blob_id stringlengths 40 40 | bodies listlengths 2 6 | bodies_text stringlengths 196 7.73k | class_docstring stringlengths 0 700 | class_name stringlengths 1 86 | detected_licenses listlengths 0 45 | format_version stringclasses 1
value | full_text stringlengths 378 8.64k | id stringlengths 44 44 | length_bytes int64 505 50k | license_type stringclasses 2
values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.88k | prompted_full_text stringlengths 565 12.5k | revision_id stringlengths 40 40 | skeleton stringlengths 162 5.05k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | snapshot_total_rows int64 75.8k 75.8k | solution stringlengths 242 8.3k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0ad1674af08cd5adbeb25bf78a127cefd04d437a | [
"global saccList, fixList\nsaccList = []\nfixList = []\nglobal trialId\nself.waitForSacc = False\nself.saccOnset = None\nself.stimTime = None\ntrialDict['saccLat'] = trialDict['xCoG'] = trialDict['xCoGMask'] = trialDict['yCoG'] = trialDict['yCoGMask'] = trialDict['rtFromStim'] = trialDict['endX'] = trialDict['endXC... | <|body_start_0|>
global saccList, fixList
saccList = []
fixList = []
global trialId
self.waitForSacc = False
self.saccOnset = None
self.stimTime = None
trialDict['saccLat'] = trialDict['xCoG'] = trialDict['xCoGMask'] = trialDict['yCoG'] = trialDict['yCoGMa... | MyReader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyReader:
def initTrial(self, trialDict):
"""Initialize a trial: Arguments: trialDict -- a trial dictionary"""
<|body_0|>
def finishTrial(self, trialDict):
"""Finalizes the trial. Arguments: trialDict -- a trial dictionary"""
<|body_1|>
def parseLine(sel... | stack_v2_sparse_classes_75kplus_train_003700 | 9,558 | no_license | [
{
"docstring": "Initialize a trial: Arguments: trialDict -- a trial dictionary",
"name": "initTrial",
"signature": "def initTrial(self, trialDict)"
},
{
"docstring": "Finalizes the trial. Arguments: trialDict -- a trial dictionary",
"name": "finishTrial",
"signature": "def finishTrial(se... | 4 | stack_v2_sparse_classes_30k_train_015731 | Implement the Python class `MyReader` described below.
Class description:
Implement the MyReader class.
Method signatures and docstrings:
- def initTrial(self, trialDict): Initialize a trial: Arguments: trialDict -- a trial dictionary
- def finishTrial(self, trialDict): Finalizes the trial. Arguments: trialDict -- a ... | Implement the Python class `MyReader` described below.
Class description:
Implement the MyReader class.
Method signatures and docstrings:
- def initTrial(self, trialDict): Initialize a trial: Arguments: trialDict -- a trial dictionary
- def finishTrial(self, trialDict): Finalizes the trial. Arguments: trialDict -- a ... | a114d422756f926c3a1256dc796c8f39d34d8078 | <|skeleton|>
class MyReader:
def initTrial(self, trialDict):
"""Initialize a trial: Arguments: trialDict -- a trial dictionary"""
<|body_0|>
def finishTrial(self, trialDict):
"""Finalizes the trial. Arguments: trialDict -- a trial dictionary"""
<|body_1|>
def parseLine(sel... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MyReader:
def initTrial(self, trialDict):
"""Initialize a trial: Arguments: trialDict -- a trial dictionary"""
global saccList, fixList
saccList = []
fixList = []
global trialId
self.waitForSacc = False
self.saccOnset = None
self.stimTime = None
... | the_stack_v2_python_sparse | 004B/bckp/backup .⁄studies._004/parseAsc.py | lvanderlinden/004 | train | 0 | |
d061b12a13f2a806e449cd905b398586931d73d6 | [
"h = hashlib.sha256()\nwith open(file_path, 'rb') as f:\n for chunk in iter(lambda: f.read(2048 * h.block_size), b''):\n h.update(chunk)\nchecksum = h.hexdigest()\nk = klass(checksum=checksum, corpus_file_id=file_path.name)\nLOGGER.info(k)\nreturn k",
"with file_path.open() as f:\n for line in iter(f... | <|body_start_0|>
h = hashlib.sha256()
with open(file_path, 'rb') as f:
for chunk in iter(lambda: f.read(2048 * h.block_size), b''):
h.update(chunk)
checksum = h.hexdigest()
k = klass(checksum=checksum, corpus_file_id=file_path.name)
LOGGER.info(k)
... | BaseCorpusFile | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseCorpusFile:
def create(klass, file_path):
"""Args: file_path(pathlib.Path): File path"""
<|body_0|>
def _readline(self, file_path):
"""Args: file_path[pathlib.Path]: File path"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
h = hashlib.sha256()
... | stack_v2_sparse_classes_75kplus_train_003701 | 791 | no_license | [
{
"docstring": "Args: file_path(pathlib.Path): File path",
"name": "create",
"signature": "def create(klass, file_path)"
},
{
"docstring": "Args: file_path[pathlib.Path]: File path",
"name": "_readline",
"signature": "def _readline(self, file_path)"
}
] | 2 | null | Implement the Python class `BaseCorpusFile` described below.
Class description:
Implement the BaseCorpusFile class.
Method signatures and docstrings:
- def create(klass, file_path): Args: file_path(pathlib.Path): File path
- def _readline(self, file_path): Args: file_path[pathlib.Path]: File path | Implement the Python class `BaseCorpusFile` described below.
Class description:
Implement the BaseCorpusFile class.
Method signatures and docstrings:
- def create(klass, file_path): Args: file_path(pathlib.Path): File path
- def _readline(self, file_path): Args: file_path[pathlib.Path]: File path
<|skeleton|>
class ... | 2a0c2b6bb42b6244afcca2601f126e7f3c7d1504 | <|skeleton|>
class BaseCorpusFile:
def create(klass, file_path):
"""Args: file_path(pathlib.Path): File path"""
<|body_0|>
def _readline(self, file_path):
"""Args: file_path[pathlib.Path]: File path"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BaseCorpusFile:
def create(klass, file_path):
"""Args: file_path(pathlib.Path): File path"""
h = hashlib.sha256()
with open(file_path, 'rb') as f:
for chunk in iter(lambda: f.read(2048 * h.block_size), b''):
h.update(chunk)
checksum = h.hexdigest()
... | the_stack_v2_python_sparse | sanakin-keep/corpus_file/base_corpus_file.py | wbydo/sanascan | train | 0 | |
e61ae8eef6835a580c4beed41fb29db68dc72cc5 | [
"temp = dict(*args, **kwargs)\nif 'Refs' in temp:\n refs = temp['Refs']\n if not isinstance(refs, DbRefs):\n refs = DbRefs(refs)\nelse:\n refs = DbRefs()\nfor key, val in temp.items():\n if key in KnownDatabases:\n refs[key] = val\n del temp[key]\nDelegator.__init__(self, refs)\nsel... | <|body_start_0|>
temp = dict(*args, **kwargs)
if 'Refs' in temp:
refs = temp['Refs']
if not isinstance(refs, DbRefs):
refs = DbRefs(refs)
else:
refs = DbRefs()
for key, val in temp.items():
if key in KnownDatabases:
... | Dictionary that stores attributes for Sequence objects. Delegates to DbRefs for database IDs. | Info | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Info:
"""Dictionary that stores attributes for Sequence objects. Delegates to DbRefs for database IDs."""
def __init__(self, *args, **kwargs):
"""Returns new Info object. Creates DbRefs if necessary."""
<|body_0|>
def __getattr__(self, attr):
"""Checks for attr i... | stack_v2_sparse_classes_75kplus_train_003702 | 4,625 | permissive | [
{
"docstring": "Returns new Info object. Creates DbRefs if necessary.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Checks for attr in Refs first.",
"name": "__getattr__",
"signature": "def __getattr__(self, attr)"
},
{
"docstring": "... | 6 | stack_v2_sparse_classes_30k_train_048327 | Implement the Python class `Info` described below.
Class description:
Dictionary that stores attributes for Sequence objects. Delegates to DbRefs for database IDs.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Returns new Info object. Creates DbRefs if necessary.
- def __getattr__(self, att... | Implement the Python class `Info` described below.
Class description:
Dictionary that stores attributes for Sequence objects. Delegates to DbRefs for database IDs.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Returns new Info object. Creates DbRefs if necessary.
- def __getattr__(self, att... | fe6f8c8dfed86d39c80f2804a753c05bb2e485b4 | <|skeleton|>
class Info:
"""Dictionary that stores attributes for Sequence objects. Delegates to DbRefs for database IDs."""
def __init__(self, *args, **kwargs):
"""Returns new Info object. Creates DbRefs if necessary."""
<|body_0|>
def __getattr__(self, attr):
"""Checks for attr i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Info:
"""Dictionary that stores attributes for Sequence objects. Delegates to DbRefs for database IDs."""
def __init__(self, *args, **kwargs):
"""Returns new Info object. Creates DbRefs if necessary."""
temp = dict(*args, **kwargs)
if 'Refs' in temp:
refs = temp['Refs'... | the_stack_v2_python_sparse | scripts/venv/lib/python2.7/site-packages/cogent/core/info.py | sauloal/cnidaria | train | 3 |
e2f6d390618541d22d65239e8053040e8137885a | [
"email = request.data['email']\nuser = User.objects.get(email=email)\nif user.withdrawal_status:\n return Response(data={'탈퇴 회원'}, status=status.HTTP_400_BAD_REQUEST)\nLENGTH = 8\nstring_pool = string.ascii_letters + string.digits\nauth_num = ''\nfor i in range(LENGTH):\n auth_num += random.choice(string_pool... | <|body_start_0|>
email = request.data['email']
user = User.objects.get(email=email)
if user.withdrawal_status:
return Response(data={'탈퇴 회원'}, status=status.HTTP_400_BAD_REQUEST)
LENGTH = 8
string_pool = string.ascii_letters + string.digits
auth_num = ''
... | ForgetPWDViewSet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ForgetPWDViewSet:
def email_auth_num(self, request):
"""비밀번호 변경 토큰 생성 -> 토큰 생성 후 User 테이블 forget_pwd_token에 저장 -> 이메일로 토큰 전송"""
<|body_0|>
def is_pwd_token(self, request):
"""토큰값이 유효한 값인지 확인"""
<|body_1|>
def password_reset(self, request):
"""USE... | stack_v2_sparse_classes_75kplus_train_003703 | 30,076 | no_license | [
{
"docstring": "비밀번호 변경 토큰 생성 -> 토큰 생성 후 User 테이블 forget_pwd_token에 저장 -> 이메일로 토큰 전송",
"name": "email_auth_num",
"signature": "def email_auth_num(self, request)"
},
{
"docstring": "토큰값이 유효한 값인지 확인",
"name": "is_pwd_token",
"signature": "def is_pwd_token(self, request)"
},
{
"docs... | 3 | stack_v2_sparse_classes_30k_train_046040 | Implement the Python class `ForgetPWDViewSet` described below.
Class description:
Implement the ForgetPWDViewSet class.
Method signatures and docstrings:
- def email_auth_num(self, request): 비밀번호 변경 토큰 생성 -> 토큰 생성 후 User 테이블 forget_pwd_token에 저장 -> 이메일로 토큰 전송
- def is_pwd_token(self, request): 토큰값이 유효한 값인지 확인
- def p... | Implement the Python class `ForgetPWDViewSet` described below.
Class description:
Implement the ForgetPWDViewSet class.
Method signatures and docstrings:
- def email_auth_num(self, request): 비밀번호 변경 토큰 생성 -> 토큰 생성 후 User 테이블 forget_pwd_token에 저장 -> 이메일로 토큰 전송
- def is_pwd_token(self, request): 토큰값이 유효한 값인지 확인
- def p... | bcc955bddd9941f2bc54f7577c26c1ddc6b36a48 | <|skeleton|>
class ForgetPWDViewSet:
def email_auth_num(self, request):
"""비밀번호 변경 토큰 생성 -> 토큰 생성 후 User 테이블 forget_pwd_token에 저장 -> 이메일로 토큰 전송"""
<|body_0|>
def is_pwd_token(self, request):
"""토큰값이 유효한 값인지 확인"""
<|body_1|>
def password_reset(self, request):
"""USE... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ForgetPWDViewSet:
def email_auth_num(self, request):
"""비밀번호 변경 토큰 생성 -> 토큰 생성 후 User 테이블 forget_pwd_token에 저장 -> 이메일로 토큰 전송"""
email = request.data['email']
user = User.objects.get(email=email)
if user.withdrawal_status:
return Response(data={'탈퇴 회원'}, status=statu... | the_stack_v2_python_sparse | users/views.py | bgy1060/Daily_Project | train | 1 | |
238010d82051af9c51dec23b7d97ce6cc2aa1788 | [
"cursor = None\nwhile head:\n node = head.next\n head.next = cursor\n cursor = head\n head = node\nreturn cursor",
"if not head:\n return None\nif not head.next:\n return head\nnode = self.reverseList_v2(head.next)\nhead.next.next = head\nhead.next = None\nreturn node"
] | <|body_start_0|>
cursor = None
while head:
node = head.next
head.next = cursor
cursor = head
head = node
return cursor
<|end_body_0|>
<|body_start_1|>
if not head:
return None
if not head.next:
return head
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reverseList_v1(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def reverseList_v2(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
cursor = None
while hea... | stack_v2_sparse_classes_75kplus_train_003704 | 1,081 | permissive | [
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "reverseList_v1",
"signature": "def reverseList_v1(self, head)"
},
{
"docstring": ":type head: ListNode :rtype: ListNode",
"name": "reverseList_v2",
"signature": "def reverseList_v2(self, head)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016370 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList_v1(self, head): :type head: ListNode :rtype: ListNode
- def reverseList_v2(self, head): :type head: ListNode :rtype: ListNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reverseList_v1(self, head): :type head: ListNode :rtype: ListNode
- def reverseList_v2(self, head): :type head: ListNode :rtype: ListNode
<|skeleton|>
class Solution:
d... | 0fd165afa2ec339a6f194bc57f8810e66cd2822b | <|skeleton|>
class Solution:
def reverseList_v1(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_0|>
def reverseList_v2(self, head):
""":type head: ListNode :rtype: ListNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def reverseList_v1(self, head):
""":type head: ListNode :rtype: ListNode"""
cursor = None
while head:
node = head.next
head.next = cursor
cursor = head
head = node
return cursor
def reverseList_v2(self, head):
... | the_stack_v2_python_sparse | LinkedList/206_ReverseLinkedList.py | wanggalex/leetcode | train | 0 | |
a29b6337bae4aa48d4e15ad98a7a6f0d939ca986 | [
"if len(payload) == 2 + 4 and payload[:2] == b'\\x00\\x01':\n return socket.inet_ntop(socket.AF_INET, bytes(payload[2:]))\nelif len(payload) == 2 + 16 and payload[:2] == b'\\x00\\x02':\n return socket.inet_ntop(socket.AF_INET6, bytes(payload[2:]))\nraise exception.CodecException('Invalid Address payload')",
... | <|body_start_0|>
if len(payload) == 2 + 4 and payload[:2] == b'\x00\x01':
return socket.inet_ntop(socket.AF_INET, bytes(payload[2:]))
elif len(payload) == 2 + 16 and payload[:2] == b'\x00\x02':
return socket.inet_ntop(socket.AF_INET6, bytes(payload[2:]))
raise exception.C... | AddressAVP | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AddressAVP:
def decode_payload(payload):
"""Decode the payload as IPV4 or IPV6 string"""
<|body_0|>
def encode_value(value):
"""Encode the payload given IPV4 or IPV6 string"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(payload) == 2 + 4 and... | stack_v2_sparse_classes_75kplus_train_003705 | 21,908 | permissive | [
{
"docstring": "Decode the payload as IPV4 or IPV6 string",
"name": "decode_payload",
"signature": "def decode_payload(payload)"
},
{
"docstring": "Encode the payload given IPV4 or IPV6 string",
"name": "encode_value",
"signature": "def encode_value(value)"
}
] | 2 | stack_v2_sparse_classes_30k_test_001265 | Implement the Python class `AddressAVP` described below.
Class description:
Implement the AddressAVP class.
Method signatures and docstrings:
- def decode_payload(payload): Decode the payload as IPV4 or IPV6 string
- def encode_value(value): Encode the payload given IPV4 or IPV6 string | Implement the Python class `AddressAVP` described below.
Class description:
Implement the AddressAVP class.
Method signatures and docstrings:
- def decode_payload(payload): Decode the payload as IPV4 or IPV6 string
- def encode_value(value): Encode the payload given IPV4 or IPV6 string
<|skeleton|>
class AddressAVP:... | 0e1d895dfe625681229e181fbc2dbad83e13c5cb | <|skeleton|>
class AddressAVP:
def decode_payload(payload):
"""Decode the payload as IPV4 or IPV6 string"""
<|body_0|>
def encode_value(value):
"""Encode the payload given IPV4 or IPV6 string"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AddressAVP:
def decode_payload(payload):
"""Decode the payload as IPV4 or IPV6 string"""
if len(payload) == 2 + 4 and payload[:2] == b'\x00\x01':
return socket.inet_ntop(socket.AF_INET, bytes(payload[2:]))
elif len(payload) == 2 + 16 and payload[:2] == b'\x00\x02':
... | the_stack_v2_python_sparse | lte/gateway/python/magma/subscriberdb/protocols/diameter/avp.py | magma/magma | train | 1,219 | |
9c3ea8f510a9346e1770aabd724aee8c2932c884 | [
"self.comment = get_object_or_404(Comment, pk=kwargs.get('pk'))\nself.userProfile = get_object_or_404(Profile, user=self.request.user)\ntry:\n CommentLike.objects.get(liked_by=self.userProfile, comment_id=self.comment)\nexcept CommentLike.DoesNotExist:\n serializer = self.serializer_class(data={})\n serial... | <|body_start_0|>
self.comment = get_object_or_404(Comment, pk=kwargs.get('pk'))
self.userProfile = get_object_or_404(Profile, user=self.request.user)
try:
CommentLike.objects.get(liked_by=self.userProfile, comment_id=self.comment)
except CommentLike.DoesNotExist:
... | CommentLikeView | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommentLikeView:
def put(self, *args, **kwargs):
"""like or unlike a specific comment Args: pk[integer]:primary key for a specific comment Returns: success message and 200 ok if complete else 404 if comment is not found"""
<|body_0|>
def get(self, *args, **kwargs):
"... | stack_v2_sparse_classes_75kplus_train_003706 | 7,652 | permissive | [
{
"docstring": "like or unlike a specific comment Args: pk[integer]:primary key for a specific comment Returns: success message and 200 ok if complete else 404 if comment is not found",
"name": "put",
"signature": "def put(self, *args, **kwargs)"
},
{
"docstring": "get all likes of a comment Ret... | 3 | stack_v2_sparse_classes_30k_train_046120 | Implement the Python class `CommentLikeView` described below.
Class description:
Implement the CommentLikeView class.
Method signatures and docstrings:
- def put(self, *args, **kwargs): like or unlike a specific comment Args: pk[integer]:primary key for a specific comment Returns: success message and 200 ok if comple... | Implement the Python class `CommentLikeView` described below.
Class description:
Implement the CommentLikeView class.
Method signatures and docstrings:
- def put(self, *args, **kwargs): like or unlike a specific comment Args: pk[integer]:primary key for a specific comment Returns: success message and 200 ok if comple... | 60c830977fa39a7eea9ab978a9ba0c3beb0c4d88 | <|skeleton|>
class CommentLikeView:
def put(self, *args, **kwargs):
"""like or unlike a specific comment Args: pk[integer]:primary key for a specific comment Returns: success message and 200 ok if complete else 404 if comment is not found"""
<|body_0|>
def get(self, *args, **kwargs):
"... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CommentLikeView:
def put(self, *args, **kwargs):
"""like or unlike a specific comment Args: pk[integer]:primary key for a specific comment Returns: success message and 200 ok if complete else 404 if comment is not found"""
self.comment = get_object_or_404(Comment, pk=kwargs.get('pk'))
... | the_stack_v2_python_sparse | authors/apps/comments/views.py | andela/Ah-backend-xmen | train | 4 | |
ada8ccf58df8e113b632e5dda96b142d18234d1e | [
"self.k = k\nself.nums = nums\nheapq.heapify(self.nums)\nwhile len(self.nums) > k:\n heapq.heappop(self.nums)",
"if len(self.nums) < self.k:\n heapq.heappush(self.nums, val)\nelif val > self.nums[0]:\n heapq.heapreplace(self.nums, val)\nreturn self.nums[0]"
] | <|body_start_0|>
self.k = k
self.nums = nums
heapq.heapify(self.nums)
while len(self.nums) > k:
heapq.heappop(self.nums)
<|end_body_0|>
<|body_start_1|>
if len(self.nums) < self.k:
heapq.heappush(self.nums, val)
elif val > self.nums[0]:
... | KthLargest1 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KthLargest1:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.k = k
self.nums = nums
heapq.heapify... | stack_v2_sparse_classes_75kplus_train_003707 | 1,362 | no_license | [
{
"docstring": ":type k: int :type nums: List[int]",
"name": "__init__",
"signature": "def __init__(self, k, nums)"
},
{
"docstring": ":type val: int :rtype: int",
"name": "add",
"signature": "def add(self, val)"
}
] | 2 | stack_v2_sparse_classes_30k_train_045183 | Implement the Python class `KthLargest1` described below.
Class description:
Implement the KthLargest1 class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int | Implement the Python class `KthLargest1` described below.
Class description:
Implement the KthLargest1 class.
Method signatures and docstrings:
- def __init__(self, k, nums): :type k: int :type nums: List[int]
- def add(self, val): :type val: int :rtype: int
<|skeleton|>
class KthLargest1:
def __init__(self, k,... | d4a33dc28a6d3f99d5179fdb6a83b2ab8c5a0beb | <|skeleton|>
class KthLargest1:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
<|body_0|>
def add(self, val):
""":type val: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class KthLargest1:
def __init__(self, k, nums):
""":type k: int :type nums: List[int]"""
self.k = k
self.nums = nums
heapq.heapify(self.nums)
while len(self.nums) > k:
heapq.heappop(self.nums)
def add(self, val):
""":type val: int :rtype: int"""
... | the_stack_v2_python_sparse | leetcode/703_kth_largest_num.py | 294150302hxq/python_learn | train | 0 | |
b9ff1d46ae3c554191dbefca37085bd0d8db7ccd | [
"self.input_directory = Path(input_directory)\nself.output_directory = Path(output_directory)\nself.output_directory.mkdir(parents=True, exist_ok=False)",
"dataset_gdf = pd.concat(dataset)\ndataset_gdf['original_file'] = dataset_gdf['original_file'].astype(str)\ndataset_gdf.to_file(str(self.output_directory / f'f... | <|body_start_0|>
self.input_directory = Path(input_directory)
self.output_directory = Path(output_directory)
self.output_directory.mkdir(parents=True, exist_ok=False)
<|end_body_0|>
<|body_start_1|>
dataset_gdf = pd.concat(dataset)
dataset_gdf['original_file'] = dataset_gdf['ori... | The GeoDataFrame generator class that turns txt files into geojson. | GeoDataGenerator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GeoDataGenerator:
"""The GeoDataFrame generator class that turns txt files into geojson."""
def __init__(self, input_directory, output_directory):
"""Initialize the GeoDataGenerator. Args: input_directory (str): Directory with images. output_directory (str): Target directory for geoj... | stack_v2_sparse_classes_75kplus_train_003708 | 5,325 | no_license | [
{
"docstring": "Initialize the GeoDataGenerator. Args: input_directory (str): Directory with images. output_directory (str): Target directory for geojson files.",
"name": "__init__",
"signature": "def __init__(self, input_directory, output_directory)"
},
{
"docstring": "Save a block of images. A... | 5 | stack_v2_sparse_classes_30k_val_000867 | Implement the Python class `GeoDataGenerator` described below.
Class description:
The GeoDataFrame generator class that turns txt files into geojson.
Method signatures and docstrings:
- def __init__(self, input_directory, output_directory): Initialize the GeoDataGenerator. Args: input_directory (str): Directory with ... | Implement the Python class `GeoDataGenerator` described below.
Class description:
The GeoDataFrame generator class that turns txt files into geojson.
Method signatures and docstrings:
- def __init__(self, input_directory, output_directory): Initialize the GeoDataGenerator. Args: input_directory (str): Directory with ... | 1b953d87968dac46ebbc9b1d5c254ea9493ee328 | <|skeleton|>
class GeoDataGenerator:
"""The GeoDataFrame generator class that turns txt files into geojson."""
def __init__(self, input_directory, output_directory):
"""Initialize the GeoDataGenerator. Args: input_directory (str): Directory with images. output_directory (str): Target directory for geoj... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GeoDataGenerator:
"""The GeoDataFrame generator class that turns txt files into geojson."""
def __init__(self, input_directory, output_directory):
"""Initialize the GeoDataGenerator. Args: input_directory (str): Directory with images. output_directory (str): Target directory for geojson files."""... | the_stack_v2_python_sparse | fmlwright/dataset_builder/GeoDataGenerator.py | rgresia-umd/fml-wright | train | 0 |
595cb31dca5acbe571ac64480c620e916df9724a | [
"self.pick = pick\nif self.pick != 3:\n raise NotImplementedError(\"Haven't implemented pick 4\")\nself.bet_type = bet_type\nself.amount = amount\nself.chosen = chosen",
"if self.bet_type == BetType.THREE_WAY_BOX:\n if not self.chosen.has_double():\n raise TypeError('Three way box demands a bet with ... | <|body_start_0|>
self.pick = pick
if self.pick != 3:
raise NotImplementedError("Haven't implemented pick 4")
self.bet_type = bet_type
self.amount = amount
self.chosen = chosen
<|end_body_0|>
<|body_start_1|>
if self.bet_type == BetType.THREE_WAY_BOX:
... | Represents a bet type and an amount. Can only represent a simple bet. | Bet | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Bet:
"""Represents a bet type and an amount. Can only represent a simple bet."""
def __init__(self, pick, bet_type, amount, chosen):
""":type pick: int :type bet_type: BetType :type amount: int|float :type chosen: Digits"""
<|body_0|>
def validate(self):
"""Is th... | stack_v2_sparse_classes_75kplus_train_003709 | 9,444 | permissive | [
{
"docstring": ":type pick: int :type bet_type: BetType :type amount: int|float :type chosen: Digits",
"name": "__init__",
"signature": "def __init__(self, pick, bet_type, amount, chosen)"
},
{
"docstring": "Is this an screwed up bet? :return:",
"name": "validate",
"signature": "def vali... | 3 | stack_v2_sparse_classes_30k_val_002415 | Implement the Python class `Bet` described below.
Class description:
Represents a bet type and an amount. Can only represent a simple bet.
Method signatures and docstrings:
- def __init__(self, pick, bet_type, amount, chosen): :type pick: int :type bet_type: BetType :type amount: int|float :type chosen: Digits
- def ... | Implement the Python class `Bet` described below.
Class description:
Represents a bet type and an amount. Can only represent a simple bet.
Method signatures and docstrings:
- def __init__(self, pick, bet_type, amount, chosen): :type pick: int :type bet_type: BetType :type amount: int|float :type chosen: Digits
- def ... | 9551cf89c55974ec51eec1daeacad1a5e4c7d8c3 | <|skeleton|>
class Bet:
"""Represents a bet type and an amount. Can only represent a simple bet."""
def __init__(self, pick, bet_type, amount, chosen):
""":type pick: int :type bet_type: BetType :type amount: int|float :type chosen: Digits"""
<|body_0|>
def validate(self):
"""Is th... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Bet:
"""Represents a bet type and an amount. Can only represent a simple bet."""
def __init__(self, pick, bet_type, amount, chosen):
""":type pick: int :type bet_type: BetType :type amount: int|float :type chosen: Digits"""
self.pick = pick
if self.pick != 3:
raise Not... | the_stack_v2_python_sparse | pick_three/ticket.py | matthewdeanmartin/pick_three | train | 1 |
c8d19c19599c89744eb69083827f33e14ea43c10 | [
"self._base_path = base_path\nself._tokenizer = tokenization.FullTokenizer(vocab_path)\nwith open(config_path) as f:\n self._conf = json.loads(f.read())\nconfig = modeling.BertConfig(**self._conf)\nself._inputs = tf.placeholder(shape=[None, None], dtype=tf.int32)\nself._mask = tf.placeholder(shape=[None, None], ... | <|body_start_0|>
self._base_path = base_path
self._tokenizer = tokenization.FullTokenizer(vocab_path)
with open(config_path) as f:
self._conf = json.loads(f.read())
config = modeling.BertConfig(**self._conf)
self._inputs = tf.placeholder(shape=[None, None], dtype=tf.i... | a class for encoding paragraphs | BERT_encoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BERT_encoder:
"""a class for encoding paragraphs"""
def __init__(self, config_path, vocab_path, base_path):
"""making instance of encoder and bert model"""
<|body_0|>
def encode(self, batch):
""":param batch: a list of sequences to be encoded :return: - a numpy a... | stack_v2_sparse_classes_75kplus_train_003710 | 4,242 | no_license | [
{
"docstring": "making instance of encoder and bert model",
"name": "__init__",
"signature": "def __init__(self, config_path, vocab_path, base_path)"
},
{
"docstring": ":param batch: a list of sequences to be encoded :return: - a numpy array of shape [batch_size,embedding(768)]",
"name": "en... | 2 | stack_v2_sparse_classes_30k_train_019697 | Implement the Python class `BERT_encoder` described below.
Class description:
a class for encoding paragraphs
Method signatures and docstrings:
- def __init__(self, config_path, vocab_path, base_path): making instance of encoder and bert model
- def encode(self, batch): :param batch: a list of sequences to be encoded... | Implement the Python class `BERT_encoder` described below.
Class description:
a class for encoding paragraphs
Method signatures and docstrings:
- def __init__(self, config_path, vocab_path, base_path): making instance of encoder and bert model
- def encode(self, batch): :param batch: a list of sequences to be encoded... | 612b34e7a8cd3854b96c39065b0136885ecbd10d | <|skeleton|>
class BERT_encoder:
"""a class for encoding paragraphs"""
def __init__(self, config_path, vocab_path, base_path):
"""making instance of encoder and bert model"""
<|body_0|>
def encode(self, batch):
""":param batch: a list of sequences to be encoded :return: - a numpy a... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BERT_encoder:
"""a class for encoding paragraphs"""
def __init__(self, config_path, vocab_path, base_path):
"""making instance of encoder and bert model"""
self._base_path = base_path
self._tokenizer = tokenization.FullTokenizer(vocab_path)
with open(config_path) as f:
... | the_stack_v2_python_sparse | BERT/make_dataset_from_indices.py | ShenakhtPajouh/transposition-simple | train | 0 |
62e58a03fb05165bd94ded54580f64e3d31edae2 | [
"def easyEnqueue(queue, num, k):\n if len(queue) == k:\n queue.popleft()\n maxValue, maxIndex = (num, len(queue))\n for index, v in enumerate(queue):\n if v > maxValue:\n maxValue = v\n maxIndex = index\n for index in range(maxIndex):\n ... | <|body_start_0|>
def easyEnqueue(queue, num, k):
if len(queue) == k:
queue.popleft()
maxValue, maxIndex = (num, len(queue))
for index, v in enumerate(queue):
if v > maxValue:
maxValue = v
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxSlidingWindow(self, nums, k):
"""(knowledge) 思路： 1. 用一个队列记录当前处于窗口内的值，这个队列有如下性质： - 队列中的元素不会超过窗口大小k； - 保证队头的元素总是队列里面最大的； 2. 每次有数据入队时都执行如下流程： - 判断当前队列长度是否为k，如果是则首先pop一个元素，并依次比对，进行若干次出队，把当前队列的最大值排到队首； - 然后将队首元素与预入队元素比对，如果小于等于将要入队的元素，则出队； - 循环执行上一步骤，直到队列为空或者队首元素大于将要入队的元素； - 最... | stack_v2_sparse_classes_75kplus_train_003711 | 6,702 | no_license | [
{
"docstring": "(knowledge) 思路： 1. 用一个队列记录当前处于窗口内的值，这个队列有如下性质： - 队列中的元素不会超过窗口大小k； - 保证队头的元素总是队列里面最大的； 2. 每次有数据入队时都执行如下流程： - 判断当前队列长度是否为k，如果是则首先pop一个元素，并依次比对，进行若干次出队，把当前队列的最大值排到队首； - 然后将队首元素与预入队元素比对，如果小于等于将要入队的元素，则出队； - 循环执行上一步骤，直到队列为空或者队首元素大于将要入队的元素； - 最后将要入队的元素入队。 3. 初始时，先用步骤2的方法，入队k-1个元素，从第k个元素开始，每次入队完，队首的元素即... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSlidingWindow(self, nums, k): (knowledge) 思路： 1. 用一个队列记录当前处于窗口内的值，这个队列有如下性质： - 队列中的元素不会超过窗口大小k； - 保证队头的元素总是队列里面最大的； 2. 每次有数据入队时都执行如下流程： - 判断当前队列长度是否为k，如果是则首先pop一个元素，并依次比对，... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSlidingWindow(self, nums, k): (knowledge) 思路： 1. 用一个队列记录当前处于窗口内的值，这个队列有如下性质： - 队列中的元素不会超过窗口大小k； - 保证队头的元素总是队列里面最大的； 2. 每次有数据入队时都执行如下流程： - 判断当前队列长度是否为k，如果是则首先pop一个元素，并依次比对，... | 19ea28c38762c65318275007932786e648a8b415 | <|skeleton|>
class Solution:
def maxSlidingWindow(self, nums, k):
"""(knowledge) 思路： 1. 用一个队列记录当前处于窗口内的值，这个队列有如下性质： - 队列中的元素不会超过窗口大小k； - 保证队头的元素总是队列里面最大的； 2. 每次有数据入队时都执行如下流程： - 判断当前队列长度是否为k，如果是则首先pop一个元素，并依次比对，进行若干次出队，把当前队列的最大值排到队首； - 然后将队首元素与预入队元素比对，如果小于等于将要入队的元素，则出队； - 循环执行上一步骤，直到队列为空或者队首元素大于将要入队的元素； - 最... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def maxSlidingWindow(self, nums, k):
"""(knowledge) 思路： 1. 用一个队列记录当前处于窗口内的值，这个队列有如下性质： - 队列中的元素不会超过窗口大小k； - 保证队头的元素总是队列里面最大的； 2. 每次有数据入队时都执行如下流程： - 判断当前队列长度是否为k，如果是则首先pop一个元素，并依次比对，进行若干次出队，把当前队列的最大值排到队首； - 然后将队首元素与预入队元素比对，如果小于等于将要入队的元素，则出队； - 循环执行上一步骤，直到队列为空或者队首元素大于将要入队的元素； - 最后将要入队的元素入队。 3.... | the_stack_v2_python_sparse | chapter3/13_sliding-window-maximum.py | SunnyQjm/algorithm-review | train | 2 | |
337b757021637c1ea01c47410999d9f0d4ff125c | [
"from math import e, log\nleft = int(e ** (0.5 * log(val)))\nright = left + 1\nreturn left if right * right > val else right",
"if val <= 2:\n return val\nleft, right = (2, val // 2)\nwhile left <= right:\n pivot = left + (right - left) // 2\n res = pivot * pivot\n if res < val:\n left = pivot ... | <|body_start_0|>
from math import e, log
left = int(e ** (0.5 * log(val)))
right = left + 1
return left if right * right > val else right
<|end_body_0|>
<|body_start_1|>
if val <= 2:
return val
left, right = (2, val // 2)
while left <= right:
... | SquareRoot | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SquareRoot:
def get_square_root_(self, val: int) -> int:
"""Approach: Pocket Calculator input: val, output: res Formulae: left-------------right res^2 <= val < (res + 1) :param val: :return:"""
<|body_0|>
def get_square_root__(self, val: int) -> int:
"""Approach: Bin... | stack_v2_sparse_classes_75kplus_train_003712 | 1,738 | no_license | [
{
"docstring": "Approach: Pocket Calculator input: val, output: res Formulae: left-------------right res^2 <= val < (res + 1) :param val: :return:",
"name": "get_square_root_",
"signature": "def get_square_root_(self, val: int) -> int"
},
{
"docstring": "Approach: Binary Search input: val, outpu... | 3 | stack_v2_sparse_classes_30k_train_011270 | Implement the Python class `SquareRoot` described below.
