input stringlengths 11 7.65k | target stringlengths 22 8.26k |
|---|---|
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def _match_greater_than_or_equal(search_base, attribute, value, candidates):
matches = list()
for entry in candidates:
dn = entry.get("dn")
if not dn.endswith(search_base):
continue
value_from_directory = entry.get("attributes").get(attribute)
... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def upload_face_image(self, img_data):
"""
Upload an image of the user's face. `img_data` should be a raw
bytestream of a PNG image. This method will take the data, encrypt it
using our FACE_IMAGE_AES_KEY, encode it with base64 and save it to the
storage backend.
Yes, en... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def _match_greater_than(search_base, attribute, value, candidates):
matches = list()
for entry in candidates:
dn = entry.get("dn")
if not dn.endswith(search_base):
continue
value_from_directory = entry.get("attributes").get(attribute)
if s... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def upload_photo_id_image(self, img_data):
"""
Upload an the user's photo ID image. `img_data` should be a raw
bytestream of a PNG image. This method will take the data, encrypt it
using a randomly generated AES key, encode it with base64 and save it
to the storage backend. The r... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def _match_less_than_or_equal(search_base, attribute, value, candidates):
matches = list()
for entry in candidates:
dn = entry.get("dn")
if not dn.endswith(search_base):
continue
value_from_directory = entry.get("attributes").get(attribute)
... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def submit(self, copy_id_photo_from=None):
"""
Submit our verification attempt to Software Secure for validation. This
will set our status to "submitted" if the post is successful, and
"must_retry" if the post fails.
Keyword Arguments:
copy_id_photo_from (SoftwareSec... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def _match_less_than(search_base, attribute, value, candidates):
matches = list()
for entry in candidates:
dn = entry.get("dn")
if not dn.endswith(search_base):
continue
value_from_directory = entry.get("attributes").get(attribute)
if str(... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def parsed_error_msg(self):
"""
Parse the error messages we receive from SoftwareSecure
Error messages are written in the form:
`[{"photoIdReasons": ["Not provided"]}]`
Returns:
str[]: List of error messages.
"""
parsed_errors = []
error... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def _match_equal_to(search_base, attribute, value, candidates):
matches = list()
match_using_regex = False
if "*" in value:
match_using_regex = True
#regex = check_escape(value)
regex = value.replace('*', '.*')
regex = "^{0}$".format(regex)
... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def image_url(self, name, override_receipt_id=None):
"""
We dynamically generate this, since we want it the expiration clock to
start when the message is created, not when the record is created.
Arguments:
name (str): Name of the image (e.g. "photo_id" or "face")
Ke... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def _match_notequal_to(search_base, attribute, value, candidates):
matches = list()
match_using_regex = False
if "*" in value:
match_using_regex = True
#regex = check_escape(value)
regex = value.replace('*', '.*')
regex = "^{0}$".format(regex)
... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def _storage(self):
"""
Return the configured django storage backend.
"""
config = settings.VERIFY_STUDENT["SOFTWARE_SECURE"]
# Default to the S3 backend for backward compatibility
storage_class = config.get("STORAGE_CLASS", "storages.backends.s3boto.S3BotoStorage")
... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def _parse_filter():
op = pyparsing.oneOf('! & |')
lpar = pyparsing.Literal('(').suppress()
rpar = pyparsing.Literal(')').suppress()
k = pyparsing.Word(pyparsing.alphanums)
# NOTE: We may need to expand on this list, but as this is not a real
# LDAP server we should be... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def _get_path(self, prefix, override_receipt_id=None):
"""
Returns the path to a resource with this instance's `receipt_id`.
If `override_receipt_id` is given, the path to that resource will be
retrieved instead. This allows us to retrieve images submitted in
previous attempts (... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def _deDuplicate(results):
found = dict()
deDuped = list()
for entry in results:
dn = entry.get("dn")
if not dn in found:
found[dn] = 1
deDuped.append(entry)
return deDuped |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def _encrypted_user_photo_key_str(self):
"""
Software Secure needs to have both UserPhoto and PhotoID decrypted in
the same manner. So even though this is going to be the same for every
request, we're also using RSA encryption to encrypt the AES key for
faces.
