
try:
df = pr.Project("test_na").load_dataset("test_na")
self.assertEqual(pd.isnull(df).sum().sum(), ix.shape[0])
finally:
pr.remove_project("test_na")
shutil.rmtree(tempdir)
def test_na_reps_list(self):
"""Test if NA values work when specified as a list."""
tempdir = tempfile.mkdtemp()
df = pd.DataFrame(np.random.rand(10, 2))
ix = np.random.randint(0, df.shape[0], size=(5,))
ix = np.unique(ix)
df.iloc[ix, 0] = "foo"
df.iloc[ix, 1] = "bar"
fpath = op.join(tempdir, "test_na.csv")
df.to_csv(fpath, index=False)
schema = {'path': fpath, 'na_values': ["foo", "bar"],
'dataframe_rules': {'drop_na': False,
'drop_duplicates': False}}
schema_fpath = op.join(tempdir, "test_na.yaml")
with open(schema_fpath, "w") as fid:
yaml.dump({'test_na': schema}, fid, Dumper=Dumper,
default_flow_style=False)
pr.add_project("test_na", schema_fpath)
try:
df = pr.Project("test_na").load_dataset("test_na")
self.assertEqual(pd.isnull(df).sum().sum(), ix.shape[0] * 2)
finally:
pr.remove_project("test_na")
shutil.rmtree(tempdir)
def test_remove_project(self):
"""Test if removing a project works properly."""
self.assertTrue(pr.remove_project("test_project"))
self.assertRaises(NoSectionError, pr.get_default_specfile,
"test_project")
def tearDown(self):
pr.remove_project("dummy_project")
def tearDown(self):
pr.remove_project("dummy_project")
def test_remove_project(self):
"""Test if removing a project works properly."""
self.assertTrue(pr.remove_project("test_project"))
self.assertRaises(NoSectionError, pr.get_default_specfile,
"test_project")
