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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
3fcc0b2735541cbdcfcf84c9e944b05d218b696c | [
"genus = Integer(genus)\nif not genus >= 0:\n raise ValueError('genus must be positive')\nif marked_separatrix is None:\n marked_separatrix = 'no'\nif not marked_separatrix in ['no', 'out', 'in']:\n raise ValueError('marked_separatrix must be no, out or in')\nself._marked_separatrix = marked_separatrix\nse... | <|body_start_0|>
genus = Integer(genus)
if not genus >= 0:
raise ValueError('genus must be positive')
if marked_separatrix is None:
marked_separatrix = 'no'
if not marked_separatrix in ['no', 'out', 'in']:
raise ValueError('marked_separatrix must be no... | Stratas of genus g surfaces. INPUT: - ``genus`` - a non negative integer - ``marked_separatrix`` - 'no', 'out' or 'in' | AbelianStrata_g | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AbelianStrata_g:
"""Stratas of genus g surfaces. INPUT: - ``genus`` - a non negative integer - ``marked_separatrix`` - 'no', 'out' or 'in'"""
def __init__(self, genus=None, marked_separatrix=None):
"""TESTS:: sage: s = AbelianStrata(genus=3) sage: s == loads(dumps(s)) True sage: Abel... | stack_v2_sparse_classes_36k_train_021900 | 49,724 | no_license | [
{
"docstring": "TESTS:: sage: s = AbelianStrata(genus=3) sage: s == loads(dumps(s)) True sage: AbelianStrata(genus=-3) Traceback (most recent call last): ... ValueError: genus must be positive sage: AbelianStrata(genus=3, marked_separatrix='yes') Traceback (most recent call last): ... ValueError: marked_separat... | 3 | null | Implement the Python class `AbelianStrata_g` described below.
Class description:
Stratas of genus g surfaces. INPUT: - ``genus`` - a non negative integer - ``marked_separatrix`` - 'no', 'out' or 'in'
Method signatures and docstrings:
- def __init__(self, genus=None, marked_separatrix=None): TESTS:: sage: s = AbelianS... | Implement the Python class `AbelianStrata_g` described below.
Class description:
Stratas of genus g surfaces. INPUT: - ``genus`` - a non negative integer - ``marked_separatrix`` - 'no', 'out' or 'in'
Method signatures and docstrings:
- def __init__(self, genus=None, marked_separatrix=None): TESTS:: sage: s = AbelianS... | 0d9eacbf74e2acffefde93e39f8bcbec745cdaba | <|skeleton|>
class AbelianStrata_g:
"""Stratas of genus g surfaces. INPUT: - ``genus`` - a non negative integer - ``marked_separatrix`` - 'no', 'out' or 'in'"""
def __init__(self, genus=None, marked_separatrix=None):
"""TESTS:: sage: s = AbelianStrata(genus=3) sage: s == loads(dumps(s)) True sage: Abel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AbelianStrata_g:
"""Stratas of genus g surfaces. INPUT: - ``genus`` - a non negative integer - ``marked_separatrix`` - 'no', 'out' or 'in'"""
def __init__(self, genus=None, marked_separatrix=None):
"""TESTS:: sage: s = AbelianStrata(genus=3) sage: s == loads(dumps(s)) True sage: AbelianStrata(gen... | the_stack_v2_python_sparse | sage/src/sage/dynamics/flat_surfaces/strata.py | bopopescu/geosci | train | 0 |
c114fc40f51d2ab2100d5669e103904de43f946f | [
"request_data = request.GET\nticket_id = kwargs.get('ticket_id')\napp_name = request.META.get('HTTP_APPNAME')\napp_permission_check, msg = account_base_service_ins.app_ticket_permission_check(app_name, ticket_id)\nif not app_permission_check:\n return api_response(-1, msg, '')\nusername = request.META.get('HTTP_... | <|body_start_0|>
request_data = request.GET
ticket_id = kwargs.get('ticket_id')
app_name = request.META.get('HTTP_APPNAME')
app_permission_check, msg = account_base_service_ins.app_ticket_permission_check(app_name, ticket_id)
if not app_permission_check:
return api_re... | TicketView | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TicketView:
def get(self, request, *args, **kwargs):
"""获取工单详情，根据用户返回不同的内容(是否有工单表单的编辑权限) :param request: :param args: :param kwargs: :return:"""
<|body_0|>
def patch(self, request, *args, **kwargs):
"""处理工单 :param request: :param args: :param kwargs: :return:"""
... | stack_v2_sparse_classes_36k_train_021901 | 26,311 | permissive | [
{
"docstring": "获取工单详情，根据用户返回不同的内容(是否有工单表单的编辑权限) :param request: :param args: :param kwargs: :return:",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "处理工单 :param request: :param args: :param kwargs: :return:",
"name": "patch",
"signature": "def ... | 3 | stack_v2_sparse_classes_30k_train_016942 | Implement the Python class `TicketView` described below.
Class description:
Implement the TicketView class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): 获取工单详情，根据用户返回不同的内容(是否有工单表单的编辑权限) :param request: :param args: :param kwargs: :return:
- def patch(self, request, *args, **kwargs): 处理... | Implement the Python class `TicketView` described below.
Class description:
Implement the TicketView class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): 获取工单详情，根据用户返回不同的内容(是否有工单表单的编辑权限) :param request: :param args: :param kwargs: :return:
- def patch(self, request, *args, **kwargs): 处理... | b0e236b314286c5f6cc6959622c9c8505e776443 | <|skeleton|>
class TicketView:
def get(self, request, *args, **kwargs):
"""获取工单详情，根据用户返回不同的内容(是否有工单表单的编辑权限) :param request: :param args: :param kwargs: :return:"""
<|body_0|>
def patch(self, request, *args, **kwargs):
"""处理工单 :param request: :param args: :param kwargs: :return:"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TicketView:
def get(self, request, *args, **kwargs):
"""获取工单详情，根据用户返回不同的内容(是否有工单表单的编辑权限) :param request: :param args: :param kwargs: :return:"""
request_data = request.GET
ticket_id = kwargs.get('ticket_id')
app_name = request.META.get('HTTP_APPNAME')
app_permission_che... | the_stack_v2_python_sparse | apps/ticket/views.py | blackholll/loonflow | train | 1,864 | |
2436376d98e548df6b8be205d01fe620f077f7c9 | [
"if not isinstance(alph_idx, Base58Alphabets):\n raise TypeError('Alphabet index is not an enumerative of Base58Alphabets')\nalphabet = Base58Const.ALPHABETS[alph_idx]\nval = 0\nfor i, c in enumerate(data_str[::-1]):\n val += alphabet.index(c) * Base58Const.RADIX ** i\ndec = bytearray()\nwhile val > 0:\n v... | <|body_start_0|>
if not isinstance(alph_idx, Base58Alphabets):
raise TypeError('Alphabet index is not an enumerative of Base58Alphabets')
alphabet = Base58Const.ALPHABETS[alph_idx]
val = 0
for i, c in enumerate(data_str[::-1]):
val += alphabet.index(c) * Base58Con... | Base58 decoder class. It provides methods for decoding and checksum decoding Base58 format. | Base58Decoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Base58Decoder:
"""Base58 decoder class. It provides methods for decoding and checksum decoding Base58 format."""
def Decode(data_str: str, alph_idx: Base58Alphabets=Base58Alphabets.BITCOIN) -> bytes:
"""Decode bytes from a Base58 string. Args: data_str (str) : Data string alph_idx (B... | stack_v2_sparse_classes_36k_train_021902 | 6,906 | permissive | [
{
"docstring": "Decode bytes from a Base58 string. Args: data_str (str) : Data string alph_idx (Base58Alphabets, optional): Alphabet index, Bitcoin by default Returns: bytes: Decoded bytes Raises: TypeError: If alphabet index is not a Base58Alphabets enumerative",
"name": "Decode",
"signature": "def Dec... | 2 | stack_v2_sparse_classes_30k_train_003778 | Implement the Python class `Base58Decoder` described below.
Class description:
Base58 decoder class. It provides methods for decoding and checksum decoding Base58 format.
Method signatures and docstrings:
- def Decode(data_str: str, alph_idx: Base58Alphabets=Base58Alphabets.BITCOIN) -> bytes: Decode bytes from a Base... | Implement the Python class `Base58Decoder` described below.
Class description:
Base58 decoder class. It provides methods for decoding and checksum decoding Base58 format.
Method signatures and docstrings:
- def Decode(data_str: str, alph_idx: Base58Alphabets=Base58Alphabets.BITCOIN) -> bytes: Decode bytes from a Base... | d15c75ddd74e4838c396a0d036ef6faf11b06a4b | <|skeleton|>
class Base58Decoder:
"""Base58 decoder class. It provides methods for decoding and checksum decoding Base58 format."""
def Decode(data_str: str, alph_idx: Base58Alphabets=Base58Alphabets.BITCOIN) -> bytes:
"""Decode bytes from a Base58 string. Args: data_str (str) : Data string alph_idx (B... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Base58Decoder:
"""Base58 decoder class. It provides methods for decoding and checksum decoding Base58 format."""
def Decode(data_str: str, alph_idx: Base58Alphabets=Base58Alphabets.BITCOIN) -> bytes:
"""Decode bytes from a Base58 string. Args: data_str (str) : Data string alph_idx (Base58Alphabet... | the_stack_v2_python_sparse | bip_utils/base58/base58.py | ebellocchia/bip_utils | train | 244 |
e4d0eb79c819bf5851fbf2d7a759e52397a0c087 | [
"super().__init__()\nself.cost_class = cost_class\nself.cost_bbox = cost_bbox\nself.cost_giou = cost_giou\nassert cost_class != 0 or cost_bbox != 0 or cost_giou != 0, 'all costs cant be 0'",
"bs, num_queries = outputs['pred_logits'].shape[:2]\npred_logits = outputs['pred_logits']\npred_boxes = outputs['pred_boxes... | <|body_start_0|>
super().__init__()
self.cost_class = cost_class
self.cost_bbox = cost_bbox
self.cost_giou = cost_giou
assert cost_class != 0 or cost_bbox != 0 or cost_giou != 0, 'all costs cant be 0'
<|end_body_0|>
<|body_start_1|>
bs, num_queries = outputs['pred_logits... | This class computes an assignment between the targets and the predictions of the network For efficiency reasons, the targets don't include the no_object. Because of this, in general, there are more predictions than targets. In this case, we do a 1-to-1 matching of the best predictions, while the others are un-matched (... | HungarianMatcher | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HungarianMatcher:
"""This class computes an assignment between the targets and the predictions of the network For efficiency reasons, the targets don't include the no_object. Because of this, in general, there are more predictions than targets. In this case, we do a 1-to-1 matching of the best pr... | stack_v2_sparse_classes_36k_train_021903 | 5,312 | permissive | [
{
"docstring": "Creates the matcher Params: cost_class: This is the relative weight of the classification error in the matching cost cost_bbox: This is the relative weight of the L1 error of the bounding box coordinates in the matching cost cost_giou: This is the relative weight of the giou loss of the bounding... | 2 | null | Implement the Python class `HungarianMatcher` described below.
Class description:
This class computes an assignment between the targets and the predictions of the network For efficiency reasons, the targets don't include the no_object. Because of this, in general, there are more predictions than targets. In this case,... | Implement the Python class `HungarianMatcher` described below.
Class description:
This class computes an assignment between the targets and the predictions of the network For efficiency reasons, the targets don't include the no_object. Because of this, in general, there are more predictions than targets. In this case,... | eab643f51336dbf7d711f02d27e6516e5affee59 | <|skeleton|>
class HungarianMatcher:
"""This class computes an assignment between the targets and the predictions of the network For efficiency reasons, the targets don't include the no_object. Because of this, in general, there are more predictions than targets. In this case, we do a 1-to-1 matching of the best pr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HungarianMatcher:
"""This class computes an assignment between the targets and the predictions of the network For efficiency reasons, the targets don't include the no_object. Because of this, in general, there are more predictions than targets. In this case, we do a 1-to-1 matching of the best predictions, wh... | the_stack_v2_python_sparse | research/cv/detr/src/matcher.py | mindspore-ai/models | train | 301 |
9db1feedb9a50452257eeb67949f75d50f15565c | [
"self.statevar = ['swq']\nself.obsvar = 'snow_cover'\nself.uncert = uncert",
"data = {}\ndb = dbio.connect(models.dbname)\ncur = db.cursor()\nfor s in self.statevar:\n sql = \"select ensemble,st_x(geom),st_y(geom),val from (select ensemble,(ST_PixelAsCentroids(rast)).* from {0}.{1} where fdate=date '{2}-{3}-{4... | <|body_start_0|>
self.statevar = ['swq']
self.obsvar = 'snow_cover'
self.uncert = uncert
<|end_body_0|>
<|body_start_1|>
data = {}
db = dbio.connect(models.dbname)
cur = db.cursor()
for s in self.statevar:
sql = "select ensemble,st_x(geom),st_y(geom),... | Snowcover | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Snowcover:
def __init__(self, uncert=None):
"""Initialize MODSCAG snow cover fraction object."""
<|body_0|>
def x(self, dt, models):
"""Retrieve state variable from database."""
<|body_1|>
def get(self, dt, models):
"""Retrieve observations from ... | stack_v2_sparse_classes_36k_train_021904 | 2,788 | permissive | [
{
"docstring": "Initialize MODSCAG snow cover fraction object.",
"name": "__init__",
"signature": "def __init__(self, uncert=None)"
},
{
"docstring": "Retrieve state variable from database.",
"name": "x",
"signature": "def x(self, dt, models)"
},
{
"docstring": "Retrieve observat... | 4 | stack_v2_sparse_classes_30k_train_008547 | Implement the Python class `Snowcover` described below.
Class description:
Implement the Snowcover class.
Method signatures and docstrings:
- def __init__(self, uncert=None): Initialize MODSCAG snow cover fraction object.
- def x(self, dt, models): Retrieve state variable from database.
- def get(self, dt, models): R... | Implement the Python class `Snowcover` described below.
Class description:
Implement the Snowcover class.
Method signatures and docstrings:
- def __init__(self, uncert=None): Initialize MODSCAG snow cover fraction object.
- def x(self, dt, models): Retrieve state variable from database.
- def get(self, dt, models): R... | 27d0abcaeefd8760ce68e05e52905aea5f8f3a51 | <|skeleton|>
class Snowcover:
def __init__(self, uncert=None):
"""Initialize MODSCAG snow cover fraction object."""
<|body_0|>
def x(self, dt, models):
"""Retrieve state variable from database."""
<|body_1|>
def get(self, dt, models):
"""Retrieve observations from ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Snowcover:
def __init__(self, uncert=None):
"""Initialize MODSCAG snow cover fraction object."""
self.statevar = ['swq']
self.obsvar = 'snow_cover'
self.uncert = uncert
def x(self, dt, models):
"""Retrieve state variable from database."""
data = {}
... | the_stack_v2_python_sparse | src/datasets/snowcover.py | nasa/RHEAS | train | 88 | |
14f58c051bd45199cc2f55a79f4e9885f8a9c5e8 | [
"if fe.ff_views in self.MAPPING:\n fe.ff_views = self.MAPPING[fe.ff_views]\n return True\nreturn False",
"self.require_cron_header()\nfeatures: ndb.Query = FeatureEntry.query(FeatureEntry.ff_views != NO_PUBLIC_SIGNALS)\ncount = 0\nbatch = []\nBATCH_SIZE = 100\nfor fe in features:\n if self.update_ff_view... | <|body_start_0|>
if fe.ff_views in self.MAPPING:
fe.ff_views = self.MAPPING[fe.ff_views]
return True
return False
<|end_body_0|>
<|body_start_1|>
self.require_cron_header()
features: ndb.Query = FeatureEntry.query(FeatureEntry.ff_views != NO_PUBLIC_SIGNALS)
... | MigrateGeckoViews | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MigrateGeckoViews:
def update_ff_views(self, fe):
"""Update ff_views and return True if update was needed."""
<|body_0|>
def get_template_data(self, **kwargs):
"""Change gecko views from old options to a more common list."""
<|body_1|>
<|end_skeleton|>
<|bo... | stack_v2_sparse_classes_36k_train_021905 | 7,549 | permissive | [
{
"docstring": "Update ff_views and return True if update was needed.",
"name": "update_ff_views",
"signature": "def update_ff_views(self, fe)"
},
{
"docstring": "Change gecko views from old options to a more common list.",
"name": "get_template_data",
"signature": "def get_template_data... | 2 | stack_v2_sparse_classes_30k_train_015325 | Implement the Python class `MigrateGeckoViews` described below.
Class description:
Implement the MigrateGeckoViews class.
Method signatures and docstrings:
- def update_ff_views(self, fe): Update ff_views and return True if update was needed.
- def get_template_data(self, **kwargs): Change gecko views from old option... | Implement the Python class `MigrateGeckoViews` described below.
Class description:
Implement the MigrateGeckoViews class.
Method signatures and docstrings:
- def update_ff_views(self, fe): Update ff_views and return True if update was needed.
- def get_template_data(self, **kwargs): Change gecko views from old option... | 17f9886d064da5bda84006d5866077727646fff2 | <|skeleton|>
class MigrateGeckoViews:
def update_ff_views(self, fe):
"""Update ff_views and return True if update was needed."""
<|body_0|>
def get_template_data(self, **kwargs):
"""Change gecko views from old options to a more common list."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MigrateGeckoViews:
def update_ff_views(self, fe):
"""Update ff_views and return True if update was needed."""
if fe.ff_views in self.MAPPING:
fe.ff_views = self.MAPPING[fe.ff_views]
return True
return False
def get_template_data(self, **kwargs):
"""... | the_stack_v2_python_sparse | internals/maintenance_scripts.py | GoogleChrome/chromium-dashboard | train | 574 | |
8f08a3634154cb2bc8caada8c7b81685d16f84bf | [
"provinces = 0\nvisited = set()\nq = deque()\nfor left in range(len(is_connected)):\n if left not in visited:\n q.append(left)\n while q:\n curr = q.popleft()\n if curr not in visited:\n visited.add(curr)\n for neighbor in range(len(is_connected)):\n ... | <|body_start_0|>
provinces = 0
visited = set()
q = deque()
for left in range(len(is_connected)):
if left not in visited:
q.append(left)
while q:
curr = q.popleft()
if curr not in visited:
... | City | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class City:
def number_of_provinces_bfs(self, is_connected: List[List[int]]) -> int:
"""Approach: BFS Time Complexity: O(N^2) Space Complexity: O(N) :param is_connected: :return:"""
<|body_0|>
def number_of_provinces_dfs(self, is_connected: List[List[int]]) -> int:
"""Appr... | stack_v2_sparse_classes_36k_train_021906 | 2,443 | no_license | [
{
"docstring": "Approach: BFS Time Complexity: O(N^2) Space Complexity: O(N) :param is_connected: :return:",
"name": "number_of_provinces_bfs",
"signature": "def number_of_provinces_bfs(self, is_connected: List[List[int]]) -> int"
},
{
"docstring": "Approach: DFS Time Complexity: O(N^2) Space Co... | 2 | stack_v2_sparse_classes_30k_train_007151 | Implement the Python class `City` described below.
Class description:
Implement the City class.
Method signatures and docstrings:
- def number_of_provinces_bfs(self, is_connected: List[List[int]]) -> int: Approach: BFS Time Complexity: O(N^2) Space Complexity: O(N) :param is_connected: :return:
- def number_of_provin... | Implement the Python class `City` described below.
Class description:
Implement the City class.
Method signatures and docstrings:
- def number_of_provinces_bfs(self, is_connected: List[List[int]]) -> int: Approach: BFS Time Complexity: O(N^2) Space Complexity: O(N) :param is_connected: :return:
- def number_of_provin... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class City:
def number_of_provinces_bfs(self, is_connected: List[List[int]]) -> int:
"""Approach: BFS Time Complexity: O(N^2) Space Complexity: O(N) :param is_connected: :return:"""
<|body_0|>
def number_of_provinces_dfs(self, is_connected: List[List[int]]) -> int:
"""Appr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class City:
def number_of_provinces_bfs(self, is_connected: List[List[int]]) -> int:
"""Approach: BFS Time Complexity: O(N^2) Space Complexity: O(N) :param is_connected: :return:"""
provinces = 0
visited = set()
q = deque()
for left in range(len(is_connected)):
if... | the_stack_v2_python_sparse | goldman_sachs/number_of_provinces.py | Shiv2157k/leet_code | train | 1 | |
5683f229e07f069407ec15c69ad24d472917e3ce | [
"try:\n params = request._serialize()\n headers = request.headers\n body = self.call('CreateTtsTask', params, headers=headers)\n response = json.loads(body)\n model = models.CreateTtsTaskResponse()\n model._deserialize(response['Response'])\n return model\nexcept Exception as e:\n if isinsta... | <|body_start_0|>
try:
params = request._serialize()
headers = request.headers
body = self.call('CreateTtsTask', params, headers=headers)
response = json.loads(body)
model = models.CreateTtsTaskResponse()
model._deserialize(response['Respons... | TtsClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TtsClient:
def CreateTtsTask(self, request):
"""本接口服务对10万字符以内的文本进行语音合成，异步返回音频结果。满足一次性合成较长文本的客户需求，如阅读播报、新闻媒体等场景。 <li>支持音频格式：mp3,wav,pcm</li> <li>支持音频采样率：16000 Hz, 8000 Hz</li> <li>支持中文普通话、英文、中英文混读、粤语合成</li> <li>支持语速、音量设置</li> <li>支持回调或轮询的方式获取结果，结果获取请参考 长文本语音合成结果查询。</li> <li>提交长文本语音合成请求后，合... | stack_v2_sparse_classes_36k_train_021907 | 5,886 | permissive | [
{
"docstring": "本接口服务对10万字符以内的文本进行语音合成，异步返回音频结果。满足一次性合成较长文本的客户需求，如阅读播报、新闻媒体等场景。 <li>支持音频格式：mp3,wav,pcm</li> <li>支持音频采样率：16000 Hz, 8000 Hz</li> <li>支持中文普通话、英文、中英文混读、粤语合成</li> <li>支持语速、音量设置</li> <li>支持回调或轮询的方式获取结果，结果获取请参考 长文本语音合成结果查询。</li> <li>提交长文本语音合成请求后，合成结果在3小时内完成，音频文件在服务端可保存24小时</li> <p></p> 长文本合成支持 SSML，语法详... | 3 | null | Implement the Python class `TtsClient` described below.
Class description:
Implement the TtsClient class.
Method signatures and docstrings:
- def CreateTtsTask(self, request): 本接口服务对10万字符以内的文本进行语音合成，异步返回音频结果。满足一次性合成较长文本的客户需求，如阅读播报、新闻媒体等场景。 <li>支持音频格式：mp3,wav,pcm</li> <li>支持音频采样率：16000 Hz, 8000 Hz</li> <li>支持中文普通话、英文、... | Implement the Python class `TtsClient` described below.
Class description:
Implement the TtsClient class.
Method signatures and docstrings:
- def CreateTtsTask(self, request): 本接口服务对10万字符以内的文本进行语音合成，异步返回音频结果。满足一次性合成较长文本的客户需求，如阅读播报、新闻媒体等场景。 <li>支持音频格式：mp3,wav,pcm</li> <li>支持音频采样率：16000 Hz, 8000 Hz</li> <li>支持中文普通话、英文、... | 6baf00a5a56ba58b6a1123423e0a1422d17a0201 | <|skeleton|>
class TtsClient:
def CreateTtsTask(self, request):
"""本接口服务对10万字符以内的文本进行语音合成，异步返回音频结果。满足一次性合成较长文本的客户需求，如阅读播报、新闻媒体等场景。 <li>支持音频格式：mp3,wav,pcm</li> <li>支持音频采样率：16000 Hz, 8000 Hz</li> <li>支持中文普通话、英文、中英文混读、粤语合成</li> <li>支持语速、音量设置</li> <li>支持回调或轮询的方式获取结果，结果获取请参考 长文本语音合成结果查询。</li> <li>提交长文本语音合成请求后，合... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TtsClient:
def CreateTtsTask(self, request):
"""本接口服务对10万字符以内的文本进行语音合成，异步返回音频结果。满足一次性合成较长文本的客户需求，如阅读播报、新闻媒体等场景。 <li>支持音频格式：mp3,wav,pcm</li> <li>支持音频采样率：16000 Hz, 8000 Hz</li> <li>支持中文普通话、英文、中英文混读、粤语合成</li> <li>支持语速、音量设置</li> <li>支持回调或轮询的方式获取结果，结果获取请参考 长文本语音合成结果查询。</li> <li>提交长文本语音合成请求后，合成结果在3小时内完成，音频文... | the_stack_v2_python_sparse | tencentcloud/tts/v20190823/tts_client.py | TencentCloud/tencentcloud-sdk-python | train | 594 | |
30bd1d1296bad3941e7174f1fc07a2e29b80ab5e | [
"self.num_points = num_points\nself.x_values = [ini_coords[0]]\nself.y_values = [ini_coords[1]]\nself.phi_ = []\nself.theta = 0\nself.phi = init_phi\nself.phi_.append(self.phi)\nself.deltaPhi = 0",
"while len(self.x_values) < self.num_points:\n self.theta = PI / 2\n self.deltaPhi = deltaAngle(a=1 / 3)\n ... | <|body_start_0|>
self.num_points = num_points
self.x_values = [ini_coords[0]]
self.y_values = [ini_coords[1]]
self.phi_ = []
self.theta = 0
self.phi = init_phi
self.phi_.append(self.phi)
self.deltaPhi = 0
<|end_body_0|>
<|body_start_1|>
while len(... | A class to generate data. | GenerateLine2D | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GenerateLine2D:
"""A class to generate data."""
def __init__(self, ini_coords=[], init_phi=PI / 4, num_points=5000):
"""Initialize attributes of a data."""
<|body_0|>
def fill_points(self):
"""Calculate all the points in the data."""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_36k_train_021908 | 20,287 | no_license | [
{
"docstring": "Initialize attributes of a data.",
"name": "__init__",
"signature": "def __init__(self, ini_coords=[], init_phi=PI / 4, num_points=5000)"
},
{
"docstring": "Calculate all the points in the data.",
"name": "fill_points",
"signature": "def fill_points(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006904 | Implement the Python class `GenerateLine2D` described below.
Class description:
A class to generate data.
Method signatures and docstrings:
- def __init__(self, ini_coords=[], init_phi=PI / 4, num_points=5000): Initialize attributes of a data.
- def fill_points(self): Calculate all the points in the data. | Implement the Python class `GenerateLine2D` described below.
Class description:
A class to generate data.
Method signatures and docstrings:
- def __init__(self, ini_coords=[], init_phi=PI / 4, num_points=5000): Initialize attributes of a data.
- def fill_points(self): Calculate all the points in the data.
<|skeleton... | 6e7a278031ff0a1eb51e7810b326d66524d4aef3 | <|skeleton|>
class GenerateLine2D:
"""A class to generate data."""
def __init__(self, ini_coords=[], init_phi=PI / 4, num_points=5000):
"""Initialize attributes of a data."""
<|body_0|>
def fill_points(self):
"""Calculate all the points in the data."""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GenerateLine2D:
"""A class to generate data."""
def __init__(self, ini_coords=[], init_phi=PI / 4, num_points=5000):
"""Initialize attributes of a data."""
self.num_points = num_points
self.x_values = [ini_coords[0]]
self.y_values = [ini_coords[1]]
self.phi_ = []
... | the_stack_v2_python_sparse | check_data/generate_data/generate_data.py | c-feng/Neuron-Tracking | train | 1 |
e821956fe365552bf5e725daea7a87b27b5d45de | [
"positive_ctx = row['positive_ctx']\npositive_ctx_tokens = self.tokenizer.tokenize(positive_ctx)\npositive_ctx_token_ids, positive_ctx_segment_labels, positive_ctx_seq_len, positive_ctx_positions = self.tensorizer_script_impl.numberize([positive_ctx_tokens])\nnegative_ctxs = row['negative_ctxs']\nif negative_ctxs:\... | <|body_start_0|>
positive_ctx = row['positive_ctx']
positive_ctx_tokens = self.tokenizer.tokenize(positive_ctx)
positive_ctx_token_ids, positive_ctx_segment_labels, positive_ctx_seq_len, positive_ctx_positions = self.tensorizer_script_impl.numberize([positive_ctx_tokens])
negative_ctxs =... | Methods numberize() and tensorize() implement https://fburl.com/an4fv7m1. | BERTContextTensorizerForDenseRetrieval | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BERTContextTensorizerForDenseRetrieval:
"""Methods numberize() and tensorize() implement https://fburl.com/an4fv7m1."""
def numberize(self, row: Dict) -> Tuple[Any, ...]:
"""This function contains logic for converting tokens into ids based on the specified vocab. It also outputs, for... | stack_v2_sparse_classes_36k_train_021909 | 5,499 | permissive | [
{
"docstring": "This function contains logic for converting tokens into ids based on the specified vocab. It also outputs, for each instance, the vectors needed to run the actual model. It works off of one sample.",
"name": "numberize",
"signature": "def numberize(self, row: Dict) -> Tuple[Any, ...]"
... | 2 | stack_v2_sparse_classes_30k_train_016818 | Implement the Python class `BERTContextTensorizerForDenseRetrieval` described below.
Class description:
Methods numberize() and tensorize() implement https://fburl.com/an4fv7m1.
Method signatures and docstrings:
- def numberize(self, row: Dict) -> Tuple[Any, ...]: This function contains logic for converting tokens in... | Implement the Python class `BERTContextTensorizerForDenseRetrieval` described below.
Class description:
Methods numberize() and tensorize() implement https://fburl.com/an4fv7m1.
Method signatures and docstrings:
- def numberize(self, row: Dict) -> Tuple[Any, ...]: This function contains logic for converting tokens in... | 3bba58a048c87d7c93a41830fa7853896c4b3e66 | <|skeleton|>
class BERTContextTensorizerForDenseRetrieval:
"""Methods numberize() and tensorize() implement https://fburl.com/an4fv7m1."""
def numberize(self, row: Dict) -> Tuple[Any, ...]:
"""This function contains logic for converting tokens into ids based on the specified vocab. It also outputs, for... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BERTContextTensorizerForDenseRetrieval:
"""Methods numberize() and tensorize() implement https://fburl.com/an4fv7m1."""
def numberize(self, row: Dict) -> Tuple[Any, ...]:
"""This function contains logic for converting tokens into ids based on the specified vocab. It also outputs, for each instanc... | the_stack_v2_python_sparse | pytext/data/dense_retrieval_tensorizer.py | mruberry/pytext | train | 2 |
984755bbd2c6d733c0252b21e9ee9c5b5a1e1ee0 | [
"stones = {tuple(p) for p in stones}\n\ndef find_min():\n p = None\n m = float('inf')\n for i, (x, y) in enumerate(stones):\n overlaps = len(xp[x].union(yp[y])) - 1\n if 0 < overlaps < m:\n m = overlaps\n p = (x, y)\n return p\n\ndef remove_stone(p):\n xp[p[0]].rem... | <|body_start_0|>
stones = {tuple(p) for p in stones}
def find_min():
p = None
m = float('inf')
for i, (x, y) in enumerate(stones):
overlaps = len(xp[x].union(yp[y])) - 1
if 0 < overlaps < m:
m = overlaps
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def removeStones(self, stones: List[List[int]]) -> int:
"""05/29/2020 00:14 Incorrect"""
<|body_0|>
def removeStones(self, stones: List[List[int]]) -> int:
"""05/29/2020 00:55"""
<|body_1|>
def removeStones(self, stones: List[List[int]]) -> int... | stack_v2_sparse_classes_36k_train_021910 | 6,379 | no_license | [
{
"docstring": "05/29/2020 00:14 Incorrect",
"name": "removeStones",
"signature": "def removeStones(self, stones: List[List[int]]) -> int"
},
{
"docstring": "05/29/2020 00:55",
"name": "removeStones",
"signature": "def removeStones(self, stones: List[List[int]]) -> int"
},
{
"doc... | 4 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeStones(self, stones: List[List[int]]) -> int: 05/29/2020 00:14 Incorrect
- def removeStones(self, stones: List[List[int]]) -> int: 05/29/2020 00:55
- def removeStones(s... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def removeStones(self, stones: List[List[int]]) -> int: 05/29/2020 00:14 Incorrect
- def removeStones(self, stones: List[List[int]]) -> int: 05/29/2020 00:55
- def removeStones(s... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def removeStones(self, stones: List[List[int]]) -> int:
"""05/29/2020 00:14 Incorrect"""
<|body_0|>
def removeStones(self, stones: List[List[int]]) -> int:
"""05/29/2020 00:55"""
<|body_1|>
def removeStones(self, stones: List[List[int]]) -> int... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def removeStones(self, stones: List[List[int]]) -> int:
"""05/29/2020 00:14 Incorrect"""
stones = {tuple(p) for p in stones}
def find_min():
p = None
m = float('inf')
for i, (x, y) in enumerate(stones):
overlaps = len(xp[x]... | the_stack_v2_python_sparse | leetcode/solved/984_Most_Stones_Removed_with_Same_Row_or_Column/solution.py | sungminoh/algorithms | train | 0 | |
a514b0b25c5b7565b1842b8c71783326d64e52ad | [
"del update_time\ncurrent_user = info.context['user']\nerr = 'Error in GQL query - resolve_all_pages.'\nwith ax_model.try_catch(info.context['session'], err, no_commit=True) as db_session:\n user_guid = current_user.get('user_id', None) if current_user else None\n user_is_admin = current_user.get('is_admin', ... | <|body_start_0|>
del update_time
current_user = info.context['user']
err = 'Error in GQL query - resolve_all_pages.'
with ax_model.try_catch(info.context['session'], err, no_commit=True) as db_session:
user_guid = current_user.get('user_id', None) if current_user else None
... | AxPage queryes | PagesQuery | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PagesQuery:
"""AxPage queryes"""
async def resolve_all_pages(self, info, update_time):
"""Get all pages"""
<|body_0|>
async def resolve_page_data(self, info, guid=None, update_time=None):
"""Get specific page"""
<|body_1|>
<|end_skeleton|>
<|body_start_... | stack_v2_sparse_classes_36k_train_021911 | 11,421 | no_license | [
{
"docstring": "Get all pages",
"name": "resolve_all_pages",
"signature": "async def resolve_all_pages(self, info, update_time)"
},
{
"docstring": "Get specific page",
"name": "resolve_page_data",
"signature": "async def resolve_page_data(self, info, guid=None, update_time=None)"
}
] | 2 | null | Implement the Python class `PagesQuery` described below.
