blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 6.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 438 7.52k | id stringlengths 40 40 | length_bytes int64 506 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
742506e84be93de338c3d4a6376f141ffd57eed1 | [
"self.b = block\nself.p = pblock\nself.nstops = nstops\nif not xend:\n if self.p == self.b:\n xend = np.random.uniform(self.p.xb0, self.p.xb1)\n else:\n bxmin, bxmax = self.b.xrange_at_y(self.p.y0)\n pxmin, pxmax = self.p.xrange_at_y(self.p.y0)\n xmin = max(pxmin, bxmin)\n x... | <|body_start_0|>
self.b = block
self.p = pblock
self.nstops = nstops
if not xend:
if self.p == self.b:
xend = np.random.uniform(self.p.xb0, self.p.xb1)
else:
bxmin, bxmax = self.b.xrange_at_y(self.p.y0)
pxmin, pxmax ... | Wiggle | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Wiggle:
def __init__(self, block, pblock, xstart, xend, ystart, yend, nstops):
"""Calculate slope to sample points. __/ /\\ \\ / \\ \\ \\ /____/\\_\\ \\_\\"""
<|body_0|>
def get_line(self):
"""Samples points within bounds to connect lower to upper edge. \\ \\ _______... | stack_v2_sparse_classes_36k_train_002900 | 19,966 | permissive | [
{
"docstring": "Calculate slope to sample points. __/ /\\\\ \\\\ / \\\\ \\\\ \\\\ /____/\\\\_\\\\ \\\\_\\\\",
"name": "__init__",
"signature": "def __init__(self, block, pblock, xstart, xend, ystart, yend, nstops)"
},
{
"docstring": "Samples points within bounds to connect lower to upper edge. \... | 2 | stack_v2_sparse_classes_30k_train_002106 | Implement the Python class `Wiggle` described below.
Class description:
Implement the Wiggle class.
Method signatures and docstrings:
- def __init__(self, block, pblock, xstart, xend, ystart, yend, nstops): Calculate slope to sample points. __/ /\\ \\ / \\ \\ \\ /____/\\_\\ \\_\\
- def get_line(self): Samples points ... | Implement the Python class `Wiggle` described below.
Class description:
Implement the Wiggle class.
Method signatures and docstrings:
- def __init__(self, block, pblock, xstart, xend, ystart, yend, nstops): Calculate slope to sample points. __/ /\\ \\ / \\ \\ \\ /____/\\_\\ \\_\\
- def get_line(self): Samples points ... | 9d706e7caad63a17f2a8a6b97e752bc79c5eefed | <|skeleton|>
class Wiggle:
def __init__(self, block, pblock, xstart, xend, ystart, yend, nstops):
"""Calculate slope to sample points. __/ /\\ \\ / \\ \\ \\ /____/\\_\\ \\_\\"""
<|body_0|>
def get_line(self):
"""Samples points within bounds to connect lower to upper edge. \\ \\ _______... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Wiggle:
def __init__(self, block, pblock, xstart, xend, ystart, yend, nstops):
"""Calculate slope to sample points. __/ /\\ \\ / \\ \\ \\ /____/\\_\\ \\_\\"""
self.b = block
self.p = pblock
self.nstops = nstops
if not xend:
if self.p == self.b:
... | the_stack_v2_python_sparse | toytree/Container.py | eaton-lab/toytree | train | 155 | |
7761259dab72aad87d471ba08bf6310965a2fbd9 | [
"context = super(ObjectDetailView, self).get_context_data(**kwargs)\nobj = self.get_object()\nattribute_list = OrderedDict()\nfor attribute in self.attributes:\n if attribute in self.typeclass._meta._property_names:\n attribute_list[attribute.title()] = getattr(obj, attribute, '')\n else:\n attr... | <|body_start_0|>
context = super(ObjectDetailView, self).get_context_data(**kwargs)
obj = self.get_object()
attribute_list = OrderedDict()
for attribute in self.attributes:
if attribute in self.typeclass._meta._property_names:
attribute_list[attribute.title()]... | This is an important view. Any view you write that deals with displaying, updating or deleting a specific object will want to inherit from this. It provides the mechanisms by which to retrieve the object and make sure the user requesting it has permissions to actually *do* things to it. | ObjectDetailView | [
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ObjectDetailView:
"""This is an important view. Any view you write that deals with displaying, updating or deleting a specific object will want to inherit from this. It provides the mechanisms by which to retrieve the object and make sure the user requesting it has permissions to actually *do* th... | stack_v2_sparse_classes_36k_train_002901 | 35,922 | permissive | [
{
"docstring": "Adds an 'attributes' list to the request context consisting of the attributes specified at the class level, and in the order provided. Django views do not provide a way to reference dynamic attributes, so we have to grab them all before we render the template. Returns: context (dict): Django con... | 2 | null | Implement the Python class `ObjectDetailView` described below.
Class description:
This is an important view. Any view you write that deals with displaying, updating or deleting a specific object will want to inherit from this. It provides the mechanisms by which to retrieve the object and make sure the user requesting... | Implement the Python class `ObjectDetailView` described below.
Class description:
This is an important view. Any view you write that deals with displaying, updating or deleting a specific object will want to inherit from this. It provides the mechanisms by which to retrieve the object and make sure the user requesting... | 5e97df013399e1a401d0a7ec184c4b9eb3100edd | <|skeleton|>
class ObjectDetailView:
"""This is an important view. Any view you write that deals with displaying, updating or deleting a specific object will want to inherit from this. It provides the mechanisms by which to retrieve the object and make sure the user requesting it has permissions to actually *do* th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ObjectDetailView:
"""This is an important view. Any view you write that deals with displaying, updating or deleting a specific object will want to inherit from this. It provides the mechanisms by which to retrieve the object and make sure the user requesting it has permissions to actually *do* things to it.""... | the_stack_v2_python_sparse | evennia-engine/evennia/evennia/web/website/views.py | rajammanabrolu/WorldGeneration | train | 69 |
cd45939921a9137f3d1bd6b5ff6846ec36087f3c | [
"output_file_name = 'sshd_config_analysis.txt'\noutput_file_path = os.path.join(self.output_dir, output_file_name)\noutput_evidence = ReportText(source_path=output_file_path)\nwith open(evidence.local_path, 'r') as input_file:\n sshd_config = input_file.read()\nreport, priority, summary = self.analyse_sshd_confi... | <|body_start_0|>
output_file_name = 'sshd_config_analysis.txt'
output_file_path = os.path.join(self.output_dir, output_file_name)
output_evidence = ReportText(source_path=output_file_path)
with open(evidence.local_path, 'r') as input_file:
sshd_config = input_file.read()
... | Task to analyze a sshd_config file. | SSHDAnalysisTask | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SSHDAnalysisTask:
"""Task to analyze a sshd_config file."""
def run(self, evidence, result):
"""Run the sshd_config analysis worker. Args: evidence (Evidence object): The evidence we will process. result (TurbiniaTaskResult): The object to place task results into. Returns: TurbiniaTa... | stack_v2_sparse_classes_36k_train_002902 | 3,612 | permissive | [
{
"docstring": "Run the sshd_config analysis worker. Args: evidence (Evidence object): The evidence we will process. result (TurbiniaTaskResult): The object to place task results into. Returns: TurbiniaTaskResult object.",
"name": "run",
"signature": "def run(self, evidence, result)"
},
{
"docst... | 2 | null | Implement the Python class `SSHDAnalysisTask` described below.
Class description:
Task to analyze a sshd_config file.
Method signatures and docstrings:
- def run(self, evidence, result): Run the sshd_config analysis worker. Args: evidence (Evidence object): The evidence we will process. result (TurbiniaTaskResult): T... | Implement the Python class `SSHDAnalysisTask` described below.
Class description:
Task to analyze a sshd_config file.
Method signatures and docstrings:
- def run(self, evidence, result): Run the sshd_config analysis worker. Args: evidence (Evidence object): The evidence we will process. result (TurbiniaTaskResult): T... | e73717549c6919e869ce4963449c36f227e3ccd6 | <|skeleton|>
class SSHDAnalysisTask:
"""Task to analyze a sshd_config file."""
def run(self, evidence, result):
"""Run the sshd_config analysis worker. Args: evidence (Evidence object): The evidence we will process. result (TurbiniaTaskResult): The object to place task results into. Returns: TurbiniaTa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SSHDAnalysisTask:
"""Task to analyze a sshd_config file."""
def run(self, evidence, result):
"""Run the sshd_config analysis worker. Args: evidence (Evidence object): The evidence we will process. result (TurbiniaTaskResult): The object to place task results into. Returns: TurbiniaTaskResult obje... | the_stack_v2_python_sparse | turbinia/workers/sshd.py | Ash515/turbinia | train | 6 |
c753697354826e8b9e43c4002a7a239160d4cdd3 | [
"self.ap = AxesSetupPanel(self.MovieFrames)\nself.dp = DisplayPanel()\nself.cp = ControlPanel()\nctrl_box = gtk.VBox()\nctrl_box.set_border_width(3)\nctrl_box.pack_start(self.dp, False, False, 5)\nctrl_box.pack_start(self.ap, False, False, 5)\nctrl_box.pack_end(self.cp, False, False, 5)\nreturn ctrl_box",
"self.M... | <|body_start_0|>
self.ap = AxesSetupPanel(self.MovieFrames)
self.dp = DisplayPanel()
self.cp = ControlPanel()
ctrl_box = gtk.VBox()
ctrl_box.set_border_width(3)
ctrl_box.pack_start(self.dp, False, False, 5)
ctrl_box.pack_start(self.ap, False, False, 5)
ctr... | GTK Window with movie frame and control elements Members: canvas -- MPL canvas ap -- Axis panel dp -- Display panel cp -- Control panel toolbar -- Toolbar | MovieGUI | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MovieGUI:
"""GTK Window with movie frame and control elements Members: canvas -- MPL canvas ap -- Axis panel dp -- Display panel cp -- Control panel toolbar -- Toolbar"""
def make_control_box(self):
"""make VBox with various control panels"""
<|body_0|>
def __init__(self... | stack_v2_sparse_classes_36k_train_002903 | 2,542 | no_license | [
{
"docstring": "make VBox with various control panels",
"name": "make_control_box",
"signature": "def make_control_box(self)"
},
{
"docstring": "canvas should set size request before",
"name": "__init__",
"signature": "def __init__(self, movie_frames, movie_file_maker, *args, **kwargs)"
... | 2 | null | Implement the Python class `MovieGUI` described below.
Class description:
GTK Window with movie frame and control elements Members: canvas -- MPL canvas ap -- Axis panel dp -- Display panel cp -- Control panel toolbar -- Toolbar
Method signatures and docstrings:
- def make_control_box(self): make VBox with various co... | Implement the Python class `MovieGUI` described below.
Class description:
GTK Window with movie frame and control elements Members: canvas -- MPL canvas ap -- Axis panel dp -- Display panel cp -- Control panel toolbar -- Toolbar
Method signatures and docstrings:
- def make_control_box(self): make VBox with various co... | 775dc841b1d8538584c8c68a5f75ae997191e685 | <|skeleton|>
class MovieGUI:
"""GTK Window with movie frame and control elements Members: canvas -- MPL canvas ap -- Axis panel dp -- Display panel cp -- Control panel toolbar -- Toolbar"""
def make_control_box(self):
"""make VBox with various control panels"""
<|body_0|>
def __init__(self... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MovieGUI:
"""GTK Window with movie frame and control elements Members: canvas -- MPL canvas ap -- Axis panel dp -- Display panel cp -- Control panel toolbar -- Toolbar"""
def make_control_box(self):
"""make VBox with various control panels"""
self.ap = AxesSetupPanel(self.MovieFrames)
... | the_stack_v2_python_sparse | Movie/Movie_GUI/GUI/movie_gui.py | atimokhin/tdc_vis | train | 0 |
a58ec008eeabfbba9c1aa4d084a25c526455dc1c | [
"if self.twitter_link or self.facebook_link or self.pinterest_link or self.youtube_link or self.github_link or self.linkedin_link or self.vk_link or self.gplus_link:\n self.has_social_network_links = True\nelse:\n self.has_social_network_links = False\nsuper(SiteConfiguration, self).save(*args, **kwargs)",
... | <|body_start_0|>
if self.twitter_link or self.facebook_link or self.pinterest_link or self.youtube_link or self.github_link or self.linkedin_link or self.vk_link or self.gplus_link:
self.has_social_network_links = True
else:
self.has_social_network_links = False
super(Sit... | A model to edit sitewide content | SiteConfiguration | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SiteConfiguration:
"""A model to edit sitewide content"""
def save(self, *args, **kwargs):
"""Set has_social_network_links"""
<|body_0|>
def render_copyright(self):
"""Render the footer"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if self.twi... | stack_v2_sparse_classes_36k_train_002904 | 16,707 | permissive | [
{
"docstring": "Set has_social_network_links",
"name": "save",
"signature": "def save(self, *args, **kwargs)"
},
{
"docstring": "Render the footer",
"name": "render_copyright",
"signature": "def render_copyright(self)"
}
] | 2 | null | Implement the Python class `SiteConfiguration` described below.
Class description:
A model to edit sitewide content
Method signatures and docstrings:
- def save(self, *args, **kwargs): Set has_social_network_links
- def render_copyright(self): Render the footer | Implement the Python class `SiteConfiguration` described below.
Class description:
A model to edit sitewide content
Method signatures and docstrings:
- def save(self, *args, **kwargs): Set has_social_network_links
- def render_copyright(self): Render the footer
<|skeleton|>
class SiteConfiguration:
"""A model to... | 69855813052243c702c9b0108d2eac3f4f1a768f | <|skeleton|>
class SiteConfiguration:
"""A model to edit sitewide content"""
def save(self, *args, **kwargs):
"""Set has_social_network_links"""
<|body_0|>
def render_copyright(self):
"""Render the footer"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SiteConfiguration:
"""A model to edit sitewide content"""
def save(self, *args, **kwargs):
"""Set has_social_network_links"""
if self.twitter_link or self.facebook_link or self.pinterest_link or self.youtube_link or self.github_link or self.linkedin_link or self.vk_link or self.gplus_link... | the_stack_v2_python_sparse | theme/models.py | hydroshare/hydroshare | train | 207 |
667426322e8b20be95be8415c8b544312fa8f4f5 | [
"role = db.Role.get(id)\nif not role:\n return ({'msg': f'Role with id={id} not found.'}, HTTPStatus.NOT_FOUND)\nif not (self.r.v_glo.can() or role in g.user.roles):\n if not (self.r.v_org.can() and role.organization == g.user.organization):\n return ({'msg': 'You do not have permission to view this.'}... | <|body_start_0|>
role = db.Role.get(id)
if not role:
return ({'msg': f'Role with id={id} not found.'}, HTTPStatus.NOT_FOUND)
if not (self.r.v_glo.can() or role in g.user.roles):
if not (self.r.v_org.can() and role.organization == g.user.organization):
retu... | Role | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Role:
def get(self, id):
"""Get roles --- description: >- Get role based on role identifier. ### Permission Table |Rule name|Scope|Operation|Assigned to node|Assigned to container| Description| |--|--|--|--|--|--| |Role|Global|View|❌|❌|View all roles| |Role|Organization|View|❌|❌|View rol... | stack_v2_sparse_classes_36k_train_002905 | 26,260 | permissive | [
{
"docstring": "Get roles --- description: >- Get role based on role identifier. ### Permission Table |Rule name|Scope|Operation|Assigned to node|Assigned to container| Description| |--|--|--|--|--|--| |Role|Global|View|❌|❌|View all roles| |Role|Organization|View|❌|❌|View roles that are part of your organizatio... | 3 | stack_v2_sparse_classes_30k_train_006643 | Implement the Python class `Role` described below.
Class description:
Implement the Role class.
Method signatures and docstrings:
- def get(self, id): Get roles --- description: >- Get role based on role identifier. ### Permission Table |Rule name|Scope|Operation|Assigned to node|Assigned to container| Description| |... | Implement the Python class `Role` described below.
Class description:
Implement the Role class.
Method signatures and docstrings:
- def get(self, id): Get roles --- description: >- Get role based on role identifier. ### Permission Table |Rule name|Scope|Operation|Assigned to node|Assigned to container| Description| |... | b3ff6e91ac4caeaf31c12c20f73dfc61cfd9baca | <|skeleton|>
class Role:
def get(self, id):
"""Get roles --- description: >- Get role based on role identifier. ### Permission Table |Rule name|Scope|Operation|Assigned to node|Assigned to container| Description| |--|--|--|--|--|--| |Role|Global|View|❌|❌|View all roles| |Role|Organization|View|❌|❌|View rol... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Role:
def get(self, id):
"""Get roles --- description: >- Get role based on role identifier. ### Permission Table |Rule name|Scope|Operation|Assigned to node|Assigned to container| Description| |--|--|--|--|--|--| |Role|Global|View|❌|❌|View all roles| |Role|Organization|View|❌|❌|View roles that are pa... | the_stack_v2_python_sparse | vantage6-server/vantage6/server/resource/role.py | vantage6/vantage6 | train | 15 | |
fe8fb2713f503e8047df614596d39cf51a68a3d5 | [
"if annotation_file:\n if annotation_file.startswith('gs://'):\n _, local_val_json = tempfile.mkstemp(suffix='.json')\n tf.gfile.Remove(local_val_json)\n tf.gfile.Copy(annotation_file, local_val_json)\n atexit.register(tf.gfile.Remove, local_val_json)\n else:\n local_val_jso... | <|body_start_0|>
if annotation_file:
if annotation_file.startswith('gs://'):
_, local_val_json = tempfile.mkstemp(suffix='.json')
tf.gfile.Remove(local_val_json)
tf.gfile.Copy(annotation_file, local_val_json)
atexit.register(tf.gfile.Re... | LVIS evaluation metric class. | LVISEvaluator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LVISEvaluator:
"""LVIS evaluation metric class."""
def __init__(self, annotation_file, include_mask, need_rescale_bboxes=True, per_category_metrics=False):
"""Constructs LVIS evaluation class. The class provides the interface to metrics_fn in TPUEstimator. The _update_op() takes dete... | stack_v2_sparse_classes_36k_train_002906 | 20,065 | permissive | [
{
"docstring": "Constructs LVIS evaluation class. The class provides the interface to metrics_fn in TPUEstimator. The _update_op() takes detections from each image and push them to self.detections. The _evaluate() loads a JSON file in LVIS annotation format as the groundtruths and runs LVIS evaluation. Args: an... | 2 | stack_v2_sparse_classes_30k_train_009586 | Implement the Python class `LVISEvaluator` described below.
Class description:
LVIS evaluation metric class.
Method signatures and docstrings:
- def __init__(self, annotation_file, include_mask, need_rescale_bboxes=True, per_category_metrics=False): Constructs LVIS evaluation class. The class provides the interface t... | Implement the Python class `LVISEvaluator` described below.
Class description:
LVIS evaluation metric class.
Method signatures and docstrings:
- def __init__(self, annotation_file, include_mask, need_rescale_bboxes=True, per_category_metrics=False): Constructs LVIS evaluation class. The class provides the interface t... | 0f7adb97a93ec3e3485c261d030c507eb16b33e4 | <|skeleton|>
class LVISEvaluator:
"""LVIS evaluation metric class."""
def __init__(self, annotation_file, include_mask, need_rescale_bboxes=True, per_category_metrics=False):
"""Constructs LVIS evaluation class. The class provides the interface to metrics_fn in TPUEstimator. The _update_op() takes dete... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LVISEvaluator:
"""LVIS evaluation metric class."""
def __init__(self, annotation_file, include_mask, need_rescale_bboxes=True, per_category_metrics=False):
"""Constructs LVIS evaluation class. The class provides the interface to metrics_fn in TPUEstimator. The _update_op() takes detections from e... | the_stack_v2_python_sparse | models/official/detection/evaluation/coco_evaluator.py | tensorflow/tpu | train | 5,627 |
3248b044a38f8f177a84c24d2eda205f09e9c038 | [
"diagnostic = SchedResetAIRCx()\nif isinstance(diagnostic, SchedResetAIRCx):\n assert True\nelse:\n assert False",
"diagnostic = SchedResetAIRCx()\ndiagnostic.set_class_values({1.0}, {2.0}, {}, {}, {}, {}, {}, {}, {}, 1, {3.0}, {4.0}, 'test', [])\nassert diagnostic.no_req_data == 1\nassert diagnostic.analys... | <|body_start_0|>
diagnostic = SchedResetAIRCx()
if isinstance(diagnostic, SchedResetAIRCx):
assert True
else:
assert False
<|end_body_0|>
<|body_start_1|>
diagnostic = SchedResetAIRCx()
diagnostic.set_class_values({1.0}, {2.0}, {}, {}, {}, {}, {}, {}, {},... | Contains all the tests for SchedResetAIRCx Diagnostic | TestDiagnosticsScheduleResetAIRCx | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestDiagnosticsScheduleResetAIRCx:
"""Contains all the tests for SchedResetAIRCx Diagnostic"""
def test_schedule_reset_dx_creation(self):
"""test the creation of schedule reset diagnostic class"""
<|body_0|>
def test_duct_static_dx_set_class_values(self):
"""test... | stack_v2_sparse_classes_36k_train_002907 | 14,928 | permissive | [
{
"docstring": "test the creation of schedule reset diagnostic class",
"name": "test_schedule_reset_dx_creation",
"signature": "def test_schedule_reset_dx_creation(self)"
},
{
"docstring": "test the creation of schedule reset diagnostic class",
"name": "test_duct_static_dx_set_class_values",... | 4 | null | Implement the Python class `TestDiagnosticsScheduleResetAIRCx` described below.
Class description:
Contains all the tests for SchedResetAIRCx Diagnostic
Method signatures and docstrings:
- def test_schedule_reset_dx_creation(self): test the creation of schedule reset diagnostic class
- def test_duct_static_dx_set_cla... | Implement the Python class `TestDiagnosticsScheduleResetAIRCx` described below.
Class description:
Contains all the tests for SchedResetAIRCx Diagnostic
Method signatures and docstrings:
- def test_schedule_reset_dx_creation(self): test the creation of schedule reset diagnostic class
- def test_duct_static_dx_set_cla... | 24d50729aef8d91036cc13b0f5c03be76f3237ed | <|skeleton|>
class TestDiagnosticsScheduleResetAIRCx:
"""Contains all the tests for SchedResetAIRCx Diagnostic"""
def test_schedule_reset_dx_creation(self):
"""test the creation of schedule reset diagnostic class"""
<|body_0|>
def test_duct_static_dx_set_class_values(self):
"""test... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestDiagnosticsScheduleResetAIRCx:
"""Contains all the tests for SchedResetAIRCx Diagnostic"""
def test_schedule_reset_dx_creation(self):
"""test the creation of schedule reset diagnostic class"""
diagnostic = SchedResetAIRCx()
if isinstance(diagnostic, SchedResetAIRCx):
... | the_stack_v2_python_sparse | EnergyEfficiency/AirsideRCxAgent/airside/test.py | shwethanidd/volttron-pnnl-applications-2 | train | 0 |
bf60b88048d06d59d634d7a70c9308fad5a51d0d | [
"if randint_function is not None:\n if not hasattr(randint_function, '__call__'):\n raise TypeError('randint_function has to be a function')\n self.randint_function = randint_function\n if period is None:\n period = self.period\nif period is not None and permutation_table is not None:\n ra... | <|body_start_0|>
if randint_function is not None:
if not hasattr(randint_function, '__call__'):
raise TypeError('randint_function has to be a function')
self.randint_function = randint_function
if period is None:
period = self.period
if... | Noise abstract base class | BaseNoise | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseNoise:
"""Noise abstract base class"""
def __init__(self, period=None, permutation_table=None, randint_function=None):
"""Initialize the noise generator. With no arguments, the default period and permutation table are used (256). The default permutation table generates the exact ... | stack_v2_sparse_classes_36k_train_002908 | 13,275 | permissive | [
{
"docstring": "Initialize the noise generator. With no arguments, the default period and permutation table are used (256). The default permutation table generates the exact same noise pattern each time. An integer period can be specified, to generate a random permutation table with period elements. The period ... | 2 | stack_v2_sparse_classes_30k_val_000108 | Implement the Python class `BaseNoise` described below.
Class description:
Noise abstract base class
Method signatures and docstrings:
- def __init__(self, period=None, permutation_table=None, randint_function=None): Initialize the noise generator. With no arguments, the default period and permutation table are used ... | Implement the Python class `BaseNoise` described below.
Class description:
Noise abstract base class
Method signatures and docstrings:
- def __init__(self, period=None, permutation_table=None, randint_function=None): Initialize the noise generator. With no arguments, the default period and permutation table are used ... | 6fc0ccbc6fb24dcc2a8532aa22eb9574f1afdb3a | <|skeleton|>
class BaseNoise:
"""Noise abstract base class"""
def __init__(self, period=None, permutation_table=None, randint_function=None):
"""Initialize the noise generator. With no arguments, the default period and permutation table are used (256). The default permutation table generates the exact ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BaseNoise:
"""Noise abstract base class"""
def __init__(self, period=None, permutation_table=None, randint_function=None):
"""Initialize the noise generator. With no arguments, the default period and permutation table are used (256). The default permutation table generates the exact same noise pa... | the_stack_v2_python_sparse | pyrt/math/perlin.py | martinchristen/pyRT | train | 79 |
0d88b97c9a45bf96b5c9ccd1af1f6f65453f6025 | [
"params = super().get_default_params(with_embedding=True, with_multi_layer_perceptron=True)\nparams['mlp_num_units'] = 256\nparams.get('mlp_num_units').hyper_space = hyper_spaces.quniform(16, 512)\nparams.get('mlp_num_layers').hyper_space = hyper_spaces.quniform(1, 5)\nreturn params",
"self.embeddinng = self._mak... | <|body_start_0|>
params = super().get_default_params(with_embedding=True, with_multi_layer_perceptron=True)
params['mlp_num_units'] = 256
params.get('mlp_num_units').hyper_space = hyper_spaces.quniform(16, 512)
params.get('mlp_num_layers').hyper_space = hyper_spaces.quniform(1, 5)
... | A simple densely connected baseline model. Examples: >>> model = DenseBaseline() >>> model.params['mlp_num_layers'] = 2 >>> model.params['mlp_num_units'] = 300 >>> model.params['mlp_num_fan_out'] = 128 >>> model.params['mlp_activation_func'] = 'relu' >>> model.guess_and_fill_missing_params(verbose=0) >>> model.build() | DenseBaseline | [
"MIT",
"LicenseRef-scancode-generic-cla",
"LicenseRef-scancode-proprietary-license",
"LicenseRef-scancode-free-unknown",
"LicenseRef-scancode-unknown-license-reference",
"LGPL-2.1-or-later",
"Apache-2.0",
"LicenseRef-scancode-public-domain",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DenseBaseline:
"""A simple densely connected baseline model. Examples: >>> model = DenseBaseline() >>> model.params['mlp_num_layers'] = 2 >>> model.params['mlp_num_units'] = 300 >>> model.params['mlp_num_fan_out'] = 128 >>> model.params['mlp_activation_func'] = 'relu' >>> model.guess_and_fill_mis... | stack_v2_sparse_classes_36k_train_002909 | 1,829 | permissive | [
{
"docstring": ":return: model default parameters.",
"name": "get_default_params",
"signature": "def get_default_params(cls) -> ParamTable"
},
{
"docstring": "Build.",
"name": "build",
"signature": "def build(self)"
},
{
"docstring": "Forward.",
"name": "forward",
"signat... | 3 | stack_v2_sparse_classes_30k_train_016861 | Implement the Python class `DenseBaseline` described below.
Class description:
A simple densely connected baseline model. Examples: >>> model = DenseBaseline() >>> model.params['mlp_num_layers'] = 2 >>> model.params['mlp_num_units'] = 300 >>> model.params['mlp_num_fan_out'] = 128 >>> model.params['mlp_activation_func'... | Implement the Python class `DenseBaseline` described below.
Class description:
A simple densely connected baseline model. Examples: >>> model = DenseBaseline() >>> model.params['mlp_num_layers'] = 2 >>> model.params['mlp_num_units'] = 300 >>> model.params['mlp_num_fan_out'] = 128 >>> model.params['mlp_activation_func'... | 4198ebce942f4afe7ddca6a96ab6f4464ade4518 | <|skeleton|>
class DenseBaseline:
"""A simple densely connected baseline model. Examples: >>> model = DenseBaseline() >>> model.params['mlp_num_layers'] = 2 >>> model.params['mlp_num_units'] = 300 >>> model.params['mlp_num_fan_out'] = 128 >>> model.params['mlp_activation_func'] = 'relu' >>> model.guess_and_fill_mis... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DenseBaseline:
"""A simple densely connected baseline model. Examples: >>> model = DenseBaseline() >>> model.params['mlp_num_layers'] = 2 >>> model.params['mlp_num_units'] = 300 >>> model.params['mlp_num_fan_out'] = 128 >>> model.params['mlp_activation_func'] = 'relu' >>> model.guess_and_fill_missing_params(v... | the_stack_v2_python_sparse | poset_decoding/traversal_path_prediction/MatchZoo-py/matchzoo/models/dense_baseline.py | microsoft/ContextualSP | train | 332 |
5559435aeacca1df61b99c1b032b3ac647dbea87 | [
"self._x = 123456789\nself._y = 362436069\nself._z = 521288629\nself._w = 88675123 ^ seed & 4294967295",
"t = (self._x ^ self._x << 11) & 4294967295\nself._x = self._y\nself._y = self._z\nself._z = self._w\nself._w = self._w ^ self._w >> 19 ^ (t ^ t >> 8)\nreturn self._w"
] | <|body_start_0|>
self._x = 123456789
self._y = 362436069
self._z = 521288629
self._w = 88675123 ^ seed & 4294967295
<|end_body_0|>
<|body_start_1|>
t = (self._x ^ self._x << 11) & 4294967295
self._x = self._y
self._y = self._z
self._z = self._w
se... | An XorShift pseudo-random number generator (PRNG) with period 2^128-1. Although Python supplies an easy-to-use :obj:`random` module, it does not necessarily ensure the reproducibility across different versions of Python. If reproducibility is the top priority in your application (e.g. bench- marks), you may consider us... | XorShift | [
"MIT",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class XorShift:
"""An XorShift pseudo-random number generator (PRNG) with period 2^128-1. Although Python supplies an easy-to-use :obj:`random` module, it does not necessarily ensure the reproducibility across different versions of Python. If reproducibility is the top priority in your application (e.g... | stack_v2_sparse_classes_36k_train_002910 | 3,359 | permissive | [
{
"docstring": "Initialize an XorShift PRNG with a seed. Args: seed (:obj:`int`): Seed for initialization. Note that only the lowest 32 bits in :obj:`seed` are used to seed this PRNG.",
"name": "__init__",
"signature": "def __init__(self, seed) -> None"
},
{
"docstring": "Return a random integer... | 2 | null | Implement the Python class `XorShift` described below.
Class description:
An XorShift pseudo-random number generator (PRNG) with period 2^128-1. Although Python supplies an easy-to-use :obj:`random` module, it does not necessarily ensure the reproducibility across different versions of Python. If reproducibility is th... | Implement the Python class `XorShift` described below.
Class description:
An XorShift pseudo-random number generator (PRNG) with period 2^128-1. Although Python supplies an easy-to-use :obj:`random` module, it does not necessarily ensure the reproducibility across different versions of Python. If reproducibility is th... | 710d953ebe8a181ff14a35daad80d56f6aa0fee8 | <|skeleton|>
class XorShift:
"""An XorShift pseudo-random number generator (PRNG) with period 2^128-1. Although Python supplies an easy-to-use :obj:`random` module, it does not necessarily ensure the reproducibility across different versions of Python. If reproducibility is the top priority in your application (e.g... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class XorShift:
"""An XorShift pseudo-random number generator (PRNG) with period 2^128-1. Although Python supplies an easy-to-use :obj:`random` module, it does not necessarily ensure the reproducibility across different versions of Python. If reproducibility is the top priority in your application (e.g. bench- mark... | the_stack_v2_python_sparse | cspuz/generator/deterministic_random.py | semiexp/cspuz | train | 20 |
20d42b7157317b34797d9b02e37422aed6a157b6 | [
"def _is_valid(act):\n return act.get('text', '') in quick_replies if quick_replies else True\nact = None\ncurr_time = time.time()\nallowed_timeout = timeout\nwhile act is None and time.time() - curr_time < allowed_timeout:\n act = agent.act()\n if act is not None and (not _is_valid(act)):\n agent.o... | <|body_start_0|>
def _is_valid(act):
return act.get('text', '') in quick_replies if quick_replies else True
act = None
curr_time = time.time()
allowed_timeout = timeout
while act is None and time.time() - curr_time < allowed_timeout:
act = agent.act()
... | Provide interface for getting an agent's act with timeout. | TimeoutUtils | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimeoutUtils:
"""Provide interface for getting an agent's act with timeout."""
def get_timeout_act(agent: Agent, timeout: int=DEFAULT_TIMEOUT, quick_replies: Optional[List[str]]=None) -> Optional[Message]:
"""Return an agent's act, with a specified timeout. :param agent: Agent who is... | stack_v2_sparse_classes_36k_train_002911 | 2,763 | permissive | [
{
"docstring": "Return an agent's act, with a specified timeout. :param agent: Agent who is acting :param timeout: how long to wait :param quick_replies: If given, agent's message *MUST* be one of the quick replies :return: An act dictionary if no timeout; else, None",
"name": "get_timeout_act",
"signat... | 2 | stack_v2_sparse_classes_30k_train_021525 | Implement the Python class `TimeoutUtils` described below.
Class description:
Provide interface for getting an agent's act with timeout.
Method signatures and docstrings:
- def get_timeout_act(agent: Agent, timeout: int=DEFAULT_TIMEOUT, quick_replies: Optional[List[str]]=None) -> Optional[Message]: Return an agent's ... | Implement the Python class `TimeoutUtils` described below.
Class description:
Provide interface for getting an agent's act with timeout.
