def available_datasets(type='%', name='%'):
try:
cur = co.Camoco("Camoco", type='Camoco').db.cursor()
datasets = cur.execute('''
SELECT type, name, description, added
FROM datasets
WHERE type LIKE ?
AND name LIKE ?
ORDER BY type;''', (type,name)).fetchall()
if datasets:
datasets = pd.DataFrame(
datasets,
columns=["Type", "Name", "Description", "Date Added"],
).set_index(['Type'])
else:
datasets = pd.DataFrame(
columns=["Type", "Name", "Description", "Date Added"]
)
# Check to see if we are looking for a specific dataset
if '%' not in type and '%' not in name:
return True if name in datasets['Name'].values else False
else:
return datasets
except CantOpenError as e:
raise e
def redescribe_dataset(type,name,new_desc):
c = co.Camoco("Camoco")
c.db.cursor().execute('''
UPDATE datasets SET description = ?
WHERE name = ? AND type = ?''',
(new_desc,name,type)
)
def del_dataset(type, name, force=False): # pragma no cover
try:
c = co.Camoco("Camoco")
except CantOpenError:
return True
if force == False:
c.log("Are you sure you want to delete:\n {}.{}", type, name)
if input("[Y/n]").upper() != 'Y':
c.log("Nothing Deleted")
return
c.log("Deleting {}", name)
try:
c.db.cursor().execute('''
DELETE FROM datasets
WHERE name LIKE '{}'
AND type LIKE '{}';'''.format(name, type))
except CantOpenError:
pass
try:
dfiles = glob.glob(
os.path.join(cf.options.basedir, 'databases',
'{}.{}.*'.format(type, name)))
for f in dfiles:
c.log('Removing {}', f)
try:
os.remove(f)
except IsADirectoryError:
shutil.rmtree(f)
except FileNotFoundError as e:
pass
if type == 'Expr':
# also have to remove the COB specific refgen
del_dataset('RefGen', 'Filtered' + name, force=force)
del_dataset('Ontology', name + 'MCL', force=force)
return True
def available_datasets(type="%", name="%"): # pragma no cover
try:
cur = co.Camoco("Camoco", type="Camoco").db.cursor()
datasets = cur.execute(
"""
SELECT type, name, description, added
FROM datasets
WHERE type LIKE ?
AND name LIKE ?
ORDER BY type;""",
(type, name),
).fetchall()
if datasets:
datasets = pd.DataFrame(
datasets,
columns=["Type", "Name", "Description",
"Date Added"]).set_index(["Type"])
else:
datasets = pd.DataFrame(
columns=["Type", "Name", "Description", "Date Added"])
# Check to see if we are looking for a specific dataset
if "%" not in type and "%" not in name:
return True if name in datasets["Name"].values else False
else:
return datasets
except CantOpenError as e:
raise e
def redescribe_dataset(type, name, new_desc): # pragma no cover
c = co.Camoco("Camoco")
c.db.cursor().execute(
"""
UPDATE datasets SET description = ?
WHERE name = ? AND type = ?""",
(new_desc, name, type),
)
def mv_dataset(type, name, new_name): # pragma no cover
c = co.Camoco("Camoco")
c.db.cursor().execute(
'''
UPDATE datasets SET name = ?
WHERE name = ? AND
type = ?''', (new_name, name, type))
os.rename(c._resource('databases', '.'.join([type, name]) + ".db"),
c._resource('databases', ".".join([type, new_name]) + ".db"))