Class description:
AxPage queryes
Method signatures and docstrings:
- async def resolve_all_pages(self, info, update_time): Get all pages
- async def resolve_page_data(self, info, guid=None, update_time=None): Get specific page | Implement the Python class `PagesQuery` described below.
Class description:
AxPage queryes
Method signatures and docstrings:
- async def resolve_all_pages(self, info, update_time): Get all pages
- async def resolve_page_data(self, info, guid=None, update_time=None): Get specific page
<|skeleton|>
class PagesQuery:
... | 3540979e680732d38e25a6b39f09338985de6743 | <|skeleton|>
class PagesQuery:
"""AxPage queryes"""
async def resolve_all_pages(self, info, update_time):
"""Get all pages"""
<|body_0|>
async def resolve_page_data(self, info, guid=None, update_time=None):
"""Get specific page"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PagesQuery:
"""AxPage queryes"""
async def resolve_all_pages(self, info, update_time):
"""Get all pages"""
del update_time
current_user = info.context['user']
err = 'Error in GQL query - resolve_all_pages.'
with ax_model.try_catch(info.context['session'], err, no_c... | the_stack_v2_python_sparse | Calculation methods/CalcMethods_Lab_3_V15_Task_3_15/venv/Lib/site-packages/ax/backend/schemas/pages_schema.py | areyykarthik/Zhukouski_Pavel_BSU_Projects | train | 0 |
8d186842ae3a41bc6d217034c9ec605047f200d8 | [
"super().__init__(label)\nself.setFocusPolicy(QtCore.Qt.StrongFocus)\nself.setChecked(checked)\nif slot:\n self.stateChanged.connect(slot)",
"if event.key() == QtCore.Qt.Key_Up or event.key() == QtCore.Qt.Key_Down:\n if self.isChecked():\n self.setCheckState(QtCore.Qt.Unchecked)\n else:\n s... | <|body_start_0|>
super().__init__(label)
self.setFocusPolicy(QtCore.Qt.StrongFocus)
self.setChecked(checked)
if slot:
self.stateChanged.connect(slot)
<|end_body_0|>
<|body_start_1|>
if event.key() == QtCore.Qt.Key_Up or event.key() == QtCore.Qt.Key_Down:
... | A checkbox with associated label and slot function. | NXCheckBox | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NXCheckBox:
"""A checkbox with associated label and slot function."""
def __init__(self, label=None, slot=None, checked=False):
"""Initialize the checkbox. Parameters ---------- label : str, optional Text describing the checkbox. slot : func, optional Function to be called when the c... | stack_v2_sparse_classes_36k_train_021912 | 43,131 | permissive | [
{
"docstring": "Initialize the checkbox. Parameters ---------- label : str, optional Text describing the checkbox. slot : func, optional Function to be called when the checkbox state is changed. checked : bool, optional Initial checkbox state (the default is False).",
"name": "__init__",
"signature": "d... | 2 | stack_v2_sparse_classes_30k_train_018075 | Implement the Python class `NXCheckBox` described below.
Class description:
A checkbox with associated label and slot function.
Method signatures and docstrings:
- def __init__(self, label=None, slot=None, checked=False): Initialize the checkbox. Parameters ---------- label : str, optional Text describing the checkbo... | Implement the Python class `NXCheckBox` described below.
Class description:
A checkbox with associated label and slot function.
Method signatures and docstrings:
- def __init__(self, label=None, slot=None, checked=False): Initialize the checkbox. Parameters ---------- label : str, optional Text describing the checkbo... | 97110aa2ebeff95cc78496bf5396d6b51fc151a7 | <|skeleton|>
class NXCheckBox:
"""A checkbox with associated label and slot function."""
def __init__(self, label=None, slot=None, checked=False):
"""Initialize the checkbox. Parameters ---------- label : str, optional Text describing the checkbox. slot : func, optional Function to be called when the c... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NXCheckBox:
"""A checkbox with associated label and slot function."""
def __init__(self, label=None, slot=None, checked=False):
"""Initialize the checkbox. Parameters ---------- label : str, optional Text describing the checkbox. slot : func, optional Function to be called when the checkbox state... | the_stack_v2_python_sparse | src/nexpy/gui/widgets.py | nexpy/nexpy | train | 42 |
ea6b5f7e90939ee120e24683a075d09b9f1fdd0f | [
"left, right = (0, len(nums) - 1)\nidx = 0\nwhile idx <= right:\n while idx <= right and nums[idx] == 2:\n nums[idx], nums[right] = (nums[right], nums[idx])\n right -= 1\n if nums[idx] == 0:\n nums[idx], nums[left] = (nums[left], nums[idx])\n left += 1\n idx += 1",
"n = len(nu... | <|body_start_0|>
left, right = (0, len(nums) - 1)
idx = 0
while idx <= right:
while idx <= right and nums[idx] == 2:
nums[idx], nums[right] = (nums[right], nums[idx])
right -= 1
if nums[idx] == 0:
nums[idx], nums[left] = (nu... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def sortColors(self, nums: List[int]) -> None:
"""双指针（头尾）"""
<|body_0|>
def sortColorsOneScan(self, nums: List[int]) -> None:
"""双指针（前后）"""
<|body_1|>
def sortColorsTwoScan(self, nums: List[int]) -> None:
"""单指针（两次遍历）"""
<|body_... | stack_v2_sparse_classes_36k_train_021913 | 3,452 | no_license | [
{
"docstring": "双指针（头尾）",
"name": "sortColors",
"signature": "def sortColors(self, nums: List[int]) -> None"
},
{
"docstring": "双指针（前后）",
"name": "sortColorsOneScan",
"signature": "def sortColorsOneScan(self, nums: List[int]) -> None"
},
{
"docstring": "单指针（两次遍历）",
"name": "s... | 4 | stack_v2_sparse_classes_30k_train_016507 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortColors(self, nums: List[int]) -> None: 双指针（头尾）
- def sortColorsOneScan(self, nums: List[int]) -> None: 双指针（前后）
- def sortColorsTwoScan(self, nums: List[int]) -> None: 单指针... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def sortColors(self, nums: List[int]) -> None: 双指针（头尾）
- def sortColorsOneScan(self, nums: List[int]) -> None: 双指针（前后）
- def sortColorsTwoScan(self, nums: List[int]) -> None: 单指针... | 52756b30e9d51794591aca030bc918e707f473f1 | <|skeleton|>
class Solution:
def sortColors(self, nums: List[int]) -> None:
"""双指针（头尾）"""
<|body_0|>
def sortColorsOneScan(self, nums: List[int]) -> None:
"""双指针（前后）"""
<|body_1|>
def sortColorsTwoScan(self, nums: List[int]) -> None:
"""单指针（两次遍历）"""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def sortColors(self, nums: List[int]) -> None:
"""双指针（头尾）"""
left, right = (0, len(nums) - 1)
idx = 0
while idx <= right:
while idx <= right and nums[idx] == 2:
nums[idx], nums[right] = (nums[right], nums[idx])
right -= 1
... | the_stack_v2_python_sparse | 75.颜色分类/solution.py | QtTao/daily_leetcode | train | 0 | |
b75b30fef07e84cb2bb9fb8eaf9e36110d12fbfa | [
"for item in response.css('#contentColumn table')[-1:].css('tr')[1:]:\n start = self._parse_start(item)\n if not start:\n continue\n meeting = Meeting(title='Monument Commission', description='', classification=COMMISSION, start=start, end=None, all_day=False, time_notes='', location=self._parse_loc... | <|body_start_0|>
for item in response.css('#contentColumn table')[-1:].css('tr')[1:]:
start = self._parse_start(item)
if not start:
continue
meeting = Meeting(title='Monument Commission', description='', classification=COMMISSION, start=start, end=None, all_da... | CuyaMonumentSpider | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CuyaMonumentSpider:
def parse(self, response):
"""`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs."""
<|body_0|>
def _parse_start(self, item):
"""Parse start datetime as a naive datetime o... | stack_v2_sparse_classes_36k_train_021914 | 2,805 | permissive | [
{
"docstring": "`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs.",
"name": "parse",
"signature": "def parse(self, response)"
},
{
"docstring": "Parse start datetime as a naive datetime object.",
"name": "_parse_st... | 4 | stack_v2_sparse_classes_30k_train_011212 | Implement the Python class `CuyaMonumentSpider` described below.
Class description:
Implement the CuyaMonumentSpider class.
Method signatures and docstrings:
- def parse(self, response): `parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs.
- d... | Implement the Python class `CuyaMonumentSpider` described below.
Class description:
Implement the CuyaMonumentSpider class.
Method signatures and docstrings:
- def parse(self, response): `parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs.
- d... | 105ed65078ab4f7ca54193cc54c8c52dc174d08b | <|skeleton|>
class CuyaMonumentSpider:
def parse(self, response):
"""`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs."""
<|body_0|>
def _parse_start(self, item):
"""Parse start datetime as a naive datetime o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CuyaMonumentSpider:
def parse(self, response):
"""`parse` should always `yield` Meeting items. Change the `_parse_title`, `_parse_start`, etc methods to fit your scraping needs."""
for item in response.css('#contentColumn table')[-1:].css('tr')[1:]:
start = self._parse_start(item)
... | the_stack_v2_python_sparse | city_scrapers/spiders/cuya_monument.py | City-Bureau/city-scrapers-cle | train | 17 | |
c1ceafabbcaff4ef3a603106b9fb1d47d4c2d58b | [
"self.rects = rects\nself.sums = []\nfor w in rects:\n weight = (w[2] - w[0] + 1) * (w[3] - w[1] + 1)\n if not self.sums:\n self.sums.append(weight)\n else:\n self.sums.append(weight + self.sums[-1])",
"import bisect\npick = random.uniform(0, self.sums[-1])\nb = bisect.bisect_left(self.sums... | <|body_start_0|>
self.rects = rects
self.sums = []
for w in rects:
weight = (w[2] - w[0] + 1) * (w[3] - w[1] + 1)
if not self.sums:
self.sums.append(weight)
else:
self.sums.append(weight + self.sums[-1])
<|end_body_0|>
<|body_s... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, rects):
""":type w: List[int] 268 ms"""
<|body_0|>
def pick(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.rects = rects
self.sums = []
for w in rects:
weight = (w[... | stack_v2_sparse_classes_36k_train_021915 | 2,805 | no_license | [
{
"docstring": ":type w: List[int] 268 ms",
"name": "__init__",
"signature": "def __init__(self, rects)"
},
{
"docstring": ":rtype: int",
"name": "pick",
"signature": "def pick(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_006797 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, rects): :type w: List[int] 268 ms
- def pick(self): :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, rects): :type w: List[int] 268 ms
- def pick(self): :rtype: int
<|skeleton|>
class Solution:
def __init__(self, rects):
""":type w: List[int] 268... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def __init__(self, rects):
""":type w: List[int] 268 ms"""
<|body_0|>
def pick(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, rects):
""":type w: List[int] 268 ms"""
self.rects = rects
self.sums = []
for w in rects:
weight = (w[2] - w[0] + 1) * (w[3] - w[1] + 1)
if not self.sums:
self.sums.append(weight)
else:
... | the_stack_v2_python_sparse | RandomPointInNonoverlappingRectangles_MID_882.py | 953250587/leetcode-python | train | 2 | |
73309d260a18bc14d6796bcd33a22d92ceb748fe | [
"self.method = method\nself.bins = bins\nself.interpolation = interpolation\nself.variable_width = variable_width\nself.model = model",
"X = load_and_check(X)\ny = load_and_check(y)\ny = column_or_1d(y)\nlabel_encoder = LabelEncoder()\ny = label_encoder.fit_transform(y).astype(np.float)\nif len(label_encoder.clas... | <|body_start_0|>
self.method = method
self.bins = bins
self.interpolation = interpolation
self.variable_width = variable_width
self.model = model
<|end_body_0|>
<|body_start_1|>
X = load_and_check(X)
y = load_and_check(y)
y = column_or_1d(y)
label... | Probability calibration. | CalibratedClassifier | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CalibratedClassifier:
"""Probability calibration."""
def __init__(self, model, method='histogram', bins=100, interpolation=None, variable_width=False):
"""Constructor. Parameters ----------"""
<|body_0|>
def fit(self, X, y):
"""Fit the calibrated model. Parameter... | stack_v2_sparse_classes_36k_train_021916 | 5,898 | permissive | [
{
"docstring": "Constructor. Parameters ----------",
"name": "__init__",
"signature": "def __init__(self, model, method='histogram', bins=100, interpolation=None, variable_width=False)"
},
{
"docstring": "Fit the calibrated model. Parameters ---------- * `X` [array-like, shape=(n_samples, n_feat... | 4 | stack_v2_sparse_classes_30k_train_009459 | Implement the Python class `CalibratedClassifier` described below.
Class description:
Probability calibration.
Method signatures and docstrings:
- def __init__(self, model, method='histogram', bins=100, interpolation=None, variable_width=False): Constructor. Parameters ----------
- def fit(self, X, y): Fit the calibr... | Implement the Python class `CalibratedClassifier` described below.
Class description:
Probability calibration.
Method signatures and docstrings:
- def __init__(self, model, method='histogram', bins=100, interpolation=None, variable_width=False): Constructor. Parameters ----------
- def fit(self, X, y): Fit the calibr... | 383ef84c449d654d783b4e8bdbb847ee8cbf24b9 | <|skeleton|>
class CalibratedClassifier:
"""Probability calibration."""
def __init__(self, model, method='histogram', bins=100, interpolation=None, variable_width=False):
"""Constructor. Parameters ----------"""
<|body_0|>
def fit(self, X, y):
"""Fit the calibrated model. Parameter... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CalibratedClassifier:
"""Probability calibration."""
def __init__(self, model, method='histogram', bins=100, interpolation=None, variable_width=False):
"""Constructor. Parameters ----------"""
self.method = method
self.bins = bins
self.interpolation = interpolation
... | the_stack_v2_python_sparse | ml/calibration.py | leonoravesterbacka/carl-torch | train | 10 |
1a40a185be9faa62d8993704205fc718adb50486 | [
"if self.CORS_ORIGIN:\n self.set_header('Access-Control-Allow-Origin', self.CORS_ORIGIN)\nif self.CORS_EXPOSE_HEADERS:\n self.set_header('Access-Control-Expose-Headers', self.CORS_EXPOSE_HEADERS)",
"if self.CORS_HEADERS:\n self.set_header('Access-Control-Allow-Headers', self.CORS_HEADERS)\nif self.CORS_M... | <|body_start_0|>
if self.CORS_ORIGIN:
self.set_header('Access-Control-Allow-Origin', self.CORS_ORIGIN)
if self.CORS_EXPOSE_HEADERS:
self.set_header('Access-Control-Expose-Headers', self.CORS_EXPOSE_HEADERS)
<|end_body_0|>
<|body_start_1|>
if self.CORS_HEADERS:
... | CorsMixin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CorsMixin:
def set_default_headers(self):
"""设置默认头"""
<|body_0|>
def options(self, *args, **kwargs):
"""写入跨域请求header"""
<|body_1|>
def _get_methods(self):
"""设置支持的跨域方法"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
if self.CORS... | stack_v2_sparse_classes_36k_train_021917 | 2,506 | permissive | [
{
"docstring": "设置默认头",
"name": "set_default_headers",
"signature": "def set_default_headers(self)"
},
{
"docstring": "写入跨域请求header",
"name": "options",
"signature": "def options(self, *args, **kwargs)"
},
{
"docstring": "设置支持的跨域方法",
"name": "_get_methods",
"signature": "... | 3 | stack_v2_sparse_classes_30k_train_021168 | Implement the Python class `CorsMixin` described below.
Class description:
Implement the CorsMixin class.
Method signatures and docstrings:
- def set_default_headers(self): 设置默认头
- def options(self, *args, **kwargs): 写入跨域请求header
- def _get_methods(self): 设置支持的跨域方法 | Implement the Python class `CorsMixin` described below.
Class description:
Implement the CorsMixin class.
Method signatures and docstrings:
- def set_default_headers(self): 设置默认头
- def options(self, *args, **kwargs): 写入跨域请求header
- def _get_methods(self): 设置支持的跨域方法
<|skeleton|>
class CorsMixin:
def set_default_... | 9999d70429d9f773501f9a11910997343ff2df93 | <|skeleton|>
class CorsMixin:
def set_default_headers(self):
"""设置默认头"""
<|body_0|>
def options(self, *args, **kwargs):
"""写入跨域请求header"""
<|body_1|>
def _get_methods(self):
"""设置支持的跨域方法"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CorsMixin:
def set_default_headers(self):
"""设置默认头"""
if self.CORS_ORIGIN:
self.set_header('Access-Control-Allow-Origin', self.CORS_ORIGIN)
if self.CORS_EXPOSE_HEADERS:
self.set_header('Access-Control-Expose-Headers', self.CORS_EXPOSE_HEADERS)
def options(s... | the_stack_v2_python_sparse | api/common/helpers/tornado_cors.py | bopopescu/smp | train | 0 | |
dd73d156fc1da3eb6ba837a2debd1c29998f67c2 | [
"super(DetachedPPaNet, self).__init__()\nself.conv_1 = nn.Sequential(nn.Conv2d(n_channels, 64, kernel_size=3, stride=1, padding=1), nn.ReLU(), nn.MaxPool2d(kernel_size=2, stride=2, padding=1))\nself.conv_2 = nn.Sequential(nn.Conv2d(64, 128, kernel_size=3, stride=1, padding=1), nn.ReLU(), nn.BatchNorm2d(128), nn.Max... | <|body_start_0|>
super(DetachedPPaNet, self).__init__()
self.conv_1 = nn.Sequential(nn.Conv2d(n_channels, 64, kernel_size=3, stride=1, padding=1), nn.ReLU(), nn.MaxPool2d(kernel_size=2, stride=2, padding=1))
self.conv_2 = nn.Sequential(nn.Conv2d(64, 128, kernel_size=3, stride=1, padding=1), nn.R... | This class implements a Multi-layer Perceptron in PyTorch. It handles the different layers and parameters of the model. Once initialized an MLP object can perform forward. | DetachedPPaNet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DetachedPPaNet:
"""This class implements a Multi-layer Perceptron in PyTorch. It handles the different layers and parameters of the model. Once initialized an MLP object can perform forward."""
def __init__(self, n_channels, EMBEDING_SIZE):
"""Initializes MLP object. Args: n_inputs: ... | stack_v2_sparse_classes_36k_train_021918 | 3,434 | no_license | [
{
"docstring": "Initializes MLP object. Args: n_inputs: number of inputs. n_hidden: list of ints, specifies the number of units in each linear layer. If the list is empty, the MLP will not have any linear layers, and the model will simply perform a multinomial logistic regression. n_classes: number of classes o... | 2 | stack_v2_sparse_classes_30k_train_011367 | Implement the Python class `DetachedPPaNet` described below.
Class description:
This class implements a Multi-layer Perceptron in PyTorch. It handles the different layers and parameters of the model. Once initialized an MLP object can perform forward.
Method signatures and docstrings:
- def __init__(self, n_channels,... | Implement the Python class `DetachedPPaNet` described below.
Class description:
This class implements a Multi-layer Perceptron in PyTorch. It handles the different layers and parameters of the model. Once initialized an MLP object can perform forward.
Method signatures and docstrings:
- def __init__(self, n_channels,... | b060caa315f0c066410da9580e64d6db0222f2a8 | <|skeleton|>
class DetachedPPaNet:
"""This class implements a Multi-layer Perceptron in PyTorch. It handles the different layers and parameters of the model. Once initialized an MLP object can perform forward."""
def __init__(self, n_channels, EMBEDING_SIZE):
"""Initializes MLP object. Args: n_inputs: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DetachedPPaNet:
"""This class implements a Multi-layer Perceptron in PyTorch. It handles the different layers and parameters of the model. Once initialized an MLP object can perform forward."""
def __init__(self, n_channels, EMBEDING_SIZE):
"""Initializes MLP object. Args: n_inputs: number of inp... | the_stack_v2_python_sparse | CIFAR-100/DetachedPPaNet.py | VCharatsidis/Unsupervised-Clustering | train | 1 |
766d0870f7958b2e883414a06d72c54e6286fb22 | [
"cname = '王jiu九'\nvalue = 'name'\nd_name = 'admin'\nbname = '2e2e2e20001'\ncp = ClientPage(self.driver)\ncp.client_inlet()\ncp.create_client_butt()\ncp.client_not_ret(cname, d_name, sj='1')\nbusy = BusinessPage(self.driver)\nbusy.business_edit_flow(0, bname, '233001')",
"cname = '王八0001'\nvalue = 'name'\nd_name =... | <|body_start_0|>
cname = '王jiu九'
value = 'name'
d_name = 'admin'
bname = '2e2e2e20001'
cp = ClientPage(self.driver)
cp.client_inlet()
cp.create_client_butt()
cp.client_not_ret(cname, d_name, sj='1')
busy = BusinessPage(self.driver)
busy.bus... | ClientAndBusiness | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClientAndBusiness:
def test_client_busniess1(self):
"""新建客户——同时创建商机"""
<|body_0|>
def test_client_busniess2(self):
"""新建客户——同时创建商机"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
cname = '王jiu九'
value = 'name'
d_name = 'admin'
... | stack_v2_sparse_classes_36k_train_021919 | 1,175 | no_license | [
{
"docstring": "新建客户——同时创建商机",
"name": "test_client_busniess1",
"signature": "def test_client_busniess1(self)"
},
{
"docstring": "新建客户——同时创建商机",
"name": "test_client_busniess2",
"signature": "def test_client_busniess2(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014216 | Implement the Python class `ClientAndBusiness` described below.
Class description:
Implement the ClientAndBusiness class.
Method signatures and docstrings:
- def test_client_busniess1(self): 新建客户——同时创建商机
- def test_client_busniess2(self): 新建客户——同时创建商机 | Implement the Python class `ClientAndBusiness` described below.
Class description:
Implement the ClientAndBusiness class.
Method signatures and docstrings:
- def test_client_busniess1(self): 新建客户——同时创建商机
- def test_client_busniess2(self): 新建客户——同时创建商机
<|skeleton|>
class ClientAndBusiness:
def test_client_busnie... | b98793fad55500ccb58105a24711ae4b3d8ac6c8 | <|skeleton|>
class ClientAndBusiness:
def test_client_busniess1(self):
"""新建客户——同时创建商机"""
<|body_0|>
def test_client_busniess2(self):
"""新建客户——同时创建商机"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ClientAndBusiness:
def test_client_busniess1(self):
"""新建客户——同时创建商机"""
cname = '王jiu九'
value = 'name'
d_name = 'admin'
bname = '2e2e2e20001'
cp = ClientPage(self.driver)
cp.client_inlet()
cp.create_client_butt()
cp.client_not_ret(cname, d... | the_stack_v2_python_sparse | testcase/test_client_and_business.py | chenkangkang002/CrmAuto | train | 0 | |
aeb1413f624bbc7ab7fa98b91e1a9a042ec7a5fa | [
"self.v = x\nself.cl = None\nself.cr = None\nreturn None",
"if not a or not isinstance(a, list):\n return TreeNode(None)\no = TreeNode(a[0])\nq = deque([o])\ni = 0\nn = len(a)\nwhile q:\n p = q.popleft()\n if 2 * i + 1 < n:\n p.cl = TreeNode(a[2 * i + 1])\n q.append(p.cl)\n if 2 * i + 2 ... | <|body_start_0|>
self.v = x
self.cl = None
self.cr = None
return None
<|end_body_0|>
<|body_start_1|>
if not a or not isinstance(a, list):
return TreeNode(None)
o = TreeNode(a[0])
q = deque([o])
i = 0
n = len(a)
while q:
... | Manage Node objects for binary trees. | TreeNode | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TreeNode:
"""Manage Node objects for binary trees."""
def __init__(self, x=None):
"""Constructor for TreeNode objects. :param (int or None) v: integer value for node :param TreeNode cl: pointer to left-side child node :param TreeNode cr: pointer to right-side child node :return: None... | stack_v2_sparse_classes_36k_train_021920 | 2,391 | permissive | [
{
"docstring": "Constructor for TreeNode objects. :param (int or None) v: integer value for node :param TreeNode cl: pointer to left-side child node :param TreeNode cr: pointer to right-side child node :return: None :rtype: None",
"name": "__init__",
"signature": "def __init__(self, x=None)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_006902 | Implement the Python class `TreeNode` described below.
Class description:
Manage Node objects for binary trees.
Method signatures and docstrings:
- def __init__(self, x=None): Constructor for TreeNode objects. :param (int or None) v: integer value for node :param TreeNode cl: pointer to left-side child node :param Tr... | Implement the Python class `TreeNode` described below.
Class description:
Manage Node objects for binary trees.
Method signatures and docstrings:
- def __init__(self, x=None): Constructor for TreeNode objects. :param (int or None) v: integer value for node :param TreeNode cl: pointer to left-side child node :param Tr... | 69f90877c5466927e8b081c4268cbcda074813ec | <|skeleton|>
class TreeNode:
"""Manage Node objects for binary trees."""
def __init__(self, x=None):
"""Constructor for TreeNode objects. :param (int or None) v: integer value for node :param TreeNode cl: pointer to left-side child node :param TreeNode cr: pointer to right-side child node :return: None... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TreeNode:
"""Manage Node objects for binary trees."""
def __init__(self, x=None):
"""Constructor for TreeNode objects. :param (int or None) v: integer value for node :param TreeNode cl: pointer to left-side child node :param TreeNode cr: pointer to right-side child node :return: None :rtype: None... | the_stack_v2_python_sparse | 0108_convert_sorted_array_binary_search_tree/python_util.py | arthurdysart/LeetCode | train | 0 |
6804043f2870e68ae5d0d4618d68b40dc09eadd9 | [
"for file, phase_sequence, output_signal in self.known_values:\n intcode_program = open(expanduser('~/code/aoc2019/07/%s' % file))\n mem = list(map(int, intcode_program.read().split(',')))\n result = intcode_computer.amplification_circuit(mem, phase_sequence)\n self.assertEqual(output_signal, result)",
... | <|body_start_0|>
for file, phase_sequence, output_signal in self.known_values:
intcode_program = open(expanduser('~/code/aoc2019/07/%s' % file))
mem = list(map(int, intcode_program.read().split(',')))
result = intcode_computer.amplification_circuit(mem, phase_sequence)
... | KnownValues | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KnownValues:
def test_amplification_circuit(self):
"""amplication_circuit should give known result with known input"""
<|body_0|>
def test_feedback_loop(self):
"""feedback_loop should give known result with known input"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_021921 | 1,426 | no_license | [
{
"docstring": "amplication_circuit should give known result with known input",
"name": "test_amplification_circuit",
"signature": "def test_amplification_circuit(self)"
},
{
"docstring": "feedback_loop should give known result with known input",
"name": "test_feedback_loop",
"signature"... | 2 | stack_v2_sparse_classes_30k_train_018635 | Implement the Python class `KnownValues` described below.
Class description:
Implement the KnownValues class.
Method signatures and docstrings:
- def test_amplification_circuit(self): amplication_circuit should give known result with known input
- def test_feedback_loop(self): feedback_loop should give known result w... | Implement the Python class `KnownValues` described below.
Class description:
Implement the KnownValues class.
Method signatures and docstrings:
- def test_amplification_circuit(self): amplication_circuit should give known result with known input
- def test_feedback_loop(self): feedback_loop should give known result w... | 98b6d2049e2331c2583d47d05061690b87ea0f2b | <|skeleton|>
class KnownValues:
def test_amplification_circuit(self):
"""amplication_circuit should give known result with known input"""
<|body_0|>
def test_feedback_loop(self):
"""feedback_loop should give known result with known input"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KnownValues:
def test_amplification_circuit(self):
"""amplication_circuit should give known result with known input"""
for file, phase_sequence, output_signal in self.known_values:
intcode_program = open(expanduser('~/code/aoc2019/07/%s' % file))
mem = list(map(int, int... | the_stack_v2_python_sparse | 07/intcode_test.py | hinzed1127/aoc2019 | train | 0 | |
214e90c5bfcf485e18e13c001f8e9e2889072097 | [
"self.encd = encd\nself.no_inner_groups = no_inner_groups\nself.istring_hook = istring_hook\nif not ifile:\n self.re_list = [DEFAULT_RE]\nelse:\n self.re_list = self.__load(ifile, encd=self.encd)",
"output = []\ngroups = ()\nfor re in self.re_list:\n for match in re.finditer(istring):\n groups = m... | <|body_start_0|>
self.encd = encd
self.no_inner_groups = no_inner_groups
self.istring_hook = istring_hook
if not ifile:
self.re_list = [DEFAULT_RE]
else:
self.re_list = self.__load(ifile, encd=self.encd)
<|end_body_0|>
<|body_start_1|>
output = []... | Container class used to hold multiple compiled regexps. | MultiRegExp | [
"BSD-3-Clause",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MultiRegExp:
"""Container class used to hold multiple compiled regexps."""
def __init__(self, ifile, encd='utf8', no_inner_groups=False, istring_hook=lambda istring: [istring]):
"""Load regular expressions from text file. Read input file passed as argument and convert lines contained... | stack_v2_sparse_classes_36k_train_021922 | 6,533 | permissive | [
{
"docstring": "Load regular expressions from text file. Read input file passed as argument and convert lines contained there to a RegExp union, i.e. regexps separated by | (OR). If istring_hook is supplied, it should be a function called for every input line except for lines with compiler directives. Return va... | 5 | stack_v2_sparse_classes_30k_train_017627 | Implement the Python class `MultiRegExp` described below.
Class description:
Container class used to hold multiple compiled regexps.
Method signatures and docstrings:
- def __init__(self, ifile, encd='utf8', no_inner_groups=False, istring_hook=lambda istring: [istring]): Load regular expressions from text file. Read ... | Implement the Python class `MultiRegExp` described below.
Class description:
Container class used to hold multiple compiled regexps.
Method signatures and docstrings:
- def __init__(self, ifile, encd='utf8', no_inner_groups=False, istring_hook=lambda istring: [istring]): Load regular expressions from text file. Read ... | ac645fb41260b86491b17fbc50e5ea3300dc28b7 | <|skeleton|>
class MultiRegExp:
"""Container class used to hold multiple compiled regexps."""
def __init__(self, ifile, encd='utf8', no_inner_groups=False, istring_hook=lambda istring: [istring]):
"""Load regular expressions from text file. Read input file passed as argument and convert lines contained... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MultiRegExp:
"""Container class used to hold multiple compiled regexps."""
def __init__(self, ifile, encd='utf8', no_inner_groups=False, istring_hook=lambda istring: [istring]):
"""Load regular expressions from text file. Read input file passed as argument and convert lines contained there to a R... | the_stack_v2_python_sparse | scripts/lib/python/ld/lingre/lre.py | WladimirSidorenko/TextNormalization | train | 1 |
abb40f6104d91f9d09907f53c15d22b40b43d962 | [
"if not root:\n return 0\nelse:\n l = self.maxDepth(root.left)\n r = self.maxDepth(root.right)\n return max(l, r) + 1",
"if not root:\n return 0\ncnt = 0\nqueue = deque()\nqueue.append(root)\nwhile len(queue):\n temp = []\n for _ in range(len(queue)):\n root = queue.pop()\n temp... | <|body_start_0|>
if not root:
return 0
else:
l = self.maxDepth(root.left)
r = self.maxDepth(root.right)
return max(l, r) + 1
<|end_body_0|>
<|body_start_1|>
if not root:
return 0
cnt = 0
queue = deque()
queue.ap... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxDepth(self, root: TreeNode) -> int:
"""dfs"""
<|body_0|>
def maxDepth2(self, root: TreeNode) -> int:
"""bfs"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
return 0
else:
l = self.maxDept... | stack_v2_sparse_classes_36k_train_021923 | 1,927 | permissive | [
{
"docstring": "dfs",
"name": "maxDepth",
"signature": "def maxDepth(self, root: TreeNode) -> int"
},
{
"docstring": "bfs",
"name": "maxDepth2",
"signature": "def maxDepth2(self, root: TreeNode) -> int"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxDepth(self, root: TreeNode) -> int: dfs
- def maxDepth2(self, root: TreeNode) -> int: bfs | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxDepth(self, root: TreeNode) -> int: dfs
- def maxDepth2(self, root: TreeNode) -> int: bfs
<|skeleton|>
class Solution:
def maxDepth(self, root: TreeNode) -> int:
... | e8a1c6cae6547cbcb6e8494be6df685f3e7c837c | <|skeleton|>
class Solution:
def maxDepth(self, root: TreeNode) -> int:
"""dfs"""
<|body_0|>
def maxDepth2(self, root: TreeNode) -> int:
"""bfs"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxDepth(self, root: TreeNode) -> int:
"""dfs"""
if not root:
return 0
else:
l = self.maxDepth(root.left)
r = self.maxDepth(root.right)
return max(l, r) + 1
def maxDepth2(self, root: TreeNode) -> int:
"""bfs"""
... | the_stack_v2_python_sparse | 104-maximum-depth-of-binary-tree.py | yuenliou/leetcode | train | 0 | |
c06d014a3bc9f9f22a071586b781764169f178e6 | [
"if not isinstance(permission, Permissions):\n try:\n permission = Permissions(permission)\n except ValueError:\n msg = \"Invalid `permission` value. Available values are: 'View', 'Modify', 'Full Control', 'Denied All', 'Default All'. See: Permissions enum.\"\n exception_handler(msg)\nrig... | <|body_start_0|>
if not isinstance(permission, Permissions):
try:
permission = Permissions(permission)
except ValueError:
msg = "Invalid `permission` value. Available values are: 'View', 'Modify', 'Full Control', 'Denied All', 'Default All'. See: Permissio... | TrusteeACLMixin class adds ACL management for Trustee classes. Objects currently supporting this Mixin are: (`User` and `UserGroup`). | TrusteeACLMixin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TrusteeACLMixin:
"""TrusteeACLMixin class adds ACL management for Trustee classes. Objects currently supporting this Mixin are: (`User` and `UserGroup`)."""
def set_permission(self, permission: Permissions | str, to_objects: str | list[str], object_type: 'ObjectTypes | int', project: 'Option... | stack_v2_sparse_classes_36k_train_021924 | 28,085 | permissive | [
{
"docstring": "Set permission to perform actions on given object(s). Function is used to set permission of the trustee to perform given actions on the provided objects. Within one execution of the function permission will be set in the same manner for each of the provided objects. The only available values of ... | 2 | stack_v2_sparse_classes_30k_train_012637 | Implement the Python class `TrusteeACLMixin` described below.