Method signatures and docstrings:
- def get_timeout_act(agent: Agent, timeout: int=DEFAULT_TIMEOUT, quick_replies: Optional[List[str]]=None) -> Optional[Message]: Return an agent's ... | e1d899edfb92471552bae153f59ad30aa7fca468 | <|skeleton|>
class TimeoutUtils:
"""Provide interface for getting an agent's act with timeout."""
def get_timeout_act(agent: Agent, timeout: int=DEFAULT_TIMEOUT, quick_replies: Optional[List[str]]=None) -> Optional[Message]:
"""Return an agent's act, with a specified timeout. :param agent: Agent who is... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TimeoutUtils:
"""Provide interface for getting an agent's act with timeout."""
def get_timeout_act(agent: Agent, timeout: int=DEFAULT_TIMEOUT, quick_replies: Optional[List[str]]=None) -> Optional[Message]:
"""Return an agent's act, with a specified timeout. :param agent: Agent who is acting :para... | the_stack_v2_python_sparse | parlai/chat_service/utils/timeout.py | facebookresearch/ParlAI | train | 10,943 |
74516029ec1c00c14d4399a6f6de56f91eab217e | [
"if not type(ff) is FFSocket and (not type(ff) is FFCavPhSocket):\n raise TypeError('The type ' + type(ff).__name__ + ' is not a valid socket forcefield')\nsuper(InputFFSocket, self).store(ff)\nself.address.store(ff.socket.address)\nself.port.store(ff.socket.port)\nself.timeout.store(ff.socket.timeout)\nself.slo... | <|body_start_0|>
if not type(ff) is FFSocket and (not type(ff) is FFCavPhSocket):
raise TypeError('The type ' + type(ff).__name__ + ' is not a valid socket forcefield')
super(InputFFSocket, self).store(ff)
self.address.store(ff.socket.address)
self.port.store(ff.socket.port)
... | Creates a ForceField object with a socket interface. Handles generating one instance of a socket interface forcefield class. Attributes: mode: Describes whether the socket will be a unix or an internet socket. Fields: address: The server socket binding address. port: The port number for the socket. slots: The number of... | InputFFSocket | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InputFFSocket:
"""Creates a ForceField object with a socket interface. Handles generating one instance of a socket interface forcefield class. Attributes: mode: Describes whether the socket will be a unix or an internet socket. Fields: address: The server socket binding address. port: The port nu... | stack_v2_sparse_classes_36k_train_002912 | 33,115 | no_license | [
{
"docstring": "Takes a ForceField instance and stores a minimal representation of it. Args: ff: A ForceField object with a FFSocket forcemodel object.",
"name": "store",
"signature": "def store(self, ff)"
},
{
"docstring": "Creates a ForceSocket object. Returns: A ForceSocket object with the co... | 3 | null | Implement the Python class `InputFFSocket` described below.
Class description:
Creates a ForceField object with a socket interface. Handles generating one instance of a socket interface forcefield class. Attributes: mode: Describes whether the socket will be a unix or an internet socket. Fields: address: The server so... | Implement the Python class `InputFFSocket` described below.
Class description:
Creates a ForceField object with a socket interface. Handles generating one instance of a socket interface forcefield class. Attributes: mode: Describes whether the socket will be a unix or an internet socket. Fields: address: The server so... | 57f255266d4668bafef0881d1e7cbf8a27270ddd | <|skeleton|>
class InputFFSocket:
"""Creates a ForceField object with a socket interface. Handles generating one instance of a socket interface forcefield class. Attributes: mode: Describes whether the socket will be a unix or an internet socket. Fields: address: The server socket binding address. port: The port nu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InputFFSocket:
"""Creates a ForceField object with a socket interface. Handles generating one instance of a socket interface forcefield class. Attributes: mode: Describes whether the socket will be a unix or an internet socket. Fields: address: The server socket binding address. port: The port number for the ... | the_stack_v2_python_sparse | ipi/inputs/forcefields.py | i-pi/i-pi | train | 170 |
976402db022bf67f63dfed5157ba4f203c6a85e9 | [
"super().__init__(netatmo_device.data_handler)\nself.entity_description = description\nself._module = netatmo_device.device\nself._id = self._module.entity_id\nself._publishers.extend([{'name': HOME, 'home_id': netatmo_device.device.home.entity_id, SIGNAL_NAME: netatmo_device.signal_name}])\nself._attr_name = f'{se... | <|body_start_0|>
super().__init__(netatmo_device.data_handler)
self.entity_description = description
self._module = netatmo_device.device
self._id = self._module.entity_id
self._publishers.extend([{'name': HOME, 'home_id': netatmo_device.device.home.entity_id, SIGNAL_NAME: netatm... | Implementation of a Netatmo sensor. | NetatmoSensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NetatmoSensor:
"""Implementation of a Netatmo sensor."""
def __init__(self, netatmo_device: NetatmoDevice, description: NetatmoSensorEntityDescription) -> None:
"""Initialize the sensor."""
<|body_0|>
def async_update_callback(self) -> None:
"""Update the entity'... | stack_v2_sparse_classes_36k_train_002913 | 25,750 | permissive | [
{
"docstring": "Initialize the sensor.",
"name": "__init__",
"signature": "def __init__(self, netatmo_device: NetatmoDevice, description: NetatmoSensorEntityDescription) -> None"
},
{
"docstring": "Update the entity's state.",
"name": "async_update_callback",
"signature": "def async_upda... | 2 | null | Implement the Python class `NetatmoSensor` described below.
Class description:
Implementation of a Netatmo sensor.
Method signatures and docstrings:
- def __init__(self, netatmo_device: NetatmoDevice, description: NetatmoSensorEntityDescription) -> None: Initialize the sensor.
- def async_update_callback(self) -> Non... | Implement the Python class `NetatmoSensor` described below.
Class description:
Implementation of a Netatmo sensor.
Method signatures and docstrings:
- def __init__(self, netatmo_device: NetatmoDevice, description: NetatmoSensorEntityDescription) -> None: Initialize the sensor.
- def async_update_callback(self) -> Non... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class NetatmoSensor:
"""Implementation of a Netatmo sensor."""
def __init__(self, netatmo_device: NetatmoDevice, description: NetatmoSensorEntityDescription) -> None:
"""Initialize the sensor."""
<|body_0|>
def async_update_callback(self) -> None:
"""Update the entity'... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NetatmoSensor:
"""Implementation of a Netatmo sensor."""
def __init__(self, netatmo_device: NetatmoDevice, description: NetatmoSensorEntityDescription) -> None:
"""Initialize the sensor."""
super().__init__(netatmo_device.data_handler)
self.entity_description = description
... | the_stack_v2_python_sparse | homeassistant/components/netatmo/sensor.py | home-assistant/core | train | 35,501 |
f0fabbe17090ab9dc795fdec5de5dffd7d655622 | [
"from django.conf import settings\nif 'db_britpick_app' not in settings.DATABASES:\n return None\nif model._meta.app_label == 'britpick_app':\n return 'db_britpick_app'\nreturn None",
"from django.conf import settings\nif 'db_britpick_app' not in settings.DATABASES:\n return None\nif model._meta.app_labe... | <|body_start_0|>
from django.conf import settings
if 'db_britpick_app' not in settings.DATABASES:
return None
if model._meta.app_label == 'britpick_app':
return 'db_britpick_app'
return None
<|end_body_0|>
<|body_start_1|>
from django.conf import settings... | A router to control britpick_app db operations | BritpickAppDBRouter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BritpickAppDBRouter:
"""A router to control britpick_app db operations"""
def db_for_read(self, model, **hints):
"""Point all operations on britpick_app models to 'db_britpick_app'"""
<|body_0|>
def db_for_write(self, model, **hints):
"""Point all operations on b... | stack_v2_sparse_classes_36k_train_002914 | 1,641 | no_license | [
{
"docstring": "Point all operations on britpick_app models to 'db_britpick_app'",
"name": "db_for_read",
"signature": "def db_for_read(self, model, **hints)"
},
{
"docstring": "Point all operations on britpick_app models to 'db_britpick_app'",
"name": "db_for_write",
"signature": "def d... | 4 | stack_v2_sparse_classes_30k_train_021073 | Implement the Python class `BritpickAppDBRouter` described below.
Class description:
A router to control britpick_app db operations
Method signatures and docstrings:
- def db_for_read(self, model, **hints): Point all operations on britpick_app models to 'db_britpick_app'
- def db_for_write(self, model, **hints): Poin... | Implement the Python class `BritpickAppDBRouter` described below.
Class description:
A router to control britpick_app db operations
Method signatures and docstrings:
- def db_for_read(self, model, **hints): Point all operations on britpick_app models to 'db_britpick_app'
- def db_for_write(self, model, **hints): Poin... | f0608c8cb035b805196deaf14d61d7548f94470f | <|skeleton|>
class BritpickAppDBRouter:
"""A router to control britpick_app db operations"""
def db_for_read(self, model, **hints):
"""Point all operations on britpick_app models to 'db_britpick_app'"""
<|body_0|>
def db_for_write(self, model, **hints):
"""Point all operations on b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BritpickAppDBRouter:
"""A router to control britpick_app db operations"""
def db_for_read(self, model, **hints):
"""Point all operations on britpick_app models to 'db_britpick_app'"""
from django.conf import settings
if 'db_britpick_app' not in settings.DATABASES:
retu... | the_stack_v2_python_sparse | britpick_app/dbRouter.py | htw229/hazelsworks | train | 0 |
b89781535e16a88c7c85e626eb77d4c6d645ffc4 | [
"self.img1 = cv2.imread(path1)\nself.img2 = cv2.imread(path2)\nself.img1_g = cv2.cvtColor(self.img1, cv2.COLOR_BGR2GRAY)\nself.img2_g = cv2.cvtColor(self.img2, cv2.COLOR_BGR2GRAY)",
"detector = cv2.xfeatures2d.SIFT_create()\nself.kp1, self.f1 = detector.detectAndCompute(self.img1_g, None)\nself.kp2, self.f2 = det... | <|body_start_0|>
self.img1 = cv2.imread(path1)
self.img2 = cv2.imread(path2)
self.img1_g = cv2.cvtColor(self.img1, cv2.COLOR_BGR2GRAY)
self.img2_g = cv2.cvtColor(self.img2, cv2.COLOR_BGR2GRAY)
<|end_body_0|>
<|body_start_1|>
detector = cv2.xfeatures2d.SIFT_create()
self.... | Simple class to stitch two images together | MyStitcher | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyStitcher:
"""Simple class to stitch two images together"""
def __init__(self, path1, path2):
"""Load and store the the imags in path1 and path2"""
<|body_0|>
def detect_and_compute(self):
"""Detect and compute SIFT features for both images"""
<|body_1|>... | stack_v2_sparse_classes_36k_train_002915 | 2,053 | no_license | [
{
"docstring": "Load and store the the imags in path1 and path2",
"name": "__init__",
"signature": "def __init__(self, path1, path2)"
},
{
"docstring": "Detect and compute SIFT features for both images",
"name": "detect_and_compute",
"signature": "def detect_and_compute(self)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_001231 | Implement the Python class `MyStitcher` described below.
Class description:
Simple class to stitch two images together
Method signatures and docstrings:
- def __init__(self, path1, path2): Load and store the the imags in path1 and path2
- def detect_and_compute(self): Detect and compute SIFT features for both images
... | Implement the Python class `MyStitcher` described below.
Class description:
Simple class to stitch two images together
Method signatures and docstrings:
- def __init__(self, path1, path2): Load and store the the imags in path1 and path2
- def detect_and_compute(self): Detect and compute SIFT features for both images
... | ca8f934f3787144335f4b160e1a10c04fbe005a2 | <|skeleton|>
class MyStitcher:
"""Simple class to stitch two images together"""
def __init__(self, path1, path2):
"""Load and store the the imags in path1 and path2"""
<|body_0|>
def detect_and_compute(self):
"""Detect and compute SIFT features for both images"""
<|body_1|>... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyStitcher:
"""Simple class to stitch two images together"""
def __init__(self, path1, path2):
"""Load and store the the imags in path1 and path2"""
self.img1 = cv2.imread(path1)
self.img2 = cv2.imread(path2)
self.img1_g = cv2.cvtColor(self.img1, cv2.COLOR_BGR2GRAY)
... | the_stack_v2_python_sparse | Courses/understanding_Images_Sanja/solutions/A3/image_stitching.py | anassBelcaid/ComputerVision | train | 0 |
f44c78dfb5ff7dbc7f0ce6b906f916e804432361 | [
"self.name = name\nself.weight = weight\nself.total_weight += weight\nself.children = []\nself.vertices[name] = self",
"parent = edge.vertex1\nchild = edge.vertex2\nif child in self.vertices:\n if parent in self.vertices:\n raise ValueError('Edge links two nodes already in tree')\n parent, child = (c... | <|body_start_0|>
self.name = name
self.weight = weight
self.total_weight += weight
self.children = []
self.vertices[name] = self
<|end_body_0|>
<|body_start_1|>
parent = edge.vertex1
child = edge.vertex2
if child in self.vertices:
if parent in... | A representation of a spanning tree. | SpanningTree | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SpanningTree:
"""A representation of a spanning tree."""
def __init__(self, name, weight):
"""Creates a new SpanningTree node with no edges. Args: name: The name to assign to this node. May be a number or string. weight: Float, the weight between this node and its parent. Should be 0... | stack_v2_sparse_classes_36k_train_002916 | 6,794 | no_license | [
{
"docstring": "Creates a new SpanningTree node with no edges. Args: name: The name to assign to this node. May be a number or string. weight: Float, the weight between this node and its parent. Should be 0 for the root, or a positive number otherwise.",
"name": "__init__",
"signature": "def __init__(se... | 2 | stack_v2_sparse_classes_30k_train_008814 | Implement the Python class `SpanningTree` described below.
Class description:
A representation of a spanning tree.
Method signatures and docstrings:
- def __init__(self, name, weight): Creates a new SpanningTree node with no edges. Args: name: The name to assign to this node. May be a number or string. weight: Float,... | Implement the Python class `SpanningTree` described below.
Class description:
A representation of a spanning tree.
Method signatures and docstrings:
- def __init__(self, name, weight): Creates a new SpanningTree node with no edges. Args: name: The name to assign to this node. May be a number or string. weight: Float,... | bf622efcfad26f95696aa0bb72edb8fadfb2f717 | <|skeleton|>
class SpanningTree:
"""A representation of a spanning tree."""
def __init__(self, name, weight):
"""Creates a new SpanningTree node with no edges. Args: name: The name to assign to this node. May be a number or string. weight: Float, the weight between this node and its parent. Should be 0... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SpanningTree:
"""A representation of a spanning tree."""
def __init__(self, name, weight):
"""Creates a new SpanningTree node with no edges. Args: name: The name to assign to this node. May be a number or string. weight: Float, the weight between this node and its parent. Should be 0 for the root... | the_stack_v2_python_sparse | span/mst.py | mmweber2/adm | train | 3 |
d4bb66368c814069f1e2e2ef3abeec0904656b6d | [
"while SocketHandler.alive:\n filenos = list(SocketHandler.socket_map.keys())\n if filenos == []:\n time.sleep(0.001)\n continue\n for fileno in filenos:\n try:\n if not SocketHandler.socket_map[fileno].alive:\n del SocketHandler.socket_map[fileno]\n ex... | <|body_start_0|>
while SocketHandler.alive:
filenos = list(SocketHandler.socket_map.keys())
if filenos == []:
time.sleep(0.001)
continue
for fileno in filenos:
try:
if not SocketHandler.socket_map[fileno].ali... | Call select() for all sockets of Server and Peer instances created in currently executing program. | SocketHandler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SocketHandler:
"""Call select() for all sockets of Server and Peer instances created in currently executing program."""
def loop():
"""Infite loop calling select()."""
<|body_0|>
def handle_sockets(read, write, exc):
"""Call appropriate methods for sockets."""
... | stack_v2_sparse_classes_36k_train_002917 | 14,729 | no_license | [
{
"docstring": "Infite loop calling select().",
"name": "loop",
"signature": "def loop()"
},
{
"docstring": "Call appropriate methods for sockets.",
"name": "handle_sockets",
"signature": "def handle_sockets(read, write, exc)"
},
{
"docstring": "Stop loop().",
"name": "close"... | 3 | stack_v2_sparse_classes_30k_test_000701 | Implement the Python class `SocketHandler` described below.
Class description:
Call select() for all sockets of Server and Peer instances created in currently executing program.
Method signatures and docstrings:
- def loop(): Infite loop calling select().
- def handle_sockets(read, write, exc): Call appropriate metho... | Implement the Python class `SocketHandler` described below.
Class description:
Call select() for all sockets of Server and Peer instances created in currently executing program.
Method signatures and docstrings:
- def loop(): Infite loop calling select().
- def handle_sockets(read, write, exc): Call appropriate metho... | 7b19b0ec1b8f4ac1322487b7be71a1cd18480a42 | <|skeleton|>
class SocketHandler:
"""Call select() for all sockets of Server and Peer instances created in currently executing program."""
def loop():
"""Infite loop calling select()."""
<|body_0|>
def handle_sockets(read, write, exc):
"""Call appropriate methods for sockets."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SocketHandler:
"""Call select() for all sockets of Server and Peer instances created in currently executing program."""
def loop():
"""Infite loop calling select()."""
while SocketHandler.alive:
filenos = list(SocketHandler.socket_map.keys())
if filenos == []:
... | the_stack_v2_python_sparse | BitTorrent/core/network.py | melanholy/python-tasks | train | 0 |
754d3a0a02fb2655478b3d9efbbd2f17777ca101 | [
"self.access_zone_name = access_zone_name\nself.nfs_mount_point = nfs_mount_point\nself.path = path\nself.protocols = protocols\nself.smb_mount_points = smb_mount_points",
"if dictionary is None:\n return None\naccess_zone_name = dictionary.get('accessZoneName')\nnfs_mount_point = cohesity_management_sdk.model... | <|body_start_0|>
self.access_zone_name = access_zone_name
self.nfs_mount_point = nfs_mount_point
self.path = path
self.protocols = protocols
self.smb_mount_points = smb_mount_points
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
ac... | Implementation of the 'IsilonMountPoint' model. Specifies information about a mount point in an Isilon OneFs Cluster. Attributes: access_zone_name (string): Specifies the name of access zone. nfs_mount_point (IsilonNfsMountPoint): Specifies information about an NFS export. This field is set if the file system supports ... | IsilonMountPoint | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IsilonMountPoint:
"""Implementation of the 'IsilonMountPoint' model. Specifies information about a mount point in an Isilon OneFs Cluster. Attributes: access_zone_name (string): Specifies the name of access zone. nfs_mount_point (IsilonNfsMountPoint): Specifies information about an NFS export. Th... | stack_v2_sparse_classes_36k_train_002918 | 3,464 | permissive | [
{
"docstring": "Constructor for the IsilonMountPoint class",
"name": "__init__",
"signature": "def __init__(self, access_zone_name=None, nfs_mount_point=None, path=None, protocols=None, smb_mount_points=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionar... | 2 | stack_v2_sparse_classes_30k_train_008484 | Implement the Python class `IsilonMountPoint` described below.
Class description:
Implementation of the 'IsilonMountPoint' model. Specifies information about a mount point in an Isilon OneFs Cluster. Attributes: access_zone_name (string): Specifies the name of access zone. nfs_mount_point (IsilonNfsMountPoint): Specif... | Implement the Python class `IsilonMountPoint` described below.
Class description:
Implementation of the 'IsilonMountPoint' model. Specifies information about a mount point in an Isilon OneFs Cluster. Attributes: access_zone_name (string): Specifies the name of access zone. nfs_mount_point (IsilonNfsMountPoint): Specif... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class IsilonMountPoint:
"""Implementation of the 'IsilonMountPoint' model. Specifies information about a mount point in an Isilon OneFs Cluster. Attributes: access_zone_name (string): Specifies the name of access zone. nfs_mount_point (IsilonNfsMountPoint): Specifies information about an NFS export. Th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IsilonMountPoint:
"""Implementation of the 'IsilonMountPoint' model. Specifies information about a mount point in an Isilon OneFs Cluster. Attributes: access_zone_name (string): Specifies the name of access zone. nfs_mount_point (IsilonNfsMountPoint): Specifies information about an NFS export. This field is s... | the_stack_v2_python_sparse | cohesity_management_sdk/models/isilon_mount_point.py | cohesity/management-sdk-python | train | 24 |
48ee17016ff2aecac0be04500feafeb60d6e2294 | [
"location_report_query = LocationReport.query().filter(LocationReport.tags == self.key)\nlocation_reports = location_report_query.fetch()\nreturn location_reports",
"location_report_keys = self.location_reports\nlocation_report_names = []\nfor lrk in location_report_keys:\n location_report_names.append(lrk.get... | <|body_start_0|>
location_report_query = LocationReport.query().filter(LocationReport.tags == self.key)
location_reports = location_report_query.fetch()
return location_reports
<|end_body_0|>
<|body_start_1|>
location_report_keys = self.location_reports
location_report_names = [... | Unique | Tag | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Tag:
"""Unique"""
def location_reports(self):
"""returns keys for location reports associated with tag"""
<|body_0|>
def location_report_names(self):
"""returns list of location report names associated with tag"""
<|body_1|>
<|end_skeleton|>
<|body_star... | stack_v2_sparse_classes_36k_train_002919 | 1,827 | permissive | [
{
"docstring": "returns keys for location reports associated with tag",
"name": "location_reports",
"signature": "def location_reports(self)"
},
{
"docstring": "returns list of location report names associated with tag",
"name": "location_report_names",
"signature": "def location_report_... | 2 | stack_v2_sparse_classes_30k_train_016330 | Implement the Python class `Tag` described below.
Class description:
Unique
Method signatures and docstrings:
- def location_reports(self): returns keys for location reports associated with tag
- def location_report_names(self): returns list of location report names associated with tag | Implement the Python class `Tag` described below.
Class description:
Unique
Method signatures and docstrings:
- def location_reports(self): returns keys for location reports associated with tag
- def location_report_names(self): returns list of location report names associated with tag
<|skeleton|>
class Tag:
""... | a7c1b92521ec086644e2d7dc6a62f24a43a78d94 | <|skeleton|>
class Tag:
"""Unique"""
def location_reports(self):
"""returns keys for location reports associated with tag"""
<|body_0|>
def location_report_names(self):
"""returns list of location report names associated with tag"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Tag:
"""Unique"""
def location_reports(self):
"""returns keys for location reports associated with tag"""
location_report_query = LocationReport.query().filter(LocationReport.tags == self.key)
location_reports = location_report_query.fetch()
return location_reports
de... | the_stack_v2_python_sparse | models/models.py | anuja1011/Pick-Up-Sports | train | 0 |
9bae1fa633e3c92f65354aad69627d8ee4b18c33 | [
"parser = config_file.SshdConfigParser()\nresults = list(parser.ParseFile(None, None, io.BytesIO(CFG)))\nself.assertLen(results, 1)\nreturn results[0]",
"result = self.GetConfig()\nself.assertIsInstance(result, rdf_config_file.SshdConfig)\nself.assertCountEqual([2], result.config.protocol)\nexpect = ['aes128-ctr'... | <|body_start_0|>
parser = config_file.SshdConfigParser()
results = list(parser.ParseFile(None, None, io.BytesIO(CFG)))
self.assertLen(results, 1)
return results[0]
<|end_body_0|>
<|body_start_1|>
result = self.GetConfig()
self.assertIsInstance(result, rdf_config_file.Ssh... | Test parsing of an sshd configuration. | SshdConfigTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SshdConfigTest:
"""Test parsing of an sshd configuration."""
def GetConfig(self):
"""Read in the test configuration file."""
<|body_0|>
def testParseConfig(self):
"""Ensure we can extract sshd settings."""
<|body_1|>
def testFindNumericValues(self):
... | stack_v2_sparse_classes_36k_train_002920 | 28,097 | permissive | [
{
"docstring": "Read in the test configuration file.",
"name": "GetConfig",
"signature": "def GetConfig(self)"
},
{
"docstring": "Ensure we can extract sshd settings.",
"name": "testParseConfig",
"signature": "def testParseConfig(self)"
},
{
"docstring": "Keywords with numeric se... | 4 | stack_v2_sparse_classes_30k_train_002407 | Implement the Python class `SshdConfigTest` described below.
Class description:
Test parsing of an sshd configuration.
Method signatures and docstrings:
- def GetConfig(self): Read in the test configuration file.
- def testParseConfig(self): Ensure we can extract sshd settings.
- def testFindNumericValues(self): Keyw... | Implement the Python class `SshdConfigTest` described below.
Class description:
Test parsing of an sshd configuration.
Method signatures and docstrings:
- def GetConfig(self): Read in the test configuration file.
- def testParseConfig(self): Ensure we can extract sshd settings.
- def testFindNumericValues(self): Keyw... | 44c0eb8c938302098ef7efae8cfd6b90bcfbb2d6 | <|skeleton|>
class SshdConfigTest:
"""Test parsing of an sshd configuration."""
def GetConfig(self):
"""Read in the test configuration file."""
<|body_0|>
def testParseConfig(self):
"""Ensure we can extract sshd settings."""
<|body_1|>
def testFindNumericValues(self):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SshdConfigTest:
"""Test parsing of an sshd configuration."""
def GetConfig(self):
"""Read in the test configuration file."""
parser = config_file.SshdConfigParser()
results = list(parser.ParseFile(None, None, io.BytesIO(CFG)))
self.assertLen(results, 1)
return resu... | the_stack_v2_python_sparse | grr/core/grr_response_core/lib/parsers/config_file_test.py | google/grr | train | 4,683 |
af7701e084d96e61f35705798cf82747af601c85 | [
"n = len(nums) - 1\nleft, right = (1, n)\nwhile left < right:\n mid = left + (right - left) // 2\n count = 0\n for num in nums:\n if num <= mid:\n count += 1\n if count > mid:\n right = mid\n else:\n left = mid + 1\nreturn right",
"slow, fast = (nums[0], nums[nums[0]... | <|body_start_0|>
n = len(nums) - 1
left, right = (1, n)
while left < right:
mid = left + (right - left) // 2
count = 0
for num in nums:
if num <= mid:
count += 1
if count > mid:
right = mid
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findDuplicate1(self, nums: List[int]) -> int:
"""一般意义上，我们都在索引维度上（空间），在给定target的情况下去二分查找。 为什么能二分，是因为索引维度上数组有序。 本题是在数值维度上去二分查找 为什么能二分，是因为在数值维度上元素分布不均，存在二分条件（抽屉原理）。"""
<|body_0|>
def findDuplicate2(self, nums: List[int]) -> int:
"""快慢指针，比较难理解，参考142题解"""
... | stack_v2_sparse_classes_36k_train_002921 | 2,089 | no_license | [
{
"docstring": "一般意义上，我们都在索引维度上（空间），在给定target的情况下去二分查找。 为什么能二分，是因为索引维度上数组有序。 本题是在数值维度上去二分查找 为什么能二分，是因为在数值维度上元素分布不均，存在二分条件（抽屉原理）。",
"name": "findDuplicate1",
"signature": "def findDuplicate1(self, nums: List[int]) -> int"
},
{
"docstring": "快慢指针，比较难理解，参考142题解",
"name": "findDuplicate2",
"... | 2 | stack_v2_sparse_classes_30k_train_020961 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicate1(self, nums: List[int]) -> int: 一般意义上，我们都在索引维度上（空间），在给定target的情况下去二分查找。 为什么能二分，是因为索引维度上数组有序。 本题是在数值维度上去二分查找 为什么能二分，是因为在数值维度上元素分布不均，存在二分条件（抽屉原理）。
- def findDupli... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicate1(self, nums: List[int]) -> int: 一般意义上，我们都在索引维度上（空间），在给定target的情况下去二分查找。 为什么能二分，是因为索引维度上数组有序。 本题是在数值维度上去二分查找 为什么能二分，是因为在数值维度上元素分布不均，存在二分条件（抽屉原理）。
- def findDupli... | 2bbb1640589aab34f2bc42489283033cc11fb885 | <|skeleton|>
class Solution:
def findDuplicate1(self, nums: List[int]) -> int:
"""一般意义上，我们都在索引维度上（空间），在给定target的情况下去二分查找。 为什么能二分，是因为索引维度上数组有序。 本题是在数值维度上去二分查找 为什么能二分，是因为在数值维度上元素分布不均，存在二分条件（抽屉原理）。"""
<|body_0|>
def findDuplicate2(self, nums: List[int]) -> int:
"""快慢指针，比较难理解，参考142题解"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findDuplicate1(self, nums: List[int]) -> int:
"""一般意义上，我们都在索引维度上（空间），在给定target的情况下去二分查找。 为什么能二分，是因为索引维度上数组有序。 本题是在数值维度上去二分查找 为什么能二分，是因为在数值维度上元素分布不均，存在二分条件（抽屉原理）。"""
n = len(nums) - 1
left, right = (1, n)
while left < right:
mid = left + (right - left) ... | the_stack_v2_python_sparse | 287_find-the-duplicate-number.py | helloocc/algorithm | train | 1 | |
9a0a0d3ec27905246514210f4a7ab9d6fc043992 | [
"if not callable(condition):\n bad_type = type(condition)\n msg = f'Expected callable function for condition, got {bad_type}'\n raise TypeError(msg)\nself.condition = condition\nself.workflow = Workflow(workflow)",
"old_circuit = circuit.copy()\nold_data = data.copy()\nawait self.workflow.run(circuit, da... | <|body_start_0|>
if not callable(condition):
bad_type = type(condition)
msg = f'Expected callable function for condition, got {bad_type}'
raise TypeError(msg)
self.condition = condition
self.workflow = Workflow(workflow)
<|end_body_0|>
<|body_start_1|>
... | The DoThenDecide class. This is a control pass that executes a workflow and then conditionally accepts the resulting circuit or reverts to the original state. | DoThenDecide | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DoThenDecide:
"""The DoThenDecide class. This is a control pass that executes a workflow and then conditionally accepts the resulting circuit or reverts to the original state."""
def __init__(self, condition: Callable[[Circuit, Circuit], bool], workflow: WorkflowLike) -> None:
"""Con... | stack_v2_sparse_classes_36k_train_002922 | 2,346 | permissive | [
{
"docstring": "Construct a DoThenDecide. Args: condition (Callable[[Circuit, Circuit], bool]): The condition function that determines if the new circuit (second parameter) after running `workflow` should replace the original circuit (first parameter). If the condition returns True, then replace the original ci... | 2 | stack_v2_sparse_classes_30k_train_009631 | Implement the Python class `DoThenDecide` described below.
Class description:
The DoThenDecide class. This is a control pass that executes a workflow and then conditionally accepts the resulting circuit or reverts to the original state.
Method signatures and docstrings:
- def __init__(self, condition: Callable[[Circu... | Implement the Python class `DoThenDecide` described below.
Class description:
The DoThenDecide class. This is a control pass that executes a workflow and then conditionally accepts the resulting circuit or reverts to the original state.
Method signatures and docstrings:
- def __init__(self, condition: Callable[[Circu... | c89112d15072e8ffffb68cf1757b184e2aeb3dc8 | <|skeleton|>
class DoThenDecide:
"""The DoThenDecide class. This is a control pass that executes a workflow and then conditionally accepts the resulting circuit or reverts to the original state."""
def __init__(self, condition: Callable[[Circuit, Circuit], bool], workflow: WorkflowLike) -> None:
"""Con... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DoThenDecide:
"""The DoThenDecide class. This is a control pass that executes a workflow and then conditionally accepts the resulting circuit or reverts to the original state."""
def __init__(self, condition: Callable[[Circuit, Circuit], bool], workflow: WorkflowLike) -> None:
"""Construct a DoTh... | the_stack_v2_python_sparse | bqskit/passes/control/dothendecide.py | BQSKit/bqskit | train | 54 |
c947f0277a106e692da2ec18fa03cc0049c88267 | [
"self.output_filename = output_filename\nself.onet_source = onet_source\nself.hash_function = hash_function\nself.ksa_types = ksa_types or KSA_TYPE_CONFIG.keys()",
"logging.info('Converting ONET %s to pandas', filename)\nwith self.onet_source.ensure_file(filename) as fullpath:\n with open(fullpath) as f:\n ... | <|body_start_0|>
self.output_filename = output_filename
self.onet_source = onet_source
self.hash_function = hash_function
self.ksa_types = ksa_types or KSA_TYPE_CONFIG.keys()
<|end_body_0|>
<|body_start_1|>
logging.info('Converting ONET %s to pandas', filename)
with self... | An object that creates a skills CSV based on ONET data Originally written by Kwame Porter Robinson | OnetSkillListProcessor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OnetSkillListProcessor:
"""An object that creates a skills CSV based on ONET data Originally written by Kwame Porter Robinson"""
def __init__(self, onet_source, output_filename, hash_function, ksa_types=None):
"""Args: output_filename: A filename to write the final dataset onet_sourc... | stack_v2_sparse_classes_36k_train_002923 | 4,463 | permissive | [
{
"docstring": "Args: output_filename: A filename to write the final dataset onet_source: An object that is able to fetch ONET files by name hash_function: A function that can hash a given string ksa_types: A list of onet skill types to include. All strings must be keys in KSA_TYPE_CONFIG. Defaults to all keys ... | 3 | stack_v2_sparse_classes_30k_train_009425 | Implement the Python class `OnetSkillListProcessor` described below.
Class description:
An object that creates a skills CSV based on ONET data Originally written by Kwame Porter Robinson
Method signatures and docstrings:
- def __init__(self, onet_source, output_filename, hash_function, ksa_types=None): Args: output_f... | Implement the Python class `OnetSkillListProcessor` described below.
Class description:
An object that creates a skills CSV based on ONET data Originally written by Kwame Porter Robinson
Method signatures and docstrings:
- def __init__(self, onet_source, output_filename, hash_function, ksa_types=None): Args: output_f... | feffead90815ccdecf24bf1a995f79683442b046 | <|skeleton|>
class OnetSkillListProcessor:
"""An object that creates a skills CSV based on ONET data Originally written by Kwame Porter Robinson"""
def __init__(self, onet_source, output_filename, hash_function, ksa_types=None):
"""Args: output_filename: A filename to write the final dataset onet_sourc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OnetSkillListProcessor:
"""An object that creates a skills CSV based on ONET data Originally written by Kwame Porter Robinson"""
def __init__(self, onet_source, output_filename, hash_function, ksa_types=None):
"""Args: output_filename: A filename to write the final dataset onet_source: An object ... | the_stack_v2_python_sparse | skills_ml/datasets/skills/onet_ksat.py | workforce-data-initiative/skills-ml | train | 164 |
7678f4c421ff69dd93275c0a0215d12d27df056e | [
"if self.get_object().owner == self.request.user:\n return True\nreturn False",
"project = self.get_object()\ndelete_project(project)\nmessages.success(self.request, self.success_message)\nreturn HttpResponseRedirect(self.success_url)"
] | <|body_start_0|>
if self.get_object().owner == self.request.user:
return True
return False
<|end_body_0|>
<|body_start_1|>
project = self.get_object()
delete_project(project)
messages.success(self.request, self.success_message)
return HttpResponseRedirect(sel... | Delete a project. Only the project owner can delete the project. | ProjectDelete | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectDelete:
"""Delete a project. Only the project owner can delete the project."""
def has_permission(self):
"""Overrides method from PermissionRequiredMixin."""
