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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
cb99203d724146daa66b1cac2376519bd1144f0d | [
"with self.getstream() as text_stream:\n for i, line in enumerate(text_stream):\n line = SMSCorpus.case_normalizer(line)\n if self.mask is not None and (not self.mask[i]):\n continue\n ngrams = []\n for ng in tokens2ngrams(self.tokenizer(line)):\n if SMSCorpus.ig... | <|body_start_0|>
with self.getstream() as text_stream:
for i, line in enumerate(text_stream):
line = SMSCorpus.case_normalizer(line)
if self.mask is not None and (not self.mask[i]):
continue
ngrams = []
for ng in tok... | SMSCorpus | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SMSCorpus:
def get_texts(self):
"""Parse documents from a .txt file assuming 1 document per line, yielding lists of filtered tokens"""
<|body_0|>
def __len__(self):
"""Enables `len(corpus)`"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
with self.g... | stack_v2_sparse_classes_75kplus_train_066600 | 5,014 | permissive | [
{
"docstring": "Parse documents from a .txt file assuming 1 document per line, yielding lists of filtered tokens",
"name": "get_texts",
"signature": "def get_texts(self)"
},
{
"docstring": "Enables `len(corpus)`",
"name": "__len__",
"signature": "def __len__(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014382 | Implement the Python class `SMSCorpus` described below.
Class description:
Implement the SMSCorpus class.
Method signatures and docstrings:
- def get_texts(self): Parse documents from a .txt file assuming 1 document per line, yielding lists of filtered tokens
- def __len__(self): Enables `len(corpus)` | Implement the Python class `SMSCorpus` described below.
Class description:
Implement the SMSCorpus class.
Method signatures and docstrings:
- def get_texts(self): Parse documents from a .txt file assuming 1 document per line, yielding lists of filtered tokens
- def __len__(self): Enables `len(corpus)`
<|skeleton|>
c... | c5898e010b04aff72215ba8549859703857698fb | <|skeleton|>
class SMSCorpus:
def get_texts(self):
"""Parse documents from a .txt file assuming 1 document per line, yielding lists of filtered tokens"""
<|body_0|>
def __len__(self):
"""Enables `len(corpus)`"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SMSCorpus:
def get_texts(self):
"""Parse documents from a .txt file assuming 1 document per line, yielding lists of filtered tokens"""
with self.getstream() as text_stream:
for i, line in enumerate(text_stream):
line = SMSCorpus.case_normalizer(line)
... | the_stack_v2_python_sparse | src/nlpia/gensim_utils.py | totalgood/nlpia3 | train | 5 | |
9c1c5754998438f0c5768d5e6eb1053e8147dffb | [
"rows_updated = queryset.update(published=False)\nif rows_updated == 1:\n message_bit = '1 story was'\nelse:\n message_bit = '%s stories were' % rows_updated\nself.message_user(request, '%s successfully marked as published.' % message_bit)",
"rows_updated = queryset.update(published=True)\nif rows_updated =... | <|body_start_0|>
rows_updated = queryset.update(published=False)
if rows_updated == 1:
message_bit = '1 story was'
else:
message_bit = '%s stories were' % rows_updated
self.message_user(request, '%s successfully marked as published.' % message_bit)
<|end_body_0|>
... | Action для публикации и снятия с публикации | ActionPublish | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ActionPublish:
"""Action для публикации и снятия с публикации"""
def unpublish(self, request, queryset):
"""Снять с публикации"""
<|body_0|>
def publish(self, request, queryset):
"""Опубликовать"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
ro... | stack_v2_sparse_classes_75kplus_train_066601 | 2,928 | no_license | [
{
"docstring": "Снять с публикации",
"name": "unpublish",
"signature": "def unpublish(self, request, queryset)"
},
{
"docstring": "Опубликовать",
"name": "publish",
"signature": "def publish(self, request, queryset)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017225 | Implement the Python class `ActionPublish` described below.
Class description:
Action для публикации и снятия с публикации
Method signatures and docstrings:
- def unpublish(self, request, queryset): Снять с публикации
- def publish(self, request, queryset): Опубликовать | Implement the Python class `ActionPublish` described below.
Class description:
Action для публикации и снятия с публикации
Method signatures and docstrings:
- def unpublish(self, request, queryset): Снять с публикации
- def publish(self, request, queryset): Опубликовать
<|skeleton|>
class ActionPublish:
"""Actio... | d761f9203e3a310c16b66b8da6fbc03d8b8d033c | <|skeleton|>
class ActionPublish:
"""Action для публикации и снятия с публикации"""
def unpublish(self, request, queryset):
"""Снять с публикации"""
<|body_0|>
def publish(self, request, queryset):
"""Опубликовать"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ActionPublish:
"""Action для публикации и снятия с публикации"""
def unpublish(self, request, queryset):
"""Снять с публикации"""
rows_updated = queryset.update(published=False)
if rows_updated == 1:
message_bit = '1 story was'
else:
message_bit = '... | the_stack_v2_python_sparse | blog/admin.py | djek9007/ich | train | 0 |
3273a4943f6155b3a306bcc9f40065ddb0c17de2 | [
"start_index = 0\nend_index = 0\nfor cur_index in range(len(s)):\n odd_len = self.expand_from_center(cur_index, cur_index, s)\n even_len = self.expand_from_center(cur_index, cur_index + 1, s)\n max_len = max(odd_len, even_len)\n if max_len > end_index - start_index:\n start_index = cur_index - in... | <|body_start_0|>
start_index = 0
end_index = 0
for cur_index in range(len(s)):
odd_len = self.expand_from_center(cur_index, cur_index, s)
even_len = self.expand_from_center(cur_index, cur_index + 1, s)
max_len = max(odd_len, even_len)
if max_len > ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def expand_from_center(self, left, right, s):
"""Helper function to simulate a sliding window to compute length of palindrome substring. :type left: int -> representing the sliding le... | stack_v2_sparse_classes_75kplus_train_066602 | 3,038 | no_license | [
{
"docstring": ":type s: str :rtype: str",
"name": "longestPalindrome",
"signature": "def longestPalindrome(self, s)"
},
{
"docstring": "Helper function to simulate a sliding window to compute length of palindrome substring. :type left: int -> representing the sliding left index :type right: int... | 2 | stack_v2_sparse_classes_30k_train_050967 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome(self, s): :type s: str :rtype: str
- def expand_from_center(self, left, right, s): Helper function to simulate a sliding window to compute length of palindr... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def longestPalindrome(self, s): :type s: str :rtype: str
- def expand_from_center(self, left, right, s): Helper function to simulate a sliding window to compute length of palindr... | 3cda643de78c8ee31da16dcb76de936ebd73073b | <|skeleton|>
class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
<|body_0|>
def expand_from_center(self, left, right, s):
"""Helper function to simulate a sliding window to compute length of palindrome substring. :type left: int -> representing the sliding le... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def longestPalindrome(self, s):
""":type s: str :rtype: str"""
start_index = 0
end_index = 0
for cur_index in range(len(s)):
odd_len = self.expand_from_center(cur_index, cur_index, s)
even_len = self.expand_from_center(cur_index, cur_index + 1,... | the_stack_v2_python_sparse | practice/leetcode/longest_palindrome.py | uzaymacar/python-interview-review | train | 0 | |
9430f70458f67d18b38397bb5b1aaa66446747b9 | [
"print('test_login1_normal is start test...')\npo = LoginPage(self.driver)\npo.login_action('51zxw', 123456)\nsleep(2)\nself.assertEqual(po.type_loginPass_hint(), '我的空间')\nfunction.insert_img(self.driver, '51zxw_login1_normal.jpg')\nprint('test_login1_normal test end!')",
"print('test_login2_passwdError is start ... | <|body_start_0|>
print('test_login1_normal is start test...')
po = LoginPage(self.driver)
po.login_action('51zxw', 123456)
sleep(2)
self.assertEqual(po.type_loginPass_hint(), '我的空间')
function.insert_img(self.driver, '51zxw_login1_normal.jpg')
print('test_login1_no... | LoginTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LoginTest:
def test_login1_normal(self):
"""username and passwd is normal"""
<|body_0|>
def test_login2_PasswdError(self):
"""username is ok,passwd is error"""
<|body_1|>
def test_login3_empty(self):
"""username and passwd is empty"""
<|b... | stack_v2_sparse_classes_75kplus_train_066603 | 1,425 | no_license | [
{
"docstring": "username and passwd is normal",
"name": "test_login1_normal",
"signature": "def test_login1_normal(self)"
},
{
"docstring": "username is ok,passwd is error",
"name": "test_login2_PasswdError",
"signature": "def test_login2_PasswdError(self)"
},
{
"docstring": "use... | 3 | null | Implement the Python class `LoginTest` described below.
Class description:
Implement the LoginTest class.
Method signatures and docstrings:
- def test_login1_normal(self): username and passwd is normal
- def test_login2_PasswdError(self): username is ok,passwd is error
- def test_login3_empty(self): username and pass... | Implement the Python class `LoginTest` described below.
Class description:
Implement the LoginTest class.
Method signatures and docstrings:
- def test_login1_normal(self): username and passwd is normal
- def test_login2_PasswdError(self): username is ok,passwd is error
- def test_login3_empty(self): username and pass... | 1c101bb5d6b06882b2f3f179b4dd548a61ed0406 | <|skeleton|>
class LoginTest:
def test_login1_normal(self):
"""username and passwd is normal"""
<|body_0|>
def test_login2_PasswdError(self):
"""username is ok,passwd is error"""
<|body_1|>
def test_login3_empty(self):
"""username and passwd is empty"""
<|b... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LoginTest:
def test_login1_normal(self):
"""username and passwd is normal"""
print('test_login1_normal is start test...')
po = LoginPage(self.driver)
po.login_action('51zxw', 123456)
sleep(2)
self.assertEqual(po.type_loginPass_hint(), '我的空间')
function.in... | the_stack_v2_python_sparse | AutoTest_project/Website/test_case/test_login.py | mcbobo/learngit | train | 1 | |
27671b9a09b3a6a82187012ba38f8193b9fbcb0c | [
"super().__init__(coordinator, entry, type_id)\nif description.name == UNDEFINED:\n self._attr_has_entity_name = True\nelse:\n self._attr_name = f'{self.product} {description.name}'\nself._attr_unique_id = f'{entry.unique_id}_{description.key}{description.sep_key}{description.subkey}'\nself.entity_description... | <|body_start_0|>
super().__init__(coordinator, entry, type_id)
if description.name == UNDEFINED:
self._attr_has_entity_name = True
else:
self._attr_name = f'{self.product} {description.name}'
self._attr_unique_id = f'{entry.unique_id}_{description.key}{description... | Define a QNAP QSW sensor. | QswSensor | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QswSensor:
"""Define a QNAP QSW sensor."""
def __init__(self, coordinator: QswDataCoordinator, description: QswSensorEntityDescription, entry: ConfigEntry, type_id: int | None=None) -> None:
"""Initialize."""