Class description:
Implement the SquareRoot class.
Method signatures and docstrings:
- def get_square_root_(self, val: int) -> int: Approach: Pocket Calculator input: val, output: res Formulae: left-------------right res^2 <= val < (res + 1) :param val: :return... | Implement the Python class `SquareRoot` described below.
Class description:
Implement the SquareRoot class.
Method signatures and docstrings:
- def get_square_root_(self, val: int) -> int: Approach: Pocket Calculator input: val, output: res Formulae: left-------------right res^2 <= val < (res + 1) :param val: :return... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class SquareRoot:
def get_square_root_(self, val: int) -> int:
"""Approach: Pocket Calculator input: val, output: res Formulae: left-------------right res^2 <= val < (res + 1) :param val: :return:"""
<|body_0|>
def get_square_root__(self, val: int) -> int:
"""Approach: Bin... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SquareRoot:
def get_square_root_(self, val: int) -> int:
"""Approach: Pocket Calculator input: val, output: res Formulae: left-------------right res^2 <= val < (res + 1) :param val: :return:"""
from math import e, log
left = int(e ** (0.5 * log(val)))
right = left + 1
r... | the_stack_v2_python_sparse | math_and_srings/square_root_x.py | Shiv2157k/leet_code | train | 1 | |
a8d25053d0ed335df10d853fd0cef4679774bd62 | [
"if 'id' not in kwargs and ('name' not in kwargs or 'version' not in kwargs) and ('registered_name' not in kwargs or ('pipeline' not in kwargs and 'pipeline_kwargs' not in kwargs)):\n raise TrainingError('Need to pass at least one of: `id`, `name, version`, `registered_name, pipeline`, `registered_name, pipeline... | <|body_start_0|>
if 'id' not in kwargs and ('name' not in kwargs or 'version' not in kwargs) and ('registered_name' not in kwargs or ('pipeline' not in kwargs and 'pipeline_kwargs' not in kwargs)):
raise TrainingError('Need to pass at least one of: `id`, `name, version`, `registered_name, pipeline`,... | ModelCreator | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModelCreator:
def determine_filters(cls, strict: bool=False, **kwargs) -> Tuple[Model, Dict[str, Any]]:
"""stateless method to determine which filters to apply when looking for existing persistable Returns: database class, filter dictionary :param registered_name: Class name registered i... | stack_v2_sparse_classes_75kplus_train_003713 | 17,135 | permissive | [
{
"docstring": "stateless method to determine which filters to apply when looking for existing persistable Returns: database class, filter dictionary :param registered_name: Class name registered in SimpleML :param strict: whether to fit objects first before assuming they are identical In theory if all inputs a... | 2 | stack_v2_sparse_classes_30k_train_030210 | Implement the Python class `ModelCreator` described below.
Class description:
Implement the ModelCreator class.
Method signatures and docstrings:
- def determine_filters(cls, strict: bool=False, **kwargs) -> Tuple[Model, Dict[str, Any]]: stateless method to determine which filters to apply when looking for existing p... | Implement the Python class `ModelCreator` described below.
Class description:
Implement the ModelCreator class.
Method signatures and docstrings:
- def determine_filters(cls, strict: bool=False, **kwargs) -> Tuple[Model, Dict[str, Any]]: stateless method to determine which filters to apply when looking for existing p... | c7cdf1fa90b373025da48aa85bf9f0d3792ce494 | <|skeleton|>
class ModelCreator:
def determine_filters(cls, strict: bool=False, **kwargs) -> Tuple[Model, Dict[str, Any]]:
"""stateless method to determine which filters to apply when looking for existing persistable Returns: database class, filter dictionary :param registered_name: Class name registered i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ModelCreator:
def determine_filters(cls, strict: bool=False, **kwargs) -> Tuple[Model, Dict[str, Any]]:
"""stateless method to determine which filters to apply when looking for existing persistable Returns: database class, filter dictionary :param registered_name: Class name registered in SimpleML :pa... | the_stack_v2_python_sparse | simpleml/utils/training/create_persistable.py | eyadgaran/SimpleML | train | 15 | |
b54dee2d24e8182ed9f7d8475f85b3db7750cdd1 | [
"self.catg = syms.getSyntaxTypeIndexNumber(category)\nself.synf = None\nself.semf = None\nself.hpnc = {}\nbrkg = _FS(syms, '[' + sID + sBRK + ']', True)\nzero = ellyBits.EllyBits()\nfor sky in smfs.keys():\n smfs[sky] = _FS(syms, smfs[sky], True)\nfor defn in defns:\n pc = defn[0]\n if len(defn) > 1:\n ... | <|body_start_0|>
self.catg = syms.getSyntaxTypeIndexNumber(category)
self.synf = None
self.semf = None
self.hpnc = {}
brkg = _FS(syms, '[' + sID + sBRK + ']', True)
zero = ellyBits.EllyBits()
for sky in smfs.keys():
smfs[sky] = _FS(syms, smfs[sky], Tru... | recognizer to support parsing attributes: catg - syntactic category for recognized punctuation synf - syntactic features semf - semantic features hpnc - hash lookup for punctuation chars | PunctuationRecognizer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PunctuationRecognizer:
"""recognizer to support parsing attributes: catg - syntactic category for recognized punctuation synf - syntactic features semf - semantic features hpnc - hash lookup for punctuation chars"""
def __init__(self, syms):
"""initialization arguments: self - syms -... | stack_v2_sparse_classes_75kplus_train_003714 | 7,773 | no_license | [
{
"docstring": "initialization arguments: self - syms - Elly symbol table exceptions: FormatFailure on error",
"name": "__init__",
"signature": "def __init__(self, syms)"
},
{
"docstring": "check whether list of chars corresponds to punctuation arguments: self - s - list or string of chars to ch... | 2 | stack_v2_sparse_classes_30k_train_027995 | Implement the Python class `PunctuationRecognizer` described below.
Class description:
recognizer to support parsing attributes: catg - syntactic category for recognized punctuation synf - syntactic features semf - semantic features hpnc - hash lookup for punctuation chars
Method signatures and docstrings:
- def __in... | Implement the Python class `PunctuationRecognizer` described below.
Class description:
recognizer to support parsing attributes: catg - syntactic category for recognized punctuation synf - syntactic features semf - semantic features hpnc - hash lookup for punctuation chars
Method signatures and docstrings:
- def __in... | bb6e4aef283229f1dbf6397112a7f5772d4020e5 | <|skeleton|>
class PunctuationRecognizer:
"""recognizer to support parsing attributes: catg - syntactic category for recognized punctuation synf - syntactic features semf - semantic features hpnc - hash lookup for punctuation chars"""
def __init__(self, syms):
"""initialization arguments: self - syms -... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PunctuationRecognizer:
"""recognizer to support parsing attributes: catg - syntactic category for recognized punctuation synf - syntactic features semf - semantic features hpnc - hash lookup for punctuation chars"""
def __init__(self, syms):
"""initialization arguments: self - syms - Elly symbol ... | the_stack_v2_python_sparse | punctuationRecognizer.py | prohippo/pyellytoo | train | 0 |
a37c02a80373a12f9bf9c3db57155b7b974f2f49 | [
"super().__init__(name)\nself.model = model\nself.alphabet = alphabet",
"one_hots = np.array([s_utils.string_to_one_hot(seq, self.alphabet) for seq in sequences])\nflattened = one_hots.reshape(one_hots.shape[0], one_hots.shape[1] * one_hots.shape[2])\nself.model.fit(flattened, labels)"
] | <|body_start_0|>
super().__init__(name)
self.model = model
self.alphabet = alphabet
<|end_body_0|>
<|body_start_1|>
one_hots = np.array([s_utils.string_to_one_hot(seq, self.alphabet) for seq in sequences])
flattened = one_hots.reshape(one_hots.shape[0], one_hots.shape[1] * one_h... | Base sklearn model wrapper. | SklearnModel | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SklearnModel:
"""Base sklearn model wrapper."""
def __init__(self, model, alphabet, name):
"""Args: model: sklearn model to wrap. alphabet: Alphabet string. name: Human-readable short model descriptipon (for logging)."""
<|body_0|>
def train(self, sequences, labels):
... | stack_v2_sparse_classes_75kplus_train_003715 | 2,860 | permissive | [
{
"docstring": "Args: model: sklearn model to wrap. alphabet: Alphabet string. name: Human-readable short model descriptipon (for logging).",
"name": "__init__",
"signature": "def __init__(self, model, alphabet, name)"
},
{
"docstring": "Flatten one-hot sequences and train model using `model.fit... | 2 | stack_v2_sparse_classes_30k_train_009294 | Implement the Python class `SklearnModel` described below.
Class description:
Base sklearn model wrapper.
Method signatures and docstrings:
- def __init__(self, model, alphabet, name): Args: model: sklearn model to wrap. alphabet: Alphabet string. name: Human-readable short model descriptipon (for logging).
- def tra... | Implement the Python class `SklearnModel` described below.
Class description:
Base sklearn model wrapper.
Method signatures and docstrings:
- def __init__(self, model, alphabet, name): Args: model: sklearn model to wrap. alphabet: Alphabet string. name: Human-readable short model descriptipon (for logging).
- def tra... | 744e792456d93e8c48fc58220689c0b4cff6ded9 | <|skeleton|>
class SklearnModel:
"""Base sklearn model wrapper."""
def __init__(self, model, alphabet, name):
"""Args: model: sklearn model to wrap. alphabet: Alphabet string. name: Human-readable short model descriptipon (for logging)."""
<|body_0|>
def train(self, sequences, labels):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SklearnModel:
"""Base sklearn model wrapper."""
def __init__(self, model, alphabet, name):
"""Args: model: sklearn model to wrap. alphabet: Alphabet string. name: Human-readable short model descriptipon (for logging)."""
super().__init__(name)
self.model = model
self.alpha... | the_stack_v2_python_sparse | flexs/baselines/models/sklearn_models.py | jonshao/FLEXS | train | 0 |
5e9a1244d481fb9db0b1459f04676a1ec401c08b | [
"maximallyOverlapObjects, overlappingAreas = self.findMaximallyOverlapObjects(segm, gold)\ngoldAreas = self.findAreas(gold)\nsegmentedNo = overlappingAreas.shape[0]\ngoldNo = goldAreas.shape[0]\nTP, FP, FN = (0, 0, 0)\nfor i in range(segmentedNo):\n if int(maximallyOverlapObjects[i]) >= 0 and overlappingAreas[i]... | <|body_start_0|>
maximallyOverlapObjects, overlappingAreas = self.findMaximallyOverlapObjects(segm, gold)
goldAreas = self.findAreas(gold)
segmentedNo = overlappingAreas.shape[0]
goldNo = goldAreas.shape[0]
TP, FP, FN = (0, 0, 0)
for i in range(segmentedNo):
i... | ObjectBasedMetrics | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ObjectBasedMetrics:
def calculate4Detection(self, segm, gold):
"""Args: segm (np.ndarray) : (H,W) connected components of segmentation gold (np.ndarray) : (H,W) connected components of annotation Returns: TP (int) : true positives FP (int) : false positives FN (int) : false negatives"""
... | stack_v2_sparse_classes_75kplus_train_003716 | 44,704 | no_license | [
{
"docstring": "Args: segm (np.ndarray) : (H,W) connected components of segmentation gold (np.ndarray) : (H,W) connected components of annotation Returns: TP (int) : true positives FP (int) : false positives FN (int) : false negatives",
"name": "calculate4Detection",
"signature": "def calculate4Detectio... | 2 | null | Implement the Python class `ObjectBasedMetrics` described below.
Class description:
Implement the ObjectBasedMetrics class.
Method signatures and docstrings:
- def calculate4Detection(self, segm, gold): Args: segm (np.ndarray) : (H,W) connected components of segmentation gold (np.ndarray) : (H,W) connected components... | Implement the Python class `ObjectBasedMetrics` described below.
Class description:
Implement the ObjectBasedMetrics class.
Method signatures and docstrings:
- def calculate4Detection(self, segm, gold): Args: segm (np.ndarray) : (H,W) connected components of segmentation gold (np.ndarray) : (H,W) connected components... | 193fc372d8cd5c9c465996b594ec0993af1d5a2e | <|skeleton|>
class ObjectBasedMetrics:
def calculate4Detection(self, segm, gold):
"""Args: segm (np.ndarray) : (H,W) connected components of segmentation gold (np.ndarray) : (H,W) connected components of annotation Returns: TP (int) : true positives FP (int) : false positives FN (int) : false negatives"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ObjectBasedMetrics:
def calculate4Detection(self, segm, gold):
"""Args: segm (np.ndarray) : (H,W) connected components of segmentation gold (np.ndarray) : (H,W) connected components of annotation Returns: TP (int) : true positives FP (int) : false positives FN (int) : false negatives"""
maxima... | the_stack_v2_python_sparse | src/metrics.py | furkanh/image-segmentation-with-shape-preserving-loss | train | 2 | |
058183e67a72dd972209650d1cb57f9176262df5 | [
"if target == 0:\n res.append(tem_res)\n return\nif target < candidates[index]:\n return\nfor i in range(index, len(candidates)):\n if target < candidates[i]:\n break\n self.curSum(candidates, i, target - candidates[i], tem_res + [candidates[i]], res)",
"res = []\ncandidates.sort()\nself.cur... | <|body_start_0|>
if target == 0:
res.append(tem_res)
return
if target < candidates[index]:
return
for i in range(index, len(candidates)):
if target < candidates[i]:
break
self.curSum(candidates, i, target - candidates[i]... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def curSum(self, candidates, index, target, tem_res, res):
""":param candidates: :param target: :param tem_res: 当前的结果 :param res: 全局的结果 :return:当前搜索的结果"""
<|body_0|>
def combinationSum(self, candidates, target):
""":type candidates: List[int] :type target: ... | stack_v2_sparse_classes_75kplus_train_003717 | 1,067 | no_license | [
{
"docstring": ":param candidates: :param target: :param tem_res: 当前的结果 :param res: 全局的结果 :return:当前搜索的结果",
"name": "curSum",
"signature": "def curSum(self, candidates, index, target, tem_res, res)"
},
{
"docstring": ":type candidates: List[int] :type target: int :rtype: List[List[int]] :组合相加",
... | 2 | stack_v2_sparse_classes_30k_train_003973 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def curSum(self, candidates, index, target, tem_res, res): :param candidates: :param target: :param tem_res: 当前的结果 :param res: 全局的结果 :return:当前搜索的结果
- def combinationSum(self, ca... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def curSum(self, candidates, index, target, tem_res, res): :param candidates: :param target: :param tem_res: 当前的结果 :param res: 全局的结果 :return:当前搜索的结果
- def combinationSum(self, ca... | 45fafcc5dd8f3a9dd26984dc6e82441cc2e8f8d7 | <|skeleton|>
class Solution:
def curSum(self, candidates, index, target, tem_res, res):
""":param candidates: :param target: :param tem_res: 当前的结果 :param res: 全局的结果 :return:当前搜索的结果"""
<|body_0|>
def combinationSum(self, candidates, target):
""":type candidates: List[int] :type target: ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def curSum(self, candidates, index, target, tem_res, res):
""":param candidates: :param target: :param tem_res: 当前的结果 :param res: 全局的结果 :return:当前搜索的结果"""
if target == 0:
res.append(tem_res)
return
if target < candidates[index]:
return
... | the_stack_v2_python_sparse | T39.py | zhanggyang/leedcode | train | 0 | |
66239f0d2abc00f54748886bbc94f68419ad962a | [
"super(FileManager, self).__init__(parent)\nself.parent = parent\nself.ctaEngine = ctaEngine\nself.eventEngine = eventEngine\nself.setFixedWidth(420)\nself.widgetDict = {}\nself.initUi()",
"self.setWindowTitle(u'策略管理')\nQtCore.QTextCodec.setCodecForTr(QtCore.QTextCodec.codecForName('utf-8'))\nhbox = QtGui.QHBoxLa... | <|body_start_0|>
super(FileManager, self).__init__(parent)
self.parent = parent
self.ctaEngine = ctaEngine
self.eventEngine = eventEngine
self.setFixedWidth(420)
self.widgetDict = {}
self.initUi()
<|end_body_0|>
<|body_start_1|>
self.setWindowTitle(u'策略管理... | 文件管理 | FileManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileManager:
"""文件管理"""
def __init__(self, ctaEngine, eventEngine, parent=None):
"""Constructor"""
<|body_0|>
def initUi(self):
"""初始化界面"""
<|body_1|>
def addStrategy(self, index):
"""显示策略"""
<|body_2|>
def add(self, filename):
... | stack_v2_sparse_classes_75kplus_train_003718 | 27,775 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, ctaEngine, eventEngine, parent=None)"
},
{
"docstring": "初始化界面",
"name": "initUi",
"signature": "def initUi(self)"
},
{
"docstring": "显示策略",
"name": "addStrategy",
"signature": "def addStra... | 5 | stack_v2_sparse_classes_30k_train_047875 | Implement the Python class `FileManager` described below.
Class description:
文件管理
Method signatures and docstrings:
- def __init__(self, ctaEngine, eventEngine, parent=None): Constructor
- def initUi(self): 初始化界面
- def addStrategy(self, index): 显示策略
- def add(self, filename): 新增回测组合
- def data(self): 加载数据 | Implement the Python class `FileManager` described below.
Class description:
文件管理
Method signatures and docstrings:
- def __init__(self, ctaEngine, eventEngine, parent=None): Constructor
- def initUi(self): 初始化界面
- def addStrategy(self, index): 显示策略
- def add(self, filename): 新增回测组合
- def data(self): 加载数据
<|skeleton... | 97707a403c3300753d988167beb6759e7ee729dc | <|skeleton|>
class FileManager:
"""文件管理"""
def __init__(self, ctaEngine, eventEngine, parent=None):
"""Constructor"""
<|body_0|>
def initUi(self):
"""初始化界面"""
<|body_1|>
def addStrategy(self, index):
"""显示策略"""
<|body_2|>
def add(self, filename):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FileManager:
"""文件管理"""
def __init__(self, ctaEngine, eventEngine, parent=None):
"""Constructor"""
super(FileManager, self).__init__(parent)
self.parent = parent
self.ctaEngine = ctaEngine
self.eventEngine = eventEngine
self.setFixedWidth(420)
self.... | the_stack_v2_python_sparse | uiCtaWidget.py | rlcjj/PythonLab | train | 1 |
35a54e0fb129c33ad1aeb5a68fa1648a213625e9 | [
"self.id = id\nself.amount = amount\nself.posted_date = posted_date\nself.description = description\nself.normalized_payee = normalized_payee\nself.institution_transaction_id = institution_transaction_id\nself.category = category\nself.memo = memo\nself.additional_properties = additional_properties",
"if dictiona... | <|body_start_0|>
self.id = id
self.amount = amount
self.posted_date = posted_date
self.description = description
self.normalized_payee = normalized_payee
self.institution_transaction_id = institution_transaction_id
self.category = category
self.memo = memo... | Implementation of the 'Transactions Report Transaction' model. The fields used in the Transactions Report Transactions record Attributes: id (long|int): The Finicity ID of the financial transaction. amount (float): The total amount of the transaction. Transactions for deposits are positive values, and withdrawals and d... | TransactionsReportTransaction | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TransactionsReportTransaction:
"""Implementation of the 'Transactions Report Transaction' model. The fields used in the Transactions Report Transactions record Attributes: id (long|int): The Finicity ID of the financial transaction. amount (float): The total amount of the transaction. Transaction... | stack_v2_sparse_classes_75kplus_train_003719 | 4,376 | permissive | [
{
"docstring": "Constructor for the TransactionsReportTransaction class",
"name": "__init__",
"signature": "def __init__(self, id=None, amount=None, posted_date=None, description=None, normalized_payee=None, institution_transaction_id=None, category=None, memo=None, additional_properties={})"
},
{
... | 2 | stack_v2_sparse_classes_30k_train_001376 | Implement the Python class `TransactionsReportTransaction` described below.
Class description:
Implementation of the 'Transactions Report Transaction' model. The fields used in the Transactions Report Transactions record Attributes: id (long|int): The Finicity ID of the financial transaction. amount (float): The total... | Implement the Python class `TransactionsReportTransaction` described below.
Class description:
Implementation of the 'Transactions Report Transaction' model. The fields used in the Transactions Report Transactions record Attributes: id (long|int): The Finicity ID of the financial transaction. amount (float): The total... | b2ab1ded435db75c78d42261f5e4acd2a3061487 | <|skeleton|>
class TransactionsReportTransaction:
"""Implementation of the 'Transactions Report Transaction' model. The fields used in the Transactions Report Transactions record Attributes: id (long|int): The Finicity ID of the financial transaction. amount (float): The total amount of the transaction. Transaction... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TransactionsReportTransaction:
"""Implementation of the 'Transactions Report Transaction' model. The fields used in the Transactions Report Transactions record Attributes: id (long|int): The Finicity ID of the financial transaction. amount (float): The total amount of the transaction. Transactions for deposit... | the_stack_v2_python_sparse | finicityapi/models/transactions_report_transaction.py | monarchmoney/finicity-python | train | 0 |
55d64fe317bd1244c5f485df7ba11465887ac780 | [
"session = None\nsession_store_class = get_session_class()\nif app_settings.COOKIE_NAME in request.COOKIES:\n session = session_store_class(key=request.COOKIES[app_settings.COOKIE_NAME].value, request=request)\nif not session:\n session = session_store_class(request=request)\nrequest.session = session",
"re... | <|body_start_0|>
session = None
session_store_class = get_session_class()
if app_settings.COOKIE_NAME in request.COOKIES:
session = session_store_class(key=request.COOKIES[app_settings.COOKIE_NAME].value, request=request)
if not session:
session = session_store_cl... | SessionMiddleware | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SessionMiddleware:
def process_request(self, request):
"""Creates a session instance for the current user."""
<|body_0|>
def process_response(self, request, response):
"""Sets the session cookie with its key"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_003720 | 984 | no_license | [
{
"docstring": "Creates a session instance for the current user.",
"name": "process_request",
"signature": "def process_request(self, request)"
},
{
"docstring": "Sets the session cookie with its key",
"name": "process_response",
"signature": "def process_response(self, request, response... | 2 | stack_v2_sparse_classes_30k_train_011165 | Implement the Python class `SessionMiddleware` described below.
Class description:
Implement the SessionMiddleware class.
Method signatures and docstrings:
- def process_request(self, request): Creates a session instance for the current user.
- def process_response(self, request, response): Sets the session cookie wi... | Implement the Python class `SessionMiddleware` described below.
Class description:
Implement the SessionMiddleware class.
Method signatures and docstrings:
- def process_request(self, request): Creates a session instance for the current user.
- def process_response(self, request, response): Sets the session cookie wi... | 875ac157b207fee80be6841f9b17c41b7069e15d | <|skeleton|>
class SessionMiddleware:
def process_request(self, request):
"""Creates a session instance for the current user."""
<|body_0|>
def process_response(self, request, response):
"""Sets the session cookie with its key"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SessionMiddleware:
def process_request(self, request):
"""Creates a session instance for the current user."""
session = None
session_store_class = get_session_class()
if app_settings.COOKIE_NAME in request.COOKIES:
session = session_store_class(key=request.COOKIES[a... | the_stack_v2_python_sparse | london/apps/sessions/middleware.py | avelino/votacao_paredao_bbb | train | 0 | |
44098b9b12434929a8f5852271bf2b0e1f3be349 | [
"prev_u_next = u_next\nwhile True:\n g = self.system.evaluate(t + dt, tslices.TimeSlice(prev_u_next, domain, time=t)).data\n dg, TOL = self.system.implicit_method_jacobian(t + dt, tslices.TimeSlice(prev_u_next, domain, time=t))\n dg = dg.data\n f = prev_u_next - u_start - dt * g\n df = 1.0 - dt * dg\... | <|body_start_0|>
prev_u_next = u_next
while True:
g = self.system.evaluate(t + dt, tslices.TimeSlice(prev_u_next, domain, time=t)).data
dg, TOL = self.system.implicit_method_jacobian(t + dt, tslices.TimeSlice(prev_u_next, domain, time=t))
dg = dg.data
f = ... | An implementation of the first order implicit Euler method. | ImplicitEuler | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImplicitEuler:
"""An implementation of the first order implicit Euler method."""
def _NR(self, u_start, u_next, t, dt, domain):
"""A Newton-Raphson auxilliary routine for the implementation of the implicit Euler scheme. Parameters ---------- u_start: numpy.ndarray Initial values of t... | stack_v2_sparse_classes_75kplus_train_003721 | 8,908 | no_license | [
{
"docstring": "A Newton-Raphson auxilliary routine for the implementation of the implicit Euler scheme. Parameters ---------- u_start: numpy.ndarray Initial values of the function. u_next: numpy.ndarray The first guess at the next values of the function. t: float Current time. dt: float Current time step. doma... | 2 | stack_v2_sparse_classes_30k_train_004558 | Implement the Python class `ImplicitEuler` described below.
Class description:
An implementation of the first order implicit Euler method.
Method signatures and docstrings:
- def _NR(self, u_start, u_next, t, dt, domain): A Newton-Raphson auxilliary routine for the implementation of the implicit Euler scheme. Paramet... | Implement the Python class `ImplicitEuler` described below.
Class description:
An implementation of the first order implicit Euler method.
Method signatures and docstrings:
- def _NR(self, u_start, u_next, t, dt, domain): A Newton-Raphson auxilliary routine for the implementation of the implicit Euler scheme. Paramet... | 2ce16d776448553e2ae5c45f3cf973c8271aefbf | <|skeleton|>
class ImplicitEuler:
"""An implementation of the first order implicit Euler method."""
def _NR(self, u_start, u_next, t, dt, domain):
"""A Newton-Raphson auxilliary routine for the implementation of the implicit Euler scheme. Parameters ---------- u_start: numpy.ndarray Initial values of t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ImplicitEuler:
"""An implementation of the first order implicit Euler method."""
def _NR(self, u_start, u_next, t, dt, domain):
"""A Newton-Raphson auxilliary routine for the implementation of the implicit Euler scheme. Parameters ---------- u_start: numpy.ndarray Initial values of the function. ... | the_stack_v2_python_sparse | Code/packages/coffee/solvers/solvers.py | mfuphi/SOFTX_2019_93 | train | 0 |
162778e4c689076cff8013dabdf418f09fc7ca6e | [
"super(PreprocessImage, self).__init__(env)\nself.img_size = (height, width)\nself.grayscale = grayscale\nself.crop = crop\nn_colors = 1 if self.grayscale else 3\nself.observation_space = Box(0.0, 1.0, [n_colors, height, width])",
"img = self.crop(img)\nimg = imresize(img, self.img_size)\nif self.grayscale:\n ... | <|body_start_0|>
super(PreprocessImage, self).__init__(env)
self.img_size = (height, width)
self.grayscale = grayscale
self.crop = crop
n_colors = 1 if self.grayscale else 3
self.observation_space = Box(0.0, 1.0, [n_colors, height, width])
<|end_body_0|>
<|body_start_1|>... | PreprocessImage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PreprocessImage:
def __init__(self, env, height=64, width=64, grayscale=True, crop=lambda img: img):
"""A gym wrapper that crops, scales image into the desired shapes and optionally grayscales it."""
<|body_0|>
def _observation(self, img):
"""what happens to the obse... | stack_v2_sparse_classes_75kplus_train_003722 | 1,713 | no_license | [
{
"docstring": "A gym wrapper that crops, scales image into the desired shapes and optionally grayscales it.",
"name": "__init__",
"signature": "def __init__(self, env, height=64, width=64, grayscale=True, crop=lambda img: img)"
},
{
"docstring": "what happens to the observation",
"name": "_... | 2 | stack_v2_sparse_classes_30k_train_047198 | Implement the Python class `PreprocessImage` described below.
Class description:
Implement the PreprocessImage class.
Method signatures and docstrings:
- def __init__(self, env, height=64, width=64, grayscale=True, crop=lambda img: img): A gym wrapper that crops, scales image into the desired shapes and optionally gr... | Implement the Python class `PreprocessImage` described below.
Class description:
Implement the PreprocessImage class.
Method signatures and docstrings:
- def __init__(self, env, height=64, width=64, grayscale=True, crop=lambda img: img): A gym wrapper that crops, scales image into the desired shapes and optionally gr... | 4c145470dfc7b594d479bf60857b6db5c1505eb7 | <|skeleton|>
class PreprocessImage:
def __init__(self, env, height=64, width=64, grayscale=True, crop=lambda img: img):
"""A gym wrapper that crops, scales image into the desired shapes and optionally grayscales it."""
<|body_0|>
def _observation(self, img):
"""what happens to the obse... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PreprocessImage:
def __init__(self, env, height=64, width=64, grayscale=True, crop=lambda img: img):
"""A gym wrapper that crops, scales image into the desired shapes and optionally grayscales it."""
super(PreprocessImage, self).__init__(env)
self.img_size = (height, width)
sel... | the_stack_v2_python_sparse | atari_experiments/src/envs/doom.py | neurips2019submission/Formal-Language-Constraints-for-Markov-Decision-Processes | train | 0 | |
e6a56d67a61e25fb70232eddd9d7590453b19e94 | [
"assert stride is None and size is None or (stride is not None and size is not None), 'Either both or neither stride and size should be None'\nself.cnn_network_dir = cnn_network_dir\nself.batch_size = batch_size\nself.config = config\nself.compare_labels = compare_labels\nself.stride = stride\nself.size = size\nsup... | <|body_start_0|>
assert stride is None and size is None or (stride is not None and size is not None), 'Either both or neither stride and size should be None'
self.cnn_network_dir = cnn_network_dir
self.batch_size = batch_size
self.config = config
self.compare_labels = compare_lab... | Train a CNN | ClassifyCNN | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClassifyCNN:
"""Train a CNN"""
def __init__(self, str_description, cnn_network_dir, batch_size=2000, config=None, compare_labels=False, stride=None, size=None):
"""Initialize TrainCNN item @param str_description: String describing item @param cnn_network_dir: Strining containing the ... | stack_v2_sparse_classes_75kplus_train_003723 | 4,216 | permissive | [
{
"docstring": "Initialize TrainCNN item @param str_description: String describing item @param cnn_network_dir: Strining containing the directiory where the CNN is stored @param batch_size: Batch size to use when classifying with Tensorflow @param config: Additional session configuration dictionary @param compa... | 2 | stack_v2_sparse_classes_30k_train_047302 | Implement the Python class `ClassifyCNN` described below.
Class description:
Train a CNN
Method signatures and docstrings:
- def __init__(self, str_description, cnn_network_dir, batch_size=2000, config=None, compare_labels=False, stride=None, size=None): Initialize TrainCNN item @param str_description: String describ... | Implement the Python class `ClassifyCNN` described below.