<|body_0|>
def delete(self, request, *args, **kwargs):
"""Overrides method from DeleteView."""
... | stack_v2_sparse_classes_36k_train_002924 | 21,511 | permissive | [
{
"docstring": "Overrides method from PermissionRequiredMixin.",
"name": "has_permission",
"signature": "def has_permission(self)"
},
{
"docstring": "Overrides method from DeleteView.",
"name": "delete",
"signature": "def delete(self, request, *args, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_004415 | Implement the Python class `ProjectDelete` described below.
Class description:
Delete a project. Only the project owner can delete the project.
Method signatures and docstrings:
- def has_permission(self): Overrides method from PermissionRequiredMixin.
- def delete(self, request, *args, **kwargs): Overrides method fr... | Implement the Python class `ProjectDelete` described below.
Class description:
Delete a project. Only the project owner can delete the project.
Method signatures and docstrings:
- def has_permission(self): Overrides method from PermissionRequiredMixin.
- def delete(self, request, *args, **kwargs): Overrides method fr... | 598b3bc10b72b7b277510cf40e1a4bc56b07452a | <|skeleton|>
class ProjectDelete:
"""Delete a project. Only the project owner can delete the project."""
def has_permission(self):
"""Overrides method from PermissionRequiredMixin."""
<|body_0|>
def delete(self, request, *args, **kwargs):
"""Overrides method from DeleteView."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProjectDelete:
"""Delete a project. Only the project owner can delete the project."""
def has_permission(self):
"""Overrides method from PermissionRequiredMixin."""
if self.get_object().owner == self.request.user:
return True
return False
def delete(self, request,... | the_stack_v2_python_sparse | jenkins_auth/views.py | antony-wilson/jenkins_auth | train | 0 |
823f68d160608aa15c52a2bf3043785db3cc4e52 | [
"super(EncoderBlock, self).__init__()\nself.mha = MultiHeadAttention(dm, h)\nself.dense_hidden = tf.keras.layers.Dense(hidden, activation='relu')\nself.dense_output = tf.keras.layers.Dense(dm)\nself.layernorm1 = tf.keras.layers.LayerNormalization(epsilon=1e-06)\nself.layernorm2 = tf.keras.layers.LayerNormalization(... | <|body_start_0|>
super(EncoderBlock, self).__init__()
self.mha = MultiHeadAttention(dm, h)
self.dense_hidden = tf.keras.layers.Dense(hidden, activation='relu')
self.dense_output = tf.keras.layers.Dense(dm)
self.layernorm1 = tf.keras.layers.LayerNormalization(epsilon=1e-06)
... | class EncoderBlock | EncoderBlock | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncoderBlock:
"""class EncoderBlock"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""class constructor"""
<|body_0|>
def call(self, x, training, mask=None):
"""call function"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(EncoderBlo... | stack_v2_sparse_classes_36k_train_002925 | 1,207 | no_license | [
{
"docstring": "class constructor",
"name": "__init__",
"signature": "def __init__(self, dm, h, hidden, drop_rate=0.1)"
},
{
"docstring": "call function",
"name": "call",
"signature": "def call(self, x, training, mask=None)"
}
] | 2 | null | Implement the Python class `EncoderBlock` described below.
Class description:
class EncoderBlock
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1): class constructor
- def call(self, x, training, mask=None): call function | Implement the Python class `EncoderBlock` described below.
Class description:
class EncoderBlock
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1): class constructor
- def call(self, x, training, mask=None): call function
<|skeleton|>
class EncoderBlock:
"""class EncoderBlock""... | a49eb348ff994f35b0efbbd5ac3ac8ae8ccb57d2 | <|skeleton|>
class EncoderBlock:
"""class EncoderBlock"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""class constructor"""
<|body_0|>
def call(self, x, training, mask=None):
"""call function"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EncoderBlock:
"""class EncoderBlock"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""class constructor"""
super(EncoderBlock, self).__init__()
self.mha = MultiHeadAttention(dm, h)
self.dense_hidden = tf.keras.layers.Dense(hidden, activation='relu')
self.dens... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/7-transformer_encoder_block.py | salmenz/holbertonschool-machine_learning | train | 4 |
2662eab3094ce1b4b0db9369edac940ffe9ada52 | [
"self.controller = controller\nself.deserializer = deserializer or RequestDeserializer()\nself.serializer = serializer or ResponseSerializer()\nself._fault_body_function = fault_body_function",
"LOG.info('%(method)s %(url)s', {'method': request.method, 'url': request.url})\ntry:\n action, args, accept = self.d... | <|body_start_0|>
self.controller = controller
self.deserializer = deserializer or RequestDeserializer()
self.serializer = serializer or ResponseSerializer()
self._fault_body_function = fault_body_function
<|end_body_0|>
<|body_start_1|>
LOG.info('%(method)s %(url)s', {'method': ... | WSGI app that handles (de)serialization and controller dispatch. WSGI app that reads routing information supplied by RoutesMiddleware and calls the requested action method upon its controller. All controller action methods must accept a 'req' argument, which is the incoming wsgi.Request. If the operation is a PUT or PO... | Resource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Resource:
"""WSGI app that handles (de)serialization and controller dispatch. WSGI app that reads routing information supplied by RoutesMiddleware and calls the requested action method upon its controller. All controller action methods must accept a 'req' argument, which is the incoming wsgi.Requ... | stack_v2_sparse_classes_36k_train_002926 | 29,625 | permissive | [
{
"docstring": "Object initialization. :param controller: object that implement methods created by routes lib :param deserializer: object that can serialize the output of a controller into a webob response :param serializer: object that can deserialize a webob request into necessary pieces :param fault_body_fun... | 3 | stack_v2_sparse_classes_30k_val_000472 | Implement the Python class `Resource` described below.
Class description:
WSGI app that handles (de)serialization and controller dispatch. WSGI app that reads routing information supplied by RoutesMiddleware and calls the requested action method upon its controller. All controller action methods must accept a 'req' ar... | Implement the Python class `Resource` described below.
Class description:
WSGI app that handles (de)serialization and controller dispatch. WSGI app that reads routing information supplied by RoutesMiddleware and calls the requested action method upon its controller. All controller action methods must accept a 'req' ar... | dde31aae392b80341f6440eb38db1583563d7d1f | <|skeleton|>
class Resource:
"""WSGI app that handles (de)serialization and controller dispatch. WSGI app that reads routing information supplied by RoutesMiddleware and calls the requested action method upon its controller. All controller action methods must accept a 'req' argument, which is the incoming wsgi.Requ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Resource:
"""WSGI app that handles (de)serialization and controller dispatch. WSGI app that reads routing information supplied by RoutesMiddleware and calls the requested action method upon its controller. All controller action methods must accept a 'req' argument, which is the incoming wsgi.Request. If the o... | the_stack_v2_python_sparse | neutron/wsgi.py | openstack/neutron | train | 1,174 |
b830e3460892bf9fe1d1cb33d1dc7d10f857c14c | [
"Gridder.__init__(self, master=master, row=row, col=col, sticky=sticky)\nif numStatusCols is not None:\n numStatusCols = int(numStatusCols)\nself._numStatusCols = numStatusCols",
"basicArgs = self._basicKArgs(**kargs)\nbasicArgs.setdefault('numStatusCols', self._numStatusCols)\ngs = _StatusConfigGridSet(master... | <|body_start_0|>
Gridder.__init__(self, master=master, row=row, col=col, sticky=sticky)
if numStatusCols is not None:
numStatusCols = int(numStatusCols)
self._numStatusCols = numStatusCols
<|end_body_0|>
<|body_start_1|>
basicArgs = self._basicKArgs(**kargs)
basicArg... | StatusConfigGridder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StatusConfigGridder:
def __init__(self, master, row=0, col=0, sticky='e', numStatusCols=None):
"""Create an object that grids a set of status and configuration widgets. Inputs: - master Master widget into which to grid - row Starting row - col Starting column - sticky Default sticky sett... | stack_v2_sparse_classes_36k_train_002927 | 10,102 | no_license | [
{
"docstring": "Create an object that grids a set of status and configuration widgets. Inputs: - master Master widget into which to grid - row Starting row - col Starting column - sticky Default sticky setting for the status and config widgets - numStatusCols default number of columns for status widgets (includ... | 2 | stack_v2_sparse_classes_30k_train_013663 | Implement the Python class `StatusConfigGridder` described below.
Class description:
Implement the StatusConfigGridder class.
Method signatures and docstrings:
- def __init__(self, master, row=0, col=0, sticky='e', numStatusCols=None): Create an object that grids a set of status and configuration widgets. Inputs: - m... | Implement the Python class `StatusConfigGridder` described below.
Class description:
Implement the StatusConfigGridder class.
Method signatures and docstrings:
- def __init__(self, master, row=0, col=0, sticky='e', numStatusCols=None): Create an object that grids a set of status and configuration widgets. Inputs: - m... | fe5578ba978e8a9cd81c08be271c2ef874a84927 | <|skeleton|>
class StatusConfigGridder:
def __init__(self, master, row=0, col=0, sticky='e', numStatusCols=None):
"""Create an object that grids a set of status and configuration widgets. Inputs: - master Master widget into which to grid - row Starting row - col Starting column - sticky Default sticky sett... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StatusConfigGridder:
def __init__(self, master, row=0, col=0, sticky='e', numStatusCols=None):
"""Create an object that grids a set of status and configuration widgets. Inputs: - master Master widget into which to grid - row Starting row - col Starting column - sticky Default sticky setting for the st... | the_stack_v2_python_sparse | python/RO-3.6.9/Wdg/StatusConfigGridder.py | Subaru-PFS/tron_actorcore | train | 3 | |
c7645ca2b6483552dc3395a2abfce2562cfeb6df | [
"caller = auth.get_current_identity()\nif not caller.is_user:\n self.abort_with_error(400, text='Caller must use email-based auth')\nreturn caller.name",
"try:\n return self.send_response({'topic': pubsub.topic_name(), 'authorized': pubsub.is_authorized_subscriber(self.caller_email()), 'gs': {'auth_db_gs_pa... | <|body_start_0|>
caller = auth.get_current_identity()
if not caller.is_user:
self.abort_with_error(400, text='Caller must use email-based auth')
return caller.name
<|end_body_0|>
<|body_start_1|>
try:
return self.send_response({'topic': pubsub.topic_name(), 'auth... | Manages authorization to AuthDB PubSub topic and Google Storage object. Members of 'auth-trusted-services' group may use this endpoint to make sure they: 1. Can subscribe to AuthDB change notification PubSub topic. 2. Read Google Storage object that contains AuthDB dump. | AuthDBSubscriptionAuthHandler | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuthDBSubscriptionAuthHandler:
"""Manages authorization to AuthDB PubSub topic and Google Storage object. Members of 'auth-trusted-services' group may use this endpoint to make sure they: 1. Can subscribe to AuthDB change notification PubSub topic. 2. Read Google Storage object that contains Auth... | stack_v2_sparse_classes_36k_train_002928 | 16,263 | permissive | [
{
"docstring": "Validates caller is using email for auth, returns it. Raises HTTP 400 if some other kind of authentication is used.",
"name": "caller_email",
"signature": "def caller_email(self)"
},
{
"docstring": "Queries whether the caller is authorized to access AuthDB already. Response body:... | 4 | null | Implement the Python class `AuthDBSubscriptionAuthHandler` described below.
Class description:
Manages authorization to AuthDB PubSub topic and Google Storage object. Members of 'auth-trusted-services' group may use this endpoint to make sure they: 1. Can subscribe to AuthDB change notification PubSub topic. 2. Read G... | Implement the Python class `AuthDBSubscriptionAuthHandler` described below.
Class description:
Manages authorization to AuthDB PubSub topic and Google Storage object. Members of 'auth-trusted-services' group may use this endpoint to make sure they: 1. Can subscribe to AuthDB change notification PubSub topic. 2. Read G... | 10cc5fdcca53e2a1690867acbe6fce099273f092 | <|skeleton|>
class AuthDBSubscriptionAuthHandler:
"""Manages authorization to AuthDB PubSub topic and Google Storage object. Members of 'auth-trusted-services' group may use this endpoint to make sure they: 1. Can subscribe to AuthDB change notification PubSub topic. 2. Read Google Storage object that contains Auth... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AuthDBSubscriptionAuthHandler:
"""Manages authorization to AuthDB PubSub topic and Google Storage object. Members of 'auth-trusted-services' group may use this endpoint to make sure they: 1. Can subscribe to AuthDB change notification PubSub topic. 2. Read Google Storage object that contains AuthDB dump."""
... | the_stack_v2_python_sparse | appengine/auth_service/handlers_frontend.py | luci/luci-py | train | 84 |
9f53640abd3d57af76b055223b2130a284e044a2 | [
"self.element = element\nself.need_update = need_update\nself.callout = None",
"points = self._get_up_down_points(offset)\nself.callout = MyView.create_callout(view.Id, view.GetTypeId(), *points)\nif self.need_update:\n self._update(symbol_point=points, rotated=rotated)\nif template_view:\n self.callout.App... | <|body_start_0|>
self.element = element
self.need_update = need_update
self.callout = None
<|end_body_0|>
<|body_start_1|>
points = self._get_up_down_points(offset)
self.callout = MyView.create_callout(view.Id, view.GetTypeId(), *points)
if self.need_update:
... | MetaClass for Callout. Need overrides: - _calc_origin_and_orientation - _get_symbol_points _need_update determines whether to rotate and crop | MyCalloutCreator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyCalloutCreator:
"""MetaClass for Callout. Need overrides: - _calc_origin_and_orientation - _get_symbol_points _need_update determines whether to rotate and crop"""
def __init__(self, element, need_update=True):
"""Initialization of instance :param element: :type element: MyElementG... | stack_v2_sparse_classes_36k_train_002929 | 2,951 | permissive | [
{
"docstring": "Initialization of instance :param element: :type element: MyElementGeom",
"name": "__init__",
"signature": "def __init__(self, element, need_update=True)"
},
{
"docstring": "Create callout on given view, offset and rotate if it needed :param view: view on which the callout will b... | 5 | stack_v2_sparse_classes_30k_train_008169 | Implement the Python class `MyCalloutCreator` described below.
Class description:
MetaClass for Callout. Need overrides: - _calc_origin_and_orientation - _get_symbol_points _need_update determines whether to rotate and crop
Method signatures and docstrings:
- def __init__(self, element, need_update=True): Initializat... | Implement the Python class `MyCalloutCreator` described below.
Class description:
MetaClass for Callout. Need overrides: - _calc_origin_and_orientation - _get_symbol_points _need_update determines whether to rotate and crop
Method signatures and docstrings:
- def __init__(self, element, need_update=True): Initializat... | c4ea77428111d186fab55501243ad4319376482b | <|skeleton|>
class MyCalloutCreator:
"""MetaClass for Callout. Need overrides: - _calc_origin_and_orientation - _get_symbol_points _need_update determines whether to rotate and crop"""
def __init__(self, element, need_update=True):
"""Initialization of instance :param element: :type element: MyElementG... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyCalloutCreator:
"""MetaClass for Callout. Need overrides: - _calc_origin_and_orientation - _get_symbol_points _need_update determines whether to rotate and crop"""
def __init__(self, element, need_update=True):
"""Initialization of instance :param element: :type element: MyElementGeom"""
... | the_stack_v2_python_sparse | scripts/my_class/my_callout.py | appolimp/Dynamo_scripts | train | 1 |
efca7c33e0d874a48280ab7284dfeecce280622c | [
"self.dim = dim\nself.scale = scale\nself.density = density\nself.width = dim[0] // scale\nself.height = dim[1] // scale\nself.surface = pygame.Surface(dim)\nself.cells = [[0 for x in range(self.width)] for y in range(self.height)]\nfor i in range(self.width * self.height // density):\n x = random.randint(1, sel... | <|body_start_0|>
self.dim = dim
self.scale = scale
self.density = density
self.width = dim[0] // scale
self.height = dim[1] // scale
self.surface = pygame.Surface(dim)
self.cells = [[0 for x in range(self.width)] for y in range(self.height)]
for i in range... | simple Cellular Automata - Conways Game of Life | GameOfLife | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GameOfLife:
"""simple Cellular Automata - Conways Game of Life"""
def __init__(self, dim: tuple, scale=2, density=15):
""":param dim: dimension of surface to draw on :param ruleset: ruleset to use"""
<|body_0|>
def update(self) -> pygame.Surface:
"""every frame a... | stack_v2_sparse_classes_36k_train_002930 | 2,813 | no_license | [
{
"docstring": ":param dim: dimension of surface to draw on :param ruleset: ruleset to use",
"name": "__init__",
"signature": "def __init__(self, dim: tuple, scale=2, density=15)"
},
{
"docstring": "every frame a new generation",
"name": "update",
"signature": "def update(self) -> pygame... | 2 | stack_v2_sparse_classes_30k_train_019784 | Implement the Python class `GameOfLife` described below.
Class description:
simple Cellular Automata - Conways Game of Life
Method signatures and docstrings:
- def __init__(self, dim: tuple, scale=2, density=15): :param dim: dimension of surface to draw on :param ruleset: ruleset to use
- def update(self) -> pygame.S... | Implement the Python class `GameOfLife` described below.
Class description:
simple Cellular Automata - Conways Game of Life
Method signatures and docstrings:
- def __init__(self, dim: tuple, scale=2, density=15): :param dim: dimension of surface to draw on :param ruleset: ruleset to use
- def update(self) -> pygame.S... | 1fd421195a2888c0588a49f5a043a1110eedcdbf | <|skeleton|>
class GameOfLife:
"""simple Cellular Automata - Conways Game of Life"""
def __init__(self, dim: tuple, scale=2, density=15):
""":param dim: dimension of surface to draw on :param ruleset: ruleset to use"""
<|body_0|>
def update(self) -> pygame.Surface:
"""every frame a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GameOfLife:
"""simple Cellular Automata - Conways Game of Life"""
def __init__(self, dim: tuple, scale=2, density=15):
""":param dim: dimension of surface to draw on :param ruleset: ruleset to use"""
self.dim = dim
self.scale = scale
self.density = density
self.wid... | the_stack_v2_python_sparse | effects/GameOfLife.py | gunny26/pygame | train | 5 |
8d2d7c499358b08cea4fd4c350bead222a568644 | [
"if type(data) is not np.ndarray:\n raise TypeError('data must be a 2D numpy.ndarray')\nif len(data.shape) != 2:\n raise TypeError('data must be a 2D numpy.ndarray')\nif data.shape[1] < 2:\n raise ValueError('data must contain multiple data points')\nd, n = data.shape\nself.mean = np.mean(data, axis=1).res... | <|body_start_0|>
if type(data) is not np.ndarray:
raise TypeError('data must be a 2D numpy.ndarray')
if len(data.shape) != 2:
raise TypeError('data must be a 2D numpy.ndarray')
if data.shape[1] < 2:
raise ValueError('data must contain multiple data points')
... | Multinormal class that represents a Multivariate Normal distribution | MultiNormal | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiNormal:
"""Multinormal class that represents a Multivariate Normal distribution"""
def __init__(self, data):
"""Init method data is a numpy.ndarray of shape (d, n) containing the data set: n is the number of data points d is the number of dimensions in each data point If data is... | stack_v2_sparse_classes_36k_train_002931 | 2,602 | no_license | [
{
"docstring": "Init method data is a numpy.ndarray of shape (d, n) containing the data set: n is the number of data points d is the number of dimensions in each data point If data is not a 2D numpy.ndarray, raise a TypeError with the message data must be a 2D numpy.ndarray If n is less than 2, raise a ValueErr... | 2 | stack_v2_sparse_classes_30k_train_010027 | Implement the Python class `MultiNormal` described below.
Class description:
Multinormal class that represents a Multivariate Normal distribution
Method signatures and docstrings:
- def __init__(self, data): Init method data is a numpy.ndarray of shape (d, n) containing the data set: n is the number of data points d ... | Implement the Python class `MultiNormal` described below.
Class description:
Multinormal class that represents a Multivariate Normal distribution
Method signatures and docstrings:
- def __init__(self, data): Init method data is a numpy.ndarray of shape (d, n) containing the data set: n is the number of data points d ... | e8a98d85b3bfd5665cb04bec9ee8c3eb23d6bd58 | <|skeleton|>
class MultiNormal:
"""Multinormal class that represents a Multivariate Normal distribution"""
def __init__(self, data):
"""Init method data is a numpy.ndarray of shape (d, n) containing the data set: n is the number of data points d is the number of dimensions in each data point If data is... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiNormal:
"""Multinormal class that represents a Multivariate Normal distribution"""
def __init__(self, data):
"""Init method data is a numpy.ndarray of shape (d, n) containing the data set: n is the number of data points d is the number of dimensions in each data point If data is not a 2D num... | the_stack_v2_python_sparse | math/0x06-multivariate_prob/multinormal.py | AndrewMiranda/holbertonschool-machine_learning-1 | train | 0 |
0274e7d795b46e40021b4930afbaf1b7a419833a | [
"url = 'http://www.zhichiwangluo.com/management/marketing/distribution/distribution-rule-management/distribution-rule-management-rule?id=EQBYDcBill'\nself.driver.get(url)\nif self.isDispalyed(self.loc12) == True:\n self.click(self.loc12)\nself.click(self.loc1)\nself.clear(self.loc2)\nself.sendKyes(self.loc2, fir... | <|body_start_0|>
url = 'http://www.zhichiwangluo.com/management/marketing/distribution/distribution-rule-management/distribution-rule-management-rule?id=EQBYDcBill'
self.driver.get(url)
if self.isDispalyed(self.loc12) == True:
self.click(self.loc12)
self.click(self.loc1)
... | 分销 | Distribuiton | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Distribuiton:
"""分销"""
def distributionRule(self, first_Commission, second_Commission):
"""分销规则设置"""
<|body_0|>
def is_distrition_rule_sucess(self, _text):
"""是否添加成功"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
url = 'http://www.zhichiwangluo... | stack_v2_sparse_classes_36k_train_002932 | 4,645 | no_license | [
{
"docstring": "分销规则设置",
"name": "distributionRule",
"signature": "def distributionRule(self, first_Commission, second_Commission)"
},
{
"docstring": "是否添加成功",
"name": "is_distrition_rule_sucess",
"signature": "def is_distrition_rule_sucess(self, _text)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017184 | Implement the Python class `Distribuiton` described below.
Class description:
分销
Method signatures and docstrings:
- def distributionRule(self, first_Commission, second_Commission): 分销规则设置
- def is_distrition_rule_sucess(self, _text): 是否添加成功 | Implement the Python class `Distribuiton` described below.
Class description:
分销
Method signatures and docstrings:
- def distributionRule(self, first_Commission, second_Commission): 分销规则设置
- def is_distrition_rule_sucess(self, _text): 是否添加成功
<|skeleton|>
class Distribuiton:
"""分销"""
def distributionRule(sel... | 3b441375fade9ebff025054cedee107217fa2e98 | <|skeleton|>
class Distribuiton:
"""分销"""
def distributionRule(self, first_Commission, second_Commission):
"""分销规则设置"""
<|body_0|>
def is_distrition_rule_sucess(self, _text):
"""是否添加成功"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Distribuiton:
"""分销"""
def distributionRule(self, first_Commission, second_Commission):
"""分销规则设置"""
url = 'http://www.zhichiwangluo.com/management/marketing/distribution/distribution-rule-management/distribution-rule-management-rule?id=EQBYDcBill'
self.driver.get(url)
if ... | the_stack_v2_python_sparse | pages/distribution.py | srf123/zhichi | train | 0 |
749b586b896d2236c4ef6c81750399b137c37347 | [
"super(RBPDecisionMaker, self).__init__(search_context, logger)\nself.__patience = patience\nself.__random = Random()\nself.__random.seed(base_seed + 1024)",
"rank = self._search_context.get_current_serp_position()\nrbp_score = self.__patience ** (rank - 1)\ndp = self.__random.random()\nif dp > rbp_score:\n re... | <|body_start_0|>
super(RBPDecisionMaker, self).__init__(search_context, logger)
self.__patience = patience
self.__random = Random()
self.__random.seed(base_seed + 1024)
<|end_body_0|>
<|body_start_1|>
rank = self._search_context.get_current_serp_position()
rbp_score = se... | An implementation of Rank-Biased Precision, operationalised as a stopping strategy. Uses a stochastic roll of the dice to determine if a searcher continues or not. Implemented as per Moffat and Zobel (2008). | RBPDecisionMaker | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RBPDecisionMaker:
"""An implementation of Rank-Biased Precision, operationalised as a stopping strategy. Uses a stochastic roll of the dice to determine if a searcher continues or not. Implemented as per Moffat and Zobel (2008)."""
def __init__(self, search_context, logger, patience=0.5, bas... | stack_v2_sparse_classes_36k_train_002933 | 1,377 | permissive | [
{
"docstring": "Instantiates the decision maker, with a patience factor (defaulting to 0.5). The patience factor of RBP determines how patient a searcher is. The closer to 1.0, the deeper the searcher will go.",
"name": "__init__",
"signature": "def __init__(self, search_context, logger, patience=0.5, b... | 2 | stack_v2_sparse_classes_30k_train_001405 | Implement the Python class `RBPDecisionMaker` described below.
Class description:
An implementation of Rank-Biased Precision, operationalised as a stopping strategy. Uses a stochastic roll of the dice to determine if a searcher continues or not. Implemented as per Moffat and Zobel (2008).
Method signatures and docstr... | Implement the Python class `RBPDecisionMaker` described below.
Class description:
An implementation of Rank-Biased Precision, operationalised as a stopping strategy. Uses a stochastic roll of the dice to determine if a searcher continues or not. Implemented as per Moffat and Zobel (2008).
Method signatures and docstr... | c6f5b48cc9916c29f109d5ef74876ff8c073a44c | <|skeleton|>
class RBPDecisionMaker:
"""An implementation of Rank-Biased Precision, operationalised as a stopping strategy. Uses a stochastic roll of the dice to determine if a searcher continues or not. Implemented as per Moffat and Zobel (2008)."""
def __init__(self, search_context, logger, patience=0.5, bas... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RBPDecisionMaker:
"""An implementation of Rank-Biased Precision, operationalised as a stopping strategy. Uses a stochastic roll of the dice to determine if a searcher continues or not. Implemented as per Moffat and Zobel (2008)."""
def __init__(self, search_context, logger, patience=0.5, base_seed=0):
... | the_stack_v2_python_sparse | simiir/stopping_decision_makers/rbp_decision_maker.py | ArthurCamara/simiir | train | 0 |
b726738dee9448c668c8883b3c63d0cb11912bd1 | [
"super().__init__()\nself.capacity = capacity\nself.cache = OrderedDict()",
"value = self.cache.pop(key)\nself.cache[key] = value\nreturn value",
"try:\n self.cache.pop(key)\nexcept KeyError:\n if len(self.cache) >= self.capacity:\n self.cache.popitem(last=False)\nself.cache[key] = value"
] | <|body_start_0|>
super().__init__()
self.capacity = capacity
self.cache = OrderedDict()
<|end_body_0|>
<|body_start_1|>
value = self.cache.pop(key)
self.cache[key] = value
return value
<|end_body_1|>
<|body_start_2|>
try:
self.cache.pop(key)
... | LRUCache | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity: int=512):
""":param capacity: The Maximum number of key-value pairs can be cached."""
<|body_0|>
def get(self, key: str) -> Any:
"""Look up the value in cache using the associated key. Returns the value if found. Raises :class:`... | stack_v2_sparse_classes_36k_train_002934 | 1,314 | permissive | [
{
"docstring": ":param capacity: The Maximum number of key-value pairs can be cached.",
"name": "__init__",
"signature": "def __init__(self, capacity: int=512)"
},
{
"docstring": "Look up the value in cache using the associated key. Returns the value if found. Raises :class:`KeyError` otherwise.... | 3 | null | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity: int=512): :param capacity: The Maximum number of key-value pairs can be cached.
- def get(self, key: str) -> Any: Look up the value in cache using th... | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity: int=512): :param capacity: The Maximum number of key-value pairs can be cached.
- def get(self, key: str) -> Any: Look up the value in cache using th... | 4f11d7596488194fc740936fe987f42864003d41 | <|skeleton|>
class LRUCache:
def __init__(self, capacity: int=512):
""":param capacity: The Maximum number of key-value pairs can be cached."""
<|body_0|>
def get(self, key: str) -> Any:
"""Look up the value in cache using the associated key. Returns the value if found. Raises :class:`... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LRUCache:
def __init__(self, capacity: int=512):
""":param capacity: The Maximum number of key-value pairs can be cached."""
super().__init__()
self.capacity = capacity
self.cache = OrderedDict()
def get(self, key: str) -> Any:
"""Look up the value in cache using t... | the_stack_v2_python_sparse | boxsdk/util/lru_cache.py | box/box-python-sdk | train | 424 | |
a16a8cedc3c3950bffc511a7f213b8715110bf6b | [
"if not strs:\n return ''\noutput = []\nfor s in strs:\n if not s:\n output.append('e')\n continue\n line = []\n for c in s:\n line.append(str(ord(c)))\n output.append('|'.join(line))\nreturn '*'.join(output)",
"if not s:\n return []\noutput = []\nfor line in s.split('*'):\n... | <|body_start_0|>
if not strs:
return ''
output = []
for s in strs:
if not s:
output.append('e')
continue
line = []
for c in s:
line.append(str(ord(c)))
output.append('|'.join(line))
... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def encode(self, strs):
"""Encodes a list of strings to a single string. :type strs: List[str] :rtype: str"""
<|body_0|>
def decode(self, s):
"""Decodes a single string to a list of strings. :type s: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k_train_002935 | 1,352 | no_license | [
{
"docstring": "Encodes a list of strings to a single string. :type strs: List[str] :rtype: str",
"name": "encode",
"signature": "def encode(self, strs)"
},
{
"docstring": "Decodes a single string to a list of strings. :type s: str :rtype: List[str]",
"name": "decode",
"signature": "def ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs): Encodes a list of strings to a single string. :type strs: List[str] :rtype: str
- def decode(self, s): Decodes a single string to a list of strings. :type s: st... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def encode(self, strs): Encodes a list of strings to a single string. :type strs: List[str] :rtype: str
- def decode(self, s): Decodes a single string to a list of strings. :type s: st... | ccc3d86000367f809fe34a1b000ec8bbe0506a36 | <|skeleton|>
class Codec:
def encode(self, strs):
"""Encodes a list of strings to a single string. :type strs: List[str] :rtype: str"""
<|body_0|>
def decode(self, s):
"""Decodes a single string to a list of strings. :type s: str :rtype: List[str]"""
<|body_1|>
<|end_skeleton|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def encode(self, strs):
"""Encodes a list of strings to a single string. :type strs: List[str] :rtype: str"""
if not strs:
return ''
output = []
for s in strs:
if not s:
output.append('e')
continue
line ... | the_stack_v2_python_sparse | strings/codecstring.py | AdsophicSolutions/freecodecamp | train | 1 | |
92d64889fbd888a966aa6ba04dddd59272162435 | [
"if plan is None:\n plan = self.migration_plan(targets)\nfull_plan = self.migration_plan(self.loader.graph.leaf_nodes(), clean_start=True)\nstate = self._migrate_all_forwards(plan, full_plan, fake=fake, fake_initial=fake_initial)\nself.check_replacements()\nreturn state",
"migrations_to_run = {m[0] for m in pl... | <|body_start_0|>
if plan is None:
plan = self.migration_plan(targets)
full_plan = self.migration_plan(self.loader.graph.leaf_nodes(), clean_start=True)
state = self._migrate_all_forwards(plan, full_plan, fake=fake, fake_initial=fake_initial)
self.check_replacements()
... | BackupMigrationExecutor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BackupMigrationExecutor:
def migrate(self, targets, plan=None, fake=False, fake_initial=False):
"""Migrates the database up to the given targets. Django first needs to create all project states before a migration is (un)applied and in a second step run all the database operations."""
... | stack_v2_sparse_classes_36k_train_002936 | 2,168 | no_license | [
{
"docstring": "Migrates the database up to the given targets. Django first needs to create all project states before a migration is (un)applied and in a second step run all the database operations.",
"name": "migrate",
"signature": "def migrate(self, targets, plan=None, fake=False, fake_initial=False)"... | 2 | stack_v2_sparse_classes_30k_train_020480 | Implement the Python class `BackupMigrationExecutor` described below.
Class description:
Implement the BackupMigrationExecutor class.
Method signatures and docstrings:
- def migrate(self, targets, plan=None, fake=False, fake_initial=False): Migrates the database up to the given targets. Django first needs to create a... | Implement the Python class `BackupMigrationExecutor` described below.
Class description:
Implement the BackupMigrationExecutor class.
Method signatures and docstrings:
- def migrate(self, targets, plan=None, fake=False, fake_initial=False): Migrates the database up to the given targets. Django first needs to create a... | 879111874d1ef70418b4890cf970720b0a2be4d8 | <|skeleton|>
class BackupMigrationExecutor:
def migrate(self, targets, plan=None, fake=False, fake_initial=False):
"""Migrates the database up to the given targets. Django first needs to create all project states before a migration is (un)applied and in a second step run all the database operations."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BackupMigrationExecutor:
def migrate(self, targets, plan=None, fake=False, fake_initial=False):
"""Migrates the database up to the given targets. Django first needs to create all project states before a migration is (un)applied and in a second step run all the database operations."""
if plan i... | the_stack_v2_python_sparse | apps/backups/executor.py | faierbol/syncano-platform | train | 0 | |
31a76b940b47708ebb4677bb82eae177799cca71 | [
"cb = EarlyStopping(2, tolerance=-10)\n'when training is not improveing'\nwith DF_AB_10.model() as m:\n m.fit(SkModel(MLPRegressor([1, 2, 1]), FeaturesAndLabels(['a'], ['b'])), FittingParameter(epochs=50), verbose=1, callbacks=cb)\n'then not all epochs were executed'\nself.assertLess(cb.call_counter, 50)\nself.a... | <|body_start_0|>
cb = EarlyStopping(2, tolerance=-10)
'when training is not improveing'
with DF_AB_10.model() as m:
m.fit(SkModel(MLPRegressor([1, 2, 1]), FeaturesAndLabels(['a'], ['b'])), FittingParameter(epochs=50), verbose=1, callbacks=cb)
'then not all epochs were execute... | TestCallBack | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestCallBack:
def test_early_stopping(self):
"""given an early stopping callback"""
<|body_0|>
def test_confidence(self):
"""given a confidence interval test callback"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
cb = EarlyStopping(2, tolerance=-1... | stack_v2_sparse_classes_36k_train_002937 | 1,962 | permissive | [
{
"docstring": "given an early stopping callback",
"name": "test_early_stopping",
"signature": "def test_early_stopping(self)"
},
{
"docstring": "given a confidence interval test callback",
"name": "test_confidence",
"signature": "def test_confidence(self)"
}
] | 2 | null | Implement the Python class `TestCallBack` described below.