"""
... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def _invert_results(self, candidates):
inverted_candidates = list(self.directory)
for candidate in candidates:
try:
inverted_candidates.remove(candidate)
except ValueError:
pass
return inverted_candidates |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def create_request(self, copy_id_photo_from=None):
"""
Construct the HTTP request to the photo verification service.
Keyword Arguments:
copy_id_photo_from (SoftwareSecurePhotoVerification): If provided, re-send the ID photo
data from this attempt. This is used for r... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def _search_not(self, base, search_filter, candidates=None):
# Create empty candidates list as we need to use self.directory for
# each search
candidates = list()
this_filter = list()
index = 0
search_filter.remove("!")
for condition in search_filter:
... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def request_message_txt(self):
"""
This is the body of the request we send across. This is never actually
used in the code, but exists for debugging purposes -- you can call
`print attempt.request_message_txt()` on the console and get a readable
rendering of the request that woul... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def _search_and(self, base, search_filter, candidates=None):
# Load the data from the directory, if we aren't passed any
if candidates == [] or candidates is None:
candidates = self.directory
this_filter = list()
index = 0
search_filter.remove("&")
for condit... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def send_request(self, copy_id_photo_from=None):
"""
Assembles a submission to Software Secure and sends it via HTTPS.
Keyword Arguments:
copy_id_photo_from (SoftwareSecurePhotoVerification): If provided, re-send the ID photo
data from this attempt. This is used for... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def _search_or(self, base, search_filter, candidates=None):
# Create empty candidates list as we need to use self.directory for
# each search
candidates = list()
this_filter = list()
index = 0
search_filter.remove("|")
for condition in search_filter:
... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def search(self, search_base=None, search_scope=None,
search_filter=None, attributes=None, paged_size=5,
size_limit=0, paged_cookie=None):
s_filter = list()
candidates = list()
self.response = list()
self.result = dict()
try:
if isinstan... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def set_deadline(cls, course_key, deadline, is_explicit=False):
"""
Configure the verification deadline for a course.
If `deadline` is `None`, then the course will have no verification
deadline. In this case, users will be able to verify for the course
at any time.
Arg... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def unbind(self):
return True |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def deadlines_for_courses(cls, course_keys):
"""
Retrieve verification deadlines for particular courses.
Arguments:
course_keys (list): List of `CourseKey`s.
Returns:
dict: Map of course keys to datetimes (verification deadlines)
"""
all_deadlin... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def __init__(self):
self._calls = CallList()
self._server_mock = None
self.directory = []
self.exception = None
self.reset() |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def deadline_for_course(cls, course_key):
"""
Retrieve the verification deadline for a particular course.
Arguments:
course_key (CourseKey): The identifier for the course.
Returns:
datetime or None
"""
try:
deadline = cls.objects.get... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def reset(self):
self._calls.reset() |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def setLDAPDirectory(self, directory=None):
if directory is None:
self.directory = []
else:
try:
with open(DIRECTORY, 'w+') as f:
f.write(str(directory))
self.directory = directory
except OSError as e:
... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def set_exception(self, exc=True):
self.exception = exc |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def _load_data(self, directory):
try:
with open(directory, 'r') as f:
data = f.read()
return literal_eval(data)
except OSError as e:
raise |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def calls(self):
return self._calls |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def __enter__(self):
self.start() |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def __exit__(self, *args):
self.stop()
self.reset() |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def activate(self, func):
evaldict = {'ldap3mock': self, 'func': func}
return get_wrapped(func, _wrapper_template, evaldict) |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def _on_Server(self, host, port, use_ssl, connect_timeout, get_info=None,
tls=None):
# mangle request packet
return "FakeServerObject" |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def _on_Connection(self, server, user, password,
auto_bind=None, client_strategy=None,
authentication=None, check_names=None,
auto_referrals=None, receive_timeout=None):
"""
We need to create a Connection object with
methods:
... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def unbound_on_Server(host, port,
use_ssl,
connect_timeout, *a, **kwargs):
return self._on_Server(host, port,
use_ssl,
connect_timeout, *a, **kwargs) |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def unbound_on_Connection(server, user,
password,
auto_bind,
client_strategy,
authentication,
check_names,
auto_refe... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def stop(self):
self._patcher.stop()
self._patcher2.stop()
self._server_mock = None |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def get_server_mock(self):
return self._server_mock |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def setUp(self):
entry_Li = ComputedEntry("Li", -1.90753119)