<|body_0|>
def _async_update_attrs(self) -> None:
"""U... | stack_v2_sparse_classes_75kplus_train_066604 | 12,861 | permissive | [
{
"docstring": "Initialize.",
"name": "__init__",
"signature": "def __init__(self, coordinator: QswDataCoordinator, description: QswSensorEntityDescription, entry: ConfigEntry, type_id: int | None=None) -> None"
},
{
"docstring": "Update sensor attributes.",
"name": "_async_update_attrs",
... | 2 | stack_v2_sparse_classes_30k_train_052412 | Implement the Python class `QswSensor` described below.
Class description:
Define a QNAP QSW sensor.
Method signatures and docstrings:
- def __init__(self, coordinator: QswDataCoordinator, description: QswSensorEntityDescription, entry: ConfigEntry, type_id: int | None=None) -> None: Initialize.
- def _async_update_a... | Implement the Python class `QswSensor` described below.
Class description:
Define a QNAP QSW sensor.
Method signatures and docstrings:
- def __init__(self, coordinator: QswDataCoordinator, description: QswSensorEntityDescription, entry: ConfigEntry, type_id: int | None=None) -> None: Initialize.
- def _async_update_a... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class QswSensor:
"""Define a QNAP QSW sensor."""
def __init__(self, coordinator: QswDataCoordinator, description: QswSensorEntityDescription, entry: ConfigEntry, type_id: int | None=None) -> None:
"""Initialize."""
<|body_0|>
def _async_update_attrs(self) -> None:
"""U... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class QswSensor:
"""Define a QNAP QSW sensor."""
def __init__(self, coordinator: QswDataCoordinator, description: QswSensorEntityDescription, entry: ConfigEntry, type_id: int | None=None) -> None:
"""Initialize."""
super().__init__(coordinator, entry, type_id)
if description.name == UND... | the_stack_v2_python_sparse | homeassistant/components/qnap_qsw/sensor.py | home-assistant/core | train | 35,501 |
930881b9a350ccaef8b6fd9c162071370daaaeda | [
"self.use_ssl = use_ssl\nself.timeout = timeout\nif persistent_params is None:\n self.persistent_params = {}\nelse:\n self.persistent_params = persistent_params\nif auth is not None:\n self.auth = auth\nself.baseurl = '{protocol}://{server}:{port}/'.format(protocol=use_ssl and 'https' or 'http', server=ser... | <|body_start_0|>
self.use_ssl = use_ssl
self.timeout = timeout
if persistent_params is None:
self.persistent_params = {}
else:
self.persistent_params = persistent_params
if auth is not None:
self.auth = auth
self.baseurl = '{protocol}:/... | Connection to pcloud.com based on their json protocol. NOTE: loads the whole file in memory on data upload. | PCloudJSONConnection | [
"LicenseRef-scancode-warranty-disclaimer",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PCloudJSONConnection:
"""Connection to pcloud.com based on their json protocol. NOTE: loads the whole file in memory on data upload."""
def __init__(self, use_ssl=True, server=PCLOUD_SERVER, port=None, timeout=30, auth=None, persistent_params=None):
"""Connection to pcloud.com based ... | stack_v2_sparse_classes_75kplus_train_066605 | 2,417 | permissive | [
{
"docstring": "Connection to pcloud.com based on their json protocol. persistent_params is a dict that augments params on each command, this is useful for storing auth data. NOTE: persistent_params overrides any values in params on send_command",
"name": "__init__",
"signature": "def __init__(self, use... | 2 | stack_v2_sparse_classes_30k_train_042583 | Implement the Python class `PCloudJSONConnection` described below.
Class description:
Connection to pcloud.com based on their json protocol. NOTE: loads the whole file in memory on data upload.
Method signatures and docstrings:
- def __init__(self, use_ssl=True, server=PCLOUD_SERVER, port=None, timeout=30, auth=None,... | Implement the Python class `PCloudJSONConnection` described below.
Class description:
Connection to pcloud.com based on their json protocol. NOTE: loads the whole file in memory on data upload.
Method signatures and docstrings:
- def __init__(self, use_ssl=True, server=PCLOUD_SERVER, port=None, timeout=30, auth=None,... | 26d0aa4fe873ec3b41e026142ba547ca5271d4e9 | <|skeleton|>
class PCloudJSONConnection:
"""Connection to pcloud.com based on their json protocol. NOTE: loads the whole file in memory on data upload."""
def __init__(self, use_ssl=True, server=PCLOUD_SERVER, port=None, timeout=30, auth=None, persistent_params=None):
"""Connection to pcloud.com based ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PCloudJSONConnection:
"""Connection to pcloud.com based on their json protocol. NOTE: loads the whole file in memory on data upload."""
def __init__(self, use_ssl=True, server=PCLOUD_SERVER, port=None, timeout=30, auth=None, persistent_params=None):
"""Connection to pcloud.com based on their json... | the_stack_v2_python_sparse | pcloudapi/pcloudjson.py | tochev/python3-pcloudapi | train | 6 |
618cd2ef55c365eedfdb416b0577aa38278d48df | [
"error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}\nerror_map.update(kwargs.pop('error_map', {}) or {})\n_headers = case_insensitive_dict(kwargs.pop('headers', {}) or {})\n_params = case_insensitive_dict(kwargs.pop('params', {}) or {})\napi_version = kwargs.pop('api_... | <|body_start_0|>
error_map = {401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError}
error_map.update(kwargs.pop('error_map', {}) or {})
_headers = case_insensitive_dict(kwargs.pop('headers', {}) or {})
_params = case_insensitive_dict(kwargs.pop('params', {... | AuthenticationOperations | [
"LicenseRef-scancode-generic-cla",
"MIT",
"LGPL-2.1-or-later"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuthenticationOperations:
def exchange_aad_access_token_for_acr_refresh_token(self, grant_type, service, tenant=None, refresh_token=None, access_token=None, **kwargs):
"""Exchange AAD tokens for an ACR refresh Token. :param grant_type: Can take a value of access_token_refresh_token, or a... | stack_v2_sparse_classes_75kplus_train_066606 | 10,864 | permissive | [
{
"docstring": "Exchange AAD tokens for an ACR refresh Token. :param grant_type: Can take a value of access_token_refresh_token, or access_token, or refresh_token. :type grant_type: str or ~container_registry.models.PostContentSchemaGrantType :param service: Indicates the name of your Azure container registry. ... | 2 | stack_v2_sparse_classes_30k_train_016703 | Implement the Python class `AuthenticationOperations` described below.
Class description:
Implement the AuthenticationOperations class.
Method signatures and docstrings:
- def exchange_aad_access_token_for_acr_refresh_token(self, grant_type, service, tenant=None, refresh_token=None, access_token=None, **kwargs): Exch... | Implement the Python class `AuthenticationOperations` described below.
Class description:
Implement the AuthenticationOperations class.
Method signatures and docstrings:
- def exchange_aad_access_token_for_acr_refresh_token(self, grant_type, service, tenant=None, refresh_token=None, access_token=None, **kwargs): Exch... | c2ca191e736bb06bfbbbc9493e8325763ba990bb | <|skeleton|>
class AuthenticationOperations:
def exchange_aad_access_token_for_acr_refresh_token(self, grant_type, service, tenant=None, refresh_token=None, access_token=None, **kwargs):
"""Exchange AAD tokens for an ACR refresh Token. :param grant_type: Can take a value of access_token_refresh_token, or a... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AuthenticationOperations:
def exchange_aad_access_token_for_acr_refresh_token(self, grant_type, service, tenant=None, refresh_token=None, access_token=None, **kwargs):
"""Exchange AAD tokens for an ACR refresh Token. :param grant_type: Can take a value of access_token_refresh_token, or access_token, o... | the_stack_v2_python_sparse | sdk/containerregistry/azure-containerregistry/azure/containerregistry/_generated/operations/_patch.py | Azure/azure-sdk-for-python | train | 4,046 | |
091b8e3aaadeb6a18ff4e1c862ed46c5c073d2b8 | [
"self.tfrecords_file = tfrecords_file\nself.height = height\nself.width = width\nself.min_queue_examples = min_queue_examples\nself.batch_size = batch_size\nself.num_threads = num_threads\nself.reader = tf.TFRecordReader()\nself.name = name",
"with tf.name_scope(self.name):\n filename_queue = tf.train.string_i... | <|body_start_0|>
self.tfrecords_file = tfrecords_file
self.height = height
self.width = width
self.min_queue_examples = min_queue_examples
self.batch_size = batch_size
self.num_threads = num_threads
self.reader = tf.TFRecordReader()
self.name = name
<|end_... | Reader | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Reader:
def __init__(self, tfrecords_file, height=64, width=64, min_queue_examples=5000, batch_size=128, num_threads=8, name=''):
"""Args: tfrecords_file: string, tfrecords file path min_queue_examples: integer, minimum number of samples to retain in the queue that provides of batches of... | stack_v2_sparse_classes_75kplus_train_066607 | 4,733 | no_license | [
{
"docstring": "Args: tfrecords_file: string, tfrecords file path min_queue_examples: integer, minimum number of samples to retain in the queue that provides of batches of examples batch_size: integer, number of images per batch num_threads: integer, number of preprocess threads",
"name": "__init__",
"s... | 3 | null | Implement the Python class `Reader` described below.
Class description:
Implement the Reader class.
Method signatures and docstrings:
- def __init__(self, tfrecords_file, height=64, width=64, min_queue_examples=5000, batch_size=128, num_threads=8, name=''): Args: tfrecords_file: string, tfrecords file path min_queue_... | Implement the Python class `Reader` described below.
Class description:
Implement the Reader class.
Method signatures and docstrings:
- def __init__(self, tfrecords_file, height=64, width=64, min_queue_examples=5000, batch_size=128, num_threads=8, name=''): Args: tfrecords_file: string, tfrecords file path min_queue_... | 8f3924ce6e34e28bdeb130d623e4271e53435b46 | <|skeleton|>
class Reader:
def __init__(self, tfrecords_file, height=64, width=64, min_queue_examples=5000, batch_size=128, num_threads=8, name=''):
"""Args: tfrecords_file: string, tfrecords file path min_queue_examples: integer, minimum number of samples to retain in the queue that provides of batches of... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Reader:
def __init__(self, tfrecords_file, height=64, width=64, min_queue_examples=5000, batch_size=128, num_threads=8, name=''):
"""Args: tfrecords_file: string, tfrecords file path min_queue_examples: integer, minimum number of samples to retain in the queue that provides of batches of examples batc... | the_stack_v2_python_sparse | read_record.py | computervisionlearner/L2-Net-TensorFlow | train | 2 | |
9d746ead1ecfa2edc7e981f2a342e95a155e7b5a | [
"self.saved_rounds = settings.COMPETITION_ROUNDS\nself.saved_start = settings.COMPETITION_START\nself.saved_end = settings.COMPETITION_END\nself.current_round = 'Round 2'\nstart = datetime.date.today() - datetime.timedelta(days=7)\nend1 = start + datetime.timedelta(days=6)\nstart2 = datetime.date.today()\nend2 = st... | <|body_start_0|>
self.saved_rounds = settings.COMPETITION_ROUNDS
self.saved_start = settings.COMPETITION_START
self.saved_end = settings.COMPETITION_END
self.current_round = 'Round 2'
start = datetime.date.today() - datetime.timedelta(days=7)
end1 = start + datetime.timed... | Tests that the proper variables are loaded into a page. | ContextProcessorFunctionalTestCase | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ContextProcessorFunctionalTestCase:
"""Tests that the proper variables are loaded into a page."""
def setUp(self):
"""Sets up round and competition info to be at the start of round 2."""