Class description:
Implement the TestCallBack class.
Method signatures and docstrings:
- def test_early_stopping(self): given an early stopping callback
- def test_confidence(self): given a confidence interval test callback | Implement the Python class `TestCallBack` described below.
Class description:
Implement the TestCallBack class.
Method signatures and docstrings:
- def test_early_stopping(self): given an early stopping callback
- def test_confidence(self): given a confidence interval test callback
<|skeleton|>
class TestCallBack:
... | 650a8e8f77bc4d71136518d1c7ee65c194a99cf0 | <|skeleton|>
class TestCallBack:
def test_early_stopping(self):
"""given an early stopping callback"""
<|body_0|>
def test_confidence(self):
"""given a confidence interval test callback"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestCallBack:
def test_early_stopping(self):
"""given an early stopping callback"""
cb = EarlyStopping(2, tolerance=-10)
'when training is not improveing'
with DF_AB_10.model() as m:
m.fit(SkModel(MLPRegressor([1, 2, 1]), FeaturesAndLabels(['a'], ['b'])), FittingPar... | the_stack_v2_python_sparse | pandas-ml-utils/pandas_ml_utils_test/ml/model/test_callback.py | jcoffi/pandas-ml-quant | train | 0 | |
5f0ff1eaf11698158d404e3a5d1565c841b9709f | [
"result = []\nfor i in range(len(nums)):\n current = nums[i]\n two_sum = self.twoSum_for_3sum(nums, 0 - current, i)\n if two_sum:\n for ts in two_sum:\n ans = sorted([current] + ts)\n if ans not in result:\n result.append(ans)\nreturn sorted(result)",
"result =... | <|body_start_0|>
result = []
for i in range(len(nums)):
current = nums[i]
two_sum = self.twoSum_for_3sum(nums, 0 - current, i)
if two_sum:
for ts in two_sum:
ans = sorted([current] + ts)
if ans not in result:
... | Solution_A | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution_A:
def threeSum(self, nums: List[int]) -> List[List[int]]:
"""Hstable method from LC001 Use modified method of two_sum (Above) with every number, check the rest of array for two_sum of (0-number) O(N^2), max time limit exceeded"""
<|body_0|>
def twoSum_for_3sum(self... | stack_v2_sparse_classes_36k_train_002938 | 8,683 | permissive | [
{
"docstring": "Hstable method from LC001 Use modified method of two_sum (Above) with every number, check the rest of array for two_sum of (0-number) O(N^2), max time limit exceeded",
"name": "threeSum",
"signature": "def threeSum(self, nums: List[int]) -> List[List[int]]"
},
{
"docstring": "Hel... | 2 | stack_v2_sparse_classes_30k_train_008116 | Implement the Python class `Solution_A` described below.
Class description:
Implement the Solution_A class.
Method signatures and docstrings:
- def threeSum(self, nums: List[int]) -> List[List[int]]: Hstable method from LC001 Use modified method of two_sum (Above) with every number, check the rest of array for two_su... | Implement the Python class `Solution_A` described below.
Class description:
Implement the Solution_A class.
Method signatures and docstrings:
- def threeSum(self, nums: List[int]) -> List[List[int]]: Hstable method from LC001 Use modified method of two_sum (Above) with every number, check the rest of array for two_su... | 143422321cbc3715ca08f6c3af8f960a55887ced | <|skeleton|>
class Solution_A:
def threeSum(self, nums: List[int]) -> List[List[int]]:
"""Hstable method from LC001 Use modified method of two_sum (Above) with every number, check the rest of array for two_sum of (0-number) O(N^2), max time limit exceeded"""
<|body_0|>
def twoSum_for_3sum(self... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution_A:
def threeSum(self, nums: List[int]) -> List[List[int]]:
"""Hstable method from LC001 Use modified method of two_sum (Above) with every number, check the rest of array for two_sum of (0-number) O(N^2), max time limit exceeded"""
result = []
for i in range(len(nums)):
... | the_stack_v2_python_sparse | LeetCode/LC015_3sum.py | jxie0755/Learning_Python | train | 0 | |
aa6015d69e4779f780c7dbc2e0d8761a79aa4a14 | [
"check_required_roles(required_roles, 'code')\nfor rr in required_roles:\n if not isinstance(self, rr):\n return False\nreturn True",
"from lino.modlib.users.choicelists import UserTypes\nfor p in UserTypes.items():\n if p.has_required_roles([cls]):\n yield p"
] | <|body_start_0|>
check_required_roles(required_roles, 'code')
for rr in required_roles:
if not isinstance(self, rr):
return False
return True
<|end_body_0|>
<|body_start_1|>
from lino.modlib.users.choicelists import UserTypes
for p in UserTypes.items(... | Base class for all user roles. Even anonymous users have this role. | UserRole | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserRole:
"""Base class for all user roles. Even anonymous users have this role."""
def satisfies_requirement(self, required_roles):
"""Return `True` if this user role satisfies the specified role requirement. `required_roles` is the set of required roles (class objects). Every item ... | stack_v2_sparse_classes_36k_train_002939 | 3,271 | permissive | [
{
"docstring": "Return `True` if this user role satisfies the specified role requirement. `required_roles` is the set of required roles (class objects). Every item is either a class object (subclass of :class:`<UserRole>`) or a tuple thereof. This role (an instance) must satisfy *every* specified requirement.",... | 2 | stack_v2_sparse_classes_30k_train_005949 | Implement the Python class `UserRole` described below.
Class description:
Base class for all user roles. Even anonymous users have this role.
Method signatures and docstrings:
- def satisfies_requirement(self, required_roles): Return `True` if this user role satisfies the specified role requirement. `required_roles` ... | Implement the Python class `UserRole` described below.
Class description:
Base class for all user roles. Even anonymous users have this role.
Method signatures and docstrings:
- def satisfies_requirement(self, required_roles): Return `True` if this user role satisfies the specified role requirement. `required_roles` ... | 64f7ca9c9b83459b5b9f26174e5e3c26a137459d | <|skeleton|>
class UserRole:
"""Base class for all user roles. Even anonymous users have this role."""
def satisfies_requirement(self, required_roles):
"""Return `True` if this user role satisfies the specified role requirement. `required_roles` is the set of required roles (class objects). Every item ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserRole:
"""Base class for all user roles. Even anonymous users have this role."""
def satisfies_requirement(self, required_roles):
"""Return `True` if this user role satisfies the specified role requirement. `required_roles` is the set of required roles (class objects). Every item is either a c... | the_stack_v2_python_sparse | lino/core/roles.py | khchine5/lino | train | 1 |
232800e01be035ed65131ed093c849f42f97c82f | [
"rindex = {c: i for i, c in enumerate(s)}\nresult = ''\nfor i, c in enumerate(s):\n if c not in result:\n while c < result[-1:] and i < rindex[result[-1]]:\n result = result[:-1]\n result += c\nreturn result",
"result = ''\nwhile s:\n i = min(map(s.rindex, set(s)))\n c = min(s[:i... | <|body_start_0|>
rindex = {c: i for i, c in enumerate(s)}
result = ''
for i, c in enumerate(s):
if c not in result:
while c < result[-1:] and i < rindex[result[-1]]:
result = result[:-1]
result += c
return result
<|end_body_... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeDuplicateLetters(self, s):
""":type s: str :rtype: str beats 82.59%"""
<|body_0|>
def removeDuplicateLetters1(self, s):
""":type s: str :rtype: str beats 70.31%"""
<|body_1|>
def removeDuplicateLetters2(self, s):
""":type s: s... | stack_v2_sparse_classes_36k_train_002940 | 1,175 | no_license | [
{
"docstring": ":type s: str :rtype: str beats 82.59%",
"name": "removeDuplicateLetters",
"signature": "def removeDuplicateLetters(self, s)"
},
{
"docstring": ":type s: str :rtype: str beats 70.31%",
"name": "removeDuplicateLetters1",
"signature": "def removeDuplicateLetters1(self, s)"
... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeDuplicateLetters(self, s): :type s: str :rtype: str beats 82.59%
- def removeDuplicateLetters1(self, s): :type s: str :rtype: str beats 70.31%
- def removeDuplicateLett... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeDuplicateLetters(self, s): :type s: str :rtype: str beats 82.59%
- def removeDuplicateLetters1(self, s): :type s: str :rtype: str beats 70.31%
- def removeDuplicateLett... | 7e0e917c15d3e35f49da3a00ef395bd5ff180d79 | <|skeleton|>
class Solution:
def removeDuplicateLetters(self, s):
""":type s: str :rtype: str beats 82.59%"""
<|body_0|>
def removeDuplicateLetters1(self, s):
""":type s: str :rtype: str beats 70.31%"""
<|body_1|>
def removeDuplicateLetters2(self, s):
""":type s: s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def removeDuplicateLetters(self, s):
""":type s: str :rtype: str beats 82.59%"""
rindex = {c: i for i, c in enumerate(s)}
result = ''
for i, c in enumerate(s):
if c not in result:
while c < result[-1:] and i < rindex[result[-1]]:
... | the_stack_v2_python_sparse | LeetCode/316_remove_duplicate_letters.py | yao23/Machine_Learning_Playground | train | 12 | |
a541f49df019c81910410ca04e628af8a4e8777b | [
"if TvbProfile.SUBPARAM_PROFILE in script_argv:\n index = script_argv.index(TvbProfile.SUBPARAM_PROFILE)\n if len(script_argv) > index + 1:\n return script_argv[index + 1]\nreturn None",
"selected_profile = TvbProfile.get_profile(script_argv)\nif try_reload:\n sys.path = os.environ.get('PYTHONPATH... | <|body_start_0|>
if TvbProfile.SUBPARAM_PROFILE in script_argv:
index = script_argv.index(TvbProfile.SUBPARAM_PROFILE)
if len(script_argv) > index + 1:
return script_argv[index + 1]
return None
<|end_body_0|>
<|body_start_1|>
selected_profile = TvbProfile... | ENUM-like class with current TVB profile values. | TvbProfile | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TvbProfile:
"""ENUM-like class with current TVB profile values."""
def get_profile(script_argv):
"""Returns the user given profile or None if the user didn't specify a profile. :param script_argv: represents a list of string arguments. If the script_argv contains the string '-profile... | stack_v2_sparse_classes_36k_train_002941 | 6,210 | no_license | [
{
"docstring": "Returns the user given profile or None if the user didn't specify a profile. :param script_argv: represents a list of string arguments. If the script_argv contains the string '-profile', than TVB profile will be set to the next element. E.g.: if script_argv=['$param1', ..., '-profile', 'TEST_SQL... | 3 | null | Implement the Python class `TvbProfile` described below.
Class description:
ENUM-like class with current TVB profile values.
Method signatures and docstrings:
- def get_profile(script_argv): Returns the user given profile or None if the user didn't specify a profile. :param script_argv: represents a list of string ar... | Implement the Python class `TvbProfile` described below.
Class description:
ENUM-like class with current TVB profile values.
Method signatures and docstrings:
- def get_profile(script_argv): Returns the user given profile or None if the user didn't specify a profile. :param script_argv: represents a list of string ar... | dd4beb028719abaa70c639f64c97ba23bd4a1f3a | <|skeleton|>
class TvbProfile:
"""ENUM-like class with current TVB profile values."""
def get_profile(script_argv):
"""Returns the user given profile or None if the user didn't specify a profile. :param script_argv: represents a list of string arguments. If the script_argv contains the string '-profile... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TvbProfile:
"""ENUM-like class with current TVB profile values."""
def get_profile(script_argv):
"""Returns the user given profile or None if the user didn't specify a profile. :param script_argv: represents a list of string arguments. If the script_argv contains the string '-profile', than TVB p... | the_stack_v2_python_sparse | tvb/basic/profile.py | HuifangWang/the-virtual-brain-website | train | 0 |
65f8d879de2f5b8527549214dbf9e4e3e6e03fec | [
"if n == 0:\n return 1\nif n == 1:\n return 0\ndp = []\ndp.append(1)\ndp.append(0)\nfor i in range(2, n + 1):\n dp.append((i - 1) * (dp[1] + dp[0]) % (10 ** 9 + 7))\n dp.pop(0)\nreturn dp[1]",
"ans, a, b = (1, 1, 0)\nfor i in range(2, n):\n ans, a, b = (i * (a + b) % 1000000007, i * (a + b) % 10000... | <|body_start_0|>
if n == 0:
return 1
if n == 1:
return 0
dp = []
dp.append(1)
dp.append(0)
for i in range(2, n + 1):
dp.append((i - 1) * (dp[1] + dp[0]) % (10 ** 9 + 7))
dp.pop(0)
return dp[1]
<|end_body_0|>
<|body_... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findDerangement(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def findDerangement2(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n == 0:
return 1
if n == 1:
... | stack_v2_sparse_classes_36k_train_002942 | 1,354 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "findDerangement",
"signature": "def findDerangement(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "findDerangement2",
"signature": "def findDerangement2(self, n)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDerangement(self, n): :type n: int :rtype: int
- def findDerangement2(self, n): :type n: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDerangement(self, n): :type n: int :rtype: int
- def findDerangement2(self, n): :type n: int :rtype: int
<|skeleton|>
class Solution:
def findDerangement(self, n):
... | b155895c90169ec97372b2517f556fd50deac2bc | <|skeleton|>
class Solution:
def findDerangement(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def findDerangement2(self, n):
""":type n: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findDerangement(self, n):
""":type n: int :rtype: int"""
if n == 0:
return 1
if n == 1:
return 0
dp = []
dp.append(1)
dp.append(0)
for i in range(2, n + 1):
dp.append((i - 1) * (dp[1] + dp[0]) % (10 ** 9 ... | the_stack_v2_python_sparse | derangement.py | claytonjwong/Sandbox-Python | train | 0 | |
32498d3315a038fba8a5e6f02cb6513c62f564d5 | [
"res = 1\nfor _ in range(k):\n res *= m\n res %= 1337\nreturn res",
"if not b or a == 1:\n return 1\na %= 1337\ns1 = self.mypow(a, b[-1])\ns2 = self.mypow(self.superPow(a, b[:-1]), 10)\nreturn s1 * s2"
] | <|body_start_0|>
res = 1
for _ in range(k):
res *= m
res %= 1337
return res
<|end_body_0|>
<|body_start_1|>
if not b or a == 1:
return 1
a %= 1337
s1 = self.mypow(a, b[-1])
s2 = self.mypow(self.superPow(a, b[:-1]), 10)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def mypow(self, m, k):
"""求 m^k 并对 1337 取模 利用： (a * b) % k = ((a % k) * (b % k)) % k"""
<|body_0|>
def superPow(self, a: int, b: list) -> int:
"""递归，利用： a ^ [1,2,3] = a^3 * (a^[1,2])^10"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
res =... | stack_v2_sparse_classes_36k_train_002943 | 879 | no_license | [
{
"docstring": "求 m^k 并对 1337 取模 利用： (a * b) % k = ((a % k) * (b % k)) % k",
"name": "mypow",
"signature": "def mypow(self, m, k)"
},
{
"docstring": "递归，利用： a ^ [1,2,3] = a^3 * (a^[1,2])^10",
"name": "superPow",
"signature": "def superPow(self, a: int, b: list) -> int"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mypow(self, m, k): 求 m^k 并对 1337 取模 利用： (a * b) % k = ((a % k) * (b % k)) % k
- def superPow(self, a: int, b: list) -> int: 递归，利用： a ^ [1,2,3] = a^3 * (a^[1,2])^10 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mypow(self, m, k): 求 m^k 并对 1337 取模 利用： (a * b) % k = ((a % k) * (b % k)) % k
- def superPow(self, a: int, b: list) -> int: 递归，利用： a ^ [1,2,3] = a^3 * (a^[1,2])^10
<|skeleto... | a1e624f0afc24ea5f159fa66fed178aa61bb0179 | <|skeleton|>
class Solution:
def mypow(self, m, k):
"""求 m^k 并对 1337 取模 利用： (a * b) % k = ((a % k) * (b % k)) % k"""
<|body_0|>
def superPow(self, a: int, b: list) -> int:
"""递归，利用： a ^ [1,2,3] = a^3 * (a^[1,2])^10"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def mypow(self, m, k):
"""求 m^k 并对 1337 取模 利用： (a * b) % k = ((a % k) * (b % k)) % k"""
res = 1
for _ in range(k):
res *= m
res %= 1337
return res
def superPow(self, a: int, b: list) -> int:
"""递归，利用： a ^ [1,2,3] = a^3 * (a^[1,2])^... | the_stack_v2_python_sparse | LeetCode/372_Super_Pow.py | HappyRocky/pythonAI | train | 2 | |
600b474162e535fa590fe388601d73e476261085 | [
"super().__init__()\nself.n_patches = int(np.prod([i / patch_size for i in img_size]))\nself.pos_embed = nn.Parameter(torch.zeros(1, self.n_patches, embed_size))\nself.patch_embed = Conv(in_channels=in_feats, out_channels=embed_size, kernel_size=patch_size, stride=patch_size)",
"x = self.patch_embed(x)\nx = x.fla... | <|body_start_0|>
super().__init__()
self.n_patches = int(np.prod([i / patch_size for i in img_size]))
self.pos_embed = nn.Parameter(torch.zeros(1, self.n_patches, embed_size))
self.patch_embed = Conv(in_channels=in_feats, out_channels=embed_size, kernel_size=patch_size, stride=patch_size... | _Embedding | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _Embedding:
def __init__(self, img_size, patch_size, in_feats, embed_size, Conv):
"""A module that creates embeddings from an image tensor. Args: img_size (tuple[int]): The size of the input image tensor (H, W, C). patch_size (int): The size of each square patch that the image is divided... | stack_v2_sparse_classes_36k_train_002944 | 24,719 | permissive | [
{
"docstring": "A module that creates embeddings from an image tensor. Args: img_size (tuple[int]): The size of the input image tensor (H, W, C). patch_size (int): The size of each square patch that the image is divided into. in_feats (int): The number of input channels in the image tensor. embed_size (int): Th... | 2 | stack_v2_sparse_classes_30k_test_000929 | Implement the Python class `_Embedding` described below.
Class description:
Implement the _Embedding class.
Method signatures and docstrings:
- def __init__(self, img_size, patch_size, in_feats, embed_size, Conv): A module that creates embeddings from an image tensor. Args: img_size (tuple[int]): The size of the inpu... | Implement the Python class `_Embedding` described below.
Class description:
Implement the _Embedding class.
Method signatures and docstrings:
- def __init__(self, img_size, patch_size, in_feats, embed_size, Conv): A module that creates embeddings from an image tensor. Args: img_size (tuple[int]): The size of the inpu... | 72eb99f68205afd5f8d49a3bb6cfc08cfd467582 | <|skeleton|>
class _Embedding:
def __init__(self, img_size, patch_size, in_feats, embed_size, Conv):
"""A module that creates embeddings from an image tensor. Args: img_size (tuple[int]): The size of the input image tensor (H, W, C). patch_size (int): The size of each square patch that the image is divided... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _Embedding:
def __init__(self, img_size, patch_size, in_feats, embed_size, Conv):
"""A module that creates embeddings from an image tensor. Args: img_size (tuple[int]): The size of the input image tensor (H, W, C). patch_size (int): The size of each square patch that the image is divided into. in_feat... | the_stack_v2_python_sparse | GANDLF/models/unetr.py | mlcommons/GaNDLF | train | 45 | |
9a1fec6a5f68cf484ebbfd2566c6515dbbe380aa | [
"my_module_path = str_plugin_path\nmy_plugin = str_plugin\ntry:\n my_module = importlib.import_module(my_module_path)\n evaluated_plugin_str = 'my_module.%s' % my_plugin\n my_class = eval(evaluated_plugin_str)\nexcept Exception:\n raise Exception('Failed to evaluate ExecEngine plugin %s.%s' % (str_plugi... | <|body_start_0|>
my_module_path = str_plugin_path
my_plugin = str_plugin
try:
my_module = importlib.import_module(my_module_path)
evaluated_plugin_str = 'my_module.%s' % my_plugin
my_class = eval(evaluated_plugin_str)
except Exception:
rais... | Provides services for the execution of algorithms. FacadeExecution.factory is an instance of FactoryExecAlgo, which must be used to instantiate separately executable algorithms Typical use of this facade: 1) Simplest use: my_exec_algo, exec_status = FacadeExecution.execute( ... ) 2) Separating steps : initializing algo... | FacadeExecution | [
"LGPL-3.0-only",
"LGPL-2.0-or-later",
"LGPL-3.0-or-later",
"Zlib",
"BSD-3-Clause",
"Python-2.0",
"ZPL-2.0",
"LicenseRef-scancode-openssl-exception-lgpl3.0plus",
"ZPL-2.1",
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FacadeExecution:
"""Provides services for the execution of algorithms. FacadeExecution.factory is an instance of FactoryExecAlgo, which must be used to instantiate separately executable algorithms Typical use of this facade: 1) Simplest use: my_exec_algo, exec_status = FacadeExecution.execute( ..... | stack_v2_sparse_classes_36k_train_002945 | 6,584 | permissive | [
{
"docstring": "private class method evaluate the configured engine from module+plugin :param cls: :type cls: :param str_plugin_path: :type str_plugin_path: :param str_plugin: :type str_plugin: :return: subclass of ExecEngine (!!! not an instance !!!)",
"name": "__eval_exec_engine_class",
"signature": "... | 3 | stack_v2_sparse_classes_30k_train_015558 | Implement the Python class `FacadeExecution` described below.
Class description:
Provides services for the execution of algorithms. FacadeExecution.factory is an instance of FactoryExecAlgo, which must be used to instantiate separately executable algorithms Typical use of this facade: 1) Simplest use: my_exec_algo, ex... | Implement the Python class `FacadeExecution` described below.
Class description:
Provides services for the execution of algorithms. FacadeExecution.factory is an instance of FactoryExecAlgo, which must be used to instantiate separately executable algorithms Typical use of this facade: 1) Simplest use: my_exec_algo, ex... | 0b04ab448faf1ffdc89687268c6192e69d61f890 | <|skeleton|>
class FacadeExecution:
"""Provides services for the execution of algorithms. FacadeExecution.factory is an instance of FactoryExecAlgo, which must be used to instantiate separately executable algorithms Typical use of this facade: 1) Simplest use: my_exec_algo, exec_status = FacadeExecution.execute( ..... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FacadeExecution:
"""Provides services for the execution of algorithms. FacadeExecution.factory is an instance of FactoryExecAlgo, which must be used to instantiate separately executable algorithms Typical use of this facade: 1) Simplest use: my_exec_algo, exec_status = FacadeExecution.execute( ... ) 2) Separa... | the_stack_v2_python_sparse | src/ikats/processing/apps/algo/execute/models/business/facade.py | IKATS/ikats-pybase | train | 0 |
03fda521bbe5e29bb4b667e00ac2bca7a3b8dd5a | [
"if BLOCK_TARGET_MIN <= celsius <= BLOCK_TARGET_MAX:\n return celsius\nraise InvalidTargetTemperatureError(f'Thermocycler block temperature must be between {BLOCK_TARGET_MIN} and {BLOCK_TARGET_MAX}, but got {celsius}.')",
"if BLOCK_VOL_MIN <= volume <= BLOCK_VOL_MAX:\n return volume\nraise InvalidBlockVolum... | <|body_start_0|>
if BLOCK_TARGET_MIN <= celsius <= BLOCK_TARGET_MAX:
return celsius
raise InvalidTargetTemperatureError(f'Thermocycler block temperature must be between {BLOCK_TARGET_MIN} and {BLOCK_TARGET_MAX}, but got {celsius}.')
<|end_body_0|>
<|body_start_1|>
if BLOCK_VOL_MIN <... | Thermocycler-specific state. Provides calculations and read-only state access for an individual loaded Thermocycler Module. | ThermocyclerModuleSubState | [
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThermocyclerModuleSubState:
"""Thermocycler-specific state. Provides calculations and read-only state access for an individual loaded Thermocycler Module."""
def validate_target_block_temperature(celsius: float) -> float:
"""Validate a given target block temperature. Args: celsius: T... | stack_v2_sparse_classes_36k_train_002946 | 4,389 | permissive | [
{
"docstring": "Validate a given target block temperature. Args: celsius: The requested block temperature. Raises: InvalidTargetTemperatureError: The given temperature is outside the thermocycler's operating range. Returns: The validated temperature in degrees Celsius.",
"name": "validate_target_block_tempe... | 6 | stack_v2_sparse_classes_30k_train_008021 | Implement the Python class `ThermocyclerModuleSubState` described below.
Class description:
Thermocycler-specific state. Provides calculations and read-only state access for an individual loaded Thermocycler Module.
Method signatures and docstrings:
- def validate_target_block_temperature(celsius: float) -> float: Va... | Implement the Python class `ThermocyclerModuleSubState` described below.
Class description:
Thermocycler-specific state. Provides calculations and read-only state access for an individual loaded Thermocycler Module.
Method signatures and docstrings:
- def validate_target_block_temperature(celsius: float) -> float: Va... | 026b523c8c9e5d45910c490efb89194d72595be9 | <|skeleton|>
class ThermocyclerModuleSubState:
"""Thermocycler-specific state. Provides calculations and read-only state access for an individual loaded Thermocycler Module."""
def validate_target_block_temperature(celsius: float) -> float:
"""Validate a given target block temperature. Args: celsius: T... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ThermocyclerModuleSubState:
"""Thermocycler-specific state. Provides calculations and read-only state access for an individual loaded Thermocycler Module."""
def validate_target_block_temperature(celsius: float) -> float:
"""Validate a given target block temperature. Args: celsius: The requested ... | the_stack_v2_python_sparse | api/src/opentrons/protocol_engine/state/module_substates/thermocycler_module_substate.py | Opentrons/opentrons | train | 326 |
6d749a4f82084b210b4a0b90d11a59ca99d1e67e | [
"if ssh_config['identity'] and ssh_config['identity'].get('ssh_key'):\n return ssh_config['identity']['ssh_key']['label']\nreturn None",
"if 'identityfile' not in config:\n return None\nidentityfile = self.choose_ssh_key(config['identityfile'], config)\nif not identityfile:\n return None\ncontent = ident... | <|body_start_0|>
if ssh_config['identity'] and ssh_config['identity'].get('ssh_key'):
return ssh_config['identity']['ssh_key']['label']
return None
<|end_body_0|>
<|body_start_1|>
if 'identityfile' not in config:
return None
identityfile = self.choose_ssh_key(con... | Class for adapting app host and ssh config hosts. | SSHConfigHostAdapter | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SSHConfigHostAdapter:
"""Class for adapting app host and ssh config hosts."""
def get_instance_ssh_key_label(self, ssh_config):
"""Retrieve the ssh_key lable."""
<|body_0|>
def create_key(self, config):
"""Construct new application ssh key instance."""
<|... | stack_v2_sparse_classes_36k_train_002947 | 2,943 | permissive | [
{
"docstring": "Retrieve the ssh_key lable.",
"name": "get_instance_ssh_key_label",
"signature": "def get_instance_ssh_key_label(self, ssh_config)"
},
{
"docstring": "Construct new application ssh key instance.",
"name": "create_key",
"signature": "def create_key(self, config)"
},
{
... | 5 | stack_v2_sparse_classes_30k_test_000928 | Implement the Python class `SSHConfigHostAdapter` described below.
Class description:
Class for adapting app host and ssh config hosts.
Method signatures and docstrings:
- def get_instance_ssh_key_label(self, ssh_config): Retrieve the ssh_key lable.
- def create_key(self, config): Construct new application ssh key in... | Implement the Python class `SSHConfigHostAdapter` described below.
Class description:
Class for adapting app host and ssh config hosts.
Method signatures and docstrings:
- def get_instance_ssh_key_label(self, ssh_config): Retrieve the ssh_key lable.
- def create_key(self, config): Construct new application ssh key in... | 2664d0c70d3d682ad931b885b4965447b156c280 | <|skeleton|>
class SSHConfigHostAdapter:
"""Class for adapting app host and ssh config hosts."""
def get_instance_ssh_key_label(self, ssh_config):
"""Retrieve the ssh_key lable."""
<|body_0|>
def create_key(self, config):
"""Construct new application ssh key instance."""
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SSHConfigHostAdapter:
"""Class for adapting app host and ssh config hosts."""
def get_instance_ssh_key_label(self, ssh_config):
"""Retrieve the ssh_key lable."""
if ssh_config['identity'] and ssh_config['identity'].get('ssh_key'):
return ssh_config['identity']['ssh_key']['labe... | the_stack_v2_python_sparse | termius/porting/providers/ssh/adapter.py | termius/termius-cli | train | 262 |
d50131fd4f3e378cc4ed773a7329192382337942 | [
"filename = utils.normalize_paths(filename)[0]\nwith_doctest = self.with_doctest\nincluded_by = [include for include in self.include_in_doctest if include != '' and filename.startswith(include)]\nif included_by:\n with_doctest = True\nfor exclude in self.exclude_from_doctest:\n if exclude != '' and filename.s... | <|body_start_0|>
filename = utils.normalize_paths(filename)[0]
with_doctest = self.with_doctest
included_by = [include for include in self.include_in_doctest if include != '' and filename.startswith(include)]
if included_by:
with_doctest = True
for exclude in self.exc... | Subclass the Pyflakes checker to conform with the flake8 API. | FlakesChecker | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FlakesChecker:
"""Subclass the Pyflakes checker to conform with the flake8 API."""
def __init__(self, tree, filename):
"""Initialize the PyFlakes plugin with an AST tree and filename."""
<|body_0|>
def add_options(cls, parser):
"""Register options for PyFlakes on... | stack_v2_sparse_classes_36k_train_002948 | 5,661 | permissive | [
{
"docstring": "Initialize the PyFlakes plugin with an AST tree and filename.",
"name": "__init__",
"signature": "def __init__(self, tree, filename)"
},
{
"docstring": "Register options for PyFlakes on the Flake8 OptionManager.",
"name": "add_options",
"signature": "def add_options(cls, ... | 4 | stack_v2_sparse_classes_30k_train_015708 | Implement the Python class `FlakesChecker` described below.
Class description:
Subclass the Pyflakes checker to conform with the flake8 API.
Method signatures and docstrings:
- def __init__(self, tree, filename): Initialize the PyFlakes plugin with an AST tree and filename.
- def add_options(cls, parser): Register op... | Implement the Python class `FlakesChecker` described below.
Class description:
Subclass the Pyflakes checker to conform with the flake8 API.
Method signatures and docstrings:
- def __init__(self, tree, filename): Initialize the PyFlakes plugin with an AST tree and filename.
- def add_options(cls, parser): Register op... | 0473ea71751d9086a835c6ae2d34d3bf0b149f4e | <|skeleton|>
class FlakesChecker:
"""Subclass the Pyflakes checker to conform with the flake8 API."""
def __init__(self, tree, filename):
"""Initialize the PyFlakes plugin with an AST tree and filename."""
<|body_0|>
def add_options(cls, parser):
"""Register options for PyFlakes on... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FlakesChecker:
"""Subclass the Pyflakes checker to conform with the flake8 API."""
def __init__(self, tree, filename):
"""Initialize the PyFlakes plugin with an AST tree and filename."""
filename = utils.normalize_paths(filename)[0]
with_doctest = self.with_doctest
include... | the_stack_v2_python_sparse | env/lib/python3.4/site-packages/flake8/plugins/pyflakes.py | tlksio/tlksio | train | 1 |
640aa914aeeec944f37d3092afa50b193b0b17b7 | [
"role = Role.get_role_by_id(role_id=role_id)\nif not role:\n raise SystemGlobalException(status_code_message_obj=StatusCodeMessage.ROLE_NOT_EXISTS)\nserializer = RoleListSerializer(role)\nreturn APIResponse(data=serializer.data).get_result()",
"role = Role.get_role_by_id(role_id=role_id)\nif not role:\n rai... | <|body_start_0|>
role = Role.get_role_by_id(role_id=role_id)
if not role:
raise SystemGlobalException(status_code_message_obj=StatusCodeMessage.ROLE_NOT_EXISTS)
serializer = RoleListSerializer(role)
return APIResponse(data=serializer.data).get_result()
<|end_body_0|>
<|body_... | 角色查询,修改,删除APIView | RoleFindPutDelAPIView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RoleFindPutDelAPIView:
"""角色查询,修改,删除APIView"""
def get(_, role_id):
"""角色查询"""
<|body_0|>
def put(request, role_id):
"""角色修改"""
<|body_1|>
def delete(_, role_id):
"""角色删除"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
role ... | stack_v2_sparse_classes_36k_train_002949 | 2,780 | no_license | [
{
"docstring": "角色查询",
"name": "get",
"signature": "def get(_, role_id)"
},
{
"docstring": "角色修改",
"name": "put",
"signature": "def put(request, role_id)"
},
{
"docstring": "角色删除",
"name": "delete",
"signature": "def delete(_, role_id)"
}
] | 3 | stack_v2_sparse_classes_30k_train_013711 | Implement the Python class `RoleFindPutDelAPIView` described below.
Class description:
角色查询,修改,删除APIView
Method signatures and docstrings:
- def get(_, role_id): 角色查询
- def put(request, role_id): 角色修改
- def delete(_, role_id): 角色删除 | Implement the Python class `RoleFindPutDelAPIView` described below.