with open(os.path.join(PymatgenTest.TEST_FILES_DIR, "LiTiO2_batt.json")) as f:
entries_LTO = json.load(f, cls=MontyDecoder)
self.ie_LTO = InsertionElectrode.from_entries(entries_LTO, entry_Li)
with open(os.pat... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def __init__(self):
"""
Every authenticator has to have a name
:param name:
"""
super().__init__() |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def testName(self):
plotter = VoltageProfilePlotter(xaxis="frac_x")
plotter.add_electrode(self.ie_LTO, "LTO insertion")
plotter.add_electrode(self.ce_FF, "FeF3 conversion")
self.assertIsNotNone(plotter.get_plot_data(self.ie_LTO))
self.assertIsNotNone(plotter.get_plot_data(self.ce... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def testPlotly(self):
plotter = VoltageProfilePlotter(xaxis="frac_x")
plotter.add_electrode(self.ie_LTO, "LTO insertion")
plotter.add_electrode(self.ce_FF, "FeF3 conversion")
fig = plotter.get_plotly_figure()
self.assertEqual(fig.layout.xaxis.title.text, "Atomic Fraction of Li")
... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def _no_ssl_required_on_debug(app, **kwargs):
if app.debug or app.testing:
os.environ['AUTHLIB_INSECURE_TRANSPORT'] = '1' |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def __init__(self, head):
self.head = head
self.lsize = 0
while head.next:
head = head.next
self.lsize += 1
self.m1_idx = None
self.m2_idx = None
if self.lsize > self._largesize:
self.m1_idx = self.lsize / 3 # start from 1/3
... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def _getN(self, n):
n -= 1
p = self.head
while n:
p = p.next
n -= 1
return p |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def _get(delta, start):
p = start
while delta:
p = p.next
delta -= 1
return p.val |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def main():
parser = argparse.ArgumentParser()
parser.add_argument("day", help="The day of the results, with format yyyymmdd")
args = parser.parse_args()
install_autopkgtest_results_formatter()
with tempfile.TemporaryDirectory(dir=os.environ.get("HOME")) as temp_dir:
clone_results_repo(temp_... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def __init__(self, parent, window):
self._parent = parent
self._window = window
self._application = self._parent._application
# create user interface
self._container = gtk.VBox(False, 5)
self._controls = gtk.HBox(False, 5)
separator = gtk.HSeparator()
# pack interface
self._container.pack_end(separ... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def install_autopkgtest_results_formatter():
subprocess.check_call(
["sudo", "snap", "install", "autopkgtest-results-formatter", "--edge"]
) |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def can_handle(self, uri):
"""Returns boolean denoting if specified URI can be handled by this extension"""
return False |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def clone_results_repo(dest_dir):
subprocess.check_call(
["git", "clone", "https://github.com/elopio/autopkgtest-results.git", dest_dir]
) |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def get_container(self):
"""Return container widget"""
return self._container |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def format_results(dest_dir, distros, day):
subprocess.check_call(
[
"/snap/bin/autopkgtest-results-formatter",
"--destination",
dest_dir,
"--distros",
*distros,
"--day",
day,
]
) |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def get_information(self):
"""Returns information about extension"""
icon = None
name = None
return icon, name |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def commit_and_push(repo_dir, day):
subprocess.check_call(
["git", "config", "--global", "user.email", "u1test+m-o@canonical.com"]
)
subprocess.check_call(["git", "config", "--global", "user.name", "snappy-m-o"])
subprocess.check_call(["git", "-C", repo_dir, "add", "--all"])
subprocess.chec... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def unmount(self, uri):
"""Method called by the mount manager for unmounting the selected URI"""
pass |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def focus_object(self):
"""Method called by the mount manager for focusing main object"""
pass |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def __init__(self, gan=None, config=None, trainer=None):
super().__init__(config=config, gan=gan, trainer=trainer)
self.d_grads = None
self.g_grads = None |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def main():
# Contingency Table from Wilks (2011) Table 8.3
table = np.array([[50, 91, 71],
[47, 2364, 170],
[54, 205, 3288]])
mct = MulticlassContingencyTable(table, n_classes=table.shape[0],
class_names=np.arange(table.shape[... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def gradients(self, d_grads, g_grads):
if self.d_grads is None:
self.d_grads = [torch.zeros_like(_g) for _g in d_grads]
self.g_grads = [torch.zeros_like(_g) for _g in g_grads] |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def __init__(self, table=None, n_classes=2, class_names=("1", "0")):
self.table = table
self.n_classes = n_classes
self.class_names = class_names
if table is None:
self.table = np.zeros((self.n_classes, self.n_classes), dtype=int) |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def __add__(self, other):
assert self.n_classes == other.n_classes, "Number of classes does not match"
return MulticlassContingencyTable(self.table + other.table,
n_classes=self.n_classes,
class_names=self.class_names) |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def peirce_skill_score(self):
"""
Multiclass Peirce Skill Score (also Hanssen and Kuipers score, True Skill Score)
"""
n = float(self.table.sum())
nf = self.table.sum(axis=1)
no = self.table.sum(axis=0)
correct = float(self.table.trace())
return (correct /... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def gerrity_score(self):
"""
Gerrity Score, which weights each cell in the contingency table by its observed relative frequency.