Class description:
TrusteeACLMixin class adds ACL management for Trustee classes. Objects currently supporting this Mixin are: (`User` and `UserGroup`).
Method signatures and docstrings:
- def set_permission(self, permission: Permissions | str, to_objects:... | Implement the Python class `TrusteeACLMixin` described below.
Class description:
TrusteeACLMixin class adds ACL management for Trustee classes. Objects currently supporting this Mixin are: (`User` and `UserGroup`).
Method signatures and docstrings:
- def set_permission(self, permission: Permissions | str, to_objects:... | c6cea33b15bcd876ded4de25138b3f5e5165cd6d | <|skeleton|>
class TrusteeACLMixin:
"""TrusteeACLMixin class adds ACL management for Trustee classes. Objects currently supporting this Mixin are: (`User` and `UserGroup`)."""
def set_permission(self, permission: Permissions | str, to_objects: str | list[str], object_type: 'ObjectTypes | int', project: 'Option... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TrusteeACLMixin:
"""TrusteeACLMixin class adds ACL management for Trustee classes. Objects currently supporting this Mixin are: (`User` and `UserGroup`)."""
def set_permission(self, permission: Permissions | str, to_objects: str | list[str], object_type: 'ObjectTypes | int', project: 'Optional[Project | ... | the_stack_v2_python_sparse | mstrio/utils/acl.py | MicroStrategy/mstrio-py | train | 84 |
00463ef5bf7a318bfe7bcf4ddaf69cb8dac74afb | [
"if SuperUserPermission().can():\n if parsed_args['limit'] is not None and parsed_args['limit'] > 100:\n raise InvalidRequest('Page limit cannot be above 100')\n if parsed_args['limit'] is None:\n users = pre_oci_model.get_active_users(disabled=parsed_args['disabled'])\n return ({'users':... | <|body_start_0|>
if SuperUserPermission().can():
if parsed_args['limit'] is not None and parsed_args['limit'] > 100:
raise InvalidRequest('Page limit cannot be above 100')
if parsed_args['limit'] is None:
users = pre_oci_model.get_active_users(disabled=par... | Resource for listing users in the system. | SuperUserList | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SuperUserList:
"""Resource for listing users in the system."""
def get(self, parsed_args, page_token):
"""Returns a list of all users in the system."""
<|body_0|>
def post(self):
"""Creates a new user."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_021925 | 40,556 | permissive | [
{
"docstring": "Returns a list of all users in the system.",
"name": "get",
"signature": "def get(self, parsed_args, page_token)"
},
{
"docstring": "Creates a new user.",
"name": "post",
"signature": "def post(self)"
}
] | 2 | null | Implement the Python class `SuperUserList` described below.
Class description:
Resource for listing users in the system.
Method signatures and docstrings:
- def get(self, parsed_args, page_token): Returns a list of all users in the system.
- def post(self): Creates a new user. | Implement the Python class `SuperUserList` described below.
Class description:
Resource for listing users in the system.
Method signatures and docstrings:
- def get(self, parsed_args, page_token): Returns a list of all users in the system.
- def post(self): Creates a new user.
<|skeleton|>
class SuperUserList:
"... | e400a0c22c5f89dd35d571654b13d262b1f6e3b3 | <|skeleton|>
class SuperUserList:
"""Resource for listing users in the system."""
def get(self, parsed_args, page_token):
"""Returns a list of all users in the system."""
<|body_0|>
def post(self):
"""Creates a new user."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SuperUserList:
"""Resource for listing users in the system."""
def get(self, parsed_args, page_token):
"""Returns a list of all users in the system."""
if SuperUserPermission().can():
if parsed_args['limit'] is not None and parsed_args['limit'] > 100:
raise Inv... | the_stack_v2_python_sparse | endpoints/api/superuser.py | quay/quay | train | 2,363 |
b47800257924c858be718f7e4051bdf4b796be5a | [
"coin_list = [0 for _ in range(amount + 1)]\ncoin_list[0] = 1\ncoins.sort()\nfor j in range(len(coins)):\n for i in range(1, amount + 1):\n if i >= coins[j]:\n coin_list[i] += coin_list[i - coins[j]]\nprint(coin_list)\nreturn coin_list[-1]",
"dp = [1] + [0] * amount\nfor c in coins:\n for ... | <|body_start_0|>
coin_list = [0 for _ in range(amount + 1)]
coin_list[0] = 1
coins.sort()
for j in range(len(coins)):
for i in range(1, amount + 1):
if i >= coins[j]:
coin_list[i] += coin_list[i - coins[j]]
print(coin_list)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def change(self, amount, coins):
""":type amount: int :type coins: List[int] :rtype: int"""
<|body_0|>
def change2(self, amount, coins):
""":type amount: int :type coins: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_021926 | 868 | no_license | [
{
"docstring": ":type amount: int :type coins: List[int] :rtype: int",
"name": "change",
"signature": "def change(self, amount, coins)"
},
{
"docstring": ":type amount: int :type coins: List[int] :rtype: int",
"name": "change2",
"signature": "def change2(self, amount, coins)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def change(self, amount, coins): :type amount: int :type coins: List[int] :rtype: int
- def change2(self, amount, coins): :type amount: int :type coins: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def change(self, amount, coins): :type amount: int :type coins: List[int] :rtype: int
- def change2(self, amount, coins): :type amount: int :type coins: List[int] :rtype: int
<|... | 4105e18050b15fc0409c75353ad31be17187dd34 | <|skeleton|>
class Solution:
def change(self, amount, coins):
""":type amount: int :type coins: List[int] :rtype: int"""
<|body_0|>
def change2(self, amount, coins):
""":type amount: int :type coins: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def change(self, amount, coins):
""":type amount: int :type coins: List[int] :rtype: int"""
coin_list = [0 for _ in range(amount + 1)]
coin_list[0] = 1
coins.sort()
for j in range(len(coins)):
for i in range(1, amount + 1):
if i >= ... | the_stack_v2_python_sparse | change.py | NeilWangziyu/Leetcode_py | train | 2 | |
06266b27143312b718530dcc5db646bd59a37831 | [
"self.env_step_time = 0.0\nself.inference_time = 0.0\nself.iters = 0\nself.explore_time_in_epi = 0.0\nself.wait_model_time = 0.0\nself.restore_model_time = 0.0\nself.n_agents = n_agents\nself.env_api_type = env_type\nself._stats = dict()",
"_steps = [sta['mean_env_step_time_ms'] for sta in agent_stats]\n_infers =... | <|body_start_0|>
self.env_step_time = 0.0
self.inference_time = 0.0
self.iters = 0
self.explore_time_in_epi = 0.0
self.wait_model_time = 0.0
self.restore_model_time = 0.0
self.n_agents = n_agents
self.env_api_type = env_type
self._stats = dict()
<|... | AgentGroup status records handle the env.step and inference time of AgentGroup the status could been make sence within once explore There should been gather by logger or others | AgentGroupStats | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AgentGroupStats:
"""AgentGroup status records handle the env.step and inference time of AgentGroup the status could been make sence within once explore There should been gather by logger or others"""
def __init__(self, n_agents, env_type):
"""init with default value"""
<|body... | stack_v2_sparse_classes_36k_train_021927 | 5,319 | permissive | [
{
"docstring": "init with default value",
"name": "__init__",
"signature": "def __init__(self, n_agents, env_type)"
},
{
"docstring": "update agent status to agent group",
"name": "update_with_agent_stats",
"signature": "def update_with_agent_stats(self, agent_stats: list)"
},
{
... | 4 | null | Implement the Python class `AgentGroupStats` described below.
Class description:
AgentGroup status records handle the env.step and inference time of AgentGroup the status could been make sence within once explore There should been gather by logger or others
Method signatures and docstrings:
- def __init__(self, n_age... | Implement the Python class `AgentGroupStats` described below.
Class description:
AgentGroup status records handle the env.step and inference time of AgentGroup the status could been make sence within once explore There should been gather by logger or others
Method signatures and docstrings:
- def __init__(self, n_age... | df51ed9c1d6dbde1deef63f2a037a369f8554406 | <|skeleton|>
class AgentGroupStats:
"""AgentGroup status records handle the env.step and inference time of AgentGroup the status could been make sence within once explore There should been gather by logger or others"""
def __init__(self, n_agents, env_type):
"""init with default value"""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AgentGroupStats:
"""AgentGroup status records handle the env.step and inference time of AgentGroup the status could been make sence within once explore There should been gather by logger or others"""
def __init__(self, n_agents, env_type):
"""init with default value"""
self.env_step_time ... | the_stack_v2_python_sparse | built-in/TensorFlow/Research/reinforcement-learning/ModelZoo_QMIX_TensorFlow/xt/util/profile_stats.py | Huawei-Ascend/modelzoo | train | 1 |
88ee99fcf4634f8a3631379788692d568c5c8ac6 | [
"follow_user = self.db.query(FollowUser).filter_by(src_user_id=self.current_user).filter_by(dst_user_id=user_id).filter(FollowUser.is_current()).first()\nif follow_user:\n self.set_status(409)\nelse:\n self.db.add(FollowUser(src_user_id=self.current_user, dst_user_id=user_id))\nself.db.commit()\nself.finish()... | <|body_start_0|>
follow_user = self.db.query(FollowUser).filter_by(src_user_id=self.current_user).filter_by(dst_user_id=user_id).filter(FollowUser.is_current()).first()
if follow_user:
self.set_status(409)
else:
self.db.add(FollowUser(src_user_id=self.current_user, dst_us... | API_FollowUser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class API_FollowUser:
def post(self, user_id):
"""start following user Parameters ---------- dst_user_id: int (required) Returns ---------- CODES: 200: OK 409: already subscribed BODY: empty"""
<|body_0|>
def delete(self, user_id):
"""stop following user Parameters -------... | stack_v2_sparse_classes_36k_train_021928 | 7,114 | no_license | [
{
"docstring": "start following user Parameters ---------- dst_user_id: int (required) Returns ---------- CODES: 200: OK 409: already subscribed BODY: empty",
"name": "post",
"signature": "def post(self, user_id)"
},
{
"docstring": "stop following user Parameters ---------- dst_user_id: int (req... | 2 | stack_v2_sparse_classes_30k_val_000828 | Implement the Python class `API_FollowUser` described below.
Class description:
Implement the API_FollowUser class.
Method signatures and docstrings:
- def post(self, user_id): start following user Parameters ---------- dst_user_id: int (required) Returns ---------- CODES: 200: OK 409: already subscribed BODY: empty
... | Implement the Python class `API_FollowUser` described below.
Class description:
Implement the API_FollowUser class.
Method signatures and docstrings:
- def post(self, user_id): start following user Parameters ---------- dst_user_id: int (required) Returns ---------- CODES: 200: OK 409: already subscribed BODY: empty
... | 0eab54eb283e7434734b9fbeabd7d3ba249772af | <|skeleton|>
class API_FollowUser:
def post(self, user_id):
"""start following user Parameters ---------- dst_user_id: int (required) Returns ---------- CODES: 200: OK 409: already subscribed BODY: empty"""
<|body_0|>
def delete(self, user_id):
"""stop following user Parameters -------... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class API_FollowUser:
def post(self, user_id):
"""start following user Parameters ---------- dst_user_id: int (required) Returns ---------- CODES: 200: OK 409: already subscribed BODY: empty"""
follow_user = self.db.query(FollowUser).filter_by(src_user_id=self.current_user).filter_by(dst_user_id=use... | the_stack_v2_python_sparse | backend/main_app/api_v1/follow.py | zzzevaka/findchat | train | 0 | |
323f137b35fe341a868599f7a62c868edeebaf91 | [
"result = {'errcode': 0, 'msg': None}\nid = request.GET.get('id', None)\nqueryset = UrlPermission.objects.only('id', 'title').all()\nrole = Role.objects.filter(id=id).first()\nper_list = []\nif role:\n role_permissions = role.permission.only('id', 'title').all()\n per_ids = [ru.id for ru in role_permissions]\... | <|body_start_0|>
result = {'errcode': 0, 'msg': None}
id = request.GET.get('id', None)
queryset = UrlPermission.objects.only('id', 'title').all()
role = Role.objects.filter(id=id).first()
per_list = []
if role:
role_permissions = role.permission.only('id', 'ti... | GetRoleAllPermission | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetRoleAllPermission:
def get(self, request, **kwargs):
"""获取当前角色的所有权限"""
<|body_0|>
def post(self, request, **kwargs):
"""修改 角色的用户信息"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
result = {'errcode': 0, 'msg': None}
id = request.GET.get('... | stack_v2_sparse_classes_36k_train_021929 | 6,998 | no_license | [
{
"docstring": "获取当前角色的所有权限",
"name": "get",
"signature": "def get(self, request, **kwargs)"
},
{
"docstring": "修改 角色的用户信息",
"name": "post",
"signature": "def post(self, request, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014734 | Implement the Python class `GetRoleAllPermission` described below.
Class description:
Implement the GetRoleAllPermission class.
Method signatures and docstrings:
- def get(self, request, **kwargs): 获取当前角色的所有权限
- def post(self, request, **kwargs): 修改 角色的用户信息 | Implement the Python class `GetRoleAllPermission` described below.
Class description:
Implement the GetRoleAllPermission class.
Method signatures and docstrings:
- def get(self, request, **kwargs): 获取当前角色的所有权限
- def post(self, request, **kwargs): 修改 角色的用户信息
<|skeleton|>
class GetRoleAllPermission:
def get(self,... | 9ceeecd85fdfd52fb90ebac7cc17092476877640 | <|skeleton|>
class GetRoleAllPermission:
def get(self, request, **kwargs):
"""获取当前角色的所有权限"""
<|body_0|>
def post(self, request, **kwargs):
"""修改 角色的用户信息"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GetRoleAllPermission:
def get(self, request, **kwargs):
"""获取当前角色的所有权限"""
result = {'errcode': 0, 'msg': None}
id = request.GET.get('id', None)
queryset = UrlPermission.objects.only('id', 'title').all()
role = Role.objects.filter(id=id).first()
per_list = []
... | the_stack_v2_python_sparse | user/api.py | vanwt/ttcmdb | train | 1 | |
ad17bbec842475a716067702df6f6f96c2e980d7 | [
"def thoughroot(root):\n nonlocal res\n if not root:\n return 0\n left = max(0, thoughroot(root.left))\n right = max(0, thoughroot(root.right))\n res = max(res, left + right + root.val)\n return max(left, right) + root.val\nres = -float('inf')\nthoughroot(root)\nreturn res",
"dp = [-float... | <|body_start_0|>
def thoughroot(root):
nonlocal res
if not root:
return 0
left = max(0, thoughroot(root.left))
right = max(0, thoughroot(root.right))
res = max(res, left + right + root.val)
return max(left, right) + root.val... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxPathSum(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def maxPathSum0(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def thoughroot(root):
nonlocal res
... | stack_v2_sparse_classes_36k_train_021930 | 1,733 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "maxPathSum",
"signature": "def maxPathSum(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: int",
"name": "maxPathSum0",
"signature": "def maxPathSum0(self, root)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017139 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxPathSum(self, root): :type root: TreeNode :rtype: int
- def maxPathSum0(self, root): :type root: TreeNode :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxPathSum(self, root): :type root: TreeNode :rtype: int
- def maxPathSum0(self, root): :type root: TreeNode :rtype: int
<|skeleton|>
class Solution:
def maxPathSum(sel... | 9e49b2c6003b957276737005d4aaac276b44d251 | <|skeleton|>
class Solution:
def maxPathSum(self, root):
""":type root: TreeNode :rtype: int"""
<|body_0|>
def maxPathSum0(self, root):
""":type root: TreeNode :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxPathSum(self, root):
""":type root: TreeNode :rtype: int"""
def thoughroot(root):
nonlocal res
if not root:
return 0
left = max(0, thoughroot(root.left))
right = max(0, thoughroot(root.right))
res = ma... | the_stack_v2_python_sparse | PythonCode/src/0124_Binary_Tree_Maximum_Path_Sum.py | oneyuan/CodeforFun | train | 0 | |
3792202cbca60b4a19deac319b8a16b7cba5d625 | [
"group1_antall, group1_image = detectFace(group1)\ngroup1_expectedNumber = 7\nself.assertEqual(group1_antall, group1_expectedNumber)",
"couple_antall, couple_image = detectFace(couple)\ncouple_expectedNumber = 2\nself.assertEqual(couple_antall, couple_expectedNumber)"
] | <|body_start_0|>
group1_antall, group1_image = detectFace(group1)
group1_expectedNumber = 7
self.assertEqual(group1_antall, group1_expectedNumber)
<|end_body_0|>
<|body_start_1|>
couple_antall, couple_image = detectFace(couple)
couple_expectedNumber = 2
self.assertEqual(... | Tests for the anonymise module | test_Anon | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class test_Anon:
"""Tests for the anonymise module"""
def test_faceDetect_Group1(self):
"""Test for face detection of image (group1.jpg)"""
<|body_0|>
def test_faceDetect_Couple(self):
"""Test for face detection of image (couple.jpg)"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_36k_train_021931 | 817 | no_license | [
{
"docstring": "Test for face detection of image (group1.jpg)",
"name": "test_faceDetect_Group1",
"signature": "def test_faceDetect_Group1(self)"
},
{
"docstring": "Test for face detection of image (couple.jpg)",
"name": "test_faceDetect_Couple",
"signature": "def test_faceDetect_Couple(... | 2 | stack_v2_sparse_classes_30k_train_021031 | Implement the Python class `test_Anon` described below.
Class description:
Tests for the anonymise module
Method signatures and docstrings:
- def test_faceDetect_Group1(self): Test for face detection of image (group1.jpg)
- def test_faceDetect_Couple(self): Test for face detection of image (couple.jpg) | Implement the Python class `test_Anon` described below.
Class description:
Tests for the anonymise module
Method signatures and docstrings:
- def test_faceDetect_Group1(self): Test for face detection of image (group1.jpg)
- def test_faceDetect_Couple(self): Test for face detection of image (couple.jpg)
<|skeleton|>
... | dd40d095231ed397cf69e3598f21483a3bcf11a6 | <|skeleton|>
class test_Anon:
"""Tests for the anonymise module"""
def test_faceDetect_Group1(self):
"""Test for face detection of image (group1.jpg)"""
<|body_0|>
def test_faceDetect_Couple(self):
"""Test for face detection of image (couple.jpg)"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class test_Anon:
"""Tests for the anonymise module"""
def test_faceDetect_Group1(self):
"""Test for face detection of image (group1.jpg)"""
group1_antall, group1_image = detectFace(group1)
group1_expectedNumber = 7
self.assertEqual(group1_antall, group1_expectedNumber)
def ... | the_stack_v2_python_sparse | src/test_FaceDetect.py | jegerud/Sciprog2020project | train | 0 |
133bf4167981f169c94a2cc6989e7c0ea0c4b5a2 | [
"test_class_pos = self.find_test_class(test_file_content)\nif test_class_pos is not None:\n test_class, pos = test_class_pos\n result = class_delimeter + test_class\n test_method = self.find_test_method(test_file_content[pos:])\n if test_method is not None:\n result += method_delimeter + test_met... | <|body_start_0|>
test_class_pos = self.find_test_class(test_file_content)
if test_class_pos is not None:
test_class, pos = test_class_pos
result = class_delimeter + test_class
test_method = self.find_test_method(test_file_content[pos:])
if test_method is n... | Match a test method under the cursor | TestMethodMatcher | [
"MIT",
"GPL-1.0-or-later",
"LGPL-2.1-or-later",
"GPL-3.0-only",
"LicenseRef-scancode-warranty-disclaimer",
"GPL-3.0-or-later",
"LGPL-2.0-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestMethodMatcher:
"""Match a test method under the cursor"""
def find_test_path(self, test_file_content: str, class_delimeter: str=TEST_DELIMETER, method_delimeter: str=TEST_DELIMETER) -> str:
"""Try to find the test path, returns None if can't be found"""
<|body_0|>
de... | stack_v2_sparse_classes_36k_train_021932 | 10,020 | permissive | [
{
"docstring": "Try to find the test path, returns None if can't be found",
"name": "find_test_path",
"signature": "def find_test_path(self, test_file_content: str, class_delimeter: str=TEST_DELIMETER, method_delimeter: str=TEST_DELIMETER) -> str"
},
{
"docstring": "Try to find the test method, ... | 3 | null | Implement the Python class `TestMethodMatcher` described below.
Class description:
Match a test method under the cursor
Method signatures and docstrings:
- def find_test_path(self, test_file_content: str, class_delimeter: str=TEST_DELIMETER, method_delimeter: str=TEST_DELIMETER) -> str: Try to find the test path, ret... | Implement the Python class `TestMethodMatcher` described below.
Class description:
Match a test method under the cursor
Method signatures and docstrings:
- def find_test_path(self, test_file_content: str, class_delimeter: str=TEST_DELIMETER, method_delimeter: str=TEST_DELIMETER) -> str: Try to find the test path, ret... | 9a3808d0d79504b488a407084b489b9d687a528a | <|skeleton|>
class TestMethodMatcher:
"""Match a test method under the cursor"""
def find_test_path(self, test_file_content: str, class_delimeter: str=TEST_DELIMETER, method_delimeter: str=TEST_DELIMETER) -> str:
"""Try to find the test path, returns None if can't be found"""
<|body_0|>
de... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestMethodMatcher:
"""Match a test method under the cursor"""
def find_test_path(self, test_file_content: str, class_delimeter: str=TEST_DELIMETER, method_delimeter: str=TEST_DELIMETER) -> str:
"""Try to find the test path, returns None if can't be found"""
test_class_pos = self.find_test... | the_stack_v2_python_sparse | sublime/Packages/Anaconda/commands/test_runner.py | Kisura/dotfiles | train | 0 |
b9e636a2944fecffcbc228bfe6a9f21bd2b8469a | [
"self.logger = DefaceLogger(__name__, debug=debug)\nself._CACHE_DIR = '/etc/securetea/web_deface/cache_dir'\nself.back_up_mapping = dict()\nself.file_names = []",
"try:\n if not os.path.isdir(path):\n Path(path).mkdir()\nexcept FileExistsError:\n os.remove(path)\n self.check_dir(path)\nexcept File... | <|body_start_0|>
self.logger = DefaceLogger(__name__, debug=debug)
self._CACHE_DIR = '/etc/securetea/web_deface/cache_dir'
self.back_up_mapping = dict()
self.file_names = []
<|end_body_0|>
<|body_start_1|>
try:
if not os.path.isdir(path):
Path(path).m... | BackUp class. | BackUp | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BackUp:
"""BackUp class."""
def __init__(self, debug=False):
"""Initialize BackUp. Args: debug (bool): Log on terminal or not Raises: None Returns: None"""
<|body_0|>
def check_dir(self, path):
"""Check whether the directory exists or not. If directory does not e... | stack_v2_sparse_classes_36k_train_021933 | 3,752 | permissive | [
{
"docstring": "Initialize BackUp. Args: debug (bool): Log on terminal or not Raises: None Returns: None",
"name": "__init__",
"signature": "def __init__(self, debug=False)"
},
{
"docstring": "Check whether the directory exists or not. If directory does not exist, create one. Args: path (str): P... | 4 | stack_v2_sparse_classes_30k_train_011914 | Implement the Python class `BackUp` described below.
Class description:
BackUp class.
Method signatures and docstrings:
- def __init__(self, debug=False): Initialize BackUp. Args: debug (bool): Log on terminal or not Raises: None Returns: None
- def check_dir(self, path): Check whether the directory exists or not. If... | Implement the Python class `BackUp` described below.
Class description:
BackUp class.
Method signatures and docstrings:
- def __init__(self, debug=False): Initialize BackUp. Args: debug (bool): Log on terminal or not Raises: None Returns: None
- def check_dir(self, path): Check whether the directory exists or not. If... | 43dec187e5848b9ced8a6b4957b6e9028d4d43cd | <|skeleton|>
class BackUp:
"""BackUp class."""
def __init__(self, debug=False):
"""Initialize BackUp. Args: debug (bool): Log on terminal or not Raises: None Returns: None"""
<|body_0|>
def check_dir(self, path):
"""Check whether the directory exists or not. If directory does not e... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BackUp:
"""BackUp class."""
def __init__(self, debug=False):
"""Initialize BackUp. Args: debug (bool): Log on terminal or not Raises: None Returns: None"""
self.logger = DefaceLogger(__name__, debug=debug)
self._CACHE_DIR = '/etc/securetea/web_deface/cache_dir'
self.back_u... | the_stack_v2_python_sparse | securetea/lib/web_deface/backup.py | rejahrehim/SecureTea-Project | train | 1 |
552a13a1ce1e7cd938b45c94e91ae7585f5443eb | [
"if name and (not namespace) and (not identifier):\n x = pmod_mappings[name]['xrefs'][0]\n namespace, identifier, name = (x.namespace, x.identifier, x.name)\nsuper().__init__(name=name, namespace=namespace, identifier=identifier, xrefs=xrefs)\nif code:\n self[PMOD_CODE] = code\nif position:\n self[PMOD_... | <|body_start_0|>
if name and (not namespace) and (not identifier):
x = pmod_mappings[name]['xrefs'][0]
namespace, identifier, name = (x.namespace, x.identifier, x.name)
super().__init__(name=name, namespace=namespace, identifier=identifier, xrefs=xrefs)
if code:
... | Build a protein modification variant dictionary. | ProteinModification | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProteinModification:
"""Build a protein modification variant dictionary."""
def __init__(self, name: str, code: Optional[str]=None, position: Optional[int]=None, namespace: Optional[str]=None, identifier: Optional[str]=None, xrefs: Optional[List[Entity]]=None) -> None:
"""Build a pro... | stack_v2_sparse_classes_36k_train_021934 | 34,684 | permissive | [
{
"docstring": "Build a protein modification variant data dictionary. :param name: The name of the modification :param code: The three letter amino acid code for the affected residue. Capital first letter. :param position: The position of the affected residue :param namespace: The namespace to which the name of... | 2 | null | Implement the Python class `ProteinModification` described below.
Class description:
Build a protein modification variant dictionary.
Method signatures and docstrings:
- def __init__(self, name: str, code: Optional[str]=None, position: Optional[int]=None, namespace: Optional[str]=None, identifier: Optional[str]=None,... | Implement the Python class `ProteinModification` described below.
Class description:
Build a protein modification variant dictionary.
Method signatures and docstrings:
- def __init__(self, name: str, code: Optional[str]=None, position: Optional[int]=None, namespace: Optional[str]=None, identifier: Optional[str]=None,... | ed66f013a77f9cbc513892b0dad1025b8f68bb46 | <|skeleton|>
class ProteinModification:
"""Build a protein modification variant dictionary."""
def __init__(self, name: str, code: Optional[str]=None, position: Optional[int]=None, namespace: Optional[str]=None, identifier: Optional[str]=None, xrefs: Optional[List[Entity]]=None) -> None:
"""Build a pro... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProteinModification:
"""Build a protein modification variant dictionary."""
def __init__(self, name: str, code: Optional[str]=None, position: Optional[int]=None, namespace: Optional[str]=None, identifier: Optional[str]=None, xrefs: Optional[List[Entity]]=None) -> None:
"""Build a protein modifica... | the_stack_v2_python_sparse | src/pybel/dsl/node_classes.py | pybel/pybel | train | 133 |
414066553086dd0ceb7e4a5861656b1c1695ed38 | [
"super(UserApplicationChangeForm, self).__init__(data=data, initial=initial, instance=instance)\nlocal_site_field = self.fields['local_site']\nlocal_site_field.queryset = LocalSite.objects.filter(users=user)\nlocal_site_field.widget.attrs['disabled'] = True",
"super(UserApplicationChangeForm, self).clean()\nif 'l... | <|body_start_0|>
super(UserApplicationChangeForm, self).__init__(data=data, initial=initial, instance=instance)
local_site_field = self.fields['local_site']
local_site_field.queryset = LocalSite.objects.filter(users=user)
local_site_field.widget.attrs['disabled'] = True
<|end_body_0|>
<... | A form for an end user to change an Application. | UserApplicationChangeForm | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserApplicationChangeForm:
"""A form for an end user to change an Application."""
def __init__(self, user, data=None, initial=None, instance=None):
"""Initialize the form. Args: user (django.contrib.auth.models.User): The user changing the form. Ignored, but included to match :py:met... | stack_v2_sparse_classes_36k_train_021935 | 13,782 | permissive | [
{
"docstring": "Initialize the form. Args: user (django.contrib.auth.models.User): The user changing the form. Ignored, but included to match :py:meth:`UserApplicationCreationForm.__init__`. data (dict): The provided data. initial (dict, optional): The initial form values. instance (reviewboard.oauth.models.App... | 2 | stack_v2_sparse_classes_30k_train_011637 | Implement the Python class `UserApplicationChangeForm` described below.
Class description:
A form for an end user to change an Application.
Method signatures and docstrings:
- def __init__(self, user, data=None, initial=None, instance=None): Initialize the form. Args: user (django.contrib.auth.models.User): The user ... | Implement the Python class `UserApplicationChangeForm` described below.
Class description:
A form for an end user to change an Application.
Method signatures and docstrings:
- def __init__(self, user, data=None, initial=None, instance=None): Initialize the form. Args: user (django.contrib.auth.models.User): The user ... | c3a991f1e9d7682239a1ab0e8661cee6da01d537 | <|skeleton|>
class UserApplicationChangeForm:
"""A form for an end user to change an Application."""
def __init__(self, user, data=None, initial=None, instance=None):
"""Initialize the form. Args: user (django.contrib.auth.models.User): The user changing the form. Ignored, but included to match :py:met... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserApplicationChangeForm:
"""A form for an end user to change an Application."""
def __init__(self, user, data=None, initial=None, instance=None):
"""Initialize the form. Args: user (django.contrib.auth.models.User): The user changing the form. Ignored, but included to match :py:meth:`UserApplic... | the_stack_v2_python_sparse | reviewboard/oauth/forms.py | reviewboard/reviewboard | train | 1,141 |
4e9878922a1df080980f6ce06c1a1fb939c05562 | [
"def from_left(nums):\n \"\"\"increase the smaller number to the previous highest\"\"\"\n found = False\n p = nums[0]\n for i in range(1, len(nums)):\n if p > nums[i]:\n if found:\n return False\n found = True\n else:\n p = nums[i]\n retur... | <|body_start_0|>
def from_left(nums):
"""increase the smaller number to the previous highest"""
found = False
p = nums[0]
for i in range(1, len(nums)):
if p > nums[i]:
if found:
return False
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def checkPossibility(self, nums: List[int]) -> bool:
"""02/03/2021 18:41 Two passes from left and from right Time complexity: O(n) Space complexity: O(1)"""
<|body_0|>
def checkPossibility(self, nums: List[int]) -> bool:
"""One pass, inplace Time complexity... | stack_v2_sparse_classes_36k_train_021936 | 3,325 | no_license | [
{
"docstring": "02/03/2021 18:41 Two passes from left and from right Time complexity: O(n) Space complexity: O(1)",
"name": "checkPossibility",
"signature": "def checkPossibility(self, nums: List[int]) -> bool"
},
{
"docstring": "One pass, inplace Time complexity: O(n) Space complexity: O(1)",
... | 3 | stack_v2_sparse_classes_30k_train_016052 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkPossibility(self, nums: List[int]) -> bool: 02/03/2021 18:41 Two passes from left and from right Time complexity: O(n) Space complexity: O(1)
- def checkPossibility(self... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def checkPossibility(self, nums: List[int]) -> bool: 02/03/2021 18:41 Two passes from left and from right Time complexity: O(n) Space complexity: O(1)
- def checkPossibility(self... | 1389a009a02e90e8700a7a00e0b7f797c129cdf4 | <|skeleton|>
class Solution:
def checkPossibility(self, nums: List[int]) -> bool:
"""02/03/2021 18:41 Two passes from left and from right Time complexity: O(n) Space complexity: O(1)"""
<|body_0|>
def checkPossibility(self, nums: List[int]) -> bool:
"""One pass, inplace Time complexity... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def checkPossibility(self, nums: List[int]) -> bool:
"""02/03/2021 18:41 Two passes from left and from right Time complexity: O(n) Space complexity: O(1)"""
def from_left(nums):
"""increase the smaller number to the previous highest"""
found = False
... | the_stack_v2_python_sparse | leetcode/solved/665_Non-decreasing_Array/solution.py | sungminoh/algorithms | train | 0 | |
73ee1bcd02aad80363ad70b5a71c5e1ab11ef13f | [
"self.kernel_fn = kernel_fn\nself.verbose = verbose\nself.random_state = check_random_state(random_state)",
"x_vector = weighted_data\nalphas, _, coefs = lars_path(x_vector, weighted_labels, method='lasso', verbose=False)\nreturn (alphas, coefs)",
"clf = Ridge(alpha=0, fit_intercept=True, random_state=self.rand... | <|body_start_0|>
self.kernel_fn = kernel_fn
self.verbose = verbose
self.random_state = check_random_state(random_state)
<|end_body_0|>
<|body_start_1|>
x_vector = weighted_data
alphas, _, coefs = lars_path(x_vector, weighted_labels, method='lasso', verbose=False)
return ... | Class for learning a locally linear sparse model from perturbed data | LimeBase | [
"MIT",
"BSD-2-Clause",
"LGPL-2.1-or-later",
"BSD-3-Clause",
"LicenseRef-scancode-free-unknown",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LimeBase:
"""Class for learning a locally linear sparse model from perturbed data"""
def __init__(self, kernel_fn, verbose=False, random_state=None):
"""Init function Args: kernel_fn: function that transforms an array of distances into an array of proximity values (floats). verbose: ... | stack_v2_sparse_classes_36k_train_021937 | 8,448 | permissive | [
{
"docstring": "Init function Args: kernel_fn: function that transforms an array of distances into an array of proximity values (floats). verbose: if true, print local prediction values from linear model. random_state: an integer or numpy.RandomState that will be used to generate random numbers. If None, the ra... | 5 | null | Implement the Python class `LimeBase` described below.