Class description:
Train a CNN
Method signatures and docstrings:
- def __init__(self, str_description, cnn_network_dir, batch_size=2000, config=None, compare_labels=False, stride=None, size=None): Initialize TrainCNN item @param str_description: String describ... | 4d22e3ef90ef842d6b390074a8b5deedc7658a2b | <|skeleton|>
class ClassifyCNN:
"""Train a CNN"""
def __init__(self, str_description, cnn_network_dir, batch_size=2000, config=None, compare_labels=False, stride=None, size=None):
"""Initialize TrainCNN item @param str_description: String describing item @param cnn_network_dir: Strining containing the ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ClassifyCNN:
"""Train a CNN"""
def __init__(self, str_description, cnn_network_dir, batch_size=2000, config=None, compare_labels=False, stride=None, size=None):
"""Initialize TrainCNN item @param str_description: String describing item @param cnn_network_dir: Strining containing the directiory wh... | the_stack_v2_python_sparse | pyinsar/processing/discovery/classify_cnn.py | MITeaps/pyinsar | train | 11 |
7039c828a334b8c8837ad6c9ff0d89af7173df4f | [
"if not strs:\n return ''\nif len(strs) == 1:\n return strs[0]\nfor i, j in zip(strs[0], strs[-1]):\n print(str(i) + ' -> ' + str(j))\nprint(strs.sort())\nstrs.sort()\np = ''\nfor x, y in zip(strs[0], strs[-1]):\n if x == y:\n p += x\n else:\n break\nreturn p",
"output = ''\nif strs i... | <|body_start_0|>
if not strs:
return ''
if len(strs) == 1:
return strs[0]
for i, j in zip(strs[0], strs[-1]):
print(str(i) + ' -> ' + str(j))
print(strs.sort())
strs.sort()
p = ''
for x, y in zip(strs[0], strs[-1]):
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestCommonPrefix(self, strs):
""":type strs: List[str] :rtype: str"""
<|body_0|>
def longestCommonPrefix_2(self, strs):
""":type strs: List[str] :rtype: str"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not strs:
re... | stack_v2_sparse_classes_75kplus_train_003724 | 1,058 | no_license | [
{
"docstring": ":type strs: List[str] :rtype: str",
"name": "longestCommonPrefix",
"signature": "def longestCommonPrefix(self, strs)"
},
{
"docstring": ":type strs: List[str] :rtype: str",
"name": "longestCommonPrefix_2",
"signature": "def longestCommonPrefix_2(self, strs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_030026 | 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 longestCommonPrefix_2(self, strs): :type strs: List[str] :rtype: str | 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 longestCommonPrefix_2(self, strs): :type strs: List[str] :rtype: str
<|skeleton|>
class Solution:
... | 15ebd6b76dd1f26bd14ee911e5eb08d6e37db8fd | <|skeleton|>
class Solution:
def longestCommonPrefix(self, strs):
""":type strs: List[str] :rtype: str"""
<|body_0|>
def longestCommonPrefix_2(self, strs):
""":type strs: List[str] :rtype: str"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def longestCommonPrefix(self, strs):
""":type strs: List[str] :rtype: str"""
if not strs:
return ''
if len(strs) == 1:
return strs[0]
for i, j in zip(strs[0], strs[-1]):
print(str(i) + ' -> ' + str(j))
print(strs.sort())
... | the_stack_v2_python_sparse | LongestCommonPrefix.py | manishkumar2k9/GitRepository-LeedCodeSolutions | train | 0 | |
b91ee64dc7ee589c7c29bce5a64d50805a82521a | [
"if 'SF' in user_id:\n res = assoc_db.read_one_associate_by_query({'salesforce_id': user_id})\nelse:\n res = assoc_db.read_one_associate_by_query({'email': user_id})\nif res['swot']:\n for swot in res['swot']:\n swot['date_created'] = converter(swot['date_created'])\nelse:\n res['swot'] = [{'auth... | <|body_start_0|>
if 'SF' in user_id:
res = assoc_db.read_one_associate_by_query({'salesforce_id': user_id})
else:
res = assoc_db.read_one_associate_by_query({'email': user_id})
if res['swot']:
for swot in res['swot']:
swot['date_created'] = con... | Class for routing employee/user_id requests | EmployeeIdRoute | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmployeeIdRoute:
"""Class for routing employee/user_id requests"""
def get(self, user_id):
"""Retrieves associate information for a designated associate vai salesforce id or email"""
<|body_0|>
def post(self, user_id):
"""Adds a SWOT to a designated associate via... | stack_v2_sparse_classes_75kplus_train_003725 | 4,872 | no_license | [
{
"docstring": "Retrieves associate information for a designated associate vai salesforce id or email",
"name": "get",
"signature": "def get(self, user_id)"
},
{
"docstring": "Adds a SWOT to a designated associate via their salesforce id or email",
"name": "post",
"signature": "def post(... | 2 | stack_v2_sparse_classes_30k_train_044207 | Implement the Python class `EmployeeIdRoute` described below.
Class description:
Class for routing employee/user_id requests
Method signatures and docstrings:
- def get(self, user_id): Retrieves associate information for a designated associate vai salesforce id or email
- def post(self, user_id): Adds a SWOT to a des... | Implement the Python class `EmployeeIdRoute` described below.
Class description:
Class for routing employee/user_id requests
Method signatures and docstrings:
- def get(self, user_id): Retrieves associate information for a designated associate vai salesforce id or email
- def post(self, user_id): Adds a SWOT to a des... | d376039c1d08f573fde536978ffce0e44a05922c | <|skeleton|>
class EmployeeIdRoute:
"""Class for routing employee/user_id requests"""
def get(self, user_id):
"""Retrieves associate information for a designated associate vai salesforce id or email"""
<|body_0|>
def post(self, user_id):
"""Adds a SWOT to a designated associate via... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EmployeeIdRoute:
"""Class for routing employee/user_id requests"""
def get(self, user_id):
"""Retrieves associate information for a designated associate vai salesforce id or email"""
if 'SF' in user_id:
res = assoc_db.read_one_associate_by_query({'salesforce_id': user_id})
... | the_stack_v2_python_sparse | src/router/employees.py | revaturelabs/csm-backend | train | 2 |
c3c6e7ab2388b58853ec08f4401f4c30dee6078f | [
"from collections import defaultdict\nself.prefixes = defaultdict(set)\nself.suffixes = defaultdict(set)\nself.weights = {}\nfor index, word in enumerate(words):\n prefix, suffix = ('', '')\n for char in [''] + list(word):\n prefix += char\n self.prefixes[prefix].add(word)\n for char in [''] ... | <|body_start_0|>
from collections import defaultdict
self.prefixes = defaultdict(set)
self.suffixes = defaultdict(set)
self.weights = {}
for index, word in enumerate(words):
prefix, suffix = ('', '')
for char in [''] + list(word):
prefix +=... | WordFilter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WordFilter:
def __init__(self, words):
""":type words: List[str]"""
<|body_0|>
def f(self, prefix, suffix):
""":type prefix: str :type suffix: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
from collections import defaultdict
... | stack_v2_sparse_classes_75kplus_train_003726 | 1,282 | no_license | [
{
"docstring": ":type words: List[str]",
"name": "__init__",
"signature": "def __init__(self, words)"
},
{
"docstring": ":type prefix: str :type suffix: str :rtype: int",
"name": "f",
"signature": "def f(self, prefix, suffix)"
}
] | 2 | stack_v2_sparse_classes_30k_train_053595 | Implement the Python class `WordFilter` described below.
Class description:
Implement the WordFilter class.
Method signatures and docstrings:
- def __init__(self, words): :type words: List[str]
- def f(self, prefix, suffix): :type prefix: str :type suffix: str :rtype: int | Implement the Python class `WordFilter` described below.
Class description:
Implement the WordFilter class.
Method signatures and docstrings:
- def __init__(self, words): :type words: List[str]
- def f(self, prefix, suffix): :type prefix: str :type suffix: str :rtype: int
<|skeleton|>
class WordFilter:
def __in... | e4c02084f26384cedbd87c4c60e9bdfbf77228cc | <|skeleton|>
class WordFilter:
def __init__(self, words):
""":type words: List[str]"""
<|body_0|>
def f(self, prefix, suffix):
""":type prefix: str :type suffix: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WordFilter:
def __init__(self, words):
""":type words: List[str]"""
from collections import defaultdict
self.prefixes = defaultdict(set)
self.suffixes = defaultdict(set)
self.weights = {}
for index, word in enumerate(words):
prefix, suffix = ('', '')... | the_stack_v2_python_sparse | Advanced/745. Prefix and Suffix Search Hard.py | dongbo910220/leetcode_ | train | 0 | |
f0ed1edd2753d76cd111be5e8587f15c612a224b | [
"super().__init__(**kwargs)\nself.factory = factory\nself.chapter_section = chapter_section\nself.content_translations = content_translations",
"for language, content in self.content_translations.items():\n i = 0\n if content.heading_tree:\n for heading_node in content.heading_tree:\n self... | <|body_start_0|>
super().__init__(**kwargs)
self.factory = factory
self.chapter_section = chapter_section
self.content_translations = content_translations
<|end_body_0|>
<|body_start_1|>
for language, content in self.content_translations.items():
i = 0
if... | Custom loader for loading headings for chapter sections. | ChapterSectionHeadingsLoader | [
"CC-BY-NC-SA-4.0",
"BSD-3-Clause",
"CC0-1.0",
"ISC",
"Unlicense",
"LicenseRef-scancode-secret-labs-2011",
"WTFPL",
"Apache-2.0",
"LGPL-3.0-only",
"MIT",
"CC-BY-SA-4.0",
"LicenseRef-scancode-public-domain",
"CC-BY-NC-2.5",
"LicenseRef-scancode-other-copyleft",
"LicenseRef-scancode-unknown... | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ChapterSectionHeadingsLoader:
"""Custom loader for loading headings for chapter sections."""
def __init__(self, factory, chapter_section, content_translations, **kwargs):
"""Create the loader for loading chapter section headings. Args: factory (LoaderFactory): LoaderFactory object fo... | stack_v2_sparse_classes_75kplus_train_003727 | 2,238 | permissive | [
{
"docstring": "Create the loader for loading chapter section headings. Args: factory (LoaderFactory): LoaderFactory object for creating loaders. chapter_section (ChapterSection): Object of related chapter section model. content_translation (dict): Dictionary of content translations.",
"name": "__init__",
... | 2 | null | Implement the Python class `ChapterSectionHeadingsLoader` described below.
Class description:
Custom loader for loading headings for chapter sections.
Method signatures and docstrings:
- def __init__(self, factory, chapter_section, content_translations, **kwargs): Create the loader for loading chapter section heading... | Implement the Python class `ChapterSectionHeadingsLoader` described below.
Class description:
Custom loader for loading headings for chapter sections.
Method signatures and docstrings:
- def __init__(self, factory, chapter_section, content_translations, **kwargs): Create the loader for loading chapter section heading... | ea3281ec6f4d17538f6d3cf6f88d74fa54581b34 | <|skeleton|>
class ChapterSectionHeadingsLoader:
"""Custom loader for loading headings for chapter sections."""
def __init__(self, factory, chapter_section, content_translations, **kwargs):
"""Create the loader for loading chapter section headings. Args: factory (LoaderFactory): LoaderFactory object fo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ChapterSectionHeadingsLoader:
"""Custom loader for loading headings for chapter sections."""
def __init__(self, factory, chapter_section, content_translations, **kwargs):
"""Create the loader for loading chapter section headings. Args: factory (LoaderFactory): LoaderFactory object for creating lo... | the_stack_v2_python_sparse | csfieldguide/chapters/management/commands/_ChapterSectionHeadingsLoader.py | uccser/cs-field-guide | train | 364 |
90e03ffb126dfed8c9ede8b699f7557e3da83338 | [
"pygame.sprite.Sprite.__init__(self)\nif image:\n self.image = image\nelse:\n self.image = Puff.IMAGE.copy()\nself.rect = self.image.get_rect()\nif alpha:\n self.image.set_alpha(int(alpha))\nelse:\n self.image.set_alpha(255)\nself.rect.centerx = coord[0]\nself.rect.centery = coord[1]\nself.countdown = l... | <|body_start_0|>
pygame.sprite.Sprite.__init__(self)
if image:
self.image = image
else:
self.image = Puff.IMAGE.copy()
self.rect = self.image.get_rect()
if alpha:
self.image.set_alpha(int(alpha))
else:
self.image.set_alpha(2... | A class which acts as temporary image, it has a life, and Surface as well as a location The class can be given an alpha value, which can be made to change at a specified rate The object will automatically kill itself after its life runs out | Puff | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Puff:
"""A class which acts as temporary image, it has a life, and Surface as well as a location The class can be given an alpha value, which can be made to change at a specified rate The object will automatically kill itself after its life runs out"""
def __init__(self, coord, life=60, alph... | stack_v2_sparse_classes_75kplus_train_003728 | 2,118 | permissive | [
{
"docstring": "Creates a puff of smoke coord(list) --> (x,y) center point of the puff life(int) --> frames before dissapearing (PRESET: 60 frames)(-1 = infinite) alpha(int) --> Alpha value of the surface (PRESET: fully opaque) alpha_decrease --> Alpha decrease per frame (PRESET: No decrease) image(Surface) -->... | 2 | stack_v2_sparse_classes_30k_train_038850 | Implement the Python class `Puff` described below.
Class description:
A class which acts as temporary image, it has a life, and Surface as well as a location The class can be given an alpha value, which can be made to change at a specified rate The object will automatically kill itself after its life runs out
Method ... | Implement the Python class `Puff` described below.
Class description:
A class which acts as temporary image, it has a life, and Surface as well as a location The class can be given an alpha value, which can be made to change at a specified rate The object will automatically kill itself after its life runs out
Method ... | 35b7127f9af204798615d820ec664a00eb45e1d2 | <|skeleton|>
class Puff:
"""A class which acts as temporary image, it has a life, and Surface as well as a location The class can be given an alpha value, which can be made to change at a specified rate The object will automatically kill itself after its life runs out"""
def __init__(self, coord, life=60, alph... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Puff:
"""A class which acts as temporary image, it has a life, and Surface as well as a location The class can be given an alpha value, which can be made to change at a specified rate The object will automatically kill itself after its life runs out"""
def __init__(self, coord, life=60, alpha=None, alpha... | the_stack_v2_python_sparse | Puff.py | Saevon/Arkanoid | train | 0 |
e5ebd27549b6c06a06ea864f3e9d02364f0a05b7 | [
"if type(network_distribution) is not type(known_distribution):\n raise TypeError('Input distributions must be of same type')\nif isinstance(network_distribution, dict):\n if network_distribution.keys() != known_distribution.keys():\n for key in list(network_distribution.keys()):\n if key no... | <|body_start_0|>
if type(network_distribution) is not type(known_distribution):
raise TypeError('Input distributions must be of same type')
if isinstance(network_distribution, dict):
if network_distribution.keys() != known_distribution.keys():
for key in list(netw... | Class of metrics/distances (norms) between probability distributions | Metrics | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Metrics:
"""Class of metrics/distances (norms) between probability distributions"""
def __init__(self, network_distribution, known_distribution):
"""Initializes a metric to compare distance between network and known (data) distribution. Args: network_distribution : dict or np.ndarray... | stack_v2_sparse_classes_75kplus_train_003729 | 11,971 | permissive | [
{
"docstring": "Initializes a metric to compare distance between network and known (data) distribution. Args: network_distribution : dict or np.ndarray Output probability distribution from network circuit. known_distribution : dict or np.ndarray Actual probability distribution from data.",
"name": "__init__... | 5 | stack_v2_sparse_classes_30k_train_048225 | Implement the Python class `Metrics` described below.
Class description:
Class of metrics/distances (norms) between probability distributions
Method signatures and docstrings:
- def __init__(self, network_distribution, known_distribution): Initializes a metric to compare distance between network and known (data) dist... | Implement the Python class `Metrics` described below.
Class description:
Class of metrics/distances (norms) between probability distributions
Method signatures and docstrings:
- def __init__(self, network_distribution, known_distribution): Initializes a metric to compare distance between network and known (data) dist... | 5fe919f100f54310a9300b32a838f965f834bbdf | <|skeleton|>
class Metrics:
"""Class of metrics/distances (norms) between probability distributions"""
def __init__(self, network_distribution, known_distribution):
"""Initializes a metric to compare distance between network and known (data) distribution. Args: network_distribution : dict or np.ndarray... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Metrics:
"""Class of metrics/distances (norms) between probability distributions"""
def __init__(self, network_distribution, known_distribution):
"""Initializes a metric to compare distance between network and known (data) distribution. Args: network_distribution : dict or np.ndarray Output proba... | the_stack_v2_python_sparse | src/nisqai/cost/_classical_costs.py | rmlarose/nisqai-dev | train | 15 |
b764c9e186da963d07af840d9743b87cc3fec3a4 | [
"with self._preprocess_graph_lock:\n if self._preprocess_graph is None:\n self._preprocess_graph = PreprocessGraph()",
"dataset, image_path, label = element\nimage_data = tf.io.gfile.GFile(image_path, 'rb').read()\nif self._preprocess_graph is None:\n raise RuntimeError('self._preprocess_graph not in... | <|body_start_0|>
with self._preprocess_graph_lock:
if self._preprocess_graph is None:
self._preprocess_graph = PreprocessGraph()
<|end_body_0|>
<|body_start_1|>
dataset, image_path, label = element
image_data = tf.io.gfile.GFile(image_path, 'rb').read()
if se... | Workflow step to preprocess input images. This workflow step does the following: 1) Reads input image from GCS 2) Resize and encodes the image as required by Inception V3 model. 3) Calculate Inception V3 bottleneck and stores it as a TFRecord. | PreprocessImage | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PreprocessImage:
"""Workflow step to preprocess input images. This workflow step does the following: 1) Reads input image from GCS 2) Resize and encodes the image as required by Inception V3 model. 3) Calculate Inception V3 bottleneck and stores it as a TFRecord."""
def start_bundle(self):
... | stack_v2_sparse_classes_75kplus_train_003730 | 12,153 | permissive | [
{
"docstring": "Starts an Apache Beam bundle. We cache the Tensorflow session per bundle to avoid cold starts for the processing of each element.",
"name": "start_bundle",
"signature": "def start_bundle(self)"
},
{
"docstring": "Calculates the bottleneck for an image. Args: element: A beam.PColl... | 2 | stack_v2_sparse_classes_30k_train_018459 | Implement the Python class `PreprocessImage` described below.
Class description:
Workflow step to preprocess input images. This workflow step does the following: 1) Reads input image from GCS 2) Resize and encodes the image as required by Inception V3 model. 3) Calculate Inception V3 bottleneck and stores it as a TFRe... | Implement the Python class `PreprocessImage` described below.
Class description:
Workflow step to preprocess input images. This workflow step does the following: 1) Reads input image from GCS 2) Resize and encodes the image as required by Inception V3 model. 3) Calculate Inception V3 bottleneck and stores it as a TFRe... | cb8ad454b351b86c70a32b70a0ff57049ab1d9c6 | <|skeleton|>
class PreprocessImage:
"""Workflow step to preprocess input images. This workflow step does the following: 1) Reads input image from GCS 2) Resize and encodes the image as required by Inception V3 model. 3) Calculate Inception V3 bottleneck and stores it as a TFRecord."""
def start_bundle(self):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PreprocessImage:
"""Workflow step to preprocess input images. This workflow step does the following: 1) Reads input image from GCS 2) Resize and encodes the image as required by Inception V3 model. 3) Calculate Inception V3 bottleneck and stores it as a TFRecord."""
def start_bundle(self):
"""Sta... | the_stack_v2_python_sparse | imaging/ml/ml_codelab/scripts/preprocess/preprocess.py | GoogleCloudPlatform/healthcare | train | 368 |
8fe4df5297b5c3d086d36d332683153b8137b822 | [
"if default_values:\n self._config_values = default_values\nelse:\n self._config_values = {}\ntry:\n fp = open(config_file)\n for line in fp:\n line = line.strip()\n if line and line[0] != '#':\n key, value = line.split(' ')\n self._config_values[key] = value\n fp.... | <|body_start_0|>
if default_values:
self._config_values = default_values
else:
self._config_values = {}
try:
fp = open(config_file)
for line in fp:
line = line.strip()
if line and line[0] != '#':
... | Class for loading and provide configuration parameters. | Configs | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Configs:
"""Class for loading and provide configuration parameters."""
def __init__(self, config_file, default_values=None):
"""Load config key/value pairs from the config file."""
<|body_0|>
def GetStr(self, key):
"""Returns the value for the given key from the ... | stack_v2_sparse_classes_75kplus_train_003731 | 1,901 | permissive | [
{
"docstring": "Load config key/value pairs from the config file.",
"name": "__init__",
"signature": "def __init__(self, config_file, default_values=None)"
},
{
"docstring": "Returns the value for the given key from the config file.",
"name": "GetStr",
"signature": "def GetStr(self, key)... | 4 | null | Implement the Python class `Configs` described below.
Class description:
Class for loading and provide configuration parameters.
Method signatures and docstrings:
- def __init__(self, config_file, default_values=None): Load config key/value pairs from the config file.
- def GetStr(self, key): Returns the value for th... | Implement the Python class `Configs` described below.
Class description:
Class for loading and provide configuration parameters.
Method signatures and docstrings:
- def __init__(self, config_file, default_values=None): Load config key/value pairs from the config file.
- def GetStr(self, key): Returns the value for th... | f7ea83f769485d9c28021b951fec8f15f641b16c | <|skeleton|>
class Configs:
"""Class for loading and provide configuration parameters."""
def __init__(self, config_file, default_values=None):
"""Load config key/value pairs from the config file."""
<|body_0|>
def GetStr(self, key):
"""Returns the value for the given key from the ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Configs:
"""Class for loading and provide configuration parameters."""
def __init__(self, config_file, default_values=None):
"""Load config key/value pairs from the config file."""
if default_values:
self._config_values = default_values
else:
self._config_v... | the_stack_v2_python_sparse | earth_enterprise/src/server/wsgi/wms/ogc/common/configs.py | tst-ccamp/earthenterprise | train | 2 |
55e1abb258743c4cc50fdf4aa1c4549d94582153 | [
"self.model = GMF(config['model'])\nself.loss = torch.nn.BCELoss()\nsuper(GMFEngine, self).__init__(config)",
"assert hasattr(self, 'model'), 'Please specify the exact model !'\nusers, items, ratings = (users.to(self.device), items.to(self.device), ratings.to(self.device))\nself.optimizer.zero_grad()\nratings_pre... | <|body_start_0|>
self.model = GMF(config['model'])
self.loss = torch.nn.BCELoss()
super(GMFEngine, self).__init__(config)
<|end_body_0|>
<|body_start_1|>
assert hasattr(self, 'model'), 'Please specify the exact model !'
users, items, ratings = (users.to(self.device), items.to(se... | Engine for training & evaluating GMF model. | GMFEngine | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GMFEngine:
"""Engine for training & evaluating GMF model."""
def __init__(self, config):
"""Initialize GMFEngine Class."""
<|body_0|>
def train_single_batch(self, users, items, ratings):
"""Train the model in a single batch. Args: batch_data (list): batch users, ... | stack_v2_sparse_classes_75kplus_train_003732 | 3,601 | permissive | [
{
"docstring": "Initialize GMFEngine Class.",
"name": "__init__",
"signature": "def __init__(self, config)"
},
{
"docstring": "Train the model in a single batch. Args: batch_data (list): batch users, positive items and negative items. Return: loss (float): batch loss.",
"name": "train_single... | 3 | stack_v2_sparse_classes_30k_train_042922 | Implement the Python class `GMFEngine` described below.
Class description:
Engine for training & evaluating GMF model.
Method signatures and docstrings:
- def __init__(self, config): Initialize GMFEngine Class.
- def train_single_batch(self, users, items, ratings): Train the model in a single batch. Args: batch_data ... | Implement the Python class `GMFEngine` described below.
Class description:
Engine for training & evaluating GMF model.
Method signatures and docstrings:
- def __init__(self, config): Initialize GMFEngine Class.
- def train_single_batch(self, users, items, ratings): Train the model in a single batch. Args: batch_data ... | 625189d5e1002a3edc27c3e3ce075fddf7ae1c92 | <|skeleton|>
class GMFEngine:
"""Engine for training & evaluating GMF model."""
def __init__(self, config):
"""Initialize GMFEngine Class."""
<|body_0|>
def train_single_batch(self, users, items, ratings):
"""Train the model in a single batch. Args: batch_data (list): batch users, ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GMFEngine:
"""Engine for training & evaluating GMF model."""
def __init__(self, config):
"""Initialize GMFEngine Class."""
self.model = GMF(config['model'])
self.loss = torch.nn.BCELoss()
super(GMFEngine, self).__init__(config)
def train_single_batch(self, users, item... | the_stack_v2_python_sparse | beta_rec/models/gmf.py | beta-team/beta-recsys | train | 156 |
5c044354700c6fdd8a0353c0bcc55b2872fa286d | [
"Entry.objects.create(pub_date=self.now, is_active=False, headline='inactive', slug='a')\nEntry.objects.create(pub_date=self.now, is_active=True, headline='active', slug='b')\nself.assertQuerysetEqual(Entry.objects.published(), ['active'], transform=lambda entry: entry.headline)",
"Entry.objects.create(pub_date=s... | <|body_start_0|>
Entry.objects.create(pub_date=self.now, is_active=False, headline='inactive', slug='a')
Entry.objects.create(pub_date=self.now, is_active=True, headline='active', slug='b')
self.assertQuerysetEqual(Entry.objects.published(), ['active'], transform=lambda entry: entry.headline)
<|... | EntryTestCase | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EntryTestCase:
def test_manager_active(self):
"""Make sure that the Entry manager's `active` method works"""
<|body_0|>
def test_manager_published(self):
"""Make sure that the Entry manager's `published` method works"""
<|body_1|>
def test_docutils_safe(... | stack_v2_sparse_classes_75kplus_train_003733 | 5,555 | permissive | [
{
"docstring": "Make sure that the Entry manager's `active` method works",
"name": "test_manager_active",
"signature": "def test_manager_active(self)"
},
{
"docstring": "Make sure that the Entry manager's `published` method works",
"name": "test_manager_published",
"signature": "def test... | 3 | null | Implement the Python class `EntryTestCase` described below.
Class description:
Implement the EntryTestCase class.
Method signatures and docstrings:
- def test_manager_active(self): Make sure that the Entry manager's `active` method works
- def test_manager_published(self): Make sure that the Entry manager's `publishe... | Implement the Python class `EntryTestCase` described below.
Class description:
Implement the EntryTestCase class.
Method signatures and docstrings:
- def test_manager_active(self): Make sure that the Entry manager's `active` method works
- def test_manager_published(self): Make sure that the Entry manager's `publishe... | 66a6e87290ee43b4935bc178c737c565570fbc7f | <|skeleton|>
class EntryTestCase:
def test_manager_active(self):
"""Make sure that the Entry manager's `active` method works"""
<|body_0|>
def test_manager_published(self):
"""Make sure that the Entry manager's `published` method works"""
<|body_1|>
def test_docutils_safe(... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EntryTestCase:
def test_manager_active(self):
"""Make sure that the Entry manager's `active` method works"""
Entry.objects.create(pub_date=self.now, is_active=False, headline='inactive', slug='a')
Entry.objects.create(pub_date=self.now, is_active=True, headline='active', slug='b')
... | the_stack_v2_python_sparse | blog/tests.py | django/djangoproject.com | train | 1,807 | |
36e48b0590000fa827a2e56b9dce38f137090867 | [
"if N == 0:\n return []\nif N == 1:\n return [TreeNode(0)]\nif N % 2 == 0:\n return []\nleft_num = 1\nright_num = N - 2\nres = []\nwhile right_num > 0:\n lefts = self.allPossibleFBT(left_num)\n rights = self.allPossibleFBT(right_num)\n for i in range(len(lefts)):\n for j in range(len(rights... | <|body_start_0|>
if N == 0:
return []
if N == 1:
return [TreeNode(0)]
if N % 2 == 0:
return []
left_num = 1
right_num = N - 2
res = []
while right_num > 0:
lefts = self.allPossibleFBT(left_num)
rights = s... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def allPossibleFBT(self, N):
""":type N: int :rtype: List[TreeNode] 现在这个树一共是N个节点的话，根节点算一个，左子树一共i个，那右子树一共就N-1-i个。 然后迭代的时候每次左边+2个，右边-2个。把所有的结果加起来就好啦。"""
<|body_0|>
def allPossibleFBT2(self, N):
""":type N: int :rtype: List[TreeNode]"""
<|body_1|>
<|e... | stack_v2_sparse_classes_75kplus_train_003734 | 2,349 | no_license | [
{
"docstring": ":type N: int :rtype: List[TreeNode] 现在这个树一共是N个节点的话，根节点算一个，左子树一共i个，那右子树一共就N-1-i个。 然后迭代的时候每次左边+2个，右边-2个。把所有的结果加起来就好啦。",
"name": "allPossibleFBT",
"signature": "def allPossibleFBT(self, N)"
},
{
"docstring": ":type N: int :rtype: List[TreeNode]",
"name": "allPossibleFBT2",
"... | 2 | stack_v2_sparse_classes_30k_train_013337 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def allPossibleFBT(self, N): :type N: int :rtype: List[TreeNode] 现在这个树一共是N个节点的话，根节点算一个，左子树一共i个，那右子树一共就N-1-i个。 然后迭代的时候每次左边+2个，右边-2个。把所有的结果加起来就好啦。
- def allPossibleFBT2(self, N): :... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def allPossibleFBT(self, N): :type N: int :rtype: List[TreeNode] 现在这个树一共是N个节点的话，根节点算一个，左子树一共i个，那右子树一共就N-1-i个。 然后迭代的时候每次左边+2个，右边-2个。把所有的结果加起来就好啦。
- def allPossibleFBT2(self, N): :... | 4105e18050b15fc0409c75353ad31be17187dd34 | <|skeleton|>
class Solution:
def allPossibleFBT(self, N):
""":type N: int :rtype: List[TreeNode] 现在这个树一共是N个节点的话，根节点算一个，左子树一共i个，那右子树一共就N-1-i个。 然后迭代的时候每次左边+2个，右边-2个。把所有的结果加起来就好啦。"""
<|body_0|>
def allPossibleFBT2(self, N):
""":type N: int :rtype: List[TreeNode]"""
<|body_1|>
<|e... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def allPossibleFBT(self, N):
""":type N: int :rtype: List[TreeNode] 现在这个树一共是N个节点的话，根节点算一个，左子树一共i个，那右子树一共就N-1-i个。 然后迭代的时候每次左边+2个，右边-2个。把所有的结果加起来就好啦。"""
if N == 0:
return []
if N == 1:
return [TreeNode(0)]
if N % 2 == 0:
return []
... | the_stack_v2_python_sparse | allPossibleFBT.py | NeilWangziyu/Leetcode_py | train | 2 | |
f2020912a71289a8bd434ec54c6ec29d3f6b9747 | [
"self.lockIO = Lock()\nself.bus = bus\nself.bus.register(self)\nself.data = [0] * (16131 + 1)\nreturn",
"if self.bus.address < 16636 or self.bus.address > 32767:\n return\nif self.bus.mode == MODE.READ:\n self.lockIO.acquire()\n self.bus.data = self.data[self.bus.address - 16636]\n self.lockIO.release... | <|body_start_0|>
self.lockIO = Lock()
self.bus = bus
self.bus.register(self)
self.data = [0] * (16131 + 1)
return
<|end_body_0|>
<|body_start_1|>
if self.bus.address < 16636 or self.bus.address > 32767:
return
if self.bus.mode == MODE.READ:
... | class IO ======================== Cette classe représente les entrées/sorties du micro-ordinateur. À chaque coup d'horloge (clock/event), la classe vérifie si elle doit effectuer une lecture ou écriture en mémoire. :example: >>> test = IO(modBus.Bus()) | IO | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IO:
"""class IO ======================== Cette classe représente les entrées/sorties du micro-ordinateur. À chaque coup d'horloge (clock/event), la classe vérifie si elle doit effectuer une lecture ou écriture en mémoire. :example: >>> test = IO(modBus.Bus())"""
def __init__(self, bus):
... | stack_v2_sparse_classes_75kplus_train_003735 | 4,185 | permissive | [
{
"docstring": "Constructeur de la classe IO. Le constructeur s'occupe d'initialiser la mémoire IO et lie ce composant avec le bus. :example: >>> test = IO(modBus.Bus()) :param bus: Composant Bus du Micro-Ordinateur. :type bus: Bus",
"name": "__init__",
"signature": "def __init__(self, bus)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_036415 | Implement the Python class `IO` described below.
Class description:
class IO ======================== Cette classe représente les entrées/sorties du micro-ordinateur. À chaque coup d'horloge (clock/event), la classe vérifie si elle doit effectuer une lecture ou écriture en mémoire. :example: >>> test = IO(modBus.Bus()... | Implement the Python class `IO` described below.
Class description:
class IO ======================== Cette classe représente les entrées/sorties du micro-ordinateur. À chaque coup d'horloge (clock/event), la classe vérifie si elle doit effectuer une lecture ou écriture en mémoire. :example: >>> test = IO(modBus.Bus()... | 0a3a9b0deffa16e8c851eb53e6aad1a8983936e6 | <|skeleton|>
class IO:
"""class IO ======================== Cette classe représente les entrées/sorties du micro-ordinateur. À chaque coup d'horloge (clock/event), la classe vérifie si elle doit effectuer une lecture ou écriture en mémoire. :example: >>> test = IO(modBus.Bus())"""
def __init__(self, bus):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IO:
"""class IO ======================== Cette classe représente les entrées/sorties du micro-ordinateur. À chaque coup d'horloge (clock/event), la classe vérifie si elle doit effectuer une lecture ou écriture en mémoire. :example: >>> test = IO(modBus.Bus())"""
def __init__(self, bus):
"""Constr... | the_stack_v2_python_sparse | Modules/04-05-IO.py | MarcAndreJean/PCONC | train | 0 |
34a39be9d385b93e2a7616fc7a8d4e6f213d6890 | [
"matches = []\nstring_params = cfn.get_sub_parameters(sub_string)\nif not string_params:\n message = \"Fn::Sub isn't needed because there are no variables at {0}\"\n matches.append(RuleMatch(tree, message.format('/'.join(map(str, tree)))))\nreturn matches",
"matches = []\nsub_objs = cfn.transform_pre.get('F... | <|body_start_0|>
matches = []
string_params = cfn.get_sub_parameters(sub_string)
if not string_params:
message = "Fn::Sub isn't needed because there are no variables at {0}"
matches.append(RuleMatch(tree, message.format('/'.join(map(str, tree)))))
return matches
<... | Check if Sub is using a variable | SubUnneeded | [
"MIT-0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SubUnneeded:
"""Check if Sub is using a variable"""
def _test_string(self, cfn, sub_string, tree):
"""Test if a string has appropriate parameters"""
<|body_0|>
def match(self, cfn):
"""Check CloudFormation Join"""
<|body_1|>
<|end_skeleton|>
<|body_star... | stack_v2_sparse_classes_75kplus_train_003736 | 2,531 | permissive | [
{
"docstring": "Test if a string has appropriate parameters",
"name": "_test_string",
"signature": "def _test_string(self, cfn, sub_string, tree)"
},
{
"docstring": "Check CloudFormation Join",
"name": "match",
"signature": "def match(self, cfn)"
}
] | 2 | null | Implement the Python class `SubUnneeded` described below.