Class description:
角色查询,修改,删除APIView
Method signatures and docstrings:
- def get(_, role_id): 角色查询
- def put(request, role_id): 角色修改
- def delete(_, role_id): 角色删除
<|skeleton|>
class RoleFindPutDelAPIView:
"""角色查询,修改,删除APIView"""
def get(_,... | bb85b52598d68956bde8756c8321ade7b8479ba7 | <|skeleton|>
class RoleFindPutDelAPIView:
"""角色查询,修改,删除APIView"""
def get(_, role_id):
"""角色查询"""
<|body_0|>
def put(request, role_id):
"""角色修改"""
<|body_1|>
def delete(_, role_id):
"""角色删除"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RoleFindPutDelAPIView:
"""角色查询,修改,删除APIView"""
def get(_, role_id):
"""角色查询"""
role = Role.get_role_by_id(role_id=role_id)
if not role:
raise SystemGlobalException(status_code_message_obj=StatusCodeMessage.ROLE_NOT_EXISTS)
serializer = RoleListSerializer(role)
... | the_stack_v2_python_sparse | rbac_v1/v1/rbac_app/views/role/role_views.py | huiiiuh/huihuiproject | train | 0 |
ff9ddca5f5fcae922243d5a07ca737197b28eb38 | [
"self.bridgeRotation = None\nself.rotatedLoopLayers = []\nself.sliceDictionary = None\nself.stopProcessing = False\nself.z = 0.0",
"for loop in rotatedLoopLayer.loops:\n for pointIndex, point in enumerate(loop):\n loop[pointIndex] = complex(point.real, -point.imag)\ntriangle_mesh.sortLoopsInOrderOfArea(... | <|body_start_0|>
self.bridgeRotation = None
self.rotatedLoopLayers = []
self.sliceDictionary = None
self.stopProcessing = False
self.z = 0.0
<|end_body_0|>
<|body_start_1|>
for loop in rotatedLoopLayer.loops:
for pointIndex, point in enumerate(loop):
... | An svg carving. | SVGReader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SVGReader:
"""An svg carving."""
def __init__(self):
"""Add empty lists."""
<|body_0|>
def flipDirectLayer(self, rotatedLoopLayer):
"""Flip the y coordinate of the layer and direct the loops."""
<|body_1|>
def getRotatedLoopLayer(self):
"""Re... | stack_v2_sparse_classes_36k_train_002950 | 39,231 | no_license | [
{
"docstring": "Add empty lists.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Flip the y coordinate of the layer and direct the loops.",
"name": "flipDirectLayer",
"signature": "def flipDirectLayer(self, rotatedLoopLayer)"
},
{
"docstring": "Return t... | 6 | stack_v2_sparse_classes_30k_train_014049 | Implement the Python class `SVGReader` described below.
Class description:
An svg carving.
Method signatures and docstrings:
- def __init__(self): Add empty lists.
- def flipDirectLayer(self, rotatedLoopLayer): Flip the y coordinate of the layer and direct the loops.
- def getRotatedLoopLayer(self): Return the rotate... | Implement the Python class `SVGReader` described below.
Class description:
An svg carving.
Method signatures and docstrings:
- def __init__(self): Add empty lists.
- def flipDirectLayer(self, rotatedLoopLayer): Flip the y coordinate of the layer and direct the loops.
- def getRotatedLoopLayer(self): Return the rotate... | c1b00a76f1550df2cbb457248205159e51fd4308 | <|skeleton|>
class SVGReader:
"""An svg carving."""
def __init__(self):
"""Add empty lists."""
<|body_0|>
def flipDirectLayer(self, rotatedLoopLayer):
"""Flip the y coordinate of the layer and direct the loops."""
<|body_1|>
def getRotatedLoopLayer(self):
"""Re... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SVGReader:
"""An svg carving."""
def __init__(self):
"""Add empty lists."""
self.bridgeRotation = None
self.rotatedLoopLayers = []
self.sliceDictionary = None
self.stopProcessing = False
self.z = 0.0
def flipDirectLayer(self, rotatedLoopLayer):
... | the_stack_v2_python_sparse | fabmetheus_utilities/svg_reader.py | amsler/skeinforge | train | 10 |
913d0fe63d4598c97a7f5bd212341eb3615e320e | [
"self.only_direct = kwargs.get('only_direct', False)\ntry:\n del kwargs['only_direct']\nexcept KeyError:\n pass\nsuper(MUCJabberBot, self).__init__(*args, **kwargs)\nuser, domain = str(self.jid).split('@')\nself.direct_message_re = re.compile('^%s(@%s)?[^\\\\w]? ' % (user, domain))",
"message = mess.getBody... | <|body_start_0|>
self.only_direct = kwargs.get('only_direct', False)
try:
del kwargs['only_direct']
except KeyError:
pass
super(MUCJabberBot, self).__init__(*args, **kwargs)
user, domain = str(self.jid).split('@')
self.direct_message_re = re.compil... | Add features in JabberBot to allow it to handle specific caractheristics of multiple users chatroom (MUC). | MUCJabberBot | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MUCJabberBot:
"""Add features in JabberBot to allow it to handle specific caractheristics of multiple users chatroom (MUC)."""
def __init__(self, *args, **kwargs):
"""Initialize variables."""
<|body_0|>
def callback_message(self, conn, mess):
"""Changes the behav... | stack_v2_sparse_classes_36k_train_002951 | 2,341 | no_license | [
{
"docstring": "Initialize variables.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Changes the behaviour of the JabberBot in order to allow it to answer direct messages. This is used often when it is connected in MUCs (multiple users chatroom).",
... | 2 | stack_v2_sparse_classes_30k_train_002501 | Implement the Python class `MUCJabberBot` described below.
Class description:
Add features in JabberBot to allow it to handle specific caractheristics of multiple users chatroom (MUC).
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Initialize variables.
- def callback_message(self, conn, mes... | Implement the Python class `MUCJabberBot` described below.
Class description:
Add features in JabberBot to allow it to handle specific caractheristics of multiple users chatroom (MUC).
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Initialize variables.
- def callback_message(self, conn, mes... | 1897867f2db96cc24ba76a4cb7ef3a7c373b4289 | <|skeleton|>
class MUCJabberBot:
"""Add features in JabberBot to allow it to handle specific caractheristics of multiple users chatroom (MUC)."""
def __init__(self, *args, **kwargs):
"""Initialize variables."""
<|body_0|>
def callback_message(self, conn, mess):
"""Changes the behav... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MUCJabberBot:
"""Add features in JabberBot to allow it to handle specific caractheristics of multiple users chatroom (MUC)."""
def __init__(self, *args, **kwargs):
"""Initialize variables."""
self.only_direct = kwargs.get('only_direct', False)
try:
del kwargs['only_dir... | the_stack_v2_python_sparse | eve_django/eve_bot/mucbot.py | zhyrohaad/eve-code | train | 0 |
f3037a1d461ece66e5fae87be3335f615c2ece9d | [
"if table_size < 1:\n raise ValueError('table_size must be at least 1.')\nif repetitions < 3:\n raise ValueError('repetitions must be at least 3.')\nif rescale_factor <= 0 or rescale_factor > table_size - 1:\n raise ValueError(f'rescale_factor must be positive and no greater than table_size - 1. Found tabl... | <|body_start_0|>
if table_size < 1:
raise ValueError('table_size must be at least 1.')
if repetitions < 3:
raise ValueError('repetitions must be at least 3.')
if rescale_factor <= 0 or rescale_factor > table_size - 1:
raise ValueError(f'rescale_factor must be ... | Hashes a string to an hyper-edge with coupled indices. For a string, generates a set of indices such that the indices are close to each as described in https://arxiv.org/pdf/2001.10500.pdf. | CoupledHyperEdgeHasher | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CoupledHyperEdgeHasher:
"""Hashes a string to an hyper-edge with coupled indices. For a string, generates a set of indices such that the indices are close to each as described in https://arxiv.org/pdf/2001.10500.pdf."""
def __init__(self, seed: int, table_size: int, repetitions: int, rescale... | stack_v2_sparse_classes_36k_train_002952 | 10,259 | permissive | [
{
"docstring": "Initialize CoupledHyperEdgeHasher. Args: seed: An integer seed for hash functions. table_size: The hash table size of the IBLT. Must be a positive integer. repetitions: The number of repetitions in IBLT data structure. Must be at least 3. rescale_factor: A float to rescale `table_size` to `table... | 6 | stack_v2_sparse_classes_30k_train_007114 | Implement the Python class `CoupledHyperEdgeHasher` described below.
Class description:
Hashes a string to an hyper-edge with coupled indices. For a string, generates a set of indices such that the indices are close to each as described in https://arxiv.org/pdf/2001.10500.pdf.
Method signatures and docstrings:
- def ... | Implement the Python class `CoupledHyperEdgeHasher` described below.
Class description:
Hashes a string to an hyper-edge with coupled indices. For a string, generates a set of indices such that the indices are close to each as described in https://arxiv.org/pdf/2001.10500.pdf.
Method signatures and docstrings:
- def ... | ad4bca66f4b483e09d8396e9948630813a343d27 | <|skeleton|>
class CoupledHyperEdgeHasher:
"""Hashes a string to an hyper-edge with coupled indices. For a string, generates a set of indices such that the indices are close to each as described in https://arxiv.org/pdf/2001.10500.pdf."""
def __init__(self, seed: int, table_size: int, repetitions: int, rescale... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CoupledHyperEdgeHasher:
"""Hashes a string to an hyper-edge with coupled indices. For a string, generates a set of indices such that the indices are close to each as described in https://arxiv.org/pdf/2001.10500.pdf."""
def __init__(self, seed: int, table_size: int, repetitions: int, rescale_factor: floa... | the_stack_v2_python_sparse | tensorflow_federated/python/analytics/heavy_hitters/iblt/hyperedge_hashers.py | tensorflow/federated | train | 2,297 |
1012df63414f91078b958f37ccc2db56e7b0405a | [
"if is_any_instance(value, str, Integral, float):\n return value\nraise TypeError",
"if value is None:\n return None\nelif not isinstance(value, str):\n raise TypeError\nelse:\n try:\n return str(value)\n except:\n return value"
] | <|body_start_0|>
if is_any_instance(value, str, Integral, float):
return value
raise TypeError
<|end_body_0|>
<|body_start_1|>
if value is None:
return None
elif not isinstance(value, str):
raise TypeError
else:
try:
... | 通用类型转换类，可以处理 str/unicode/int/float 类型值。 | GenericTypeCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GenericTypeCase:
"""通用类型转换类，可以处理 str/unicode/int/float 类型值。"""
def to_redis(value):
"""接受 int/long/str/unicode/float 类型值， 否则抛出 TypeError 。"""
<|body_0|>
def to_python(value):
"""将传入值转换成 int/long/str/unicode/float 等格式。 因为 redis 只返回字符串值，这个函数也只接受字符串值，否则抛出 TypeError ... | stack_v2_sparse_classes_36k_train_002953 | 1,235 | no_license | [
{
"docstring": "接受 int/long/str/unicode/float 类型值， 否则抛出 TypeError 。",
"name": "to_redis",
"signature": "def to_redis(value)"
},
{
"docstring": "将传入值转换成 int/long/str/unicode/float 等格式。 因为 redis 只返回字符串值，这个函数也只接受字符串值，否则抛出 TypeError 。",
"name": "to_python",
"signature": "def to_python(value)... | 2 | null | Implement the Python class `GenericTypeCase` described below.
Class description:
通用类型转换类，可以处理 str/unicode/int/float 类型值。
Method signatures and docstrings:
- def to_redis(value): 接受 int/long/str/unicode/float 类型值， 否则抛出 TypeError 。
- def to_python(value): 将传入值转换成 int/long/str/unicode/float 等格式。 因为 redis 只返回字符串值，这个函数也只接... | Implement the Python class `GenericTypeCase` described below.
Class description:
通用类型转换类，可以处理 str/unicode/int/float 类型值。
Method signatures and docstrings:
- def to_redis(value): 接受 int/long/str/unicode/float 类型值， 否则抛出 TypeError 。
- def to_python(value): 将传入值转换成 int/long/str/unicode/float 等格式。 因为 redis 只返回字符串值，这个函数也只接... | f9fb551afbf47aaca7cdeba8b64a32d2fe3e30d6 | <|skeleton|>
class GenericTypeCase:
"""通用类型转换类，可以处理 str/unicode/int/float 类型值。"""
def to_redis(value):
"""接受 int/long/str/unicode/float 类型值， 否则抛出 TypeError 。"""
<|body_0|>
def to_python(value):
"""将传入值转换成 int/long/str/unicode/float 等格式。 因为 redis 只返回字符串值，这个函数也只接受字符串值，否则抛出 TypeError ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GenericTypeCase:
"""通用类型转换类，可以处理 str/unicode/int/float 类型值。"""
def to_redis(value):
"""接受 int/long/str/unicode/float 类型值， 否则抛出 TypeError 。"""
if is_any_instance(value, str, Integral, float):
return value
raise TypeError
def to_python(value):
"""将传入值转换成 int... | the_stack_v2_python_sparse | mysite/base/ooredis/type_case/generic_type_case.py | RockyLiys/erp | train | 1 |
58ac35541d30e1e96a6a242ea29e29c3f8cba894 | [
"super().__init__()\nassert len(transforms_list) > 0, 'Argument transforms_list cannot be empty.'\nassert num_sample_op > 0, 'Need to sample at least one transform.'\nassert num_sample_op <= len(transforms_list), 'Argument num_sample_op cannot be greater than number of available transforms.'\nif transforms_prob is ... | <|body_start_0|>
super().__init__()
assert len(transforms_list) > 0, 'Argument transforms_list cannot be empty.'
assert num_sample_op > 0, 'Need to sample at least one transform.'
assert num_sample_op <= len(transforms_list), 'Argument num_sample_op cannot be greater than number of avail... | Given a list of transforms with weights, OpSampler applies weighted sampling to select n transforms, which are then applied sequentially to the input. | OpSampler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OpSampler:
"""Given a list of transforms with weights, OpSampler applies weighted sampling to select n transforms, which are then applied sequentially to the input."""
def __init__(self, transforms_list: List[Callable], transforms_prob: Optional[List[float]]=None, num_sample_op: int=1, rando... | stack_v2_sparse_classes_36k_train_002954 | 10,994 | permissive | [
{
"docstring": "Args: transforms_list (List[Callable]): A list of tuples of all available transforms to sample from. transforms_prob (Optional[List[float]]): The probabilities associated with each transform in transforms_list. If not provided, the sampler assumes a uniform distribution over all transforms. They... | 2 | stack_v2_sparse_classes_30k_train_015646 | Implement the Python class `OpSampler` described below.
Class description:
Given a list of transforms with weights, OpSampler applies weighted sampling to select n transforms, which are then applied sequentially to the input.
Method signatures and docstrings:
- def __init__(self, transforms_list: List[Callable], tran... | Implement the Python class `OpSampler` described below.
Class description:
Given a list of transforms with weights, OpSampler applies weighted sampling to select n transforms, which are then applied sequentially to the input.
Method signatures and docstrings:
- def __init__(self, transforms_list: List[Callable], tran... | 16f2abf2f8aa174915316007622bbb260215dee8 | <|skeleton|>
class OpSampler:
"""Given a list of transforms with weights, OpSampler applies weighted sampling to select n transforms, which are then applied sequentially to the input."""
def __init__(self, transforms_list: List[Callable], transforms_prob: Optional[List[float]]=None, num_sample_op: int=1, rando... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OpSampler:
"""Given a list of transforms with weights, OpSampler applies weighted sampling to select n transforms, which are then applied sequentially to the input."""
def __init__(self, transforms_list: List[Callable], transforms_prob: Optional[List[float]]=None, num_sample_op: int=1, randomly_sample_de... | the_stack_v2_python_sparse | pytorchvideo/transforms/transforms.py | xchani/pytorchvideo | train | 0 |
6e14bf0472e328dbac299c7c80ed27b62685cbd9 | [
"if out_frames not in self.VALID_OUT_FRAMES:\n raise ValueError('Invalid number of frames in desired output: %d' % out_frames)\nsuper(Deconv, self).__init__()\nself.deconv_name = deconv_name\nself.out_frames = out_frames\nself.conv3d_1a = nn.Conv3d(in_channels=in_channels, out_channels=256, kernel_size=(3, 3, 3)... | <|body_start_0|>
if out_frames not in self.VALID_OUT_FRAMES:
raise ValueError('Invalid number of frames in desired output: %d' % out_frames)
super(Deconv, self).__init__()
self.deconv_name = deconv_name
self.out_frames = out_frames
self.conv3d_1a = nn.Conv3d(in_channe... | Class representing the Deconvolutional network that is used to estimate the video keypoints. | Deconv | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Deconv:
"""Class representing the Deconvolutional network that is used to estimate the video keypoints."""
def __init__(self, in_channels, out_frames, deconv_name='Deconvolutional Network'):
"""Initializes the Deconvolutional network. :param in_channels: (int) The number of channels ... | stack_v2_sparse_classes_36k_train_002955 | 2,862 | no_license | [
{
"docstring": "Initializes the Deconvolutional network. :param in_channels: (int) The number of channels in the input tensor. :param out_frames: (int) The number of frames desired in the generated output video. Legal values: 8, 16 :param deconv_name: (str, optional) The name of the network (default 'Deconvolut... | 2 | stack_v2_sparse_classes_30k_test_000245 | Implement the Python class `Deconv` described below.
Class description:
Class representing the Deconvolutional network that is used to estimate the video keypoints.
Method signatures and docstrings:
- def __init__(self, in_channels, out_frames, deconv_name='Deconvolutional Network'): Initializes the Deconvolutional n... | Implement the Python class `Deconv` described below.
Class description:
Class representing the Deconvolutional network that is used to estimate the video keypoints.
Method signatures and docstrings:
- def __init__(self, in_channels, out_frames, deconv_name='Deconvolutional Network'): Initializes the Deconvolutional n... | 6de28b5a8992f6122f2e9813de8b92d9e97ccbf3 | <|skeleton|>
class Deconv:
"""Class representing the Deconvolutional network that is used to estimate the video keypoints."""
def __init__(self, in_channels, out_frames, deconv_name='Deconvolutional Network'):
"""Initializes the Deconvolutional network. :param in_channels: (int) The number of channels ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Deconv:
"""Class representing the Deconvolutional network that is used to estimate the video keypoints."""
def __init__(self, in_channels, out_frames, deconv_name='Deconvolutional Network'):
"""Initializes the Deconvolutional network. :param in_channels: (int) The number of channels in the input ... | the_stack_v2_python_sparse | archive/phase1/netWith2828i3dOutput/deconv3.py | schatzkara/REU2019 | train | 0 |
0627d2caafcfd47f44e0c6288fc802ec50349495 | [
"super().__init__()\nself.dataframe = self.process_data(data_path, file_geometries=file_geometries)\nself.clean_dataframe(sanitize=sanitize)\nif 'positions' not in self.dataframe:\n self.dataframe['positions'] = guess_positions(self.dataframe.molecules, optimize_molecule)\nif properties is not None:\n self.la... | <|body_start_0|>
super().__init__()
self.dataframe = self.process_data(data_path, file_geometries=file_geometries)
self.clean_dataframe(sanitize=sanitize)
if 'positions' not in self.dataframe:
self.dataframe['positions'] = guess_positions(self.dataframe.molecules, optimize_mo... | Base class for the Data represented as graphs. | SwanGraphData | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SwanGraphData:
"""Base class for the Data represented as graphs."""
def __init__(self, data_path: PathLike, properties: Optional[Union[str, List[str]]]=None, sanitize: bool=True, file_geometries: Optional[PathLike]=None, optimize_molecule: bool=False) -> None:
"""Generate a dataset u... | stack_v2_sparse_classes_36k_train_002956 | 2,301 | permissive | [
{
"docstring": "Generate a dataset using graphs Parameters ---------- data_path path of the csv file properties Labels names sanitize Check that molecules have a valid conformer file_geometries Path to a file with the geometries in PDB format optimize_molecule Perform a molecular optimization using a force fiel... | 2 | stack_v2_sparse_classes_30k_train_000837 | Implement the Python class `SwanGraphData` described below.
Class description:
Base class for the Data represented as graphs.
Method signatures and docstrings:
- def __init__(self, data_path: PathLike, properties: Optional[Union[str, List[str]]]=None, sanitize: bool=True, file_geometries: Optional[PathLike]=None, opt... | Implement the Python class `SwanGraphData` described below.
Class description:
Base class for the Data represented as graphs.
Method signatures and docstrings:
- def __init__(self, data_path: PathLike, properties: Optional[Union[str, List[str]]]=None, sanitize: bool=True, file_geometries: Optional[PathLike]=None, opt... | 4edc9dc363ce901b1fcc19444bec42fc5930c4b9 | <|skeleton|>
class SwanGraphData:
"""Base class for the Data represented as graphs."""
def __init__(self, data_path: PathLike, properties: Optional[Union[str, List[str]]]=None, sanitize: bool=True, file_geometries: Optional[PathLike]=None, optimize_molecule: bool=False) -> None:
"""Generate a dataset u... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SwanGraphData:
"""Base class for the Data represented as graphs."""
def __init__(self, data_path: PathLike, properties: Optional[Union[str, List[str]]]=None, sanitize: bool=True, file_geometries: Optional[PathLike]=None, optimize_molecule: bool=False) -> None:
"""Generate a dataset using graphs P... | the_stack_v2_python_sparse | swan/dataset/data_graph_base.py | nlesc-nano/swan | train | 15 |
60cfdbe48aae286d02fda3f6c3359b1a9d9a7663 | [
"data = self.get_initial()\npassword1 = value\npassword2 = data.get('new_password2')\nif password1 != password2:\n raise serializers.ValidationError('The two Passwords must match.')\nreturn value",
"try:\n password = data.get('new_password1')\n token = data.get('token')\n uidb64 = data.get('uidb64')\n... | <|body_start_0|>
data = self.get_initial()
password1 = value
password2 = data.get('new_password2')
if password1 != password2:
raise serializers.ValidationError('The two Passwords must match.')
return value
<|end_body_0|>
<|body_start_1|>
try:
pass... | Password reset serializer. | PasswordResetSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PasswordResetSerializer:
"""Password reset serializer."""
def validate_new_password1(self, value):
"""Validate passwords."""
<|body_0|>
def validate(self, data):
"""Validate entered data."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
data = se... | stack_v2_sparse_classes_36k_train_002957 | 9,392 | no_license | [
{
"docstring": "Validate passwords.",
"name": "validate_new_password1",
"signature": "def validate_new_password1(self, value)"
},
{
"docstring": "Validate entered data.",
"name": "validate",
"signature": "def validate(self, data)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006871 | Implement the Python class `PasswordResetSerializer` described below.
Class description:
Password reset serializer.
Method signatures and docstrings:
- def validate_new_password1(self, value): Validate passwords.
- def validate(self, data): Validate entered data. | Implement the Python class `PasswordResetSerializer` described below.
Class description:
Password reset serializer.
Method signatures and docstrings:
- def validate_new_password1(self, value): Validate passwords.
- def validate(self, data): Validate entered data.
<|skeleton|>
class PasswordResetSerializer:
"""Pa... | 6c2e8bc6b0a172ff34d0f3191dfdebbd85584525 | <|skeleton|>
class PasswordResetSerializer:
"""Password reset serializer."""
def validate_new_password1(self, value):
"""Validate passwords."""
<|body_0|>
def validate(self, data):
"""Validate entered data."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PasswordResetSerializer:
"""Password reset serializer."""
def validate_new_password1(self, value):
"""Validate passwords."""
data = self.get_initial()
password1 = value
password2 = data.get('new_password2')
if password1 != password2:
raise serializers.V... | the_stack_v2_python_sparse | accounts/serializers.py | OmarFateh/api-ecommerce | train | 1 |
8b65721c96a813cd8ed57b5ebfb86526a81fdfb0 | [
"self.grid_size = Vector2(config.get('GRID_SIZE'))\nself.pixel_count = globals.mapping_data.pixel_count\nsize = self.pixel_count * 4\nself.data = bytearray(size)\nself.clear_data()\nself.spi_index = 0\nself.updated = None\nself.packet_length = 0\nself._dirty = True\nself._signal_startrecv = blinker.signal('stripdat... | <|body_start_0|>
self.grid_size = Vector2(config.get('GRID_SIZE'))
self.pixel_count = globals.mapping_data.pixel_count
size = self.pixel_count * 4
self.data = bytearray(size)
self.clear_data()
self.spi_index = 0
self.updated = None
self.packet_length = 0
... | StripData | [
"OFL-1.1",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StripData:
def __init__(self):
"""Data model of a strip of LED's and also handles processes received data packets. :return:"""
<|body_0|>
def spi_recv(self, msg):
"""Currently no checking of msg integrity or first four bytes being 0x00 is done. Msg is assumed to be c... | stack_v2_sparse_classes_36k_train_002958 | 4,170 | permissive | [
{
"docstring": "Data model of a strip of LED's and also handles processes received data packets. :return:",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Currently no checking of msg integrity or first four bytes being 0x00 is done. Msg is assumed to be correct. Future... | 6 | stack_v2_sparse_classes_30k_train_009043 | Implement the Python class `StripData` described below.
Class description:
Implement the StripData class.
Method signatures and docstrings:
- def __init__(self): Data model of a strip of LED's and also handles processes received data packets. :return:
- def spi_recv(self, msg): Currently no checking of msg integrity ... | Implement the Python class `StripData` described below.
Class description:
Implement the StripData class.
Method signatures and docstrings:
- def __init__(self): Data model of a strip of LED's and also handles processes received data packets. :return:
- def spi_recv(self, msg): Currently no checking of msg integrity ... | 9302ca1ae8c5089c9f2ce4ba471e6b4649609c5c | <|skeleton|>
class StripData:
def __init__(self):
"""Data model of a strip of LED's and also handles processes received data packets. :return:"""
<|body_0|>
def spi_recv(self, msg):
"""Currently no checking of msg integrity or first four bytes being 0x00 is done. Msg is assumed to be c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StripData:
def __init__(self):
"""Data model of a strip of LED's and also handles processes received data packets. :return:"""
self.grid_size = Vector2(config.get('GRID_SIZE'))
self.pixel_count = globals.mapping_data.pixel_count
size = self.pixel_count * 4
self.data = b... | the_stack_v2_python_sparse | DotStar_Emulator/emulator/data/strip_data.py | nicofirst1/DotStar_Emulator | train | 1 | |
d17b0ac3ac62cf0d442ec7efab84c5548c61e747 | [
"wallet_query = wallets.select().where(wallets.c.id == wallet_id)\nwallet = await self._db.fetch_one(wallet_query)\nif wallet:\n return WalletEntity(**wallet)\nreturn None",
"wallet_query = wallets.select().where(wallets.c.user_id == user_id)\nwallet = await self._db.fetch_one(wallet_query)\nif wallet:\n re... | <|body_start_0|>
wallet_query = wallets.select().where(wallets.c.id == wallet_id)
wallet = await self._db.fetch_one(wallet_query)
if wallet:
return WalletEntity(**wallet)
return None
<|end_body_0|>
<|body_start_1|>
wallet_query = wallets.select().where(wallets.c.user... | Implementation of wallet repository. | WalletRepository | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WalletRepository:
"""Implementation of wallet repository."""
async def get_by_id(self, wallet_id: int) -> Optional[WalletEntity]:
"""Retrieve wallet record by wallet id. :param wallet_id: ID of use :returns: Wallet schema"""
<|body_0|>
async def get_by_user_id(self, user... | stack_v2_sparse_classes_36k_train_002959 | 4,539 | no_license | [
{
"docstring": "Retrieve wallet record by wallet id. :param wallet_id: ID of use :returns: Wallet schema",
"name": "get_by_id",
"signature": "async def get_by_id(self, wallet_id: int) -> Optional[WalletEntity]"
},
{
"docstring": "Retrieve wallet record by user id. :param user_id: ID of use :retu... | 5 | stack_v2_sparse_classes_30k_train_021228 | Implement the Python class `WalletRepository` described below.
Class description:
Implementation of wallet repository.
Method signatures and docstrings:
- async def get_by_id(self, wallet_id: int) -> Optional[WalletEntity]: Retrieve wallet record by wallet id. :param wallet_id: ID of use :returns: Wallet schema
- asy... | Implement the Python class `WalletRepository` described below.
Class description:
Implementation of wallet repository.
Method signatures and docstrings:
- async def get_by_id(self, wallet_id: int) -> Optional[WalletEntity]: Retrieve wallet record by wallet id. :param wallet_id: ID of use :returns: Wallet schema
- asy... | 4cd339bdbe9ca1ac9ab01849dcd43c81e068488d | <|skeleton|>
class WalletRepository:
"""Implementation of wallet repository."""
async def get_by_id(self, wallet_id: int) -> Optional[WalletEntity]:
"""Retrieve wallet record by wallet id. :param wallet_id: ID of use :returns: Wallet schema"""
<|body_0|>
async def get_by_user_id(self, user... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WalletRepository:
"""Implementation of wallet repository."""
async def get_by_id(self, wallet_id: int) -> Optional[WalletEntity]:
"""Retrieve wallet record by wallet id. :param wallet_id: ID of use :returns: Wallet schema"""
wallet_query = wallets.select().where(wallets.c.id == wallet_id)... | the_stack_v2_python_sparse | app/repositories/wallet.py | vsokoltsov/billing_system_test_task | train | 0 |
02ca29ae508ea1fcd2935150a9170381a800aff2 | [
"super(Critic, self).__init__()\nself.critic1 = tf.keras.Sequential([tf.keras.layers.Dense(256, input_shape=(state_dim + action_dim,), activation=tf.nn.relu, kernel_initializer='orthogonal'), tf.keras.layers.Dense(256, activation=tf.nn.relu, kernel_initializer='orthogonal'), tf.keras.layers.Dense(1, kernel_initiali... | <|body_start_0|>
super(Critic, self).__init__()
self.critic1 = tf.keras.Sequential([tf.keras.layers.Dense(256, input_shape=(state_dim + action_dim,), activation=tf.nn.relu, kernel_initializer='orthogonal'), tf.keras.layers.Dense(256, activation=tf.nn.relu, kernel_initializer='orthogonal'), tf.keras.laye... | A critic network that estimates a dual Q-function. | Critic | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Critic:
"""A critic network that estimates a dual Q-function."""
def __init__(self, state_dim, action_dim):
"""Creates networks. Args: state_dim: State size. action_dim: Action size."""
<|body_0|>
def call(self, states, actions):
"""Returns Q-value estimates for ... | stack_v2_sparse_classes_36k_train_002960 | 13,412 | permissive | [
{
"docstring": "Creates networks. Args: state_dim: State size. action_dim: Action size.",
"name": "__init__",
"signature": "def __init__(self, state_dim, action_dim)"
},
{
"docstring": "Returns Q-value estimates for given states and actions. Args: states: A batch of states. actions: A batch of a... | 2 | stack_v2_sparse_classes_30k_train_011265 | Implement the Python class `Critic` described below.
Class description:
A critic network that estimates a dual Q-function.
Method signatures and docstrings:
- def __init__(self, state_dim, action_dim): Creates networks. Args: state_dim: State size. action_dim: Action size.
- def call(self, states, actions): Returns Q... | Implement the Python class `Critic` described below.
Class description:
A critic network that estimates a dual Q-function.
Method signatures and docstrings:
- def __init__(self, state_dim, action_dim): Creates networks. Args: state_dim: State size. action_dim: Action size.
- def call(self, states, actions): Returns Q... | 727ec399ad17b4dd1f71ce69a26fc3b0371d9fa7 | <|skeleton|>
class Critic:
"""A critic network that estimates a dual Q-function."""
def __init__(self, state_dim, action_dim):
"""Creates networks. Args: state_dim: State size. action_dim: Action size."""
<|body_0|>
def call(self, states, actions):
"""Returns Q-value estimates for ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Critic:
"""A critic network that estimates a dual Q-function."""
def __init__(self, state_dim, action_dim):
"""Creates networks. Args: state_dim: State size. action_dim: Action size."""
super(Critic, self).__init__()
self.critic1 = tf.keras.Sequential([tf.keras.layers.Dense(256, i... | the_stack_v2_python_sparse | value_dice/twin_sac.py | Ayoob7/google-research | train | 2 |
c47418b0559807e90f5df83f59e0413944bf4a20 | [
"base_url = case.get_full_base_url()\nkwargs = case.as_requests_kwargs(base_url)\nrequest = requests.Request(**kwargs)\nprepared = session.prepare_request(request)\nreturn cls.from_prepared_request(prepared)",
"body = prepared.body or b''\nif isinstance(body, str):\n body = body.encode('utf-8')\nuri = cast(str... | <|body_start_0|>
base_url = case.get_full_base_url()
kwargs = case.as_requests_kwargs(base_url)
request = requests.Request(**kwargs)
prepared = session.prepare_request(request)
return cls.from_prepared_request(prepared)
<|end_body_0|>
<|body_start_1|>
body = prepared.bod... | Request data extracted from `Case`. | Request | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Request:
"""Request data extracted from `Case`."""
def from_case(cls, case: Case, session: requests.Session) -> 'Request':
"""Create a new `Request` instance from `Case`."""
<|body_0|>
def from_prepared_request(cls, prepared: requests.PreparedRequest) -> 'Request':
... | stack_v2_sparse_classes_36k_train_002961 | 32,203 | permissive | [
{
"docstring": "Create a new `Request` instance from `Case`.",
"name": "from_case",
"signature": "def from_case(cls, case: Case, session: requests.Session) -> 'Request'"
},
{
"docstring": "A prepared request version is already stored in `requests.Response`.",
"name": "from_prepared_request",... | 2 | stack_v2_sparse_classes_30k_train_018630 | Implement the Python class `Request` described below.
Class description:
Request data extracted from `Case`.
Method signatures and docstrings:
- def from_case(cls, case: Case, session: requests.Session) -> 'Request': Create a new `Request` instance from `Case`.
- def from_prepared_request(cls, prepared: requests.Prep... | Implement the Python class `Request` described below.
Class description:
Request data extracted from `Case`.
Method signatures and docstrings:
- def from_case(cls, case: Case, session: requests.Session) -> 'Request': Create a new `Request` instance from `Case`.
- def from_prepared_request(cls, prepared: requests.Prep... | 9ba2244bf0e52db6f149243de403c8c7c157216f | <|skeleton|>
class Request:
"""Request data extracted from `Case`."""
def from_case(cls, case: Case, session: requests.Session) -> 'Request':
"""Create a new `Request` instance from `Case`."""