Class description:
Class for learning a locally linear sparse model from perturbed data
Method signatures and docstrings:
- def __init__(self, kernel_fn, verbose=False, random_state=None): Init function Args: kernel_fn: function that transforms an array of distan... | Implement the Python class `LimeBase` described below.
Class description:
Class for learning a locally linear sparse model from perturbed data
Method signatures and docstrings:
- def __init__(self, kernel_fn, verbose=False, random_state=None): Init function Args: kernel_fn: function that transforms an array of distan... | f59730dc7a8735232ef417685800652372c3b5dd | <|skeleton|>
class LimeBase:
"""Class for learning a locally linear sparse model from perturbed data"""
def __init__(self, kernel_fn, verbose=False, random_state=None):
"""Init function Args: kernel_fn: function that transforms an array of distances into an array of proximity values (floats). verbose: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LimeBase:
"""Class for learning a locally linear sparse model from perturbed data"""
def __init__(self, kernel_fn, verbose=False, random_state=None):
"""Init function Args: kernel_fn: function that transforms an array of distances into an array of proximity values (floats). verbose: if true, prin... | the_stack_v2_python_sparse | tensorwatch/saliency/lime/lime_base.py | microsoft/tensorwatch | train | 3,626 |
f90dd8e2a674920e934d3e925634901e27cc6e1a | [
"super(DynamoDBLambdaTrigger, self).__init__(start_time)\nself.deserializer = TypeDeserializer() if TypeDeserializer else None\nrecord = event['Records'][0]\nself.event_id = record['eventID']\nself.resource['name'] = record['eventSourceARN'].split('/')[-3]\nself.resource['operation'] = record['eventName']\nif recor... | <|body_start_0|>
super(DynamoDBLambdaTrigger, self).__init__(start_time)
self.deserializer = TypeDeserializer() if TypeDeserializer else None
record = event['Records'][0]
self.event_id = record['eventID']
self.resource['name'] = record['eventSourceARN'].split('/')[-3]
sel... | Represents DynamoDB Lambda trigger | DynamoDBLambdaTrigger | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DynamoDBLambdaTrigger:
"""Represents DynamoDB Lambda trigger"""
def __init__(self, start_time, event, context):
"""Initialize. :param start_time: event's start time (epoch) :param event: event dict from the entry point :param context: the context dict from the entry point"""
... | stack_v2_sparse_classes_36k_train_021938 | 18,528 | permissive | [
{
"docstring": "Initialize. :param start_time: event's start time (epoch) :param event: event dict from the entry point :param context: the context dict from the entry point",
"name": "__init__",
"signature": "def __init__(self, start_time, event, context)"
},
{
"docstring": "Deserialize DynamoD... | 2 | stack_v2_sparse_classes_30k_train_008668 | Implement the Python class `DynamoDBLambdaTrigger` described below.
Class description:
Represents DynamoDB Lambda trigger
Method signatures and docstrings:
- def __init__(self, start_time, event, context): Initialize. :param start_time: event's start time (epoch) :param event: event dict from the entry point :param c... | Implement the Python class `DynamoDBLambdaTrigger` described below.
Class description:
Represents DynamoDB Lambda trigger
Method signatures and docstrings:
- def __init__(self, start_time, event, context): Initialize. :param start_time: event's start time (epoch) :param event: event dict from the entry point :param c... | 91e28fe43bc4f42152fb156145088cb8c9f69b85 | <|skeleton|>
class DynamoDBLambdaTrigger:
"""Represents DynamoDB Lambda trigger"""
def __init__(self, start_time, event, context):
"""Initialize. :param start_time: event's start time (epoch) :param event: event dict from the entry point :param context: the context dict from the entry point"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DynamoDBLambdaTrigger:
"""Represents DynamoDB Lambda trigger"""
def __init__(self, start_time, event, context):
"""Initialize. :param start_time: event's start time (epoch) :param event: event dict from the entry point :param context: the context dict from the entry point"""
super(DynamoD... | the_stack_v2_python_sparse | epsagon/triggers/aws_lambda.py | epsagon/epsagon-python | train | 57 |
56b2ed806f6eefe6a3b01626e2ffb8abc020fb04 | [
"super(RNN, self).__init__()\nself.D_in = D_in\nself.H = H\nself.D_out = D_out\nself.L = L\nself.nonlinearity = nonlinearity\nself.dropout = dropout if L > 1 else 0\nself.device = device\nself.rnn = nn.RNN(input_size=self.D_in, hidden_size=self.H, num_layers=self.L, nonlinearity=self.nonlinearity, dropout=self.drop... | <|body_start_0|>
super(RNN, self).__init__()
self.D_in = D_in
self.H = H
self.D_out = D_out
self.L = L
self.nonlinearity = nonlinearity
self.dropout = dropout if L > 1 else 0
self.device = device
self.rnn = nn.RNN(input_size=self.D_in, hidden_size=... | Vanilla RNN | RNN | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RNN:
"""Vanilla RNN"""
def __init__(self, D_in, H, D_ctx, D_out, L=1, nonlinearity='tanh', dropout=0.0, device=None):
"""params D_in: input feature count H: hidden state feature count D_out: output feature count L: number of layers nonlinearity: nonlinearity to use (either tanh or re... | stack_v2_sparse_classes_36k_train_021939 | 2,083 | no_license | [
{
"docstring": "params D_in: input feature count H: hidden state feature count D_out: output feature count L: number of layers nonlinearity: nonlinearity to use (either tanh or relu) dropout: dropout probability for each Dropout layer on RNN outputs device: tensor device",
"name": "__init__",
"signature... | 2 | stack_v2_sparse_classes_30k_train_014404 | Implement the Python class `RNN` described below.
Class description:
Vanilla RNN
Method signatures and docstrings:
- def __init__(self, D_in, H, D_ctx, D_out, L=1, nonlinearity='tanh', dropout=0.0, device=None): params D_in: input feature count H: hidden state feature count D_out: output feature count L: number of la... | Implement the Python class `RNN` described below.
Class description:
Vanilla RNN
Method signatures and docstrings:
- def __init__(self, D_in, H, D_ctx, D_out, L=1, nonlinearity='tanh', dropout=0.0, device=None): params D_in: input feature count H: hidden state feature count D_out: output feature count L: number of la... | 274ff8db17271106155e34725ae69b1a35c962b2 | <|skeleton|>
class RNN:
"""Vanilla RNN"""
def __init__(self, D_in, H, D_ctx, D_out, L=1, nonlinearity='tanh', dropout=0.0, device=None):
"""params D_in: input feature count H: hidden state feature count D_out: output feature count L: number of layers nonlinearity: nonlinearity to use (either tanh or re... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RNN:
"""Vanilla RNN"""
def __init__(self, D_in, H, D_ctx, D_out, L=1, nonlinearity='tanh', dropout=0.0, device=None):
"""params D_in: input feature count H: hidden state feature count D_out: output feature count L: number of layers nonlinearity: nonlinearity to use (either tanh or relu) dropout: ... | the_stack_v2_python_sparse | ml/models/RNN.py | gravaman/fleishco | train | 0 |
24b7b5b45c7a8137917896aac65f9de43994ca8e | [
"radii = ['10000']\nlead_times = None\nradii_out, lead_times_out = radius_by_lead_time(radii, lead_times)\nself.assertEqual(radii_out, float(radii[0]))\nself.assertEqual(lead_times_out, None)\nself.assertIsInstance(radii_out, float)",
"radii = ['10000', '20000']\nlead_times = ['0', '10']\nradii_out, lead_times_ou... | <|body_start_0|>
radii = ['10000']
lead_times = None
radii_out, lead_times_out = radius_by_lead_time(radii, lead_times)
self.assertEqual(radii_out, float(radii[0]))
self.assertEqual(lead_times_out, None)
self.assertIsInstance(radii_out, float)
<|end_body_0|>
<|body_start... | Test the radius_by_lead_time method. | Test_radius_by_lead_time | [
"BSD-3-Clause",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_radius_by_lead_time:
"""Test the radius_by_lead_time method."""
def test_single_radius(self):
"""Test that when a single radius is provided with no lead times the returned objects are a float equal to the input radius and a NoneType representing the lead times."""
<|body... | stack_v2_sparse_classes_36k_train_021940 | 3,848 | permissive | [
{
"docstring": "Test that when a single radius is provided with no lead times the returned objects are a float equal to the input radius and a NoneType representing the lead times.",
"name": "test_single_radius",
"signature": "def test_single_radius(self)"
},
{
"docstring": "Test that when multi... | 4 | null | Implement the Python class `Test_radius_by_lead_time` described below.
Class description:
Test the radius_by_lead_time method.
Method signatures and docstrings:
- def test_single_radius(self): Test that when a single radius is provided with no lead times the returned objects are a float equal to the input radius and ... | Implement the Python class `Test_radius_by_lead_time` described below.
Class description:
Test the radius_by_lead_time method.
Method signatures and docstrings:
- def test_single_radius(self): Test that when a single radius is provided with no lead times the returned objects are a float equal to the input radius and ... | cd2c9019944345df1e703bf8f625db537ad9f559 | <|skeleton|>
class Test_radius_by_lead_time:
"""Test the radius_by_lead_time method."""
def test_single_radius(self):
"""Test that when a single radius is provided with no lead times the returned objects are a float equal to the input radius and a NoneType representing the lead times."""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test_radius_by_lead_time:
"""Test the radius_by_lead_time method."""
def test_single_radius(self):
"""Test that when a single radius is provided with no lead times the returned objects are a float equal to the input radius and a NoneType representing the lead times."""
radii = ['10000']
... | the_stack_v2_python_sparse | improver_tests/nbhood/test_init.py | metoppv/improver | train | 101 |
baf805206c9f377705c1288d0e95895b89490361 | [
"left = 0\nwhile left <= right:\n mid = left + (right - left >> 1)\n if nums[mid] == target:\n return mid\n if nums[mid] > target:\n right = mid - 1\n else:\n left = mid + 1\nreturn -1",
"n = len(arr)\nret = 0\ndp = [[0 for i in range(n)] for j in range(n)]\nfor i in range(1, n):\... | <|body_start_0|>
left = 0
while left <= right:
mid = left + (right - left >> 1)
if nums[mid] == target:
return mid
if nums[mid] > target:
right = mid - 1
else:
left = mid + 1
return -1
<|end_body_0|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def binary_search(self, nums, right, target):
"""二分查找"""
<|body_0|>
def lenLongestFibSubseq(self, arr):
""":type arr: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
left = 0
while left <= right:
m... | stack_v2_sparse_classes_36k_train_021941 | 860 | no_license | [
{
"docstring": "二分查找",
"name": "binary_search",
"signature": "def binary_search(self, nums, right, target)"
},
{
"docstring": ":type arr: List[int] :rtype: int",
"name": "lenLongestFibSubseq",
"signature": "def lenLongestFibSubseq(self, arr)"
}
] | 2 | stack_v2_sparse_classes_30k_val_000902 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def binary_search(self, nums, right, target): 二分查找
- def lenLongestFibSubseq(self, arr): :type arr: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def binary_search(self, nums, right, target): 二分查找
- def lenLongestFibSubseq(self, arr): :type arr: List[int] :rtype: int
<|skeleton|>
class Solution:
def binary_search(sel... | 4b30dd6a3f683c8dc71a85f7b947232613a28dc1 | <|skeleton|>
class Solution:
def binary_search(self, nums, right, target):
"""二分查找"""
<|body_0|>
def lenLongestFibSubseq(self, arr):
""":type arr: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def binary_search(self, nums, right, target):
"""二分查找"""
left = 0
while left <= right:
mid = left + (right - left >> 1)
if nums[mid] == target:
return mid
if nums[mid] > target:
right = mid - 1
el... | the_stack_v2_python_sparse | 最长斐波那契数列__时间超时.py | saintifly/leetcode | train | 0 | |
b18156591ffa6a2e2378d6b77eb15b079ccba36c | [
"try:\n\n def generate(vo):\n for exception in list_exceptions(exception_id, vo=vo):\n yield (dumps(exception, cls=APIEncoder) + '\\n')\n return try_stream(generate(vo=request.environ.get('vo')))\nexcept LifetimeExceptionNotFound as error:\n return generate_http_error_flask(404, 'Lifetime... | <|body_start_0|>
try:
def generate(vo):
for exception in list_exceptions(exception_id, vo=vo):
yield (dumps(exception, cls=APIEncoder) + '\n')
return try_stream(generate(vo=request.environ.get('vo')))
except LifetimeExceptionNotFound as error:... | REST APIs for Lifetime Model exception. | LifetimeExceptionId | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LifetimeExceptionId:
"""REST APIs for Lifetime Model exception."""
def get(self, exception_id):
"""Retrieve an exception. .. :quickref: LifetimeExceptionId; Get an exceptions. :param exception_id: The exception identifier. :resheader Content-Type: application/x-json-stream :status 20... | stack_v2_sparse_classes_36k_train_021942 | 8,648 | permissive | [
{
"docstring": "Retrieve an exception. .. :quickref: LifetimeExceptionId; Get an exceptions. :param exception_id: The exception identifier. :resheader Content-Type: application/x-json-stream :status 200: OK. :status 401: Invalid Auth Token. :status 404: Lifetime Exception Not Found. :status 406: Not Acceptable.... | 2 | stack_v2_sparse_classes_30k_train_005803 | Implement the Python class `LifetimeExceptionId` described below.
Class description:
REST APIs for Lifetime Model exception.
Method signatures and docstrings:
- def get(self, exception_id): Retrieve an exception. .. :quickref: LifetimeExceptionId; Get an exceptions. :param exception_id: The exception identifier. :res... | Implement the Python class `LifetimeExceptionId` described below.
Class description:
REST APIs for Lifetime Model exception.
Method signatures and docstrings:
- def get(self, exception_id): Retrieve an exception. .. :quickref: LifetimeExceptionId; Get an exceptions. :param exception_id: The exception identifier. :res... | bf33d9441d3b4ff160a392eed56724f635a03fe6 | <|skeleton|>
class LifetimeExceptionId:
"""REST APIs for Lifetime Model exception."""
def get(self, exception_id):
"""Retrieve an exception. .. :quickref: LifetimeExceptionId; Get an exceptions. :param exception_id: The exception identifier. :resheader Content-Type: application/x-json-stream :status 20... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LifetimeExceptionId:
"""REST APIs for Lifetime Model exception."""
def get(self, exception_id):
"""Retrieve an exception. .. :quickref: LifetimeExceptionId; Get an exceptions. :param exception_id: The exception identifier. :resheader Content-Type: application/x-json-stream :status 200: OK. :statu... | the_stack_v2_python_sparse | lib/rucio/web/rest/flaskapi/v1/lifetime_exceptions.py | viveknigam3003/rucio | train | 1 |
6bf725f2fb10e51125e36272a73e385b71ecd697 | [
"super().__init__(agent)\nself.id = agent_id\nself.experience_replay = experience_replay\nself.param_pipe = param_pipe",
"if self.param_pipe is not None and self.param_pipe.poll():\n env_episodes = self.algo.env_episodes\n env_steps = self.algo.env_steps\n self.algo.load(load_dict=self.param_pipe.recv())... | <|body_start_0|>
super().__init__(agent)
self.id = agent_id
self.experience_replay = experience_replay
self.param_pipe = param_pipe
<|end_body_0|>
<|body_start_1|>
if self.param_pipe is not None and self.param_pipe.poll():
env_episodes = self.algo.env_episodes
... | An agent that sends its experiences into a queue 1 at a time rather than training directly. | QueueAgent | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QueueAgent:
"""An agent that sends its experiences into a queue 1 at a time rather than training directly."""
def __init__(self, agent: OffPolicyAgent, agent_id: int, experience_replay: PER, param_pipe: Optional[Pipe]=None):
"""Creates the queue agent, that passes experiences to a qu... | stack_v2_sparse_classes_36k_train_021943 | 4,100 | permissive | [
{
"docstring": "Creates the queue agent, that passes experiences to a queue to be inserting into replay buffer. Args: agent: The off policy agent to wrap. agent_id: The id of the agent. experience_replay: The PER object responsible for computing the errors and priorites of experiences. param_pipe: The pipe to r... | 4 | null | Implement the Python class `QueueAgent` described below.
Class description:
An agent that sends its experiences into a queue 1 at a time rather than training directly.
Method signatures and docstrings:
- def __init__(self, agent: OffPolicyAgent, agent_id: int, experience_replay: PER, param_pipe: Optional[Pipe]=None):... | Implement the Python class `QueueAgent` described below.
Class description:
An agent that sends its experiences into a queue 1 at a time rather than training directly.
Method signatures and docstrings:
- def __init__(self, agent: OffPolicyAgent, agent_id: int, experience_replay: PER, param_pipe: Optional[Pipe]=None):... | cde3be1c69bfd76fe4a78fa529e851d0a78318c7 | <|skeleton|>
class QueueAgent:
"""An agent that sends its experiences into a queue 1 at a time rather than training directly."""
def __init__(self, agent: OffPolicyAgent, agent_id: int, experience_replay: PER, param_pipe: Optional[Pipe]=None):
"""Creates the queue agent, that passes experiences to a qu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QueueAgent:
"""An agent that sends its experiences into a queue 1 at a time rather than training directly."""
def __init__(self, agent: OffPolicyAgent, agent_id: int, experience_replay: PER, param_pipe: Optional[Pipe]=None):
"""Creates the queue agent, that passes experiences to a queue to be ins... | the_stack_v2_python_sparse | hlrl/core/agents/wrappers/queue_agent.py | Chainso/HLRL | train | 3 |
f91725621eb611b46d9bea5aa2c998109d460bbe | [
"id = request.args.get('id')\nif id:\n verify_request = db.get_identity(id)\nelse:\n verify_request = db.get_next_identity()\ncache.set(Identity.get_key(verify_request.id), verify_request, 15 * 60)\nself.id.data = verify_request.id\nreturn verify_request",
"verify_request.address_1.value = self.address_1.da... | <|body_start_0|>
id = request.args.get('id')
if id:
verify_request = db.get_identity(id)
else:
verify_request = db.get_next_identity()
cache.set(Identity.get_key(verify_request.id), verify_request, 15 * 60)
self.id.data = verify_request.id
return v... | VerifyForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VerifyForm:
def get(self, request):
"""do verify form get processing, basically get the request to verify"""
<|body_0|>
def update_verify_request(self, verify_request):
"""updates a verification request using form data"""
<|body_1|>
def get_request(self)... | stack_v2_sparse_classes_36k_train_021944 | 8,284 | no_license | [
{
"docstring": "do verify form get processing, basically get the request to verify",
"name": "get",
"signature": "def get(self, request)"
},
{
"docstring": "updates a verification request using form data",
"name": "update_verify_request",
"signature": "def update_verify_request(self, ver... | 4 | stack_v2_sparse_classes_30k_train_008939 | Implement the Python class `VerifyForm` described below.
Class description:
Implement the VerifyForm class.
Method signatures and docstrings:
- def get(self, request): do verify form get processing, basically get the request to verify
- def update_verify_request(self, verify_request): updates a verification request u... | Implement the Python class `VerifyForm` described below.
Class description:
Implement the VerifyForm class.
Method signatures and docstrings:
- def get(self, request): do verify form get processing, basically get the request to verify
- def update_verify_request(self, verify_request): updates a verification request u... | 932864230d113311674cbe898259d068505c76af | <|skeleton|>
class VerifyForm:
def get(self, request):
"""do verify form get processing, basically get the request to verify"""
<|body_0|>
def update_verify_request(self, verify_request):
"""updates a verification request using form data"""
<|body_1|>
def get_request(self)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VerifyForm:
def get(self, request):
"""do verify form get processing, basically get the request to verify"""
id = request.args.get('id')
if id:
verify_request = db.get_identity(id)
else:
verify_request = db.get_next_identity()
cache.set(Identity.... | the_stack_v2_python_sparse | verifier/verifier/forms/verify_form.py | bpalazzola/vote | train | 0 | |
cb4d280d91cefa328246ec822ca149d55a5c27a0 | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('kobesay', 'kobesay')\nrepo.dropCollection('regionhospital')\nrepo.createCollection('regionhospital')\nitems = {}\nhospital = repo.kobesay.hospital.find()\nfor x in hospital:\n zipcode = x['zipcode'].s... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('kobesay', 'kobesay')
repo.dropCollection('regionhospital')
repo.createCollection('regionhospital')
items = {}
hospital = repo.kobe... | trans_hospital | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class trans_hospital:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everythin... | stack_v2_sparse_classes_36k_train_021945 | 3,673 | no_license | [
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"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 d... | 2 | stack_v2_sparse_classes_30k_train_006168 | Implement the Python class `trans_hospital` described below.
Class description:
Implement the trans_hospital class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=None,... | Implement the Python class `trans_hospital` described below.
Class description:
Implement the trans_hospital class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=None,... | 0df485d0469c5451ebdcd684bed2a0960ba3ab84 | <|skeleton|>
class trans_hospital:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everythin... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class trans_hospital:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('kobesay', 'kobesay')
repo.dr... | the_stack_v2_python_sparse | kobesay/trans_hospital.py | lingyigu/course-2017-spr-proj | train | 0 | |
2e1b2f4c33c58bbb6d9c87f3bfe4ff617a0c67df | [
"super(GridSearch, self).__init__(task=task, stopCriteria=stopCriteria, parameters=parameters)\nself.name = 'Grid Search'\nself.order = 0\nself.resolution = np.array(parameters.get('resolution'))\nself.randomize_evaluation_order = parameters.get('randomize_evaluation_order', False)\nif self.resolution.size == self.... | <|body_start_0|>
super(GridSearch, self).__init__(task=task, stopCriteria=stopCriteria, parameters=parameters)
self.name = 'Grid Search'
self.order = 0
self.resolution = np.array(parameters.get('resolution'))
self.randomize_evaluation_order = parameters.get('randomize_evaluation_... | GridSearch | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GridSearch:
def __init__(self, task, stopCriteria, parameters=DotMap()):
"""Grid Search :param task: :param parameters: resolution: scalar or np.array. define the resolution of the grid to be evaluated. randomize_evaluation_order: Bool. if True, randomize the order in which the points of... | stack_v2_sparse_classes_36k_train_021946 | 2,630 | permissive | [
{
"docstring": "Grid Search :param task: :param parameters: resolution: scalar or np.array. define the resolution of the grid to be evaluated. randomize_evaluation_order: Bool. if True, randomize the order in which the points of the grid are evaluated. Useful for purposes of comparing grid search against other ... | 2 | stack_v2_sparse_classes_30k_train_007404 | Implement the Python class `GridSearch` described below.
Class description:
Implement the GridSearch class.
Method signatures and docstrings:
- def __init__(self, task, stopCriteria, parameters=DotMap()): Grid Search :param task: :param parameters: resolution: scalar or np.array. define the resolution of the grid to ... | Implement the Python class `GridSearch` described below.
Class description:
Implement the GridSearch class.
Method signatures and docstrings:
- def __init__(self, task, stopCriteria, parameters=DotMap()): Grid Search :param task: :param parameters: resolution: scalar or np.array. define the resolution of the grid to ... | e8a108c1975353e5576d5ab8ec7b8017452ea177 | <|skeleton|>
class GridSearch:
def __init__(self, task, stopCriteria, parameters=DotMap()):
"""Grid Search :param task: :param parameters: resolution: scalar or np.array. define the resolution of the grid to be evaluated. randomize_evaluation_order: Bool. if True, randomize the order in which the points of... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GridSearch:
def __init__(self, task, stopCriteria, parameters=DotMap()):
"""Grid Search :param task: :param parameters: resolution: scalar or np.array. define the resolution of the grid to be evaluated. randomize_evaluation_order: Bool. if True, randomize the order in which the points of the grid are ... | the_stack_v2_python_sparse | opto/GridSearch.py | robertocalandra/opto | train | 5 | |
d82b75e430e01c48cbb9fe7c2d16af6159b8448c | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')"
] | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Proto file describing the Custom Interest service. Service to manage custom interests. | CustomInterestServiceServicer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CustomInterestServiceServicer:
"""Proto file describing the Custom Interest service. Service to manage custom interests."""
def GetCustomInterest(self, request, context):
"""Returns the requested custom interest in full detail."""
<|body_0|>
def MutateCustomInterests(sel... | stack_v2_sparse_classes_36k_train_021947 | 3,482 | permissive | [
{
"docstring": "Returns the requested custom interest in full detail.",
"name": "GetCustomInterest",
"signature": "def GetCustomInterest(self, request, context)"
},
{
"docstring": "Creates or updates custom interests. Operation statuses are returned.",
"name": "MutateCustomInterests",
"s... | 2 | stack_v2_sparse_classes_30k_train_013565 | Implement the Python class `CustomInterestServiceServicer` described below.
Class description:
Proto file describing the Custom Interest service. Service to manage custom interests.
Method signatures and docstrings:
- def GetCustomInterest(self, request, context): Returns the requested custom interest in full detail.... | Implement the Python class `CustomInterestServiceServicer` described below.
Class description:
Proto file describing the Custom Interest service. Service to manage custom interests.
Method signatures and docstrings:
- def GetCustomInterest(self, request, context): Returns the requested custom interest in full detail.... | a5b6cede64f4d9912ae6ad26927a54e40448c9fe | <|skeleton|>
class CustomInterestServiceServicer:
"""Proto file describing the Custom Interest service. Service to manage custom interests."""
def GetCustomInterest(self, request, context):
"""Returns the requested custom interest in full detail."""
<|body_0|>
def MutateCustomInterests(sel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CustomInterestServiceServicer:
"""Proto file describing the Custom Interest service. Service to manage custom interests."""
def GetCustomInterest(self, request, context):
"""Returns the requested custom interest in full detail."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
co... | the_stack_v2_python_sparse | google/ads/google_ads/v3/proto/services/custom_interest_service_pb2_grpc.py | fiboknacky/google-ads-python | train | 0 |
29e80ecbd55e38b9e35b16fbef9a747a4d35a73d | [
"try:\n cls.abrir_conexion()\n sql = 'SELECT mat_ins.cantidad,mat_ins.idMaterial FROM mat_ins WHERE idInsumo = {};'.format(id)\n cls.cursor.execute(sql)\n cantmats_ = cls.cursor.fetchall()\n cantmats = []\n for m in cantmats_:\n cantmat = CantMaterial... | <|body_start_0|>
try:
cls.abrir_conexion()
sql = 'SELECT mat_ins.cantidad,mat_ins.idMaterial FROM mat_ins WHERE idInsumo = {};'.format(id)
cls.cursor.execute(sql)
cantmats_ = cls.cursor.fetchall()
cantmats = []
... | DatosCantMaterial | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DatosCantMaterial:
def get_from_Insid(cls, id, noClose=False):
"""Obtiene los materiales que componen un insumo de la BD"""
<|body_0|>
def addComponente(cls, idMat, idIns, cant):
"""Registra una cantidad de un material requerido para la produccion de un insumo."""
... | stack_v2_sparse_classes_36k_train_021948 | 5,360 | no_license | [
{
"docstring": "Obtiene los materiales que componen un insumo de la BD",
"name": "get_from_Insid",
"signature": "def get_from_Insid(cls, id, noClose=False)"
},
{
"docstring": "Registra una cantidad de un material requerido para la produccion de un insumo.",
"name": "addComponente",
"sign... | 6 | null | Implement the Python class `DatosCantMaterial` described below.
Class description:
Implement the DatosCantMaterial class.
Method signatures and docstrings:
- def get_from_Insid(cls, id, noClose=False): Obtiene los materiales que componen un insumo de la BD
- def addComponente(cls, idMat, idIns, cant): Registra una ca... | Implement the Python class `DatosCantMaterial` described below.
Class description:
Implement the DatosCantMaterial class.
Method signatures and docstrings:
- def get_from_Insid(cls, id, noClose=False): Obtiene los materiales que componen un insumo de la BD
- def addComponente(cls, idMat, idIns, cant): Registra una ca... | 57ca674dba4dabd2526c450ba7210933240f19c5 | <|skeleton|>
class DatosCantMaterial:
def get_from_Insid(cls, id, noClose=False):
"""Obtiene los materiales que componen un insumo de la BD"""
<|body_0|>
def addComponente(cls, idMat, idIns, cant):
"""Registra una cantidad de un material requerido para la produccion de un insumo."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DatosCantMaterial:
def get_from_Insid(cls, id, noClose=False):
"""Obtiene los materiales que componen un insumo de la BD"""
try:
cls.abrir_conexion()
sql = 'SELECT mat_ins.cantidad,mat_ins.idMaterial FROM mat_ins WHERE idInsumo = ... | the_stack_v2_python_sparse | data/data_cant_material.py | JoaquinCardonaRuiz/proyecto-final | train | 0 | |
2a87983b567a571508f64824ea32e201e8d1f83a | [
"if model._meta.app_label in self.db_user_apps:\n return 'rbac_db'\nreturn None",
"if model._meta.app_label in self.db_user_apps:\n return 'rbac_db'\nreturn None",
"if app_label in self.db_user_apps:\n return db == 'rbac_db'\nreturn None"
] | <|body_start_0|>
if model._meta.app_label in self.db_user_apps:
return 'rbac_db'
return None
<|end_body_0|>
<|body_start_1|>
if model._meta.app_label in self.db_user_apps:
return 'rbac_db'
return None
<|end_body_1|>
<|body_start_2|>
if app_label in self.... | A router to control all database operations on models in the auth application. | DatabaseRouter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DatabaseRouter:
"""A router to control all database operations on models in the auth application."""
def db_for_read(self, model, **hints):
"""Attempts to read auth models go to default."""
<|body_0|>
def db_for_write(self, model, **hints):
"""Attempts to write a... | stack_v2_sparse_classes_36k_train_021949 | 1,058 | no_license | [
{
"docstring": "Attempts to read auth models go to default.",
"name": "db_for_read",
"signature": "def db_for_read(self, model, **hints)"
},
{
"docstring": "Attempts to write auth models go to default.",
"name": "db_for_write",
"signature": "def db_for_write(self, model, **hints)"
},
... | 3 | stack_v2_sparse_classes_30k_train_018515 | Implement the Python class `DatabaseRouter` described below.
Class description:
A router to control all database operations on models in the auth application.
Method signatures and docstrings:
- def db_for_read(self, model, **hints): Attempts to read auth models go to default.
- def db_for_write(self, model, **hints)... | Implement the Python class `DatabaseRouter` described below.
Class description:
A router to control all database operations on models in the auth application.
Method signatures and docstrings:
- def db_for_read(self, model, **hints): Attempts to read auth models go to default.
- def db_for_write(self, model, **hints)... | bb85b52598d68956bde8756c8321ade7b8479ba7 | <|skeleton|>
class DatabaseRouter:
"""A router to control all database operations on models in the auth application."""
def db_for_read(self, model, **hints):
"""Attempts to read auth models go to default."""