Class description:
Check if Sub is using a variable
Method signatures and docstrings:
- def _test_string(self, cfn, sub_string, tree): Test if a string has appropriate parameters
- def match(self, cfn): Check CloudFormation Join | Implement the Python class `SubUnneeded` described below.
Class description:
Check if Sub is using a variable
Method signatures and docstrings:
- def _test_string(self, cfn, sub_string, tree): Test if a string has appropriate parameters
- def match(self, cfn): Check CloudFormation Join
<|skeleton|>
class SubUnneeded... | 3f5324cfd000e14d9324a242bb7fad528b22a7df | <|skeleton|>
class SubUnneeded:
"""Check if Sub is using a variable"""
def _test_string(self, cfn, sub_string, tree):
"""Test if a string has appropriate parameters"""
<|body_0|>
def match(self, cfn):
"""Check CloudFormation Join"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SubUnneeded:
"""Check if Sub is using a variable"""
def _test_string(self, cfn, sub_string, tree):
"""Test if a string has appropriate parameters"""
matches = []
string_params = cfn.get_sub_parameters(sub_string)
if not string_params:
message = "Fn::Sub isn't n... | the_stack_v2_python_sparse | src/cfnlint/rules/functions/SubUnneeded.py | jlongtine/cfn-python-lint | train | 1 |
c8cd3b38b3574c70ca73f8ba67902a270b85999c | [
"jumps = 0\ni, n = (0, len(nums))\nif n <= 1:\n return jumps\nwhile i < n:\n j = i + nums[i]\n if j < n - 1:\n i = max(range(i + 1, j + 1), key=lambda ind: ind + nums[ind])\n jumps += 1\n else:\n jumps += 1\n return jumps",
"jumps = 0\ncurEnd, curMax = (0, 0)\nfor i in rang... | <|body_start_0|>
jumps = 0
i, n = (0, len(nums))
if n <= 1:
return jumps
while i < n:
j = i + nums[i]
if j < n - 1:
i = max(range(i + 1, j + 1), key=lambda ind: ind + nums[ind])
jumps += 1
else:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def jump(self, nums: List[int]) -> int:
"""1. 贪心算法：位置i可达的点 i+1~i+nums[i]，从中选择可以跳最远的那个点为下一点 直观、且可直接记录下每次的跳跃点"""
<|body_0|>
def jump_1(self, nums: List[int]) -> int:
"""2. 重构代码 - curEnd 表示选择一个点后的可达边界，curMax 所有可达点中可以跳最远的那个点 - 初始时：位于 0 处，curEnd=0 - 在可达边界点内选择跳的最... | stack_v2_sparse_classes_75kplus_train_003737 | 2,327 | no_license | [
{
"docstring": "1. 贪心算法：位置i可达的点 i+1~i+nums[i]，从中选择可以跳最远的那个点为下一点 直观、且可直接记录下每次的跳跃点",
"name": "jump",
"signature": "def jump(self, nums: List[int]) -> int"
},
{
"docstring": "2. 重构代码 - curEnd 表示选择一个点后的可达边界，curMax 所有可达点中可以跳最远的那个点 - 初始时：位于 0 处，curEnd=0 - 在可达边界点内选择跳的最远的那一个，即每次达到边界处时，一定已经进行了一次选择",
... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def jump(self, nums: List[int]) -> int: 1. 贪心算法：位置i可达的点 i+1~i+nums[i]，从中选择可以跳最远的那个点为下一点 直观、且可直接记录下每次的跳跃点
- def jump_1(self, nums: List[int]) -> int: 2. 重构代码 - curEnd 表示选择一个点后的可达边... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def jump(self, nums: List[int]) -> int: 1. 贪心算法：位置i可达的点 i+1~i+nums[i]，从中选择可以跳最远的那个点为下一点 直观、且可直接记录下每次的跳跃点
- def jump_1(self, nums: List[int]) -> int: 2. 重构代码 - curEnd 表示选择一个点后的可达边... | 4732fb80710a08a715c3e7080c394f5298b8326d | <|skeleton|>
class Solution:
def jump(self, nums: List[int]) -> int:
"""1. 贪心算法：位置i可达的点 i+1~i+nums[i]，从中选择可以跳最远的那个点为下一点 直观、且可直接记录下每次的跳跃点"""
<|body_0|>
def jump_1(self, nums: List[int]) -> int:
"""2. 重构代码 - curEnd 表示选择一个点后的可达边界，curMax 所有可达点中可以跳最远的那个点 - 初始时：位于 0 处，curEnd=0 - 在可达边界点内选择跳的最... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def jump(self, nums: List[int]) -> int:
"""1. 贪心算法：位置i可达的点 i+1~i+nums[i]，从中选择可以跳最远的那个点为下一点 直观、且可直接记录下每次的跳跃点"""
jumps = 0
i, n = (0, len(nums))
if n <= 1:
return jumps
while i < n:
j = i + nums[i]
if j < n - 1:
... | the_stack_v2_python_sparse | .leetcode/45.跳跃游戏-ii.py | xiaoruijiang/algorithm | train | 0 | |
eed7c5fb5ce9a5f6f17c55de3988356cead6fc17 | [
"self.cloud_tier_download = cloud_tier_download\nself.cloud_tier_upload = cloud_tier_upload\nself.download = download\nself.upload = upload",
"if dictionary is None:\n return None\ncloud_tier_download = cohesity_management_sdk.models.bandwidth_limit.BandwidthLimit.from_dictionary(dictionary.get('cloudTierDownl... | <|body_start_0|>
self.cloud_tier_download = cloud_tier_download
self.cloud_tier_upload = cloud_tier_upload
self.download = download
self.upload = upload
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
cloud_tier_download = cohesity_manageme... | Implementation of the 'VaultBandwidthLimits' model. VaultBandwidthLimits represents the network bandwidth limits while uploading/downloading data to/from the external media. Attributes: cloud_tier_download (BandwidthLimit): Specifies the max rate limit at which we download the data to cloud tier vaults. cloud_tier_uplo... | VaultBandwidthLimits | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VaultBandwidthLimits:
"""Implementation of the 'VaultBandwidthLimits' model. VaultBandwidthLimits represents the network bandwidth limits while uploading/downloading data to/from the external media. Attributes: cloud_tier_download (BandwidthLimit): Specifies the max rate limit at which we downloa... | stack_v2_sparse_classes_75kplus_train_003738 | 3,010 | permissive | [
{
"docstring": "Constructor for the VaultBandwidthLimits class",
"name": "__init__",
"signature": "def __init__(self, cloud_tier_download=None, cloud_tier_upload=None, download=None, upload=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary... | 2 | stack_v2_sparse_classes_30k_train_035267 | Implement the Python class `VaultBandwidthLimits` described below.
Class description:
Implementation of the 'VaultBandwidthLimits' model. VaultBandwidthLimits represents the network bandwidth limits while uploading/downloading data to/from the external media. Attributes: cloud_tier_download (BandwidthLimit): Specifies... | Implement the Python class `VaultBandwidthLimits` described below.
Class description:
Implementation of the 'VaultBandwidthLimits' model. VaultBandwidthLimits represents the network bandwidth limits while uploading/downloading data to/from the external media. Attributes: cloud_tier_download (BandwidthLimit): Specifies... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class VaultBandwidthLimits:
"""Implementation of the 'VaultBandwidthLimits' model. VaultBandwidthLimits represents the network bandwidth limits while uploading/downloading data to/from the external media. Attributes: cloud_tier_download (BandwidthLimit): Specifies the max rate limit at which we downloa... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class VaultBandwidthLimits:
"""Implementation of the 'VaultBandwidthLimits' model. VaultBandwidthLimits represents the network bandwidth limits while uploading/downloading data to/from the external media. Attributes: cloud_tier_download (BandwidthLimit): Specifies the max rate limit at which we download the data to... | the_stack_v2_python_sparse | cohesity_management_sdk/models/vault_bandwidth_limits.py | cohesity/management-sdk-python | train | 24 |
ec313e6d6a59df9f3b299beb2a087d79fc181060 | [
"response = self.client.get('/accounts/register/')\nself.assertEqual(response.status_code, HTTPStatus.OK)\nself.assertContains(response, '<h2>Sign up</h2>', html=True)",
"form = {'first_name': 'test', 'last_name': 'test', 'email': 'test@test.com', 'password1': '12345678!', 'password2': '12345678!', 'username': 't... | <|body_start_0|>
response = self.client.get('/accounts/register/')
self.assertEqual(response.status_code, HTTPStatus.OK)
self.assertContains(response, '<h2>Sign up</h2>', html=True)
<|end_body_0|>
<|body_start_1|>
form = {'first_name': 'test', 'last_name': 'test', 'email': 'test@test.co... | RegisterViewTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RegisterViewTest:
def test_register_view_load(self):
"""test if register view loads successfully"""
<|body_0|>
def test_register_success(self):
"""test if a valid registration redirects to the home page and creates a new user"""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_75kplus_train_003739 | 1,065 | no_license | [
{
"docstring": "test if register view loads successfully",
"name": "test_register_view_load",
"signature": "def test_register_view_load(self)"
},
{
"docstring": "test if a valid registration redirects to the home page and creates a new user",
"name": "test_register_success",
"signature":... | 2 | stack_v2_sparse_classes_30k_train_054199 | Implement the Python class `RegisterViewTest` described below.
Class description:
Implement the RegisterViewTest class.
Method signatures and docstrings:
- def test_register_view_load(self): test if register view loads successfully
- def test_register_success(self): test if a valid registration redirects to the home ... | Implement the Python class `RegisterViewTest` described below.
Class description:
Implement the RegisterViewTest class.
Method signatures and docstrings:
- def test_register_view_load(self): test if register view loads successfully
- def test_register_success(self): test if a valid registration redirects to the home ... | be5b8d133a88340fe7347f1aaafb51660ad92f09 | <|skeleton|>
class RegisterViewTest:
def test_register_view_load(self):
"""test if register view loads successfully"""
<|body_0|>
def test_register_success(self):
"""test if a valid registration redirects to the home page and creates a new user"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RegisterViewTest:
def test_register_view_load(self):
"""test if register view loads successfully"""
response = self.client.get('/accounts/register/')
self.assertEqual(response.status_code, HTTPStatus.OK)
self.assertContains(response, '<h2>Sign up</h2>', html=True)
def test... | the_stack_v2_python_sparse | accounts/tests.py | harteros/MovieRama | train | 0 | |
61facdd6002d4a64240f621f884ef31cfb6d8596 | [
"if s == '':\n return 1\nif s[0] == '0':\n return 0\nways = 0\nif int(s[0]) != 0:\n ways += self._numDecodings(s[1:])\nif len(s) >= 2 and 1 <= int(s[0:2]) <= 26:\n ways += self._numDecodings(s[2:])\nreturn ways",
"if s == '':\n return 0\nreturn self._numDecodings(s)"
] | <|body_start_0|>
if s == '':
return 1
if s[0] == '0':
return 0
ways = 0
if int(s[0]) != 0:
ways += self._numDecodings(s[1:])
if len(s) >= 2 and 1 <= int(s[0:2]) <= 26:
ways += self._numDecodings(s[2:])
return ways
<|end_body... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def _numDecodings(self, s):
""":type s:str :rtype: int"""
<|body_0|>
def numDecodings(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if s == '':
return 1
if s[0] == '0':
... | stack_v2_sparse_classes_75kplus_train_003740 | 875 | no_license | [
{
"docstring": ":type s:str :rtype: int",
"name": "_numDecodings",
"signature": "def _numDecodings(self, s)"
},
{
"docstring": ":type s: str :rtype: int",
"name": "numDecodings",
"signature": "def numDecodings(self, s)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017777 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _numDecodings(self, s): :type s:str :rtype: int
- def numDecodings(self, s): :type s: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _numDecodings(self, s): :type s:str :rtype: int
- def numDecodings(self, s): :type s: str :rtype: int
<|skeleton|>
class Solution:
def _numDecodings(self, s):
"... | cd3900a7d91d1d94d308bc7a65533b8262781ee9 | <|skeleton|>
class Solution:
def _numDecodings(self, s):
""":type s:str :rtype: int"""
<|body_0|>
def numDecodings(self, s):
""":type s: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def _numDecodings(self, s):
""":type s:str :rtype: int"""
if s == '':
return 1
if s[0] == '0':
return 0
ways = 0
if int(s[0]) != 0:
ways += self._numDecodings(s[1:])
if len(s) >= 2 and 1 <= int(s[0:2]) <= 26:
... | the_stack_v2_python_sparse | lc0091_DecodeWays/lc0091.py | cgi0911/LeetCodePractice | train | 0 | |
706b1292cd76563f798b9614c6f02bc933d9c7b1 | [
"self.candidate_class = candidate_class\nself.candidate_spaces = cspaces if type(cspaces) in [list, tuple] else [cspaces]\nself.matchers = matchers if type(matchers) in [list, tuple] else [matchers]\nself.candidate_filter = candidate_filter\nself.nested_relations = nested_relations\nself.self_relations = self_relat... | <|body_start_0|>
self.candidate_class = candidate_class
self.candidate_spaces = cspaces if type(cspaces) in [list, tuple] else [cspaces]
self.matchers = matchers if type(matchers) in [list, tuple] else [matchers]
self.candidate_filter = candidate_filter
self.nested_relations = ne... | UDF for performing candidate extraction. | CandidateExtractorUDF | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CandidateExtractorUDF:
"""UDF for performing candidate extraction."""
def __init__(self, candidate_class, cspaces, matchers, candidate_filter, self_relations, nested_relations, symmetric_relations, **kwargs):
"""Initialize the CandidateExtractorUDF."""
<|body_0|>
def app... | stack_v2_sparse_classes_75kplus_train_003741 | 11,751 | permissive | [
{
"docstring": "Initialize the CandidateExtractorUDF.",
"name": "__init__",
"signature": "def __init__(self, candidate_class, cspaces, matchers, candidate_filter, self_relations, nested_relations, symmetric_relations, **kwargs)"
},
{
"docstring": "Extract candidates from the given Context. Here,... | 2 | stack_v2_sparse_classes_30k_train_012490 | Implement the Python class `CandidateExtractorUDF` described below.
Class description:
UDF for performing candidate extraction.
Method signatures and docstrings:
- def __init__(self, candidate_class, cspaces, matchers, candidate_filter, self_relations, nested_relations, symmetric_relations, **kwargs): Initialize the ... | Implement the Python class `CandidateExtractorUDF` described below.
Class description:
UDF for performing candidate extraction.
Method signatures and docstrings:
- def __init__(self, candidate_class, cspaces, matchers, candidate_filter, self_relations, nested_relations, symmetric_relations, **kwargs): Initialize the ... | 362aa56afe60194498c8e0a67b37053abebf04a2 | <|skeleton|>
class CandidateExtractorUDF:
"""UDF for performing candidate extraction."""
def __init__(self, candidate_class, cspaces, matchers, candidate_filter, self_relations, nested_relations, symmetric_relations, **kwargs):
"""Initialize the CandidateExtractorUDF."""
<|body_0|>
def app... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CandidateExtractorUDF:
"""UDF for performing candidate extraction."""
def __init__(self, candidate_class, cspaces, matchers, candidate_filter, self_relations, nested_relations, symmetric_relations, **kwargs):
"""Initialize the CandidateExtractorUDF."""
self.candidate_class = candidate_cla... | the_stack_v2_python_sparse | fonduer/candidates/candidates.py | stevenMevans/fonduer | train | 1 |
c5fb848c63bea4cfe0e1da7984780e4f83828bb8 | [
"self.primary_language = primary_language\nself.secondary_language = secondary_language\nself.xml_signature = xml_signature\nself.additional_properties = additional_properties",
"if dictionary is None:\n return None\nprimary_language = dictionary.get('PrimaryLanguage')\nsecondary_language = dictionary.get('Sec... | <|body_start_0|>
self.primary_language = primary_language
self.secondary_language = secondary_language
self.xml_signature = xml_signature
self.additional_properties = additional_properties
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
pri... | Implementation of the 'TemplateWithIdPreview' model. TODO: type model description here. Attributes: primary_language (PrimaryLanguage): Primary language to use in the preview (required) secondary_language (SecondaryLanguage): Secondary language to use in the prewview (optional) xml_signature (string): Xml package signa... | TemplateWithIdPreview | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TemplateWithIdPreview:
"""Implementation of the 'TemplateWithIdPreview' model. TODO: type model description here. Attributes: primary_language (PrimaryLanguage): Primary language to use in the preview (required) secondary_language (SecondaryLanguage): Secondary language to use in the prewview (op... | stack_v2_sparse_classes_75kplus_train_003742 | 2,616 | permissive | [
{
"docstring": "Constructor for the TemplateWithIdPreview class",
"name": "__init__",
"signature": "def __init__(self, primary_language=None, secondary_language=None, xml_signature=None, additional_properties={})"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dicti... | 2 | stack_v2_sparse_classes_30k_val_003019 | Implement the Python class `TemplateWithIdPreview` described below.
Class description:
Implementation of the 'TemplateWithIdPreview' model. TODO: type model description here. Attributes: primary_language (PrimaryLanguage): Primary language to use in the preview (required) secondary_language (SecondaryLanguage): Second... | Implement the Python class `TemplateWithIdPreview` described below.
Class description:
Implementation of the 'TemplateWithIdPreview' model. TODO: type model description here. Attributes: primary_language (PrimaryLanguage): Primary language to use in the preview (required) secondary_language (SecondaryLanguage): Second... | fa3918a6c54ea0eedb9146578645b7eb1755b642 | <|skeleton|>
class TemplateWithIdPreview:
"""Implementation of the 'TemplateWithIdPreview' model. TODO: type model description here. Attributes: primary_language (PrimaryLanguage): Primary language to use in the preview (required) secondary_language (SecondaryLanguage): Secondary language to use in the prewview (op... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TemplateWithIdPreview:
"""Implementation of the 'TemplateWithIdPreview' model. TODO: type model description here. Attributes: primary_language (PrimaryLanguage): Primary language to use in the preview (required) secondary_language (SecondaryLanguage): Secondary language to use in the prewview (optional) xml_s... | the_stack_v2_python_sparse | idfy_rest_client/models/template_with_id_preview.py | dealflowteam/Idfy | train | 0 |
5061e129e9736dc1118f104472f16efaea4ba612 | [
"if self.model.metadata['file_in']:\n self.model._read_from_file(tag_scripts=['p1.individuals.tag = 0;', 'tags = rbinom(1, p0.individualCount, 0.5);', 'p0.individuals.tag = tags;'])\nelse:\n self.model.early(time=1, scripts=[\"sim.addSubpop('p1', SPO_POP_SIZE)\", \"sim.addSubpop('p0', 0)\", 'p1.individuals.ta... | <|body_start_0|>
if self.model.metadata['file_in']:
self.model._read_from_file(tag_scripts=['p1.individuals.tag = 0;', 'tags = rbinom(1, p0.individualCount, 0.5);', 'p0.individuals.tag = tags;'])
else:
self.model.early(time=1, scripts=["sim.addSubpop('p1', SPO_POP_SIZE)", "sim.ad... | Reproduction mode based on NON Wright-Fisher model. This is a subclass that is extended for organism specific reproduction models in shadie.reproduction. All NonWF models include alternation of generations (p0 and p1 subpops). The alternative is to implement a WF model. | NonWrightFisher | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NonWrightFisher:
"""Reproduction mode based on NON Wright-Fisher model. This is a subclass that is extended for organism specific reproduction models in shadie.reproduction. All NonWF models include alternation of generations (p0 and p1 subpops). The alternative is to implement a WF model."""
... | stack_v2_sparse_classes_75kplus_train_003743 | 11,092 | no_license | [
{
"docstring": "add haploid and diploid life stages as subpopulations.",
"name": "_define_subpopulations",
"signature": "def _define_subpopulations(self)"
},
{
"docstring": "Add defineConstant calls to init variables. When this is called by different superclasses that have different attributes u... | 3 | null | Implement the Python class `NonWrightFisher` described below.
Class description:
Reproduction mode based on NON Wright-Fisher model. This is a subclass that is extended for organism specific reproduction models in shadie.reproduction. All NonWF models include alternation of generations (p0 and p1 subpops). The alterna... | Implement the Python class `NonWrightFisher` described below.
Class description:
Reproduction mode based on NON Wright-Fisher model. This is a subclass that is extended for organism specific reproduction models in shadie.reproduction. All NonWF models include alternation of generations (p0 and p1 subpops). The alterna... | dfdd853ed4ff3fd8f8d3430a9c74ab8db5d3d096 | <|skeleton|>
class NonWrightFisher:
"""Reproduction mode based on NON Wright-Fisher model. This is a subclass that is extended for organism specific reproduction models in shadie.reproduction. All NonWF models include alternation of generations (p0 and p1 subpops). The alternative is to implement a WF model."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NonWrightFisher:
"""Reproduction mode based on NON Wright-Fisher model. This is a subclass that is extended for organism specific reproduction models in shadie.reproduction. All NonWF models include alternation of generations (p0 and p1 subpops). The alternative is to implement a WF model."""
def _define... | the_stack_v2_python_sparse | shadie/reproduction/base.py | eaton-lab/shadie | train | 0 |
158a984a3eb238590f8c559a4ddb68550061853e | [
"for sqrt_b in [WhiteCovariance, BrownianCovariance, PinkCovariance]:\n n = 64\n ident = jnp.eye(n)[:, :, None]\n sqrt_b_dense = sqrt_b.forward(ident)[Ellipsis, 0]\n _, slogdet = jnp.linalg.slogdet(sqrt_b_dense)\n logdet = slogdet * 2\n logdet2 = sqrt_b.logdet((ident + jnp.zeros(2)).shape)[0]\n ... | <|body_start_0|>
for sqrt_b in [WhiteCovariance, BrownianCovariance, PinkCovariance]:
n = 64
ident = jnp.eye(n)[:, :, None]
sqrt_b_dense = sqrt_b.forward(ident)[Ellipsis, 0]
_, slogdet = jnp.linalg.slogdet(sqrt_b_dense)
logdet = slogdet * 2
... | CovarianceTest | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CovarianceTest:
def test_covariance_logdet(self):
"""Test whether logdet method matches numpy logdet with dense matrix."""
<|body_0|>
def test_covariance_inverse(self):
"""Test covariance forward and inverse are in fact inverses of each other."""
<|body_1|>
... | stack_v2_sparse_classes_75kplus_train_003744 | 2,268 | permissive | [
{
"docstring": "Test whether logdet method matches numpy logdet with dense matrix.",
"name": "test_covariance_logdet",
"signature": "def test_covariance_logdet(self)"
},
{
"docstring": "Test covariance forward and inverse are in fact inverses of each other.",
"name": "test_covariance_inverse... | 2 | stack_v2_sparse_classes_30k_train_036249 | Implement the Python class `CovarianceTest` described below.
Class description:
Implement the CovarianceTest class.
Method signatures and docstrings:
- def test_covariance_logdet(self): Test whether logdet method matches numpy logdet with dense matrix.
- def test_covariance_inverse(self): Test covariance forward and ... | Implement the Python class `CovarianceTest` described below.
Class description:
Implement the CovarianceTest class.
Method signatures and docstrings:
- def test_covariance_logdet(self): Test whether logdet method matches numpy logdet with dense matrix.
- def test_covariance_inverse(self): Test covariance forward and ... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class CovarianceTest:
def test_covariance_logdet(self):
"""Test whether logdet method matches numpy logdet with dense matrix."""
<|body_0|>
def test_covariance_inverse(self):
"""Test covariance forward and inverse are in fact inverses of each other."""
<|body_1|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CovarianceTest:
def test_covariance_logdet(self):
"""Test whether logdet method matches numpy logdet with dense matrix."""
for sqrt_b in [WhiteCovariance, BrownianCovariance, PinkCovariance]:
n = 64
ident = jnp.eye(n)[:, :, None]
sqrt_b_dense = sqrt_b.forwar... | the_stack_v2_python_sparse | simulation_research/diffusion/covariance_test.py | Jimmy-INL/google-research | train | 1 | |
0804b3860a9d58ea9e9fde52399b3a06dd72c61d | [
"if self.config_file is None:\n msg = ' %(cls)s 未定义配置文件路径，需定义config_file的值' % {'cls': self.__class__.__name__}\n error_logger.error(msg)\n raise ValueError(msg)\nreturn self.config_file",
"_config = self.get_config_file()\nwith open(_config) as f:\n content = yaml.load(f)\nif key is not None:\n try... | <|body_start_0|>
if self.config_file is None:
msg = ' %(cls)s 未定义配置文件路径，需定义config_file的值' % {'cls': self.__class__.__name__}
error_logger.error(msg)
raise ValueError(msg)
return self.config_file
<|end_body_0|>
<|body_start_1|>
_config = self.get_config_file()... | ConfigFileMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConfigFileMixin:
def get_config_file(self):
"""获取配置文件"""
<|body_0|>
def get_conf_content(self, *key):
"""获取配置文件对应的key"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if self.config_file is None:
msg = ' %(cls)s 未定义配置文件路径，需定义config_file的值... | stack_v2_sparse_classes_75kplus_train_003745 | 3,226 | no_license | [
{
"docstring": "获取配置文件",
"name": "get_config_file",
"signature": "def get_config_file(self)"
},
{
"docstring": "获取配置文件对应的key",
"name": "get_conf_content",
"signature": "def get_conf_content(self, *key)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002626 | Implement the Python class `ConfigFileMixin` described below.
Class description:
Implement the ConfigFileMixin class.
Method signatures and docstrings:
- def get_config_file(self): 获取配置文件
- def get_conf_content(self, *key): 获取配置文件对应的key | Implement the Python class `ConfigFileMixin` described below.
Class description:
Implement the ConfigFileMixin class.
Method signatures and docstrings:
- def get_config_file(self): 获取配置文件
- def get_conf_content(self, *key): 获取配置文件对应的key
<|skeleton|>
class ConfigFileMixin:
def get_config_file(self):
"""获... | abf784479ed90b47b6a2611991baf202aea662d2 | <|skeleton|>
class ConfigFileMixin:
def get_config_file(self):
"""获取配置文件"""
<|body_0|>
def get_conf_content(self, *key):
"""获取配置文件对应的key"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ConfigFileMixin:
def get_config_file(self):
"""获取配置文件"""
if self.config_file is None:
msg = ' %(cls)s 未定义配置文件路径，需定义config_file的值' % {'cls': self.__class__.__name__}
error_logger.error(msg)
raise ValueError(msg)
return self.config_file
def get_co... | the_stack_v2_python_sparse | apps/utils/common.py | Sirius1942/rock2020 | train | 2 | |
b9d714996f4458349c371fa7e16d4499fea2638b | [
"self.item_code = item_code\nself.description = description\nself.market_price = market_price\nself.rental_price = rental_price",
"outputdict = {}\noutputdict['item_code'] = self.item_code\noutputdict['description'] = self.description\noutputdict['market_price'] = self.market_price\noutputdict['rental_price'] = s... | <|body_start_0|>
self.item_code = item_code
self.description = description
self.market_price = market_price
self.rental_price = rental_price
<|end_body_0|>
<|body_start_1|>
outputdict = {}
outputdict['item_code'] = self.item_code
outputdict['description'] = self.... | some stuff8 | Inventory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Inventory:
"""some stuff8"""
def __init__(self, item_code, description, market_price, rental_price):
"""some stuff9"""
<|body_0|>
def return_as_dictionary(self):
"""some stuff10"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.item_code = it... | stack_v2_sparse_classes_75kplus_train_003746 | 684 | no_license | [
{
"docstring": "some stuff9",
"name": "__init__",
"signature": "def __init__(self, item_code, description, market_price, rental_price)"
},
{
"docstring": "some stuff10",
"name": "return_as_dictionary",
"signature": "def return_as_dictionary(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_016037 | Implement the Python class `Inventory` described below.
Class description:
some stuff8
Method signatures and docstrings:
- def __init__(self, item_code, description, market_price, rental_price): some stuff9
- def return_as_dictionary(self): some stuff10 | Implement the Python class `Inventory` described below.
Class description:
some stuff8
Method signatures and docstrings:
- def __init__(self, item_code, description, market_price, rental_price): some stuff9
- def return_as_dictionary(self): some stuff10
<|skeleton|>
class Inventory:
"""some stuff8"""
def __... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class Inventory:
"""some stuff8"""
def __init__(self, item_code, description, market_price, rental_price):
"""some stuff9"""
<|body_0|>
def return_as_dictionary(self):
"""some stuff10"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Inventory:
"""some stuff8"""
def __init__(self, item_code, description, market_price, rental_price):
"""some stuff9"""
self.item_code = item_code
self.description = description
self.market_price = market_price
self.rental_price = rental_price
def return_as_dic... | the_stack_v2_python_sparse | students/ScotchWSplenda/lesson01/assignment/inventory_management/inventory_class.py | JavaRod/SP_Python220B_2019 | train | 1 |
69197fe0f6c84c807e50d5836c7931d11955d9e0 | [
"self.workflow = kwargs.pop('workflow')\nself.user = kwargs.pop('user')\nsuper().__init__(*args, **kwargs)",
"if record.is_verified:\n return format_html('<a href=\"{0}\" ' + 'data-bs-toggle=\"tooltip\" title=\"{1}\">{2}', reverse('dataops:plugin_invoke', kwargs={'pk': record.id}), _('Execute the transformatio... | <|body_start_0|>
self.workflow = kwargs.pop('workflow')
self.user = kwargs.pop('user')
super().__init__(*args, **kwargs)
<|end_body_0|>
<|body_start_1|>
if record.is_verified:
return format_html('<a href="{0}" ' + 'data-bs-toggle="tooltip" title="{1}">{2}', reverse('dataops:... | Class to render the table with plugins available for execution. The Operations column is inheriting from another class to centralise the customisation. | PluginAvailableTable | [
"LGPL-2.0-or-later",
"BSD-3-Clause",
"MIT",
"Apache-2.0",
"LGPL-2.1-only",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PluginAvailableTable:
"""Class to render the table with plugins available for execution. The Operations column is inheriting from another class to centralise the customisation."""
def __init__(self, *args, **kwargs):
"""Set workflow and user from the given args."""
<|body_0|>... | stack_v2_sparse_classes_75kplus_train_003747 | 5,524 | permissive | [
{
"docstring": "Set workflow and user from the given args.",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "Render as a link or empty if it has not been verified.",
"name": "render_name",
"signature": "def render_name(record)"
},
{
"docs... | 3 | null | Implement the Python class `PluginAvailableTable` described below.
Class description:
Class to render the table with plugins available for execution. The Operations column is inheriting from another class to centralise the customisation.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Set wor... | Implement the Python class `PluginAvailableTable` described below.
Class description:
Class to render the table with plugins available for execution. The Operations column is inheriting from another class to centralise the customisation.
Method signatures and docstrings:
- def __init__(self, *args, **kwargs): Set wor... | c432745dfff932cbe7397100422d49df78f0a882 | <|skeleton|>
class PluginAvailableTable:
"""Class to render the table with plugins available for execution. The Operations column is inheriting from another class to centralise the customisation."""
def __init__(self, *args, **kwargs):
"""Set workflow and user from the given args."""
<|body_0|>... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PluginAvailableTable:
"""Class to render the table with plugins available for execution. The Operations column is inheriting from another class to centralise the customisation."""
def __init__(self, *args, **kwargs):
"""Set workflow and user from the given args."""
self.workflow = kwargs.... | the_stack_v2_python_sparse | ontask/dataops/services/plugin_run.py | abelardopardo/ontask_b | train | 43 |
fcb0bded96199e93c2eb5196f72d8da001de0924 | [
"if not overwrite_destination and os.path.exists(installation_dir):\n raise ValueError(f'Plugin {repr(cls)} cannot be installed into existing path {installation_dir} because overwrite_destination={overwrite_destination}.')\nsuper().install(installation_dir=installation_dir, overwrite_destination=True)\nprint(f'P... | <|body_start_0|>
if not overwrite_destination and os.path.exists(installation_dir):
raise ValueError(f'Plugin {repr(cls)} cannot be installed into existing path {installation_dir} because overwrite_destination={overwrite_destination}.')
super().install(installation_dir=installation_dir, over... | Plugins are self-contained, python modules that may assume enb is installed. - They can be installed into your projects via the enb CLI (e.g., with `enb plugin install <name> <clone_dir>`), and then imported like any other module. - The list of plugins available off-the-box can be obtained using the enb CLI (e.g., with... | Plugin | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Plugin:
"""Plugins are self-contained, python modules that may assume enb is installed. - They can be installed into your projects via the enb CLI (e.g., with `enb plugin install <name> <clone_dir>`), and then imported like any other module. - The list of plugins available off-the-box can be obta... | stack_v2_sparse_classes_75kplus_train_003748 | 5,481 | permissive | [
{
"docstring": "Make a copy of this plugin into installation_dir, ready to be imported. By default, a verbatim copy of the source plugin's dir is made. Any previous contents in installation_dir are overwritten. Then any explicit requirements are met (external software may be downloaded and pip packages installe... | 2 | stack_v2_sparse_classes_30k_val_002338 | Implement the Python class `Plugin` described below.
Class description:
Plugins are self-contained, python modules that may assume enb is installed. - They can be installed into your projects via the enb CLI (e.g., with `enb plugin install <name> <clone_dir>`), and then imported like any other module. - The list of pl... | Implement the Python class `Plugin` described below.