<|body_0|>
def from_prepared_request(cls, prepared: requests.PreparedRequest) -> 'Request':
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Request:
"""Request data extracted from `Case`."""
def from_case(cls, case: Case, session: requests.Session) -> 'Request':
"""Create a new `Request` instance from `Case`."""
base_url = case.get_full_base_url()
kwargs = case.as_requests_kwargs(base_url)
request = requests.R... | the_stack_v2_python_sparse | schemathesis/models.py | ngalongc/openapi_security_scanner | train | 167 |
c1c03a353afa75881332d04cfbc335811935317c | [
"flowerbed = [1, 0] + flowerbed + [0, 1]\ncur = 0\nresult = 0\nfor flower in flowerbed:\n if flower == 0:\n cur += 1\n else:\n result += int((cur - 1) / 2)\n cur = 0\nreturn result >= n",
"s = ('10' + ''.join([str(x) for x in flowerbed]) + '01').split('1')\nprint(s)\nresult = 0\nfor x i... | <|body_start_0|>
flowerbed = [1, 0] + flowerbed + [0, 1]
cur = 0
result = 0
for flower in flowerbed:
if flower == 0:
cur += 1
else:
result += int((cur - 1) / 2)
cur = 0
return result >= n
<|end_body_0|>
<|bo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canPlaceFlowers(self, flowerbed, n):
""":type flowerbed: List[int] :type n: int :rtype: bool"""
<|body_0|>
def canPlaceFlowers1(self, flowerbed, n):
""":type flowerbed: List[int] :type n: int :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_002962 | 1,040 | no_license | [
{
"docstring": ":type flowerbed: List[int] :type n: int :rtype: bool",
"name": "canPlaceFlowers",
"signature": "def canPlaceFlowers(self, flowerbed, n)"
},
{
"docstring": ":type flowerbed: List[int] :type n: int :rtype: bool",
"name": "canPlaceFlowers1",
"signature": "def canPlaceFlowers... | 2 | stack_v2_sparse_classes_30k_train_018319 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canPlaceFlowers(self, flowerbed, n): :type flowerbed: List[int] :type n: int :rtype: bool
- def canPlaceFlowers1(self, flowerbed, n): :type flowerbed: List[int] :type n: int ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canPlaceFlowers(self, flowerbed, n): :type flowerbed: List[int] :type n: int :rtype: bool
- def canPlaceFlowers1(self, flowerbed, n): :type flowerbed: List[int] :type n: int ... | 70bdd75b6af2e1811c1beab22050c01d28d7373e | <|skeleton|>
class Solution:
def canPlaceFlowers(self, flowerbed, n):
""":type flowerbed: List[int] :type n: int :rtype: bool"""
<|body_0|>
def canPlaceFlowers1(self, flowerbed, n):
""":type flowerbed: List[int] :type n: int :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def canPlaceFlowers(self, flowerbed, n):
""":type flowerbed: List[int] :type n: int :rtype: bool"""
flowerbed = [1, 0] + flowerbed + [0, 1]
cur = 0
result = 0
for flower in flowerbed:
if flower == 0:
cur += 1
else:
... | the_stack_v2_python_sparse | python/leetcode/605_Can_Place_Flowers.py | bobcaoge/my-code | train | 0 | |
cc7cf4c7058db216aa09c6ebbd7fc7632a939ed3 | [
"if not nums:\n return\ncounter = {}\nfor i in nums:\n if not counter.get(i, None):\n counter[i] = 1\n else:\n return i\nreturn",
"l, r = (0, len(nums) - 1)\nwhile l < r:\n m = (l + r) // 2\n if sum([i <= m for i in nums]) > m:\n r = m\n else:\n l = m + 1\nreturn l"
] | <|body_start_0|>
if not nums:
return
counter = {}
for i in nums:
if not counter.get(i, None):
counter[i] = 1
else:
return i
return
<|end_body_0|>
<|body_start_1|>
l, r = (0, len(nums) - 1)
while l < r:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findDuplicate(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findDuplicate(self, nums):
""":type nums: List[int] :rtype: int discuss: https://leetcode.com/problems/find-the-duplicate-number/discuss/72912/Python-solution-with-detaile... | stack_v2_sparse_classes_36k_train_002963 | 2,067 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "findDuplicate",
"signature": "def findDuplicate(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int discuss: https://leetcode.com/problems/find-the-duplicate-number/discuss/72912/Python-solution-with-detailed-explanation ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicate(self, nums): :type nums: List[int] :rtype: int
- def findDuplicate(self, nums): :type nums: List[int] :rtype: int discuss: https://leetcode.com/problems/find-th... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findDuplicate(self, nums): :type nums: List[int] :rtype: int
- def findDuplicate(self, nums): :type nums: List[int] :rtype: int discuss: https://leetcode.com/problems/find-th... | 673e51199a2d07198894a283479d459bef0272c5 | <|skeleton|>
class Solution:
def findDuplicate(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findDuplicate(self, nums):
""":type nums: List[int] :rtype: int discuss: https://leetcode.com/problems/find-the-duplicate-number/discuss/72912/Python-solution-with-detaile... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findDuplicate(self, nums):
""":type nums: List[int] :rtype: int"""
if not nums:
return
counter = {}
for i in nums:
if not counter.get(i, None):
counter[i] = 1
else:
return i
return
de... | the_stack_v2_python_sparse | binary_search_medium/1219_find_the_duplicate_number.py | myungwooko/algorithm | train | 1 | |
0bbeb7d60c7634768afe97dc21b55acca44fd6ba | [
"self.size = capacity\nself.lru_hashmap = {}\nself.dll = DLL()",
"if key not in self.lru_hashmap:\n return -1\nnode = self.lru_hashmap[key]\nvalue = node.value\nself.dll.delete_node(node)\nnode = self.dll.appned_node_at_front(key, value)\nself.lru_hashmap[key] = node\nreturn value",
"if key in self.lru_hashm... | <|body_start_0|>
self.size = capacity
self.lru_hashmap = {}
self.dll = DLL()
<|end_body_0|>
<|body_start_1|>
if key not in self.lru_hashmap:
return -1
node = self.lru_hashmap[key]
value = node.value
self.dll.delete_node(node)
node = self.dll.a... | LRUCache | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k_train_002964 | 4,210 | no_license | [
{
"docstring": ":type capacity: int",
"name": "__init__",
"signature": "def __init__(self, capacity)"
},
{
"docstring": ":type key: int :rtype: int",
"name": "get",
"signature": "def get(self, key)"
},
{
"docstring": ":type key: int :type value: int :rtype: None",
"name": "pu... | 3 | null | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None | Implement the Python class `LRUCache` described below.
Class description:
Implement the LRUCache class.
Method signatures and docstrings:
- def __init__(self, capacity): :type capacity: int
- def get(self, key): :type key: int :rtype: int
- def put(self, key, value): :type key: int :type value: int :rtype: None
<|sk... | 1211eac167f33084f536007468ea10c1a0ceab08 | <|skeleton|>
class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
<|body_0|>
def get(self, key):
""":type key: int :rtype: int"""
<|body_1|>
def put(self, key, value):
""":type key: int :type value: int :rtype: None"""
<|body_2|>
<|end_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LRUCache:
def __init__(self, capacity):
""":type capacity: int"""
self.size = capacity
self.lru_hashmap = {}
self.dll = DLL()
def get(self, key):
""":type key: int :rtype: int"""
if key not in self.lru_hashmap:
return -1
node = self.lru_... | the_stack_v2_python_sparse | 146_LRUCache.py | renukadeshmukh/Leetcode_Solutions | train | 3 | |
2f0cfa672d6a1069d0647c0dd3593ccaa8527330 | [
"self.SetTitle('This is an example Dialog')\nself.AddDlgGroup(c4d.DLG_OK | c4d.DLG_CANCEL)\nreturn True",
"if messageId == c4d.DLG_OK:\n print('User Click on Ok')\n return True\nelif messageId == c4d.DLG_CANCEL:\n print('User Click on Cancel')\n self.Close()\n return True\nreturn True"
] | <|body_start_0|>
self.SetTitle('This is an example Dialog')
self.AddDlgGroup(c4d.DLG_OK | c4d.DLG_CANCEL)
return True
<|end_body_0|>
<|body_start_1|>
if messageId == c4d.DLG_OK:
print('User Click on Ok')
return True
elif messageId == c4d.DLG_CANCEL:
... | ExampleDialog | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExampleDialog:
def CreateLayout(self):
"""This Method is called automatically when Cinema 4D creates the Layout of the Dialog. Returns: bool: False if there was an error, otherwise True."""
<|body_0|>
def Command(self, messageId, bc):
"""This Method is called automat... | stack_v2_sparse_classes_36k_train_002965 | 7,074 | permissive | [
{
"docstring": "This Method is called automatically when Cinema 4D creates the Layout of the Dialog. Returns: bool: False if there was an error, otherwise True.",
"name": "CreateLayout",
"signature": "def CreateLayout(self)"
},
{
"docstring": "This Method is called automatically when the user cl... | 2 | stack_v2_sparse_classes_30k_train_007920 | Implement the Python class `ExampleDialog` described below.
Class description:
Implement the ExampleDialog class.
Method signatures and docstrings:
- def CreateLayout(self): This Method is called automatically when Cinema 4D creates the Layout of the Dialog. Returns: bool: False if there was an error, otherwise True.... | Implement the Python class `ExampleDialog` described below.
Class description:
Implement the ExampleDialog class.
Method signatures and docstrings:
- def CreateLayout(self): This Method is called automatically when Cinema 4D creates the Layout of the Dialog. Returns: bool: False if there was an error, otherwise True.... | b1ea3fce533df34094bc3d0bd6460dfb84306e53 | <|skeleton|>
class ExampleDialog:
def CreateLayout(self):
"""This Method is called automatically when Cinema 4D creates the Layout of the Dialog. Returns: bool: False if there was an error, otherwise True."""
<|body_0|>
def Command(self, messageId, bc):
"""This Method is called automat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExampleDialog:
def CreateLayout(self):
"""This Method is called automatically when Cinema 4D creates the Layout of the Dialog. Returns: bool: False if there was an error, otherwise True."""
self.SetTitle('This is an example Dialog')
self.AddDlgGroup(c4d.DLG_OK | c4d.DLG_CANCEL)
... | the_stack_v2_python_sparse | plugins/py-ies_meta_r12/py-ies-meta_loader.pyp | PluginCafe/cinema4d_py_sdk_extended | train | 112 | |
aeaed8de414b3a6dc826524e7d24600dbfc657d0 | [
"range = max(nums) + 1\ncounts = [0] * range\nfor num in nums:\n counts[num] += 1\nidx = 0\nfor i, count in enumerate(counts):\n while count > 0:\n nums[idx] = i\n idx += 1\n count -= 1",
"def swap(a, i, j):\n temp = arr[i]\n arr[i] = arr[j]\n arr[j] = temp\nzero_idx = 0\nfor i... | <|body_start_0|>
range = max(nums) + 1
counts = [0] * range
for num in nums:
counts[num] += 1
idx = 0
for i, count in enumerate(counts):
while count > 0:
nums[idx] = i
idx += 1
count -= 1
<|end_body_0|>
<|bo... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def sortColors(self, nums):
"""This is a simple counting sort solution for the problem"""
<|body_0|>
def sort_colors_2(self, arr):
"""Second approach. Two pass still. Shift all zeros to beginning of the list in one scan. Shift all ones in second scan."""
... | stack_v2_sparse_classes_36k_train_002966 | 3,103 | no_license | [
{
"docstring": "This is a simple counting sort solution for the problem",
"name": "sortColors",
"signature": "def sortColors(self, nums)"
},
{
"docstring": "Second approach. Two pass still. Shift all zeros to beginning of the list in one scan. Shift all ones in second scan.",
"name": "sort_c... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortColors(self, nums): This is a simple counting sort solution for the problem
- def sort_colors_2(self, arr): Second approach. Two pass still. Shift all zeros to beginning ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortColors(self, nums): This is a simple counting sort solution for the problem
- def sort_colors_2(self, arr): Second approach. Two pass still. Shift all zeros to beginning ... | 8da310a8bbaf5369be2448e8de72d28eed1a5410 | <|skeleton|>
class Solution:
def sortColors(self, nums):
"""This is a simple counting sort solution for the problem"""
<|body_0|>
def sort_colors_2(self, arr):
"""Second approach. Two pass still. Shift all zeros to beginning of the list in one scan. Shift all ones in second scan."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def sortColors(self, nums):
"""This is a simple counting sort solution for the problem"""
range = max(nums) + 1
counts = [0] * range
for num in nums:
counts[num] += 1
idx = 0
for i, count in enumerate(counts):
while count > 0:
... | the_stack_v2_python_sparse | leetcode/75_sort_colors.py | varunkudva/Programming | train | 0 | |
2e6c8a09c9640b5f7aa0c6933f1c02fcf95bcd69 | [
"self._cmd = cmd\nself._preexec_fn = preexec_fn\nself._timeout_secs = timeout_secs",
"try:\n subprocess.check_call(self._cmd, timeout=self._timeout_secs, shell=True, preexec_fn=self._preexec_fn)\n return (True, None)\nexcept subprocess.CalledProcessError as reason:\n return (False, str(reason))\nexcept s... | <|body_start_0|>
self._cmd = cmd
self._preexec_fn = preexec_fn
self._timeout_secs = timeout_secs
<|end_body_0|>
<|body_start_1|>
try:
subprocess.check_call(self._cmd, timeout=self._timeout_secs, shell=True, preexec_fn=self._preexec_fn)
return (True, None)
... | ShellHealthCheck | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ShellHealthCheck:
def __init__(self, cmd, preexec_fn=None, timeout_secs=None):
"""Initialize with the commmand we would like to call. :param cmd: Command to execute that is expected to have a 0 return code on success. :type cmd: str :param preexec_fn: Callable to invoke just before the c... | stack_v2_sparse_classes_36k_train_002967 | 2,179 | permissive | [
{
"docstring": "Initialize with the commmand we would like to call. :param cmd: Command to execute that is expected to have a 0 return code on success. :type cmd: str :param preexec_fn: Callable to invoke just before the child shell process is executed. :type preexec_fn: callable :param timeout_secs: Timeout in... | 2 | stack_v2_sparse_classes_30k_train_000081 | Implement the Python class `ShellHealthCheck` described below.
Class description:
Implement the ShellHealthCheck class.
Method signatures and docstrings:
- def __init__(self, cmd, preexec_fn=None, timeout_secs=None): Initialize with the commmand we would like to call. :param cmd: Command to execute that is expected t... | Implement the Python class `ShellHealthCheck` described below.
Class description:
Implement the ShellHealthCheck class.
Method signatures and docstrings:
- def __init__(self, cmd, preexec_fn=None, timeout_secs=None): Initialize with the commmand we would like to call. :param cmd: Command to execute that is expected t... | 88dddb51ed9ad070340edb33eef9fd12745b9f8a | <|skeleton|>
class ShellHealthCheck:
def __init__(self, cmd, preexec_fn=None, timeout_secs=None):
"""Initialize with the commmand we would like to call. :param cmd: Command to execute that is expected to have a 0 return code on success. :type cmd: str :param preexec_fn: Callable to invoke just before the c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ShellHealthCheck:
def __init__(self, cmd, preexec_fn=None, timeout_secs=None):
"""Initialize with the commmand we would like to call. :param cmd: Command to execute that is expected to have a 0 return code on success. :type cmd: str :param preexec_fn: Callable to invoke just before the child shell pro... | the_stack_v2_python_sparse | Chapter4/Aurora/src/main/python/apache/aurora/common/health_check/shell.py | PacktPublishing/Mastering-Mesos | train | 12 | |
bf5c591488cc48dc66f8e75f8670472dada4dbf4 | [
"node_list = response.xpath(\"//tr[@class='even'] | //tr[@class='odd']\")\nfor node in node_list:\n item = TenmultiItem()\n item['position_name'] = node.xpath('./td[1]/a/text()').extract_first()\n item['position_link'] = 'https://hr.tencent.com/' + node.xpath('./td[1]/a/@href').extract_first()\n item['p... | <|body_start_0|>
node_list = response.xpath("//tr[@class='even'] | //tr[@class='odd']")
for node in node_list:
item = TenmultiItem()
item['position_name'] = node.xpath('./td[1]/a/text()').extract_first()
item['position_link'] = 'https://hr.tencent.com/' + node.xpath('... | TencMultiGradeSpider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TencMultiGradeSpider:
def parse(self, response):
"""列表页解析方法"""
<|body_0|>
def parse_detail(self, response):
"""解析详情页的响应内容"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
node_list = response.xpath("//tr[@class='even'] | //tr[@class='odd']")
... | stack_v2_sparse_classes_36k_train_002968 | 2,257 | no_license | [
{
"docstring": "列表页解析方法",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "解析详情页的响应内容",
"name": "parse_detail",
"signature": "def parse_detail(self, response)"
}
] | 2 | null | Implement the Python class `TencMultiGradeSpider` described below.
Class description:
Implement the TencMultiGradeSpider class.
Method signatures and docstrings:
- def parse(self, response): 列表页解析方法
- def parse_detail(self, response): 解析详情页的响应内容 | Implement the Python class `TencMultiGradeSpider` described below.
Class description:
Implement the TencMultiGradeSpider class.
Method signatures and docstrings:
- def parse(self, response): 列表页解析方法
- def parse_detail(self, response): 解析详情页的响应内容
<|skeleton|>
class TencMultiGradeSpider:
def parse(self, response)... | 298869fa9fb0291b9e364fbf4a6d8bd992840eb2 | <|skeleton|>
class TencMultiGradeSpider:
def parse(self, response):
"""列表页解析方法"""
<|body_0|>
def parse_detail(self, response):
"""解析详情页的响应内容"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TencMultiGradeSpider:
def parse(self, response):
"""列表页解析方法"""
node_list = response.xpath("//tr[@class='even'] | //tr[@class='odd']")
for node in node_list:
item = TenmultiItem()
item['position_name'] = node.xpath('./td[1]/a/text()').extract_first()
... | the_stack_v2_python_sparse | Scrapy/Tenc/TenMulti/TenMulti/spiders/tenc_multi_grade.py | AssassinHotstrip/personal_spider_pra | train | 0 | |
2abbdba1ee0368edab09cc38e7b874c08a189183 | [
"self.sess = sess\nself.name_map = {v.name: v for v in vars_to_update}\nself.ignore_mismatch = ignore_mismatch",
"assert isinstance(var, tf.Variable)\nname = var.op.name\nvarshape = tuple(var.get_shape().as_list())\nif varshape != value.shape:\n if np.prod(varshape) != np.prod(value.shape):\n if ignore_... | <|body_start_0|>
self.sess = sess
self.name_map = {v.name: v for v in vars_to_update}
self.ignore_mismatch = ignore_mismatch
<|end_body_0|>
<|body_start_1|>
assert isinstance(var, tf.Variable)
name = var.op.name
varshape = tuple(var.get_shape().as_list())
if vars... | Update the variables in a session | SessionUpdate | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SessionUpdate:
"""Update the variables in a session"""
def __init__(self, sess, vars_to_update, ignore_mismatch=False):
"""Args: sess (tf.Session): a session object vars_to_update: a collection of variables to update ignore_mismatch (bool): ignore failures when the value and the vari... | stack_v2_sparse_classes_36k_train_002969 | 10,466 | permissive | [
{
"docstring": "Args: sess (tf.Session): a session object vars_to_update: a collection of variables to update ignore_mismatch (bool): ignore failures when the value and the variable does not match.",
"name": "__init__",
"signature": "def __init__(self, sess, vars_to_update, ignore_mismatch=False)"
},
... | 3 | null | Implement the Python class `SessionUpdate` described below.
Class description:
Update the variables in a session
Method signatures and docstrings:
- def __init__(self, sess, vars_to_update, ignore_mismatch=False): Args: sess (tf.Session): a session object vars_to_update: a collection of variables to update ignore_mis... | Implement the Python class `SessionUpdate` described below.
Class description:
Update the variables in a session
Method signatures and docstrings:
- def __init__(self, sess, vars_to_update, ignore_mismatch=False): Args: sess (tf.Session): a session object vars_to_update: a collection of variables to update ignore_mis... | 1547a54e8546494614ca31c984a1bfd1d0e24b77 | <|skeleton|>
class SessionUpdate:
"""Update the variables in a session"""
def __init__(self, sess, vars_to_update, ignore_mismatch=False):
"""Args: sess (tf.Session): a session object vars_to_update: a collection of variables to update ignore_mismatch (bool): ignore failures when the value and the vari... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SessionUpdate:
"""Update the variables in a session"""
def __init__(self, sess, vars_to_update, ignore_mismatch=False):
"""Args: sess (tf.Session): a session object vars_to_update: a collection of variables to update ignore_mismatch (bool): ignore failures when the value and the variable does not... | the_stack_v2_python_sparse | tensorpack/tfutils/varmanip.py | tensorpack/tensorpack | train | 4,600 |
e42462dd0a4417d7d473fe26708c502fd5b28a28 | [
"self.ontology_file_path = path\nself.ontology = self.load_ontology()\nself.agent_requestable = self.ontology['system_requestable']\nself.user_requestable = self.ontology['user_requestable']\nself.slots_not_required_NLU = self.ontology['slots_not_required_NLU']\nself.slots_annotation = self.ontology['slots_annotati... | <|body_start_0|>
self.ontology_file_path = path
self.ontology = self.load_ontology()
self.agent_requestable = self.ontology['system_requestable']
self.user_requestable = self.ontology['user_requestable']
self.slots_not_required_NLU = self.ontology['slots_not_required_NLU']
... | Ontology is a class that loads ontology files (in .json format) into IAI MovieBot. | Ontology | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ontology:
"""Ontology is a class that loads ontology files (in .json format) into IAI MovieBot."""
def __init__(self, path):
"""Initializes the internal structures of the Domain Args: path: path to load the ontology from"""
<|body_0|>
def load_ontology(self):
"""... | stack_v2_sparse_classes_36k_train_002970 | 1,114 | permissive | [
{
"docstring": "Initializes the internal structures of the Domain Args: path: path to load the ontology from",
"name": "__init__",
"signature": "def __init__(self, path)"
},
{
"docstring": "Loads the ontology file Returns: nothing",
"name": "load_ontology",
"signature": "def load_ontolog... | 2 | stack_v2_sparse_classes_30k_train_009077 | Implement the Python class `Ontology` described below.
Class description:
Ontology is a class that loads ontology files (in .json format) into IAI MovieBot.
Method signatures and docstrings:
- def __init__(self, path): Initializes the internal structures of the Domain Args: path: path to load the ontology from
- def ... | Implement the Python class `Ontology` described below.
Class description:
Ontology is a class that loads ontology files (in .json format) into IAI MovieBot.
Method signatures and docstrings:
- def __init__(self, path): Initializes the internal structures of the Domain Args: path: path to load the ontology from
- def ... | 172966ba2b90e22037b17467d69068dad5e26b09 | <|skeleton|>
class Ontology:
"""Ontology is a class that loads ontology files (in .json format) into IAI MovieBot."""
def __init__(self, path):
"""Initializes the internal structures of the Domain Args: path: path to load the ontology from"""
<|body_0|>
def load_ontology(self):
"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Ontology:
"""Ontology is a class that loads ontology files (in .json format) into IAI MovieBot."""
def __init__(self, path):
"""Initializes the internal structures of the Domain Args: path: path to load the ontology from"""
self.ontology_file_path = path
self.ontology = self.load_... | the_stack_v2_python_sparse | moviebot/ontology/ontology.py | fseimb/moviebot-1 | train | 0 |
3a6aeef4edcd56416e6a73d27400accceaefdef3 | [
"chart = pygal.Bar()\nword_counter_list = Counter(word_cut_list).most_common(topk)\nx_labels = [word[0] for word in word_counter_list]\ny_values = [{'value': word[1], 'color': color} for word in word_counter_list]\nchart.title = title\nchart.x_labels = map(str, x_labels)\nchart.add('频次', y_values)\nchart.render_to_... | <|body_start_0|>
chart = pygal.Bar()
word_counter_list = Counter(word_cut_list).most_common(topk)
x_labels = [word[0] for word in word_counter_list]
y_values = [{'value': word[1], 'color': color} for word in word_counter_list]
chart.title = title
chart.x_labels = map(str,... | Chart | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Chart:
def chart_word_frequency(cls, app=None, word_cut_list=[], title=None, topk=20, color='green'):
"""高频词 条状图 :param app: :param word_cut_list: :param title: :return: url('static', 'pygal_chart_images')"""
<|body_0|>
def chart_word_positive(cls, app=None, word_positive_li... | stack_v2_sparse_classes_36k_train_002971 | 6,157 | no_license | [
{
"docstring": "高频词 条状图 :param app: :param word_cut_list: :param title: :return: url('static', 'pygal_chart_images')",
"name": "chart_word_frequency",
"signature": "def chart_word_frequency(cls, app=None, word_cut_list=[], title=None, topk=20, color='green')"
},
{
"docstring": "积极性词 条状图 通过积极词字典筛... | 4 | null | Implement the Python class `Chart` described below.
Class description:
Implement the Chart class.
Method signatures and docstrings:
- def chart_word_frequency(cls, app=None, word_cut_list=[], title=None, topk=20, color='green'): 高频词 条状图 :param app: :param word_cut_list: :param title: :return: url('static', 'pygal_cha... | Implement the Python class `Chart` described below.
Class description:
Implement the Chart class.
Method signatures and docstrings:
- def chart_word_frequency(cls, app=None, word_cut_list=[], title=None, topk=20, color='green'): 高频词 条状图 :param app: :param word_cut_list: :param title: :return: url('static', 'pygal_cha... | 9afe9ec7809529af05a971993d9ee17421364f76 | <|skeleton|>
class Chart:
def chart_word_frequency(cls, app=None, word_cut_list=[], title=None, topk=20, color='green'):
"""高频词 条状图 :param app: :param word_cut_list: :param title: :return: url('static', 'pygal_chart_images')"""
<|body_0|>
def chart_word_positive(cls, app=None, word_positive_li... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Chart:
def chart_word_frequency(cls, app=None, word_cut_list=[], title=None, topk=20, color='green'):
"""高频词 条状图 :param app: :param word_cut_list: :param title: :return: url('static', 'pygal_chart_images')"""
chart = pygal.Bar()
word_counter_list = Counter(word_cut_list).most_common(to... | the_stack_v2_python_sparse | tutorial/L46数据分析和图表可视化/jd_spider/service/pygal.py | liuxiaoxiao666/python_study | train | 0 | |
403e9ea96fbe85646a9b856d519ef02afda2cc45 | [
"def memoize(i, j):\n if i == 0:\n return 1\n if j == 0:\n return 1\n if cache[i][j] != 0:\n return cache[i][j]\n cache[i][j] = memoize(i, j - 1) + memoize(i - 1, j)\n return cache[i][j]\nif m <= 0 or n <= 0:\n return 0\ncache = [[0 for _ in range(n)] for _ in range(m)]\nretur... | <|body_start_0|>
def memoize(i, j):
if i == 0:
return 1
if j == 0:
return 1
if cache[i][j] != 0:
return cache[i][j]
cache[i][j] = memoize(i, j - 1) + memoize(i - 1, j)
return cache[i][j]
if m <= 0... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def uniquePaths(self, m: int, n: int) -> int:
"""状态转移方程：自顶向下 dp[m][n] = dp[m][n-1] + dp[m-1][n]"""
<|body_0|>
def uniquePaths1(self, m: int, n: int) -> int:
"""状态转移方程：自底向上 dp[m][n] = dp[m][n-1] + dp[m-1][n]"""
<|body_1|>
def uniquePaths2(self, ... | stack_v2_sparse_classes_36k_train_002972 | 3,174 | permissive | [
{
"docstring": "状态转移方程：自顶向下 dp[m][n] = dp[m][n-1] + dp[m-1][n]",
"name": "uniquePaths",
"signature": "def uniquePaths(self, m: int, n: int) -> int"
},
{
"docstring": "状态转移方程：自底向上 dp[m][n] = dp[m][n-1] + dp[m-1][n]",
"name": "uniquePaths1",
"signature": "def uniquePaths1(self, m: int, n: ... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniquePaths(self, m: int, n: int) -> int: 状态转移方程：自顶向下 dp[m][n] = dp[m][n-1] + dp[m-1][n]
- def uniquePaths1(self, m: int, n: int) -> int: 状态转移方程：自底向上 dp[m][n] = dp[m][n-1] + ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniquePaths(self, m: int, n: int) -> int: 状态转移方程：自顶向下 dp[m][n] = dp[m][n-1] + dp[m-1][n]
- def uniquePaths1(self, m: int, n: int) -> int: 状态转移方程：自底向上 dp[m][n] = dp[m][n-1] + ... | e8a1c6cae6547cbcb6e8494be6df685f3e7c837c | <|skeleton|>
class Solution:
def uniquePaths(self, m: int, n: int) -> int:
"""状态转移方程：自顶向下 dp[m][n] = dp[m][n-1] + dp[m-1][n]"""
<|body_0|>
def uniquePaths1(self, m: int, n: int) -> int:
"""状态转移方程：自底向上 dp[m][n] = dp[m][n-1] + dp[m-1][n]"""
<|body_1|>
def uniquePaths2(self, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def uniquePaths(self, m: int, n: int) -> int:
"""状态转移方程：自顶向下 dp[m][n] = dp[m][n-1] + dp[m-1][n]"""
def memoize(i, j):
if i == 0:
return 1
if j == 0:
return 1
if cache[i][j] != 0:
return cache[i][j]
... | the_stack_v2_python_sparse | 62-unique-paths.py | yuenliou/leetcode | train | 0 | |
94239537bd6c69e1b6ee9abcdb4f8b5907df5e21 | [
"flag = 1 if x > -1 else -1\npositiveX = flag * x\nstrX = str(positiveX)\nrevsedX = strX[::-1]\nrevsedIntX = int(revsedX) * flag\nif revsedIntX < -2 ** 31 or revsedIntX > 2 ** 31 - 1:\n revsedIntX = 0\nreturn revsedIntX",
"flag = 1 if x > -1 else -1\npositiveX = flag * x\nres = 0\nwhile positiveX > 0:\n res... | <|body_start_0|>
flag = 1 if x > -1 else -1
positiveX = flag * x
strX = str(positiveX)
revsedX = strX[::-1]
revsedIntX = int(revsedX) * flag
if revsedIntX < -2 ** 31 or revsedIntX > 2 ** 31 - 1:
revsedIntX = 0
return revsedIntX
<|end_body_0|>
<|body_s... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverse2(self, x):
""":type x: int :rtype: int"""
<|body_0|>
def reverse(self, x):
""":type x: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
flag = 1 if x > -1 else -1
positiveX = flag * x
strX = str(p... | stack_v2_sparse_classes_36k_train_002973 | 790 | no_license | [
{
"docstring": ":type x: int :rtype: int",
"name": "reverse2",
"signature": "def reverse2(self, x)"
},
{
"docstring": ":type x: int :rtype: int",
"name": "reverse",
"signature": "def reverse(self, x)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016646 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse2(self, x): :type x: int :rtype: int
- def reverse(self, x): :type x: int :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverse2(self, x): :type x: int :rtype: int
- def reverse(self, x): :type x: int :rtype: int
<|skeleton|>
class Solution:
def reverse2(self, x):
""":type x: int... | 238995bd23c8a6c40c6035890e94baa2473d4bbc | <|skeleton|>
class Solution:
def reverse2(self, x):
""":type x: int :rtype: int"""
<|body_0|>
def reverse(self, x):
""":type x: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverse2(self, x):
""":type x: int :rtype: int"""
flag = 1 if x > -1 else -1
positiveX = flag * x
strX = str(positiveX)
revsedX = strX[::-1]
revsedIntX = int(revsedX) * flag
if revsedIntX < -2 ** 31 or revsedIntX > 2 ** 31 - 1:
... | the_stack_v2_python_sparse | problems/ReverseInteger.py | wan-catherine/Leetcode | train | 5 | |
9bb6b023b0c1f489f9175d0d8326b86d147ae98c | [
"_input = DataFrame({'a': [0, 1, 'b']})\n_expected = DataFrame({'a': [0, 1, 2]})\n_groupings = [{'operator': 'replace', 'columns': ['a'], 'value': ['b', 2]}]\n_vc = VariableCleaner(_input)\n_vc.clean(_groupings)\nassert_frame_equal(_expected, _vc.frame)",
"_input = DataFrame({'a': [0, 1, 'b']})\n_expected = DataF... | <|body_start_0|>
_input = DataFrame({'a': [0, 1, 'b']})
_expected = DataFrame({'a': [0, 1, 2]})
_groupings = [{'operator': 'replace', 'columns': ['a'], 'value': ['b', 2]}]
_vc = VariableCleaner(_input)
_vc.clean(_groupings)
assert_frame_equal(_expected, _vc.frame)
<|end_b... | CleanReplaceTests | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CleanReplaceTests:
def test_clean_replace_string_values():
"""Replace strings in a column."""
<|body_0|>
def test_clean_replace_int_values():
"""Replace an int in a column."""
<|body_1|>
def test_clean_replace_nan_values():
"""Replace NaN values ... | stack_v2_sparse_classes_36k_train_002974 | 1,560 | permissive | [
{
"docstring": "Replace strings in a column.",
"name": "test_clean_replace_string_values",
"signature": "def test_clean_replace_string_values()"
},
{
"docstring": "Replace an int in a column.",
"name": "test_clean_replace_int_values",
"signature": "def test_clean_replace_int_values()"
... | 3 | stack_v2_sparse_classes_30k_train_020416 | Implement the Python class `CleanReplaceTests` described below.
Class description:
Implement the CleanReplaceTests class.
Method signatures and docstrings:
- def test_clean_replace_string_values(): Replace strings in a column.
- def test_clean_replace_int_values(): Replace an int in a column.
- def test_clean_replace... | Implement the Python class `CleanReplaceTests` described below.
Class description:
Implement the CleanReplaceTests class.
Method signatures and docstrings:
- def test_clean_replace_string_values(): Replace strings in a column.
- def test_clean_replace_int_values(): Replace an int in a column.
- def test_clean_replace... | 2e89bc55a61ce2a4ce77646bb427f5b3040f672c | <|skeleton|>
class CleanReplaceTests:
def test_clean_replace_string_values():
"""Replace strings in a column."""
<|body_0|>
def test_clean_replace_int_values():
"""Replace an int in a column."""
<|body_1|>
def test_clean_replace_nan_values():
"""Replace NaN values ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CleanReplaceTests:
def test_clean_replace_string_values():
"""Replace strings in a column."""