<|body_0|>
def db_for_write(self, model, **hints):
"""Attempts to write a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DatabaseRouter:
"""A router to control all database operations on models in the auth application."""
def db_for_read(self, model, **hints):
"""Attempts to read auth models go to default."""
if model._meta.app_label in self.db_user_apps:
return 'rbac_db'
return None
... | the_stack_v2_python_sparse | rbac_v1/rbac/db_router_setting.py | huiiiuh/huihuiproject | train | 0 |
6edb0cb8f34a40d8ff576e6d6bc42983ff81abe8 | [
"if isinstance(schema, dict):\n schema = vol.Schema(schema)\nself._schema = schema\nself._allow_empty = allow_empty",
"@wraps(method)\nasync def wrapper(view: _HassViewT, request: web.Request, *args: _P.args, **kwargs: _P.kwargs) -> web.Response:\n \"\"\"Wrap a request handler with data validation.\"\"\"\n ... | <|body_start_0|>
if isinstance(schema, dict):
schema = vol.Schema(schema)
self._schema = schema
self._allow_empty = allow_empty
<|end_body_0|>
<|body_start_1|>
@wraps(method)
async def wrapper(view: _HassViewT, request: web.Request, *args: _P.args, **kwargs: _P.kwarg... | Decorator that will validate the incoming data. Takes in a voluptuous schema and adds 'data' as keyword argument to the function call. Will return a 400 if no JSON provided or doesn't match schema. | RequestDataValidator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RequestDataValidator:
"""Decorator that will validate the incoming data. Takes in a voluptuous schema and adds 'data' as keyword argument to the function call. Will return a 400 if no JSON provided or doesn't match schema."""
def __init__(self, schema: vol.Schema, allow_empty: bool=False) ->... | stack_v2_sparse_classes_36k_train_021950 | 2,410 | permissive | [
{
"docstring": "Initialize the decorator.",
"name": "__init__",
"signature": "def __init__(self, schema: vol.Schema, allow_empty: bool=False) -> None"
},
{
"docstring": "Decorate a function.",
"name": "__call__",
"signature": "def __call__(self, method: Callable[Concatenate[_HassViewT, w... | 2 | stack_v2_sparse_classes_30k_train_004601 | Implement the Python class `RequestDataValidator` described below.
Class description:
Decorator that will validate the incoming data. Takes in a voluptuous schema and adds 'data' as keyword argument to the function call. Will return a 400 if no JSON provided or doesn't match schema.
Method signatures and docstrings:
... | Implement the Python class `RequestDataValidator` described below.
Class description:
Decorator that will validate the incoming data. Takes in a voluptuous schema and adds 'data' as keyword argument to the function call. Will return a 400 if no JSON provided or doesn't match schema.
Method signatures and docstrings:
... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class RequestDataValidator:
"""Decorator that will validate the incoming data. Takes in a voluptuous schema and adds 'data' as keyword argument to the function call. Will return a 400 if no JSON provided or doesn't match schema."""
def __init__(self, schema: vol.Schema, allow_empty: bool=False) ->... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RequestDataValidator:
"""Decorator that will validate the incoming data. Takes in a voluptuous schema and adds 'data' as keyword argument to the function call. Will return a 400 if no JSON provided or doesn't match schema."""
def __init__(self, schema: vol.Schema, allow_empty: bool=False) -> None:
... | the_stack_v2_python_sparse | homeassistant/components/http/data_validator.py | home-assistant/core | train | 35,501 |
32632a85dc78eef9588f422bb3ad2b38452baa05 | [
"if (delta_value := data.get('delta')):\n if isinstance(delta_value, str):\n if (internal_value := DISTRIBUTED_COST_INTERNAL.get(delta_value)):\n data['delta'] = internal_value\n if delta_value == 'cost':\n data['delta'] = 'cost_total'\nreturn super().to_internal_value(data)",... | <|body_start_0|>
if (delta_value := data.get('delta')):
if isinstance(delta_value, str):
if (internal_value := DISTRIBUTED_COST_INTERNAL.get(delta_value)):
data['delta'] = internal_value
if delta_value == 'cost':
data['delta'] =... | Serializer for handling query parameters. | OCPQueryParamSerializer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OCPQueryParamSerializer:
"""Serializer for handling query parameters."""
def to_internal_value(self, data):
"""Send to internal value."""
<|body_0|>
def validate(self, data):
"""Validate incoming data. Args: data (Dict): data to be validated Returns: (Dict): Vali... | stack_v2_sparse_classes_36k_train_021951 | 8,876 | permissive | [
{
"docstring": "Send to internal value.",
"name": "to_internal_value",
"signature": "def to_internal_value(self, data)"
},
{
"docstring": "Validate incoming data. Args: data (Dict): data to be validated Returns: (Dict): Validated data Raises: (ValidationError): if field inputs are invalid",
... | 3 | stack_v2_sparse_classes_30k_train_009141 | Implement the Python class `OCPQueryParamSerializer` described below.
Class description:
Serializer for handling query parameters.
Method signatures and docstrings:
- def to_internal_value(self, data): Send to internal value.
- def validate(self, data): Validate incoming data. Args: data (Dict): data to be validated ... | Implement the Python class `OCPQueryParamSerializer` described below.
Class description:
Serializer for handling query parameters.
Method signatures and docstrings:
- def to_internal_value(self, data): Send to internal value.
- def validate(self, data): Validate incoming data. Args: data (Dict): data to be validated ... | 0416e5216eb1ec4b41c8dd4999adde218b1ab2e1 | <|skeleton|>
class OCPQueryParamSerializer:
"""Serializer for handling query parameters."""
def to_internal_value(self, data):
"""Send to internal value."""
<|body_0|>
def validate(self, data):
"""Validate incoming data. Args: data (Dict): data to be validated Returns: (Dict): Vali... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OCPQueryParamSerializer:
"""Serializer for handling query parameters."""
def to_internal_value(self, data):
"""Send to internal value."""
if (delta_value := data.get('delta')):
if isinstance(delta_value, str):
if (internal_value := DISTRIBUTED_COST_INTERNAL.get... | the_stack_v2_python_sparse | koku/api/report/ocp/serializers.py | project-koku/koku | train | 225 |
a9560075c848dc46dfdefac5754c8036489c793d | [
"if isinstance(id, basestring):\n try:\n id = int(id)\n except ValueError:\n return\nreturn cls.reverse_color.get(id)",
"if cls.color_rus.get(name):\n return cls.color_rus.get(name)\nif cls.color_eng.get(name):\n return cls.color_eng.get(name)\nreturn cls.OTHER"
] | <|body_start_0|>
if isinstance(id, basestring):
try:
id = int(id)
except ValueError:
return
return cls.reverse_color.get(id)
<|end_body_0|>
<|body_start_1|>
if cls.color_rus.get(name):
return cls.color_rus.get(name)
if ... | Colors | Color | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Color:
"""Colors"""
def get_name(cls, id):
"""Return color name"""
<|body_0|>
def get_id(cls, name):
"""Return color id"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if isinstance(id, basestring):
try:
id = int(id)
... | stack_v2_sparse_classes_36k_train_021952 | 1,457 | no_license | [
{
"docstring": "Return color name",
"name": "get_name",
"signature": "def get_name(cls, id)"
},
{
"docstring": "Return color id",
"name": "get_id",
"signature": "def get_id(cls, name)"
}
] | 2 | null | Implement the Python class `Color` described below.
Class description:
Colors
Method signatures and docstrings:
- def get_name(cls, id): Return color name
- def get_id(cls, name): Return color id | Implement the Python class `Color` described below.
Class description:
Colors
Method signatures and docstrings:
- def get_name(cls, id): Return color name
- def get_id(cls, name): Return color id
<|skeleton|>
class Color:
"""Colors"""
def get_name(cls, id):
"""Return color name"""
<|body_0|>... | b642bc81cf633c95ccd978d5e9fb4177eee38be4 | <|skeleton|>
class Color:
"""Colors"""
def get_name(cls, id):
"""Return color name"""
<|body_0|>
def get_id(cls, name):
"""Return color id"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Color:
"""Colors"""
def get_name(cls, id):
"""Return color name"""
if isinstance(id, basestring):
try:
id = int(id)
except ValueError:
return
return cls.reverse_color.get(id)
def get_id(cls, name):
"""Return colo... | the_stack_v2_python_sparse | apps/catalog/static_names.py | amyard/findinshopGit | train | 0 |
4b612ccddcca123d374e51540159ac2215f18f3c | [
"group = Group.query.get(id)\nif not group:\n api.abort(code=404, message='Group not found')\nreturn {'data': group.__jsonapi__()}",
"group = Group.query.get(id)\nif not group:\n api.abort(code=404, message='Group not found')\ndata = request.get_json()['data']\nif 'name' in data['attributes']:\n group.na... | <|body_start_0|>
group = Group.query.get(id)
if not group:
api.abort(code=404, message='Group not found')
return {'data': group.__jsonapi__()}
<|end_body_0|>
<|body_start_1|>
group = Group.query.get(id)
if not group:
api.abort(code=404, message='Group not... | Groups | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Groups:
def get(self, id):
"""Get group"""
<|body_0|>
def put(self, id):
"""Update group"""
<|body_1|>
def delete(self, id):
"""Delete group"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
group = Group.query.get(id)
if ... | stack_v2_sparse_classes_36k_train_021953 | 46,738 | permissive | [
{
"docstring": "Get group",
"name": "get",
"signature": "def get(self, id)"
},
{
"docstring": "Update group",
"name": "put",
"signature": "def put(self, id)"
},
{
"docstring": "Delete group",
"name": "delete",
"signature": "def delete(self, id)"
}
] | 3 | stack_v2_sparse_classes_30k_train_009406 | Implement the Python class `Groups` described below.
Class description:
Implement the Groups class.
Method signatures and docstrings:
- def get(self, id): Get group
- def put(self, id): Update group
- def delete(self, id): Delete group | Implement the Python class `Groups` described below.
Class description:
Implement the Groups class.
Method signatures and docstrings:
- def get(self, id): Get group
- def put(self, id): Update group
- def delete(self, id): Delete group
<|skeleton|>
class Groups:
def get(self, id):
"""Get group"""
... | 3439a2dd0bd527c5d604801fec3a5aac904a72e2 | <|skeleton|>
class Groups:
def get(self, id):
"""Get group"""
<|body_0|>
def put(self, id):
"""Update group"""
<|body_1|>
def delete(self, id):
"""Delete group"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Groups:
def get(self, id):
"""Get group"""
group = Group.query.get(id)
if not group:
api.abort(code=404, message='Group not found')
return {'data': group.__jsonapi__()}
def put(self, id):
"""Update group"""
group = Group.query.get(id)
if... | the_stack_v2_python_sparse | app/views.py | taidos/lxc-rest | train | 0 | |
52102028f9d7e53f6f41be7dcc7b2aa4cdb8850c | [
"allure.description('Testing drs creating device')\ndevicetype = 'ovibovi'\nmodel = 'OVI-BOVI'\nhubId = 0\ndevice2 = DRS.create_device(deviceType=devicetype, model=model, hubId=hubId, sensorId=random.randint(1, 100000))",
"allure.description('Testing drs creating and delete device')\ndeviceType = 'ovibovi'\nmodel... | <|body_start_0|>
allure.description('Testing drs creating device')
devicetype = 'ovibovi'
model = 'OVI-BOVI'
hubId = 0
device2 = DRS.create_device(deviceType=devicetype, model=model, hubId=hubId, sensorId=random.randint(1, 100000))
<|end_body_0|>
<|body_start_1|>
allure.... | Test_DRS_Basic | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_DRS_Basic:
def test_create_device(self, DRS):
"""Create device test Send http request to create device"""
<|body_0|>
def test_create_and_delete_device(self, DRS):
"""Create and delete device test Send http request to create and then delete device"""
<|bo... | stack_v2_sparse_classes_36k_train_021954 | 6,212 | no_license | [
{
"docstring": "Create device test Send http request to create device",
"name": "test_create_device",
"signature": "def test_create_device(self, DRS)"
},
{
"docstring": "Create and delete device test Send http request to create and then delete device",
"name": "test_create_and_delete_device"... | 6 | stack_v2_sparse_classes_30k_test_000085 | Implement the Python class `Test_DRS_Basic` described below.
Class description:
Implement the Test_DRS_Basic class.
Method signatures and docstrings:
- def test_create_device(self, DRS): Create device test Send http request to create device
- def test_create_and_delete_device(self, DRS): Create and delete device test... | Implement the Python class `Test_DRS_Basic` described below.
Class description:
Implement the Test_DRS_Basic class.
Method signatures and docstrings:
- def test_create_device(self, DRS): Create device test Send http request to create device
- def test_create_and_delete_device(self, DRS): Create and delete device test... | 2b08d3cc153f0ebdd6272a17962e1601390391c5 | <|skeleton|>
class Test_DRS_Basic:
def test_create_device(self, DRS):
"""Create device test Send http request to create device"""
<|body_0|>
def test_create_and_delete_device(self, DRS):
"""Create and delete device test Send http request to create and then delete device"""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test_DRS_Basic:
def test_create_device(self, DRS):
"""Create device test Send http request to create device"""
allure.description('Testing drs creating device')
devicetype = 'ovibovi'
model = 'OVI-BOVI'
hubId = 0
device2 = DRS.create_device(deviceType=devicetype... | the_stack_v2_python_sparse | test_framework_pytest/pytests/farming/cases/test_sf_drs_operations.py | jinnymus/Python | train | 0 | |
d4fb412624cdeb3ac37d40944cbbc8e9b16048ba | [
"self.ret = ''\n\ndef traverse(node):\n if node is None:\n self.ret += ',#'\n return\n self.ret += ',' + str(node.val)\n traverse(node.left)\n traverse(node.right)\ntraverse(root)\nreturn self.ret[1:]",
"data = data.split(',')\n\ndef decode(d):\n if not d:\n return None\n r ... | <|body_start_0|>
self.ret = ''
def traverse(node):
if node is None:
self.ret += ',#'
return
self.ret += ',' + str(node.val)
traverse(node.left)
traverse(node.right)
traverse(root)
return self.ret[1:]
<|end_b... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_... | stack_v2_sparse_classes_36k_train_021955 | 995 | no_license | [
{
"docstring": "Encodes a tree to a single string. :type root: TreeNode :rtype: str",
"name": "serialize",
"signature": "def serialize(self, root)"
},
{
"docstring": "Decodes your encoded data to tree. :type data: str :rtype: TreeNode",
"name": "deserialize",
"signature": "def deserializ... | 2 | null | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root): Encodes a tree to a single string. :type root: TreeNode :rtype: str
- def deserialize(self, data): Decodes your encoded data to tree. :type data: str :rtype:... | 116e84e41750b8e62e630deceda2e61589c66a3c | <|skeleton|>
class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
<|body_0|>
def deserialize(self, data):
"""Decodes your encoded data to tree. :type data: str :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
self.ret = ''
def traverse(node):
if node is None:
self.ret += ',#'
return
self.ret += ',' + str(node.val)
tr... | the_stack_v2_python_sparse | code/algorithm/系列问题/二叉树/14.二叉树的序列化和反序列化.py | fadeawaylove/interview_mkdocs | train | 0 | |
da3f89c26f777e1069c26b74158029bc51940ef4 | [
"self.prot_attr = prot_attr\nself.adj_mat = adj_mat\npkgs = ('ranger', 'fairadapt')\npkgs = [p for p in pkgs if not robjects.packages.isinstalled(p)]\nif len(pkgs) > 0:\n utls = robjects.packages.importr('utils')\n utls.chooseCRANmirror(ind=1)\n utls.install_packages(StrVector(pkgs))",
"df_train = pd.con... | <|body_start_0|>
self.prot_attr = prot_attr
self.adj_mat = adj_mat
pkgs = ('ranger', 'fairadapt')
pkgs = [p for p in pkgs if not robjects.packages.isinstalled(p)]
if len(pkgs) > 0:
utls = robjects.packages.importr('utils')
utls.chooseCRANmirror(ind=1)
... | Fair Data Adaptation. Fairadapt is a pre-processing technique that can be used for both fair classification and fair regression [#plecko20]_. The method is a causal inference approach to bias removal and it relies on the causal graph for the dataset. The original implementation is in R [#plecko21]_. References: .. [#pl... | FairAdapt | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FairAdapt:
"""Fair Data Adaptation. Fairadapt is a pre-processing technique that can be used for both fair classification and fair regression [#plecko20]_. The method is a causal inference approach to bias removal and it relies on the causal graph for the dataset. The original implementation is i... | stack_v2_sparse_classes_36k_train_021956 | 4,623 | permissive | [
{
"docstring": "Args: prot_attr (single label): Name of the protected attribute. Must be binary. adj_mat (array-like): A 2-dimensional array representing the adjacency matrix of the causal diagram of the data generating process. Row/column order must match `X_train`.",
"name": "__init__",
"signature": "... | 2 | stack_v2_sparse_classes_30k_train_010174 | Implement the Python class `FairAdapt` described below.
Class description:
Fair Data Adaptation. Fairadapt is a pre-processing technique that can be used for both fair classification and fair regression [#plecko20]_. The method is a causal inference approach to bias removal and it relies on the causal graph for the da... | Implement the Python class `FairAdapt` described below.
Class description:
Fair Data Adaptation. Fairadapt is a pre-processing technique that can be used for both fair classification and fair regression [#plecko20]_. The method is a causal inference approach to bias removal and it relies on the causal graph for the da... | 6f9972e4a7dbca2402f29b86ea67889143dbeb3e | <|skeleton|>
class FairAdapt:
"""Fair Data Adaptation. Fairadapt is a pre-processing technique that can be used for both fair classification and fair regression [#plecko20]_. The method is a causal inference approach to bias removal and it relies on the causal graph for the dataset. The original implementation is i... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FairAdapt:
"""Fair Data Adaptation. Fairadapt is a pre-processing technique that can be used for both fair classification and fair regression [#plecko20]_. The method is a causal inference approach to bias removal and it relies on the causal graph for the dataset. The original implementation is in R [#plecko2... | the_stack_v2_python_sparse | aif360/sklearn/preprocessing/fairadapt.py | Trusted-AI/AIF360 | train | 1,157 |
eb348e4e342a4ed87ef952c10a0674295f25127b | [
"self.i_pv_4 = i_pv_4\nself.i_pv_6 = i_pv_6\nself.start_date = start_date\nself.end_date = end_date\nself.comments = comments\nself.active = active",
"if dictionary is None:\n return None\nstart_date = dictionary.get('Start_Date')\nend_date = dictionary.get('End_Date')\ncomments = dictionary.get('Comments')\na... | <|body_start_0|>
self.i_pv_4 = i_pv_4
self.i_pv_6 = i_pv_6
self.start_date = start_date
self.end_date = end_date
self.comments = comments
self.active = active
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
start_date = dict... | Implementation of the 'IP Address' model. The IP address information referenced by Bouncer when building `ufw` rules Attributes: i_pv_4 (string): IP Address v4 in CIDR Format. Either IPv4 or IPv6 MUST be present. i_pv_6 (string): IP Address v6 in CIDR Format. Either IPv4 or IPv6 MUST be present. start_date (string): St... | IPAddress | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IPAddress:
"""Implementation of the 'IP Address' model. The IP address information referenced by Bouncer when building `ufw` rules Attributes: i_pv_4 (string): IP Address v4 in CIDR Format. Either IPv4 or IPv6 MUST be present. i_pv_6 (string): IP Address v6 in CIDR Format. Either IPv4 or IPv6 MUS... | stack_v2_sparse_classes_36k_train_021957 | 2,646 | permissive | [
{
"docstring": "Constructor for the IPAddress class",
"name": "__init__",
"signature": "def __init__(self, start_date=None, end_date=None, comments=None, active=None, i_pv_4=None, i_pv_6=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): ... | 2 | stack_v2_sparse_classes_30k_train_004349 | Implement the Python class `IPAddress` described below.
Class description:
Implementation of the 'IP Address' model. The IP address information referenced by Bouncer when building `ufw` rules Attributes: i_pv_4 (string): IP Address v4 in CIDR Format. Either IPv4 or IPv6 MUST be present. i_pv_6 (string): IP Address v6 ... | Implement the Python class `IPAddress` described below.
Class description:
Implementation of the 'IP Address' model. The IP address information referenced by Bouncer when building `ufw` rules Attributes: i_pv_4 (string): IP Address v4 in CIDR Format. Either IPv4 or IPv6 MUST be present. i_pv_6 (string): IP Address v6 ... | a178244dbf0b8a165aabc02a5d1ba05006f9ec22 | <|skeleton|>
class IPAddress:
"""Implementation of the 'IP Address' model. The IP address information referenced by Bouncer when building `ufw` rules Attributes: i_pv_4 (string): IP Address v4 in CIDR Format. Either IPv4 or IPv6 MUST be present. i_pv_6 (string): IP Address v6 in CIDR Format. Either IPv4 or IPv6 MUS... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IPAddress:
"""Implementation of the 'IP Address' model. The IP address information referenced by Bouncer when building `ufw` rules Attributes: i_pv_4 (string): IP Address v4 in CIDR Format. Either IPv4 or IPv6 MUST be present. i_pv_6 (string): IP Address v6 in CIDR Format. Either IPv4 or IPv6 MUST be present.... | the_stack_v2_python_sparse | sdk/python/bouncerapi/models/ip_address.py | nmfta-repo/nmfta-bouncer | train | 1 |
837e832b59279df66cbd53e5b3eb8b7384cdef11 | [
"self._lock = Lock()\nself._condition = Condition(self._lock)\nself._last_rubble = None\nself._qr_sub = rospy.Subscriber('/qr_codes', String, callback=self.qr_cb, queue_size=5)\nself._as = actionlib.SimpleActionServer(action_server_name, RubbleCheckAction, execute_cb=self.execute_cb, auto_start=False)\nself._as.sta... | <|body_start_0|>
self._lock = Lock()
self._condition = Condition(self._lock)
self._last_rubble = None
self._qr_sub = rospy.Subscriber('/qr_codes', String, callback=self.qr_cb, queue_size=5)
self._as = actionlib.SimpleActionServer(action_server_name, RubbleCheckAction, execute_cb=... | Class for rubble check action server. Attributes: _lock: For locking access to qr messages _condition: Condition variable _last_rubble: Last rubble message received _as: The action server _qr_sub: The subscriber to the qr code topic | RubbleCheckServer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RubbleCheckServer:
"""Class for rubble check action server. Attributes: _lock: For locking access to qr messages _condition: Condition variable _last_rubble: Last rubble message received _as: The action server _qr_sub: The subscriber to the qr code topic"""
def __init__(self, action_server_n... | stack_v2_sparse_classes_36k_train_021958 | 2,928 | no_license | [
{
"docstring": "Creates and starts the action server. Args: action_server_name: The name of the action server.",
"name": "__init__",
"signature": "def __init__(self, action_server_name)"
},
{
"docstring": "Checks qr topic until something is called or timeout reached. Args: goal: Goal message (em... | 3 | stack_v2_sparse_classes_30k_train_006261 | Implement the Python class `RubbleCheckServer` described below.
Class description:
Class for rubble check action server. Attributes: _lock: For locking access to qr messages _condition: Condition variable _last_rubble: Last rubble message received _as: The action server _qr_sub: The subscriber to the qr code topic
Me... | Implement the Python class `RubbleCheckServer` described below.
Class description:
Class for rubble check action server. Attributes: _lock: For locking access to qr messages _condition: Condition variable _last_rubble: Last rubble message received _as: The action server _qr_sub: The subscriber to the qr code topic
Me... | 6217a34519dac55a4597410250f2d26ed23cbcf6 | <|skeleton|>
class RubbleCheckServer:
"""Class for rubble check action server. Attributes: _lock: For locking access to qr messages _condition: Condition variable _last_rubble: Last rubble message received _as: The action server _qr_sub: The subscriber to the qr code topic"""
def __init__(self, action_server_n... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RubbleCheckServer:
"""Class for rubble check action server. Attributes: _lock: For locking access to qr messages _condition: Condition variable _last_rubble: Last rubble message received _as: The action server _qr_sub: The subscriber to the qr code topic"""
def __init__(self, action_server_name):
... | the_stack_v2_python_sparse | aims_rubble_check/scripts/rubble_check_server.py | Forrest-Z/aims_ori_wheel | train | 0 |
fd05645598835592fb1e9c22e8857f6c99964232 | [
"self.path = self.__default_filepath if filepath is None else filepath\nself.parser = configparser.ConfigParser()\nif self.__section_default not in self.parser.sections():\n self.parser.add_section(self.__section_default)\nself.parser.read(self.path)",
"if self.parser.has_option(section, name):\n return sel... | <|body_start_0|>
self.path = self.__default_filepath if filepath is None else filepath
self.parser = configparser.ConfigParser()
if self.__section_default not in self.parser.sections():
self.parser.add_section(self.__section_default)
self.parser.read(self.path)
<|end_body_0|>... | A controller class for getting and setting key/value pairs in the config file | Controller | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Controller:
"""A controller class for getting and setting key/value pairs in the config file"""
def __init__(self, filepath=None):
"""Create an instance of a config controller for getting and setting information"""
<|body_0|>
def get(self, name, section=__section_default... | stack_v2_sparse_classes_36k_train_021959 | 2,040 | permissive | [
{
"docstring": "Create an instance of a config controller for getting and setting information",
"name": "__init__",
"signature": "def __init__(self, filepath=None)"
},
{
"docstring": "Returns a value with a given name from the configuration file.",
"name": "get",
"signature": "def get(se... | 4 | stack_v2_sparse_classes_30k_train_021047 | Implement the Python class `Controller` described below.
Class description:
A controller class for getting and setting key/value pairs in the config file
Method signatures and docstrings:
- def __init__(self, filepath=None): Create an instance of a config controller for getting and setting information
- def get(self,... | Implement the Python class `Controller` described below.
Class description:
A controller class for getting and setting key/value pairs in the config file
Method signatures and docstrings:
- def __init__(self, filepath=None): Create an instance of a config controller for getting and setting information
- def get(self,... | 25bc6118427f3b369fb61ba0bd38c977be05644f | <|skeleton|>
class Controller:
"""A controller class for getting and setting key/value pairs in the config file"""
def __init__(self, filepath=None):
"""Create an instance of a config controller for getting and setting information"""
<|body_0|>
def get(self, name, section=__section_default... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Controller:
"""A controller class for getting and setting key/value pairs in the config file"""
def __init__(self, filepath=None):
"""Create an instance of a config controller for getting and setting information"""
self.path = self.__default_filepath if filepath is None else filepath
... | the_stack_v2_python_sparse | apiwrapper/config/controller.py | OGKevin/ComBunqWebApp | train | 31 |
3a8b2f25b2ede5a50ac79f6478866acedd225294 | [
"self.content_type = content_type\nself.s3_uri = s3_uri\nself.content_digest = content_digest",
"file_source_request = {'S3Uri': self.s3_uri}\nif self.content_digest is not None:\n file_source_request['ContentDigest'] = self.content_digest\nif self.content_type is not None:\n file_source_request['ContentTyp... | <|body_start_0|>
self.content_type = content_type
self.s3_uri = s3_uri
self.content_digest = content_digest
<|end_body_0|>
<|body_start_1|>
file_source_request = {'S3Uri': self.s3_uri}
if self.content_digest is not None:
file_source_request['ContentDigest'] = self.co... | Accepts file source parameters for conversion to request dict. | FileSource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileSource:
"""Accepts file source parameters for conversion to request dict."""
def __init__(self, s3_uri: Union[str, PipelineVariable], content_digest: Optional[Union[str, PipelineVariable]]=None, content_type: Optional[Union[str, PipelineVariable]]=None):
"""Initialize a ``FileSou... | stack_v2_sparse_classes_36k_train_021960 | 7,143 | permissive | [
{
"docstring": "Initialize a ``FileSource`` instance and turn parameters into dict. Args: s3_uri (str or PipelineVariable): The S3 URI of the metric content_digest (str or PipelineVariable): The digest of the metric (default: None) content_type (str or PipelineVariable): Specifies the type of content in S3 URI ... | 2 | null | Implement the Python class `FileSource` described below.
Class description:
Accepts file source parameters for conversion to request dict.
Method signatures and docstrings:
- def __init__(self, s3_uri: Union[str, PipelineVariable], content_digest: Optional[Union[str, PipelineVariable]]=None, content_type: Optional[Un... | Implement the Python class `FileSource` described below.
Class description:
Accepts file source parameters for conversion to request dict.
Method signatures and docstrings:
- def __init__(self, s3_uri: Union[str, PipelineVariable], content_digest: Optional[Union[str, PipelineVariable]]=None, content_type: Optional[Un... | 8d5d7fd8ae1a917ed3e2b988d5e533bce244fd85 | <|skeleton|>
class FileSource:
"""Accepts file source parameters for conversion to request dict."""
def __init__(self, s3_uri: Union[str, PipelineVariable], content_digest: Optional[Union[str, PipelineVariable]]=None, content_type: Optional[Union[str, PipelineVariable]]=None):
"""Initialize a ``FileSou... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FileSource:
"""Accepts file source parameters for conversion to request dict."""
def __init__(self, s3_uri: Union[str, PipelineVariable], content_digest: Optional[Union[str, PipelineVariable]]=None, content_type: Optional[Union[str, PipelineVariable]]=None):
"""Initialize a ``FileSource`` instanc... | the_stack_v2_python_sparse | src/sagemaker/model_metrics.py | aws/sagemaker-python-sdk | train | 2,050 |
2a50bb02d8ef45ec96a91d48a2ff4dd94eee5e84 | [
"with TemporaryDirectory() as temp:\n trim([self.path / 'input/run'], self.path / 'samples.csv', dir_out=temp)\n files = sorted([p.name for p in Path(temp).glob('*')])\n files_expected = sorted([p.name for p in (self.path / 'output').glob('*')])\n self.assertEqual(files_expected, files)\n for path in... | <|body_start_0|>
with TemporaryDirectory() as temp:
trim([self.path / 'input/run'], self.path / 'samples.csv', dir_out=temp)
files = sorted([p.name for p in Path(temp).glob('*')])
files_expected = sorted([p.name for p in (self.path / 'output').glob('*')])
self.ass... | Basic tests of trim with actual cutadapt. Here we have a simple case with two sample with perfect adapters in R1 and R2. We should see the adapters get removed in the output, cutadapt's JSON report written, and our counts.csv files written. This should work with either a directory or individual R1/R2 pairs as input. Ea... | TestTrimLive | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestTrimLive:
"""Basic tests of trim with actual cutadapt. Here we have a simple case with two sample with perfect adapters in R1 and R2. We should see the adapters get removed in the output, cutadapt's JSON report written, and our counts.csv files written. This should work with either a director... | stack_v2_sparse_classes_36k_train_021961 | 2,759 | no_license | [
{
"docstring": "Test that adapters are trimmed from R1 and R2 pairs with dir input.",
"name": "test_trim_dir_input",
"signature": "def test_trim_dir_input(self)"
},
{
"docstring": "Test that adapters are trimmed from R1 and R2 pairs with file input.",
"name": "test_trim_file_input",
"sig... | 2 | stack_v2_sparse_classes_30k_train_008084 | Implement the Python class `TestTrimLive` described below.
Class description:
Basic tests of trim with actual cutadapt. Here we have a simple case with two sample with perfect adapters in R1 and R2. We should see the adapters get removed in the output, cutadapt's JSON report written, and our counts.csv files written. ... | Implement the Python class `TestTrimLive` described below.
Class description:
Basic tests of trim with actual cutadapt. Here we have a simple case with two sample with perfect adapters in R1 and R2. We should see the adapters get removed in the output, cutadapt's JSON report written, and our counts.csv files written. ... | 539868dab2041b7694c0d53e8e74cf1b5b033653 | <|skeleton|>
class TestTrimLive:
"""Basic tests of trim with actual cutadapt. Here we have a simple case with two sample with perfect adapters in R1 and R2. We should see the adapters get removed in the output, cutadapt's JSON report written, and our counts.csv files written. This should work with either a director... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestTrimLive:
"""Basic tests of trim with actual cutadapt. Here we have a simple case with two sample with perfect adapters in R1 and R2. We should see the adapters get removed in the output, cutadapt's JSON report written, and our counts.csv files written. This should work with either a directory or individu... | the_stack_v2_python_sparse | test_igseq/test_trim.py | ShawHahnLab/igseq | train | 1 |
0f77a53beb23197c6f3f9cc240d603ba29f5ba22 | [
"from collections import defaultdict\nself.index = defaultdict(set)\nself.nums = []",
"if val not in self.index:\n self.nums.append(val)\n self.index[val].add(len(self.nums) - 1)\n return True\nself.nums.append(val)\nself.index[val].add(len(self.nums) - 1)\nreturn False",
"if val not in self.index:\n ... | <|body_start_0|>
from collections import defaultdict
self.index = defaultdict(set)
self.nums = []
<|end_body_0|>
<|body_start_1|>
if val not in self.index:
self.nums.append(val)
self.index[val].add(len(self.nums) - 1)
return True
self.nums.app... | RandomizedCollection | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RandomizedCollection:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def insert(self, val: int) -> bool:
"""Inserts a value to the collection. Returns true if the collection did not already contain the specified element."""
<|body_1... | stack_v2_sparse_classes_36k_train_021962 | 1,815 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Inserts a value to the collection. Returns true if the collection did not already contain the specified element.",
"name": "insert",
"signature": "def insert(se... | 4 | null | Implement the Python class `RandomizedCollection` described below.
Class description:
Implement the RandomizedCollection class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def insert(self, val: int) -> bool: Inserts a value to the collection. Returns true if the coll... | Implement the Python class `RandomizedCollection` described below.
Class description:
Implement the RandomizedCollection class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def insert(self, val: int) -> bool: Inserts a value to the collection. Returns true if the coll... | 0d59c9fb2bec2bcea706733cba0d4ca73e1db0e8 | <|skeleton|>
class RandomizedCollection:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def insert(self, val: int) -> bool:
"""Inserts a value to the collection. Returns true if the collection did not already contain the specified element."""