<|body_0|>
def testRoundInfo(self):
"""Tests that round info is available fo... | stack_v2_sparse_classes_75kplus_train_066608 | 7,747 | no_license | [
{
"docstring": "Sets up round and competition info to be at the start of round 2.",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Tests that round info is available for the page to process.",
"name": "testRoundInfo",
"signature": "def testRoundInfo(self)"
},
{
... | 3 | null | Implement the Python class `ContextProcessorFunctionalTestCase` described below.
Class description:
Tests that the proper variables are loaded into a page.
Method signatures and docstrings:
- def setUp(self): Sets up round and competition info to be at the start of round 2.
- def testRoundInfo(self): Tests that round... | Implement the Python class `ContextProcessorFunctionalTestCase` described below.
Class description:
Tests that the proper variables are loaded into a page.
Method signatures and docstrings:
- def setUp(self): Sets up round and competition info to be at the start of round 2.
- def testRoundInfo(self): Tests that round... | 783db33ed0b38fb4dccc371c426265f7028a2d13 | <|skeleton|>
class ContextProcessorFunctionalTestCase:
"""Tests that the proper variables are loaded into a page."""
def setUp(self):
"""Sets up round and competition info to be at the start of round 2."""
<|body_0|>
def testRoundInfo(self):
"""Tests that round info is available fo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ContextProcessorFunctionalTestCase:
"""Tests that the proper variables are loaded into a page."""
def setUp(self):
"""Sets up round and competition info to be at the start of round 2."""
self.saved_rounds = settings.COMPETITION_ROUNDS
self.saved_start = settings.COMPETITION_START
... | the_stack_v2_python_sparse | makahiki/apps/components/makahiki_base/tests.py | keokilee/makahiki | train | 2 |
5b4aec72b768dc96f5310aea98c1d8e0897e3970 | [
"super().__init__()\nself.postnet = nn.LayerList()\nfor layer in six.moves.range(n_layers - 1):\n ichans = odim if layer == 0 else n_chans\n ochans = odim if layer == n_layers - 1 else n_chans\n if use_batch_norm:\n self.postnet.append(nn.Sequential(nn.Conv1D(ichans, ochans, n_filts, stride=1, paddi... | <|body_start_0|>
super().__init__()
self.postnet = nn.LayerList()
for layer in six.moves.range(n_layers - 1):
ichans = odim if layer == 0 else n_chans
ochans = odim if layer == n_layers - 1 else n_chans
if use_batch_norm:
self.postnet.append(nn... | Postnet module for Spectrogram prediction network. This is a module of Postnet in Spectrogram prediction network, which described in `Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions`_. The Postnet predicts refines the predicted Mel-filterbank of the decoder, which helps to compensate the de... | Postnet | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Postnet:
"""Postnet module for Spectrogram prediction network. This is a module of Postnet in Spectrogram prediction network, which described in `Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions`_. The Postnet predicts refines the predicted Mel-filterbank of the decode... | stack_v2_sparse_classes_75kplus_train_066609 | 6,559 | permissive | [
{
"docstring": "Initialize postnet module. Parameters ---------- idim : int Dimension of the inputs. odim : int Dimension of the outputs. n_layers : int, optional The number of layers. n_filts : int, optional The number of filter size. n_units : int, optional The number of filter channels. use_batch_norm : bool... | 2 | stack_v2_sparse_classes_30k_val_000429 | Implement the Python class `Postnet` described below.
Class description:
Postnet module for Spectrogram prediction network. This is a module of Postnet in Spectrogram prediction network, which described in `Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions`_. The Postnet predicts refines the... | Implement the Python class `Postnet` described below.
Class description:
Postnet module for Spectrogram prediction network. This is a module of Postnet in Spectrogram prediction network, which described in `Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions`_. The Postnet predicts refines the... | 8705a2a8405e3c63f2174d69880d2b5525a6c9fd | <|skeleton|>
class Postnet:
"""Postnet module for Spectrogram prediction network. This is a module of Postnet in Spectrogram prediction network, which described in `Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions`_. The Postnet predicts refines the predicted Mel-filterbank of the decode... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Postnet:
"""Postnet module for Spectrogram prediction network. This is a module of Postnet in Spectrogram prediction network, which described in `Natural TTS Synthesis by Conditioning WaveNet on Mel Spectrogram Predictions`_. The Postnet predicts refines the predicted Mel-filterbank of the decoder, which help... | the_stack_v2_python_sparse | parakeet/modules/tacotron2/decoder.py | PaddlePaddle/Parakeet | train | 609 |
924e9f67a6cb32feb7708409647d9cb221b04cbe | [
"if not parse_node:\n raise TypeError('parse_node cannot be null.')\nreturn ConditionalAccessGuestsOrExternalUsers()",
"from .conditional_access_external_tenants import ConditionalAccessExternalTenants\nfrom .conditional_access_guest_or_external_user_types import ConditionalAccessGuestOrExternalUserTypes\nfrom... | <|body_start_0|>
if not parse_node:
raise TypeError('parse_node cannot be null.')
return ConditionalAccessGuestsOrExternalUsers()
<|end_body_0|>
<|body_start_1|>
from .conditional_access_external_tenants import ConditionalAccessExternalTenants
from .conditional_access_guest_... | ConditionalAccessGuestsOrExternalUsers | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConditionalAccessGuestsOrExternalUsers:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ConditionalAccessGuestsOrExternalUsers:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the... | stack_v2_sparse_classes_75kplus_train_066610 | 3,844 | permissive | [
{
"docstring": "Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator value and create the object Returns: ConditionalAccessGuestsOrExternalUsers",
"name": "create_from_discriminator_value",
"signature": "def create... | 3 | stack_v2_sparse_classes_30k_train_015570 | Implement the Python class `ConditionalAccessGuestsOrExternalUsers` described below.
Class description:
Implement the ConditionalAccessGuestsOrExternalUsers class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ConditionalAccessGuestsOrExternalUsers: C... | Implement the Python class `ConditionalAccessGuestsOrExternalUsers` described below.
Class description:
Implement the ConditionalAccessGuestsOrExternalUsers class.
Method signatures and docstrings:
- def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ConditionalAccessGuestsOrExternalUsers: C... | 27de7ccbe688d7614b2f6bde0fdbcda4bc5cc949 | <|skeleton|>
class ConditionalAccessGuestsOrExternalUsers:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ConditionalAccessGuestsOrExternalUsers:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ConditionalAccessGuestsOrExternalUsers:
def create_from_discriminator_value(parse_node: Optional[ParseNode]=None) -> ConditionalAccessGuestsOrExternalUsers:
"""Creates a new instance of the appropriate class based on discriminator value Args: parse_node: The parse node to use to read the discriminator... | the_stack_v2_python_sparse | msgraph/generated/models/conditional_access_guests_or_external_users.py | microsoftgraph/msgraph-sdk-python | train | 135 | |
54c4f3520d5d633aec41806b924b17ff1faf61a8 | [
"QtWidgets.QDialog.__init__(self)\nself.df = pandaTable\nself.layout = QtWidgets.QGridLayout(self)\nself.rankSelect = QtWidgets.QComboBox()\nself.rankSelect.addItems(self.df.columns.values)\nself.programSelect = QtWidgets.QComboBox()\nself.programSelect.addItems(self.df.columns.values)\nself.layout.addWidget(self.p... | <|body_start_0|>
QtWidgets.QDialog.__init__(self)
self.df = pandaTable
self.layout = QtWidgets.QGridLayout(self)
self.rankSelect = QtWidgets.QComboBox()
self.rankSelect.addItems(self.df.columns.values)
self.programSelect = QtWidgets.QComboBox()
self.programSelect.... | A dialog box to get the information required by the ranksbyPrograms function. | RanksByProgramsDialogBox | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RanksByProgramsDialogBox:
"""A dialog box to get the information required by the ranksbyPrograms function."""
def __init__(self, pandaTable, parent):
"""Initializes the UI and sets the two dropdowns to display column names of the active Panda."""
<|body_0|>
def getResult... | stack_v2_sparse_classes_75kplus_train_066611 | 29,548 | no_license | [
{
"docstring": "Initializes the UI and sets the two dropdowns to display column names of the active Panda.",
"name": "__init__",
"signature": "def __init__(self, pandaTable, parent)"
},
{
"docstring": "Returns the user's input",
"name": "getResults",
"signature": "def getResults(self, pa... | 2 | stack_v2_sparse_classes_30k_train_034838 | Implement the Python class `RanksByProgramsDialogBox` described below.
Class description:
A dialog box to get the information required by the ranksbyPrograms function.
Method signatures and docstrings:
- def __init__(self, pandaTable, parent): Initializes the UI and sets the two dropdowns to display column names of t... | Implement the Python class `RanksByProgramsDialogBox` described below.
Class description:
A dialog box to get the information required by the ranksbyPrograms function.
Method signatures and docstrings:
- def __init__(self, pandaTable, parent): Initializes the UI and sets the two dropdowns to display column names of t... | 1a3c5ad967472faf66236a311cc07a5128f5f911 | <|skeleton|>
class RanksByProgramsDialogBox:
"""A dialog box to get the information required by the ranksbyPrograms function."""
def __init__(self, pandaTable, parent):
"""Initializes the UI and sets the two dropdowns to display column names of the active Panda."""
<|body_0|>
def getResult... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RanksByProgramsDialogBox:
"""A dialog box to get the information required by the ranksbyPrograms function."""
def __init__(self, pandaTable, parent):
"""Initializes the UI and sets the two dropdowns to display column names of the active Panda."""
QtWidgets.QDialog.__init__(self)
s... | the_stack_v2_python_sparse | datatool/gui/Model.py | scottawalton/datatool | train | 0 |
d1f50397ba3593ee2bd6da2b2e2cd558563458b4 | [
"def two_sum(left, right, target):\n while left < right:\n if nums[left] + nums[right] + target == 0:\n output.append([target, nums[left], nums[right]])\n while left < right and nums[left] == nums[left + 1]:\n left += 1\n while left < right and nums[right] =... | <|body_start_0|>
def two_sum(left, right, target):
while left < right:
if nums[left] + nums[right] + target == 0:
output.append([target, nums[left], nums[right]])
while left < right and nums[left] == nums[left + 1]:
left... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def threeSum(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def threeSum_failed(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
def threeSum_failed2(self, nums):
""":type nums: Li... | stack_v2_sparse_classes_75kplus_train_066612 | 3,729 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "threeSum",
"signature": "def threeSum(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: List[List[int]]",
"name": "threeSum_failed",
"signature": "def threeSum_failed(self, nums)"
},
{
"docstring... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def threeSum(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def threeSum_failed(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def threeSum_failed2(se... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def threeSum(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def threeSum_failed(self, nums): :type nums: List[int] :rtype: List[List[int]]
- def threeSum_failed2(se... | e60ba45fe2f2e5e3b3abfecec3db76f5ce1fde59 | <|skeleton|>
class Solution:
def threeSum(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_0|>
def threeSum_failed(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
<|body_1|>
def threeSum_failed2(self, nums):
""":type nums: Li... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def threeSum(self, nums):
""":type nums: List[int] :rtype: List[List[int]]"""
def two_sum(left, right, target):
while left < right:
if nums[left] + nums[right] + target == 0:
output.append([target, nums[left], nums[right]])
... | the_stack_v2_python_sparse | src/lt_15.py | oxhead/CodingYourWay | train | 0 | |
4f84e207d7b9eeebbb7e92b77aafeadb97b4514a | [
"errors = {}\nif user_input is not None:\n if user_input[CONF_DEVICE] == CONF_MANUAL_PATH:\n return await self.async_step_setup_serial_manual_path()\n dev_path = await self.hass.async_add_executor_job(usb.get_serial_by_id, user_input[CONF_DEVICE])\n _LOGGER.debug('Using this path : %s', dev_path)\n ... | <|body_start_0|>
errors = {}
if user_input is not None:
if user_input[CONF_DEVICE] == CONF_MANUAL_PATH:
return await self.async_step_setup_serial_manual_path()
dev_path = await self.hass.async_add_executor_job(usb.get_serial_by_id, user_input[CONF_DEVICE])
... | Handle a config flow for Ultraheat Heat Meter. | ConfigFlow | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConfigFlow:
"""Handle a config flow for Ultraheat Heat Meter."""
async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult:
"""Step when setting up serial configuration."""