_input = DataFrame({'a': [0, 1, 'b']})
_expected = DataFrame({'a': [0, 1, 2]})
_groupings = [{'operator': 'replace', 'columns': ['a'], 'value': ['b', 2]}]
_vc = VariableCleaner... | the_stack_v2_python_sparse | numom2b_preprocessing/unittests/cleaning_tests/test_replace.py | hayesall/nuMoM2b_preprocessing | train | 2 | |
4488f5a28e056f5348d9a6fe51aca8f41c006500 | [
"@wraps(func)\ndef wrapper(*args, **kwargs):\n print(' \\n\\n _ooOoo_\\n o8888888o\\n 88\" . \"88\\n (| -_- |)\\n O\\\\ = /O\\n ____/`---\\'\\\\____\\n .\\' \\\\| ... | <|body_start_0|>
@wraps(func)
def wrapper(*args, **kwargs):
print(' \n\n _ooOoo_\n o8888888o\n 88" . "88\n (| -_- |)\n O\\ = /O\n ____/`---\'\\____\n ... | DecoratorUtil | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecoratorUtil:
def buddha_bless_me(func):
"""佛祖保佑"""
<|body_0|>
def sleipmon_bless_me(func):
"""神兽羊驼保佑"""
<|body_1|>
def tangbohu(func):
"""佛祖保佑"""
<|body_2|>
def no_bug_forever(func):
"""永无bug，一个永无 bug 的文字瀑布在程序运行的时候慢慢晃过"""
... | stack_v2_sparse_classes_36k_train_002975 | 4,089 | no_license | [
{
"docstring": "佛祖保佑",
"name": "buddha_bless_me",
"signature": "def buddha_bless_me(func)"
},
{
"docstring": "神兽羊驼保佑",
"name": "sleipmon_bless_me",
"signature": "def sleipmon_bless_me(func)"
},
{
"docstring": "佛祖保佑",
"name": "tangbohu",
"signature": "def tangbohu(func)"
... | 5 | null | Implement the Python class `DecoratorUtil` described below.
Class description:
Implement the DecoratorUtil class.
Method signatures and docstrings:
- def buddha_bless_me(func): 佛祖保佑
- def sleipmon_bless_me(func): 神兽羊驼保佑
- def tangbohu(func): 佛祖保佑
- def no_bug_forever(func): 永无bug，一个永无 bug 的文字瀑布在程序运行的时候慢慢晃过
- def time... | Implement the Python class `DecoratorUtil` described below.
Class description:
Implement the DecoratorUtil class.
Method signatures and docstrings:
- def buddha_bless_me(func): 佛祖保佑
- def sleipmon_bless_me(func): 神兽羊驼保佑
- def tangbohu(func): 佛祖保佑
- def no_bug_forever(func): 永无bug，一个永无 bug 的文字瀑布在程序运行的时候慢慢晃过
- def time... | 32e64be10a6cd2856850f6720d70b4c6e7033f4e | <|skeleton|>
class DecoratorUtil:
def buddha_bless_me(func):
"""佛祖保佑"""
<|body_0|>
def sleipmon_bless_me(func):
"""神兽羊驼保佑"""
<|body_1|>
def tangbohu(func):
"""佛祖保佑"""
<|body_2|>
def no_bug_forever(func):
"""永无bug，一个永无 bug 的文字瀑布在程序运行的时候慢慢晃过"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DecoratorUtil:
def buddha_bless_me(func):
"""佛祖保佑"""
@wraps(func)
def wrapper(*args, **kwargs):
print(' \n\n _ooOoo_\n o8888888o\n 88" . "88\n (| -_- |)\n O\\ = ... | the_stack_v2_python_sparse | Report/DecoratorUtil.py | newjokker/PyUtil | train | 0 | |
24a62a9b5454dd71d0b49e60ee00322806989144 | [
"timestamp = self._GetRowValue(query_hash, row, value_name)\nif timestamp is None:\n return None\nreturn dfdatetime_posix_time.PosixTime(timestamp=timestamp)",
"query_hash = hash(query)\nevent_data = MacOSApplicationUsageEventData()\nevent_data.application = self._GetRowValue(query_hash, row, 'app_path')\neven... | <|body_start_0|>
timestamp = self._GetRowValue(query_hash, row, value_name)
if timestamp is None:
return None
return dfdatetime_posix_time.PosixTime(timestamp=timestamp)
<|end_body_0|>
<|body_start_1|>
query_hash = hash(query)
event_data = MacOSApplicationUsageEventD... | SQLite parser plugin for MacOS application usage database files. The MacOS application usage database is typically stored in: /var/db/application_usage.sqlite Application usage is a SQLite database that logs down entries triggered by NSWorkspaceWillLaunchApplicationNotification and NSWorkspaceDidTerminateApplicationNot... | MacOSApplicationUsagePlugin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MacOSApplicationUsagePlugin:
"""SQLite parser plugin for MacOS application usage database files. The MacOS application usage database is typically stored in: /var/db/application_usage.sqlite Application usage is a SQLite database that logs down entries triggered by NSWorkspaceWillLaunchApplicatio... | stack_v2_sparse_classes_36k_train_002976 | 4,191 | permissive | [
{
"docstring": "Retrieves a date and time value from the row. Args: query_hash (int): hash of the query, that uniquely identifies the query that produced the row. row (sqlite3.Row): row. value_name (str): name of the value. Returns: dfdatetime.PosixTime: date and time value or None if not available.",
"name... | 2 | null | Implement the Python class `MacOSApplicationUsagePlugin` described below.
Class description:
SQLite parser plugin for MacOS application usage database files. The MacOS application usage database is typically stored in: /var/db/application_usage.sqlite Application usage is a SQLite database that logs down entries trigg... | Implement the Python class `MacOSApplicationUsagePlugin` described below.
Class description:
SQLite parser plugin for MacOS application usage database files. The MacOS application usage database is typically stored in: /var/db/application_usage.sqlite Application usage is a SQLite database that logs down entries trigg... | d6022f8cfebfddf2d08ab2d300a41b61f3349933 | <|skeleton|>
class MacOSApplicationUsagePlugin:
"""SQLite parser plugin for MacOS application usage database files. The MacOS application usage database is typically stored in: /var/db/application_usage.sqlite Application usage is a SQLite database that logs down entries triggered by NSWorkspaceWillLaunchApplicatio... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MacOSApplicationUsagePlugin:
"""SQLite parser plugin for MacOS application usage database files. The MacOS application usage database is typically stored in: /var/db/application_usage.sqlite Application usage is a SQLite database that logs down entries triggered by NSWorkspaceWillLaunchApplicationNotification... | the_stack_v2_python_sparse | plaso/parsers/sqlite_plugins/macos_appusage.py | log2timeline/plaso | train | 1,506 |
df01075832f54c7c78874828d901c42eb7348d1c | [
"v = NSView.alloc().initWithFrame_(NSMakeRect(0, 0, 1, 1))\nr = RendererCocoa(v)\nself.assertEqual(r.nsview, v)",
"import matplotlib.transforms as transforms\nm = transforms.Affine2D.identity()\npass",
"star_path = Path.unit_regular_star(10)\nr = RendererCocoa(None, None)\nbpath = r.mpl_to_bezier_path(star_path... | <|body_start_0|>
v = NSView.alloc().initWithFrame_(NSMakeRect(0, 0, 1, 1))
r = RendererCocoa(v)
self.assertEqual(r.nsview, v)
<|end_body_0|>
<|body_start_1|>
import matplotlib.transforms as transforms
m = transforms.Affine2D.identity()
pass
<|end_body_1|>
<|body_start_2... | Unit tests for RendererCocoa | RendererCocoaTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RendererCocoaTests:
"""Unit tests for RendererCocoa"""
def test_init_sets_properties(self):
"""test_init"""
<|body_0|>
def test_mpl_to_affine_transform(self):
"""test_mpl_to_affine_transform"""
<|body_1|>
def test_mpl_to_bezier_path(self):
""... | stack_v2_sparse_classes_36k_train_002977 | 24,942 | no_license | [
{
"docstring": "test_init",
"name": "test_init_sets_properties",
"signature": "def test_init_sets_properties(self)"
},
{
"docstring": "test_mpl_to_affine_transform",
"name": "test_mpl_to_affine_transform",
"signature": "def test_mpl_to_affine_transform(self)"
},
{
"docstring": "t... | 4 | stack_v2_sparse_classes_30k_train_001715 | Implement the Python class `RendererCocoaTests` described below.
Class description:
Unit tests for RendererCocoa
Method signatures and docstrings:
- def test_init_sets_properties(self): test_init
- def test_mpl_to_affine_transform(self): test_mpl_to_affine_transform
- def test_mpl_to_bezier_path(self): test_mpl_to_be... | Implement the Python class `RendererCocoaTests` described below.
Class description:
Unit tests for RendererCocoa
Method signatures and docstrings:
- def test_init_sets_properties(self): test_init
- def test_mpl_to_affine_transform(self): test_mpl_to_affine_transform
- def test_mpl_to_bezier_path(self): test_mpl_to_be... | e648a6acd6230025e422f15b0a3573a5439d5ab4 | <|skeleton|>
class RendererCocoaTests:
"""Unit tests for RendererCocoa"""
def test_init_sets_properties(self):
"""test_init"""
<|body_0|>
def test_mpl_to_affine_transform(self):
"""test_mpl_to_affine_transform"""
<|body_1|>
def test_mpl_to_bezier_path(self):
""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RendererCocoaTests:
"""Unit tests for RendererCocoa"""
def test_init_sets_properties(self):
"""test_init"""
v = NSView.alloc().initWithFrame_(NSMakeRect(0, 0, 1, 1))
r = RendererCocoa(v)
self.assertEqual(r.nsview, v)
def test_mpl_to_affine_transform(self):
"""... | the_stack_v2_python_sparse | CocoaInteraction/cocoa_backend.py | zoccolan/eyetracker | train | 0 |
69cd7a004977df6951dda67690458c86b1397761 | [
"if isinstance(expressions, tuple):\n expressions = [expressions]\nmasks = map(list, [comp(self.loc[(slice(None), method), :], thr).any(axis=1) for method, comp, thr in expressions])\nif len(masks) > 1:\n masks = numpy.logical_and(*masks)\nelse:\n masks = masks[0]\nidx = [f for f in masks for _ in xrange(l... | <|body_start_0|>
if isinstance(expressions, tuple):
expressions = [expressions]
masks = map(list, [comp(self.loc[(slice(None), method), :], thr).any(axis=1) for method, comp, thr in expressions])
if len(masks) > 1:
masks = numpy.logical_and(*masks)
else:
... | A :class:`~Fred2.Core.Result.EpitopePredictionResult` object is a DataFrame with multi-indexing, where column Ids are the prediction model (i.e HLA :class:`~Fred2.Core.Allele.Allele` for epitope prediction), row ID the target of the prediction (i.e. :class:`~Fred2.Core.Peptide.Peptide`) and the second row ID the predic... | EpitopePredictionResult | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EpitopePredictionResult:
"""A :class:`~Fred2.Core.Result.EpitopePredictionResult` object is a DataFrame with multi-indexing, where column Ids are the prediction model (i.e HLA :class:`~Fred2.Core.Allele.Allele` for epitope prediction), row ID the target of the prediction (i.e. :class:`~Fred2.Core... | stack_v2_sparse_classes_36k_train_002978 | 14,645 | permissive | [
{
"docstring": "Filters a result data frame based on a specified expression consisting of a list of triple with (method_name, comparator, threshold). The expression is applied to each row. If any of the columns fulfill the criteria the row remains. :param list((str,comparator,float)) expressions: A list of trip... | 2 | stack_v2_sparse_classes_30k_train_017773 | Implement the Python class `EpitopePredictionResult` described below.
Class description:
A :class:`~Fred2.Core.Result.EpitopePredictionResult` object is a DataFrame with multi-indexing, where column Ids are the prediction model (i.e HLA :class:`~Fred2.Core.Allele.Allele` for epitope prediction), row ID the target of t... | Implement the Python class `EpitopePredictionResult` described below.
Class description:
A :class:`~Fred2.Core.Result.EpitopePredictionResult` object is a DataFrame with multi-indexing, where column Ids are the prediction model (i.e HLA :class:`~Fred2.Core.Allele.Allele` for epitope prediction), row ID the target of t... | b3e54c8c4ed12b780b61f74672e9667245a7bb78 | <|skeleton|>
class EpitopePredictionResult:
"""A :class:`~Fred2.Core.Result.EpitopePredictionResult` object is a DataFrame with multi-indexing, where column Ids are the prediction model (i.e HLA :class:`~Fred2.Core.Allele.Allele` for epitope prediction), row ID the target of the prediction (i.e. :class:`~Fred2.Core... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EpitopePredictionResult:
"""A :class:`~Fred2.Core.Result.EpitopePredictionResult` object is a DataFrame with multi-indexing, where column Ids are the prediction model (i.e HLA :class:`~Fred2.Core.Allele.Allele` for epitope prediction), row ID the target of the prediction (i.e. :class:`~Fred2.Core.Peptide.Pept... | the_stack_v2_python_sparse | Fred2/Core/Result.py | FRED-2/Fred2 | train | 42 |
6fc65ffd5d0fffc67d1404693d6c601dedca93ce | [
"self.left_pq = []\nself.right_pq = []\nself.l = 0",
"self.l += 1\nif len(self.right_pq) > len(self.left_pq):\n rightmin = heappop(self.right_pq)\n heappush(self.left_pq, -min(num, rightmin))\n heappush(self.right_pq, max(num, rightmin))\n return\nheappush(self.left_pq, -num)\nheappush(self.right_pq, ... | <|body_start_0|>
self.left_pq = []
self.right_pq = []
self.l = 0
<|end_body_0|>
<|body_start_1|>
self.l += 1
if len(self.right_pq) > len(self.left_pq):
rightmin = heappop(self.right_pq)
heappush(self.left_pq, -min(num, rightmin))
heappush(self... | MedianFinder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MedianFinder:
def __init__(self):
"""initialize your data structure here."""
<|body_0|>
def addNum(self, num):
""":type num: int :rtype: void"""
<|body_1|>
def findMedian(self):
""":rtype: float"""
<|body_2|>
<|end_skeleton|>
<|body_sta... | stack_v2_sparse_classes_36k_train_002979 | 1,282 | no_license | [
{
"docstring": "initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": ":type num: int :rtype: void",
"name": "addNum",
"signature": "def addNum(self, num)"
},
{
"docstring": ":rtype: float",
"name": "findMedian",
"s... | 3 | stack_v2_sparse_classes_30k_train_003160 | Implement the Python class `MedianFinder` described below.
Class description:
Implement the MedianFinder class.
Method signatures and docstrings:
- def __init__(self): initialize your data structure here.
- def addNum(self, num): :type num: int :rtype: void
- def findMedian(self): :rtype: float | Implement the Python class `MedianFinder` described below.
Class description:
Implement the MedianFinder class.
Method signatures and docstrings:
- def __init__(self): initialize your data structure here.
- def addNum(self, num): :type num: int :rtype: void
- def findMedian(self): :rtype: float
<|skeleton|>
class Me... | b0ce69985c51a9a794397cd98a996fca0e91d7d1 | <|skeleton|>
class MedianFinder:
def __init__(self):
"""initialize your data structure here."""
<|body_0|>
def addNum(self, num):
""":type num: int :rtype: void"""
<|body_1|>
def findMedian(self):
""":rtype: float"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MedianFinder:
def __init__(self):
"""initialize your data structure here."""
self.left_pq = []
self.right_pq = []
self.l = 0
def addNum(self, num):
""":type num: int :rtype: void"""
self.l += 1
if len(self.right_pq) > len(self.left_pq):
... | the_stack_v2_python_sparse | Solutions/295-Find-Median-from-Data-Stream/python.py | JerryHu1994/LeetCode-Practice | train | 0 | |
3979e7236a2560c99b09f91a9097478c850e43d4 | [
"global result\nif len(s) < 4 or len(s) > 12:\n return result\nself.search_helper(s, 0, 0)\nreturn result",
"global COUNT\nglobal segment\nglobal result\nif seg_id == COUNT:\n if start == len(s):\n result.append('.'.join(segment))\n return\nif start == len(s):\n return\nif s[start] == '0':\n ... | <|body_start_0|>
global result
if len(s) < 4 or len(s) > 12:
return result
self.search_helper(s, 0, 0)
return result
<|end_body_0|>
<|body_start_1|>
global COUNT
global segment
global result
if seg_id == COUNT:
if start == len(s):
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def restore_ip_addresses(self, s: str) -> List[str]:
"""修复ip Args: s: 字符串 Returns: ip的list"""
<|body_0|>
def search_helper(self, s: str, seg_id: int, start: int) -> None:
"""查找帮助类 Args: s: 字符串 seg_id: 区域id start: 开始位置 Returns: None"""
<|body_1|>
<|... | stack_v2_sparse_classes_36k_train_002980 | 2,850 | permissive | [
{
"docstring": "修复ip Args: s: 字符串 Returns: ip的list",
"name": "restore_ip_addresses",
"signature": "def restore_ip_addresses(self, s: str) -> List[str]"
},
{
"docstring": "查找帮助类 Args: s: 字符串 seg_id: 区域id start: 开始位置 Returns: None",
"name": "search_helper",
"signature": "def search_helper(... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def restore_ip_addresses(self, s: str) -> List[str]: 修复ip Args: s: 字符串 Returns: ip的list
- def search_helper(self, s: str, seg_id: int, start: int) -> None: 查找帮助类 Args: s: 字符串 seg... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def restore_ip_addresses(self, s: str) -> List[str]: 修复ip Args: s: 字符串 Returns: ip的list
- def search_helper(self, s: str, seg_id: int, start: int) -> None: 查找帮助类 Args: s: 字符串 seg... | 50f35eef6a0ad63173efed10df3c835b1dceaa3f | <|skeleton|>
class Solution:
def restore_ip_addresses(self, s: str) -> List[str]:
"""修复ip Args: s: 字符串 Returns: ip的list"""
<|body_0|>
def search_helper(self, s: str, seg_id: int, start: int) -> None:
"""查找帮助类 Args: s: 字符串 seg_id: 区域id start: 开始位置 Returns: None"""
<|body_1|>
<|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def restore_ip_addresses(self, s: str) -> List[str]:
"""修复ip Args: s: 字符串 Returns: ip的list"""
global result
if len(s) < 4 or len(s) > 12:
return result
self.search_helper(s, 0, 0)
return result
def search_helper(self, s: str, seg_id: int, star... | the_stack_v2_python_sparse | src/leetcodepython/string/restore_ip_addresses_93.py | zhangyu345293721/leetcode | train | 101 | |
add111fd03470d7634a0f93240a92f8aca439b24 | [
"super().__init__(graph)\nself.op_to_module_dict = dict()\nself._num_products_made = 0\nself.starting_op_names = starting_op_names\nself._valid_ops = valid_ops\nself.processed_ops = set()\nself._sub_graph_matcher = sub_graph_matcher.SubGraphMatcher(self._graph, self.op_to_module_dict, self._valid_ops)",
"default_... | <|body_start_0|>
super().__init__(graph)
self.op_to_module_dict = dict()
self._num_products_made = 0
self.starting_op_names = starting_op_names
self._valid_ops = valid_ops
self.processed_ops = set()
self._sub_graph_matcher = sub_graph_matcher.SubGraphMatcher(self.... | Module identifier using graph structures | StructureModuleIdentifier | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StructureModuleIdentifier:
"""Module identifier using graph structures"""
def __init__(self, graph: tf.Graph, starting_op_names: List[str], valid_ops: Set[tf.Operation]):
"""Initializer for ModuleIdentifier :param graph: Tensorflow graph to represent using connected graph. :param sta... | stack_v2_sparse_classes_36k_train_002981 | 4,653 | permissive | [
{
"docstring": "Initializer for ModuleIdentifier :param graph: Tensorflow graph to represent using connected graph. :param starting_op_names: Names of the starting ops of the model. :param valid_ops: Set of tf operations that are valid",
"name": "__init__",
"signature": "def __init__(self, graph: tf.Gra... | 2 | null | Implement the Python class `StructureModuleIdentifier` described below.
Class description:
Module identifier using graph structures
Method signatures and docstrings:
- def __init__(self, graph: tf.Graph, starting_op_names: List[str], valid_ops: Set[tf.Operation]): Initializer for ModuleIdentifier :param graph: Tensor... | Implement the Python class `StructureModuleIdentifier` described below.
Class description:
Module identifier using graph structures
Method signatures and docstrings:
- def __init__(self, graph: tf.Graph, starting_op_names: List[str], valid_ops: Set[tf.Operation]): Initializer for ModuleIdentifier :param graph: Tensor... | 5a406e657082b6a4f6e4bf48f0e46e085cb1e351 | <|skeleton|>
class StructureModuleIdentifier:
"""Module identifier using graph structures"""
def __init__(self, graph: tf.Graph, starting_op_names: List[str], valid_ops: Set[tf.Operation]):
"""Initializer for ModuleIdentifier :param graph: Tensorflow graph to represent using connected graph. :param sta... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StructureModuleIdentifier:
"""Module identifier using graph structures"""
def __init__(self, graph: tf.Graph, starting_op_names: List[str], valid_ops: Set[tf.Operation]):
"""Initializer for ModuleIdentifier :param graph: Tensorflow graph to represent using connected graph. :param starting_op_name... | the_stack_v2_python_sparse | TrainingExtensions/tensorflow/src/python/aimet_tensorflow/common/module_identifier.py | quic/aimet | train | 1,676 |
372bfd1ed69120e9870b44c6a7b0104164ce7e9a | [
"self._descriptors = 'descriptors'\nself._db = 'world_model'\nself.conn = psycopg2.connect(database=self._db, user=user, password=pwd, host=host)\nself.lock = thread.allocate_lock()",
"if 'descriptor_id' in entity.keys():\n del entity['descriptor_id']\nwith self.lock:\n if 'data' in entity.keys():\n ... | <|body_start_0|>
self._descriptors = 'descriptors'
self._db = 'world_model'
self.conn = psycopg2.connect(database=self._db, user=user, password=pwd, host=host)
self.lock = thread.allocate_lock()
<|end_body_0|>
<|body_start_1|>
if 'descriptor_id' in entity.keys():
del... | The main DescriptorConnection object which communicates with the PostgreSQL World Model database. | DescriptorConnection | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DescriptorConnection:
"""The main DescriptorConnection object which communicates with the PostgreSQL World Model database."""
def __init__(self, user, pwd, host='localhost'):
"""Creates the DescriptorConnection object and connects to the descriptors table. @param user: the database u... | stack_v2_sparse_classes_36k_train_002982 | 7,245 | no_license | [
{
"docstring": "Creates the DescriptorConnection object and connects to the descriptors table. @param user: the database username @type user: string @param pwd: the database password @type pwd: string @param host: the database hostname @type host: string",
"name": "__init__",
"signature": "def __init__(... | 5 | stack_v2_sparse_classes_30k_train_008493 | Implement the Python class `DescriptorConnection` described below.
Class description:
The main DescriptorConnection object which communicates with the PostgreSQL World Model database.
Method signatures and docstrings:
- def __init__(self, user, pwd, host='localhost'): Creates the DescriptorConnection object and conne... | Implement the Python class `DescriptorConnection` described below.
Class description:
The main DescriptorConnection object which communicates with the PostgreSQL World Model database.
Method signatures and docstrings:
- def __init__(self, user, pwd, host='localhost'): Creates the DescriptorConnection object and conne... | 4a835a04b469360b11243405d4d1f19b706c510d | <|skeleton|>
class DescriptorConnection:
"""The main DescriptorConnection object which communicates with the PostgreSQL World Model database."""
def __init__(self, user, pwd, host='localhost'):
"""Creates the DescriptorConnection object and connects to the descriptors table. @param user: the database u... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DescriptorConnection:
"""The main DescriptorConnection object which communicates with the PostgreSQL World Model database."""
def __init__(self, user, pwd, host='localhost'):
"""Creates the DescriptorConnection object and connects to the descriptors table. @param user: the database username @type... | the_stack_v2_python_sparse | spatial_world_model/worldlib/src/worldlib/descriptor_connection.py | Playfish/cafe_demo | train | 0 |
30bad695936ec14a8c0f5a485e113d947c47b60f | [
"config_filename = '%s-slave-config.json' % socket.gethostname()\nconfig_path = os.path.join('config', config_filename)\nsuper().__init__(config_path=config_path)\nself.task_q = []\nself.master_nodes = []\nself.config['port'] = port\nmessenger_type = messenger.ZMQMessenger.TYPE_CLIENT\nself.messenger = messenger.ZM... | <|body_start_0|>
config_filename = '%s-slave-config.json' % socket.gethostname()
config_path = os.path.join('config', config_filename)
super().__init__(config_path=config_path)
self.task_q = []
self.master_nodes = []
self.config['port'] = port
messenger_type = mes... | An instance of this class represents a slave node. A slave node can accept work units from a master and process and send the results back. | Slave | [
"WTFPL"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Slave:
"""An instance of this class represents a slave node. A slave node can accept work units from a master and process and send the results back."""
def __init__(self, port, ip=None):
""":param port: port number to run this slave on."""
<|body_0|>
def associate(self):... | stack_v2_sparse_classes_36k_train_002983 | 3,136 | permissive | [
{
"docstring": ":param port: port number to run this slave on.",
"name": "__init__",
"signature": "def __init__(self, port, ip=None)"
},
{
"docstring": "Associate with the master(s). This involves sending a status update to the master.",
"name": "associate",
"signature": "def associate(s... | 3 | stack_v2_sparse_classes_30k_train_003586 | Implement the Python class `Slave` described below.
Class description:
An instance of this class represents a slave node. A slave node can accept work units from a master and process and send the results back.
Method signatures and docstrings:
- def __init__(self, port, ip=None): :param port: port number to run this ... | Implement the Python class `Slave` described below.
Class description:
An instance of this class represents a slave node. A slave node can accept work units from a master and process and send the results back.
Method signatures and docstrings:
- def __init__(self, port, ip=None): :param port: port number to run this ... | 97a46f165475f71b1cd0b10626232cd586e102b3 | <|skeleton|>
class Slave:
"""An instance of this class represents a slave node. A slave node can accept work units from a master and process and send the results back."""
def __init__(self, port, ip=None):
""":param port: port number to run this slave on."""
<|body_0|>
def associate(self):... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Slave:
"""An instance of this class represents a slave node. A slave node can accept work units from a master and process and send the results back."""
def __init__(self, port, ip=None):
""":param port: port number to run this slave on."""
config_filename = '%s-slave-config.json' % socket... | the_stack_v2_python_sparse | slave.py | mtahmed/antnest | train | 1 |
5868c972ff8320e9830c2658436fc8e247b3b7f9 | [
"if self.df.empty:\n return self.df._default_to_pandas(lambda df: df.iloc[key])\nif isinstance(key, tuple):\n key = self._validate_key_length(key)\nrow_loc, col_loc, ndim = self._parse_row_and_column_locators(key)\nrow_scalar = is_scalar(row_loc)\ncol_scalar = is_scalar(col_loc)\nself._check_dtypes(row_loc)\n... | <|body_start_0|>
if self.df.empty:
return self.df._default_to_pandas(lambda df: df.iloc[key])
if isinstance(key, tuple):
key = self._validate_key_length(key)
row_loc, col_loc, ndim = self._parse_row_and_column_locators(key)
row_scalar = is_scalar(row_loc)
... | An indexer for modin_df.iloc[] functionality. Parameters ---------- modin_df : modin.pandas.DataFrame DataFrame to operate on. | _iLocIndexer | [
"Apache-2.0",
"LicenseRef-scancode-generic-cla",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _iLocIndexer:
"""An indexer for modin_df.iloc[] functionality. Parameters ---------- modin_df : modin.pandas.DataFrame DataFrame to operate on."""
def __getitem__(self, key):
"""Retrieve dataset according to `key`. Parameters ---------- key : callable or tuple The global row numbers ... | stack_v2_sparse_classes_36k_train_002984 | 41,072 | permissive | [
{
"docstring": "Retrieve dataset according to `key`. Parameters ---------- key : callable or tuple The global row numbers to retrieve data from. Returns ------- DataFrame or Series Located dataset. See Also -------- pandas.DataFrame.iloc",
"name": "__getitem__",
"signature": "def __getitem__(self, key)"... | 4 | stack_v2_sparse_classes_30k_train_011661 | Implement the Python class `_iLocIndexer` described below.
Class description:
An indexer for modin_df.iloc[] functionality. Parameters ---------- modin_df : modin.pandas.DataFrame DataFrame to operate on.
Method signatures and docstrings:
- def __getitem__(self, key): Retrieve dataset according to `key`. Parameters -... | Implement the Python class `_iLocIndexer` described below.
Class description:
An indexer for modin_df.iloc[] functionality. Parameters ---------- modin_df : modin.pandas.DataFrame DataFrame to operate on.
Method signatures and docstrings:
- def __getitem__(self, key): Retrieve dataset according to `key`. Parameters -... | 8f6e00378e095817deccd25f4140406c5ee6c992 | <|skeleton|>
class _iLocIndexer:
"""An indexer for modin_df.iloc[] functionality. Parameters ---------- modin_df : modin.pandas.DataFrame DataFrame to operate on."""
def __getitem__(self, key):
"""Retrieve dataset according to `key`. Parameters ---------- key : callable or tuple The global row numbers ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _iLocIndexer:
"""An indexer for modin_df.iloc[] functionality. Parameters ---------- modin_df : modin.pandas.DataFrame DataFrame to operate on."""
def __getitem__(self, key):
"""Retrieve dataset according to `key`. Parameters ---------- key : callable or tuple The global row numbers to retrieve d... | the_stack_v2_python_sparse | modin/pandas/indexing.py | modin-project/modin | train | 9,241 |
3c620b699ecff95c27f0ba5ee4a73f770fb45089 | [
"check_cluster_name(cluster_name, application_name)\nvalidate_fields(instance_schema, {'application': application_name, 'cluster': cluster_name, 'key': key})\nim = InstanceManagement(huskar_client, application_name, SERVICE_SUBDOMAIN)\ninstance, _ = im.get_instance(cluster_name, key, resolve=False)\nif instance.sta... | <|body_start_0|>
check_cluster_name(cluster_name, application_name)
validate_fields(instance_schema, {'application': application_name, 'cluster': cluster_name, 'key': key})
im = InstanceManagement(huskar_client, application_name, SERVICE_SUBDOMAIN)
instance, _ = im.get_instance(cluster_n... | ServiceInstanceWeightView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ServiceInstanceWeightView:
def get(self, application_name, cluster_name, key):
"""Gets the weight of specified service instance. :param application_name: The name of application. :param cluster_name: The name of cluster. :param key: The key of service instance. :<header Authorization: Hu... | stack_v2_sparse_classes_36k_train_002985 | 17,926 | permissive | [
{
"docstring": "Gets the weight of specified service instance. :param application_name: The name of application. :param cluster_name: The name of cluster. :param key: The key of service instance. :<header Authorization: Huskar Token (See :ref:`token`) :status 404: The instance is not found. :status 200: The res... | 2 | null | Implement the Python class `ServiceInstanceWeightView` described below.
Class description:
Implement the ServiceInstanceWeightView class.
Method signatures and docstrings:
- def get(self, application_name, cluster_name, key): Gets the weight of specified service instance. :param application_name: The name of applicat... | Implement the Python class `ServiceInstanceWeightView` described below.
Class description:
Implement the ServiceInstanceWeightView class.
Method signatures and docstrings:
- def get(self, application_name, cluster_name, key): Gets the weight of specified service instance. :param application_name: The name of applicat... | 395775c59c7da97c46efe9756365cad028b7c95a | <|skeleton|>
class ServiceInstanceWeightView:
def get(self, application_name, cluster_name, key):
"""Gets the weight of specified service instance. :param application_name: The name of application. :param cluster_name: The name of cluster. :param key: The key of service instance. :<header Authorization: Hu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ServiceInstanceWeightView:
def get(self, application_name, cluster_name, key):
"""Gets the weight of specified service instance. :param application_name: The name of application. :param cluster_name: The name of cluster. :param key: The key of service instance. :<header Authorization: Huskar Token (Se... | the_stack_v2_python_sparse | huskar_api/api/service_instance.py | Zheaoli/huskar | train | 0 | |
604443f0b21640cb0eca42c8ed532957bdc0e9a4 | [
"ng = self.get_object_or_404(self.single, group_id)\ncheck_if_network_configuration_locked(ng.nodegroup)\ndata = self.checked_data(self.validator.validate_update, instance=ng)\nself.single.update(ng, data)\nreturn self.single.to_dict(ng)",
"ng = self.get_object_or_404(self.single, group_id)\ncheck_if_network_conf... | <|body_start_0|>
ng = self.get_object_or_404(self.single, group_id)
check_if_network_configuration_locked(ng.nodegroup)
data = self.checked_data(self.validator.validate_update, instance=ng)
self.single.update(ng, data)
return self.single.to_dict(ng)
<|end_body_0|>
<|body_start_1... | Network group handler | NetworkGroupHandler | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NetworkGroupHandler:
"""Network group handler"""
def PUT(self, group_id):
""":returns: JSONized Network Group object. :http: * 200 (OK) * 400 (error occured while processing of data) * 403 (change of configuration is forbidden) * 404 (Network group was not found in db)"""
<|b... | stack_v2_sparse_classes_36k_train_002986 | 3,725 | permissive | [
{
"docstring": ":returns: JSONized Network Group object. :http: * 200 (OK) * 400 (error occured while processing of data) * 403 (change of configuration is forbidden) * 404 (Network group was not found in db)",
"name": "PUT",
"signature": "def PUT(self, group_id)"
},
{
"docstring": "Remove Netwo... | 2 | null | Implement the Python class `NetworkGroupHandler` described below.
Class description:
Network group handler
Method signatures and docstrings:
- def PUT(self, group_id): :returns: JSONized Network Group object. :http: * 200 (OK) * 400 (error occured while processing of data) * 403 (change of configuration is forbidden)... | Implement the Python class `NetworkGroupHandler` described below.
Class description:
Network group handler
Method signatures and docstrings:
- def PUT(self, group_id): :returns: JSONized Network Group object. :http: * 200 (OK) * 400 (error occured while processing of data) * 403 (change of configuration is forbidden)... | 768ac74a420f822261c4eb8da72f1d8af3c6bbff | <|skeleton|>
class NetworkGroupHandler:
"""Network group handler"""
def PUT(self, group_id):
""":returns: JSONized Network Group object. :http: * 200 (OK) * 400 (error occured while processing of data) * 403 (change of configuration is forbidden) * 404 (Network group was not found in db)"""
<|b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NetworkGroupHandler:
"""Network group handler"""
def PUT(self, group_id):
""":returns: JSONized Network Group object. :http: * 200 (OK) * 400 (error occured while processing of data) * 403 (change of configuration is forbidden) * 404 (Network group was not found in db)"""
ng = self.get_ob... | the_stack_v2_python_sparse | nailgun/nailgun/extensions/network_manager/handlers/network_group.py | dis-xcom/fuel-web | train | 0 |
6c1ca1685c9d8a58203ee228e2cd73ec2af6c954 | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('ashleyyu_bzwtong', 'ashleyyu_bzwtong')\nrepo.dropPermanent('aggpublicschools')\nrepo.createPermanent('aggpublicschools')\npublicschools = list(repo.ashleyyu_bzwtong.publicschools.find())\nzipCount = []\n... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('ashleyyu_bzwtong', 'ashleyyu_bzwtong')
repo.dropPermanent('aggpublicschools')
repo.createPermanent('aggpublicschools')
publicschools = lis... | aggpublicschools | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class aggpublicschools:
def execute(trial=False):
"""Find number of public schools within each zipcode"""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything happening in this scrip... | stack_v2_sparse_classes_36k_train_002987 | 3,932 | no_license | [
{
"docstring": "Find number of public schools within each zipcode",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new document describing that inv... | 2 | stack_v2_sparse_classes_30k_train_019458 | Implement the Python class `aggpublicschools` described below.