Class description:
Plugins are self-contained, python modules that may assume enb is installed. - They can be installed into your projects via the enb CLI (e.g., with `enb plugin install <name> <clone_dir>`), and then imported like any other module. - The list of pl... | 35f9eecd93a3e8cc90631c3a819a36de1c40401f | <|skeleton|>
class Plugin:
"""Plugins are self-contained, python modules that may assume enb is installed. - They can be installed into your projects via the enb CLI (e.g., with `enb plugin install <name> <clone_dir>`), and then imported like any other module. - The list of plugins available off-the-box can be obta... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Plugin:
"""Plugins are self-contained, python modules that may assume enb is installed. - They can be installed into your projects via the enb CLI (e.g., with `enb plugin install <name> <clone_dir>`), and then imported like any other module. - The list of plugins available off-the-box can be obtained using th... | the_stack_v2_python_sparse | enb/plugins/plugin.py | esterjara/experiment-notebook | train | 0 |
db13b1c29f3c8393d943bb6497f11772104e5255 | [
"self.use_default = use_default\nself.included_cidr = included_cidr\nself.excluded_cidr = excluded_cidr",
"if dictionary is None:\n return None\nuse_default = dictionary.get('useDefault')\nincluded_cidr = dictionary.get('includedCidr')\nexcluded_cidr = dictionary.get('excludedCidr')\nreturn cls(use_default, in... | <|body_start_0|>
self.use_default = use_default
self.included_cidr = included_cidr
self.excluded_cidr = excluded_cidr
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
use_default = dictionary.get('useDefault')
included_cidr = dictionary.get(... | Implementation of the 'ProtectedNetworks' model. Set the included/excluded networks from the intrusion engine (optional - omitting will leave current config unchanged). This is available only in 'passthrough' mode Attributes: use_default (bool): true/false whether to use special IPv4 addresses: https://tools.ietf.org/h... | ProtectedNetworksModel | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProtectedNetworksModel:
"""Implementation of the 'ProtectedNetworks' model. Set the included/excluded networks from the intrusion engine (optional - omitting will leave current config unchanged). This is available only in 'passthrough' mode Attributes: use_default (bool): true/false whether to us... | stack_v2_sparse_classes_75kplus_train_003749 | 2,461 | permissive | [
{
"docstring": "Constructor for the ProtectedNetworksModel class",
"name": "__init__",
"signature": "def __init__(self, use_default=None, included_cidr=None, excluded_cidr=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary re... | 2 | null | Implement the Python class `ProtectedNetworksModel` described below.
Class description:
Implementation of the 'ProtectedNetworks' model. Set the included/excluded networks from the intrusion engine (optional - omitting will leave current config unchanged). This is available only in 'passthrough' mode Attributes: use_d... | Implement the Python class `ProtectedNetworksModel` described below.
Class description:
Implementation of the 'ProtectedNetworks' model. Set the included/excluded networks from the intrusion engine (optional - omitting will leave current config unchanged). This is available only in 'passthrough' mode Attributes: use_d... | 9894089eb013318243ae48869cc5130eb37f80c0 | <|skeleton|>
class ProtectedNetworksModel:
"""Implementation of the 'ProtectedNetworks' model. Set the included/excluded networks from the intrusion engine (optional - omitting will leave current config unchanged). This is available only in 'passthrough' mode Attributes: use_default (bool): true/false whether to us... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ProtectedNetworksModel:
"""Implementation of the 'ProtectedNetworks' model. Set the included/excluded networks from the intrusion engine (optional - omitting will leave current config unchanged). This is available only in 'passthrough' mode Attributes: use_default (bool): true/false whether to use special IPv... | the_stack_v2_python_sparse | meraki_sdk/models/protected_networks_model.py | RaulCatalano/meraki-python-sdk | train | 1 |
7855050aa19aabacc405f76bc8e7b56d9b1df5c4 | [
"self.factory = RequestFactory()\nself.user = User.objects.create(username='Abdullah', email='abd@gmail.com', password=\"Abdullah's passwd\")\nself.airline = Airline.objects.create(title='Summer Break', verified=True)\nself.airline_url = 'airlines:create_airline'\nself.review_url = 'airlines:create_review'",
"sel... | <|body_start_0|>
self.factory = RequestFactory()
self.user = User.objects.create(username='Abdullah', email='abd@gmail.com', password="Abdullah's passwd")
self.airline = Airline.objects.create(title='Summer Break', verified=True)
self.airline_url = 'airlines:create_airline'
self.... | Users add Airline and Review objects to the database. | AirlineAndReviewCreateTests | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AirlineAndReviewCreateTests:
"""Users add Airline and Review objects to the database."""
def setUp(self):
"""Instantiate the Users, Airline, Review, and RequestFactory instances needed for testing."""
<|body_0|>
def test_get_create_airline_form(self):
"""User req... | stack_v2_sparse_classes_75kplus_train_003750 | 8,369 | permissive | [
{
"docstring": "Instantiate the Users, Airline, Review, and RequestFactory instances needed for testing.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "User requests to see the form to add a new airline.",
"name": "test_get_create_airline_form",
"signature": "def te... | 5 | stack_v2_sparse_classes_30k_train_051573 | Implement the Python class `AirlineAndReviewCreateTests` described below.
Class description:
Users add Airline and Review objects to the database.
Method signatures and docstrings:
- def setUp(self): Instantiate the Users, Airline, Review, and RequestFactory instances needed for testing.
- def test_get_create_airline... | Implement the Python class `AirlineAndReviewCreateTests` described below.
Class description:
Users add Airline and Review objects to the database.
Method signatures and docstrings:
- def setUp(self): Instantiate the Users, Airline, Review, and RequestFactory instances needed for testing.
- def test_get_create_airline... | 65d933c64a3bf830f51ac237f5781ddfb69f342c | <|skeleton|>
class AirlineAndReviewCreateTests:
"""Users add Airline and Review objects to the database."""
def setUp(self):
"""Instantiate the Users, Airline, Review, and RequestFactory instances needed for testing."""
<|body_0|>
def test_get_create_airline_form(self):
"""User req... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AirlineAndReviewCreateTests:
"""Users add Airline and Review objects to the database."""
def setUp(self):
"""Instantiate the Users, Airline, Review, and RequestFactory instances needed for testing."""
self.factory = RequestFactory()
self.user = User.objects.create(username='Abdull... | the_stack_v2_python_sparse | travelly/airlines/tests.py | UPstartDeveloper/fiercely-souvenir | train | 0 |
52b989eb48d45c51964beca7ce85a4cb7a654c78 | [
"mtz_file = mtz.object()\nmtz_file.set_title(f'From {env.dispatcher_name}')\ndate_str = time.strftime('%Y-%m-%d at %H:%M:%S %Z')\nif time.strftime('%Z') != 'GMT':\n date_str += time.strftime(' (%Y-%m-%d at %H:%M:%S %Z)', time.gmtime())\nmtz_file.add_history(f'From {dials_version()}, run on {date_str}')\nmtz_fil... | <|body_start_0|>
mtz_file = mtz.object()
mtz_file.set_title(f'From {env.dispatcher_name}')
date_str = time.strftime('%Y-%m-%d at %H:%M:%S %Z')
if time.strftime('%Z') != 'GMT':
date_str += time.strftime(' (%Y-%m-%d at %H:%M:%S %Z)', time.gmtime())
mtz_file.add_history... | Helper for adding metadata, crystals and datasets to an mtz file object. | MTZWriterBase | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MTZWriterBase:
"""Helper for adding metadata, crystals and datasets to an mtz file object."""
def __init__(self, space_group, unit_cell=None):
"""If a unit cell is provided, will be used as default unless specified for each crystal."""
<|body_0|>
def add_crystal(self, cr... | stack_v2_sparse_classes_75kplus_train_003751 | 23,243 | permissive | [
{
"docstring": "If a unit cell is provided, will be used as default unless specified for each crystal.",
"name": "__init__",
"signature": "def __init__(self, space_group, unit_cell=None)"
},
{
"docstring": "Add a crystal to the mtz file object.",
"name": "add_crystal",
"signature": "def ... | 3 | stack_v2_sparse_classes_30k_train_042385 | Implement the Python class `MTZWriterBase` described below.
Class description:
Helper for adding metadata, crystals and datasets to an mtz file object.
Method signatures and docstrings:
- def __init__(self, space_group, unit_cell=None): If a unit cell is provided, will be used as default unless specified for each cry... | Implement the Python class `MTZWriterBase` described below.
Class description:
Helper for adding metadata, crystals and datasets to an mtz file object.
Method signatures and docstrings:
- def __init__(self, space_group, unit_cell=None): If a unit cell is provided, will be used as default unless specified for each cry... | e611c7680a02b5766a8f476557834daf6361d124 | <|skeleton|>
class MTZWriterBase:
"""Helper for adding metadata, crystals and datasets to an mtz file object."""
def __init__(self, space_group, unit_cell=None):
"""If a unit cell is provided, will be used as default unless specified for each crystal."""
<|body_0|>
def add_crystal(self, cr... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MTZWriterBase:
"""Helper for adding metadata, crystals and datasets to an mtz file object."""
def __init__(self, space_group, unit_cell=None):
"""If a unit cell is provided, will be used as default unless specified for each crystal."""
mtz_file = mtz.object()
mtz_file.set_title(f'... | the_stack_v2_python_sparse | util/export_mtz.py | dagewa/dials | train | 1 |
9c756a6141f5477340b66a77efaa26821bf7ef29 | [
"work_pool = await models.workers.read_work_pool_by_name(session=session, work_pool_name=work_pool_name)\nif not work_pool:\n raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=f'Work pool \"{work_pool_name}\" not found.')\nreturn work_pool.id",
"work_pool = await models.workers.read_work_pool_b... | <|body_start_0|>
work_pool = await models.workers.read_work_pool_by_name(session=session, work_pool_name=work_pool_name)
if not work_pool:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=f'Work pool "{work_pool_name}" not found.')
return work_pool.id
<|end_body_0|>
... | WorkerLookups | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WorkerLookups:
async def _get_work_pool_id_from_name(self, session: AsyncSession, work_pool_name: str) -> UUID:
"""Given a work pool name, return its ID. Used for translating user-facing APIs (which are name-based) to internal ones (which are id-based)."""
<|body_0|>
async d... | stack_v2_sparse_classes_75kplus_train_003752 | 18,979 | permissive | [
{
"docstring": "Given a work pool name, return its ID. Used for translating user-facing APIs (which are name-based) to internal ones (which are id-based).",
"name": "_get_work_pool_id_from_name",
"signature": "async def _get_work_pool_id_from_name(self, session: AsyncSession, work_pool_name: str) -> UUI... | 3 | stack_v2_sparse_classes_30k_train_004553 | Implement the Python class `WorkerLookups` described below.
Class description:
Implement the WorkerLookups class.
Method signatures and docstrings:
- async def _get_work_pool_id_from_name(self, session: AsyncSession, work_pool_name: str) -> UUID: Given a work pool name, return its ID. Used for translating user-facing... | Implement the Python class `WorkerLookups` described below.
Class description:
Implement the WorkerLookups class.
Method signatures and docstrings:
- async def _get_work_pool_id_from_name(self, session: AsyncSession, work_pool_name: str) -> UUID: Given a work pool name, return its ID. Used for translating user-facing... | 2c50d2b64c811c364cbc5faa2b5c80a742572090 | <|skeleton|>
class WorkerLookups:
async def _get_work_pool_id_from_name(self, session: AsyncSession, work_pool_name: str) -> UUID:
"""Given a work pool name, return its ID. Used for translating user-facing APIs (which are name-based) to internal ones (which are id-based)."""
<|body_0|>
async d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WorkerLookups:
async def _get_work_pool_id_from_name(self, session: AsyncSession, work_pool_name: str) -> UUID:
"""Given a work pool name, return its ID. Used for translating user-facing APIs (which are name-based) to internal ones (which are id-based)."""
work_pool = await models.workers.read... | the_stack_v2_python_sparse | src/prefect/server/api/workers.py | PrefectHQ/prefect | train | 12,917 | |
a3a7385e79a5496d92d8fa0b6500965a2dd01f3a | [
"super(My_attention, self).__init__()\nself.encoder_att = nn.Linear(encoder_dim, attention_dim)\nself.decoder_att = nn.Linear(decoder_dim, attention_dim)\nself.full_att = nn.Linear(attention_dim, 1)\nself.relu = nn.ReLU()\nself.softmax = nn.Softmax(dim=1)",
"att1 = self.encoder_att(encoder_out)\natt2 = self.decod... | <|body_start_0|>
super(My_attention, self).__init__()
self.encoder_att = nn.Linear(encoder_dim, attention_dim)
self.decoder_att = nn.Linear(decoder_dim, attention_dim)
self.full_att = nn.Linear(attention_dim, 1)
self.relu = nn.ReLU()
self.softmax = nn.Softmax(dim=1)
<|end... | Attention Network. | My_attention | [
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class My_attention:
"""Attention Network."""
def __init__(self, encoder_dim, decoder_dim, attention_dim):
""":param encoder_dim: feature size of encoded images :param decoder_dim: size of decoder's RNN :param attention_dim: size of the attention network"""
<|body_0|>
def forwa... | stack_v2_sparse_classes_75kplus_train_003753 | 30,636 | permissive | [
{
"docstring": ":param encoder_dim: feature size of encoded images :param decoder_dim: size of decoder's RNN :param attention_dim: size of the attention network",
"name": "__init__",
"signature": "def __init__(self, encoder_dim, decoder_dim, attention_dim)"
},
{
"docstring": "Forward propagation... | 2 | stack_v2_sparse_classes_30k_train_048646 | Implement the Python class `My_attention` described below.
Class description:
Attention Network.
Method signatures and docstrings:
- def __init__(self, encoder_dim, decoder_dim, attention_dim): :param encoder_dim: feature size of encoded images :param decoder_dim: size of decoder's RNN :param attention_dim: size of t... | Implement the Python class `My_attention` described below.
Class description:
Attention Network.
Method signatures and docstrings:
- def __init__(self, encoder_dim, decoder_dim, attention_dim): :param encoder_dim: feature size of encoded images :param decoder_dim: size of decoder's RNN :param attention_dim: size of t... | 54e05d68c66c9cc5b9698e453981c0f1a6b216cf | <|skeleton|>
class My_attention:
"""Attention Network."""
def __init__(self, encoder_dim, decoder_dim, attention_dim):
""":param encoder_dim: feature size of encoded images :param decoder_dim: size of decoder's RNN :param attention_dim: size of the attention network"""
<|body_0|>
def forwa... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class My_attention:
"""Attention Network."""
def __init__(self, encoder_dim, decoder_dim, attention_dim):
""":param encoder_dim: feature size of encoded images :param decoder_dim: size of decoder's RNN :param attention_dim: size of the attention network"""
super(My_attention, self).__init__()
... | the_stack_v2_python_sparse | src/model/decoder/decoder_vis_old.py | daniil-777/geneuclidean | train | 0 |
ca33239d16e723674ac0b47248a63a19bb204b7c | [
"self.redshift = redshift\nself.light_profile_list = light_profile_list\nself.mass_profile_list = mass_profile_list",
"if self.light_profile_list is not None:\n return sum(map(lambda p: p.image_from_grid(grid=grid), self.light_profile_list))\nreturn np.zeros((grid.shape[0],))",
"if self.mass_profile_list is ... | <|body_start_0|>
self.redshift = redshift
self.light_profile_list = light_profile_list
self.mass_profile_list = mass_profile_list
<|end_body_0|>
<|body_start_1|>
if self.light_profile_list is not None:
return sum(map(lambda p: p.image_from_grid(grid=grid), self.light_profile... | Galaxy | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Galaxy:
def __init__(self, redshift: float, light_profile_list: Optional[List]=None, mass_profile_list: Optional[List]=None):
"""A galaxy, which contains light and mass profiles at a specified redshift. Parameters ---------- redshift The redshift of the galaxy. light_profile_list A list ... | stack_v2_sparse_classes_75kplus_train_003754 | 2,345 | no_license | [
{
"docstring": "A galaxy, which contains light and mass profiles at a specified redshift. Parameters ---------- redshift The redshift of the galaxy. light_profile_list A list of the galaxy's light profiles. mass_profile_list A list of the galaxy's mass profiles.",
"name": "__init__",
"signature": "def _... | 3 | stack_v2_sparse_classes_30k_train_000941 | Implement the Python class `Galaxy` described below.
Class description:
Implement the Galaxy class.
Method signatures and docstrings:
- def __init__(self, redshift: float, light_profile_list: Optional[List]=None, mass_profile_list: Optional[List]=None): A galaxy, which contains light and mass profiles at a specified ... | Implement the Python class `Galaxy` described below.
Class description:
Implement the Galaxy class.
Method signatures and docstrings:
- def __init__(self, redshift: float, light_profile_list: Optional[List]=None, mass_profile_list: Optional[List]=None): A galaxy, which contains light and mass profiles at a specified ... | ac76dfef4643189a130ce18d23070bb81272a93c | <|skeleton|>
class Galaxy:
def __init__(self, redshift: float, light_profile_list: Optional[List]=None, mass_profile_list: Optional[List]=None):
"""A galaxy, which contains light and mass profiles at a specified redshift. Parameters ---------- redshift The redshift of the galaxy. light_profile_list A list ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Galaxy:
def __init__(self, redshift: float, light_profile_list: Optional[List]=None, mass_profile_list: Optional[List]=None):
"""A galaxy, which contains light and mass profiles at a specified redshift. Parameters ---------- redshift The redshift of the galaxy. light_profile_list A list of the galaxy'... | the_stack_v2_python_sparse | projects/cosmology/src/galaxy.py | Jammy2211/autofit_workspace | train | 6 | |
e934afdf672100acc5c3383f840b000fcf000a7b | [
"n = len(nums)\nbuffer, res = ([0] * n, [0] * n)\nind = list(range(0, n))\n\ndef merge_sort(l, r):\n if l >= r:\n return\n m = l + (r - l >> 1)\n merge_sort(l, m)\n merge_sort(m + 1, r)\n i, j, k = (l, m + 1, 0)\n while i <= m:\n while j <= r and nums[ind[i]] > nums[ind[j]]:\n ... | <|body_start_0|>
n = len(nums)
buffer, res = ([0] * n, [0] * n)
ind = list(range(0, n))
def merge_sort(l, r):
if l >= r:
return
m = l + (r - l >> 1)
merge_sort(l, m)
merge_sort(m + 1, r)
i, j, k = (l, m + 1, 0)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countSmaller(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def countSmaller_with_binary_search(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
n = len(nums... | stack_v2_sparse_classes_75kplus_train_003755 | 2,379 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "countSmaller",
"signature": "def countSmaller(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[int]",
"name": "countSmaller_with_binary_search",
"signature": "def countSmaller_with_binary_search(self, nu... | 2 | stack_v2_sparse_classes_30k_train_029711 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countSmaller(self, nums): :type nums: List[int] :rtype: List[int]
- def countSmaller_with_binary_search(self, nums): :type nums: List[int] :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countSmaller(self, nums): :type nums: List[int] :rtype: List[int]
- def countSmaller_with_binary_search(self, nums): :type nums: List[int] :rtype: List[int]
<|skeleton|>
cla... | 6c640581a642fc1a1c43e4b9f9f397b4d67bb67b | <|skeleton|>
class Solution:
def countSmaller(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_0|>
def countSmaller_with_binary_search(self, nums):
""":type nums: List[int] :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def countSmaller(self, nums):
""":type nums: List[int] :rtype: List[int]"""
n = len(nums)
buffer, res = ([0] * n, [0] * n)
ind = list(range(0, n))
def merge_sort(l, r):
if l >= r:
return
m = l + (r - l >> 1)
... | the_stack_v2_python_sparse | python/315-counter-of-smaller-numbers-after-self.py | whiledoing/leetcode | train | 0 | |
3296013021e21a4b02247ad50aa6f1474999508f | [
"resource_args.AddConversionWorkspaceResourceArg(parser, 'to describe issues')\ncw_flags.AddCommitIdFlag(parser)\ncw_flags.AddUncomittedFlag(parser)\ncw_flags.AddFilterFlag(parser)\nparser.display_info.AddFormat('\\n table(\\n parentEntity:label=PARENT,\\n shortName:label=NAME,\\n ... | <|body_start_0|>
resource_args.AddConversionWorkspaceResourceArg(parser, 'to describe issues')
cw_flags.AddCommitIdFlag(parser)
cw_flags.AddUncomittedFlag(parser)
cw_flags.AddFilterFlag(parser)
parser.display_info.AddFormat('\n table(\n parentEntity:label=PARE... | Describe issues in a Database Migration Service conversion workspace. | DescribeIssues | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DescribeIssues:
"""Describe issues in a Database Migration Service conversion workspace."""
def Args(parser):
"""Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line after this ... | stack_v2_sparse_classes_75kplus_train_003756 | 3,120 | permissive | [
{
"docstring": "Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line after this command. Positional arguments are allowed.",
"name": "Args",
"signature": "def Args(parser)"
},
{
"docstring"... | 2 | stack_v2_sparse_classes_30k_train_002824 | Implement the Python class `DescribeIssues` described below.
Class description:
Describe issues in a Database Migration Service conversion workspace.
Method signatures and docstrings:
- def Args(parser): Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use... | Implement the Python class `DescribeIssues` described below.
Class description:
Describe issues in a Database Migration Service conversion workspace.
Method signatures and docstrings:
- def Args(parser): Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use... | 392abf004b16203030e6efd2f0af24db7c8d669e | <|skeleton|>
class DescribeIssues:
"""Describe issues in a Database Migration Service conversion workspace."""
def Args(parser):
"""Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line after this ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DescribeIssues:
"""Describe issues in a Database Migration Service conversion workspace."""
def Args(parser):
"""Args is called by calliope to gather arguments for this command. Args: parser: An argparse parser that you can use to add arguments that go on the command line after this command. Posi... | the_stack_v2_python_sparse | lib/surface/database_migration/conversion_workspaces/describe_issues.py | google-cloud-sdk-unofficial/google-cloud-sdk | train | 9 |
d8984cecf28de1ce3a47112c5f4c4706c0c67f2b | [
"qs = super(NHDLakeManager, self).get_queryset().filter(ftype__in=[390, 436], parent=None, is_in_oregon=True)\nqs = qs.prefetch_related('county_set')\nqs = qs.extra(select={'is_important': 'has_mussels OR has_docs OR has_photos OR has_plants OR (aol_page IS NOT NULL)'}, order_by=['-is_important'])\nreturn qs",
"q... | <|body_start_0|>
qs = super(NHDLakeManager, self).get_queryset().filter(ftype__in=[390, 436], parent=None, is_in_oregon=True)
qs = qs.prefetch_related('county_set')
qs = qs.extra(select={'is_important': 'has_mussels OR has_docs OR has_photos OR has_plants OR (aol_page IS NOT NULL)'}, order_by=['... | NHDLakeManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NHDLakeManager:
def get_queryset(self):
"""We only want to return lakes that are coded as LakePond or Reservoir which have the types 390, 436 in the NHD. See http://nhd.usgs.gov/NHDv2.0_poster_6_2_2010.pdf We also only want to get lakes in oregon"""
<|body_0|>
def search(sel... | stack_v2_sparse_classes_75kplus_train_003757 | 19,344 | no_license | [
{
"docstring": "We only want to return lakes that are coded as LakePond or Reservoir which have the types 390, 436 in the NHD. See http://nhd.usgs.gov/NHDv2.0_poster_6_2_2010.pdf We also only want to get lakes in oregon",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstr... | 4 | stack_v2_sparse_classes_30k_train_053783 | Implement the Python class `NHDLakeManager` described below.
Class description:
Implement the NHDLakeManager class.
Method signatures and docstrings:
- def get_queryset(self): We only want to return lakes that are coded as LakePond or Reservoir which have the types 390, 436 in the NHD. See http://nhd.usgs.gov/NHDv2.0... | Implement the Python class `NHDLakeManager` described below.
Class description:
Implement the NHDLakeManager class.
Method signatures and docstrings:
- def get_queryset(self): We only want to return lakes that are coded as LakePond or Reservoir which have the types 390, 436 in the NHD. See http://nhd.usgs.gov/NHDv2.0... | d29538a502d028574e142baca508db5bfc4430ca | <|skeleton|>
class NHDLakeManager:
def get_queryset(self):
"""We only want to return lakes that are coded as LakePond or Reservoir which have the types 390, 436 in the NHD. See http://nhd.usgs.gov/NHDv2.0_poster_6_2_2010.pdf We also only want to get lakes in oregon"""
<|body_0|>
def search(sel... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NHDLakeManager:
def get_queryset(self):
"""We only want to return lakes that are coded as LakePond or Reservoir which have the types 390, 436 in the NHD. See http://nhd.usgs.gov/NHDv2.0_poster_6_2_2010.pdf We also only want to get lakes in oregon"""
qs = super(NHDLakeManager, self).get_queryse... | the_stack_v2_python_sparse | aol/lakes/models.py | conwayb/aol | train | 0 | |
40b63c91b082df3233ea7d3be1192db92e0e6fa1 | [
"def _preorderTraversal(root, result):\n if not root:\n return result\n result.append(root.val)\n _preorderTraversal(root.left, result)\n _preorderTraversal(root.right, result)\n return result\nresult = []\nreturn _preorderTraversal(root, result)",
"result, stack = ([], [root])\nwhile stack:... | <|body_start_0|>
def _preorderTraversal(root, result):
if not root:
return result
result.append(root.val)
_preorderTraversal(root.left, result)
_preorderTraversal(root.right, result)
return result
result = []
return _pre... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def preorderTraversal(self, root):
""":type root: TreeNode :rtype List[int] (knowledge) 思路： 1. 使用一个列表记录遍历过的值； 2. 每次先将当前节点的值加入结果集，然后递归遍历左右子树;"""
<|body_0|>
def preorderTraversal2(self, root):
""":type root: TreeNode :rtype List[int] (knowledge) 非递归解法 思路： 1. ... | stack_v2_sparse_classes_75kplus_train_003758 | 1,962 | no_license | [
{
"docstring": ":type root: TreeNode :rtype List[int] (knowledge) 思路： 1. 使用一个列表记录遍历过的值； 2. 每次先将当前节点的值加入结果集，然后递归遍历左右子树;",
"name": "preorderTraversal",
"signature": "def preorderTraversal(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype List[int] (knowledge) 非递归解法 思路： 1. 使用一个列表记录遍历过的值； ... | 2 | stack_v2_sparse_classes_30k_train_023395 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preorderTraversal(self, root): :type root: TreeNode :rtype List[int] (knowledge) 思路： 1. 使用一个列表记录遍历过的值； 2. 每次先将当前节点的值加入结果集，然后递归遍历左右子树;
- def preorderTraversal2(self, root): :t... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preorderTraversal(self, root): :type root: TreeNode :rtype List[int] (knowledge) 思路： 1. 使用一个列表记录遍历过的值； 2. 每次先将当前节点的值加入结果集，然后递归遍历左右子树;
- def preorderTraversal2(self, root): :t... | 19ea28c38762c65318275007932786e648a8b415 | <|skeleton|>
class Solution:
def preorderTraversal(self, root):
""":type root: TreeNode :rtype List[int] (knowledge) 思路： 1. 使用一个列表记录遍历过的值； 2. 每次先将当前节点的值加入结果集，然后递归遍历左右子树;"""
<|body_0|>
def preorderTraversal2(self, root):
""":type root: TreeNode :rtype List[int] (knowledge) 非递归解法 思路： 1. ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def preorderTraversal(self, root):
""":type root: TreeNode :rtype List[int] (knowledge) 思路： 1. 使用一个列表记录遍历过的值； 2. 每次先将当前节点的值加入结果集，然后递归遍历左右子树;"""
def _preorderTraversal(root, result):
if not root:
return result
result.append(root.val)
... | the_stack_v2_python_sparse | chapter9/7_binary-tree-preorder-traversal.py | SunnyQjm/algorithm-review | train | 2 | |
2b4892d09f731faadfd2f0200810abde0eaee104 | [
"self.client = TcpClient(ip=ip, port=port, port_out=port_out, exceed_time=timeout)\nself.use_center = use_center\npass",
"text, centers = parse_json(content)\nres = self.client.request([text])\nif self.use_center:\n res = center_json(res[0], centers)\nreturn res"
] | <|body_start_0|>
self.client = TcpClient(ip=ip, port=port, port_out=port_out, exceed_time=timeout)
self.use_center = use_center
pass
<|end_body_0|>
<|body_start_1|>
text, centers = parse_json(content)
res = self.client.request([text])
if self.use_center:
res ... | Predictor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Predictor:
def __init__(self, ip='localhost', port=5555, port_out=5556, timeout=-1, use_center=True):
"""初始化模型、配置"""
<|body_0|>
def predict(self, content: dict) -> dict:
"""输入标注格式，已转为dict 输出同标注格式，dict格式 :param content: :return str:"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_75kplus_train_003759 | 1,684 | no_license | [
{
"docstring": "初始化模型、配置",
"name": "__init__",
"signature": "def __init__(self, ip='localhost', port=5555, port_out=5556, timeout=-1, use_center=True)"
},
{
"docstring": "输入标注格式，已转为dict 输出同标注格式，dict格式 :param content: :return str:",
"name": "predict",
"signature": "def predict(self, conte... | 2 | stack_v2_sparse_classes_30k_train_043395 | Implement the Python class `Predictor` described below.
Class description:
Implement the Predictor class.
Method signatures and docstrings:
- def __init__(self, ip='localhost', port=5555, port_out=5556, timeout=-1, use_center=True): 初始化模型、配置
- def predict(self, content: dict) -> dict: 输入标注格式，已转为dict 输出同标注格式，dict格式 :p... | Implement the Python class `Predictor` described below.
Class description:
Implement the Predictor class.
Method signatures and docstrings:
- def __init__(self, ip='localhost', port=5555, port_out=5556, timeout=-1, use_center=True): 初始化模型、配置
- def predict(self, content: dict) -> dict: 输入标注格式，已转为dict 输出同标注格式，dict格式 :p... | 5355abd4bc18f1294fe07f324c21ef88baa30f81 | <|skeleton|>
class Predictor:
def __init__(self, ip='localhost', port=5555, port_out=5556, timeout=-1, use_center=True):
"""初始化模型、配置"""
<|body_0|>
def predict(self, content: dict) -> dict:
"""输入标注格式，已转为dict 输出同标注格式，dict格式 :param content: :return str:"""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Predictor:
def __init__(self, ip='localhost', port=5555, port_out=5556, timeout=-1, use_center=True):
"""初始化模型、配置"""
self.client = TcpClient(ip=ip, port=port, port_out=port_out, exceed_time=timeout)
self.use_center = use_center
pass
def predict(self, content: dict) -> dict... | the_stack_v2_python_sparse | predictor.py | homzer/BERT-CRF | train | 1 | |
80d987c09743f66d7c7997655523d5e0aa163d1d | [
"result = 0\nfor i in xrange(0, len(nums)):\n for j in xrange(i + 1, len(nums)):\n result += self.findHammingDistance(nums[i] ^ nums[j])\nreturn result",
"count = 0\nwhile num != 0:\n count += num & 1\n num >>= 1\nreturn count"
] | <|body_start_0|>
result = 0
for i in xrange(0, len(nums)):
for j in xrange(i + 1, len(nums)):
result += self.findHammingDistance(nums[i] ^ nums[j])
return result
<|end_body_0|>
<|body_start_1|>
count = 0
while num != 0:
count += num & 1
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def totalHammingDistance(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findHammingDistance(self, num):
""":param num: int :return: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
result = 0
for i in xrange... | stack_v2_sparse_classes_75kplus_train_003760 | 561 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "totalHammingDistance",
"signature": "def totalHammingDistance(self, nums)"
},
{
"docstring": ":param num: int :return: int",
"name": "findHammingDistance",
"signature": "def findHammingDistance(self, num)"
}
] | 2 | stack_v2_sparse_classes_30k_train_027495 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def totalHammingDistance(self, nums): :type nums: List[int] :rtype: int
- def findHammingDistance(self, num): :param num: int :return: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def totalHammingDistance(self, nums): :type nums: List[int] :rtype: int
- def findHammingDistance(self, num): :param num: int :return: int
<|skeleton|>
class Solution:
def ... | 0a833b8f666385500de5a55731b1a5590827b207 | <|skeleton|>
class Solution:
def totalHammingDistance(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def findHammingDistance(self, num):
""":param num: int :return: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def totalHammingDistance(self, nums):
""":type nums: List[int] :rtype: int"""
result = 0
for i in xrange(0, len(nums)):
for j in xrange(i + 1, len(nums)):
result += self.findHammingDistance(nums[i] ^ nums[j])
return result
def findHamm... | the_stack_v2_python_sparse | LeetCode-Python/477. Total Hamming Distance.py | KaranJaswani/Codes | train | 0 | |
8ec785a2db8cc441907ac8788750a33fe5528388 | [
"try:\n import pypdf\nexcept ImportError:\n raise ValueError('pypdf package not found, please install it with `pip install pypdf`')\nself._file_path = file_path",
"import pypdf\nwith open(self._file_path, 'rb') as pdf_file_obj:\n pdf_reader = pypdf.PdfReader(pdf_file_obj)\n return [Document(page_conte... | <|body_start_0|>
try:
import pypdf
except ImportError:
raise ValueError('pypdf package not found, please install it with `pip install pypdf`')
self._file_path = file_path
<|end_body_0|>
<|body_start_1|>
import pypdf
with open(self._file_path, 'rb') as pdf... | Loads a PDF with pypdf and chunks at character level. Loader also stores page numbers in metadatas. | PagedPDFSplitter | [
"LicenseRef-scancode-generic-cla",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PagedPDFSplitter:
"""Loads a PDF with pypdf and chunks at character level. Loader also stores page numbers in metadatas."""
def __init__(self, file_path: str):
"""Initialize with file path."""
<|body_0|>
def load(self) -> List[Document]:
"""Load given path as pag... | stack_v2_sparse_classes_75kplus_train_003761 | 1,152 | permissive | [
{
"docstring": "Initialize with file path.",
"name": "__init__",
"signature": "def __init__(self, file_path: str)"
},
{
"docstring": "Load given path as pages.",
"name": "load",
"signature": "def load(self) -> List[Document]"
}
] | 2 | null | Implement the Python class `PagedPDFSplitter` described below.