<|body_0|>
async def async_step_setup_serial_manual_path(self, user_in... | stack_v2_sparse_classes_75kplus_train_066613 | 4,924 | permissive | [
{
"docstring": "Step when setting up serial configuration.",
"name": "async_step_user",
"signature": "async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult"
},
{
"docstring": "Set path manually.",
"name": "async_step_setup_serial_manual_path",
"signature":... | 4 | stack_v2_sparse_classes_30k_train_026082 | Implement the Python class `ConfigFlow` described below.
Class description:
Handle a config flow for Ultraheat Heat Meter.
Method signatures and docstrings:
- async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult: Step when setting up serial configuration.
- async def async_step_setup_... | Implement the Python class `ConfigFlow` described below.
Class description:
Handle a config flow for Ultraheat Heat Meter.
Method signatures and docstrings:
- async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult: Step when setting up serial configuration.
- async def async_step_setup_... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class ConfigFlow:
"""Handle a config flow for Ultraheat Heat Meter."""
async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult:
"""Step when setting up serial configuration."""
<|body_0|>
async def async_step_setup_serial_manual_path(self, user_in... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ConfigFlow:
"""Handle a config flow for Ultraheat Heat Meter."""
async def async_step_user(self, user_input: dict[str, Any] | None=None) -> FlowResult:
"""Step when setting up serial configuration."""
errors = {}
if user_input is not None:
if user_input[CONF_DEVICE] ==... | the_stack_v2_python_sparse | homeassistant/components/landisgyr_heat_meter/config_flow.py | home-assistant/core | train | 35,501 |
76b3eb3cf2623d39f2eb054cc0b7636ae6827484 | [
"data = {'id': self.id, 'email': self.email}\ntoken = SecretTool.encryption(data)\nverify_url = 'http://www.meiduo.site:8080/usercenter/verify_email?token=' + token\nreturn verify_url",
"data = SecretTool.decryption(token)\nif data is None:\n return data\nid = data.get('id')\nemail = data.get('email')\ntry:\n ... | <|body_start_0|>
data = {'id': self.id, 'email': self.email}
token = SecretTool.encryption(data)
verify_url = 'http://www.meiduo.site:8080/usercenter/verify_email?token=' + token
return verify_url
<|end_body_0|>
<|body_start_1|>
data = SecretTool.decryption(token)
if dat... | User | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class User:
def generate_verify_email_url(self):
"""在模型类中写入生成验证邮箱的地址，那么在视图或者序列化器中，就可以通过模型对象直接调用"""
<|body_0|>
def check_verify_email_token(token):
"""验证邮箱token"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
data = {'id': self.id, 'email': self.email}
... | stack_v2_sparse_classes_75kplus_train_066614 | 2,764 | no_license | [
{
"docstring": "在模型类中写入生成验证邮箱的地址，那么在视图或者序列化器中，就可以通过模型对象直接调用",
"name": "generate_verify_email_url",
"signature": "def generate_verify_email_url(self)"
},
{
"docstring": "验证邮箱token",
"name": "check_verify_email_token",
"signature": "def check_verify_email_token(token)"
}
] | 2 | null | Implement the Python class `User` described below.
Class description:
Implement the User class.
Method signatures and docstrings:
- def generate_verify_email_url(self): 在模型类中写入生成验证邮箱的地址，那么在视图或者序列化器中，就可以通过模型对象直接调用
- def check_verify_email_token(token): 验证邮箱token | Implement the Python class `User` described below.
Class description:
Implement the User class.
Method signatures and docstrings:
- def generate_verify_email_url(self): 在模型类中写入生成验证邮箱的地址，那么在视图或者序列化器中，就可以通过模型对象直接调用
- def check_verify_email_token(token): 验证邮箱token
<|skeleton|>
class User:
def generate_verify_email... | a8fb0fc2352e0c71bab756a06c5a8babd8c350da | <|skeleton|>
class User:
def generate_verify_email_url(self):
"""在模型类中写入生成验证邮箱的地址，那么在视图或者序列化器中，就可以通过模型对象直接调用"""
<|body_0|>
def check_verify_email_token(token):
"""验证邮箱token"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class User:
def generate_verify_email_url(self):
"""在模型类中写入生成验证邮箱的地址，那么在视图或者序列化器中，就可以通过模型对象直接调用"""
data = {'id': self.id, 'email': self.email}
token = SecretTool.encryption(data)
verify_url = 'http://www.meiduo.site:8080/usercenter/verify_email?token=' + token
return verify_u... | the_stack_v2_python_sparse | meiduo_mall/meiduo_mall/apps/users/models.py | zhangjian-ai/meiduo | train | 22 | |
fb029b428627adba554347dbf73638f0e9527ac3 | [
"today = datetime.today()\nprint(f'today: {today} (local time, NO time zone info)')\nself.assertTrue(today.year > 0)\nself.assertTrue(today.month > 0)\nself.assertTrue(today.day > 0)\nself.assertTrue(today.hour >= 0)\nself.assertTrue(today.minute >= 0)\nself.assertTrue(today.second >= 0)\nself.assertTrue(today.micr... | <|body_start_0|>
today = datetime.today()
print(f'today: {today} (local time, NO time zone info)')
self.assertTrue(today.year > 0)
self.assertTrue(today.month > 0)
self.assertTrue(today.day > 0)
self.assertTrue(today.hour >= 0)
self.assertTrue(today.minute >= 0)
... | Test_datetime | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test_datetime:
def test_today(self):
"""Demo of `datetime.datetime.today()`. https://docs.python.org/3/library/datetime.html#datetime.datetime.today This method returns the local time but WITHOUT time zone info. Therefore, simply looking at the returned object by `today()` one would not ... | stack_v2_sparse_classes_75kplus_train_066615 | 3,889 | no_license | [
{
"docstring": "Demo of `datetime.datetime.today()`. https://docs.python.org/3/library/datetime.html#datetime.datetime.today This method returns the local time but WITHOUT time zone info. Therefore, simply looking at the returned object by `today()` one would not be able to tell if it's UTC or local time. There... | 3 | stack_v2_sparse_classes_30k_train_004142 | Implement the Python class `Test_datetime` described below.
Class description:
Implement the Test_datetime class.
Method signatures and docstrings:
- def test_today(self): Demo of `datetime.datetime.today()`. https://docs.python.org/3/library/datetime.html#datetime.datetime.today This method returns the local time bu... | Implement the Python class `Test_datetime` described below.
Class description:
Implement the Test_datetime class.
Method signatures and docstrings:
- def test_today(self): Demo of `datetime.datetime.today()`. https://docs.python.org/3/library/datetime.html#datetime.datetime.today This method returns the local time bu... | 2669a47213983879361e66aa7634a0897cf1695e | <|skeleton|>
class Test_datetime:
def test_today(self):
"""Demo of `datetime.datetime.today()`. https://docs.python.org/3/library/datetime.html#datetime.datetime.today This method returns the local time but WITHOUT time zone info. Therefore, simply looking at the returned object by `today()` one would not ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Test_datetime:
def test_today(self):
"""Demo of `datetime.datetime.today()`. https://docs.python.org/3/library/datetime.html#datetime.datetime.today This method returns the local time but WITHOUT time zone info. Therefore, simply looking at the returned object by `today()` one would not be able to tel... | the_stack_v2_python_sparse | Python/datetime/datetime_demo.py | yaobinwen/robin_on_rails | train | 9 | |
c32de2297c1e259a3fb0b1d07f320c3a200fe0be | [
"if id is not None:\n self.id = id\nelse:\n Base.__nb_objects += 1\n self.id = Base.__nb_objects",
"if list_dictionaries is None:\n return '[]'\nelse:\n return json.dumps(list_dictionaries)",
"if list_objs is None:\n list_objs = []\ndic_t = []\nfor a in list_objs:\n dic_t.append(cls.to_dict... | <|body_start_0|>
if id is not None:
self.id = id
else:
Base.__nb_objects += 1
self.id = Base.__nb_objects
<|end_body_0|>
<|body_start_1|>
if list_dictionaries is None:
return '[]'
else:
return json.dumps(list_dictionaries)
<|en... | creando la clase | Base | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Base:
"""creando la clase"""
def __init__(self, id=None):
"""constructor de clase"""
<|body_0|>
def to_json_string(list_dictionaries):
"""return list in json"""
<|body_1|>
def save_to_file(cls, list_objs):
"""class method to file in json stri... | stack_v2_sparse_classes_75kplus_train_066616 | 1,447 | no_license | [
{
"docstring": "constructor de clase",
"name": "__init__",
"signature": "def __init__(self, id=None)"
},
{
"docstring": "return list in json",
"name": "to_json_string",
"signature": "def to_json_string(list_dictionaries)"
},
{
"docstring": "class method to file in json string",
... | 5 | stack_v2_sparse_classes_30k_train_043412 | Implement the Python class `Base` described below.
Class description:
creando la clase
Method signatures and docstrings:
- def __init__(self, id=None): constructor de clase
- def to_json_string(list_dictionaries): return list in json
- def save_to_file(cls, list_objs): class method to file in json string
- def from_j... | Implement the Python class `Base` described below.