Class description:
Implement the aggpublicschools class.
Method signatures and docstrings:
- def execute(trial=False): Find number of public schools within each zipcode
- def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None): Create ... | Implement the Python class `aggpublicschools` described below.
Class description:
Implement the aggpublicschools class.
Method signatures and docstrings:
- def execute(trial=False): Find number of public schools within each zipcode
- def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None): Create ... | b5ccaad97f6e35f9580e645ca764f36eb3406f43 | <|skeleton|>
class aggpublicschools:
def execute(trial=False):
"""Find number of public schools within each zipcode"""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything happening in this scrip... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class aggpublicschools:
def execute(trial=False):
"""Find number of public schools within each zipcode"""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('ashleyyu_bzwtong', 'ashleyyu_bzwtong')
repo.dropPerma... | the_stack_v2_python_sparse | ashleyyu_bzwtong/aggpublicschools.py | dwang1995/course-2018-spr-proj | train | 1 | |
325e0d89af4778dd574ee997c3c67b58a1a5b2c0 | [
"if len(parts) < 3:\n self.client.sendServerMessage('You must provide a username and a message.')\nelse:\n try:\n from_user = self.client.username.lower()\n to_user = parts[1].lower()\n mess = ' '.join(parts[2:])\n file = open('config/data/inbox.dat', 'r')\n messages = cPick... | <|body_start_0|>
if len(parts) < 3:
self.client.sendServerMessage('You must provide a username and a message.')
else:
try:
from_user = self.client.username.lower()
to_user = parts[1].lower()
mess = ' '.join(parts[2:])
... | OfflineMessPlugin | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OfflineMessPlugin:
def commandSendMessage(self, parts, fromloc, overriderank):
"""/s username message - Guest Aliases: sendmessage Sends an message to the users Inbox."""
<|body_0|>
def commandCheckMessages(self, parts, fromloc, overriderank):
"""/inbox - Guest Check... | stack_v2_sparse_classes_36k_train_002988 | 3,110 | permissive | [
{
"docstring": "/s username message - Guest Aliases: sendmessage Sends an message to the users Inbox.",
"name": "commandSendMessage",
"signature": "def commandSendMessage(self, parts, fromloc, overriderank)"
},
{
"docstring": "/inbox - Guest Checks your Inbox of messages",
"name": "commandCh... | 3 | stack_v2_sparse_classes_30k_train_013810 | Implement the Python class `OfflineMessPlugin` described below.
Class description:
Implement the OfflineMessPlugin class.
Method signatures and docstrings:
- def commandSendMessage(self, parts, fromloc, overriderank): /s username message - Guest Aliases: sendmessage Sends an message to the users Inbox.
- def commandC... | Implement the Python class `OfflineMessPlugin` described below.
Class description:
Implement the OfflineMessPlugin class.
Method signatures and docstrings:
- def commandSendMessage(self, parts, fromloc, overriderank): /s username message - Guest Aliases: sendmessage Sends an message to the users Inbox.
- def commandC... | 5482def8b50562fdbae980cda9b1708bfad8bffb | <|skeleton|>
class OfflineMessPlugin:
def commandSendMessage(self, parts, fromloc, overriderank):
"""/s username message - Guest Aliases: sendmessage Sends an message to the users Inbox."""
<|body_0|>
def commandCheckMessages(self, parts, fromloc, overriderank):
"""/inbox - Guest Check... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OfflineMessPlugin:
def commandSendMessage(self, parts, fromloc, overriderank):
"""/s username message - Guest Aliases: sendmessage Sends an message to the users Inbox."""
if len(parts) < 3:
self.client.sendServerMessage('You must provide a username and a message.')
else:
... | the_stack_v2_python_sparse | core/plugins/inbox.py | TheArchives/Nexus | train | 1 | |
d400bcf196f4f6b36e4df115035cb6f3253ed76c | [
"pivotedData = projectedData.dissolve(by=['severity', angleColumn], aggfunc='sum').reset_index().pivot(angleColumn, 'severity', 'effectedPopulation').reset_index().fillna(0)\nif ax is None:\n fig = plt.gcf()\n ax = fig.add_subplot(111, polar=True)\nelif isinstance(ax, list):\n fig = plt.gcf()\n ax = fig... | <|body_start_0|>
pivotedData = projectedData.dissolve(by=['severity', angleColumn], aggfunc='sum').reset_index().pivot(angleColumn, 'severity', 'effectedPopulation').reset_index().fillna(0)
if ax is None:
fig = plt.gcf()
ax = fig.add_subplot(111, polar=True)
elif isinstan... | A class for plotting the different plots related to the casualties. | casualtiesPlot | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class casualtiesPlot:
"""A class for plotting the different plots related to the casualties."""
def plotCasualtiesRose(self, projectedData, severityList, ax=None, angleColumn='mathematical_angle_rad', legend=True, weights=None, cycler=None, coordsTickConvertor=toAzimuthAngle):
"""plots the... | stack_v2_sparse_classes_36k_train_002989 | 4,815 | no_license | [
{
"docstring": "plots the total valueColumn in a radial bars according to the severity. *param: :data: a pandas like with the columns :severity and [valueColumn],[angleColumn]. :severityList: The list of severity values to plot. :valueColumn: the value to plot. :angleColumn: the column that holds the angle. the... | 2 | stack_v2_sparse_classes_30k_val_000440 | Implement the Python class `casualtiesPlot` described below.
Class description:
A class for plotting the different plots related to the casualties.
Method signatures and docstrings:
- def plotCasualtiesRose(self, projectedData, severityList, ax=None, angleColumn='mathematical_angle_rad', legend=True, weights=None, cy... | Implement the Python class `casualtiesPlot` described below.
Class description:
A class for plotting the different plots related to the casualties.
Method signatures and docstrings:
- def plotCasualtiesRose(self, projectedData, severityList, ax=None, angleColumn='mathematical_angle_rad', legend=True, weights=None, cy... | 7fbf20536c81c54cd69d1745f88bbcb264158e82 | <|skeleton|>
class casualtiesPlot:
"""A class for plotting the different plots related to the casualties."""
def plotCasualtiesRose(self, projectedData, severityList, ax=None, angleColumn='mathematical_angle_rad', legend=True, weights=None, cycler=None, coordsTickConvertor=toAzimuthAngle):
"""plots the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class casualtiesPlot:
"""A class for plotting the different plots related to the casualties."""
def plotCasualtiesRose(self, projectedData, severityList, ax=None, angleColumn='mathematical_angle_rad', legend=True, weights=None, cycler=None, coordsTickConvertor=toAzimuthAngle):
"""plots the total valueC... | the_stack_v2_python_sparse | hera/riskassessment/presentation/casualtiesFigs.py | swipswaps/Hera | train | 0 |
c7c2034df9959505cd524084a5ea0dd0364fc8e6 | [
"self.attempt_differential_restore = attempt_differential_restore\nself.datastore_folder_id = datastore_folder_id\nself.detach_network = detach_network\nself.disable_network = disable_network\nself.network_id = network_id\nself.network_mappings = network_mappings\nself.org_vdc_network = org_vdc_network\nself.overwr... | <|body_start_0|>
self.attempt_differential_restore = attempt_differential_restore
self.datastore_folder_id = datastore_folder_id
self.detach_network = detach_network
self.disable_network = disable_network
self.network_id = network_id
self.network_mappings = network_mappin... | Implementation of the 'VmwareCloneParameters' model. Specifies the information required for recovering or cloning VmWare VMs. Attributes: attempt_differential_restore (bool): Specifies whether to attempt differential restore. datastore_folder_id (long|int): Specifies the folder where the restore datastore should be cre... | VmwareCloneParameters | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VmwareCloneParameters:
"""Implementation of the 'VmwareCloneParameters' model. Specifies the information required for recovering or cloning VmWare VMs. Attributes: attempt_differential_restore (bool): Specifies whether to attempt differential restore. datastore_folder_id (long|int): Specifies the... | stack_v2_sparse_classes_36k_train_002990 | 11,797 | permissive | [
{
"docstring": "Constructor for the VmwareCloneParameters class",
"name": "__init__",
"signature": "def __init__(self, attempt_differential_restore=None, datastore_folder_id=None, detach_network=None, disable_network=None, network_id=None, network_mappings=None, org_vdc_network=None, overwrite_existing_... | 2 | null | Implement the Python class `VmwareCloneParameters` described below.
Class description:
Implementation of the 'VmwareCloneParameters' model. Specifies the information required for recovering or cloning VmWare VMs. Attributes: attempt_differential_restore (bool): Specifies whether to attempt differential restore. datast... | Implement the Python class `VmwareCloneParameters` described below.
Class description:
Implementation of the 'VmwareCloneParameters' model. Specifies the information required for recovering or cloning VmWare VMs. Attributes: attempt_differential_restore (bool): Specifies whether to attempt differential restore. datast... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class VmwareCloneParameters:
"""Implementation of the 'VmwareCloneParameters' model. Specifies the information required for recovering or cloning VmWare VMs. Attributes: attempt_differential_restore (bool): Specifies whether to attempt differential restore. datastore_folder_id (long|int): Specifies the... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VmwareCloneParameters:
"""Implementation of the 'VmwareCloneParameters' model. Specifies the information required for recovering or cloning VmWare VMs. Attributes: attempt_differential_restore (bool): Specifies whether to attempt differential restore. datastore_folder_id (long|int): Specifies the folder where... | the_stack_v2_python_sparse | cohesity_management_sdk/models/vmware_clone_parameters.py | cohesity/management-sdk-python | train | 24 |
d47028bd18f41970e469e42016adc01a88b4596f | [
"mol = np.zeros(natoms, dtype=int)\nnmol = natoms / npol\nk = 0\nfor i in range(nmol):\n for j in range(npol):\n mol[k] = i\n k = k + 1\nreturn (mol, nmol)",
"line = line.split()\nself.nbins = int(line[1])\nself.vmin = float(line[2])\nself.vmax = float(line[3])\nself.mol, self.nmol = self.gen_mol... | <|body_start_0|>
mol = np.zeros(natoms, dtype=int)
nmol = natoms / npol
k = 0
for i in range(nmol):
for j in range(npol):
mol[k] = i
k = k + 1
return (mol, nmol)
<|end_body_0|>
<|body_start_1|>
line = line.split()
self.... | VoronoiDensity | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VoronoiDensity:
def gen_mol_info(self, natoms, npol):
"""generate information on molecules"""
<|body_0|>
def __init__(self, nsteps, natoms, npol, line):
"""initialize, allocate required arrays and precompute misc required information"""
<|body_1|>
def co... | stack_v2_sparse_classes_36k_train_002991 | 2,417 | no_license | [
{
"docstring": "generate information on molecules",
"name": "gen_mol_info",
"signature": "def gen_mol_info(self, natoms, npol)"
},
{
"docstring": "initialize, allocate required arrays and precompute misc required information",
"name": "__init__",
"signature": "def __init__(self, nsteps, ... | 3 | null | Implement the Python class `VoronoiDensity` described below.
Class description:
Implement the VoronoiDensity class.
Method signatures and docstrings:
- def gen_mol_info(self, natoms, npol): generate information on molecules
- def __init__(self, nsteps, natoms, npol, line): initialize, allocate required arrays and pre... | Implement the Python class `VoronoiDensity` described below.
Class description:
Implement the VoronoiDensity class.
Method signatures and docstrings:
- def gen_mol_info(self, natoms, npol): generate information on molecules
- def __init__(self, nsteps, natoms, npol, line): initialize, allocate required arrays and pre... | 7d2659bee85c955c680eda019cbff6e2b93ecff2 | <|skeleton|>
class VoronoiDensity:
def gen_mol_info(self, natoms, npol):
"""generate information on molecules"""
<|body_0|>
def __init__(self, nsteps, natoms, npol, line):
"""initialize, allocate required arrays and precompute misc required information"""
<|body_1|>
def co... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VoronoiDensity:
def gen_mol_info(self, natoms, npol):
"""generate information on molecules"""
mol = np.zeros(natoms, dtype=int)
nmol = natoms / npol
k = 0
for i in range(nmol):
for j in range(npol):
mol[k] = i
k = k + 1
... | the_stack_v2_python_sparse | analyse_collective/voronoidensity.py | melampyge/CollectiveFilament | train | 0 | |
65309477df33f56a86553c74184ed3d757a11e45 | [
"Thread.__init__(self)\nwith open('text.txt', 'r') as file:\n self.text = file.read()\nself.character = character",
"lock = Lock()\nwith lock:\n counter = 0\n for char in self.text:\n if char == self.character:\n counter += 1\n print('The character {0} appeared in the text {1} times'... | <|body_start_0|>
Thread.__init__(self)
with open('text.txt', 'r') as file:
self.text = file.read()
self.character = character
<|end_body_0|>
<|body_start_1|>
lock = Lock()
with lock:
counter = 0
for char in self.text:
if char =... | Class which handles searching in a text for a character. | CharThread | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CharThread:
"""Class which handles searching in a text for a character."""
def __init__(self, character):
"""Constructor of the CharThread class. :param character: The desired character."""
<|body_0|>
def run(self):
"""Method which searches for a character in a t... | stack_v2_sparse_classes_36k_train_002992 | 868 | no_license | [
{
"docstring": "Constructor of the CharThread class. :param character: The desired character.",
"name": "__init__",
"signature": "def __init__(self, character)"
},
{
"docstring": "Method which searches for a character in a text.",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000680 | Implement the Python class `CharThread` described below.
Class description:
Class which handles searching in a text for a character.
Method signatures and docstrings:
- def __init__(self, character): Constructor of the CharThread class. :param character: The desired character.
- def run(self): Method which searches f... | Implement the Python class `CharThread` described below.
Class description:
Class which handles searching in a text for a character.
Method signatures and docstrings:
- def __init__(self, character): Constructor of the CharThread class. :param character: The desired character.
- def run(self): Method which searches f... | 7b3c92c151266cd3ccdd63e7dc0a37f7a60476fa | <|skeleton|>
class CharThread:
"""Class which handles searching in a text for a character."""
def __init__(self, character):
"""Constructor of the CharThread class. :param character: The desired character."""
<|body_0|>
def run(self):
"""Method which searches for a character in a t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CharThread:
"""Class which handles searching in a text for a character."""
def __init__(self, character):
"""Constructor of the CharThread class. :param character: The desired character."""
Thread.__init__(self)
with open('text.txt', 'r') as file:
self.text = file.read... | the_stack_v2_python_sparse | Laboratory 8/problem3/thread.py | BabyCakes13/Python-Treasure | train | 0 |
37870f4d81c034edb2ab33232d9d10a12b2fb07a | [
"super().__init__(name, bases, attributes, **kwds)\nif not namespace:\n package = self.pyre_package()\n if package:\n namespace = package.name\nself.pyre_namespace = namespace\nreturn",
"if name is not None:\n loc = pyre.tracking.simple(f\"while initializing application '{name}'\")\n locator = ... | <|body_start_0|>
super().__init__(name, bases, attributes, **kwds)
if not namespace:
package = self.pyre_package()
if package:
namespace = package.name
self.pyre_namespace = namespace
return
<|end_body_0|>
<|body_start_1|>
if name is not N... | The metaclass of applications {Director} takes care of all the tasks necessary to register an application family with the framework | Director | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Director:
"""The metaclass of applications {Director} takes care of all the tasks necessary to register an application family with the framework"""
def __init__(self, name, bases, attributes, namespace=None, **kwds):
"""Initialization of application class records"""
<|body_0|... | stack_v2_sparse_classes_36k_train_002993 | 1,873 | permissive | [
{
"docstring": "Initialization of application class records",
"name": "__init__",
"signature": "def __init__(self, name, bases, attributes, namespace=None, **kwds)"
},
{
"docstring": "Build an application instance",
"name": "__call__",
"signature": "def __call__(self, name=None, globalAl... | 2 | null | Implement the Python class `Director` described below.
Class description:
The metaclass of applications {Director} takes care of all the tasks necessary to register an application family with the framework
Method signatures and docstrings:
- def __init__(self, name, bases, attributes, namespace=None, **kwds): Initial... | Implement the Python class `Director` described below.
Class description:
The metaclass of applications {Director} takes care of all the tasks necessary to register an application family with the framework
Method signatures and docstrings:
- def __init__(self, name, bases, attributes, namespace=None, **kwds): Initial... | d741c44ffb3e9e1f726bf492202ac8738bb4aa1c | <|skeleton|>
class Director:
"""The metaclass of applications {Director} takes care of all the tasks necessary to register an application family with the framework"""
def __init__(self, name, bases, attributes, namespace=None, **kwds):
"""Initialization of application class records"""
<|body_0|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Director:
"""The metaclass of applications {Director} takes care of all the tasks necessary to register an application family with the framework"""
def __init__(self, name, bases, attributes, namespace=None, **kwds):
"""Initialization of application class records"""
super().__init__(name,... | the_stack_v2_python_sparse | packages/pyre/shells/Director.py | pyre/pyre | train | 27 |
ceab5716b0cdfeae3a9c4efeeb00dfd45738efed | [
"if not s:\n return 0\nt, c = min(((s.count(c), c) for c in s))\nif t >= k:\n return len(s)\nreturn max((self.longestSubstring(x, k) for x in s.split(c)))",
"stack = []\nstack.append(s)\nans = 0\nwhile stack:\n s = stack.pop()\n for c in set(s):\n if s.count(c) < k:\n stack.extend([z... | <|body_start_0|>
if not s:
return 0
t, c = min(((s.count(c), c) for c in s))
if t >= k:
return len(s)
return max((self.longestSubstring(x, k) for x in s.split(c)))
<|end_body_0|>
<|body_start_1|>
stack = []
stack.append(s)
ans = 0
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestSubstring(self, s, k):
"""分治 从出现次数最小的字母开始分隔字符串，依次递归分隔后的所有字符串 :param s: :param k: :return:"""
<|body_0|>
def longestSubstring2(self, s, k):
"""迭代 模拟函数栈 for ... else ... 语句： 当for循环正常执行完后会执行else语句，如果for循环被break中断，则不会执行else语句 :type s: str :type k: in... | stack_v2_sparse_classes_36k_train_002994 | 9,679 | no_license | [
{
"docstring": "分治 从出现次数最小的字母开始分隔字符串，依次递归分隔后的所有字符串 :param s: :param k: :return:",
"name": "longestSubstring",
"signature": "def longestSubstring(self, s, k)"
},
{
"docstring": "迭代 模拟函数栈 for ... else ... 语句： 当for循环正常执行完后会执行else语句，如果for循环被break中断，则不会执行else语句 :type s: str :type k: int :rtype: int",... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestSubstring(self, s, k): 分治 从出现次数最小的字母开始分隔字符串，依次递归分隔后的所有字符串 :param s: :param k: :return:
- def longestSubstring2(self, s, k): 迭代 模拟函数栈 for ... else ... 语句： 当for循环正常执行完后会... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestSubstring(self, s, k): 分治 从出现次数最小的字母开始分隔字符串，依次递归分隔后的所有字符串 :param s: :param k: :return:
- def longestSubstring2(self, s, k): 迭代 模拟函数栈 for ... else ... 语句： 当for循环正常执行完后会... | 5d3574ccd282d0146c83c286ae28d8baaabd4910 | <|skeleton|>
class Solution:
def longestSubstring(self, s, k):
"""分治 从出现次数最小的字母开始分隔字符串，依次递归分隔后的所有字符串 :param s: :param k: :return:"""
<|body_0|>
def longestSubstring2(self, s, k):
"""迭代 模拟函数栈 for ... else ... 语句： 当for循环正常执行完后会执行else语句，如果for循环被break中断，则不会执行else语句 :type s: str :type k: in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestSubstring(self, s, k):
"""分治 从出现次数最小的字母开始分隔字符串，依次递归分隔后的所有字符串 :param s: :param k: :return:"""
if not s:
return 0
t, c = min(((s.count(c), c) for c in s))
if t >= k:
return len(s)
return max((self.longestSubstring(x, k) for x i... | the_stack_v2_python_sparse | 395_至少有K个重复字符的最长子串.py | lovehhf/LeetCode | train | 0 | |
2259e2431ace6d5cb0e49a13846306c652976c4c | [
"global channel_list_page, admin_page\nchannel_list_page = ChannelListPage(self.driver)\nadmin_page = AdminPage(self.driver)\nadmin_page.into_subsystem('业务管理')\nadmin_page.select_menu('首页/渠道业务管理')",
"admin_page.select_menu('渠道列表')\nchannel_list_page.simple_query_channel(channel_name='三沙市')\nassert '三沙市' in channe... | <|body_start_0|>
global channel_list_page, admin_page
channel_list_page = ChannelListPage(self.driver)
admin_page = AdminPage(self.driver)
admin_page.into_subsystem('业务管理')
admin_page.select_menu('首页/渠道业务管理')
<|end_body_0|>
<|body_start_1|>
admin_page.select_menu('渠道列表')... | TestChannelList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestChannelList:
def set_up(self):
"""前置操作 :return:"""
<|body_0|>
def test_query_channel(self, set_up):
"""渠道查询 :return:"""
<|body_1|>
def test_reset_channel_query(self):
"""重置渠道列表查询 :return:"""
<|body_2|>
def test_click_more_channel... | stack_v2_sparse_classes_36k_train_002995 | 2,199 | no_license | [
{
"docstring": "前置操作 :return:",
"name": "set_up",
"signature": "def set_up(self)"
},
{
"docstring": "渠道查询 :return:",
"name": "test_query_channel",
"signature": "def test_query_channel(self, set_up)"
},
{
"docstring": "重置渠道列表查询 :return:",
"name": "test_reset_channel_query",
... | 5 | null | Implement the Python class `TestChannelList` described below.
Class description:
Implement the TestChannelList class.
Method signatures and docstrings:
- def set_up(self): 前置操作 :return:
- def test_query_channel(self, set_up): 渠道查询 :return:
- def test_reset_channel_query(self): 重置渠道列表查询 :return:
- def test_click_more_... | Implement the Python class `TestChannelList` described below.
Class description:
Implement the TestChannelList class.
Method signatures and docstrings:
- def set_up(self): 前置操作 :return:
- def test_query_channel(self, set_up): 渠道查询 :return:
- def test_reset_channel_query(self): 重置渠道列表查询 :return:
- def test_click_more_... | 86d1b085af2d3808ac8472d541f4bf26d26591e0 | <|skeleton|>
class TestChannelList:
def set_up(self):
"""前置操作 :return:"""
<|body_0|>
def test_query_channel(self, set_up):
"""渠道查询 :return:"""
<|body_1|>
def test_reset_channel_query(self):
"""重置渠道列表查询 :return:"""
<|body_2|>
def test_click_more_channel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestChannelList:
def set_up(self):
"""前置操作 :return:"""
global channel_list_page, admin_page
channel_list_page = ChannelListPage(self.driver)
admin_page = AdminPage(self.driver)
admin_page.into_subsystem('业务管理')
admin_page.select_menu('首页/渠道业务管理')
def test_q... | the_stack_v2_python_sparse | src/cases/business_manage/channel_business_manage/test_channel_list_page_140.py | 102244653/SeleniumByPython | train | 2 | |
62faaccf74199d4800fa9dd50b65ab42be2e855f | [
"self.num_parallel_calls = tf.convert_to_tensor(num_parallel_calls, tf.int32)\nself.event_size = tf.convert_to_tensor(event_size, tf.int32)\nself.data = [tf.cast(c, float_type) if c.dtype is not float_type else c for c in data]\nself.index_feed = index_feed\nself.slice_size = self.index_feed.step\nwith tf.control_d... | <|body_start_0|>
self.num_parallel_calls = tf.convert_to_tensor(num_parallel_calls, tf.int32)
self.event_size = tf.convert_to_tensor(event_size, tf.int32)
self.data = [tf.cast(c, float_type) if c.dtype is not float_type else c for c in data]
self.index_feed = index_feed
self.slic... | DataFeed | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataFeed:
def __init__(self, index_feed: IndexFeed, *data, event_size=1, num_parallel_calls=10):
"""Create a time feed :param index_feed: IndexFeed Pulse of this feed :param data: list of float_type, Tensor, [Nt, ..., D] Data to grab unflattened :param num_parallel_calls:"""
<|bo... | stack_v2_sparse_classes_36k_train_002996 | 18,860 | permissive | [
{
"docstring": "Create a time feed :param index_feed: IndexFeed Pulse of this feed :param data: list of float_type, Tensor, [Nt, ..., D] Data to grab unflattened :param num_parallel_calls:",
"name": "__init__",
"signature": "def __init__(self, index_feed: IndexFeed, *data, event_size=1, num_parallel_cal... | 2 | stack_v2_sparse_classes_30k_train_016004 | Implement the Python class `DataFeed` described below.
Class description:
Implement the DataFeed class.
Method signatures and docstrings:
- def __init__(self, index_feed: IndexFeed, *data, event_size=1, num_parallel_calls=10): Create a time feed :param index_feed: IndexFeed Pulse of this feed :param data: list of flo... | Implement the Python class `DataFeed` described below.
Class description:
Implement the DataFeed class.
Method signatures and docstrings:
- def __init__(self, index_feed: IndexFeed, *data, event_size=1, num_parallel_calls=10): Create a time feed :param index_feed: IndexFeed Pulse of this feed :param data: list of flo... | 2997d60d8cf07f875e42c0b5f07944e9ab7e9d33 | <|skeleton|>
class DataFeed:
def __init__(self, index_feed: IndexFeed, *data, event_size=1, num_parallel_calls=10):
"""Create a time feed :param index_feed: IndexFeed Pulse of this feed :param data: list of float_type, Tensor, [Nt, ..., D] Data to grab unflattened :param num_parallel_calls:"""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataFeed:
def __init__(self, index_feed: IndexFeed, *data, event_size=1, num_parallel_calls=10):
"""Create a time feed :param index_feed: IndexFeed Pulse of this feed :param data: list of float_type, Tensor, [Nt, ..., D] Data to grab unflattened :param num_parallel_calls:"""
self.num_parallel_... | the_stack_v2_python_sparse | bayes_filter/feeds.py | Joshuaalbert/bayes_filter | train | 0 | |
49b30b7fe93956329bc1fc8ffe663f976f1ba00b | [
"ans = 0\nfor item in S:\n if item in J:\n ans += 1\nreturn ans",
"mydict = {}\nfor item in J:\n if item in mydict.keys():\n mydict[item] += 1\n else:\n mydict[item] = 1\nans = 0\nfor item in S:\n if item in mydict.keys():\n ans += 1\nreturn ans"
] | <|body_start_0|>
ans = 0
for item in S:
if item in J:
ans += 1
return ans
<|end_body_0|>
<|body_start_1|>
mydict = {}
for item in J:
if item in mydict.keys():
mydict[item] += 1
else:
mydict[item]... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def numJewelsInStones(self, J, S):
""":type J: str :type S: str :rtype: int"""
<|body_0|>
def numJewelsInStones2(self, J, S):
""":type J: str :type S: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ans = 0
for item... | stack_v2_sparse_classes_36k_train_002997 | 1,186 | no_license | [
{
"docstring": ":type J: str :type S: str :rtype: int",
"name": "numJewelsInStones",
"signature": "def numJewelsInStones(self, J, S)"
},
{
"docstring": ":type J: str :type S: str :rtype: int",
"name": "numJewelsInStones2",
"signature": "def numJewelsInStones2(self, J, S)"
}
] | 2 | stack_v2_sparse_classes_30k_train_010882 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numJewelsInStones(self, J, S): :type J: str :type S: str :rtype: int
- def numJewelsInStones2(self, J, S): :type J: str :type S: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def numJewelsInStones(self, J, S): :type J: str :type S: str :rtype: int
- def numJewelsInStones2(self, J, S): :type J: str :type S: str :rtype: int
<|skeleton|>
class Solution:... | 690b685048c8e89d26047b6bc48b5f9af7d59cbb | <|skeleton|>
class Solution:
def numJewelsInStones(self, J, S):
""":type J: str :type S: str :rtype: int"""
<|body_0|>
def numJewelsInStones2(self, J, S):
""":type J: str :type S: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def numJewelsInStones(self, J, S):
""":type J: str :type S: str :rtype: int"""
ans = 0
for item in S:
if item in J:
ans += 1
return ans
def numJewelsInStones2(self, J, S):
""":type J: str :type S: str :rtype: int"""
myd... | the_stack_v2_python_sparse | 哈希表/771. 宝石与石头.py | SimmonsChen/LeetCode | train | 0 | |
ac2b79ed7726626b548e71e2fee40a984ad157a5 | [
"def cal(s):\n sum_1 = 0\n for char in s:\n if char == '1':\n sum_1 += 1\n return sum_1\nprime = {2, 3, 5, 7, 11, 13, 17, 19, 23}\nans = 0\nfor i in range(L, R + 1):\n if cal(bin(i)[2:]) in prime:\n ans += 1\nreturn ans",
"count = 0\nfor x in range(L, R + 1):\n num = bin(x)... | <|body_start_0|>
def cal(s):
sum_1 = 0
for char in s:
if char == '1':
sum_1 += 1
return sum_1
prime = {2, 3, 5, 7, 11, 13, 17, 19, 23}
ans = 0
for i in range(L, R + 1):
if cal(bin(i)[2:]) in prime:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countPrimeSetBits(self, L, R):
""":type L: int :type R: int :rtype: int 1138ms"""
<|body_0|>
def countPrimeSetBits_1(self, L, R):
"""1488ms :param L: :param R: :return:"""
<|body_1|>
def countPrimeSetBits_2(self, L, R):
"""63ms :par... | stack_v2_sparse_classes_36k_train_002998 | 2,525 | no_license | [
{
"docstring": ":type L: int :type R: int :rtype: int 1138ms",
"name": "countPrimeSetBits",
"signature": "def countPrimeSetBits(self, L, R)"
},
{
"docstring": "1488ms :param L: :param R: :return:",
"name": "countPrimeSetBits_1",
"signature": "def countPrimeSetBits_1(self, L, R)"
},
{... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countPrimeSetBits(self, L, R): :type L: int :type R: int :rtype: int 1138ms
- def countPrimeSetBits_1(self, L, R): 1488ms :param L: :param R: :return:
- def countPrimeSetBits... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countPrimeSetBits(self, L, R): :type L: int :type R: int :rtype: int 1138ms
- def countPrimeSetBits_1(self, L, R): 1488ms :param L: :param R: :return:
- def countPrimeSetBits... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def countPrimeSetBits(self, L, R):
""":type L: int :type R: int :rtype: int 1138ms"""
<|body_0|>
def countPrimeSetBits_1(self, L, R):
"""1488ms :param L: :param R: :return:"""
<|body_1|>
def countPrimeSetBits_2(self, L, R):
"""63ms :par... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def countPrimeSetBits(self, L, R):
""":type L: int :type R: int :rtype: int 1138ms"""
def cal(s):
sum_1 = 0
for char in s:
if char == '1':
sum_1 += 1
return sum_1
prime = {2, 3, 5, 7, 11, 13, 17, 19, 23}
... | the_stack_v2_python_sparse | PrimeNumberOfSetBitsInBinaryRepresentation_762.py | 953250587/leetcode-python | train | 2 | |
8d3fbc72f95891fe45b86724380600c7616d8be8 | [
"low = self.action_space.low\nhigh = self.action_space.high\nscale_factor = (high - low) / 2\nreloc_factor = high - scale_factor\naction = action * scale_factor + reloc_factor\naction = np.clip(action, low, high)\nreturn action",
"low = self.action_space.low\nhigh = self.action_space.high\nscale_factor = (high - ... | <|body_start_0|>
low = self.action_space.low
high = self.action_space.high
scale_factor = (high - low) / 2
reloc_factor = high - scale_factor
action = action * scale_factor + reloc_factor
action = np.clip(action, low, high)
return action
<|end_body_0|>
<|body_sta... | Rescale and relocate the actions. | ActionNormalizer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ActionNormalizer:
"""Rescale and relocate the actions."""
def action(self, action: np.ndarray) -> np.ndarray:
"""Change the range (-1, 1) to (low, high)."""
<|body_0|>
def reverse_action(self, action: np.ndarray) -> np.ndarray:
"""Change the range (low, high) to ... | stack_v2_sparse_classes_36k_train_002999 | 13,315 | no_license | [
{
"docstring": "Change the range (-1, 1) to (low, high).",
"name": "action",
"signature": "def action(self, action: np.ndarray) -> np.ndarray"
},
{
"docstring": "Change the range (low, high) to (-1, 1).",
"name": "reverse_action",
"signature": "def reverse_action(self, action: np.ndarray... | 2 | stack_v2_sparse_classes_30k_train_002631 | Implement the Python class `ActionNormalizer` described below.
Class description:
Rescale and relocate the actions.
Method signatures and docstrings:
- def action(self, action: np.ndarray) -> np.ndarray: Change the range (-1, 1) to (low, high).
- def reverse_action(self, action: np.ndarray) -> np.ndarray: Change the ... | Implement the Python class `ActionNormalizer` described below.
Class description:
Rescale and relocate the actions.
Method signatures and docstrings:
- def action(self, action: np.ndarray) -> np.ndarray: Change the range (-1, 1) to (low, high).
- def reverse_action(self, action: np.ndarray) -> np.ndarray: Change the ... | 14ddfb81295c349acc2ede7588ebc73c235246c0 | <|skeleton|>
class ActionNormalizer:
"""Rescale and relocate the actions."""
def action(self, action: np.ndarray) -> np.ndarray:
"""Change the range (-1, 1) to (low, high)."""
<|body_0|>
def reverse_action(self, action: np.ndarray) -> np.ndarray:
"""Change the range (low, high) to ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ActionNormalizer:
"""Rescale and relocate the actions."""
def action(self, action: np.ndarray) -> np.ndarray:
"""Change the range (-1, 1) to (low, high)."""
low = self.action_space.low
high = self.action_space.high
scale_factor = (high - low) / 2
reloc_factor = hig... | the_stack_v2_python_sparse | PPO_GAE_TEST/PPO_gae_test2.py | namjiwon1023/Reinforcement_learning | train | 2 |
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