Class description:
Loads a PDF with pypdf and chunks at character level. Loader also stores page numbers in metadatas.
Method signatures and docstrings:
- def __init__(self, file_path: str): Initialize with file path.
- def load(self) -> List[Document]: L... | Implement the Python class `PagedPDFSplitter` described below.
Class description:
Loads a PDF with pypdf and chunks at character level. Loader also stores page numbers in metadatas.
Method signatures and docstrings:
- def __init__(self, file_path: str): Initialize with file path.
- def load(self) -> List[Document]: L... | b8f29af7f3c24cf3a4554bebfa2053064467fbdb | <|skeleton|>
class PagedPDFSplitter:
"""Loads a PDF with pypdf and chunks at character level. Loader also stores page numbers in metadatas."""
def __init__(self, file_path: str):
"""Initialize with file path."""
<|body_0|>
def load(self) -> List[Document]:
"""Load given path as pag... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PagedPDFSplitter:
"""Loads a PDF with pypdf and chunks at character level. Loader also stores page numbers in metadatas."""
def __init__(self, file_path: str):
"""Initialize with file path."""
try:
import pypdf
except ImportError:
raise ValueError('pypdf pa... | the_stack_v2_python_sparse | langchain/document_loaders/paged_pdf.py | microsoft/MM-REACT | train | 705 |
53a18cd3e81f48926d87984ecbb2520100c8a375 | [
"if new_level is not None:\n Msg.level = new_level\ntry:\n if Msg.nullfp is None:\n Msg.nullfp = open('/dev/null', 'w')\nexcept (IOError, OSError):\n Msg.chlderr = sys.stderr\n Msg.chldout = sys.stdout\n Msg.chldnul = sys.stderr\nelse:\n Msg.chlderr = Msg.nullfp\n Msg.chldout = Msg.nullf... | <|body_start_0|>
if new_level is not None:
Msg.level = new_level
try:
if Msg.nullfp is None:
Msg.nullfp = open('/dev/null', 'w')
except (IOError, OSError):
Msg.chlderr = sys.stderr
Msg.chldout = sys.stdout
Msg.chldnul = ... | Write messages to stdout and stderr. Allows to filter the messages to be displayed through a verbose level, also allows to control if child process that produce output through a file descriptor should be redirected to /dev/null | Msg | [
"LicenseRef-scancode-proprietary-license",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Msg:
"""Write messages to stdout and stderr. Allows to filter the messages to be displayed through a verbose level, also allows to control if child process that produce output through a file descriptor should be redirected to /dev/null"""
def __init__(self, new_level=None):
"""Initia... | stack_v2_sparse_classes_75kplus_train_003762 | 2,136 | permissive | [
{
"docstring": "Initialize Msg level and /dev/null file pointers to be used in subprocess calls to obfuscate output and errors",
"name": "__init__",
"signature": "def __init__(self, new_level=None)"
},
{
"docstring": "Define debug level",
"name": "setlevel",
"signature": "def setlevel(se... | 4 | null | Implement the Python class `Msg` described below.
Class description:
Write messages to stdout and stderr. Allows to filter the messages to be displayed through a verbose level, also allows to control if child process that produce output through a file descriptor should be redirected to /dev/null
Method signatures and... | Implement the Python class `Msg` described below.
Class description:
Write messages to stdout and stderr. Allows to filter the messages to be displayed through a verbose level, also allows to control if child process that produce output through a file descriptor should be redirected to /dev/null
Method signatures and... | f50104a4ee9c83af207a2de1aef46e2f1ec67379 | <|skeleton|>
class Msg:
"""Write messages to stdout and stderr. Allows to filter the messages to be displayed through a verbose level, also allows to control if child process that produce output through a file descriptor should be redirected to /dev/null"""
def __init__(self, new_level=None):
"""Initia... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Msg:
"""Write messages to stdout and stderr. Allows to filter the messages to be displayed through a verbose level, also allows to control if child process that produce output through a file descriptor should be redirected to /dev/null"""
def __init__(self, new_level=None):
"""Initialize Msg leve... | the_stack_v2_python_sparse | udocker/msg.py | indigo-dc/udocker | train | 1,121 |
9195d92fbcaf14c4e970203f0d86e8062dc87da8 | [
"super(CompoundForm, self).__init__(*args, **kwargs)\nself.compound = None\nself.chemSpider = ChemSpider(settings.CHEMSPIDER_TOKEN)\nself.fields['labGroup'].queryset = user.labgroup_set.all()\nif user.labgroup_set.all().exists():\n self.fields['labGroup'].empty_label = None",
"searchResults = self.chemSpider.s... | <|body_start_0|>
super(CompoundForm, self).__init__(*args, **kwargs)
self.compound = None
self.chemSpider = ChemSpider(settings.CHEMSPIDER_TOKEN)
self.fields['labGroup'].queryset = user.labgroup_set.all()
if user.labgroup_set.all().exists():
self.fields['labGroup'].em... | A form for users to add compounds to the compound guide. Forces a check against the chemspider database to ensure no spurious compounds make their way into the compound guide. | CompoundForm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CompoundForm:
"""A form for users to add compounds to the compound guide. Forces a check against the chemspider database to ensure no spurious compounds make their way into the compound guide."""
def __init__(self, user, *args, **kwargs):
"""Overridden version of the init method allo... | stack_v2_sparse_classes_75kplus_train_003763 | 9,303 | no_license | [
{
"docstring": "Overridden version of the init method allows us to place the user's lab groups as a restricted set.",
"name": "__init__",
"signature": "def __init__(self, user, *args, **kwargs)"
},
{
"docstring": "Check that the CSID is actually a valid id from chemspider.",
"name": "clean_C... | 4 | stack_v2_sparse_classes_30k_train_030633 | Implement the Python class `CompoundForm` described below.
Class description:
A form for users to add compounds to the compound guide. Forces a check against the chemspider database to ensure no spurious compounds make their way into the compound guide.
Method signatures and docstrings:
- def __init__(self, user, *ar... | Implement the Python class `CompoundForm` described below.
Class description:
A form for users to add compounds to the compound guide. Forces a check against the chemspider database to ensure no spurious compounds make their way into the compound guide.
Method signatures and docstrings:
- def __init__(self, user, *ar... | eae2009eadf87ffd2378233f3e153d385f4654d2 | <|skeleton|>
class CompoundForm:
"""A form for users to add compounds to the compound guide. Forces a check against the chemspider database to ensure no spurious compounds make their way into the compound guide."""
def __init__(self, user, *args, **kwargs):
"""Overridden version of the init method allo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CompoundForm:
"""A form for users to add compounds to the compound guide. Forces a check against the chemspider database to ensure no spurious compounds make their way into the compound guide."""
def __init__(self, user, *args, **kwargs):
"""Overridden version of the init method allows us to plac... | the_stack_v2_python_sparse | DRP/forms/compound/modelforms.py | zhaojhao/DRP | train | 0 |
87d3fa012c78f75bc18022837963c26b26839da6 | [
"threading.Thread.__init__(self, *args, **kw)\nself.queue = q\nself.workers = N\nself.sorting = sorting\nself.output = []",
"while self.workers:\n p = self.queue.get()\n if p is None:\n self.workers -= 1\n else:\n self.output.append(p)\nprint('Length of Final String: {} chars'.format(len(se... | <|body_start_0|>
threading.Thread.__init__(self, *args, **kw)
self.queue = q
self.workers = N
self.sorting = sorting
self.output = []
<|end_body_0|>
<|body_start_1|>
while self.workers:
p = self.queue.get()
if p is None:
self.worke... | OutThread | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OutThread:
def __init__(self, N, q, sorting=True, *args, **kw):
"""Initialize thread and save queue reference."""
<|body_0|>
def run(self):
"""Extract items from the output queue and print until all done"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_003764 | 1,297 | no_license | [
{
"docstring": "Initialize thread and save queue reference.",
"name": "__init__",
"signature": "def __init__(self, N, q, sorting=True, *args, **kw)"
},
{
"docstring": "Extract items from the output queue and print until all done",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020465 | Implement the Python class `OutThread` described below.
Class description:
Implement the OutThread class.
Method signatures and docstrings:
- def __init__(self, N, q, sorting=True, *args, **kw): Initialize thread and save queue reference.
- def run(self): Extract items from the output queue and print until all done | Implement the Python class `OutThread` described below.
Class description:
Implement the OutThread class.
Method signatures and docstrings:
- def __init__(self, N, q, sorting=True, *args, **kw): Initialize thread and save queue reference.
- def run(self): Extract items from the output queue and print until all done
... | b32f83aa1b705a5ad384b73c618f04f7d2622753 | <|skeleton|>
class OutThread:
def __init__(self, N, q, sorting=True, *args, **kw):
"""Initialize thread and save queue reference."""
<|body_0|>
def run(self):
"""Extract items from the output queue and print until all done"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OutThread:
def __init__(self, N, q, sorting=True, *args, **kw):
"""Initialize thread and save queue reference."""
threading.Thread.__init__(self, *args, **kw)
self.queue = q
self.workers = N
self.sorting = sorting
self.output = []
def run(self):
"""... | the_stack_v2_python_sparse | ostPython4/output.py | deepbsd/OST_Python | train | 1 | |
60a03e5b5fe81c9dc1e08ca8ed48f6f3e3442d15 | [
"self.analyzer = analyzer\nself.running = True\nTealThread.__init__(self)\nreturn",
"try:\n try:\n while self.running:\n func, item = self.analyzer.queue.get()\n try:\n func(item)\n except ThreadKilled:\n raise\n except:\n ... | <|body_start_0|>
self.analyzer = analyzer
self.running = True
TealThread.__init__(self)
return
<|end_body_0|>
<|body_start_1|>
try:
try:
while self.running:
func, item = self.analyzer.queue.get()
try:
... | This class is used to spawn a separate thread to run the analyzer in | AnalyzerAsynch | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AnalyzerAsynch:
"""This class is used to spawn a separate thread to run the analyzer in"""
def __init__(self, analyzer):
"""Constructor"""
<|body_0|>
def run(self):
"""Wait on the input queue"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.... | stack_v2_sparse_classes_75kplus_train_003765 | 24,649 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, analyzer)"
},
{
"docstring": "Wait on the input queue",
"name": "run",
"signature": "def run(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_002144 | Implement the Python class `AnalyzerAsynch` described below.
Class description:
This class is used to spawn a separate thread to run the analyzer in
Method signatures and docstrings:
- def __init__(self, analyzer): Constructor
- def run(self): Wait on the input queue | Implement the Python class `AnalyzerAsynch` described below.
Class description:
This class is used to spawn a separate thread to run the analyzer in
Method signatures and docstrings:
- def __init__(self, analyzer): Constructor
- def run(self): Wait on the input queue
<|skeleton|>
class AnalyzerAsynch:
"""This cl... | eba6c1489b503fdcf040a126942643b355867bcd | <|skeleton|>
class AnalyzerAsynch:
"""This class is used to spawn a separate thread to run the analyzer in"""
def __init__(self, analyzer):
"""Constructor"""
<|body_0|>
def run(self):
"""Wait on the input queue"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AnalyzerAsynch:
"""This class is used to spawn a separate thread to run the analyzer in"""
def __init__(self, analyzer):
"""Constructor"""
self.analyzer = analyzer
self.running = True
TealThread.__init__(self)
return
def run(self):
"""Wait on the input... | the_stack_v2_python_sparse | src/ibm/teal/analyzer/analyzer.py | ppjsand/pyteal | train | 1 |
202f46bca7ca06dc9848361e4647c25c8c85317c | [
"expired, invalid, user = confirm_email_token_status(token)\nif not user or invalid:\n _abort(get_message('INVALID_CONFIRMATION_TOKEN'))\nalready_confirmed = user is not None and user.confirmed_at is not None\nif expired and (not already_confirmed):\n _abort(get_message('CONFIRMATION_EXPIRED', email=user.emai... | <|body_start_0|>
expired, invalid, user = confirm_email_token_status(token)
if not user or invalid:
_abort(get_message('INVALID_CONFIRMATION_TOKEN'))
already_confirmed = user is not None and user.confirmed_at is not None
if expired and (not already_confirmed):
_ab... | View that handles a email confirmation request. | ConfirmEmailView | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConfirmEmailView:
"""View that handles a email confirmation request."""
def get_user(self, token=None, **kwargs):
"""Retrieve a user by the provided arguments."""
<|body_0|>
def post(self, **kwargs):
"""Confirm user email."""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_75kplus_train_003766 | 19,229 | permissive | [
{
"docstring": "Retrieve a user by the provided arguments.",
"name": "get_user",
"signature": "def get_user(self, token=None, **kwargs)"
},
{
"docstring": "Confirm user email.",
"name": "post",
"signature": "def post(self, **kwargs)"
}
] | 2 | null | Implement the Python class `ConfirmEmailView` described below.
Class description:
View that handles a email confirmation request.
Method signatures and docstrings:
- def get_user(self, token=None, **kwargs): Retrieve a user by the provided arguments.
- def post(self, **kwargs): Confirm user email. | Implement the Python class `ConfirmEmailView` described below.
Class description:
View that handles a email confirmation request.
Method signatures and docstrings:
- def get_user(self, token=None, **kwargs): Retrieve a user by the provided arguments.
- def post(self, **kwargs): Confirm user email.
<|skeleton|>
class... | 3caced556fdc5fe5737416e8672fa8e4c03cdb7f | <|skeleton|>
class ConfirmEmailView:
"""View that handles a email confirmation request."""
def get_user(self, token=None, **kwargs):
"""Retrieve a user by the provided arguments."""
<|body_0|>
def post(self, **kwargs):
"""Confirm user email."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ConfirmEmailView:
"""View that handles a email confirmation request."""
def get_user(self, token=None, **kwargs):
"""Retrieve a user by the provided arguments."""
expired, invalid, user = confirm_email_token_status(token)
if not user or invalid:
_abort(get_message('INV... | the_stack_v2_python_sparse | invenio_accounts/views/rest.py | inveniosoftware/invenio-accounts | train | 5 |
0fac23f0c9200a8706078c2e92389f4385c455a8 | [
"labextensions_path = labextensions_path or []\next_paths = []\nfor ext_dir in labextensions_path:\n theme_pattern = ext_dir + '/**/themes'\n ext_paths.extend([path for path in glob(theme_pattern, recursive=True)])\nif not isinstance(path, list):\n path = [path]\npath = ext_paths + path\nFileFindHandler.in... | <|body_start_0|>
labextensions_path = labextensions_path or []
ext_paths = []
for ext_dir in labextensions_path:
theme_pattern = ext_dir + '/**/themes'
ext_paths.extend([path for path in glob(theme_pattern, recursive=True)])
if not isinstance(path, list):
... | A file handler that mangles local urls in CSS files. | ThemesHandler | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ThemesHandler:
"""A file handler that mangles local urls in CSS files."""
def initialize(self, path, default_filename=None, no_cache_paths=None, themes_url=None, labextensions_path=None, **kwargs):
"""Initialize the handler."""
<|body_0|>
def get_content(self, abspath, s... | stack_v2_sparse_classes_75kplus_train_003767 | 3,206 | permissive | [
{
"docstring": "Initialize the handler.",
"name": "initialize",
"signature": "def initialize(self, path, default_filename=None, no_cache_paths=None, themes_url=None, labextensions_path=None, **kwargs)"
},
{
"docstring": "Retrieve the content of the requested resource which is located at the give... | 4 | stack_v2_sparse_classes_30k_train_042286 | Implement the Python class `ThemesHandler` described below.
Class description:
A file handler that mangles local urls in CSS files.
Method signatures and docstrings:
- def initialize(self, path, default_filename=None, no_cache_paths=None, themes_url=None, labextensions_path=None, **kwargs): Initialize the handler.
- ... | Implement the Python class `ThemesHandler` described below.
Class description:
A file handler that mangles local urls in CSS files.
Method signatures and docstrings:
- def initialize(self, path, default_filename=None, no_cache_paths=None, themes_url=None, labextensions_path=None, **kwargs): Initialize the handler.
- ... | b3e9bc150e64c1c915ab600557ea267783939684 | <|skeleton|>
class ThemesHandler:
"""A file handler that mangles local urls in CSS files."""
def initialize(self, path, default_filename=None, no_cache_paths=None, themes_url=None, labextensions_path=None, **kwargs):
"""Initialize the handler."""
<|body_0|>
def get_content(self, abspath, s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ThemesHandler:
"""A file handler that mangles local urls in CSS files."""
def initialize(self, path, default_filename=None, no_cache_paths=None, themes_url=None, labextensions_path=None, **kwargs):
"""Initialize the handler."""
labextensions_path = labextensions_path or []
ext_pat... | the_stack_v2_python_sparse | jupyterlab_server/themes_handler.py | jupyterlab/jupyterlab_server | train | 108 |
f2f2e397e5c3d816e0664f9b35e93a2710c3b6b4 | [
"so_far = []\n\ndef dfs(node):\n if not node:\n so_far.append('None')\n return\n so_far.append(str(node.val))\n dfs(node.left)\n dfs(node.right)\ndfs(root)\nreturn ','.join(so_far)",
"def create_tree(node_list):\n first_elem_val = node_list.pop(0)\n if first_elem_val == 'None':\n ... | <|body_start_0|>
so_far = []
def dfs(node):
if not node:
so_far.append('None')
return
so_far.append(str(node.val))
dfs(node.left)
dfs(node.right)
dfs(root)
return ','.join(so_far)
<|end_body_0|>
<|body_star... | 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_75kplus_train_003768 | 2,410 | 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 | stack_v2_sparse_classes_30k_train_025323 | 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:... | a5635356953df472e71d49c8db3b493ac59b860f | <|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_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Codec:
def serialize(self, root):
"""Encodes a tree to a single string. :type root: TreeNode :rtype: str"""
so_far = []
def dfs(node):
if not node:
so_far.append('None')
return
so_far.append(str(node.val))
dfs(node.le... | the_stack_v2_python_sparse | python/tree/q449_serialize_second.py | ksparkje/leetcode-practice | train | 1 | |
68024d45a6397e03ccc2bd7a7bfe9c0bd4ec51c5 | [
"list_ = List.objects.create()\nfirst_item = Item.objects.create(text='Hai', list=list_)\nnew_item = {'item_text': 'new item!'}\nself.client.post(f'/lists/{list_.id}/add_item', data=new_item)\nresponse = self.client.get(f'/lists/{list_.id}/')\nself.assertEqual(response.status_code, 200)\nself.assertContains(respons... | <|body_start_0|>
list_ = List.objects.create()
first_item = Item.objects.create(text='Hai', list=list_)
new_item = {'item_text': 'new item!'}
self.client.post(f'/lists/{list_.id}/add_item', data=new_item)
response = self.client.get(f'/lists/{list_.id}/')
self.assertEqual(... | Tests the addition of new items to a current list | NewItemTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NewItemTest:
"""Tests the addition of new items to a current list"""
def test_can_save_a_post_request_to_an_existing_list(self):
"""as written by me!"""
<|body_0|>
def test_can_save_a_post_request_to_an_existing_list_book(self):
"""as appears on the book"""
... | stack_v2_sparse_classes_75kplus_train_003769 | 6,998 | no_license | [
{
"docstring": "as written by me!",
"name": "test_can_save_a_post_request_to_an_existing_list",
"signature": "def test_can_save_a_post_request_to_an_existing_list(self)"
},
{
"docstring": "as appears on the book",
"name": "test_can_save_a_post_request_to_an_existing_list_book",
"signatur... | 3 | null | Implement the Python class `NewItemTest` described below.
Class description:
Tests the addition of new items to a current list
Method signatures and docstrings:
- def test_can_save_a_post_request_to_an_existing_list(self): as written by me!
- def test_can_save_a_post_request_to_an_existing_list_book(self): as appears... | Implement the Python class `NewItemTest` described below.
Class description:
Tests the addition of new items to a current list
Method signatures and docstrings:
- def test_can_save_a_post_request_to_an_existing_list(self): as written by me!
- def test_can_save_a_post_request_to_an_existing_list_book(self): as appears... | 41651b51cade98cd4fe22c248ac67ba90ce68f25 | <|skeleton|>
class NewItemTest:
"""Tests the addition of new items to a current list"""
def test_can_save_a_post_request_to_an_existing_list(self):
"""as written by me!"""
<|body_0|>
def test_can_save_a_post_request_to_an_existing_list_book(self):
"""as appears on the book"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NewItemTest:
"""Tests the addition of new items to a current list"""
def test_can_save_a_post_request_to_an_existing_list(self):
"""as written by me!"""
list_ = List.objects.create()
first_item = Item.objects.create(text='Hai', list=list_)
new_item = {'item_text': 'new ite... | the_stack_v2_python_sparse | tdd-python/project01/superlists/lists/tests.py | fbidu/Etudes | train | 2 |
e94d8964679264d6e5b9a26d94c73a57982fc7bc | [
"new_list = sorted(points, key=lambda point: (point[0], point[1]))\nprint(new_list)\nif len(new_list) <= 0:\n return 0\nend = new_list[0][1]\ncount = 1\nfor i in new_list[1:]:\n if i[0] <= end:\n end = min(end, i[1])\n continue\n else:\n count += 1\n end = i[1]\nreturn count",
... | <|body_start_0|>
new_list = sorted(points, key=lambda point: (point[0], point[1]))
print(new_list)
if len(new_list) <= 0:
return 0
end = new_list[0][1]
count = 1
for i in new_list[1:]:
if i[0] <= end:
end = min(end, i[1])
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMinArrowShots(self, points):
""":type points: List[List[int]] :rtype: int 209ms"""
<|body_0|>
def findMinArrowShots_1(self, points):
""":type points: List[List[int]] :rtype: int 122ms"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_003770 | 2,261 | no_license | [
{
"docstring": ":type points: List[List[int]] :rtype: int 209ms",
"name": "findMinArrowShots",
"signature": "def findMinArrowShots(self, points)"
},
{
"docstring": ":type points: List[List[int]] :rtype: int 122ms",
"name": "findMinArrowShots_1",
"signature": "def findMinArrowShots_1(self... | 2 | stack_v2_sparse_classes_30k_train_015092 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMinArrowShots(self, points): :type points: List[List[int]] :rtype: int 209ms
- def findMinArrowShots_1(self, points): :type points: List[List[int]] :rtype: int 122ms | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMinArrowShots(self, points): :type points: List[List[int]] :rtype: int 209ms
- def findMinArrowShots_1(self, points): :type points: List[List[int]] :rtype: int 122ms
<|s... | 679a2b246b8b6bb7fc55ed1c8096d3047d6d4461 | <|skeleton|>
class Solution:
def findMinArrowShots(self, points):
""":type points: List[List[int]] :rtype: int 209ms"""
<|body_0|>
def findMinArrowShots_1(self, points):
""":type points: List[List[int]] :rtype: int 122ms"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def findMinArrowShots(self, points):
""":type points: List[List[int]] :rtype: int 209ms"""
new_list = sorted(points, key=lambda point: (point[0], point[1]))
print(new_list)
if len(new_list) <= 0:
return 0
end = new_list[0][1]
count = 1
... | the_stack_v2_python_sparse | Minimum NumberOfArrowsToBurstBalloons_MID_452.py | 953250587/leetcode-python | train | 2 | |
8eeb7cdcd401bb143d843667d6ab05850e646e07 | [
"tkinter.ttk.Frame.__init__(self, parent)\nself.parent = parent\nself.var = var\nself.funcs = funcs\nself.kwargs = kwargs\nself.label = tkinter.ttk.Label(self, textvariable=self.var, **self.kwargs)\nself.entry = tkinter.ttk.Entry(self, textvariable=self.var, **self.kwargs)\nself.label.bind('<Double-Button-1>', self... | <|body_start_0|>
tkinter.ttk.Frame.__init__(self, parent)
self.parent = parent
self.var = var
self.funcs = funcs
self.kwargs = kwargs
self.label = tkinter.ttk.Label(self, textvariable=self.var, **self.kwargs)
self.entry = tkinter.ttk.Entry(self, textvariable=self.... | ModifiableLabel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModifiableLabel:
def __init__(self, parent, var, funcs=(None, None), **kwargs):
""":param parent: parent frame or window :param var: variable stocking the string :param funcs: tuple of two functions called :param kwargs: passed to entry and label widgets"""
<|body_0|>
def sh... | stack_v2_sparse_classes_75kplus_train_003771 | 36,391 | permissive | [
{
"docstring": ":param parent: parent frame or window :param var: variable stocking the string :param funcs: tuple of two functions called :param kwargs: passed to entry and label widgets",
"name": "__init__",
"signature": "def __init__(self, parent, var, funcs=(None, None), **kwargs)"
},
{
"doc... | 3 | stack_v2_sparse_classes_30k_train_052408 | Implement the Python class `ModifiableLabel` described below.
Class description:
Implement the ModifiableLabel class.
Method signatures and docstrings:
- def __init__(self, parent, var, funcs=(None, None), **kwargs): :param parent: parent frame or window :param var: variable stocking the string :param funcs: tuple of... | Implement the Python class `ModifiableLabel` described below.
Class description:
Implement the ModifiableLabel class.
Method signatures and docstrings:
- def __init__(self, parent, var, funcs=(None, None), **kwargs): :param parent: parent frame or window :param var: variable stocking the string :param funcs: tuple of... | c6d8091239712df209914fcf6490c0fdca92c741 | <|skeleton|>
class ModifiableLabel:
def __init__(self, parent, var, funcs=(None, None), **kwargs):
""":param parent: parent frame or window :param var: variable stocking the string :param funcs: tuple of two functions called :param kwargs: passed to entry and label widgets"""
<|body_0|>
def sh... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ModifiableLabel:
def __init__(self, parent, var, funcs=(None, None), **kwargs):
""":param parent: parent frame or window :param var: variable stocking the string :param funcs: tuple of two functions called :param kwargs: passed to entry and label widgets"""
tkinter.ttk.Frame.__init__(self, par... | the_stack_v2_python_sparse | tkinter_utilities.py | PyDEF/PyDEF-2.0 | train | 1 | |
a8a148c64de5c00d6e3e3fb29f6fa235012c3aa1 | [
"self.front = -1\nself.rare = -1\nself.max_size = 5\nself.queue = [0] * self.max_size",
"if self.front == 0 and self.rare == self.max_size - 1 or self.front == self.rare + 1:\n print('Overflow')\nelse:\n if self.front == -1:\n self.front = 0\n self.rare = 0\n elif self.rare == self.max_size... | <|body_start_0|>
self.front = -1
self.rare = -1
self.max_size = 5
self.queue = [0] * self.max_size
<|end_body_0|>
<|body_start_1|>
if self.front == 0 and self.rare == self.max_size - 1 or self.front == self.rare + 1:
print('Overflow')
else:
if sel... | This class contains functions for doubly ended queue. | deQueue | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class deQueue:
"""This class contains functions for doubly ended queue."""
def __init__(self):
"""Constructor function. Argument: self -- represents the object of the class."""
<|body_0|>
def insert_rare(self, item):
"""This function inserts at the rare position. Argum... | stack_v2_sparse_classes_75kplus_train_003772 | 3,636 | no_license | [
{
"docstring": "Constructor function. Argument: self -- represents the object of the class.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "This function inserts at the rare position. Arguments: self -- represents the object of the class. item -- integer value, the val... | 6 | stack_v2_sparse_classes_30k_train_018368 | Implement the Python class `deQueue` described below.
Class description:
This class contains functions for doubly ended queue.
Method signatures and docstrings:
- def __init__(self): Constructor function. Argument: self -- represents the object of the class.
- def insert_rare(self, item): This function inserts at the... | Implement the Python class `deQueue` described below.
Class description:
This class contains functions for doubly ended queue.
Method signatures and docstrings:
- def __init__(self): Constructor function. Argument: self -- represents the object of the class.
- def insert_rare(self, item): This function inserts at the... | 6870426104aef417086788221dad29e887ddfe3f | <|skeleton|>
class deQueue:
"""This class contains functions for doubly ended queue."""
def __init__(self):
"""Constructor function. Argument: self -- represents the object of the class."""
<|body_0|>
def insert_rare(self, item):
"""This function inserts at the rare position. Argum... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class deQueue:
"""This class contains functions for doubly ended queue."""
def __init__(self):
"""Constructor function. Argument: self -- represents the object of the class."""
self.front = -1
self.rare = -1
self.max_size = 5
self.queue = [0] * self.max_size
def ins... | the_stack_v2_python_sparse | Data Structure/03. Queue/03. Doubly Ended Queue/py_code.py | Slothfulwave612/Coding-Problems | train | 5 |
b956596338ec082f9ab18daa3abece65b6978826 | [
"employees = []\ntry:\n with transaction.atomic():\n for employee in data['employees']:\n user = self.find_or_create_user(employee['email'])\n token, _ = Token.objects.get_or_create(user=user)\n company = Company.objects.get(id=data['company_id'])\n self.__creat... | <|body_start_0|>
employees = []
try:
with transaction.atomic():
for employee in data['employees']:
user = self.find_or_create_user(employee['email'])
token, _ = Token.objects.get_or_create(user=user)
company = Compan... | Employees serializer list. | EmployeesSerializer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EmployeesSerializer:
"""Employees serializer list."""
def create(self, data):
"""Create employees."""
<|body_0|>
def to_representation(self, instance):
"""Represent serializer data."""
<|body_1|>
def find_or_create_user(self, email):
"""Find ... | stack_v2_sparse_classes_75kplus_train_003773 | 3,659 | no_license | [
{
"docstring": "Create employees.",
"name": "create",
"signature": "def create(self, data)"
},
{
"docstring": "Represent serializer data.",
"name": "to_representation",
"signature": "def to_representation(self, instance)"
},
{
"docstring": "Find or create user by email.",
"na... | 5 | stack_v2_sparse_classes_30k_train_040368 | Implement the Python class `EmployeesSerializer` described below.
Class description:
Employees serializer list.
Method signatures and docstrings:
- def create(self, data): Create employees.
- def to_representation(self, instance): Represent serializer data.
- def find_or_create_user(self, email): Find or create user ... | Implement the Python class `EmployeesSerializer` described below.
Class description:
Employees serializer list.
Method signatures and docstrings:
- def create(self, data): Create employees.
- def to_representation(self, instance): Represent serializer data.
- def find_or_create_user(self, email): Find or create user ... | 252b0ebd77eefbcc945a0efc3068cc3421f46d5f | <|skeleton|>
class EmployeesSerializer:
"""Employees serializer list."""
def create(self, data):
"""Create employees."""
<|body_0|>
def to_representation(self, instance):
"""Represent serializer data."""
<|body_1|>
def find_or_create_user(self, email):
"""Find ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EmployeesSerializer:
"""Employees serializer list."""
def create(self, data):
"""Create employees."""
employees = []
try:
with transaction.atomic():
for employee in data['employees']:
user = self.find_or_create_user(employee['email']... | the_stack_v2_python_sparse | app/companies/serializers/employees_serializer.py | vsokoltsov/Interview360Server | train | 2 |
34e0d578c4c401fbd18d61e0b2ed758f5523bb73 | [
"instance = get_object_or_404(Mapping, pk=pk)\ndata = request.data\nif request.FILES or 'files' in data:\n return self.partial_update_with_files(request, instance)\nif 'xforms' not in data:\n return Response(data={'xforms': [_('This field is required')]}, status=status.HTTP_400_BAD_REQUEST)\nreturn self.parti... | <|body_start_0|>
instance = get_object_or_404(Mapping, pk=pk)
data = request.data
if request.FILES or 'files' in data:
return self.partial_update_with_files(request, instance)
if 'xforms' not in data:
return Response(data={'xforms': [_('This field is required')]},... | Create new Mapping entries. | MappingViewSet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MappingViewSet:
"""Create new Mapping entries."""
def partial_update(self, request, pk, *args, **kwargs):
"""We are posting the xForms in only one call, to update them all together. There are two options: - JSON format - Multipart format The first case will be straight forward, the s... | stack_v2_sparse_classes_75kplus_train_003774 | 15,950 | permissive | [
{
"docstring": "We are posting the xForms in only one call, to update them all together. There are two options: - JSON format - Multipart format The first case will be straight forward, the second one will imply FILES. This means that only a list with the xform id and the file will be sent. The xforms will be c... | 3 | null | Implement the Python class `MappingViewSet` described below.
Class description:
Create new Mapping entries.
Method signatures and docstrings:
- def partial_update(self, request, pk, *args, **kwargs): We are posting the xForms in only one call, to update them all together. There are two options: - JSON format - Multip... | Implement the Python class `MappingViewSet` described below.
Class description:
Create new Mapping entries.
Method signatures and docstrings:
- def partial_update(self, request, pk, *args, **kwargs): We are posting the xForms in only one call, to update them all together. There are two options: - JSON format - Multip... | 36cc8c2d7d9fb4f7bd9cf6019f8d726e18540dc9 | <|skeleton|>
class MappingViewSet:
"""Create new Mapping entries."""
def partial_update(self, request, pk, *args, **kwargs):
"""We are posting the xForms in only one call, to update them all together. There are two options: - JSON format - Multipart format The first case will be straight forward, the s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class MappingViewSet:
"""Create new Mapping entries."""
def partial_update(self, request, pk, *args, **kwargs):
"""We are posting the xForms in only one call, to update them all together. There are two options: - JSON format - Multipart format The first case will be straight forward, the second one wil... | the_stack_v2_python_sparse | aether-odk-module/aether/odk/api/views.py | zabi-kamran/aether | train | 0 |
3bf4e22d92209198c370e2ad995abc2083cb1475 | [
"if 'partial_game_from' in kwargs.keys():\n self.game = kwargs['partial_game_from']\n self.attacker_types = kwargs['attacker_types']\n self._create_partial_game()\nelif 'game' in kwargs.keys():\n self.game = kwargs['game']\n if self.game.type == 'compact':\n self._compact_to_normal()\n ... | <|body_start_0|>
if 'partial_game_from' in kwargs.keys():
self.game = kwargs['partial_game_from']
self.attacker_types = kwargs['attacker_types']
self._create_partial_game()
elif 'game' in kwargs.keys():
self.game = kwargs['game']
if self.game.t... | NormalFormGame | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NormalFormGame:
def __init__(self, **kwargs):
"""Transform given game into normalform if it's compact form, Conduct harsanyi transformation if requested or if given game is already in normalform. Otherwise, generate a random game given arguments."""