Class description:
creando la clase
Method signatures and docstrings:
- def __init__(self, id=None): constructor de clase
- def to_json_string(list_dictionaries): return list in json
- def save_to_file(cls, list_objs): class method to file in json string
- def from_j... | 6ede96eb50808e6e39aa57ffe0abfe4089408288 | <|skeleton|>
class Base:
"""creando la clase"""
def __init__(self, id=None):
"""constructor de clase"""
<|body_0|>
def to_json_string(list_dictionaries):
"""return list in json"""
<|body_1|>
def save_to_file(cls, list_objs):
"""class method to file in json stri... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Base:
"""creando la clase"""
def __init__(self, id=None):
"""constructor de clase"""
if id is not None:
self.id = id
else:
Base.__nb_objects += 1
self.id = Base.__nb_objects
def to_json_string(list_dictionaries):
"""return list in j... | the_stack_v2_python_sparse | 0x0C-python-almost_a_circle/models/base.py | SebastianMH14/holbertonschool-higher_level_programming | train | 0 |
a64222290f506accae7857e7e16d9ddc2b66a2da | [
"if not people:\n return []\npeopledct, height, res = ({}, [], [])\nfor i in range(len(people)):\n p = people[i]\n if p[0] in peopledct:\n peopledct[p[0]] += ((p[1], i),)\n else:\n peopledct[p[0]] = [(p[1], i)]\n height += (p[0],)\nheight.sort()\nfor h in height[::-1]:\n peopledc... | <|body_start_0|>
if not people:
return []
peopledct, height, res = ({}, [], [])
for i in range(len(people)):
p = people[i]
if p[0] in peopledct:
peopledct[p[0]] += ((p[1], i),)
else:
peopledct[p[0]] = [(p[1], i)]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def reconstructQueueFast(self, people):
""":type people: List[List[int]] :rtype: List[List[int]] Pick out tallest group of people and sort them in a subarray (S). Since there's no other groups of people taller than them, therefore each guy's index will be just as same as his k ... | stack_v2_sparse_classes_75kplus_train_066617 | 3,454 | no_license | [
{
"docstring": ":type people: List[List[int]] :rtype: List[List[int]] Pick out tallest group of people and sort them in a subarray (S). Since there's no other groups of people taller than them, therefore each guy's index will be just as same as his k value. For 2nd tallest group (and the rest), insert each one ... | 2 | stack_v2_sparse_classes_30k_val_000424 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reconstructQueueFast(self, people): :type people: List[List[int]] :rtype: List[List[int]] Pick out tallest group of people and sort them in a subarray (S). Since there's no o... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def reconstructQueueFast(self, people): :type people: List[List[int]] :rtype: List[List[int]] Pick out tallest group of people and sort them in a subarray (S). Since there's no o... | 810575368ecffa97677bdb51744d1f716140bbb1 | <|skeleton|>
class Solution:
def reconstructQueueFast(self, people):
""":type people: List[List[int]] :rtype: List[List[int]] Pick out tallest group of people and sort them in a subarray (S). Since there's no other groups of people taller than them, therefore each guy's index will be just as same as his k ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def reconstructQueueFast(self, people):
""":type people: List[List[int]] :rtype: List[List[int]] Pick out tallest group of people and sort them in a subarray (S). Since there's no other groups of people taller than them, therefore each guy's index will be just as same as his k value. For 2nd... | the_stack_v2_python_sparse | Q/QueueReconstructionByHeight.py | bssrdf/pyleet | train | 2 | |
0dcdea92aec4ba85a80891a6725b54f37490b6a1 | [
"processed_query = {}\nfor key, value in request.GET.items():\n processed_query[key] = value\nali_sign = processed_query.pop('sign', None)\nalipay = AliPay(appid='2016102600761595', app_notify_url=settings.NOTIFY_URL, app_private_key_path=settings.APP_PRIVATE_KEY_PATH, alipay_public_key_path=settings.ALIPAY_PUBL... | <|body_start_0|>
processed_query = {}
for key, value in request.GET.items():
processed_query[key] = value
ali_sign = processed_query.pop('sign', None)
alipay = AliPay(appid='2016102600761595', app_notify_url=settings.NOTIFY_URL, app_private_key_path=settings.APP_PRIVATE_KEY_P... | AliPayView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AliPayView:
def get(request):
"""处理支付宝return_url :param request: :return:"""
<|body_0|>
def post(request):
"""处理支付宝notify_url :param request: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
processed_query = {}
for key, value in req... | stack_v2_sparse_classes_75kplus_train_066618 | 5,432 | no_license | [
{
"docstring": "处理支付宝return_url :param request: :return:",
"name": "get",
"signature": "def get(request)"
},
{
"docstring": "处理支付宝notify_url :param request: :return:",
"name": "post",
"signature": "def post(request)"
}
] | 2 | stack_v2_sparse_classes_30k_train_051713 | Implement the Python class `AliPayView` described below.
Class description:
Implement the AliPayView class.
Method signatures and docstrings:
- def get(request): 处理支付宝return_url :param request: :return:
- def post(request): 处理支付宝notify_url :param request: :return: | Implement the Python class `AliPayView` described below.
Class description:
Implement the AliPayView class.
Method signatures and docstrings:
- def get(request): 处理支付宝return_url :param request: :return:
- def post(request): 处理支付宝notify_url :param request: :return:
<|skeleton|>
class AliPayView:
def get(request)... | bd8309087e2fc32c527e87af82d8f8e839763f97 | <|skeleton|>
class AliPayView:
def get(request):
"""处理支付宝return_url :param request: :return:"""
<|body_0|>
def post(request):
"""处理支付宝notify_url :param request: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class AliPayView:
def get(request):
"""处理支付宝return_url :param request: :return:"""
processed_query = {}
for key, value in request.GET.items():
processed_query[key] = value
ali_sign = processed_query.pop('sign', None)
alipay = AliPay(appid='2016102600761595', app_n... | the_stack_v2_python_sparse | apps/trades/views.py | Lchyang/SpaceShop | train | 0 | |
92d21f23e8f986666ede4e10477e79a34ec5dd81 | [
"self.words = words\nself.temp_dict = {}\nfor i in range(len(words)):\n if words[i] not in self.temp_dict:\n self.temp_dict[words[i]] = [i]\n else:\n self.temp_dict[words[i]].append(i)",
"maxi = sys.maxint\nlist1 = self.temp_dict[word1]\nlist2 = self.temp_dict[word2]\nfor i in range(len(list1)... | <|body_start_0|>
self.words = words
self.temp_dict = {}
for i in range(len(words)):
if words[i] not in self.temp_dict:
self.temp_dict[words[i]] = [i]
else:
self.temp_dict[words[i]].append(i)
<|end_body_0|>
<|body_start_1|>
maxi = s... | WordDistance | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WordDistance:
def __init__(self, words):
""":type words: List[str]"""
<|body_0|>
def shortest(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.words = words
self.temp_... | stack_v2_sparse_classes_75kplus_train_066619 | 935 | no_license | [
{
"docstring": ":type words: List[str]",
"name": "__init__",
"signature": "def __init__(self, words)"
},
{
"docstring": ":type word1: str :type word2: str :rtype: int",
"name": "shortest",
"signature": "def shortest(self, word1, word2)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017521 | Implement the Python class `WordDistance` described below.
Class description:
Implement the WordDistance class.
Method signatures and docstrings:
- def __init__(self, words): :type words: List[str]
- def shortest(self, word1, word2): :type word1: str :type word2: str :rtype: int | Implement the Python class `WordDistance` described below.
Class description:
Implement the WordDistance class.
Method signatures and docstrings:
- def __init__(self, words): :type words: List[str]
- def shortest(self, word1, word2): :type word1: str :type word2: str :rtype: int
<|skeleton|>
class WordDistance:
... | 2f53c4e16d244c83aad9b4d67a249f669b9da92a | <|skeleton|>
class WordDistance:
def __init__(self, words):
""":type words: List[str]"""
<|body_0|>
def shortest(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class WordDistance:
def __init__(self, words):
""":type words: List[str]"""
self.words = words
self.temp_dict = {}
for i in range(len(words)):
if words[i] not in self.temp_dict:
self.temp_dict[words[i]] = [i]
else:
self.temp_dic... | the_stack_v2_python_sparse | prob244/shortest_word_distance2.py | sharath28/leetcode | train | 1 | |
32cfea1d1dd907b10d0ff264908bad6ac01880ff | [
"server = jenkins_server.get_jenkins_server()\ntry:\n env = server.get_build_env_vars(job_name, build_number)\nexcept JenkinsException as e:\n return '%s#%d不存在' % (job_name, build_number)\nreturn env",
"server = jenkins_server.get_jenkins_server()\ntry:\n console_text = server.get_build_console_output(jo... | <|body_start_0|>
server = jenkins_server.get_jenkins_server()
try:
env = server.get_build_env_vars(job_name, build_number)
except JenkinsException as e:
return '%s#%d不存在' % (job_name, build_number)
return env
<|end_body_0|>
<|body_start_1|>
server = jenki... | Manage builds | Build | [
"LicenseRef-scancode-mulanpsl-2.0-en",
"MulanPSL-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Build:
"""Manage builds"""
def env(self, job_name, build_number):
"""Display env vars of a build"""
<|body_0|>
def log(self, job_name, build_number):
"""Display log of a build"""
<|body_1|>
def info(self, job_name, build_number):
"""Display i... | stack_v2_sparse_classes_75kplus_train_066620 | 2,328 | permissive | [
{
"docstring": "Display env vars of a build",
"name": "env",
"signature": "def env(self, job_name, build_number)"
},
{
"docstring": "Display log of a build",
"name": "log",
"signature": "def log(self, job_name, build_number)"
},
{
"docstring": "Display info of a build",
"name... | 4 | null | Implement the Python class `Build` described below.
Class description:
Manage builds
Method signatures and docstrings:
- def env(self, job_name, build_number): Display env vars of a build
- def log(self, job_name, build_number): Display log of a build
- def info(self, job_name, build_number): Display info of a build
... | Implement the Python class `Build` described below.
Class description:
Manage builds
Method signatures and docstrings:
- def env(self, job_name, build_number): Display env vars of a build
- def log(self, job_name, build_number): Display log of a build
- def info(self, job_name, build_number): Display info of a build
... | d8cbdab84d837a45c644a67e1072778f41bb89a5 | <|skeleton|>
class Build:
"""Manage builds"""
def env(self, job_name, build_number):
"""Display env vars of a build"""
<|body_0|>
def log(self, job_name, build_number):
"""Display log of a build"""
<|body_1|>
def info(self, job_name, build_number):
"""Display i... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Build:
"""Manage builds"""
def env(self, job_name, build_number):
"""Display env vars of a build"""
server = jenkins_server.get_jenkins_server()
try:
env = server.get_build_env_vars(job_name, build_number)
except JenkinsException as e:
return '%s#%d... | the_stack_v2_python_sparse | jenkinsclient/build.py | project-demo-auto/jenkinsclient | train | 0 |
61844fe67498f91247ffde49913534ab30d59a3a | [
"user.set_unusable_password()\nuser = self.update_user(user, attributes, attribute_mapping, force_save=True)\nuser_pendings = Invitation.objects.filter(email=user.email)\nfor user_pending in user_pendings:\n CourseTeacher.objects.get_or_create(course=user_pending.course, teacher=user)\n user_pending.delete()\... | <|body_start_0|>
user.set_unusable_password()
user = self.update_user(user, attributes, attribute_mapping, force_save=True)
user_pendings = Invitation.objects.filter(email=user.email)
for user_pending in user_pendings:
CourseTeacher.objects.get_or_create(course=user_pending.c... | Extend the SAML2 backend for the integration with OpenMOOC. .. versionadded:: 0.1 | Saml2BackendExtension | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Saml2BackendExtension:
"""Extend the SAML2 backend for the integration with OpenMOOC. .. versionadded:: 0.1"""
def configure_user(self, user, attributes, attribute_mapping):
"""Configures a user after creation and returns the updated user. By default, returns the user with his attrib... | stack_v2_sparse_classes_75kplus_train_066621 | 3,604 | permissive | [
{
"docstring": "Configures a user after creation and returns the updated user. By default, returns the user with his attributes updated.",
"name": "configure_user",
"signature": "def configure_user(self, user, attributes, attribute_mapping)"
},
{
"docstring": "Update a user with a set of attribu... | 2 | stack_v2_sparse_classes_30k_train_037342 | Implement the Python class `Saml2BackendExtension` described below.