<|body_1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RandomizedCollection:
def __init__(self):
"""Initialize your data structure here."""
from collections import defaultdict
self.index = defaultdict(set)
self.nums = []
def insert(self, val: int) -> bool:
"""Inserts a value to the collection. Returns true if the colle... | the_stack_v2_python_sparse | LeetCode/LeetCode381.py | LChanger/LeetCode | train | 0 | |
89272bb16a1a6d6e609bbc091f224660b5061ede | [
"super().__init__(name=name, **kwargs)\nself._output_last_dim = output_last_dim\nself._output_w_init = output_w_init\nself._use_query_residual = use_query_residual\nself._qk_last_dim = qk_last_dim\nself._v_last_dim = v_last_dim\nself._final_project = False\nself._num_heads = num_heads",
"decoder_query_shape = inp... | <|body_start_0|>
super().__init__(name=name, **kwargs)
self._output_last_dim = output_last_dim
self._output_w_init = output_w_init
self._use_query_residual = use_query_residual
self._qk_last_dim = qk_last_dim
self._v_last_dim = v_last_dim
self._final_project = Fal... | Perceiver Decoder layer. Uses cross attention decoder layer. This layer implements a Perceiver Decoder from "Perceiver: General Perception with Iterative Attention". (https://arxiv.org/abs/2103.03206) References: [Attention Is All You Need](https://arxiv.org/abs/1706.03762) [Perceiver: General Perception with Iterative... | Decoder | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Decoder:
"""Perceiver Decoder layer. Uses cross attention decoder layer. This layer implements a Perceiver Decoder from "Perceiver: General Perception with Iterative Attention". (https://arxiv.org/abs/2103.03206) References: [Attention Is All You Need](https://arxiv.org/abs/1706.03762) [Perceiver... | stack_v2_sparse_classes_36k_train_021963 | 5,196 | permissive | [
{
"docstring": "Init. Args: output_last_dim: Last dim size for output. qk_last_dim: When set, determines the last dimension of the attention score output. Check `qk_last_dim` doc in `utils.build_cross_attention_block_args`. v_last_dim: When set, determines the value's last dimension in the multi-head attention.... | 3 | null | Implement the Python class `Decoder` described below.
Class description:
Perceiver Decoder layer. Uses cross attention decoder layer. This layer implements a Perceiver Decoder from "Perceiver: General Perception with Iterative Attention". (https://arxiv.org/abs/2103.03206) References: [Attention Is All You Need](https... | Implement the Python class `Decoder` described below.
Class description:
Perceiver Decoder layer. Uses cross attention decoder layer. This layer implements a Perceiver Decoder from "Perceiver: General Perception with Iterative Attention". (https://arxiv.org/abs/2103.03206) References: [Attention Is All You Need](https... | d3507b550a3ade40cade60a79eb5b8978b56c7ae | <|skeleton|>
class Decoder:
"""Perceiver Decoder layer. Uses cross attention decoder layer. This layer implements a Perceiver Decoder from "Perceiver: General Perception with Iterative Attention". (https://arxiv.org/abs/2103.03206) References: [Attention Is All You Need](https://arxiv.org/abs/1706.03762) [Perceiver... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Decoder:
"""Perceiver Decoder layer. Uses cross attention decoder layer. This layer implements a Perceiver Decoder from "Perceiver: General Perception with Iterative Attention". (https://arxiv.org/abs/2103.03206) References: [Attention Is All You Need](https://arxiv.org/abs/1706.03762) [Perceiver: General Per... | the_stack_v2_python_sparse | official/projects/perceiver/modeling/layers/decoder.py | jianzhnie/models | train | 2 |
17e687ecd76601cb44d77bc8a36681eb9e327c97 | [
"super().__init__()\nself.bg_file = bg_file\nself.rmap = rmap\nself.ref_file = ref_file\nself.vcf_file = vcf_file\nself.inputq = inputq\nself.outputter = outputter\nself.annotations = annotations\nif outputter.sample_column:\n self.sample_index = outputter.sample_column - 9\nelse:\n self.sample_index = None\n... | <|body_start_0|>
super().__init__()
self.bg_file = bg_file
self.rmap = rmap
self.ref_file = ref_file
self.vcf_file = vcf_file
self.inputq = inputq
self.outputter = outputter
self.annotations = annotations
if outputter.sample_column:
sel... | Fetches vcf entries in a region and calculates coverage to enotype | PCMP | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PCMP:
"""Fetches vcf entries in a region and calculates coverage to enotype"""
def __init__(self, bg_file, rmap, ref_file, vcf_file, inputq, outputter, annotations, ref_pad_bases, passonly=None, phasing=False):
"""Runs over regions"""
<|body_0|>
def process_region(self, ... | stack_v2_sparse_classes_36k_train_021964 | 35,836 | permissive | [
{
"docstring": "Runs over regions",
"name": "__init__",
"signature": "def __init__(self, bg_file, rmap, ref_file, vcf_file, inputq, outputter, annotations, ref_pad_bases, passonly=None, phasing=False)"
},
{
"docstring": "work on all the entries in a region # this needs to fetch the vcf entries #... | 6 | null | Implement the Python class `PCMP` described below.
Class description:
Fetches vcf entries in a region and calculates coverage to enotype
Method signatures and docstrings:
- def __init__(self, bg_file, rmap, ref_file, vcf_file, inputq, outputter, annotations, ref_pad_bases, passonly=None, phasing=False): Runs over reg... | Implement the Python class `PCMP` described below.
Class description:
Fetches vcf entries in a region and calculates coverage to enotype
Method signatures and docstrings:
- def __init__(self, bg_file, rmap, ref_file, vcf_file, inputq, outputter, annotations, ref_pad_bases, passonly=None, phasing=False): Runs over reg... | 5f40198e95b0626ae143e021ec97884de634e61d | <|skeleton|>
class PCMP:
"""Fetches vcf entries in a region and calculates coverage to enotype"""
def __init__(self, bg_file, rmap, ref_file, vcf_file, inputq, outputter, annotations, ref_pad_bases, passonly=None, phasing=False):
"""Runs over regions"""
<|body_0|>
def process_region(self, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PCMP:
"""Fetches vcf entries in a region and calculates coverage to enotype"""
def __init__(self, bg_file, rmap, ref_file, vcf_file, inputq, outputter, annotations, ref_pad_bases, passonly=None, phasing=False):
"""Runs over regions"""
super().__init__()
self.bg_file = bg_file
... | the_stack_v2_python_sparse | python/biograph/tools/coverage.py | spiralgenetics/biograph | train | 21 |
a371f4a2a4444c83b33edfdbd76d304f7d132049 | [
"self.object_name = object_name\nself.comparitor = comparitor\nself.threshold = threshold\nself.feature = feature\nself.weights = weights",
"values = measurements.get_current_measurement(self.object_name, self.feature)\nif values is None:\n values = np.array([np.NaN])\nelif np.isscalar(values):\n values = n... | <|body_start_0|>
self.object_name = object_name
self.comparitor = comparitor
self.threshold = threshold
self.feature = feature
self.weights = weights
<|end_body_0|>
<|body_start_1|>
values = measurements.get_current_measurement(self.object_name, self.feature)
if ... | Represents a single rule | Rule | [
"BSD-3-Clause",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Rule:
"""Represents a single rule"""
def __init__(self, object_name, feature, comparitor, threshold, weights):
"""Create a rule object_name - the name of the object in the measurements feature - the name of the measurement (for instance, "AreaShape_Area") comparitor - the comparison ... | stack_v2_sparse_classes_36k_train_021965 | 5,488 | permissive | [
{
"docstring": "Create a rule object_name - the name of the object in the measurements feature - the name of the measurement (for instance, \"AreaShape_Area\") comparitor - the comparison to be performed (for instance, \">\") threshold - the positive / negative threshold for the comparison weights - a 2xN matri... | 2 | stack_v2_sparse_classes_30k_train_020904 | Implement the Python class `Rule` described below.
Class description:
Represents a single rule
Method signatures and docstrings:
- def __init__(self, object_name, feature, comparitor, threshold, weights): Create a rule object_name - the name of the object in the measurements feature - the name of the measurement (for... | Implement the Python class `Rule` described below.
Class description:
Represents a single rule
Method signatures and docstrings:
- def __init__(self, object_name, feature, comparitor, threshold, weights): Create a rule object_name - the name of the object in the measurements feature - the name of the measurement (for... | 1d230f129588838a926f93a47b86aa045a8ba93c | <|skeleton|>
class Rule:
"""Represents a single rule"""
def __init__(self, object_name, feature, comparitor, threshold, weights):
"""Create a rule object_name - the name of the object in the measurements feature - the name of the measurement (for instance, "AreaShape_Area") comparitor - the comparison ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Rule:
"""Represents a single rule"""
def __init__(self, object_name, feature, comparitor, threshold, weights):
"""Create a rule object_name - the name of the object in the measurements feature - the name of the measurement (for instance, "AreaShape_Area") comparitor - the comparison to be perform... | the_stack_v2_python_sparse | cellprofiler/utilities/rules.py | votti/CellProfiler | train | 0 |
370ebfa3944c455fab11b29d1bfb942bda7d2ab0 | [
"self.url = '/ydtp-backend-service/api/central/duty_info'\nre = self.get(url=self.zby_api, headers=form_headers)\nreturn re.json()",
"self.url = '/ydtp-backend-service/api/hand_over_central_duty'\ndata = {'user_id': user, 'password': pwd}\nre = self.post(self.zby_api, data=data, headers=form_headers)\nreturn re.j... | <|body_start_0|>
self.url = '/ydtp-backend-service/api/central/duty_info'
re = self.get(url=self.zby_api, headers=form_headers)
return re.json()
<|end_body_0|>
<|body_start_1|>
self.url = '/ydtp-backend-service/api/hand_over_central_duty'
data = {'user_id': user, 'password': pwd... | 个人中心 | CentralPersonalInfo | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CentralPersonalInfo:
"""个人中心"""
def duty_info(self):
"""个人信息"""
<|body_0|>
def handOverCentralDuty(self, user, pwd):
"""中央收费处交接班"""
<|body_1|>
def centralOffDuty(self):
"""中央收费处下班"""
<|body_2|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_021966 | 988 | no_license | [
{
"docstring": "个人信息",
"name": "duty_info",
"signature": "def duty_info(self)"
},
{
"docstring": "中央收费处交接班",
"name": "handOverCentralDuty",
"signature": "def handOverCentralDuty(self, user, pwd)"
},
{
"docstring": "中央收费处下班",
"name": "centralOffDuty",
"signature": "def cen... | 3 | stack_v2_sparse_classes_30k_train_007127 | Implement the Python class `CentralPersonalInfo` described below.
Class description:
个人中心
Method signatures and docstrings:
- def duty_info(self): 个人信息
- def handOverCentralDuty(self, user, pwd): 中央收费处交接班
- def centralOffDuty(self): 中央收费处下班 | Implement the Python class `CentralPersonalInfo` described below.
Class description:
个人中心
Method signatures and docstrings:
- def duty_info(self): 个人信息
- def handOverCentralDuty(self, user, pwd): 中央收费处交接班
- def centralOffDuty(self): 中央收费处下班
<|skeleton|>
class CentralPersonalInfo:
"""个人中心"""
def duty_info(se... | 34c368c109867da26d9256bca85f872b0fac2ea7 | <|skeleton|>
class CentralPersonalInfo:
"""个人中心"""
def duty_info(self):
"""个人信息"""
<|body_0|>
def handOverCentralDuty(self, user, pwd):
"""中央收费处交接班"""
<|body_1|>
def centralOffDuty(self):
"""中央收费处下班"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CentralPersonalInfo:
"""个人中心"""
def duty_info(self):
"""个人信息"""
self.url = '/ydtp-backend-service/api/central/duty_info'
re = self.get(url=self.zby_api, headers=form_headers)
return re.json()
def handOverCentralDuty(self, user, pwd):
"""中央收费处交接班"""
sel... | the_stack_v2_python_sparse | Api/centralTollCollection_service/centralPersonalInfo.py | oyebino/pomp_api | train | 1 |
1ae74b7040b53eac06642d2bfb15618f68ba8725 | [
"if isinstance(value, Integral):\n return value\nraise TypeError",
"if value is None:\n return None\nelse:\n try:\n return int(value)\n except:\n try:\n return long(value)\n except:\n raise TypeError"
] | <|body_start_0|>
if isinstance(value, Integral):
return value
raise TypeError
<|end_body_0|>
<|body_start_1|>
if value is None:
return None
else:
try:
return int(value)
except:
try:
retur... | 处理 int(long) 类型值的转换。 | IntTypeCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IntTypeCase:
"""处理 int(long) 类型值的转换。"""
def to_redis(value):
"""接受 int 类型值，否则抛出 TypeError 。"""
<|body_0|>
def to_python(value):
"""尝试将值转回 int 类型， 如果转换失败，抛出 TypeError。"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if isinstance(value, Integral)... | stack_v2_sparse_classes_36k_train_021967 | 753 | no_license | [
{
"docstring": "接受 int 类型值，否则抛出 TypeError 。",
"name": "to_redis",
"signature": "def to_redis(value)"
},
{
"docstring": "尝试将值转回 int 类型， 如果转换失败，抛出 TypeError。",
"name": "to_python",
"signature": "def to_python(value)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000342 | Implement the Python class `IntTypeCase` described below.
Class description:
处理 int(long) 类型值的转换。
Method signatures and docstrings:
- def to_redis(value): 接受 int 类型值，否则抛出 TypeError 。
- def to_python(value): 尝试将值转回 int 类型， 如果转换失败，抛出 TypeError。 | Implement the Python class `IntTypeCase` described below.
Class description:
处理 int(long) 类型值的转换。
Method signatures and docstrings:
- def to_redis(value): 接受 int 类型值，否则抛出 TypeError 。
- def to_python(value): 尝试将值转回 int 类型， 如果转换失败，抛出 TypeError。
<|skeleton|>
class IntTypeCase:
"""处理 int(long) 类型值的转换。"""
def to... | f9fb551afbf47aaca7cdeba8b64a32d2fe3e30d6 | <|skeleton|>
class IntTypeCase:
"""处理 int(long) 类型值的转换。"""
def to_redis(value):
"""接受 int 类型值，否则抛出 TypeError 。"""
<|body_0|>
def to_python(value):
"""尝试将值转回 int 类型， 如果转换失败，抛出 TypeError。"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class IntTypeCase:
"""处理 int(long) 类型值的转换。"""
def to_redis(value):
"""接受 int 类型值，否则抛出 TypeError 。"""
if isinstance(value, Integral):
return value
raise TypeError
def to_python(value):
"""尝试将值转回 int 类型， 如果转换失败，抛出 TypeError。"""
if value is None:
... | the_stack_v2_python_sparse | mysite/base/ooredis/type_case/int_type_case.py | RockyLiys/erp | train | 1 |
7f02a712bd24ffc1fc9155af5a78881d76225f18 | [
"self.agent_upgrade_task = agent_upgrade_task\nself.analysis_task = analysis_task\nself.backup_task = backup_task\nself.bulk_install_app_task = bulk_install_app_task\nself.clone_task = clone_task\nself.created_time_secs = created_time_secs\nself.description = description\nself.dismissed = dismissed\nself.dismissed_... | <|body_start_0|>
self.agent_upgrade_task = agent_upgrade_task
self.analysis_task = analysis_task
self.backup_task = backup_task
self.bulk_install_app_task = bulk_install_app_task
self.clone_task = clone_task
self.created_time_secs = created_time_secs
self.descript... | Implementation of the 'TaskNotification' model. Structure that captures Task Notifications for a user. Attributes: agent_upgrade_task (AgentUpgradeTaskInfo): The notification details of Agent upgrade Task. analysis_task (AnalysisTaskInfo): The notifications details of Analysis Task. backup_task (BackupTaskInfo): The no... | TaskNotification | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TaskNotification:
"""Implementation of the 'TaskNotification' model. Structure that captures Task Notifications for a user. Attributes: agent_upgrade_task (AgentUpgradeTaskInfo): The notification details of Agent upgrade Task. analysis_task (AnalysisTaskInfo): The notifications details of Analysi... | stack_v2_sparse_classes_36k_train_021968 | 8,762 | permissive | [
{
"docstring": "Constructor for the TaskNotification class",
"name": "__init__",
"signature": "def __init__(self, agent_upgrade_task=None, analysis_task=None, backup_task=None, bulk_install_app_task=None, clone_task=None, created_time_secs=None, description=None, dismissed=None, dismissed_time_secs=None... | 2 | stack_v2_sparse_classes_30k_val_000934 | Implement the Python class `TaskNotification` described below.
Class description:
Implementation of the 'TaskNotification' model. Structure that captures Task Notifications for a user. Attributes: agent_upgrade_task (AgentUpgradeTaskInfo): The notification details of Agent upgrade Task. analysis_task (AnalysisTaskInfo... | Implement the Python class `TaskNotification` described below.
Class description:
Implementation of the 'TaskNotification' model. Structure that captures Task Notifications for a user. Attributes: agent_upgrade_task (AgentUpgradeTaskInfo): The notification details of Agent upgrade Task. analysis_task (AnalysisTaskInfo... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class TaskNotification:
"""Implementation of the 'TaskNotification' model. Structure that captures Task Notifications for a user. Attributes: agent_upgrade_task (AgentUpgradeTaskInfo): The notification details of Agent upgrade Task. analysis_task (AnalysisTaskInfo): The notifications details of Analysi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TaskNotification:
"""Implementation of the 'TaskNotification' model. Structure that captures Task Notifications for a user. Attributes: agent_upgrade_task (AgentUpgradeTaskInfo): The notification details of Agent upgrade Task. analysis_task (AnalysisTaskInfo): The notifications details of Analysis Task. backu... | the_stack_v2_python_sparse | cohesity_management_sdk/models/task_notification.py | cohesity/management-sdk-python | train | 24 |
363aab6d0afd1376016ecf93c5e464ad36fe97f9 | [
"retDataSet = []\nfor featVec in dataSet:\n if featVec[axis] == value:\n reducedFeatVec = featVec[:axis]\n reducedFeatVec.extend(featVec[axis + 1:])\n retDataSet.append(reducedFeatVec)\nreturn retDataSet",
"numFeatures = len(dataSet[0]) - 1\nbaseEntropy = ShannonEnt().calcShannonEnt(dataSe... | <|body_start_0|>
retDataSet = []
for featVec in dataSet:
if featVec[axis] == value:
reducedFeatVec = featVec[:axis]
reducedFeatVec.extend(featVec[axis + 1:])
retDataSet.append(reducedFeatVec)
return retDataSet
<|end_body_0|>
<|body_sta... | DecisionEnt | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DecisionEnt:
def splitDataSet(dataSet, axis, value):
"""按照给定特征划分数据集 :param dataSet: 待划分的数据集 :param axis: 划分数据集的特征 如：0 :param value: 特征的返回值 如：0 结果是第一个字符为0的各个子列表 :return:"""
<|body_0|>
def chooseBestFeatureToSplit(self, dataSet):
"""选择最优特征， Gain(D,g) = Ent(D) - SUM(|Dv... | stack_v2_sparse_classes_36k_train_021969 | 9,864 | no_license | [
{
"docstring": "按照给定特征划分数据集 :param dataSet: 待划分的数据集 :param axis: 划分数据集的特征 如：0 :param value: 特征的返回值 如：0 结果是第一个字符为0的各个子列表 :return:",
"name": "splitDataSet",
"signature": "def splitDataSet(dataSet, axis, value)"
},
{
"docstring": "选择最优特征， Gain(D,g) = Ent(D) - SUM(|Dv|/|D|)*Ent(Dv) :param dataSet: 数... | 4 | stack_v2_sparse_classes_30k_train_000658 | Implement the Python class `DecisionEnt` described below.
Class description:
Implement the DecisionEnt class.
Method signatures and docstrings:
- def splitDataSet(dataSet, axis, value): 按照给定特征划分数据集 :param dataSet: 待划分的数据集 :param axis: 划分数据集的特征 如：0 :param value: 特征的返回值 如：0 结果是第一个字符为0的各个子列表 :return:
- def chooseBestFea... | Implement the Python class `DecisionEnt` described below.
Class description:
Implement the DecisionEnt class.
Method signatures and docstrings:
- def splitDataSet(dataSet, axis, value): 按照给定特征划分数据集 :param dataSet: 待划分的数据集 :param axis: 划分数据集的特征 如：0 :param value: 特征的返回值 如：0 结果是第一个字符为0的各个子列表 :return:
- def chooseBestFea... | 42b82bab46e00dfbdd6b66a3581f35d62f12d3de | <|skeleton|>
class DecisionEnt:
def splitDataSet(dataSet, axis, value):
"""按照给定特征划分数据集 :param dataSet: 待划分的数据集 :param axis: 划分数据集的特征 如：0 :param value: 特征的返回值 如：0 结果是第一个字符为0的各个子列表 :return:"""
<|body_0|>
def chooseBestFeatureToSplit(self, dataSet):
"""选择最优特征， Gain(D,g) = Ent(D) - SUM(|Dv... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DecisionEnt:
def splitDataSet(dataSet, axis, value):
"""按照给定特征划分数据集 :param dataSet: 待划分的数据集 :param axis: 划分数据集的特征 如：0 :param value: 特征的返回值 如：0 结果是第一个字符为0的各个子列表 :return:"""
retDataSet = []
for featVec in dataSet:
if featVec[axis] == value:
reducedFeatVec = fe... | the_stack_v2_python_sparse | 决策树/DecisionTree/ShannonEntropy.py | LiuX666/Machin_learning | train | 0 | |
058247bfe20f7d32a0080121ecf6f7fe92003dc0 | [
"my_grid = grid_setup(self.rp, ng=4)\nmy_data = fv.FV2d(my_grid)\nbc = bc_setup(self.rp)[0]\nmy_data.register_var('density', bc)\nmy_data.create()\nself.cc_data = my_data\nif self.rp.get_param('particles.do_particles') == 1:\n n_particles = self.rp.get_param('particles.n_particles')\n particle_generator = sel... | <|body_start_0|>
my_grid = grid_setup(self.rp, ng=4)
my_data = fv.FV2d(my_grid)
bc = bc_setup(self.rp)[0]
my_data.register_var('density', bc)
my_data.create()
self.cc_data = my_data
if self.rp.get_param('particles.do_particles') == 1:
n_particles = sel... | Simulation | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Simulation:
def initialize(self):
"""Initialize the grid and variables for advection and set the initial conditions for the chosen problem."""
<|body_0|>
def substep(self, myd):
"""take a single substep in the RK timestepping starting with the conservative state defi... | stack_v2_sparse_classes_36k_train_021970 | 1,846 | permissive | [
{
"docstring": "Initialize the grid and variables for advection and set the initial conditions for the chosen problem.",
"name": "initialize",
"signature": "def initialize(self)"
},
{
"docstring": "take a single substep in the RK timestepping starting with the conservative state defined as part ... | 2 | null | Implement the Python class `Simulation` described below.
Class description:
Implement the Simulation class.
Method signatures and docstrings:
- def initialize(self): Initialize the grid and variables for advection and set the initial conditions for the chosen problem.
- def substep(self, myd): take a single substep i... | Implement the Python class `Simulation` described below.
Class description:
Implement the Simulation class.
Method signatures and docstrings:
- def initialize(self): Initialize the grid and variables for advection and set the initial conditions for the chosen problem.
- def substep(self, myd): take a single substep i... | f91789a319caa98dfbc3f496e9953756e6ee3ca9 | <|skeleton|>
class Simulation:
def initialize(self):
"""Initialize the grid and variables for advection and set the initial conditions for the chosen problem."""
<|body_0|>
def substep(self, myd):
"""take a single substep in the RK timestepping starting with the conservative state defi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Simulation:
def initialize(self):
"""Initialize the grid and variables for advection and set the initial conditions for the chosen problem."""
my_grid = grid_setup(self.rp, ng=4)
my_data = fv.FV2d(my_grid)
bc = bc_setup(self.rp)[0]
my_data.register_var('density', bc)
... | the_stack_v2_python_sparse | pyro/advection_fv4/simulation.py | python-hydro/pyro2 | train | 202 | |
e57bcd00437420e1587ad9161c5f0376240d42d8 | [
"ans = [[]]\nfor n in nums:\n new_ans = []\n for l in ans:\n for i in range(len(l) + 1):\n new_ans.append(l[:i] + [n] + l[i:])\n print(i, l, new_ans)\n if i < len(l) and l[i] == n:\n print('skip')\n break\n ans = new_ans\nreturn ans",
... | <|body_start_0|>
ans = [[]]
for n in nums:
new_ans = []
for l in ans:
for i in range(len(l) + 1):
new_ans.append(l[:i] + [n] + l[i:])
print(i, l, new_ans)
if i < len(l) and l[i] == n:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def permuteUnique(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def permuteUnique(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ans = [[]]
... | stack_v2_sparse_classes_36k_train_021971 | 2,807 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "permuteUnique",
"signature": "def permuteUnique(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "permuteUnique",
"signature": "def permuteUnique(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019370 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def permuteUnique(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def permuteUnique(self, nums): :type nums: List[int] :rtype: List[List[int]] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def permuteUnique(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def permuteUnique(self, nums): :type nums: List[int] :rtype: List[List[int]]
<|skeleton|>
class So... | f3fc71f344cd758cfce77f16ab72992c99ab288e | <|skeleton|>
class Solution:
def permuteUnique(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def permuteUnique(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def permuteUnique(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
ans = [[]]
for n in nums:
new_ans = []
for l in ans:
for i in range(len(l) + 1):
new_ans.append(l[:i] + [n] + l[i:])
... | the_stack_v2_python_sparse | 47_permutations2.py | jennyChing/leetCode | train | 2 | |
84123323e36d291c029dfec05bf31edac7ee1d2a | [
"self.SetStartDate(month=10, day=8, year=2013)\nself.SetEndDate(month=10, day=17, year=2013)\nself.SetCash(startingCash=100000)\nif self.StartDate.year != 2013 or self.StartDate.month != 10 or self.StartDate.day != 8:\n raise AssertionError(f'Start date was incorrect! Expected 10/8/2013 Recieved {self.StartDate}... | <|body_start_0|>
self.SetStartDate(month=10, day=8, year=2013)
self.SetEndDate(month=10, day=17, year=2013)
self.SetCash(startingCash=100000)
if self.StartDate.year != 2013 or self.StartDate.month != 10 or self.StartDate.day != 8:
raise AssertionError(f'Start date was incorre... | Regression algorithm that makes use of PythonNet kwargs | NamedArgumentsRegression | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NamedArgumentsRegression:
"""Regression algorithm that makes use of PythonNet kwargs"""
def Initialize(self):
"""Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized."""
<|body_0|>
def On... | stack_v2_sparse_classes_36k_train_021972 | 2,980 | permissive | [
{
"docstring": "Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.",
"name": "Initialize",
"signature": "def Initialize(self)"
},
{
"docstring": "OnData event is the primary entry point for your algorithm. Eac... | 2 | null | Implement the Python class `NamedArgumentsRegression` described below.
Class description:
Regression algorithm that makes use of PythonNet kwargs
Method signatures and docstrings:
- def Initialize(self): Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algor... | Implement the Python class `NamedArgumentsRegression` described below.
Class description:
Regression algorithm that makes use of PythonNet kwargs
Method signatures and docstrings:
- def Initialize(self): Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algor... | b33dd3bc140e14b883f39ecf848a793cf7292277 | <|skeleton|>
class NamedArgumentsRegression:
"""Regression algorithm that makes use of PythonNet kwargs"""
def Initialize(self):
"""Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized."""
<|body_0|>
def On... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NamedArgumentsRegression:
"""Regression algorithm that makes use of PythonNet kwargs"""
def Initialize(self):
"""Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized."""
self.SetStartDate(month=10, day=8, ... | the_stack_v2_python_sparse | Algorithm.Python/NamedArgumentsRegression.py | Capnode/Algoloop | train | 87 |
b2b57eae3dd6257e454da629dc88a142b8609890 | [
"token = {'email': email, 'operation': operation, 'key': key}\nif more:\n if not isinstance(more, types.DictType):\n raise TypeError('Expecting a dict')\n token.update(more)\nreturn base64.b64encode(json.dumps(token))",
"try:\n confirm_data = json.loads(base64.b64decode(token))\n try:\n ... | <|body_start_0|>
token = {'email': email, 'operation': operation, 'key': key}
if more:
if not isinstance(more, types.DictType):
raise TypeError('Expecting a dict')
token.update(more)
return base64.b64encode(json.dumps(token))
<|end_body_0|>
<|body_start_1... | Response status codes. | ConfirmationToken | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConfirmationToken:
"""Response status codes."""
def generate(email, operation, key, more=None):
"""Returns a Base64 encoded string containing the confirmation data."""
<|body_0|>
def process(token):
"""Process confirmation token and, if valid, extract respective ... | stack_v2_sparse_classes_36k_train_021973 | 2,194 | permissive | [
{
"docstring": "Returns a Base64 encoded string containing the confirmation data.",
"name": "generate",
"signature": "def generate(email, operation, key, more=None)"
},
{
"docstring": "Process confirmation token and, if valid, extract respective info.",
"name": "process",
"signature": "d... | 2 | stack_v2_sparse_classes_30k_train_006083 | Implement the Python class `ConfirmationToken` described below.
Class description:
Response status codes.
Method signatures and docstrings:
- def generate(email, operation, key, more=None): Returns a Base64 encoded string containing the confirmation data.
- def process(token): Process confirmation token and, if valid... | Implement the Python class `ConfirmationToken` described below.
Class description:
Response status codes.
Method signatures and docstrings:
- def generate(email, operation, key, more=None): Returns a Base64 encoded string containing the confirmation data.
- def process(token): Process confirmation token and, if valid... | 0df3033320619d787aab6c81c8445bdd9fb58a9b | <|skeleton|>
class ConfirmationToken:
"""Response status codes."""
def generate(email, operation, key, more=None):
"""Returns a Base64 encoded string containing the confirmation data."""
<|body_0|>
def process(token):
"""Process confirmation token and, if valid, extract respective ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConfirmationToken:
"""Response status codes."""
def generate(email, operation, key, more=None):
"""Returns a Base64 encoded string containing the confirmation data."""
token = {'email': email, 'operation': operation, 'key': key}
if more:
if not isinstance(more, types.D... | the_stack_v2_python_sparse | yaccounts/utils.py | andrecrt/django-yaccounts | train | 0 |
3b0401d4e87768b1f6e20eb4f30eefb933cefd9e | [
"self.function = function\nself.var = var\nself.finite_support = np.isfinite(support)\nself.support = support / np.sqrt(self.var)",
"if self.finite_support:\n return self.support * bw\nelse:\n\n def f(x):\n return self.evaluate(x, bw=bw) - atol\n try:\n xtol = 0.001\n ans = brentq(f,... | <|body_start_0|>
self.function = function
self.var = var
self.finite_support = np.isfinite(support)
self.support = support / np.sqrt(self.var)
<|end_body_0|>
<|body_start_1|>
if self.finite_support:
return self.support * bw
else:
def f(x):
... | Kernel | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Kernel:
def __init__(self, function, var=1, support=3):
"""Initialize a new kernel function. function: callable, numpy.arr -> numpy.arr, should integrate to 1 expected_value : peak, typically 0 support: support of the function. Example ------- >>> from scipy.special import gamma >>> # No... | stack_v2_sparse_classes_36k_train_021974 | 10,297 | permissive | [
{
"docstring": "Initialize a new kernel function. function: callable, numpy.arr -> numpy.arr, should integrate to 1 expected_value : peak, typically 0 support: support of the function. Example ------- >>> from scipy.special import gamma >>> # Normalized function of x >>> def exp(x, dims=1): ... normalization = ... | 3 | stack_v2_sparse_classes_30k_train_002831 | Implement the Python class `Kernel` described below.
Class description:
Implement the Kernel class.
Method signatures and docstrings:
- def __init__(self, function, var=1, support=3): Initialize a new kernel function. function: callable, numpy.arr -> numpy.arr, should integrate to 1 expected_value : peak, typically 0... | Implement the Python class `Kernel` described below.
Class description:
Implement the Kernel class.
Method signatures and docstrings:
- def __init__(self, function, var=1, support=3): Initialize a new kernel function. function: callable, numpy.arr -> numpy.arr, should integrate to 1 expected_value : peak, typically 0... | 0f7611ee2f7d534b68dd36c8c34900f100e9a8c7 | <|skeleton|>
class Kernel:
def __init__(self, function, var=1, support=3):
"""Initialize a new kernel function. function: callable, numpy.arr -> numpy.arr, should integrate to 1 expected_value : peak, typically 0 support: support of the function. Example ------- >>> from scipy.special import gamma >>> # No... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Kernel:
def __init__(self, function, var=1, support=3):
"""Initialize a new kernel function. function: callable, numpy.arr -> numpy.arr, should integrate to 1 expected_value : peak, typically 0 support: support of the function. Example ------- >>> from scipy.special import gamma >>> # Normalized funct... | the_stack_v2_python_sparse | KDEpy/kernel_funcs.py | tommyod/KDEpy | train | 502 | |
5128d21897591fcb97daa2913be1c0a109d8c41e | [
"res = super(ProductConfigSession, self).get_session_search_domain(product_tmpl_id=product_tmpl_id, state=state, parent_id=parent_id)\nif 'website_id' in self._context:\n public_user_id = request.env.ref('base.public_user').id\n res.append(('website', '=', True))\n if request.env.uid == public_user_id:\n ... | <|body_start_0|>
res = super(ProductConfigSession, self).get_session_search_domain(product_tmpl_id=product_tmpl_id, state=state, parent_id=parent_id)
if 'website_id' in self._context:
public_user_id = request.env.ref('base.public_user').id
res.append(('website', '=', True))
... | ProductConfigSession | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProductConfigSession:
def get_session_search_domain(self, product_tmpl_id, state='draft', parent_id=None):
"""Add website relevant arguments to the standard search domain"""
<|body_0|>
def get_session_vals(self, product_tmpl_id, parent_id=None):
"""Add website releva... | stack_v2_sparse_classes_36k_train_021975 | 2,409 | no_license | [
{
"docstring": "Add website relevant arguments to the standard search domain",
"name": "get_session_search_domain",
"signature": "def get_session_search_domain(self, product_tmpl_id, state='draft', parent_id=None)"
},
{
"docstring": "Add website relevant arguments to the session create values",
... | 2 | stack_v2_sparse_classes_30k_train_005980 | Implement the Python class `ProductConfigSession` described below.