<|body_0|>
def _generate_... | stack_v2_sparse_classes_75kplus_train_003775 | 16,375 | no_license | [
{
"docstring": "Transform given game into normalform if it's compact form, Conduct harsanyi transformation if requested or if given game is already in normalform. Otherwise, generate a random game given arguments.",
"name": "__init__",
"signature": "def __init__(self, **kwargs)"
},
{
"docstring"... | 6 | stack_v2_sparse_classes_30k_train_030294 | Implement the Python class `NormalFormGame` described below.
Class description:
Implement the NormalFormGame class.
Method signatures and docstrings:
- def __init__(self, **kwargs): Transform given game into normalform if it's compact form, Conduct harsanyi transformation if requested or if given game is already in n... | Implement the Python class `NormalFormGame` described below.
Class description:
Implement the NormalFormGame class.
Method signatures and docstrings:
- def __init__(self, **kwargs): Transform given game into normalform if it's compact form, Conduct harsanyi transformation if requested or if given game is already in n... | 44a0df025ca73065f291994df103dcb39da59b55 | <|skeleton|>
class NormalFormGame:
def __init__(self, **kwargs):
"""Transform given game into normalform if it's compact form, Conduct harsanyi transformation if requested or if given game is already in normalform. Otherwise, generate a random game given arguments."""
<|body_0|>
def _generate_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class NormalFormGame:
def __init__(self, **kwargs):
"""Transform given game into normalform if it's compact form, Conduct harsanyi transformation if requested or if given game is already in normalform. Otherwise, generate a random game given arguments."""
if 'partial_game_from' in kwargs.keys():
... | the_stack_v2_python_sparse | games.py | adriangonciarz/game_theory | train | 0 | |
1a98cc9ab99016897fb2d2a97ac2904ffffa5978 | [
"filename = 'rented_items.csv'\nfile = open(filename, 'a')\nfile.close()\nwith open('test_items.csv', 'a', newline='') as file:\n writer = csv.writer(file)\n writer.writerow(['LR04', 'Leather Sofa', 25.0])\n writer.writerow(['KT78', 'Kitchen Tablee', 10.0])\n writer.writerow(['BR02', 'Queen Mattress', 1... | <|body_start_0|>
filename = 'rented_items.csv'
file = open(filename, 'a')
file.close()
with open('test_items.csv', 'a', newline='') as file:
writer = csv.writer(file)
writer.writerow(['LR04', 'Leather Sofa', 25.0])
writer.writerow(['KT78', 'Kitchen Tab... | Tests the inventory functionalities | TestInventory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestInventory:
"""Tests the inventory functionalities"""
def setUp(self):
"""Sets up the environment for testing"""
<|body_0|>
def tearDown(self):
"""Tears down all creations for testing"""
<|body_1|>
def test_add_furniture(self):
"""test to ... | stack_v2_sparse_classes_75kplus_train_003776 | 2,415 | no_license | [
{
"docstring": "Sets up the environment for testing",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Tears down all creations for testing",
"name": "tearDown",
"signature": "def tearDown(self)"
},
{
"docstring": "test to make sure an entry is added to the file... | 4 | stack_v2_sparse_classes_30k_train_043623 | Implement the Python class `TestInventory` described below.
Class description:
Tests the inventory functionalities
Method signatures and docstrings:
- def setUp(self): Sets up the environment for testing
- def tearDown(self): Tears down all creations for testing
- def test_add_furniture(self): test to make sure an en... | Implement the Python class `TestInventory` described below.
Class description:
Tests the inventory functionalities
Method signatures and docstrings:
- def setUp(self): Sets up the environment for testing
- def tearDown(self): Tears down all creations for testing
- def test_add_furniture(self): test to make sure an en... | 5dac60f39e3909ff05b26721d602ed20f14d6be3 | <|skeleton|>
class TestInventory:
"""Tests the inventory functionalities"""
def setUp(self):
"""Sets up the environment for testing"""
<|body_0|>
def tearDown(self):
"""Tears down all creations for testing"""
<|body_1|>
def test_add_furniture(self):
"""test to ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestInventory:
"""Tests the inventory functionalities"""
def setUp(self):
"""Sets up the environment for testing"""
filename = 'rented_items.csv'
file = open(filename, 'a')
file.close()
with open('test_items.csv', 'a', newline='') as file:
writer = csv.... | the_stack_v2_python_sparse | students/humberto_gonzalez/lesson08/test_unit.py | JavaRod/SP_Python220B_2019 | train | 1 |
bac7b55908cf76bd816555628da09384d3d2d77d | [
"def path(x: int, y: int) -> int:\n if x == 0 or y == 0:\n return 1\n return path(x - 1, y) + path(x, y - 1)\nreturn path(m - 1, n - 1)",
"if m == 0 or n == 0:\n return 0\ndp = [[0] * n for _ in range(m)]\nfor i in range(m):\n dp[i][0] = 1\nfor i in range(n):\n dp[0][i] = 1\nfor i in range(1... | <|body_start_0|>
def path(x: int, y: int) -> int:
if x == 0 or y == 0:
return 1
return path(x - 1, y) + path(x, y - 1)
return path(m - 1, n - 1)
<|end_body_0|>
<|body_start_1|>
if m == 0 or n == 0:
return 0
dp = [[0] * n for _ in range... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def uniquePaths(self, m: int, n: int) -> int:
"""递归"""
<|body_0|>
def uniquePaths_2(self, m: int, n: int) -> int:
"""动态规划, 时间复杂度O(m*n), 空间复杂度O(m*n)"""
<|body_1|>
def uniquePaths_3(self, m: int, n: int) -> int:
"""优化动态规划, 通过画表可以将空间复杂度优化为... | stack_v2_sparse_classes_75kplus_train_003777 | 2,196 | no_license | [
{
"docstring": "递归",
"name": "uniquePaths",
"signature": "def uniquePaths(self, m: int, n: int) -> int"
},
{
"docstring": "动态规划, 时间复杂度O(m*n), 空间复杂度O(m*n)",
"name": "uniquePaths_2",
"signature": "def uniquePaths_2(self, m: int, n: int) -> int"
},
{
"docstring": "优化动态规划, 通过画表可以将空间复... | 3 | stack_v2_sparse_classes_30k_train_000469 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniquePaths(self, m: int, n: int) -> int: 递归
- def uniquePaths_2(self, m: int, n: int) -> int: 动态规划, 时间复杂度O(m*n), 空间复杂度O(m*n)
- def uniquePaths_3(self, m: int, n: int) -> int... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniquePaths(self, m: int, n: int) -> int: 递归
- def uniquePaths_2(self, m: int, n: int) -> int: 动态规划, 时间复杂度O(m*n), 空间复杂度O(m*n)
- def uniquePaths_3(self, m: int, n: int) -> int... | 13e7ec9fe7a92ab13b247bd4edeb1ada5de81a08 | <|skeleton|>
class Solution:
def uniquePaths(self, m: int, n: int) -> int:
"""递归"""
<|body_0|>
def uniquePaths_2(self, m: int, n: int) -> int:
"""动态规划, 时间复杂度O(m*n), 空间复杂度O(m*n)"""
<|body_1|>
def uniquePaths_3(self, m: int, n: int) -> int:
"""优化动态规划, 通过画表可以将空间复杂度优化为... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def uniquePaths(self, m: int, n: int) -> int:
"""递归"""
def path(x: int, y: int) -> int:
if x == 0 or y == 0:
return 1
return path(x - 1, y) + path(x, y - 1)
return path(m - 1, n - 1)
def uniquePaths_2(self, m: int, n: int) -> int:
... | the_stack_v2_python_sparse | Algorithms/62_Unique_Paths/Unique_Paths.py | lirui-ML/my_leetcode | train | 1 | |
12163a0ec70b6745928f98b90f40bab8f2833585 | [
"super(SMPLFlow, self).__init__()\nself.cfg = cfg\nself.npose = 6 * (cfg.SMPL.NUM_BODY_JOINTS + 1)\nself.flow = ConditionalGlow(cfg.MODEL.FLOW.DIM, cfg.MODEL.FLOW.LAYER_HIDDEN_FEATURES, cfg.MODEL.FLOW.NUM_LAYERS, cfg.MODEL.FLOW.LAYER_DEPTH, context_features=cfg.MODEL.FLOW.CONTEXT_FEATURES)\nself.fc_head = FCHead(cf... | <|body_start_0|>
super(SMPLFlow, self).__init__()
self.cfg = cfg
self.npose = 6 * (cfg.SMPL.NUM_BODY_JOINTS + 1)
self.flow = ConditionalGlow(cfg.MODEL.FLOW.DIM, cfg.MODEL.FLOW.LAYER_HIDDEN_FEATURES, cfg.MODEL.FLOW.NUM_LAYERS, cfg.MODEL.FLOW.LAYER_DEPTH, context_features=cfg.MODEL.FLOW.CO... | SMPLFlow | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SMPLFlow:
def __init__(self, cfg: CfgNode):
"""Probabilistic SMPL head using Normalizing Flows. Args: cfg (CfgNode): Model config as yacs CfgNode."""
<|body_0|>
def log_prob(self, smpl_params: Dict, feats: torch.Tensor) -> Tuple:
"""Compute the log-probability of a s... | stack_v2_sparse_classes_75kplus_train_003778 | 4,412 | permissive | [
{
"docstring": "Probabilistic SMPL head using Normalizing Flows. Args: cfg (CfgNode): Model config as yacs CfgNode.",
"name": "__init__",
"signature": "def __init__(self, cfg: CfgNode)"
},
{
"docstring": "Compute the log-probability of a set of smpl_params given a batch of images. Args: smpl_par... | 3 | stack_v2_sparse_classes_30k_train_018213 | Implement the Python class `SMPLFlow` described below.
Class description:
Implement the SMPLFlow class.
Method signatures and docstrings:
- def __init__(self, cfg: CfgNode): Probabilistic SMPL head using Normalizing Flows. Args: cfg (CfgNode): Model config as yacs CfgNode.
- def log_prob(self, smpl_params: Dict, feat... | Implement the Python class `SMPLFlow` described below.
Class description:
Implement the SMPLFlow class.
Method signatures and docstrings:
- def __init__(self, cfg: CfgNode): Probabilistic SMPL head using Normalizing Flows. Args: cfg (CfgNode): Model config as yacs CfgNode.
- def log_prob(self, smpl_params: Dict, feat... | dac2409c0b451b6dd5d91f03cbe7132aa495792f | <|skeleton|>
class SMPLFlow:
def __init__(self, cfg: CfgNode):
"""Probabilistic SMPL head using Normalizing Flows. Args: cfg (CfgNode): Model config as yacs CfgNode."""
<|body_0|>
def log_prob(self, smpl_params: Dict, feats: torch.Tensor) -> Tuple:
"""Compute the log-probability of a s... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SMPLFlow:
def __init__(self, cfg: CfgNode):
"""Probabilistic SMPL head using Normalizing Flows. Args: cfg (CfgNode): Model config as yacs CfgNode."""
super(SMPLFlow, self).__init__()
self.cfg = cfg
self.npose = 6 * (cfg.SMPL.NUM_BODY_JOINTS + 1)
self.flow = ConditionalG... | the_stack_v2_python_sparse | prohmr/models/heads/smpl_flow.py | goyallon/ProHMR | train | 0 | |
9c2645d349bde35c198a6ddce725eb846ecb36f0 | [
"self = object.__new__(cls)\nself.name = name\nself.value = value\nself.args = args\nreturn self",
"repr_parts = [self.__class__.__name__, '(', repr(self.value), ', ', repr(self.name)]\nargs = self.args\nfor arg in args:\n repr_parts.append(', ')\n repr_parts.append(repr(arg))\nrepr_parts.append(')')\nretur... | <|body_start_0|>
self = object.__new__(cls)
self.name = name
self.value = value
self.args = args
return self
<|end_body_0|>
<|body_start_1|>
repr_parts = [self.__class__.__name__, '(', repr(self.value), ', ', repr(self.name)]
args = self.args
for arg in a... | name : `str` The instance's name. value : `str`, `int` The instance's value. args : `tuple` of `Any` Additional parameters to preinstance with. | Preinstance | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Preinstance:
"""name : `str` The instance's name. value : `str`, `int` The instance's value. args : `tuple` of `Any` Additional parameters to preinstance with."""
def __new__(cls, value, name, *args):
"""Creates a new ``Preinstance`` with the given parameters. Parameters ---------- v... | stack_v2_sparse_classes_75kplus_train_003779 | 8,693 | permissive | [
{
"docstring": "Creates a new ``Preinstance`` with the given parameters. Parameters ---------- value : `str`, `int` The instance's value. name : `str` The instance's name. *args : Parameters Additional parameters to preinstance with.",
"name": "__new__",
"signature": "def __new__(cls, value, name, *args... | 2 | stack_v2_sparse_classes_30k_train_043656 | Implement the Python class `Preinstance` described below.
Class description:
name : `str` The instance's name. value : `str`, `int` The instance's value. args : `tuple` of `Any` Additional parameters to preinstance with.
Method signatures and docstrings:
- def __new__(cls, value, name, *args): Creates a new ``Preinst... | Implement the Python class `Preinstance` described below.
Class description:
name : `str` The instance's name. value : `str`, `int` The instance's value. args : `tuple` of `Any` Additional parameters to preinstance with.
Method signatures and docstrings:
- def __new__(cls, value, name, *args): Creates a new ``Preinst... | 53f24fdb38459dc5a4fd04f11bdbfee8295b76a4 | <|skeleton|>
class Preinstance:
"""name : `str` The instance's name. value : `str`, `int` The instance's value. args : `tuple` of `Any` Additional parameters to preinstance with."""
def __new__(cls, value, name, *args):
"""Creates a new ``Preinstance`` with the given parameters. Parameters ---------- v... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Preinstance:
"""name : `str` The instance's name. value : `str`, `int` The instance's value. args : `tuple` of `Any` Additional parameters to preinstance with."""
def __new__(cls, value, name, *args):
"""Creates a new ``Preinstance`` with the given parameters. Parameters ---------- value : `str`,... | the_stack_v2_python_sparse | hata/discord/bases/preinstanced.py | HuyaneMatsu/hata | train | 3 |
e77a820a86d3222217a9fbe36cc494e583f4c6c5 | [
"try:\n date = ElectionDay.objects.get(date=self.kwargs['date'])\nexcept:\n raise APIException('No elections on {}.'.format(self.kwargs['date']))\nbody_ids = []\nfor election in date.elections.all():\n body = election.race.office.body\n if body:\n body_ids.append(body.uid)\nreturn Body.objects.fi... | <|body_start_0|>
try:
date = ElectionDay.objects.get(date=self.kwargs['date'])
except:
raise APIException('No elections on {}.'.format(self.kwargs['date']))
body_ids = []
for election in date.elections.all():
body = election.race.office.body
... | BodyMixin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BodyMixin:
def get_queryset(self):
"""Returns a queryset of all bodies holding an election on a date."""
<|body_0|>
def get_serializer_context(self):
"""Adds ``election_day`` to serializer context."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try... | stack_v2_sparse_classes_75kplus_train_003780 | 5,447 | no_license | [
{
"docstring": "Returns a queryset of all bodies holding an election on a date.",
"name": "get_queryset",
"signature": "def get_queryset(self)"
},
{
"docstring": "Adds ``election_day`` to serializer context.",
"name": "get_serializer_context",
"signature": "def get_serializer_context(sel... | 2 | stack_v2_sparse_classes_30k_train_038749 | Implement the Python class `BodyMixin` described below.
Class description:
Implement the BodyMixin class.
Method signatures and docstrings:
- def get_queryset(self): Returns a queryset of all bodies holding an election on a date.
- def get_serializer_context(self): Adds ``election_day`` to serializer context. | Implement the Python class `BodyMixin` described below.
Class description:
Implement the BodyMixin class.
Method signatures and docstrings:
- def get_queryset(self): Returns a queryset of all bodies holding an election on a date.
- def get_serializer_context(self): Adds ``election_day`` to serializer context.
<|skel... | 9137a0c59e044d081d6c34f0e9e97b789e69bdbf | <|skeleton|>
class BodyMixin:
def get_queryset(self):
"""Returns a queryset of all bodies holding an election on a date."""
<|body_0|>
def get_serializer_context(self):
"""Adds ``election_day`` to serializer context."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BodyMixin:
def get_queryset(self):
"""Returns a queryset of all bodies holding an election on a date."""
try:
date = ElectionDay.objects.get(date=self.kwargs['date'])
except:
raise APIException('No elections on {}.'.format(self.kwargs['date']))
body_ids ... | the_stack_v2_python_sparse | theshow/viewsets.py | The-Politico/politico-elections | train | 0 | |
7f84373b522c4f315b7cafc9536a6a957bf152d2 | [
"if data:\n useragent = data['useragent']\n print(useragent)\n if 'mobile' in useragent:\n return packinfo(infostatus=2, infomsg='此系统不支持移动端浏览器！请切换至计算机上使用。')\n elif 'firefox' in useragent:\n return packinfo(infostatus=1, infomsg='支持的浏览器')\n elif 'edge' in useragent:\n return packi... | <|body_start_0|>
if data:
useragent = data['useragent']
print(useragent)
if 'mobile' in useragent:
return packinfo(infostatus=2, infomsg='此系统不支持移动端浏览器！请切换至计算机上使用。')
elif 'firefox' in useragent:
return packinfo(infostatus=1, infomsg=... | LoginDAO | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoginDAO:
def checkuseragent(data):
"""检测浏览器"""
<|body_0|>
def checktoken(username, token):
"""检测admin的token"""
<|body_1|>
def logout(token, username, req):
"""用户退出"""
<|body_2|>
def login(username, password, req):
"""用户登录"""... | stack_v2_sparse_classes_75kplus_train_003781 | 3,343 | no_license | [
{
"docstring": "检测浏览器",
"name": "checkuseragent",
"signature": "def checkuseragent(data)"
},
{
"docstring": "检测admin的token",
"name": "checktoken",
"signature": "def checktoken(username, token)"
},
{
"docstring": "用户退出",
"name": "logout",
"signature": "def logout(token, us... | 4 | stack_v2_sparse_classes_30k_train_007320 | Implement the Python class `LoginDAO` described below.
Class description:
Implement the LoginDAO class.
Method signatures and docstrings:
- def checkuseragent(data): 检测浏览器
- def checktoken(username, token): 检测admin的token
- def logout(token, username, req): 用户退出
- def login(username, password, req): 用户登录 | Implement the Python class `LoginDAO` described below.
Class description:
Implement the LoginDAO class.
Method signatures and docstrings:
- def checkuseragent(data): 检测浏览器
- def checktoken(username, token): 检测admin的token
- def logout(token, username, req): 用户退出
- def login(username, password, req): 用户登录
<|skeleton|>... | 473d330fab9ee6b42af446d68b03668c286021d6 | <|skeleton|>
class LoginDAO:
def checkuseragent(data):
"""检测浏览器"""
<|body_0|>
def checktoken(username, token):
"""检测admin的token"""
<|body_1|>
def logout(token, username, req):
"""用户退出"""
<|body_2|>
def login(username, password, req):
"""用户登录"""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LoginDAO:
def checkuseragent(data):
"""检测浏览器"""
if data:
useragent = data['useragent']
print(useragent)
if 'mobile' in useragent:
return packinfo(infostatus=2, infomsg='此系统不支持移动端浏览器！请切换至计算机上使用。')
elif 'firefox' in useragent:
... | the_stack_v2_python_sparse | services/daos/loginDAO.py | tanoshiisekai/examsystem | train | 0 | |
aee94e2b32578a600c058fd946f736913c19698a | [
"Process.__init__(self)\nself.v = v\nself.event = event",
"self.event.wait()\nsumme = 0\nfor i in range(self.v.value + 1):\n summe += i\nself.v.value = summe"
] | <|body_start_0|>
Process.__init__(self)
self.v = v
self.event = event
<|end_body_0|>
<|body_start_1|>
self.event.wait()
summe = 0
for i in range(self.v.value + 1):
summe += i
self.v.value = summe
<|end_body_1|>
| Stellt einen simplen Worker-Prozess dar, welcher auf ein Event wartet und dann die Summe von 1 bis n berechnet. Das Ergebnis wird in einen geteilten Speicher gelegt. | CalculatorProcess | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CalculatorProcess:
"""Stellt einen simplen Worker-Prozess dar, welcher auf ein Event wartet und dann die Summe von 1 bis n berechnet. Das Ergebnis wird in einen geteilten Speicher gelegt."""
def __init__(self, v, event):
"""Initialisiert die Basisklasse Process :param v: ein geteilte... | stack_v2_sparse_classes_75kplus_train_003782 | 1,243 | no_license | [
{
"docstring": "Initialisiert die Basisklasse Process :param v: ein geteilter Wert :param event: das Event, auf welches gewartet wird",
"name": "__init__",
"signature": "def __init__(self, v, event)"
},
{
"docstring": "Wartet auf das Event und legt das Ergebnis in den geteilten Speicher :return:... | 2 | stack_v2_sparse_classes_30k_train_023608 | Implement the Python class `CalculatorProcess` described below.
Class description:
Stellt einen simplen Worker-Prozess dar, welcher auf ein Event wartet und dann die Summe von 1 bis n berechnet. Das Ergebnis wird in einen geteilten Speicher gelegt.
Method signatures and docstrings:
- def __init__(self, v, event): Ini... | Implement the Python class `CalculatorProcess` described below.
Class description:
Stellt einen simplen Worker-Prozess dar, welcher auf ein Event wartet und dann die Summe von 1 bis n berechnet. Das Ergebnis wird in einen geteilten Speicher gelegt.
Method signatures and docstrings:
- def __init__(self, v, event): Ini... | 262499bbbc5ed6a53280dc2d596592c48155dcd7 | <|skeleton|>
class CalculatorProcess:
"""Stellt einen simplen Worker-Prozess dar, welcher auf ein Event wartet und dann die Summe von 1 bis n berechnet. Das Ergebnis wird in einen geteilten Speicher gelegt."""
def __init__(self, v, event):
"""Initialisiert die Basisklasse Process :param v: ein geteilte... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CalculatorProcess:
"""Stellt einen simplen Worker-Prozess dar, welcher auf ein Event wartet und dann die Summe von 1 bis n berechnet. Das Ergebnis wird in einen geteilten Speicher gelegt."""
def __init__(self, v, event):
"""Initialisiert die Basisklasse Process :param v: ein geteilter Wert :param... | the_stack_v2_python_sparse | Interprozesskommunikation/multiprocessing/multiprocess_event.py | mborko/sew4_foerderkurs | train | 0 |
d37c5a53aa46a706f3d0e7d54fde0c7ed069cf97 | [
"if root is None:\n return None\nif root.val == val:\n return root\nelif val < root.val:\n return self.searchBST(root.left, val)\nelse:\n return self.searchBST(root.right, val)",
"if not root:\n return None\nif root.val == val:\n return root\nelif val < root.val:\n return self.searchBST2(root... | <|body_start_0|>
if root is None:
return None
if root.val == val:
return root
elif val < root.val:
return self.searchBST(root.left, val)
else:
return self.searchBST(root.right, val)
<|end_body_0|>
<|body_start_1|>
if not root:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def searchBST(self, root, val):
""":type root: TreeNode :type val: int :rtype: TreeNode"""
<|body_0|>
def searchBST2(self, root, val):
""":param root: :param val: :return: Recursion Space: O(logn) Time: O(logn)"""
<|body_1|>
<|end_skeleton|>
<|bod... | stack_v2_sparse_classes_75kplus_train_003783 | 2,333 | no_license | [
{
"docstring": ":type root: TreeNode :type val: int :rtype: TreeNode",
"name": "searchBST",
"signature": "def searchBST(self, root, val)"
},
{
"docstring": ":param root: :param val: :return: Recursion Space: O(logn) Time: O(logn)",
"name": "searchBST2",
"signature": "def searchBST2(self,... | 2 | stack_v2_sparse_classes_30k_train_053440 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchBST(self, root, val): :type root: TreeNode :type val: int :rtype: TreeNode
- def searchBST2(self, root, val): :param root: :param val: :return: Recursion Space: O(logn)... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchBST(self, root, val): :type root: TreeNode :type val: int :rtype: TreeNode
- def searchBST2(self, root, val): :param root: :param val: :return: Recursion Space: O(logn)... | a5b02044ef39154b6a8d32eb57682f447e1632ba | <|skeleton|>
class Solution:
def searchBST(self, root, val):
""":type root: TreeNode :type val: int :rtype: TreeNode"""
<|body_0|>
def searchBST2(self, root, val):
""":param root: :param val: :return: Recursion Space: O(logn) Time: O(logn)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def searchBST(self, root, val):
""":type root: TreeNode :type val: int :rtype: TreeNode"""
if root is None:
return None
if root.val == val:
return root
elif val < root.val:
return self.searchBST(root.left, val)
else:
... | the_stack_v2_python_sparse | algo/tree/search_in_binary_search_tree.py | xys234/coding-problems | train | 0 | |
5ab1ef018811ab2e46fbd5412ac2ca820e9a5588 | [
"try:\n setattr(type(self), '__optimize_not_implemented__', True)\n out = self.self_optimize_with_info(dataset, **kwargs)[0]\n delattr(type(self), '__optimize_not_implemented__')\nexcept NotImplementedError as e:\n raise NotImplementedError() from e\nreturn out",
"try:\n if getattr(type(self), '__o... | <|body_start_0|>
try:
setattr(type(self), '__optimize_not_implemented__', True)
out = self.self_optimize_with_info(dataset, **kwargs)[0]
delattr(type(self), '__optimize_not_implemented__')
except NotImplementedError as e:
raise NotImplementedError() from e... | Pipeline with custom ways to optimize and/or train input parameters. OptimizablePipelines are expected to implement a concrete way to train internal models or optimize parameters. This should not be a reimplementation of GridSearch or similar methods. For this :class:`tpcp.pipelines.GridSearch` should be used directly.... | OptimizablePipeline | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OptimizablePipeline:
"""Pipeline with custom ways to optimize and/or train input parameters. OptimizablePipelines are expected to implement a concrete way to train internal models or optimize parameters. This should not be a reimplementation of GridSearch or similar methods. For this :class:`tpcp... | stack_v2_sparse_classes_75kplus_train_003784 | 7,840 | permissive | [
{
"docstring": "Optimize the input parameters of the pipeline or algorithm using any logic. This method can be used to adapt the input parameters (values provided in the init) based on any data driven heuristic. .. note:: The optimizations must only modify the input parameters (aka `self.clone` should retain th... | 2 | stack_v2_sparse_classes_30k_train_009190 | Implement the Python class `OptimizablePipeline` described below.
Class description:
Pipeline with custom ways to optimize and/or train input parameters. OptimizablePipelines are expected to implement a concrete way to train internal models or optimize parameters. This should not be a reimplementation of GridSearch or... | Implement the Python class `OptimizablePipeline` described below.
Class description:
Pipeline with custom ways to optimize and/or train input parameters. OptimizablePipelines are expected to implement a concrete way to train internal models or optimize parameters. This should not be a reimplementation of GridSearch or... | 75b958ee691d6d5b0eee070c1eb20d1017ec619b | <|skeleton|>
class OptimizablePipeline:
"""Pipeline with custom ways to optimize and/or train input parameters. OptimizablePipelines are expected to implement a concrete way to train internal models or optimize parameters. This should not be a reimplementation of GridSearch or similar methods. For this :class:`tpcp... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OptimizablePipeline:
"""Pipeline with custom ways to optimize and/or train input parameters. OptimizablePipelines are expected to implement a concrete way to train internal models or optimize parameters. This should not be a reimplementation of GridSearch or similar methods. For this :class:`tpcp.pipelines.Gr... | the_stack_v2_python_sparse | tpcp/_pipeline.py | mad-lab-fau/tpcp | train | 11 |
2ec247a99e66f79f4dc75cc0817e473c113075c6 | [
"form = super(AjaxCreateView, self).get_form()\nif form.initial.get('part', None):\n form.fields['part'].widget = HiddenInput()\nreturn form",
"initials = super(SupplierPartCreate, self).get_initial().copy()\nmanufacturer_id = self.get_param('manufacturer')\nsupplier_id = self.get_param('supplier')\npart_id = ... | <|body_start_0|>
form = super(AjaxCreateView, self).get_form()
if form.initial.get('part', None):
form.fields['part'].widget = HiddenInput()
return form
<|end_body_0|>
<|body_start_1|>
initials = super(SupplierPartCreate, self).get_initial().copy()
manufacturer_id = ... | Create view for making new SupplierPart | SupplierPartCreate | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SupplierPartCreate:
"""Create view for making new SupplierPart"""
def get_form(self):
"""Create Form instance to create a new SupplierPart object. Hide some fields if they are not appropriate in context"""
<|body_0|>
def get_initial(self):
"""Provide initial data... | stack_v2_sparse_classes_75kplus_train_003785 | 12,536 | permissive | [
{
"docstring": "Create Form instance to create a new SupplierPart object. Hide some fields if they are not appropriate in context",
"name": "get_form",
"signature": "def get_form(self)"
},
{
"docstring": "Provide initial data for new SupplierPart: - If 'supplier_id' provided, pre-fill supplier f... | 2 | stack_v2_sparse_classes_30k_train_010861 | Implement the Python class `SupplierPartCreate` described below.
Class description:
Create view for making new SupplierPart
Method signatures and docstrings:
- def get_form(self): Create Form instance to create a new SupplierPart object. Hide some fields if they are not appropriate in context
- def get_initial(self):... | Implement the Python class `SupplierPartCreate` described below.
Class description:
Create view for making new SupplierPart
Method signatures and docstrings:
- def get_form(self): Create Form instance to create a new SupplierPart object. Hide some fields if they are not appropriate in context
- def get_initial(self):... | daab81fa2cf6f3ce1760e31d8cd94951c6dffdd2 | <|skeleton|>
class SupplierPartCreate:
"""Create view for making new SupplierPart"""
def get_form(self):
"""Create Form instance to create a new SupplierPart object. Hide some fields if they are not appropriate in context"""
<|body_0|>
def get_initial(self):
"""Provide initial data... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SupplierPartCreate:
"""Create view for making new SupplierPart"""
def get_form(self):
"""Create Form instance to create a new SupplierPart object. Hide some fields if they are not appropriate in context"""
form = super(AjaxCreateView, self).get_form()
if form.initial.get('part', N... | the_stack_v2_python_sparse | InvenTree/company/views.py | fritzlim/InvenTree | train | 1 |
97938a132a550eadcd181989f6c163445c517cbd | [
"super(_ExprInMatch, self).__init__(backend, key, operand, transform, args)\nself._prefix = prefix\nself._suffix = suffix",
"def _InMatch(value):\n \"\"\"Applies case insensitive string prefix/suffix match to value.\"\"\"\n if value is None:\n return False\n v = str(value).lower()\n return (not... | <|body_start_0|>
super(_ExprInMatch, self).__init__(backend, key, operand, transform, args)
self._prefix = prefix
self._suffix = suffix
<|end_body_0|>
<|body_start_1|>
def _InMatch(value):
"""Applies case insensitive string prefix/suffix match to value."""
if val... | Membership and anchored prefix*suffix match node. | _ExprInMatch | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _ExprInMatch:
"""Membership and anchored prefix*suffix match node."""
def __init__(self, backend, key, operand, transform, args, prefix, suffix):
"""Initializes the anchored prefix and suffix patterns. Args: backend: The parser backend object. key: Resource object key (list of str, i... | stack_v2_sparse_classes_75kplus_train_003786 | 15,555 | permissive | [
{
"docstring": "Initializes the anchored prefix and suffix patterns. Args: backend: The parser backend object. key: Resource object key (list of str, int and/or None values). operand: The term ExprOperand operand. transform: Optional key value transform function. args: Optional key value transform function actu... | 2 | stack_v2_sparse_classes_30k_train_024090 | Implement the Python class `_ExprInMatch` described below.
Class description:
Membership and anchored prefix*suffix match node.
Method signatures and docstrings:
- def __init__(self, backend, key, operand, transform, args, prefix, suffix): Initializes the anchored prefix and suffix patterns. Args: backend: The parser... | Implement the Python class `_ExprInMatch` described below.
Class description:
Membership and anchored prefix*suffix match node.
Method signatures and docstrings:
- def __init__(self, backend, key, operand, transform, args, prefix, suffix): Initializes the anchored prefix and suffix patterns. Args: backend: The parser... | dcf4886d4ec06b13282143ef795c5f0ff20ffee3 | <|skeleton|>
class _ExprInMatch:
"""Membership and anchored prefix*suffix match node."""
def __init__(self, backend, key, operand, transform, args, prefix, suffix):
"""Initializes the anchored prefix and suffix patterns. Args: backend: The parser backend object. key: Resource object key (list of str, i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class _ExprInMatch:
"""Membership and anchored prefix*suffix match node."""
def __init__(self, backend, key, operand, transform, args, prefix, suffix):
"""Initializes the anchored prefix and suffix patterns. Args: backend: The parser backend object. key: Resource object key (list of str, int and/or Non... | the_stack_v2_python_sparse | google-cloud-sdk/.install/.backup/lib/googlecloudsdk/core/resource/resource_expr.py | MD-Anderson-Bioinformatics/NG-CHM_Galaxy | train | 0 |
de3197270ef377218c6fe275535386ba842e3898 | [
"self.rgb = rgb\nself.lwir = lwir\nself.bsize = args.batch_size\nself.psize = args.patch_size\nself.hdisp = int(float(args.max_disparity) / 2.0)\nself.channels = 3\nself.ptr = 0\nself.disparity = io.read_disparity_gt(disparity)\nprint(f'total testing locations: {self.disparity.shape[0]}')\npatch_size = 2 * self.psi... | <|body_start_0|>
self.rgb = rgb
self.lwir = lwir
self.bsize = args.batch_size
self.psize = args.patch_size
self.hdisp = int(float(args.max_disparity) / 2.0)
self.channels = 3
self.ptr = 0
self.disparity = io.read_disparity_gt(disparity)
print(f'tot... | TestLITIVDataset | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestLITIVDataset:
def __init__(self, rgb: List[str], lwir: List[str], disparity: str, args: Namespace):
"""represents the LITIV dataset used for testing. :param rgb: list of paths to rgb images. :param lwir: list of paths to lwir images. :param disparity: file contraining all data points... | stack_v2_sparse_classes_75kplus_train_003787 | 6,156 | permissive | [
{
"docstring": "represents the LITIV dataset used for testing. :param rgb: list of paths to rgb images. :param lwir: list of paths to lwir images. :param disparity: file contraining all data points. :param args: structure containing all user arguments.",
"name": "__init__",
"signature": "def __init__(se... | 2 | stack_v2_sparse_classes_30k_val_000685 | Implement the Python class `TestLITIVDataset` described below.