Class description:
Extend the SAML2 backend for the integration with OpenMOOC. .. versionadded:: 0.1
Method signatures and docstrings:
- def configure_user(self, user, attributes, attribute_mapping): Configures a user after creation and returns the u... | Implement the Python class `Saml2BackendExtension` described below.
Class description:
Extend the SAML2 backend for the integration with OpenMOOC. .. versionadded:: 0.1
Method signatures and docstrings:
- def configure_user(self, user, attributes, attribute_mapping): Configures a user after creation and returns the u... | d5301ba867cc6c982754478ad26df39d7d858b8d | <|skeleton|>
class Saml2BackendExtension:
"""Extend the SAML2 backend for the integration with OpenMOOC. .. versionadded:: 0.1"""
def configure_user(self, user, attributes, attribute_mapping):
"""Configures a user after creation and returns the updated user. By default, returns the user with his attrib... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Saml2BackendExtension:
"""Extend the SAML2 backend for the integration with OpenMOOC. .. versionadded:: 0.1"""
def configure_user(self, user, attributes, attribute_mapping):
"""Configures a user after creation and returns the updated user. By default, returns the user with his attributes updated.... | the_stack_v2_python_sparse | moocng/courses/backends.py | GeographicaGS/moocng | train | 2 |
fbadcf696316b48fe484cb4894cb801bffb54001 | [
"stub = reco_pb2_grpc.UserRecommendStub(current_app.rpc_reco)\nreq = reco_pb2.UserRequest()\nreq.user_id = str(g.user_id) if g.user_id is not None else 'Anony'\nreq.channel_id = channel_id\nreq.article_num = feed_count\nreq.time_stamp = timestamp\nret = stub.user_recommend(req)\npre_timestamp = ret.time_stamp\narti... | <|body_start_0|>
stub = reco_pb2_grpc.UserRecommendStub(current_app.rpc_reco)
req = reco_pb2.UserRequest()
req.user_id = str(g.user_id) if g.user_id is not None else 'Anony'
req.channel_id = channel_id
req.article_num = feed_count
req.time_stamp = timestamp
ret = ... | 获取推荐文章列表数据 | ArticleListResource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ArticleListResource:
"""获取推荐文章列表数据"""
def _feed_articles(self, channel_id, timestamp, feed_count):
"""获取推荐文章 :param channel_id: 频道id :param feed_count: 推荐数量 :param timestamp: 时间戳 :return: [{article_id, trace_params}, ...], timestamp"""
<|body_0|>
def get(self):
"... | stack_v2_sparse_classes_75kplus_train_066622 | 9,216 | no_license | [
{
"docstring": "获取推荐文章 :param channel_id: 频道id :param feed_count: 推荐数量 :param timestamp: 时间戳 :return: [{article_id, trace_params}, ...], timestamp",
"name": "_feed_articles",
"signature": "def _feed_articles(self, channel_id, timestamp, feed_count)"
},
{
"docstring": "获取文章列表 /v1_1/articles?chann... | 2 | stack_v2_sparse_classes_30k_train_024846 | Implement the Python class `ArticleListResource` described below.
Class description:
获取推荐文章列表数据
Method signatures and docstrings:
- def _feed_articles(self, channel_id, timestamp, feed_count): 获取推荐文章 :param channel_id: 频道id :param feed_count: 推荐数量 :param timestamp: 时间戳 :return: [{article_id, trace_params}, ...], time... | Implement the Python class `ArticleListResource` described below.
Class description:
获取推荐文章列表数据
Method signatures and docstrings:
- def _feed_articles(self, channel_id, timestamp, feed_count): 获取推荐文章 :param channel_id: 频道id :param feed_count: 推荐数量 :param timestamp: 时间戳 :return: [{article_id, trace_params}, ...], time... | 12b52f21a4ec20b4853870468c28d2385dc185a8 | <|skeleton|>
class ArticleListResource:
"""获取推荐文章列表数据"""
def _feed_articles(self, channel_id, timestamp, feed_count):
"""获取推荐文章 :param channel_id: 频道id :param feed_count: 推荐数量 :param timestamp: 时间戳 :return: [{article_id, trace_params}, ...], timestamp"""
<|body_0|>
def get(self):
"... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ArticleListResource:
"""获取推荐文章列表数据"""
def _feed_articles(self, channel_id, timestamp, feed_count):
"""获取推荐文章 :param channel_id: 频道id :param feed_count: 推荐数量 :param timestamp: 时间戳 :return: [{article_id, trace_params}, ...], timestamp"""
stub = reco_pb2_grpc.UserRecommendStub(current_app.rp... | the_stack_v2_python_sparse | flask_prj/tbd_42/toutiao/resources/news/article.py | 123wuyu/demo_prj | train | 1 |
ff0eb24014181d10dac403ffc269d5e581b658a9 | [
"html_class = super(BaseBookmarkPlugin, self).html_class\nif self.data.image:\n html_class += ' iconic-url'\nreturn html_class",
"try:\n bookmark = Bookmark._default_manager.get(pk=self.data.bookmark)\nexcept ObjectDoesNotExist:\n return\nif bookmark:\n data = {'bookmark': bookmark.pk, 'title': bookma... | <|body_start_0|>
html_class = super(BaseBookmarkPlugin, self).html_class
if self.data.image:
html_class += ' iconic-url'
return html_class
<|end_body_0|>
<|body_start_1|>
try:
bookmark = Bookmark._default_manager.get(pk=self.data.bookmark)
except ObjectDo... | Base URL plugin. | BaseBookmarkPlugin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseBookmarkPlugin:
"""Base URL plugin."""
def html_class(self):
"""HTML class. If plugin has an image, we add a class `iconic` to it."""
<|body_0|>
def update_plugin_data(self, dashboard_entry):
"""Update plugin data. Should return a dictionary with the plugin d... | stack_v2_sparse_classes_75kplus_train_066623 | 3,111 | no_license | [
{
"docstring": "HTML class. If plugin has an image, we add a class `iconic` to it.",
"name": "html_class",
"signature": "def html_class(self)"
},
{
"docstring": "Update plugin data. Should return a dictionary with the plugin data which is supposed to be updated.",
"name": "update_plugin_data... | 2 | stack_v2_sparse_classes_30k_train_014505 | Implement the Python class `BaseBookmarkPlugin` described below.
Class description:
Base URL plugin.
Method signatures and docstrings:
- def html_class(self): HTML class. If plugin has an image, we add a class `iconic` to it.
- def update_plugin_data(self, dashboard_entry): Update plugin data. Should return a diction... | Implement the Python class `BaseBookmarkPlugin` described below.
Class description:
Base URL plugin.
Method signatures and docstrings:
- def html_class(self): HTML class. If plugin has an image, we add a class `iconic` to it.
- def update_plugin_data(self, dashboard_entry): Update plugin data. Should return a diction... | bef95536e96417e18972a3118e19a8074bfc8684 | <|skeleton|>
class BaseBookmarkPlugin:
"""Base URL plugin."""
def html_class(self):
"""HTML class. If plugin has an image, we add a class `iconic` to it."""
<|body_0|>
def update_plugin_data(self, dashboard_entry):
"""Update plugin data. Should return a dictionary with the plugin d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BaseBookmarkPlugin:
"""Base URL plugin."""
def html_class(self):
"""HTML class. If plugin has an image, we add a class `iconic` to it."""
html_class = super(BaseBookmarkPlugin, self).html_class
if self.data.image:
html_class += ' iconic-url'
return html_class
... | the_stack_v2_python_sparse | ENV/Lib/site-packages/dash/contrib/plugins/url/dash_plugins.py | JulianYangJingJun/OSVRCMS | train | 3 |
14f229d21cf6ef1b3df5017db0273fd6874a0179 | [
"result = []\nif not root:\n return result\nqueue = collections.deque([root])\nwhile queue:\n root = queue.pop()\n if root:\n result.append(str(root.val))\n queue.appendleft(root.left)\n queue.appendleft(root.right)\n else:\n result.append('#')\nreturn ' '.join(result)",
"i... | <|body_start_0|>
result = []
if not root:
return result
queue = collections.deque([root])
while queue:
root = queue.pop()
if root:
result.append(str(root.val))
queue.appendleft(root.left)
queue.appendleft... | 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_066624 | 3,899 | 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_026013 | 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:... | d953abe2c9680f636563e76287d2f907e90ced63 | <|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"""
result = []
if not root:
return result
queue = collections.deque([root])
while queue:
root = queue.pop()
if root:
... | the_stack_v2_python_sparse | Python_leetcode/297_serialize_and_deserialize.py | xiangcao/Leetcode | train | 0 | |
0638b165ff32189c208a1bdbba2f874e7e4d2f2b | [
"self.loader = self.loader_class()\nsuper().__init__(loader=self.loader)\nself.resource = resource\nself.dynamic_inventory()",
"if isinstance(self.resource, list):\n self.parse_resource(self.resource, 'default')\nelif isinstance(self.resource, dict):\n for groupname, hosts_and_vars in self.resource.items():... | <|body_start_0|>
self.loader = self.loader_class()
super().__init__(loader=self.loader)
self.resource = resource
self.dynamic_inventory()
<|end_body_0|>
<|body_start_1|>
if isinstance(self.resource, list):
self.parse_resource(self.resource, 'default')
elif is... | 动态生成Inventory类 | BaseInventory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseInventory:
"""动态生成Inventory类"""
def __init__(self, resource=None):
"""resource的数据格式是一个列表字典，比如： { 'group1':{ "hosts": [{"ip": "10.0.0.0", "port": "22", "username": "root", "password": "pass"}, ...] "group_vars": {"var1", "var2", "var3", ...} } } 如果只传入一个列表，默认改列表内的所有主机属于default组，比如：... | stack_v2_sparse_classes_75kplus_train_066625 | 16,686 | no_license | [
{
"docstring": "resource的数据格式是一个列表字典，比如： { 'group1':{ \"hosts\": [{\"ip\": \"10.0.0.0\", \"port\": \"22\", \"username\": \"root\", \"password\": \"pass\"}, ...] \"group_vars\": {\"var1\", \"var2\", \"var3\", ...} } } 如果只传入一个列表，默认改列表内的所有主机属于default组，比如： [{\"ip\": \"10.0.0.0\", \"port\": \"22\", \"username\": \"r... | 3 | stack_v2_sparse_classes_30k_train_047085 | Implement the Python class `BaseInventory` described below.