Class description:
Implement the ProductConfigSession class.
Method signatures and docstrings:
- def get_session_search_domain(self, product_tmpl_id, state='draft', parent_id=None): Add website relevant arguments to the standard search domain
- def ge... | Implement the Python class `ProductConfigSession` described below.
Class description:
Implement the ProductConfigSession class.
Method signatures and docstrings:
- def get_session_search_domain(self, product_tmpl_id, state='draft', parent_id=None): Add website relevant arguments to the standard search domain
- def ge... | 5a235827896e6d7bff420f85228d7609715a2efb | <|skeleton|>
class ProductConfigSession:
def get_session_search_domain(self, product_tmpl_id, state='draft', parent_id=None):
"""Add website relevant arguments to the standard search domain"""
<|body_0|>
def get_session_vals(self, product_tmpl_id, parent_id=None):
"""Add website releva... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProductConfigSession:
def get_session_search_domain(self, product_tmpl_id, state='draft', parent_id=None):
"""Add website relevant arguments to the standard search domain"""
res = super(ProductConfigSession, self).get_session_search_domain(product_tmpl_id=product_tmpl_id, state=state, parent_i... | the_stack_v2_python_sparse | website_product_configurator/models/product_config.py | AULODE/somafish_2019 | train | 1 | |
e1503bdc515cff30f2d36cedff0c87f37cd12b73 | [
"Bar.__init__(self, w, h)\nself.character = character\nself._colour = MP_BLUE",
"self._base.fill(DARK_PURPLE)\nratio = self.character.curr_mp / self.character.max_mp\nnew_w = int(ratio * self._w)\nself._top = pg.Surface((new_w, self._h))\nself._top.fill(self._colour)"
] | <|body_start_0|>
Bar.__init__(self, w, h)
self.character = character
self._colour = MP_BLUE
<|end_body_0|>
<|body_start_1|>
self._base.fill(DARK_PURPLE)
ratio = self.character.curr_mp / self.character.max_mp
new_w = int(ratio * self._w)
self._top = pg.Surface((ne... | Class for drawing party members' MP bars in battle. | MPBar | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MPBar:
"""Class for drawing party members' MP bars in battle."""
def __init__(self, w, h, character):
"""Class constructor for MP bars. args: character: Character object; specifies the character associated with the bar colour: colour tuple; colour of the bar"""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_021976 | 3,427 | no_license | [
{
"docstring": "Class constructor for MP bars. args: character: Character object; specifies the character associated with the bar colour: colour tuple; colour of the bar",
"name": "__init__",
"signature": "def __init__(self, w, h, character)"
},
{
"docstring": "Updates the bar based on current M... | 2 | stack_v2_sparse_classes_30k_train_002967 | Implement the Python class `MPBar` described below.
Class description:
Class for drawing party members' MP bars in battle.
Method signatures and docstrings:
- def __init__(self, w, h, character): Class constructor for MP bars. args: character: Character object; specifies the character associated with the bar colour: ... | Implement the Python class `MPBar` described below.
Class description:
Class for drawing party members' MP bars in battle.
Method signatures and docstrings:
- def __init__(self, w, h, character): Class constructor for MP bars. args: character: Character object; specifies the character associated with the bar colour: ... | e86420c145c1d929649ac5d4c98a4d1b75e218a7 | <|skeleton|>
class MPBar:
"""Class for drawing party members' MP bars in battle."""
def __init__(self, w, h, character):
"""Class constructor for MP bars. args: character: Character object; specifies the character associated with the bar colour: colour tuple; colour of the bar"""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MPBar:
"""Class for drawing party members' MP bars in battle."""
def __init__(self, w, h, character):
"""Class constructor for MP bars. args: character: Character object; specifies the character associated with the bar colour: colour tuple; colour of the bar"""
Bar.__init__(self, w, h)
... | the_stack_v2_python_sparse | src/entities/bar.py | nuclearkittens/ot-projekti | train | 0 |
fe6f208cddc84bea8d5bca52e0bc3c6d2764cfcc | [
"tests = ['KIF.test1', 'KIF.test2']\nexpected = 'NAME:test1|test2'\nself.assertEqual(test_runner.get_kif_test_filter(tests), expected)",
"tests = ['KIF.test1', 'KIF.test2']\nexpected = '-NAME:test1|test2'\nself.assertEqual(test_runner.get_kif_test_filter(tests, invert=True), expected)"
] | <|body_start_0|>
tests = ['KIF.test1', 'KIF.test2']
expected = 'NAME:test1|test2'
self.assertEqual(test_runner.get_kif_test_filter(tests), expected)
<|end_body_0|>
<|body_start_1|>
tests = ['KIF.test1', 'KIF.test2']
expected = '-NAME:test1|test2'
self.assertEqual(test_ru... | Tests for test_runner.get_kif_test_filter. | GetKIFTestFilterTest | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetKIFTestFilterTest:
"""Tests for test_runner.get_kif_test_filter."""
def test_correct(self):
"""Ensures correctness of filter."""
<|body_0|>
def test_correct_inverted(self):
"""Ensures correctness of inverted filter."""
<|body_1|>
<|end_skeleton|>
<|b... | stack_v2_sparse_classes_36k_train_021977 | 19,298 | permissive | [
{
"docstring": "Ensures correctness of filter.",
"name": "test_correct",
"signature": "def test_correct(self)"
},
{
"docstring": "Ensures correctness of inverted filter.",
"name": "test_correct_inverted",
"signature": "def test_correct_inverted(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003809 | Implement the Python class `GetKIFTestFilterTest` described below.
Class description:
Tests for test_runner.get_kif_test_filter.
Method signatures and docstrings:
- def test_correct(self): Ensures correctness of filter.
- def test_correct_inverted(self): Ensures correctness of inverted filter. | Implement the Python class `GetKIFTestFilterTest` described below.
Class description:
Tests for test_runner.get_kif_test_filter.
Method signatures and docstrings:
- def test_correct(self): Ensures correctness of filter.
- def test_correct_inverted(self): Ensures correctness of inverted filter.
<|skeleton|>
class Get... | 4896f732fc747dfdcfcbac3d442f2d2d42df264a | <|skeleton|>
class GetKIFTestFilterTest:
"""Tests for test_runner.get_kif_test_filter."""
def test_correct(self):
"""Ensures correctness of filter."""
<|body_0|>
def test_correct_inverted(self):
"""Ensures correctness of inverted filter."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GetKIFTestFilterTest:
"""Tests for test_runner.get_kif_test_filter."""
def test_correct(self):
"""Ensures correctness of filter."""
tests = ['KIF.test1', 'KIF.test2']
expected = 'NAME:test1|test2'
self.assertEqual(test_runner.get_kif_test_filter(tests), expected)
def ... | the_stack_v2_python_sparse | ios/build/bots/scripts/test_runner_test.py | Samsung/Castanets | train | 58 |
a6f8effbb72cbea1226d1c5b87cb71ab79e3bea4 | [
"inputs, outputs = equation.split('->')\ninput_dims, output_dims = (inputs.split(','), outputs.split(','))\nassert len(input_dims) <= 2, 'Only support at most two inputs'\nassert len(output_dims) == 1, 'Only support single output'\noutput_dim = output_dims[0]\nreturn (input_dims, output_dim)",
"dim_char_set = set... | <|body_start_0|>
inputs, outputs = equation.split('->')
input_dims, output_dims = (inputs.split(','), outputs.split(','))
assert len(input_dims) <= 2, 'Only support at most two inputs'
assert len(output_dims) == 1, 'Only support single output'
output_dim = output_dims[0]
... | EinsumDims | [
"BSD-3-Clause",
"BSD-2-Clause",
"LicenseRef-scancode-secret-labs-2011",
"LicenseRef-scancode-generic-cla",
"BSL-1.0",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EinsumDims:
def parse_equation(cls, equation: str) -> Tuple[List[str], str]:
"""Parse the einsum equation str to input dim chars and output dim char"""
<|body_0|>
def parse_dims(cls, input_dims: List[str], output_dim: str) -> 'EinsumDims':
"""Parse the dims and extra... | stack_v2_sparse_classes_36k_train_021978 | 6,665 | permissive | [
{
"docstring": "Parse the einsum equation str to input dim chars and output dim char",
"name": "parse_equation",
"signature": "def parse_equation(cls, equation: str) -> Tuple[List[str], str]"
},
{
"docstring": "Parse the dims and extract the contracting, batch, and free dimensions for the left a... | 2 | stack_v2_sparse_classes_30k_train_002888 | Implement the Python class `EinsumDims` described below.
Class description:
Implement the EinsumDims class.
Method signatures and docstrings:
- def parse_equation(cls, equation: str) -> Tuple[List[str], str]: Parse the einsum equation str to input dim chars and output dim char
- def parse_dims(cls, input_dims: List[s... | Implement the Python class `EinsumDims` described below.
Class description:
Implement the EinsumDims class.
Method signatures and docstrings:
- def parse_equation(cls, equation: str) -> Tuple[List[str], str]: Parse the einsum equation str to input dim chars and output dim char
- def parse_dims(cls, input_dims: List[s... | a6f7dd4707ac116c0f5fb5f44f42429f38d23ab4 | <|skeleton|>
class EinsumDims:
def parse_equation(cls, equation: str) -> Tuple[List[str], str]:
"""Parse the einsum equation str to input dim chars and output dim char"""
<|body_0|>
def parse_dims(cls, input_dims: List[str], output_dim: str) -> 'EinsumDims':
"""Parse the dims and extra... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EinsumDims:
def parse_equation(cls, equation: str) -> Tuple[List[str], str]:
"""Parse the einsum equation str to input dim chars and output dim char"""
inputs, outputs = equation.split('->')
input_dims, output_dims = (inputs.split(','), outputs.split(','))
assert len(input_dims... | the_stack_v2_python_sparse | torch/distributed/_tensor/ops/basic_strategy.py | pytorch/pytorch | train | 77,092 | |
7c1c547e719c3209dd5e08480cf91d5339a48537 | [
"self.driver.get('https://work.weixin.qq.com/wework_admin/frame#apps')\ncookies = self.driver.get_cookies()\nwith shelve.open('cookies') as db:\n db['cookie'] = cookies\nfor cookie in cookies:\n self.driver.add_cookie(cookie)\nself.driver.refresh()",
"cookies = []\nwith shelve.open('cookies') as db:\n db... | <|body_start_0|>
self.driver.get('https://work.weixin.qq.com/wework_admin/frame#apps')
cookies = self.driver.get_cookies()
with shelve.open('cookies') as db:
db['cookie'] = cookies
for cookie in cookies:
self.driver.add_cookie(cookie)
self.driver.refresh()... | TestHgwarts | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestHgwarts:
def test_getCookies(self):
"""获取cookies"""
<|body_0|>
def test_saveCookies(self):
"""保存cookies到shelve中"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.driver.get('https://work.weixin.qq.com/wework_admin/frame#apps')
cookies... | stack_v2_sparse_classes_36k_train_021979 | 1,112 | no_license | [
{
"docstring": "获取cookies",
"name": "test_getCookies",
"signature": "def test_getCookies(self)"
},
{
"docstring": "保存cookies到shelve中",
"name": "test_saveCookies",
"signature": "def test_saveCookies(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_015171 | Implement the Python class `TestHgwarts` described below.
Class description:
Implement the TestHgwarts class.
Method signatures and docstrings:
- def test_getCookies(self): 获取cookies
- def test_saveCookies(self): 保存cookies到shelve中 | Implement the Python class `TestHgwarts` described below.
Class description:
Implement the TestHgwarts class.
Method signatures and docstrings:
- def test_getCookies(self): 获取cookies
- def test_saveCookies(self): 保存cookies到shelve中
<|skeleton|>
class TestHgwarts:
def test_getCookies(self):
"""获取cookies""... | eb3d3aabb8706a0ba649061e5f1aebfb307c5b1d | <|skeleton|>
class TestHgwarts:
def test_getCookies(self):
"""获取cookies"""
<|body_0|>
def test_saveCookies(self):
"""保存cookies到shelve中"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestHgwarts:
def test_getCookies(self):
"""获取cookies"""
self.driver.get('https://work.weixin.qq.com/wework_admin/frame#apps')
cookies = self.driver.get_cookies()
with shelve.open('cookies') as db:
db['cookie'] = cookies
for cookie in cookies:
sel... | the_stack_v2_python_sparse | WebUITest/实战课程/test_case01.py | sunyanfen1995/HGWZ_syf | train | 0 | |
426c05bde6c29282b64aa6bebe82bbd251694892 | [
"if n == 1:\n return 0\nif n == 2:\n return 2\ndp_list = [n for n in range(n + 1)]\ndp_list[1] = 0\nfor i in range(3, n + 1):\n j = 1\n list = []\n while j <= i // 2:\n if i % j == 0:\n list.append(j)\n j += 1\n check_list = []\n for each in list:\n check_list.ap... | <|body_start_0|>
if n == 1:
return 0
if n == 2:
return 2
dp_list = [n for n in range(n + 1)]
dp_list[1] = 0
for i in range(3, n + 1):
j = 1
list = []
while j <= i // 2:
if i % j == 0:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minSteps(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def minSteps2(self, n):
""":type n: int :rtype: int"""
<|body_1|>
def minSteps3(self, n):
""":type n: int :rtype: int"""
<|body_2|>
<|end_skeleton|>
<|body_start... | stack_v2_sparse_classes_36k_train_021980 | 1,290 | no_license | [
{
"docstring": ":type n: int :rtype: int",
"name": "minSteps",
"signature": "def minSteps(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "minSteps2",
"signature": "def minSteps2(self, n)"
},
{
"docstring": ":type n: int :rtype: int",
"name": "minSteps3",
... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minSteps(self, n): :type n: int :rtype: int
- def minSteps2(self, n): :type n: int :rtype: int
- def minSteps3(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 minSteps(self, n): :type n: int :rtype: int
- def minSteps2(self, n): :type n: int :rtype: int
- def minSteps3(self, n): :type n: int :rtype: int
<|skeleton|>
class Solution... | 4105e18050b15fc0409c75353ad31be17187dd34 | <|skeleton|>
class Solution:
def minSteps(self, n):
""":type n: int :rtype: int"""
<|body_0|>
def minSteps2(self, n):
""":type n: int :rtype: int"""
<|body_1|>
def minSteps3(self, n):
""":type n: int :rtype: int"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minSteps(self, n):
""":type n: int :rtype: int"""
if n == 1:
return 0
if n == 2:
return 2
dp_list = [n for n in range(n + 1)]
dp_list[1] = 0
for i in range(3, n + 1):
j = 1
list = []
while... | the_stack_v2_python_sparse | minSteps.py | NeilWangziyu/Leetcode_py | train | 2 | |
e58c19fe5cdd33cd9cab1b8585cf8011a5950bb9 | [
"if len(strs) == 1:\n return strs[0]\nelif len(strs) == 0:\n return ''\nlongest = ''\nsize = 0\nj = 0\nwhile j < len(strs[0]) and j < len(strs[1]):\n if strs[0][j] == strs[1][j]:\n size += 1\n else:\n break\n j += 1\nlongest = strs[0][:size]\nfor i in range(2, len(strs)):\n j = 0\n ... | <|body_start_0|>
if len(strs) == 1:
return strs[0]
elif len(strs) == 0:
return ''
longest = ''
size = 0
j = 0
while j < len(strs[0]) and j < len(strs[1]):
if strs[0][j] == strs[1][j]:
size += 1
else:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestCommonPrefix(self, strs):
""":type strs: List[str] :rtype: str"""
<|body_0|>
def longestCommonPrefix2(self, strs):
"""Vertical scanning algorithm."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(strs) == 1:
re... | stack_v2_sparse_classes_36k_train_021981 | 1,783 | no_license | [
{
"docstring": ":type strs: List[str] :rtype: str",
"name": "longestCommonPrefix",
"signature": "def longestCommonPrefix(self, strs)"
},
{
"docstring": "Vertical scanning algorithm.",
"name": "longestCommonPrefix2",
"signature": "def longestCommonPrefix2(self, strs)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestCommonPrefix(self, strs): :type strs: List[str] :rtype: str
- def longestCommonPrefix2(self, strs): Vertical scanning algorithm. | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestCommonPrefix(self, strs): :type strs: List[str] :rtype: str
- def longestCommonPrefix2(self, strs): Vertical scanning algorithm.
<|skeleton|>
class Solution:
def... | b7e92f9a7c4d6652d4901b189f51063ce5520653 | <|skeleton|>
class Solution:
def longestCommonPrefix(self, strs):
""":type strs: List[str] :rtype: str"""
<|body_0|>
def longestCommonPrefix2(self, strs):
"""Vertical scanning algorithm."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def longestCommonPrefix(self, strs):
""":type strs: List[str] :rtype: str"""
if len(strs) == 1:
return strs[0]
elif len(strs) == 0:
return ''
longest = ''
size = 0
j = 0
while j < len(strs[0]) and j < len(strs[1]):
... | the_stack_v2_python_sparse | leetcode/easy/longest_common_prefix.py | abkunal/Data-Structures-and-Algorithms | train | 2 | |
8d02b1173ee9efcb235d80fa04868c83971d0df3 | [
"super().__init__()\nimport sklearn\nimport sklearn.linear_model\nself.model = sklearn.linear_model.BayesianRidge",
"specs = super(BayesianRidge, cls).getInputSpecification()\nspecs.description = 'The \\\\xmlNode{BayesianRidge} is Bayesian Ridge regression.\\n It estimates a probabilistic m... | <|body_start_0|>
super().__init__()
import sklearn
import sklearn.linear_model
self.model = sklearn.linear_model.BayesianRidge
<|end_body_0|>
<|body_start_1|>
specs = super(BayesianRidge, cls).getInputSpecification()
specs.description = 'The \\xmlNode{BayesianRidge} is B... | Bayesian ARD regression | BayesianRidge | [
"Apache-2.0",
"LicenseRef-scancode-warranty-disclaimer",
"BSD-2-Clause",
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BayesianRidge:
"""Bayesian ARD regression"""
def __init__(self):
"""Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None"""
<|body_0|>
def getInputSpecification(cls):
"""Method to get a reference to a class that speci... | stack_v2_sparse_classes_36k_train_021982 | 7,228 | permissive | [
{
"docstring": "Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Method to get a reference to a class that specifies the input data for class cls. @ In, cls, the class for... | 3 | null | Implement the Python class `BayesianRidge` described below.
Class description:
Bayesian ARD regression
Method signatures and docstrings:
- def __init__(self): Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None
- def getInputSpecification(cls): Method to get a reference ... | Implement the Python class `BayesianRidge` described below.
Class description:
Bayesian ARD regression
Method signatures and docstrings:
- def __init__(self): Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None
- def getInputSpecification(cls): Method to get a reference ... | 2b16e7aa3325fe84cab2477947a951414c635381 | <|skeleton|>
class BayesianRidge:
"""Bayesian ARD regression"""
def __init__(self):
"""Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None"""
<|body_0|>
def getInputSpecification(cls):
"""Method to get a reference to a class that speci... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BayesianRidge:
"""Bayesian ARD regression"""
def __init__(self):
"""Constructor that will appropriately initialize a supervised learning object @ In, None @ Out, None"""
super().__init__()
import sklearn
import sklearn.linear_model
self.model = sklearn.linear_model... | the_stack_v2_python_sparse | ravenframework/SupervisedLearning/ScikitLearn/LinearModel/BayesianRidge.py | idaholab/raven | train | 201 |
a4989dd2ed22b287f2fe0543d3888aa50fbeed93 | [
"query = Exercise.get_query(info)\nif author:\n user = UserModel.find_by_username(author)\n return query.order_by(ExerciseModel.name.desc()).filter(ExerciseModel.author == user.id).all()\nreturn query.all()",
"query = Exercise.get_query(info)\nif id:\n return query.filter(ExerciseModel.id == id).first()\... | <|body_start_0|>
query = Exercise.get_query(info)
if author:
user = UserModel.find_by_username(author)
return query.order_by(ExerciseModel.name.desc()).filter(ExerciseModel.author == user.id).all()
return query.all()
<|end_body_0|>
<|body_start_1|>
query = Exerci... | Query | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Query:
def resolve_exercises(root, info, author=None):
"""Return a list of all exercises. Search by author: A user's username."""
<|body_0|>
def resolve_exercise(root, info, id=None, name=None, desc=None):
"""Return a single exercise by id."""
<|body_1|>
<|e... | stack_v2_sparse_classes_36k_train_021983 | 1,111 | no_license | [
{
"docstring": "Return a list of all exercises. Search by author: A user's username.",
"name": "resolve_exercises",
"signature": "def resolve_exercises(root, info, author=None)"
},
{
"docstring": "Return a single exercise by id.",
"name": "resolve_exercise",
"signature": "def resolve_exe... | 2 | stack_v2_sparse_classes_30k_train_015278 | Implement the Python class `Query` described below.
Class description:
Implement the Query class.
Method signatures and docstrings:
- def resolve_exercises(root, info, author=None): Return a list of all exercises. Search by author: A user's username.
- def resolve_exercise(root, info, id=None, name=None, desc=None): ... | Implement the Python class `Query` described below.
Class description:
Implement the Query class.
Method signatures and docstrings:
- def resolve_exercises(root, info, author=None): Return a list of all exercises. Search by author: A user's username.
- def resolve_exercise(root, info, id=None, name=None, desc=None): ... | f0056da32453fce0a9dece90508fcdcad8cc905b | <|skeleton|>
class Query:
def resolve_exercises(root, info, author=None):
"""Return a list of all exercises. Search by author: A user's username."""
<|body_0|>
def resolve_exercise(root, info, id=None, name=None, desc=None):
"""Return a single exercise by id."""
<|body_1|>
<|e... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Query:
def resolve_exercises(root, info, author=None):
"""Return a list of all exercises. Search by author: A user's username."""
query = Exercise.get_query(info)
if author:
user = UserModel.find_by_username(author)
return query.order_by(ExerciseModel.name.desc(... | the_stack_v2_python_sparse | stronk/schemas/exercise/query.py | not-monday/stronk-backend | train | 3 | |
bac7eb9694e74420e2190ac4dda1dc34118be6d1 | [
"connected_indexes = []\nfor i in reversed(range(0, idx)):\n if row[i] == 1:\n connected_indexes.append(i)\n else:\n break\nfor i in range(idx, len(row)):\n if row[i] == 1:\n connected_indexes.append(i)\n else:\n break\nreturn connected_indexes",
"opens = [i for i in pre_tu... | <|body_start_0|>
connected_indexes = []
for i in reversed(range(0, idx)):
if row[i] == 1:
connected_indexes.append(i)
else:
break
for i in range(idx, len(row)):
if row[i] == 1:
connected_indexes.append(i)
... | Percolation | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Percolation:
def expand_check(self, idx, row):
"""to check the valid tunnel connecting in this row starting from the tunnel point from last tunnel then expand the tunnel to all the indexes that is directly linked to tunnel connecting point"""
<|body_0|>
def isPercolate(self,... | stack_v2_sparse_classes_36k_train_021984 | 3,374 | no_license | [
{
"docstring": "to check the valid tunnel connecting in this row starting from the tunnel point from last tunnel then expand the tunnel to all the indexes that is directly linked to tunnel connecting point",
"name": "expand_check",
"signature": "def expand_check(self, idx, row)"
},
{
"docstring"... | 3 | stack_v2_sparse_classes_30k_train_011188 | Implement the Python class `Percolation` described below.
Class description:
Implement the Percolation class.
Method signatures and docstrings:
- def expand_check(self, idx, row): to check the valid tunnel connecting in this row starting from the tunnel point from last tunnel then expand the tunnel to all the indexes... | Implement the Python class `Percolation` described below.
Class description:
Implement the Percolation class.
Method signatures and docstrings:
- def expand_check(self, idx, row): to check the valid tunnel connecting in this row starting from the tunnel point from last tunnel then expand the tunnel to all the indexes... | 143422321cbc3715ca08f6c3af8f960a55887ced | <|skeleton|>
class Percolation:
def expand_check(self, idx, row):
"""to check the valid tunnel connecting in this row starting from the tunnel point from last tunnel then expand the tunnel to all the indexes that is directly linked to tunnel connecting point"""
<|body_0|>
def isPercolate(self,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Percolation:
def expand_check(self, idx, row):
"""to check the valid tunnel connecting in this row starting from the tunnel point from last tunnel then expand the tunnel to all the indexes that is directly linked to tunnel connecting point"""
connected_indexes = []
for i in reversed(ra... | the_stack_v2_python_sparse | QuickProjects/Algorithm/p01_percolation.py | jxie0755/Learning_Python | train | 0 | |
61d45856e9086d995d36a317c86d342465370442 | [
"assert isinstance(display_fn_name, str), '\"display_fn_name\" must be provided as a string.'\nactive_identifying_session_ctx = self.sess.get_context()\ndisplay_subcontext = IdentifyingContext(display_fn_name=display_fn_name, **kwargs)\nreturn active_identifying_session_ctx.merging_context('display_', display_subco... | <|body_start_0|>
assert isinstance(display_fn_name, str), '"display_fn_name" must be provided as a string.'
active_identifying_session_ctx = self.sess.get_context()
display_subcontext = IdentifyingContext(display_fn_name=display_fn_name, **kwargs)
return active_identifying_session_ctx.me... | provides functionality for saving figures to file. from pyphoplacecellanalysis.General.Pipeline.Stages.Display import PipelineWithDisplaySavingMixin | PipelineWithDisplaySavingMixin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PipelineWithDisplaySavingMixin:
"""provides functionality for saving figures to file. from pyphoplacecellanalysis.General.Pipeline.Stages.Display import PipelineWithDisplaySavingMixin"""
def build_display_context_for_session(self, display_fn_name: str, **kwargs) -> 'IdentifyingContext':
... | stack_v2_sparse_classes_36k_train_021985 | 34,127 | permissive | [
{
"docstring": "builds a new display context for the session out of kwargs Usage: curr_active_pipeline.build_display_context_for_session(display_fn_name='DecodedEpochSlices', epochs='replays', decoder='long_results_obj')",
"name": "build_display_context_for_session",
"signature": "def build_display_cont... | 4 | stack_v2_sparse_classes_30k_train_003857 | Implement the Python class `PipelineWithDisplaySavingMixin` described below.
Class description:
provides functionality for saving figures to file. from pyphoplacecellanalysis.General.Pipeline.Stages.Display import PipelineWithDisplaySavingMixin
Method signatures and docstrings:
- def build_display_context_for_session... | Implement the Python class `PipelineWithDisplaySavingMixin` described below.
Class description:
provides functionality for saving figures to file. from pyphoplacecellanalysis.General.Pipeline.Stages.Display import PipelineWithDisplaySavingMixin
Method signatures and docstrings:
- def build_display_context_for_session... | 212399d826284b394fce8894ff1a93133aef783f | <|skeleton|>
class PipelineWithDisplaySavingMixin:
"""provides functionality for saving figures to file. from pyphoplacecellanalysis.General.Pipeline.Stages.Display import PipelineWithDisplaySavingMixin"""
def build_display_context_for_session(self, display_fn_name: str, **kwargs) -> 'IdentifyingContext':
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PipelineWithDisplaySavingMixin:
"""provides functionality for saving figures to file. from pyphoplacecellanalysis.General.Pipeline.Stages.Display import PipelineWithDisplaySavingMixin"""
def build_display_context_for_session(self, display_fn_name: str, **kwargs) -> 'IdentifyingContext':
"""builds... | the_stack_v2_python_sparse | src/pyphoplacecellanalysis/General/Pipeline/Stages/Display.py | CommanderPho/pyPhoPlaceCellAnalysis | train | 1 |
f74071a4c84e8dbae94651f159150cbbf7475626 | [
"if not t1:\n return t2\nelif not t2:\n return t1\nelse:\n t1.val += t2.val\n t1.left = self.mergeTrees(t1.left, t2.left)\n t1.right = self.mergeTrees(t1.right, t2.right)\n return t1",
"if not t1:\n return t2\nelif not t2:\n return t1\ntraverse_stack = [(t1, t2)]\nwhile traverse_stack:\n ... | <|body_start_0|>
if not t1:
return t2
elif not t2:
return t1
else:
t1.val += t2.val
t1.left = self.mergeTrees(t1.left, t2.left)
t1.right = self.mergeTrees(t1.right, t2.right)
return t1
<|end_body_0|>
<|body_start_1|>
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def mergeTrees(self, t1, t2):
""":type t1: TreeNode :type t2: TreeNode :rtype: TreeNode 时间复杂度: O(n) 空间复杂度: O(n)"""
<|body_0|>
def mergeTreesIter(self, t1, t2):
"""时间复杂度: O(n) 空间复杂度: O(n)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if n... | stack_v2_sparse_classes_36k_train_021986 | 1,793 | no_license | [
{
"docstring": ":type t1: TreeNode :type t2: TreeNode :rtype: TreeNode 时间复杂度: O(n) 空间复杂度: O(n)",
"name": "mergeTrees",
"signature": "def mergeTrees(self, t1, t2)"
},
{
"docstring": "时间复杂度: O(n) 空间复杂度: O(n)",
"name": "mergeTreesIter",
"signature": "def mergeTreesIter(self, t1, t2)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeTrees(self, t1, t2): :type t1: TreeNode :type t2: TreeNode :rtype: TreeNode 时间复杂度: O(n) 空间复杂度: O(n)
- def mergeTreesIter(self, t1, t2): 时间复杂度: O(n) 空间复杂度: O(n) | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeTrees(self, t1, t2): :type t1: TreeNode :type t2: TreeNode :rtype: TreeNode 时间复杂度: O(n) 空间复杂度: O(n)
- def mergeTreesIter(self, t1, t2): 时间复杂度: O(n) 空间复杂度: O(n)
<|skelet... | 8853f85214ac88db024d26e228f1848dd5acd933 | <|skeleton|>
class Solution:
def mergeTrees(self, t1, t2):
""":type t1: TreeNode :type t2: TreeNode :rtype: TreeNode 时间复杂度: O(n) 空间复杂度: O(n)"""
<|body_0|>
def mergeTreesIter(self, t1, t2):
"""时间复杂度: O(n) 空间复杂度: O(n)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def mergeTrees(self, t1, t2):
""":type t1: TreeNode :type t2: TreeNode :rtype: TreeNode 时间复杂度: O(n) 空间复杂度: O(n)"""
if not t1:
return t2
elif not t2:
return t1
else:
t1.val += t2.val
t1.left = self.mergeTrees(t1.left, t2.... | the_stack_v2_python_sparse | 617-MergeTwoBinaryTrees/MergeTwoBinaryTrees.py | cqxmzhc/my_leetcode_solutions | train | 2 | |
3c1a63bb7f983fe9682c749ecd2c5f7c8cafbec9 | [
"if scale not in ('linear', 'log'):\n raise ValueError('invalid parameter scale: %s' % scale)\nself.name = name\nself.min_value = min_value\nself.max_value = max_value\nself.scale = scale",
"if self.scale == 'linear':\n return random.uniform(self.min_value, self.max_value)\nelse:\n log_min_value = math.l... | <|body_start_0|>
if scale not in ('linear', 'log'):
raise ValueError('invalid parameter scale: %s' % scale)
self.name = name
self.min_value = min_value
self.max_value = max_value
self.scale = scale
<|end_body_0|>
<|body_start_1|>
if self.scale == 'linear':
... | An audio transform parameter with min and max value. | AudioTransformParameter | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AudioTransformParameter:
"""An audio transform parameter with min and max value."""
def __init__(self, name, min_value, max_value, scale):
"""Initialize an AudioTransformParameter. Args: name: The name of the parameter. Should be the same as the name of the parameter passed to sox. m... | stack_v2_sparse_classes_36k_train_021987 | 9,154 | permissive | [
{
"docstring": "Initialize an AudioTransformParameter. Args: name: The name of the parameter. Should be the same as the name of the parameter passed to sox. min_value: The minimum value of the parameter, a float. max_value: The maximum value of the parameter, a float. scale: 'linear' or 'log', the scale with wh... | 2 | null | Implement the Python class `AudioTransformParameter` described below.
Class description:
An audio transform parameter with min and max value.
Method signatures and docstrings:
- def __init__(self, name, min_value, max_value, scale): Initialize an AudioTransformParameter. Args: name: The name of the parameter. Should ... | Implement the Python class `AudioTransformParameter` described below.
Class description:
An audio transform parameter with min and max value.