Class description:
Implement the TestLITIVDataset class.
Method signatures and docstrings:
- def __init__(self, rgb: List[str], lwir: List[str], disparity: str, args: Namespace): represents the LITIV dataset used for testing. :param rgb: list of paths to ... | Implement the Python class `TestLITIVDataset` described below.
Class description:
Implement the TestLITIVDataset class.
Method signatures and docstrings:
- def __init__(self, rgb: List[str], lwir: List[str], disparity: str, args: Namespace): represents the LITIV dataset used for testing. :param rgb: list of paths to ... | 583e6868864582f081f18689124e74e9ca169f28 | <|skeleton|>
class TestLITIVDataset:
def __init__(self, rgb: List[str], lwir: List[str], disparity: str, args: Namespace):
"""represents the LITIV dataset used for testing. :param rgb: list of paths to rgb images. :param lwir: list of paths to lwir images. :param disparity: file contraining all data points... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestLITIVDataset:
def __init__(self, rgb: List[str], lwir: List[str], disparity: str, args: Namespace):
"""represents the LITIV dataset used for testing. :param rgb: list of paths to rgb images. :param lwir: list of paths to lwir images. :param disparity: file contraining all data points. :param args:... | the_stack_v2_python_sparse | datahandler/LITIVDataset.py | beaupreda/domain-networks | train | 1 | |
60eecbc9886dc6e7e022d5c87830e49e1975c31f | [
"self.quark = quark\nself.nucleon = nucleon\nself.ip = input_dict",
"self.mN = (self.ip['mproton'] + self.ip['mneutron']) / 2\nif self.nucleon == 'p':\n if self.quark == 'u':\n return self.mN ** 2 * 2 * self.ip['gA']\n if self.quark == 'd':\n return -self.mN ** 2 * 2 * self.ip['gA']\n if se... | <|body_start_0|>
self.quark = quark
self.nucleon = nucleon
self.ip = input_dict
<|end_body_0|>
<|body_start_1|>
self.mN = (self.ip['mproton'] + self.ip['mneutron']) / 2
if self.nucleon == 'p':
if self.quark == 'u':
return self.mN ** 2 * 2 * self.ip['g... | FPprimed | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FPprimed:
def __init__(self, quark, nucleon, input_dict):
"""The nuclear form factor FPprimed Return the nuclear form factor FPprimed Arguments --------- quark = 'u', 'd', 's' -- the quark flavor (up, down, strange) nucleon = 'p', 'n' -- the nucleon (proton or neutron) input_dict (option... | stack_v2_sparse_classes_75kplus_train_003788 | 18,337 | permissive | [
{
"docstring": "The nuclear form factor FPprimed Return the nuclear form factor FPprimed Arguments --------- quark = 'u', 'd', 's' -- the quark flavor (up, down, strange) nucleon = 'p', 'n' -- the nucleon (proton or neutron) input_dict (optional) -- a dictionary of hadronic input parameters (default is Num_inpu... | 3 | stack_v2_sparse_classes_30k_train_041057 | Implement the Python class `FPprimed` described below.
Class description:
Implement the FPprimed class.
Method signatures and docstrings:
- def __init__(self, quark, nucleon, input_dict): The nuclear form factor FPprimed Return the nuclear form factor FPprimed Arguments --------- quark = 'u', 'd', 's' -- the quark fl... | Implement the Python class `FPprimed` described below.
Class description:
Implement the FPprimed class.
Method signatures and docstrings:
- def __init__(self, quark, nucleon, input_dict): The nuclear form factor FPprimed Return the nuclear form factor FPprimed Arguments --------- quark = 'u', 'd', 's' -- the quark fl... | 4a714e4701f817fdc96e10e461eef7c4756ef71d | <|skeleton|>
class FPprimed:
def __init__(self, quark, nucleon, input_dict):
"""The nuclear form factor FPprimed Return the nuclear form factor FPprimed Arguments --------- quark = 'u', 'd', 's' -- the quark flavor (up, down, strange) nucleon = 'p', 'n' -- the nucleon (proton or neutron) input_dict (option... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class FPprimed:
def __init__(self, quark, nucleon, input_dict):
"""The nuclear form factor FPprimed Return the nuclear form factor FPprimed Arguments --------- quark = 'u', 'd', 's' -- the quark flavor (up, down, strange) nucleon = 'p', 'n' -- the nucleon (proton or neutron) input_dict (optional) -- a dicti... | the_stack_v2_python_sparse | directdm/num/single_nucleon_form_factors.py | DirectDM/directdm-py | train | 6 | |
aad0bf99b79d76a1c8563c40a4dd035058c8ae4f | [
"add_failed = kwargs.get('add_failed', False)\nadd_succeeded = kwargs.get('add_succeeded', False)\nbook_list = get_object_or_404(models.List, id=list_id)\nbook_list.raise_visible_to_user(request.user)\nif is_api_request(request):\n return ActivitypubResponse(book_list.to_activity(**request.GET))\nif (redirect_op... | <|body_start_0|>
add_failed = kwargs.get('add_failed', False)
add_succeeded = kwargs.get('add_succeeded', False)
book_list = get_object_or_404(models.List, id=list_id)
book_list.raise_visible_to_user(request.user)
if is_api_request(request):
return ActivitypubResponse... | book list page | List | [
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class List:
"""book list page"""
def get(self, request, list_id, **kwargs):
"""display a book list"""
<|body_0|>
def post(self, request, list_id):
"""edit a list"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
add_failed = kwargs.get('add_failed', Fal... | stack_v2_sparse_classes_75kplus_train_003789 | 11,267 | no_license | [
{
"docstring": "display a book list",
"name": "get",
"signature": "def get(self, request, list_id, **kwargs)"
},
{
"docstring": "edit a list",
"name": "post",
"signature": "def post(self, request, list_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_008900 | Implement the Python class `List` described below.
Class description:
book list page
Method signatures and docstrings:
- def get(self, request, list_id, **kwargs): display a book list
- def post(self, request, list_id): edit a list | Implement the Python class `List` described below.
Class description:
book list page
Method signatures and docstrings:
- def get(self, request, list_id, **kwargs): display a book list
- def post(self, request, list_id): edit a list
<|skeleton|>
class List:
"""book list page"""
def get(self, request, list_id... | 0f8da5b738047f3c34d60d93f59bdedd8f797224 | <|skeleton|>
class List:
"""book list page"""
def get(self, request, list_id, **kwargs):
"""display a book list"""
<|body_0|>
def post(self, request, list_id):
"""edit a list"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class List:
"""book list page"""
def get(self, request, list_id, **kwargs):
"""display a book list"""
add_failed = kwargs.get('add_failed', False)
add_succeeded = kwargs.get('add_succeeded', False)
book_list = get_object_or_404(models.List, id=list_id)
book_list.raise_vi... | the_stack_v2_python_sparse | bookwyrm/views/list/list.py | bookwyrm-social/bookwyrm | train | 1,398 |
136179789a29ac14403dc31ad56dfe9f1db9e318 | [
"try:\n from avx_commons import get_db_credentials\n self.hostname = socket.gethostbyname(socket.gethostname())\n self.db_username, self.db_password, self.db_name = get_db_credentials()\n self.db_ip = db_ip\n self.db_port = db_port\n self.path = path\nexcept Exception as e:\n print(colored(e, '... | <|body_start_0|>
try:
from avx_commons import get_db_credentials
self.hostname = socket.gethostbyname(socket.gethostname())
self.db_username, self.db_password, self.db_name = get_db_credentials()
self.db_ip = db_ip
self.db_port = db_port
se... | . | PushLB | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PushLB:
"""."""
def __init__(self, path, db_ip, db_port):
"""."""
<|body_0|>
def generate_load_balancer():
"""."""
<|body_1|>
def push_load_balancer(self):
"""."""
<|body_2|>
def initialize(self):
"""."""
<|body_3... | stack_v2_sparse_classes_75kplus_train_003790 | 4,027 | no_license | [
{
"docstring": ".",
"name": "__init__",
"signature": "def __init__(self, path, db_ip, db_port)"
},
{
"docstring": ".",
"name": "generate_load_balancer",
"signature": "def generate_load_balancer()"
},
{
"docstring": ".",
"name": "push_load_balancer",
"signature": "def push... | 4 | stack_v2_sparse_classes_30k_train_001430 | Implement the Python class `PushLB` described below.
Class description:
.
Method signatures and docstrings:
- def __init__(self, path, db_ip, db_port): .
- def generate_load_balancer(): .
- def push_load_balancer(self): .
- def initialize(self): . | Implement the Python class `PushLB` described below.
Class description:
.
Method signatures and docstrings:
- def __init__(self, path, db_ip, db_port): .
- def generate_load_balancer(): .
- def push_load_balancer(self): .
- def initialize(self): .
<|skeleton|>
class PushLB:
"""."""
def __init__(self, path, ... | e513224364dce05ea4d17ac25ecfa981238b1311 | <|skeleton|>
class PushLB:
"""."""
def __init__(self, path, db_ip, db_port):
"""."""
<|body_0|>
def generate_load_balancer():
"""."""
<|body_1|>
def push_load_balancer(self):
"""."""
<|body_2|>
def initialize(self):
"""."""
<|body_3... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PushLB:
"""."""
def __init__(self, path, db_ip, db_port):
"""."""
try:
from avx_commons import get_db_credentials
self.hostname = socket.gethostbyname(socket.gethostname())
self.db_username, self.db_password, self.db_name = get_db_credentials()
... | the_stack_v2_python_sparse | scripts_avx/scripts/scripts/Commons/push_lb.py | Poonammahunta/Integration | train | 0 |
8ff9cd90e7067709f148f66e5048cd5825d7dd22 | [
"if masksModel == 'deeplab_resnet':\n print('Creating Deeplabv3-Resnet model for masks and loading checkpoint')\n self.model = deeplab_masks.DeepLab(num_classes=2, backbone='resnet', sync_bn=True, freeze_bn=False)\nelif masksModel == 'deeplab_xception':\n self.model = deeplab_masks.DeepLab(num_classes=2, b... | <|body_start_0|>
if masksModel == 'deeplab_resnet':
print('Creating Deeplabv3-Resnet model for masks and loading checkpoint')
self.model = deeplab_masks.DeepLab(num_classes=2, backbone='resnet', sync_bn=True, freeze_bn=False)
elif masksModel == 'deeplab_xception':
sel... | InferenceMasks | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class InferenceMasks:
def __init__(self, masksWeightsFile, masksModel='drn', imgHeight=288, imgWidth=512):
"""Class to run Inference of the Outlines Prediction Model Args: masksWeightsFile (str): Path to the weights file for the model masksModel (str): Which model to use. Can be one of ["deepl... | stack_v2_sparse_classes_75kplus_train_003791 | 17,088 | permissive | [
{
"docstring": "Class to run Inference of the Outlines Prediction Model Args: masksWeightsFile (str): Path to the weights file for the model masksModel (str): Which model to use. Can be one of [\"deeplab_xception\", \"deeplab_resnet\", \"drn\"] imgHeight (int): The height to which images should be resized to be... | 2 | null | Implement the Python class `InferenceMasks` described below.
Class description:
Implement the InferenceMasks class.
Method signatures and docstrings:
- def __init__(self, masksWeightsFile, masksModel='drn', imgHeight=288, imgWidth=512): Class to run Inference of the Outlines Prediction Model Args: masksWeightsFile (s... | Implement the Python class `InferenceMasks` described below.
Class description:
Implement the InferenceMasks class.
Method signatures and docstrings:
- def __init__(self, masksWeightsFile, masksModel='drn', imgHeight=288, imgWidth=512): Class to run Inference of the Outlines Prediction Model Args: masksWeightsFile (s... | 0688647e49380139e440bacbe8562132bb2afbd7 | <|skeleton|>
class InferenceMasks:
def __init__(self, masksWeightsFile, masksModel='drn', imgHeight=288, imgWidth=512):
"""Class to run Inference of the Outlines Prediction Model Args: masksWeightsFile (str): Path to the weights file for the model masksModel (str): Which model to use. Can be one of ["deepl... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class InferenceMasks:
def __init__(self, masksWeightsFile, masksModel='drn', imgHeight=288, imgWidth=512):
"""Class to run Inference of the Outlines Prediction Model Args: masksWeightsFile (str): Path to the weights file for the model masksModel (str): Which model to use. Can be one of ["deeplab_xception", ... | the_stack_v2_python_sparse | api/inference_models.py | Shreeyak/cleargrasp | train | 253 | |
61fb61379af3f23f6e053eaf8d7c1e5904a72afa | [
"if qca_passwd is None:\n qca_passwd = os.environ.get('QCAUSR', None)\nself.qc_spec = qc_spec\nself.client = FractalClient(address, username='user', password=qca_passwd, verify=False)\ntry:\n self.coll = base_class.from_server(name=coll_name, client=self.client)\nexcept KeyError as ex:\n if create:\n ... | <|body_start_0|>
if qca_passwd is None:
qca_passwd = os.environ.get('QCAUSR', None)
self.qc_spec = qc_spec
self.client = FractalClient(address, username='user', password=qca_passwd, verify=False)
try:
self.coll = base_class.from_server(name=coll_name, client=self.... | Wrapper over a QFractal Dataset class Handles creating and authenticating with the underlying class method. It is a base class for building superclasses that create utility operations for adding molecules to the database (e.g., generate XYZ coordinates to allow for a 'just add this SMILES'), using a consistent identifi... | QCFractalWrapper | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QCFractalWrapper:
"""Wrapper over a QFractal Dataset class Handles creating and authenticating with the underlying class method. It is a base class for building superclasses that create utility operations for adding molecules to the database (e.g., generate XYZ coordinates to allow for a 'just ad... | stack_v2_sparse_classes_75kplus_train_003792 | 29,582 | no_license | [
{
"docstring": "Open the geometry computation dataset Args: address: Address for the QCFractal server base_class: Type of the collection qc_spec: Name of the QC specification coll_name: Name of the collection holding the data qca_passwd: Password for the QCFractal server create: Whether creating a new collectio... | 2 | stack_v2_sparse_classes_30k_train_002360 | Implement the Python class `QCFractalWrapper` described below.
Class description:
Wrapper over a QFractal Dataset class Handles creating and authenticating with the underlying class method. It is a base class for building superclasses that create utility operations for adding molecules to the database (e.g., generate ... | Implement the Python class `QCFractalWrapper` described below.
Class description:
Wrapper over a QFractal Dataset class Handles creating and authenticating with the underlying class method. It is a base class for building superclasses that create utility operations for adding molecules to the database (e.g., generate ... | ef9e586e89053d1f6bea541717db8be43dbce0a4 | <|skeleton|>
class QCFractalWrapper:
"""Wrapper over a QFractal Dataset class Handles creating and authenticating with the underlying class method. It is a base class for building superclasses that create utility operations for adding molecules to the database (e.g., generate XYZ coordinates to allow for a 'just ad... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class QCFractalWrapper:
"""Wrapper over a QFractal Dataset class Handles creating and authenticating with the underlying class method. It is a base class for building superclasses that create utility operations for adding molecules to the database (e.g., generate XYZ coordinates to allow for a 'just add this SMILES... | the_stack_v2_python_sparse | moldesign/simulate/qcfractal.py | exalearn/electrolyte-design | train | 4 |
9e66e39888d060d7556ebc9be2c468239e5e95c4 | [
"try:\n return os.environ[key]\nexcept KeyError:\n return ''",
"env = []\nfor ek in os.environ.keys():\n env.append((ek, os.environ[ek]))\nreturn env"
] | <|body_start_0|>
try:
return os.environ[key]
except KeyError:
return ''
<|end_body_0|>
<|body_start_1|>
env = []
for ek in os.environ.keys():
env.append((ek, os.environ[ek]))
return env
<|end_body_1|>
| basic miscellanous functions | Base | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Base:
"""basic miscellanous functions"""
def Env(self, key):
"""return operating system enviroment variables"""
<|body_0|>
def EnvAll(self):
"""return all environment variables as a list with containing tuples (key, value)"""
<|body_1|>
<|end_skeleton|>
... | stack_v2_sparse_classes_75kplus_train_003793 | 585 | no_license | [
{
"docstring": "return operating system enviroment variables",
"name": "Env",
"signature": "def Env(self, key)"
},
{
"docstring": "return all environment variables as a list with containing tuples (key, value)",
"name": "EnvAll",
"signature": "def EnvAll(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_048105 | Implement the Python class `Base` described below.
Class description:
basic miscellanous functions
Method signatures and docstrings:
- def Env(self, key): return operating system enviroment variables
- def EnvAll(self): return all environment variables as a list with containing tuples (key, value) | Implement the Python class `Base` described below.
Class description:
basic miscellanous functions
Method signatures and docstrings:
- def Env(self, key): return operating system enviroment variables
- def EnvAll(self): return all environment variables as a list with containing tuples (key, value)
<|skeleton|>
class... | 3cfcae894c165189cc3ff61e27ca284f09e87871 | <|skeleton|>
class Base:
"""basic miscellanous functions"""
def Env(self, key):
"""return operating system enviroment variables"""
<|body_0|>
def EnvAll(self):
"""return all environment variables as a list with containing tuples (key, value)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Base:
"""basic miscellanous functions"""
def Env(self, key):
"""return operating system enviroment variables"""
try:
return os.environ[key]
except KeyError:
return ''
def EnvAll(self):
"""return all environment variables as a list with containi... | the_stack_v2_python_sparse | dmerce2/Core/OS.py | rbe/dmerce | train | 0 |
65e5d45f9cdc0835a3f8d7a3229b49b7d68a21a0 | [
"self.K = K\nfile = open(file, 'r')\nself.file_data = file.readlines()\nfile.close()",
"vertices_and_edges = self.file_data[0].replace('\\n', '').split(' ')\nself.number_of_vertices = int(vertices_and_edges[0])\nself.number_of_edges = int(vertices_and_edges[1])\nself.vertexes = list()\nself.edges = list()\nfile_i... | <|body_start_0|>
self.K = K
file = open(file, 'r')
self.file_data = file.readlines()
file.close()
<|end_body_0|>
<|body_start_1|>
vertices_and_edges = self.file_data[0].replace('\n', '').split(' ')
self.number_of_vertices = int(vertices_and_edges[0])
self.number_... | self.numberOfVertices = the number of vertices in the graph self.numberOfEdges = the number of edges in the graph self.vertexes = 2-dimensional list. For each vertex, [0] denotes the index, [1] the x coord and [2] the y coord. Values are all type float self. self.edges = 2-dimensional list. For each edge, [0] denotes t... | Board | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Board:
"""self.numberOfVertices = the number of vertices in the graph self.numberOfEdges = the number of edges in the graph self.vertexes = 2-dimensional list. For each vertex, [0] denotes the index, [1] the x coord and [2] the y coord. Values are all type float self. self.edges = 2-dimensional l... | stack_v2_sparse_classes_75kplus_train_003794 | 2,456 | no_license | [
{
"docstring": "Initializes by reading a file, and setting the K value.",
"name": "__init__",
"signature": "def __init__(self, file, K)"
},
{
"docstring": "Parses the text file, and placing values in data structures.",
"name": "parse_text_file",
"signature": "def parse_text_file(self)"
... | 4 | null | Implement the Python class `Board` described below.
Class description:
self.numberOfVertices = the number of vertices in the graph self.numberOfEdges = the number of edges in the graph self.vertexes = 2-dimensional list. For each vertex, [0] denotes the index, [1] the x coord and [2] the y coord. Values are all type f... | Implement the Python class `Board` described below.
Class description:
self.numberOfVertices = the number of vertices in the graph self.numberOfEdges = the number of edges in the graph self.vertexes = 2-dimensional list. For each vertex, [0] denotes the index, [1] the x coord and [2] the y coord. Values are all type f... | 9f3d6d040406a183d25fca8801af48fcb8b6d875 | <|skeleton|>
class Board:
"""self.numberOfVertices = the number of vertices in the graph self.numberOfEdges = the number of edges in the graph self.vertexes = 2-dimensional list. For each vertex, [0] denotes the index, [1] the x coord and [2] the y coord. Values are all type float self. self.edges = 2-dimensional l... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Board:
"""self.numberOfVertices = the number of vertices in the graph self.numberOfEdges = the number of edges in the graph self.vertexes = 2-dimensional list. For each vertex, [0] denotes the index, [1] the x coord and [2] the y coord. Values are all type float self. self.edges = 2-dimensional list. For each... | the_stack_v2_python_sparse | module2/board.py | talepre/AIProg | train | 0 |
700fb28af3caa49e9b8acc28cc41c7452f945845 | [
"ret = []\n\ndef preorder(root):\n if not root:\n return\n ret.append(root.val)\n preorder(root.left)\n preorder(root.right)\npreorder(root)\nreturn ret",
"ret = []\ns = []\nif root:\n s.append(root)\nwhile s:\n node = s.pop()\n ret.append(node.val)\n if node.right:\n s.appen... | <|body_start_0|>
ret = []
def preorder(root):
if not root:
return
ret.append(root.val)
preorder(root.left)
preorder(root.right)
preorder(root)
return ret
<|end_body_0|>
<|body_start_1|>
ret = []
s = []
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def preorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_0|>
def preorderTraversal2(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ret = []
def ... | stack_v2_sparse_classes_75kplus_train_003795 | 1,093 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: List[int]",
"name": "preorderTraversal",
"signature": "def preorderTraversal(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: List[int]",
"name": "preorderTraversal2",
"signature": "def preorderTraversal2(self, root)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019056 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preorderTraversal(self, root): :type root: TreeNode :rtype: List[int]
- def preorderTraversal2(self, root): :type root: TreeNode :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preorderTraversal(self, root): :type root: TreeNode :rtype: List[int]
- def preorderTraversal2(self, root): :type root: TreeNode :rtype: List[int]
<|skeleton|>
class Solutio... | f55573181bf1ed29c998e0b9d22d307ee4d7b42e | <|skeleton|>
class Solution:
def preorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_0|>
def preorderTraversal2(self, root):
""":type root: TreeNode :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def preorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int]"""
ret = []
def preorder(root):
if not root:
return
ret.append(root.val)
preorder(root.left)
preorder(root.right)
preorder(roo... | the_stack_v2_python_sparse | stack/二叉树的前序遍历-144.py | chenchaojie/leetcode350 | train | 1 | |
42ffa662c5f7dd12746030c45d9256227a477f9f | [
"average = 0.040577\nstd_dev = 0.014887\nbetter_sign = -1\nreturn (average, std_dev, better_sign)",
"total = source_data.B25014_001E\nper_1_0 = source_data.B25014_004E + source_data.B25014_010E\nper_1_5 = source_data.B25014_005E + source_data.B25014_011E\nper_2_0 = source_data.B25014_006E + source_data.B25014_012... | <|body_start_0|>
average = 0.040577
std_dev = 0.014887
better_sign = -1
return (average, std_dev, better_sign)
<|end_body_0|>
<|body_start_1|>
total = source_data.B25014_001E
per_1_0 = source_data.B25014_004E + source_data.B25014_010E
per_1_5 = source_data.B25014... | Score based on weighted occupants per room | PercentOvercrowdingAlgorithm | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PercentOvercrowdingAlgorithm:
"""Score based on weighted occupants per room"""
def get_default_stats(self, source_data):
"""Stats for census tracts in Oklahoma"""
<|body_0|>
def local_percent(self, source_data):
"""Return a weighted percentage of over-occupied re... | stack_v2_sparse_classes_75kplus_train_003796 | 34,944 | no_license | [
{
"docstring": "Stats for census tracts in Oklahoma",
"name": "get_default_stats",
"signature": "def get_default_stats(self, source_data)"
},
{
"docstring": "Return a weighted percentage of over-occupied residences",
"name": "local_percent",
"signature": "def local_percent(self, source_d... | 2 | null | Implement the Python class `PercentOvercrowdingAlgorithm` described below.
Class description:
Score based on weighted occupants per room
Method signatures and docstrings:
- def get_default_stats(self, source_data): Stats for census tracts in Oklahoma
- def local_percent(self, source_data): Return a weighted percentag... | Implement the Python class `PercentOvercrowdingAlgorithm` described below.
Class description:
Score based on weighted occupants per room
Method signatures and docstrings:
- def get_default_stats(self, source_data): Stats for census tracts in Oklahoma
- def local_percent(self, source_data): Return a weighted percentag... | 0d29c3e1599b187c17ea2a2c68f8a9b78f430442 | <|skeleton|>
class PercentOvercrowdingAlgorithm:
"""Score based on weighted occupants per room"""
def get_default_stats(self, source_data):
"""Stats for census tracts in Oklahoma"""
<|body_0|>
def local_percent(self, source_data):
"""Return a weighted percentage of over-occupied re... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PercentOvercrowdingAlgorithm:
"""Score based on weighted occupants per room"""
def get_default_stats(self, source_data):
"""Stats for census tracts in Oklahoma"""
average = 0.040577
std_dev = 0.014887
better_sign = -1
return (average, std_dev, better_sign)
def... | the_stack_v2_python_sparse | healthdata/algorithms.py | CivicNinjas/HealthAround.me | train | 1 |
218b1351e4058fee2cb91eff1bd0534136acc9a3 | [
"n = len(nums)\nmax_window = []\nfor i in range(0, n - k + 1):\n curr_max = float('-inf')\n for j in range(i, i + k):\n curr_max = max(curr_max, nums[j])\n max_window.append(curr_max)\nreturn max_window",
"if not nums:\n return []\nif k > len(nums):\n return [max(nums)]\nmax_window = []\ndeq... | <|body_start_0|>
n = len(nums)
max_window = []
for i in range(0, n - k + 1):
curr_max = float('-inf')
for j in range(i, i + k):
curr_max = max(curr_max, nums[j])
max_window.append(curr_max)
return max_window
<|end_body_0|>
<|body_start... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def max_window_brute(self, nums, k):
"""Brute force algorithm. Time complexity: O(n * k). Space complexity: O(1), n is len(nums)."""
<|body_0|>
def max_window_deque(self, nums, k):
"""Algorithm based on using dequeue. Assumes k <= len(nums). Time complexity... | stack_v2_sparse_classes_75kplus_train_003797 | 2,969 | no_license | [
{
"docstring": "Brute force algorithm. Time complexity: O(n * k). Space complexity: O(1), n is len(nums).",
"name": "max_window_brute",
"signature": "def max_window_brute(self, nums, k)"
},
{
"docstring": "Algorithm based on using dequeue. Assumes k <= len(nums). Time complexity: O(n). Space com... | 2 | stack_v2_sparse_classes_30k_train_020659 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def max_window_brute(self, nums, k): Brute force algorithm. Time complexity: O(n * k). Space complexity: O(1), n is len(nums).
- def max_window_deque(self, nums, k): Algorithm ba... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def max_window_brute(self, nums, k): Brute force algorithm. Time complexity: O(n * k). Space complexity: O(1), n is len(nums).
- def max_window_deque(self, nums, k): Algorithm ba... | 71b722ddfe8da04572e527b055cf8723d5c87bbf | <|skeleton|>
class Solution:
def max_window_brute(self, nums, k):
"""Brute force algorithm. Time complexity: O(n * k). Space complexity: O(1), n is len(nums)."""
<|body_0|>
def max_window_deque(self, nums, k):
"""Algorithm based on using dequeue. Assumes k <= len(nums). Time complexity... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def max_window_brute(self, nums, k):
"""Brute force algorithm. Time complexity: O(n * k). Space complexity: O(1), n is len(nums)."""
n = len(nums)
max_window = []
for i in range(0, n - k + 1):
curr_max = float('-inf')
for j in range(i, i + k):
... | the_stack_v2_python_sparse | Stack/sliding_window_maximum.py | vladn90/Algorithms | train | 0 | |
227b67acc3af1459d1f52eb6dea52e39782e2e39 | [
"if not root:\n return None\nif key > root.val:\n root.right = self.deleteNode(root.right, key)\nelif key < root.val:\n root.left = self.deleteNode(root.left, key)\nelif not root.left and (not root.right):\n root = None\nelif root.right:\n root.val = self.successor(root)\n root.right = self.delete... | <|body_start_0|>
if not root:
return None
if key > root.val:
root.right = self.deleteNode(root.right, key)
elif key < root.val:
root.left = self.deleteNode(root.left, key)
elif not root.left and (not root.right):
root = None
elif ro... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def deleteNode(self, root, key):
""":type root: TreeNode :type key: int :rtype: TreeNode"""
<|body_0|>
def successor(self, root):
"""One step right and then always left"""
<|body_1|>
def predecessor(self, root):
"""One step left and the... | stack_v2_sparse_classes_75kplus_train_003798 | 2,749 | no_license | [
{
"docstring": ":type root: TreeNode :type key: int :rtype: TreeNode",
"name": "deleteNode",
"signature": "def deleteNode(self, root, key)"
},
{
"docstring": "One step right and then always left",
"name": "successor",
"signature": "def successor(self, root)"
},
{
"docstring": "On... | 3 | stack_v2_sparse_classes_30k_train_040436 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def deleteNode(self, root, key): :type root: TreeNode :type key: int :rtype: TreeNode
- def successor(self, root): One step right and then always left
- def predecessor(self, roo... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def deleteNode(self, root, key): :type root: TreeNode :type key: int :rtype: TreeNode
- def successor(self, root): One step right and then always left
- def predecessor(self, roo... | 90c000c3be70727cde4f7494fbbb1c425bfd3da4 | <|skeleton|>
class Solution:
def deleteNode(self, root, key):
""":type root: TreeNode :type key: int :rtype: TreeNode"""
<|body_0|>
def successor(self, root):
"""One step right and then always left"""
<|body_1|>
def predecessor(self, root):
"""One step left and the... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def deleteNode(self, root, key):
""":type root: TreeNode :type key: int :rtype: TreeNode"""
if not root:
return None
if key > root.val:
root.right = self.deleteNode(root.right, key)
elif key < root.val:
root.left = self.deleteNode(r... | the_stack_v2_python_sparse | 450.delete-node-in-a-bst.py | chenjienan/python-leetcode | train | 16 | |
e28aa78fd6a3e653cd88e47e8dc2131e748e875f | [
"self.key = int(key, 16).to_bytes(16, byteorder='little')\nself.max = bound\nself.byte_length = len(self.key) + ((bound - 1).bit_length() + 7) // 8",
"n_ = n if n else 1\nl = self.byte_length\ndk = hashlib.pbkdf2_hmac('sha1', self.key, s.encode(), 1, n_ * l)\nx = [int.from_bytes(dk[i * l:(i + 1) * l], byteorder='... | <|body_start_0|>
self.key = int(key, 16).to_bytes(16, byteorder='little')
self.max = bound
self.byte_length = len(self.key) + ((bound - 1).bit_length() + 7) // 8
<|end_body_0|>
<|body_start_1|>
n_ = n if n else 1
l = self.byte_length
dk = hashlib.pbkdf2_hmac('sha1', self... | A pseudorandom function (PRF) with 128-bit keys. A PRF is determined by a secret key and a public maximum. | PRF | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PRF:
"""A pseudorandom function (PRF) with 128-bit keys. A PRF is determined by a secret key and a public maximum."""
def __init__(self, key, bound):
"""Create a PRF determined by the given key and (upper) bound. The key is a hex string, whereas bound is a number. Output values will ... | stack_v2_sparse_classes_75kplus_train_003799 | 6,165 | no_license | [
{
"docstring": "Create a PRF determined by the given key and (upper) bound. The key is a hex string, whereas bound is a number. Output values will be in range(bound).",
"name": "__init__",
"signature": "def __init__(self, key, bound)"
},
{
"docstring": "Return a number or list of numbers in rang... | 2 | stack_v2_sparse_classes_30k_train_024836 | Implement the Python class `PRF` described below.
Class description:
A pseudorandom function (PRF) with 128-bit keys. A PRF is determined by a secret key and a public maximum.
Method signatures and docstrings:
- def __init__(self, key, bound): Create a PRF determined by the given key and (upper) bound. The key is a h... | Implement the Python class `PRF` described below.
Class description:
A pseudorandom function (PRF) with 128-bit keys. A PRF is determined by a secret key and a public maximum.
Method signatures and docstrings:
- def __init__(self, key, bound): Create a PRF determined by the given key and (upper) bound. The key is a h... | ae8e421fb840937ccd7c8d5c35a011e5eb2c63df | <|skeleton|>
class PRF:
"""A pseudorandom function (PRF) with 128-bit keys. A PRF is determined by a secret key and a public maximum."""
def __init__(self, key, bound):
"""Create a PRF determined by the given key and (upper) bound. The key is a hex string, whereas bound is a number. Output values will ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PRF:
"""A pseudorandom function (PRF) with 128-bit keys. A PRF is determined by a secret key and a public maximum."""
def __init__(self, key, bound):
"""Create a PRF determined by the given key and (upper) bound. The key is a hex string, whereas bound is a number. Output values will be in range(b... | the_stack_v2_python_sparse | device/mpyc/mpyc/thresha.py | Fluxmux/securefacematching | train | 4 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.