Class description:
动态生成Inventory类
Method signatures and docstrings:
- def __init__(self, resource=None): resource的数据格式是一个列表字典，比如： { 'group1':{ "hosts": [{"ip": "10.0.0.0", "port": "22", "username": "root", "password": "pass"}, ...] "group_vars": {"var1", "va... | Implement the Python class `BaseInventory` described below.
Class description:
动态生成Inventory类
Method signatures and docstrings:
- def __init__(self, resource=None): resource的数据格式是一个列表字典，比如： { 'group1':{ "hosts": [{"ip": "10.0.0.0", "port": "22", "username": "root", "password": "pass"}, ...] "group_vars": {"var1", "va... | 04bb7f387633ba8af81148dc73a95c2a6d56a8d1 | <|skeleton|>
class BaseInventory:
"""动态生成Inventory类"""
def __init__(self, resource=None):
"""resource的数据格式是一个列表字典，比如： { 'group1':{ "hosts": [{"ip": "10.0.0.0", "port": "22", "username": "root", "password": "pass"}, ...] "group_vars": {"var1", "var2", "var3", ...} } } 如果只传入一个列表，默认改列表内的所有主机属于default组，比如：... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BaseInventory:
"""动态生成Inventory类"""
def __init__(self, resource=None):
"""resource的数据格式是一个列表字典，比如： { 'group1':{ "hosts": [{"ip": "10.0.0.0", "port": "22", "username": "root", "password": "pass"}, ...] "group_vars": {"var1", "var2", "var3", ...} } } 如果只传入一个列表，默认改列表内的所有主机属于default组，比如： [{"ip": "10.... | the_stack_v2_python_sparse | app/utils/ansible_api_v2.py | Rabbit-st/rabbit | train | 0 |
27eb444023ba78a86999c926b4fd257944e2a312 | [
"if getattr(user, 'is_superuser', False):\n return False\nif not getattr(user, 'is_authenticated', False):\n return True\nis_owner = instance.owner.id == user.id\nis_editor = user.id in [editor.id for editor in instance.authorized_editors.all()]\nis_game_master = user.id in [gm.id for gm in instance.get_parti... | <|body_start_0|>
if getattr(user, 'is_superuser', False):
return False
if not getattr(user, 'is_authenticated', False):
return True
is_owner = instance.owner.id == user.id
is_editor = user.id in [editor.id for editor in instance.authorized_editors.all()]
i... | Serializer for the Handout model. Includes secret content. | HandoutSerializer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HandoutSerializer:
"""Serializer for the Handout model. Includes secret content."""
def should_hide_secrets(user, instance):
"""Determine whether to hide the secret content and private files"""
<|body_0|>
def to_representation(self, instance):
"""Override to acco... | stack_v2_sparse_classes_75kplus_train_066626 | 1,967 | permissive | [
{
"docstring": "Determine whether to hide the secret content and private files",
"name": "should_hide_secrets",
"signature": "def should_hide_secrets(user, instance)"
},
{
"docstring": "Override to account for secret data",
"name": "to_representation",
"signature": "def to_representation... | 2 | stack_v2_sparse_classes_30k_train_000761 | Implement the Python class `HandoutSerializer` described below.
Class description:
Serializer for the Handout model. Includes secret content.
Method signatures and docstrings:
- def should_hide_secrets(user, instance): Determine whether to hide the secret content and private files
- def to_representation(self, instan... | Implement the Python class `HandoutSerializer` described below.
Class description:
Serializer for the Handout model. Includes secret content.
Method signatures and docstrings:
- def should_hide_secrets(user, instance): Determine whether to hide the secret content and private files
- def to_representation(self, instan... | 76a43f48b70c6a4b509c90757d7906689799cc25 | <|skeleton|>
class HandoutSerializer:
"""Serializer for the Handout model. Includes secret content."""
def should_hide_secrets(user, instance):
"""Determine whether to hide the secret content and private files"""
<|body_0|>
def to_representation(self, instance):
"""Override to acco... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class HandoutSerializer:
"""Serializer for the Handout model. Includes secret content."""
def should_hide_secrets(user, instance):
"""Determine whether to hide the secret content and private files"""
if getattr(user, 'is_superuser', False):
return False
if not getattr(user, ... | the_stack_v2_python_sparse | game_mastering/serializers/handout.py | seedwithroot/myth-caster-api | train | 0 |
52863f0e3a17dce398ab62a8519da6e457f840b8 | [
"serialized = []\nif not root:\n return ''\nqueue, q_index, q_cnt = ([root], 0, 1)\nwhile q_cnt > 0:\n curr, q_index, q_cnt = (queue[q_index], q_index + 1, q_cnt - 1)\n if curr is None:\n serialized.append('NULL')\n continue\n serialized.append(str(curr.val))\n queue.append(curr.left)\n... | <|body_start_0|>
serialized = []
if not root:
return ''
queue, q_index, q_cnt = ([root], 0, 1)
while q_cnt > 0:
curr, q_index, q_cnt = (queue[q_index], q_index + 1, q_cnt - 1)
if curr is None:
serialized.append('NULL')
c... | 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_066627 | 1,998 | 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_val_002116 | 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:... | 49da8fca3e94cce01f2758b3f42f08b317db044d | <|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"""
serialized = []
if not root:
return ''
queue, q_index, q_cnt = ([root], 0, 1)
while q_cnt > 0:
curr, q_index, q_cnt = (queue[q_index], q_i... | the_stack_v2_python_sparse | Solutions/297 Serialize and Deserialize Binar Tree/Solution2.py | raoqiyu/LeetCode | train | 1 | |
90a51f49ad0ab093a135c5e70c07863e897b30d3 | [
"dp = [0] * (N + 1)\ncnt = 0\nfor i in range(N + 1):\n if i == 0 or i == 1 or i == 8:\n dp[i] = 1\n elif i == 2 or i == 5 or i == 6 or (i == 9):\n dp[i] = 2\n cnt += 1\n else:\n a, b = (dp[i // 10], dp[i % 10])\n if a == 1 and b == 1:\n dp[i] = 1\n elif ... | <|body_start_0|>
dp = [0] * (N + 1)
cnt = 0
for i in range(N + 1):
if i == 0 or i == 1 or i == 8:
dp[i] = 1
elif i == 2 or i == 5 or i == 6 or (i == 9):
dp[i] = 2
cnt += 1
else:
a, b = (dp[i // 10... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rotatedDigits_MK1(self, N: int) -> int:
"""Time complexity: O(n) Space complexity: O(n)"""
<|body_0|>
def rotatedDigits(self, N: int) -> int:
"""Time complexity: O(lgn) Space complexity: O(lgn)"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_066628 | 1,596 | no_license | [
{
"docstring": "Time complexity: O(n) Space complexity: O(n)",
"name": "rotatedDigits_MK1",
"signature": "def rotatedDigits_MK1(self, N: int) -> int"
},
{
"docstring": "Time complexity: O(lgn) Space complexity: O(lgn)",
"name": "rotatedDigits",
"signature": "def rotatedDigits(self, N: in... | 2 | stack_v2_sparse_classes_30k_train_046365 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotatedDigits_MK1(self, N: int) -> int: Time complexity: O(n) Space complexity: O(n)
- def rotatedDigits(self, N: int) -> int: Time complexity: O(lgn) Space complexity: O(lgn... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rotatedDigits_MK1(self, N: int) -> int: Time complexity: O(n) Space complexity: O(n)
- def rotatedDigits(self, N: int) -> int: Time complexity: O(lgn) Space complexity: O(lgn... | d7ba416d22becfa8f2a2ae4eee04c86617cd9332 | <|skeleton|>
class Solution:
def rotatedDigits_MK1(self, N: int) -> int:
"""Time complexity: O(n) Space complexity: O(n)"""
<|body_0|>
def rotatedDigits(self, N: int) -> int:
"""Time complexity: O(lgn) Space complexity: O(lgn)"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def rotatedDigits_MK1(self, N: int) -> int:
"""Time complexity: O(n) Space complexity: O(n)"""
dp = [0] * (N + 1)
cnt = 0
for i in range(N + 1):
if i == 0 or i == 1 or i == 8:
dp[i] = 1
elif i == 2 or i == 5 or i == 6 or (i == 9... | the_stack_v2_python_sparse | 0788. Rotated Digits/Solution.py | faterazer/LeetCode | train | 4 | |
44eb49d4a90b58cc8112aec5c115d04556fb898f | [
"self.safe_update(**kwargs)\nif butler is not None:\n self.log.warn('Ignoring butler')\nif not self.config.skip:\n outtable = vstack_tables(data, tablename='ptc_stats')\ndtables = TableDict()\ndtables.add_datatable('ptc_sum', outtable)\ndtables.make_datatable('runs', dict(runs=sorted(data.keys())))\nreturn dt... | <|body_start_0|>
self.safe_update(**kwargs)
if butler is not None:
self.log.warn('Ignoring butler')
if not self.config.skip:
outtable = vstack_tables(data, tablename='ptc_stats')
dtables = TableDict()
dtables.add_datatable('ptc_sum', outtable)
dtab... | Summarize the results for the analysis of variations of the photon transfer curves frames | PTCSummaryTask | [
"BSD-2-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PTCSummaryTask:
"""Summarize the results for the analysis of variations of the photon transfer curves frames"""
def extract(self, butler, data, **kwargs):
"""Extract the summary data from the PTC analyses Parameters ---------- butler : `Butler` The data butler data : `dict` Dictionar... | stack_v2_sparse_classes_75kplus_train_066629 | 13,776 | permissive | [
{
"docstring": "Extract the summary data from the PTC analyses Parameters ---------- butler : `Butler` The data butler data : `dict` Dictionary (or other structure) contain the input data kwargs Used to override default configuration Returns ------- dtables : `TableDict` The resulting data",
"name": "extrac... | 2 | stack_v2_sparse_classes_30k_train_018333 | Implement the Python class `PTCSummaryTask` described below.
Class description:
Summarize the results for the analysis of variations of the photon transfer curves frames
Method signatures and docstrings:
- def extract(self, butler, data, **kwargs): Extract the summary data from the PTC analyses Parameters ---------- ... | Implement the Python class `PTCSummaryTask` described below.
Class description:
Summarize the results for the analysis of variations of the photon transfer curves frames
Method signatures and docstrings:
- def extract(self, butler, data, **kwargs): Extract the summary data from the PTC analyses Parameters ---------- ... | 28418284fdaf2b2fb0afbeccd4324f7ad3e676c8 | <|skeleton|>
class PTCSummaryTask:
"""Summarize the results for the analysis of variations of the photon transfer curves frames"""
def extract(self, butler, data, **kwargs):
"""Extract the summary data from the PTC analyses Parameters ---------- butler : `Butler` The data butler data : `dict` Dictionar... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PTCSummaryTask:
"""Summarize the results for the analysis of variations of the photon transfer curves frames"""
def extract(self, butler, data, **kwargs):
"""Extract the summary data from the PTC analyses Parameters ---------- butler : `Butler` The data butler data : `dict` Dictionary (or other s... | the_stack_v2_python_sparse | python/lsst/eo_utils/flat/ptc.py | lsst-camera-dh/EO-utilities | train | 2 |
fbd56d646930a400bad223587d419ae56059ad6a | [
"if graph.is_directed():\n raise ValueError('the graph is directed')\nself.graph = graph\nfor edge in self.graph.iteredges():\n if edge.source == edge.target:\n raise ValueError('a loop detected')\nself.independent_set = dict(((node, True) for node in self.graph.iternodes()))\nself.cardinality = self.g... | <|body_start_0|>
if graph.is_directed():
raise ValueError('the graph is directed')
self.graph = graph
for edge in self.graph.iteredges():
if edge.source == edge.target:
raise ValueError('a loop detected')
self.independent_set = dict(((node, True) f... | Find a maximal independent set. | LargestLastIndependentSet2 | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LargestLastIndependentSet2:
"""Find a maximal independent set."""
def __init__(self, graph):
"""The algorithm initialization."""