:return:
"""
k = self.table.shape[0]
n = float(self.table.sum())
p_o = self.table.sum(axis=0) / n
p_sum = np.cumsum(p_o)[:-1]
... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def heidke_skill_score(self):
n = float(self.table.sum())
nf = self.table.sum(axis=1)
no = self.table.sum(axis=0)
correct = float(self.table.trace())
return (correct / n - (nf * no).sum() / n ** 2) / (1 - (nf * no).sum() / n ** 2) |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def git_checkout(git_url, git_branch=None, git_tag=None, git_hash=None):
git_dst = tempfile.mkdtemp()
g = GitManager(url=git_url, git_dst=git_dst, git_branch=git_branch, git_tag=git_tag, git_hash=git_hash)
g.run()
shutil.rmtree(git_dst) |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def test_git_tag():
""" Test checkout w/ Tag """
git_checkout(git_url='https://github.com/voltgrid/voltgrid-pie.git', git_branch=None, git_tag='v0.1.0') |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def test_git_branch():
""" Test checkout w/ Branch """
git_checkout(git_url='https://github.com/voltgrid/voltgrid-pie.git', git_branch='master', git_tag=None) |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def test_make_gym_venv_nostack(name, num_envs, state_shape, reward_scale):
seed = 0
frame_op = None
frame_op_len = None
venv = make_gym_venv(name, num_envs, seed, frame_op=frame_op, frame_op_len=frame_op_len, reward_scale=reward_scale)
venv.reset()
for i in range(5):
state, reward, done,... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def compute_rbf_kernel_matrix(X):
"""Compute the RBF kernel matrix with sigma2 as the median pairwise
distance.
"""
sigma2 = np.median(pairwise_distances(X, metric='euclidean'))**2
K = pairwise_kernels(X, X, metric='rbf', gamma=1.0/sigma2, n_jobs=-1)
return K |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def test_make_gym_concat(name, num_envs, state_shape, reward_scale):
seed = 0
frame_op = 'concat' # used for image, or for concat vector
frame_op_len = 4
venv = make_gym_venv(name, num_envs, seed, frame_op=frame_op, frame_op_len=frame_op_len, reward_scale=reward_scale)
venv.reset()
for i in ran... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def balanced_accuracy_scoring(clf, X, y):
"""Scoring function that computes the balanced accuracy to be used
internally in the cross-validation procedure.
"""
y_pred = clf.predict(X)
conf_mat = confusion_matrix(y, y_pred)
bal_acc = 0.
for i in range(len(conf_mat)):
bal_acc += (float(... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def test_make_gym_stack(name, num_envs, state_shape, reward_scale):
seed = 0
frame_op = 'stack' # used for rnn
frame_op_len = 4
venv = make_gym_venv(name, num_envs, seed, frame_op=frame_op, frame_op_len=frame_op_len, reward_scale=reward_scale)
venv.reset()
for i in range(5):
state, rewa... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def compute_svm_cv(K, y, C=100.0, n_folds=5,
scoring=balanced_accuracy_scoring):
"""Compute cross-validated score of SVM with given precomputed kernel.