Method signatures and docstrings:
- def __init__(self, name, min_value, max_value, scale): Initialize an AudioTransformParameter. Args: name: The name of the parameter. Should ... | 548dc4e2e6a8e3ac65e1921bd94fe589d661d47b | <|skeleton|>
class AudioTransformParameter:
"""An audio transform parameter with min and max value."""
def __init__(self, name, min_value, max_value, scale):
"""Initialize an AudioTransformParameter. Args: name: The name of the parameter. Should be the same as the name of the parameter passed to sox. m... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AudioTransformParameter:
"""An audio transform parameter with min and max value."""
def __init__(self, name, min_value, max_value, scale):
"""Initialize an AudioTransformParameter. Args: name: The name of the parameter. Should be the same as the name of the parameter passed to sox. min_value: The... | the_stack_v2_python_sparse | magenta/models/onsets_frames_transcription/audio_transform.py | magenta/magenta | train | 4,142 |
15a8faea643011472c446cfaae6fb06ba43d6b87 | [
"hops = validated_data.pop('recipe_hops')\nmalts = validated_data.pop('recipe_malts')\nuser = validated_data.pop('user')\nreturn Recipe.objects.create_recipe(user, validated_data, malts, hops)",
"instance.recipe_name = validated_data.get('recipe_name', instance.recipe_name)\ninstance.recipe_style = validated_data... | <|body_start_0|>
hops = validated_data.pop('recipe_hops')
malts = validated_data.pop('recipe_malts')
user = validated_data.pop('user')
return Recipe.objects.create_recipe(user, validated_data, malts, hops)
<|end_body_0|>
<|body_start_1|>
instance.recipe_name = validated_data.get... | Serialization class for all your yummy recipes. | RecipeSerializer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RecipeSerializer:
"""Serialization class for all your yummy recipes."""
def create(self, validated_data):
"""Create the recipe and all related data"""
<|body_0|>
def update(self, instance, validated_data):
"""Update a recipe. This will clear all previous malts/ho... | stack_v2_sparse_classes_36k_train_021988 | 3,077 | permissive | [
{
"docstring": "Create the recipe and all related data",
"name": "create",
"signature": "def create(self, validated_data)"
},
{
"docstring": "Update a recipe. This will clear all previous malts/hops and replace them with a new list",
"name": "update",
"signature": "def update(self, insta... | 2 | stack_v2_sparse_classes_30k_train_008970 | Implement the Python class `RecipeSerializer` described below.
Class description:
Serialization class for all your yummy recipes.
Method signatures and docstrings:
- def create(self, validated_data): Create the recipe and all related data
- def update(self, instance, validated_data): Update a recipe. This will clear ... | Implement the Python class `RecipeSerializer` described below.
Class description:
Serialization class for all your yummy recipes.
Method signatures and docstrings:
- def create(self, validated_data): Create the recipe and all related data
- def update(self, instance, validated_data): Update a recipe. This will clear ... | 6d0a31f021755425d420394d84aa7250f86f5ebe | <|skeleton|>
class RecipeSerializer:
"""Serialization class for all your yummy recipes."""
def create(self, validated_data):
"""Create the recipe and all related data"""
<|body_0|>
def update(self, instance, validated_data):
"""Update a recipe. This will clear all previous malts/ho... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RecipeSerializer:
"""Serialization class for all your yummy recipes."""
def create(self, validated_data):
"""Create the recipe and all related data"""
hops = validated_data.pop('recipe_hops')
malts = validated_data.pop('recipe_malts')
user = validated_data.pop('user')
... | the_stack_v2_python_sparse | brew_journal/recipies/serializers.py | moonboy13/brew-journal | train | 0 |
e84165a17541cbf3a18d2b082add8111bfb290e9 | [
"unindexed_sentences = SubtitleReader.__get_list_of_sentences(file_path)\nsegments = SubtitleReader.__get_time_stamped_segments(unindexed_sentences, sentences)\nreturn segments",
"f = open(file_path)\nsentences = []\ncurrent_sentence = {}\nfor line in f:\n line.rstrip()\n if re.match('\\\\d{2}:\\\\d{2}:\\\\... | <|body_start_0|>
unindexed_sentences = SubtitleReader.__get_list_of_sentences(file_path)
segments = SubtitleReader.__get_time_stamped_segments(unindexed_sentences, sentences)
return segments
<|end_body_0|>
<|body_start_1|>
f = open(file_path)
sentences = []
current_sente... | Class was created to aid views that need to process srt files in activities such as transcription and shadowing. | SubtitleReader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SubtitleReader:
"""Class was created to aid views that need to process srt files in activities such as transcription and shadowing."""
def read_file(file_path, sentences=False):
"""Processes the file by calling helper function, return a list of timestamped words :param file_path: :pa... | stack_v2_sparse_classes_36k_train_021989 | 4,663 | no_license | [
{
"docstring": "Processes the file by calling helper function, return a list of timestamped words :param file_path: :param sentences: :return:",
"name": "read_file",
"signature": "def read_file(file_path, sentences=False)"
},
{
"docstring": "# Get a list of all the sentences from file and its ti... | 4 | null | Implement the Python class `SubtitleReader` described below.
Class description:
Class was created to aid views that need to process srt files in activities such as transcription and shadowing.
Method signatures and docstrings:
- def read_file(file_path, sentences=False): Processes the file by calling helper function,... | Implement the Python class `SubtitleReader` described below.
Class description:
Class was created to aid views that need to process srt files in activities such as transcription and shadowing.
Method signatures and docstrings:
- def read_file(file_path, sentences=False): Processes the file by calling helper function,... | 174c8c6c9ecb2905830832419e9c332b4d8b13df | <|skeleton|>
class SubtitleReader:
"""Class was created to aid views that need to process srt files in activities such as transcription and shadowing."""
def read_file(file_path, sentences=False):
"""Processes the file by calling helper function, return a list of timestamped words :param file_path: :pa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SubtitleReader:
"""Class was created to aid views that need to process srt files in activities such as transcription and shadowing."""
def read_file(file_path, sentences=False):
"""Processes the file by calling helper function, return a list of timestamped words :param file_path: :param sentences... | the_stack_v2_python_sparse | CreeTutorBackEnd/common_to_apps/subtitle_readers.py | EdTeKLA/Cree-Tutor | train | 0 |
6bafca1176eb8fe22e24008acd3c17c798b4e9ad | [
"axs = subplots(len(xs), 2, imgsize=imgsize, figsize=figsize)\nfor i, (x, y) in enumerate(zip(xs, ys)):\n x.show(ax=axs[i, 0], **kwargs)\n y.show(ax=axs[i, 1], **kwargs)\nplt.tight_layout()",
"title = 'Input / Prediction / Target'\naxs = subplots(len(xs), 3, imgsize=imgsize, figsize=figsize, title=title, we... | <|body_start_0|>
axs = subplots(len(xs), 2, imgsize=imgsize, figsize=figsize)
for i, (x, y) in enumerate(zip(xs, ys)):
x.show(ax=axs[i, 0], **kwargs)
y.show(ax=axs[i, 1], **kwargs)
plt.tight_layout()
<|end_body_0|>
<|body_start_1|>
title = 'Input / Prediction / T... | `ItemList` suitable for `Image` to `Image` tasks. | ImageImageList | [
"MIT",
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageImageList:
"""`ItemList` suitable for `Image` to `Image` tasks."""
def show_xys(self, xs, ys, imgsize: int=4, figsize: Optional[Tuple[int, int]]=None, **kwargs):
"""Show the `xs` (inputs) and `ys`(targets) on a figure of `figsize`."""
<|body_0|>
def show_xyzs(self, ... | stack_v2_sparse_classes_36k_train_021990 | 23,540 | permissive | [
{
"docstring": "Show the `xs` (inputs) and `ys`(targets) on a figure of `figsize`.",
"name": "show_xys",
"signature": "def show_xys(self, xs, ys, imgsize: int=4, figsize: Optional[Tuple[int, int]]=None, **kwargs)"
},
{
"docstring": "Show `xs` (inputs), `ys` (targets) and `zs` (predictions) on a ... | 2 | stack_v2_sparse_classes_30k_train_000105 | Implement the Python class `ImageImageList` described below.
Class description:
`ItemList` suitable for `Image` to `Image` tasks.
Method signatures and docstrings:
- def show_xys(self, xs, ys, imgsize: int=4, figsize: Optional[Tuple[int, int]]=None, **kwargs): Show the `xs` (inputs) and `ys`(targets) on a figure of `... | Implement the Python class `ImageImageList` described below.
Class description:
`ItemList` suitable for `Image` to `Image` tasks.
Method signatures and docstrings:
- def show_xys(self, xs, ys, imgsize: int=4, figsize: Optional[Tuple[int, int]]=None, **kwargs): Show the `xs` (inputs) and `ys`(targets) on a figure of `... | 141e873e42eb5e40665d20349f4b8e9a267ba1c4 | <|skeleton|>
class ImageImageList:
"""`ItemList` suitable for `Image` to `Image` tasks."""
def show_xys(self, xs, ys, imgsize: int=4, figsize: Optional[Tuple[int, int]]=None, **kwargs):
"""Show the `xs` (inputs) and `ys`(targets) on a figure of `figsize`."""
<|body_0|>
def show_xyzs(self, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImageImageList:
"""`ItemList` suitable for `Image` to `Image` tasks."""
def show_xys(self, xs, ys, imgsize: int=4, figsize: Optional[Tuple[int, int]]=None, **kwargs):
"""Show the `xs` (inputs) and `ys`(targets) on a figure of `figsize`."""
axs = subplots(len(xs), 2, imgsize=imgsize, figsi... | the_stack_v2_python_sparse | fastai/vision/data.py | jantic/DeOldify | train | 17,137 |
24de685695a38fe580ff96bbc2b7326f3a706915 | [
"self.cloud_vtk_points = vtk.vtkPoints()\nself.cloud_vtk_polydata = vtk.vtkPolyData()\nself.cloud_octree = vtk.vtkOctreePointLocator()\nself.cloud_color = vtk.vtkUnsignedCharArray()\nself.cloud_actor = vtk.vtkActor()\nself.v_filter = vtk.vtkVertexGlyphFilter()\nself.mapper = vtk.vtkPolyDataMapper()",
"self.np_clo... | <|body_start_0|>
self.cloud_vtk_points = vtk.vtkPoints()
self.cloud_vtk_polydata = vtk.vtkPolyData()
self.cloud_octree = vtk.vtkOctreePointLocator()
self.cloud_color = vtk.vtkUnsignedCharArray()
self.cloud_actor = vtk.vtkActor()
self.v_filter = vtk.vtkVertexGlyphFilter()
... | Cloud | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Cloud:
def __init__(self):
"""初始化变量"""
<|body_0|>
def initialize_car(self, path):
"""载入点云数据"""
<|body_1|>
def build_car(self):
"""汽车点云染色"""
<|body_2|>
def color_points(self, cloud_clipped_points):
"""对被切割点染色"""
<|body... | stack_v2_sparse_classes_36k_train_021991 | 4,869 | no_license | [
{
"docstring": "初始化变量",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "载入点云数据",
"name": "initialize_car",
"signature": "def initialize_car(self, path)"
},
{
"docstring": "汽车点云染色",
"name": "build_car",
"signature": "def build_car(self)"
},
{
... | 4 | stack_v2_sparse_classes_30k_train_020817 | Implement the Python class `Cloud` described below.
Class description:
Implement the Cloud class.
Method signatures and docstrings:
- def __init__(self): 初始化变量
- def initialize_car(self, path): 载入点云数据
- def build_car(self): 汽车点云染色
- def color_points(self, cloud_clipped_points): 对被切割点染色 | Implement the Python class `Cloud` described below.
Class description:
Implement the Cloud class.
Method signatures and docstrings:
- def __init__(self): 初始化变量
- def initialize_car(self, path): 载入点云数据
- def build_car(self): 汽车点云染色
- def color_points(self, cloud_clipped_points): 对被切割点染色
<|skeleton|>
class Cloud:
... | 2f18e869bcc2dfb118da69f02a5e231ff2602a68 | <|skeleton|>
class Cloud:
def __init__(self):
"""初始化变量"""
<|body_0|>
def initialize_car(self, path):
"""载入点云数据"""
<|body_1|>
def build_car(self):
"""汽车点云染色"""
<|body_2|>
def color_points(self, cloud_clipped_points):
"""对被切割点染色"""
<|body... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Cloud:
def __init__(self):
"""初始化变量"""
self.cloud_vtk_points = vtk.vtkPoints()
self.cloud_vtk_polydata = vtk.vtkPolyData()
self.cloud_octree = vtk.vtkOctreePointLocator()
self.cloud_color = vtk.vtkUnsignedCharArray()
self.cloud_actor = vtk.vtkActor()
sel... | the_stack_v2_python_sparse | wind_planes.py | baobaotang0/new_outline | train | 0 | |
0b36f9e436908596d4923f6c3e8aa69bdf535968 | [
"if has_permissions(request, self, 'delete'):\n super(OwnerModel, obj).delete(*args, **kwargs)\nelse:\n messages.warning(request, 'You do not have the Permission to delete Item #%s' % obj.pk)",
"if not self.pk:\n if request:\n self.access_control_list = isinstance(self.access_control_list, dict) o... | <|body_start_0|>
if has_permissions(request, self, 'delete'):
super(OwnerModel, obj).delete(*args, **kwargs)
else:
messages.warning(request, 'You do not have the Permission to delete Item #%s' % obj.pk)
<|end_body_0|>
<|body_start_1|>
if not self.pk:
if reque... | For access control purposes, We have a base class that will be extended inorder to have site/person based filtering and data hiding. | OwnerModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OwnerModel:
"""For access control purposes, We have a base class that will be extended inorder to have site/person based filtering and data hiding."""
def delete(self, request=None, *args, **kwargs):
"""Override delete for the object, making sure that the current user has the permiss... | stack_v2_sparse_classes_36k_train_021992 | 5,128 | no_license | [
{
"docstring": "Override delete for the object, making sure that the current user has the permission to delete this object",
"name": "delete",
"signature": "def delete(self, request=None, *args, **kwargs)"
},
{
"docstring": "if is not a new object, lets go through the drill: check if user is sup... | 2 | null | Implement the Python class `OwnerModel` described below.
Class description:
For access control purposes, We have a base class that will be extended inorder to have site/person based filtering and data hiding.
Method signatures and docstrings:
- def delete(self, request=None, *args, **kwargs): Override delete for the ... | Implement the Python class `OwnerModel` described below.
Class description:
For access control purposes, We have a base class that will be extended inorder to have site/person based filtering and data hiding.
Method signatures and docstrings:
- def delete(self, request=None, *args, **kwargs): Override delete for the ... | c2a55848c1dee14bd3eec75ac93810fe5e4f049b | <|skeleton|>
class OwnerModel:
"""For access control purposes, We have a base class that will be extended inorder to have site/person based filtering and data hiding."""
def delete(self, request=None, *args, **kwargs):
"""Override delete for the object, making sure that the current user has the permiss... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OwnerModel:
"""For access control purposes, We have a base class that will be extended inorder to have site/person based filtering and data hiding."""
def delete(self, request=None, *args, **kwargs):
"""Override delete for the object, making sure that the current user has the permission to delete... | the_stack_v2_python_sparse | uhai/core/models.py | Jaramba/Wellness | train | 0 |
e7d766f34572154b7a0fec27fef9cf801aa40c0f | [
"super(BiSeNetHead, self).__init__()\nif is_aux:\n self.conv_3x3 = ConvBnRelu(in_planes, 256, 3, 1, 1, norm_layer=norm_layer, Conv2d=Conv2d)\nelse:\n self.conv_3x3 = ConvBnRelu(in_planes, 64, 3, 1, 1, norm_layer=norm_layer, Conv2d=Conv2d)\nif is_aux:\n self.conv_1x1 = nn.Conv2d(256, out_planes, kernel_size... | <|body_start_0|>
super(BiSeNetHead, self).__init__()
if is_aux:
self.conv_3x3 = ConvBnRelu(in_planes, 256, 3, 1, 1, norm_layer=norm_layer, Conv2d=Conv2d)
else:
self.conv_3x3 = ConvBnRelu(in_planes, 64, 3, 1, 1, norm_layer=norm_layer, Conv2d=Conv2d)
if is_aux:
... | BiSeNetHead module. | BiSeNetHead | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BiSeNetHead:
"""BiSeNetHead module."""
def __init__(self, in_planes, out_planes, scale, is_aux=False, norm_layer='BN', Conv2d=nn.Conv2d):
"""Create BiSeNetHead. :param in_planes: input channels :param out_planes: output channels :param scale: scale factor. :param is_aux: whether use ... | stack_v2_sparse_classes_36k_train_021993 | 9,350 | permissive | [
{
"docstring": "Create BiSeNetHead. :param in_planes: input channels :param out_planes: output channels :param scale: scale factor. :param is_aux: whether use aux weight. :param norm_layer: type of norm layer. :param Conv2d: type of conv layer.",
"name": "__init__",
"signature": "def __init__(self, in_p... | 2 | stack_v2_sparse_classes_30k_train_013410 | Implement the Python class `BiSeNetHead` described below.
Class description:
BiSeNetHead module.
Method signatures and docstrings:
- def __init__(self, in_planes, out_planes, scale, is_aux=False, norm_layer='BN', Conv2d=nn.Conv2d): Create BiSeNetHead. :param in_planes: input channels :param out_planes: output channel... | Implement the Python class `BiSeNetHead` described below.
Class description:
BiSeNetHead module.
Method signatures and docstrings:
- def __init__(self, in_planes, out_planes, scale, is_aux=False, norm_layer='BN', Conv2d=nn.Conv2d): Create BiSeNetHead. :param in_planes: input channels :param out_planes: output channel... | e4ef3a1c92d19d1d08c3ef0e2156b6fecefdbe04 | <|skeleton|>
class BiSeNetHead:
"""BiSeNetHead module."""
def __init__(self, in_planes, out_planes, scale, is_aux=False, norm_layer='BN', Conv2d=nn.Conv2d):
"""Create BiSeNetHead. :param in_planes: input channels :param out_planes: output channels :param scale: scale factor. :param is_aux: whether use ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BiSeNetHead:
"""BiSeNetHead module."""
def __init__(self, in_planes, out_planes, scale, is_aux=False, norm_layer='BN', Conv2d=nn.Conv2d):
"""Create BiSeNetHead. :param in_planes: input channels :param out_planes: output channels :param scale: scale factor. :param is_aux: whether use aux weight. :... | the_stack_v2_python_sparse | zeus/networks/pytorch/customs/bisenet.py | huawei-noah/xingtian | train | 308 |
c971cb1e0e7b9b07e6904e3d57f5607543dad4bc | [
"d = inspector.DefaultFields(a=5)\nself.assertEqual(('{foo}', '.*'), d['foo'])\nself.assertEqual(5, d['a'])\nself.assertTrue('nothing' in d)",
"f = inspector.DefaultFormatter()\nself.assertEqual(('{nothing}', '.*'), f.SPECIAL_FIELDS['nothing'])\nself.assertEqual('foo_{bar}_{Y:04d}_{nothing}', f.expand_format('foo... | <|body_start_0|>
d = inspector.DefaultFields(a=5)
self.assertEqual(('{foo}', '.*'), d['foo'])
self.assertEqual(5, d['a'])
self.assertTrue('nothing' in d)
<|end_body_0|>
<|body_start_1|>
f = inspector.DefaultFormatter()
self.assertEqual(('{nothing}', '.*'), f.SPECIAL_FIEL... | Test inspector support classes | InspectorSupportClass | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InspectorSupportClass:
"""Test inspector support classes"""
def testDefaultFields(self):
"""default dict that returns generic match"""
<|body_0|>
def testDefaultFormatter(self):
"""formatter that returns generics"""
<|body_1|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_36k_train_021994 | 7,654 | no_license | [
{
"docstring": "default dict that returns generic match",
"name": "testDefaultFields",
"signature": "def testDefaultFields(self)"
},
{
"docstring": "formatter that returns generics",
"name": "testDefaultFormatter",
"signature": "def testDefaultFormatter(self)"
}
] | 2 | null | Implement the Python class `InspectorSupportClass` described below.
Class description:
Test inspector support classes
Method signatures and docstrings:
- def testDefaultFields(self): default dict that returns generic match
- def testDefaultFormatter(self): formatter that returns generics | Implement the Python class `InspectorSupportClass` described below.
Class description:
Test inspector support classes
Method signatures and docstrings:
- def testDefaultFields(self): default dict that returns generic match
- def testDefaultFormatter(self): formatter that returns generics
<|skeleton|>
class Inspector... | a0bf5e682fb917bb707b4f66787b0ecb860efce1 | <|skeleton|>
class InspectorSupportClass:
"""Test inspector support classes"""
def testDefaultFields(self):
"""default dict that returns generic match"""
<|body_0|>
def testDefaultFormatter(self):
"""formatter that returns generics"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class InspectorSupportClass:
"""Test inspector support classes"""
def testDefaultFields(self):
"""default dict that returns generic match"""
d = inspector.DefaultFields(a=5)
self.assertEqual(('{foo}', '.*'), d['foo'])
self.assertEqual(5, d['a'])
self.assertTrue('nothing'... | the_stack_v2_python_sparse | unit_tests/test_Inspector.py | spacepy/dbprocessing | train | 4 |
47bf3fdd9d8cafef8d71a5ae66f1061ae59e707a | [
"super().__init__(**attrs)\nself.value = value\nself.padding = padding\nself.width = real_length(value) + self.padding",
"value_style = self.get_style('value')\nlines = break_line(value_style(self.padding * ' ' + self.value), self.width)\nreturn list(lines) or ['']"
] | <|body_start_0|>
super().__init__(**attrs)
self.value = value
self.padding = padding
self.width = real_length(value) + self.padding
<|end_body_0|>
<|body_start_1|>
value_style = self.get_style('value')
lines = break_line(value_style(self.padding * ' ' + self.value), self... | Unselectable text object | Label | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Label:
"""Unselectable text object"""
def __init__(self, value: str='', padding: int=0, **attrs: Any) -> None:
"""Set up object"""
<|body_0|>
def get_lines(self) -> list[str]:
"""Get lines of object"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_021995 | 29,898 | no_license | [
{
"docstring": "Set up object",
"name": "__init__",
"signature": "def __init__(self, value: str='', padding: int=0, **attrs: Any) -> None"
},
{
"docstring": "Get lines of object",
"name": "get_lines",
"signature": "def get_lines(self) -> list[str]"
}
] | 2 | stack_v2_sparse_classes_30k_train_006510 | Implement the Python class `Label` described below.
Class description:
Unselectable text object
Method signatures and docstrings:
- def __init__(self, value: str='', padding: int=0, **attrs: Any) -> None: Set up object
- def get_lines(self) -> list[str]: Get lines of object | Implement the Python class `Label` described below.
Class description:
Unselectable text object
Method signatures and docstrings:
- def __init__(self, value: str='', padding: int=0, **attrs: Any) -> None: Set up object
- def get_lines(self) -> list[str]: Get lines of object
<|skeleton|>
class Label:
"""Unselecta... | 05ddaf41fd8de11c7300a8ba125eddf9e1ee1131 | <|skeleton|>
class Label:
"""Unselectable text object"""
def __init__(self, value: str='', padding: int=0, **attrs: Any) -> None:
"""Set up object"""
<|body_0|>
def get_lines(self) -> list[str]:
"""Get lines of object"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Label:
"""Unselectable text object"""
def __init__(self, value: str='', padding: int=0, **attrs: Any) -> None:
"""Set up object"""
super().__init__(**attrs)
self.value = value
self.padding = padding
self.width = real_length(value) + self.padding
def get_lines(... | the_stack_v2_python_sparse | pytermgui/widgets/base.py | ekapujiw2002/pytermgui | train | 0 |
94736cac4d6c768c63c9559b9aa8c9750fc4b0a6 | [
"this_verbose_string, this_abbrev_string = model_interpretation.model_component_to_string(component_type_string=model_interpretation.CLASS_COMPONENT_TYPE_STRING, target_class=TARGET_CLASS, layer_name=LAYER_NAME, neuron_indices=NEURON_INDICES, channel_index=CHANNEL_INDEX)\nself.assertTrue(this_verbose_string == CLAS... | <|body_start_0|>
this_verbose_string, this_abbrev_string = model_interpretation.model_component_to_string(component_type_string=model_interpretation.CLASS_COMPONENT_TYPE_STRING, target_class=TARGET_CLASS, layer_name=LAYER_NAME, neuron_indices=NEURON_INDICES, channel_index=CHANNEL_INDEX)
self.assertTrue(... | Each method is a unit test for model_interpretation.py. | ModelInterpretationTests | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModelInterpretationTests:
"""Each method is a unit test for model_interpretation.py."""
def test_model_component_to_string_class(self):
"""Ensures correct output from model_component_to_string. In this case, the component is an output class."""
<|body_0|>
def test_model_... | stack_v2_sparse_classes_36k_train_021996 | 2,860 | permissive | [
{
"docstring": "Ensures correct output from model_component_to_string. In this case, the component is an output class.",
"name": "test_model_component_to_string_class",
"signature": "def test_model_component_to_string_class(self)"
},
{
"docstring": "Ensures correct output from model_component_to... | 3 | null | Implement the Python class `ModelInterpretationTests` described below.
Class description:
Each method is a unit test for model_interpretation.py.
Method signatures and docstrings:
- def test_model_component_to_string_class(self): Ensures correct output from model_component_to_string. In this case, the component is an... | Implement the Python class `ModelInterpretationTests` described below.
Class description:
Each method is a unit test for model_interpretation.py.
Method signatures and docstrings:
- def test_model_component_to_string_class(self): Ensures correct output from model_component_to_string. In this case, the component is an... | 1835a71ababb7ad7e47bfa19e62948d466559d56 | <|skeleton|>
class ModelInterpretationTests:
"""Each method is a unit test for model_interpretation.py."""
def test_model_component_to_string_class(self):
"""Ensures correct output from model_component_to_string. In this case, the component is an output class."""
<|body_0|>
def test_model_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ModelInterpretationTests:
"""Each method is a unit test for model_interpretation.py."""
def test_model_component_to_string_class(self):
"""Ensures correct output from model_component_to_string. In this case, the component is an output class."""
this_verbose_string, this_abbrev_string = mo... | the_stack_v2_python_sparse | gewittergefahr/deep_learning/model_interpretation_test.py | thunderhoser/GewitterGefahr | train | 29 |
e6c83c663fafdfaa0c3d8f3cb43f84f4ae1e97f3 | [
"terms = self.flatten()\nif len(terms) == 1:\n return simplify_if_possible(terms[0])\nelse:\n return Sum([simplify_if_possible(term) for term in terms]).flatten()",
"terms = []\nfor term in self:\n if isinstance(term, Sum):\n terms += list(term)\n elif isinstance(term, Expression) and len(term)... | <|body_start_0|>
terms = self.flatten()
if len(terms) == 1:
return simplify_if_possible(terms[0])
else:
return Sum([simplify_if_possible(term) for term in terms]).flatten()
<|end_body_0|>
<|body_start_1|>
terms = []
for term in self:
if isinst... | A Sum acts just like a list in almost all regards, except that this code can tell it is a Sum using isinstance(), and we add useful methods such as simplify(). Because of this: * You can index into a sum like a list, as in term = sum[0]. * You can iterate over a sum with "for term in sum:". * You can convert a sum to a... | Sum | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Sum:
"""A Sum acts just like a list in almost all regards, except that this code can tell it is a Sum using isinstance(), and we add useful methods such as simplify(). Because of this: * You can index into a sum like a list, as in term = sum[0]. * You can iterate over a sum with "for term in sum:... | stack_v2_sparse_classes_36k_train_021997 | 9,240 | permissive | [
{
"docstring": "This is the starting point for the task you need to perform. It removes unnecessary nesting and applies the associative law.",
"name": "simplify",
"signature": "def simplify(self)"
},
{
"docstring": "Simplifies nested sums.",
"name": "flatten",
"signature": "def flatten(s... | 2 | stack_v2_sparse_classes_30k_train_009028 | Implement the Python class `Sum` described below.
Class description:
A Sum acts just like a list in almost all regards, except that this code can tell it is a Sum using isinstance(), and we add useful methods such as simplify(). Because of this: * You can index into a sum like a list, as in term = sum[0]. * You can it... | Implement the Python class `Sum` described below.
Class description:
A Sum acts just like a list in almost all regards, except that this code can tell it is a Sum using isinstance(), and we add useful methods such as simplify(). Because of this: * You can index into a sum like a list, as in term = sum[0]. * You can it... | 4fbac9f751a990b567c5ceb67384440ee528dbd0 | <|skeleton|>
class Sum:
"""A Sum acts just like a list in almost all regards, except that this code can tell it is a Sum using isinstance(), and we add useful methods such as simplify(). Because of this: * You can index into a sum like a list, as in term = sum[0]. * You can iterate over a sum with "for term in sum:... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Sum:
"""A Sum acts just like a list in almost all regards, except that this code can tell it is a Sum using isinstance(), and we add useful methods such as simplify(). Because of this: * You can index into a sum like a list, as in term = sum[0]. * You can iterate over a sum with "for term in sum:". * You can ... | the_stack_v2_python_sparse | labs/lab0/algebra.py | AdamSpannbauer/mit6034 | train | 1 |
41930511464d501e34aef5e0ab72a94c4f786d2e | [
"for k in filter_munge:\n if k in params and params[k] in ['true', '1']:\n params[k] = 'True'\n if k in params and params[k] in ['false', '0']:\n params[k] = 'False'\nreturn params",
"filter_class = self.get_filter_class(view, queryset)\nfilter_munge = getattr(view, 'filter_munge', ())\nparams... | <|body_start_0|>
for k in filter_munge:
if k in params and params[k] in ['true', '1']:
params[k] = 'True'
if k in params and params[k] in ['false', '0']:
params[k] = 'False'
return params
<|end_body_0|>
<|body_start_1|>
filter_class = self... | MktFilterBackend | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MktFilterBackend:
def munge_params(self, filter_munge, params):
"""Cast some more things as truthful."""
<|body_0|>
def filter_queryset(self, request, queryset, view):
"""Overriding DRF in order to munging the incoming params. It will only munge fields that are in th... | stack_v2_sparse_classes_36k_train_021998 | 1,040 | permissive | [
{
"docstring": "Cast some more things as truthful.",
"name": "munge_params",
"signature": "def munge_params(self, filter_munge, params)"
},
{
"docstring": "Overriding DRF in order to munging the incoming params. It will only munge fields that are in the filter_munge tuple on the view, other fiel... | 2 | stack_v2_sparse_classes_30k_train_001458 | Implement the Python class `MktFilterBackend` described below.
Class description:
Implement the MktFilterBackend class.
Method signatures and docstrings:
- def munge_params(self, filter_munge, params): Cast some more things as truthful.
- def filter_queryset(self, request, queryset, view): Overriding DRF in order to ... | Implement the Python class `MktFilterBackend` described below.
Class description:
Implement the MktFilterBackend class.
Method signatures and docstrings:
- def munge_params(self, filter_munge, params): Cast some more things as truthful.
- def filter_queryset(self, request, queryset, view): Overriding DRF in order to ... | 5fa5400a447f2e905372d4c8eba6d959d22d4f3e | <|skeleton|>
class MktFilterBackend:
def munge_params(self, filter_munge, params):
"""Cast some more things as truthful."""
<|body_0|>
def filter_queryset(self, request, queryset, view):
"""Overriding DRF in order to munging the incoming params. It will only munge fields that are in th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MktFilterBackend:
def munge_params(self, filter_munge, params):
"""Cast some more things as truthful."""
for k in filter_munge:
if k in params and params[k] in ['true', '1']:
params[k] = 'True'
if k in params and params[k] in ['false', '0']:
... | the_stack_v2_python_sparse | mkt/api/filters.py | sarvex/zamboni | train | 0 | |
885dedc6f6d6c765ac8a5d36eaf0d8adf4612b4d | [
"rev, cur = (None, head)\nwhile cur:\n rev, rev.next, cur = (cur, rev, cur.next)\nreturn rev",
"if not head or not head.next:\n return head\nrev = self.reverseListRecursive(head.next)\nhead.next.next = head\nhead.next = None\nreturn rev"
] | <|body_start_0|>
rev, cur = (None, head)
while cur:
rev, rev.next, cur = (cur, rev, cur.next)
return rev
<|end_body_0|>
<|body_start_1|>
if not head or not head.next:
return head
rev = self.reverseListRecursive(head.next)
head.next.next = head
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseList(self, head):
"""offical solution: https://leetcode.com/problems/reverse-linked-list/solution/ :type head: ListNode :rtype: ListNode"""
<|body_0|>
def reverseListRecursive(self, head):
"""offical solution: https://leetcode.com/problems/revers... | stack_v2_sparse_classes_36k_train_021999 | 1,219 | no_license | [
{
"docstring": "offical solution: https://leetcode.com/problems/reverse-linked-list/solution/ :type head: ListNode :rtype: ListNode",
"name": "reverseList",
"signature": "def reverseList(self, head)"
},
{
"docstring": "offical solution: https://leetcode.com/problems/reverse-linked-list/solution/... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList(self, head): offical solution: https://leetcode.com/problems/reverse-linked-list/solution/ :type head: ListNode :rtype: ListNode
- def reverseListRecursive(self, ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList(self, head): offical solution: https://leetcode.com/problems/reverse-linked-list/solution/ :type head: ListNode :rtype: ListNode
- def reverseListRecursive(self, ... | 2526f8c0dec7101123123740e146ee4081e979ee | <|skeleton|>
class Solution:
def reverseList(self, head):
"""offical solution: https://leetcode.com/problems/reverse-linked-list/solution/ :type head: ListNode :rtype: ListNode"""
<|body_0|>
def reverseListRecursive(self, head):
"""offical solution: https://leetcode.com/problems/revers... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def reverseList(self, head):
"""offical solution: https://leetcode.com/problems/reverse-linked-list/solution/ :type head: ListNode :rtype: ListNode"""
rev, cur = (None, head)
while cur:
rev, rev.next, cur = (cur, rev, cur.next)
return rev
def reverseL... | the_stack_v2_python_sparse | 242. Reverse Linked List.py | zhangpengGenedock/leetcode_python | train | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.