"""
cv = StratifiedKFold(y, n_folds=n_folds)
clf = SVC(C=C, kernel='precomputed', class_weight='auto')
scores = cross_val_score(c... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def compute_svm_subjects(K, y, n_folds=5):
"""
"""
cv = KFold(len(K)/2, n_folds)
scores = np.zeros(n_folds)
for i, (train, test) in enumerate(cv):
train_ids = np.concatenate((train, len(K)/2+train))
test_ids = np.concatenate((test, len(K)/2+test))
clf = SVC(kernel='precompute... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def permutation_subjects(y):
"""Permute class labels of Contextual Disorder dataset.
"""
y_perm = np.random.randint(0, 2, len(y)/2)
y_perm = np.concatenate((y_perm, np.logical_not(y_perm).astype(int)))
return y_perm |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def permutation_subjects_ktst(y):
"""Permute class labels of Contextual Disorder dataset for KTST.
"""
yp = np.random.randint(0, 2, len(y)/2)
yp = np.concatenate((yp, np.logical_not(yp).astype(int)))
y_perm = np.arange(len(y))
for i in range(len(y)/2):
if yp[i] == 1:
y_perm[i... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def compute_svm_score_nestedCV(K, y, n_folds,
scoring=balanced_accuracy_scoring,
random_state=None,
param_grid=[{'C': np.logspace(-5, 5, 25)}]):
"""Compute cross-validated score of SVM using precomputed kernel.
"""
... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def apply_svm(K, y, n_folds=5, iterations=10000, subjects=False, verbose=True,
random_state=None):
"""
Compute the balanced accuracy, its null distribution and the p-value.
Parameters:
----------
K: array-like
Kernel matrix
y: array_like
class labels
cv: Number... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def apply_ktst(K, y, iterations=10000, subjects=False, verbose=True):
"""
Compute MMD^2_u, its null distribution and the p-value of the
kernel two-sample test.
Parameters:
----------
K: array-like
Kernel matrix
y: array_like
class labels
verbose: bool
Verbosity
... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def test_login(self, mock_login_with_token, mock_input, mock_open_url):
quilt3.login()
url = quilt3.session.get_registry_url()
mock_open_url.assert_called_with(f'{url}/login')
mock_login_with_token.assert_called_with('123456') |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def decode(value):
if isinstance(value, bytes):
value = value.decode(errors="surrogateescape")
for char in ("\\", "\n", "\t"):
value = value.replace(
char.encode(encoding="unicode-escape").decode(), char
)
return value |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def test_login_with_token(self, mock_save_credentials, mock_save_auth):
url = quilt3.session.get_registry_url()
mock_auth = dict(
refresh_token='refresh-token',
access_token='access-token',
expires_at=123456789
)
self.requests_mock.add(
r... |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def encode(value):
if isinstance(value, bytes):
value = value.decode(errors="surrogateescape")
for char in ("\\", "\n", "\t"):
value = value.replace(
char, char.encode(encoding="unicode-escape").decode()
)
return value |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def format_date(date):
return date.replace(tzinfo=datetime.timezone.utc, microsecond=0).isoformat() |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def deserialize(self, value):
"""Cast raw string to appropriate type."""
return decode(value) |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def serialize(self, value, display=False):
"""Convert value back to string for saving."""
if value is None:
return ""
return str(value) |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def deserialize(self, value):
return DeprecatedValue() |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def serialize(self, value, display=False):
return DeprecatedValue() |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def __init__(self, optional=False, choices=None):
self._required = not optional
self._choices = choices |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def deserialize(self, value):
value = decode(value).strip()
validators.validate_required(value, self._required)
if not value:
return None
validators.validate_choice(value, self._choices)
return value |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def serialize(self, value, display=False):
if value is None:
return ""
return encode(value) |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def __init__(self, optional=False, choices=None):
self._required = not optional
self._choices = None # Choices doesn't make sense for secrets |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def serialize(self, value, display=False):
if value is not None and display:
return "********"
return super().serialize(value, display) |
def search(self, regex):
try:
spec = {'$or': [{'data.content' : {'$regex': regex, '$options': 'im'}},
{'data.description': {'$regex': regex, '$options': 'im'}}]}
fields = {'_id': 0}
cur = self.db.docs.find(spec, fields)
except Exception ... | def __init__(
self, minimum=None, maximum=None, choices=None, optional=False
):
self._required = not optional
self._minimum = minimum
self._maximum = maximum
self._choices = choices |
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