<|body_0|>
def run(self, source=None):
"""Executable pseudocode."""
<|body_1|>
def _is_independent(self):
"""Inde... | stack_v2_sparse_classes_75kplus_train_066630 | 12,259 | permissive | [
{
"docstring": "The algorithm initialization.",
"name": "__init__",
"signature": "def __init__(self, graph)"
},
{
"docstring": "Executable pseudocode.",
"name": "run",
"signature": "def run(self, source=None)"
},
{
"docstring": "Independence test.",
"name": "_is_independent",... | 3 | stack_v2_sparse_classes_30k_train_021211 | Implement the Python class `LargestLastIndependentSet2` described below.
Class description:
Find a maximal independent set.
Method signatures and docstrings:
- def __init__(self, graph): The algorithm initialization.
- def run(self, source=None): Executable pseudocode.
- def _is_independent(self): Independence test. | Implement the Python class `LargestLastIndependentSet2` described below.
Class description:
Find a maximal independent set.
Method signatures and docstrings:
- def __init__(self, graph): The algorithm initialization.
- def run(self, source=None): Executable pseudocode.
- def _is_independent(self): Independence test.
... | 0ff4ae303e8824e6bb8474d23b29a7b3e5ed8e60 | <|skeleton|>
class LargestLastIndependentSet2:
"""Find a maximal independent set."""
def __init__(self, graph):
"""The algorithm initialization."""
<|body_0|>
def run(self, source=None):
"""Executable pseudocode."""
<|body_1|>
def _is_independent(self):
"""Inde... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LargestLastIndependentSet2:
"""Find a maximal independent set."""
def __init__(self, graph):
"""The algorithm initialization."""
if graph.is_directed():
raise ValueError('the graph is directed')
self.graph = graph
for edge in self.graph.iteredges():
... | the_stack_v2_python_sparse | graphtheory/independentsets/isetll.py | kgashok/graphs-dict | train | 0 |
a2f227a6ebc857f96ccb2e45570b7ca7ec431079 | [
"super().__init__(productcode, description, marketprice, rentalprice)\nself.productcode = productcode\nself.description = description\nself.marketprice = marketprice\nself.rentalprice = rentalprice\nself.brand = brand\nself.voltage = voltage",
"outputdict = {}\noutputdict['productcode'] = self.productcode\noutput... | <|body_start_0|>
super().__init__(productcode, description, marketprice, rentalprice)
self.productcode = productcode
self.description = description
self.marketprice = marketprice
self.rentalprice = rentalprice
self.brand = brand
self.voltage = voltage
<|end_body_0... | Class docstring | Electricappliances | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Electricappliances:
"""Class docstring"""
def __init__(self, productcode, description, marketprice, rentalprice, brand, voltage):
"""initializing variables"""
<|body_0|>
def returnasdictionary(self):
"""method docstring"""
<|body_1|>
<|end_skeleton|>
<|... | stack_v2_sparse_classes_75kplus_train_066631 | 1,134 | no_license | [
{
"docstring": "initializing variables",
"name": "__init__",
"signature": "def __init__(self, productcode, description, marketprice, rentalprice, brand, voltage)"
},
{
"docstring": "method docstring",
"name": "returnasdictionary",
"signature": "def returnasdictionary(self)"
}
] | 2 | stack_v2_sparse_classes_30k_val_002823 | Implement the Python class `Electricappliances` described below.
Class description:
Class docstring
Method signatures and docstrings:
- def __init__(self, productcode, description, marketprice, rentalprice, brand, voltage): initializing variables
- def returnasdictionary(self): method docstring | Implement the Python class `Electricappliances` described below.
Class description:
Class docstring
Method signatures and docstrings:
- def __init__(self, productcode, description, marketprice, rentalprice, brand, voltage): initializing variables
- def returnasdictionary(self): method docstring
<|skeleton|>
class El... | ac12beeae8aa57135bbcd03ac7a4f977fa3bdb56 | <|skeleton|>
class Electricappliances:
"""Class docstring"""
def __init__(self, productcode, description, marketprice, rentalprice, brand, voltage):
"""initializing variables"""
<|body_0|>
def returnasdictionary(self):
"""method docstring"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Electricappliances:
"""Class docstring"""
def __init__(self, productcode, description, marketprice, rentalprice, brand, voltage):
"""initializing variables"""
super().__init__(productcode, description, marketprice, rentalprice)
self.productcode = productcode
self.descripti... | the_stack_v2_python_sparse | students/Daniel_Carrasco/lesson01/assignment/inventory_management/electricAppliancesClass.py | UWPCE-PythonCert-ClassRepos/py220-online-201904-V2 | train | 1 |
18099e29558d9db2e8d09fe8786733c6a3a884c6 | [
"super(DQNModel, self).__init__()\nself.device = device\nself.conv_1 = nn.Conv2d(in_channels=in_channels, out_channels=32, kernel_size=8, stride=4)\nself.conv_2 = nn.Conv2d(in_channels=32, out_channels=64, kernel_size=4, stride=2)\nself.conv_3 = nn.Conv2d(in_channels=64, out_channels=64, kernel_size=3, stride=1)\ns... | <|body_start_0|>
super(DQNModel, self).__init__()
self.device = device
self.conv_1 = nn.Conv2d(in_channels=in_channels, out_channels=32, kernel_size=8, stride=4)
self.conv_2 = nn.Conv2d(in_channels=32, out_channels=64, kernel_size=4, stride=2)
self.conv_3 = nn.Conv2d(in_channels=... | DQNModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DQNModel:
def __init__(self, nr_actions, device, in_channels=4):
""":param in_channels: :param nr_actions: :param device:"""
<|body_0|>
def forward(self, state):
""":param state: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(DQNMode... | stack_v2_sparse_classes_75kplus_train_066632 | 19,004 | no_license | [
{
"docstring": ":param in_channels: :param nr_actions: :param device:",
"name": "__init__",
"signature": "def __init__(self, nr_actions, device, in_channels=4)"
},
{
"docstring": ":param state: :return:",
"name": "forward",
"signature": "def forward(self, state)"
}
] | 2 | stack_v2_sparse_classes_30k_val_002720 | Implement the Python class `DQNModel` described below.
Class description:
Implement the DQNModel class.
Method signatures and docstrings:
- def __init__(self, nr_actions, device, in_channels=4): :param in_channels: :param nr_actions: :param device:
- def forward(self, state): :param state: :return: | Implement the Python class `DQNModel` described below.
Class description:
Implement the DQNModel class.
Method signatures and docstrings:
- def __init__(self, nr_actions, device, in_channels=4): :param in_channels: :param nr_actions: :param device:
- def forward(self, state): :param state: :return:
<|skeleton|>
clas... | 375633b9dc34302fa1d806a7ee69c86f97f1054d | <|skeleton|>
class DQNModel:
def __init__(self, nr_actions, device, in_channels=4):
""":param in_channels: :param nr_actions: :param device:"""
<|body_0|>
def forward(self, state):
""":param state: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DQNModel:
def __init__(self, nr_actions, device, in_channels=4):
""":param in_channels: :param nr_actions: :param device:"""
super(DQNModel, self).__init__()
self.device = device
self.conv_1 = nn.Conv2d(in_channels=in_channels, out_channels=32, kernel_size=8, stride=4)
... | the_stack_v2_python_sparse | models/models.py | kessi1990/masterthesis | train | 1 | |
c015f7d1cb7f3ef62db3471c6959cb6cb2750a4b | [
"super(GateUnit, self).__init__()\nself.conv1 = nn.Conv2d(out_feat, in_feat, kernel_size=3, padding=1, stride=1, bias=False)\nself.bn1 = nn.BatchNorm2d(in_feat)\nself.relu1 = nn.ReLU(inplace=True)\nself.conv2 = nn.Conv2d(in_feat, in_feat, kernel_size=3, padding=1, stride=1, bias=False)\nself.bn2 = nn.BatchNorm2d(in... | <|body_start_0|>
super(GateUnit, self).__init__()
self.conv1 = nn.Conv2d(out_feat, in_feat, kernel_size=3, padding=1, stride=1, bias=False)
self.bn1 = nn.BatchNorm2d(in_feat)
self.relu1 = nn.ReLU(inplace=True)
self.conv2 = nn.Conv2d(in_feat, in_feat, kernel_size=3, padding=1, str... | GateUnit | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GateUnit:
def __init__(self, in_feat, out_feat):
"""First is a smaller feature and second is a larger feature"""
<|body_0|>
def forward(self, x1, x2):
"""x1 is smaller feature map"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
super(GateUnit, self)... | stack_v2_sparse_classes_75kplus_train_066633 | 29,670 | no_license | [
{
"docstring": "First is a smaller feature and second is a larger feature",
"name": "__init__",
"signature": "def __init__(self, in_feat, out_feat)"
},
{
"docstring": "x1 is smaller feature map",
"name": "forward",
"signature": "def forward(self, x1, x2)"
}
] | 2 | stack_v2_sparse_classes_30k_train_014246 | Implement the Python class `GateUnit` described below.
Class description:
Implement the GateUnit class.
Method signatures and docstrings:
- def __init__(self, in_feat, out_feat): First is a smaller feature and second is a larger feature
- def forward(self, x1, x2): x1 is smaller feature map | Implement the Python class `GateUnit` described below.
Class description:
Implement the GateUnit class.
Method signatures and docstrings:
- def __init__(self, in_feat, out_feat): First is a smaller feature and second is a larger feature
- def forward(self, x1, x2): x1 is smaller feature map
<|skeleton|>
class GateUn... | 23ab1cbe8a1e3f9d68ef774a51ce23eeff81aea9 | <|skeleton|>
class GateUnit:
def __init__(self, in_feat, out_feat):
"""First is a smaller feature and second is a larger feature"""
<|body_0|>
def forward(self, x1, x2):
"""x1 is smaller feature map"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GateUnit:
def __init__(self, in_feat, out_feat):
"""First is a smaller feature and second is a larger feature"""
super(GateUnit, self).__init__()
self.conv1 = nn.Conv2d(out_feat, in_feat, kernel_size=3, padding=1, stride=1, bias=False)
self.bn1 = nn.BatchNorm2d(in_feat)
... | the_stack_v2_python_sparse | refinenet.py | JunhongXu/kaggle-carvana-car-masking | train | 1 | |
1a77a9303e4409fcd63876798322549aa828af96 | [
"super(GraspSensorSimulator, self).__init__()\npackage_path = rospkg.RosPack().get_path('test_tools')\nui_filename = os.path.join(package_path, 'resource', 'grasp_sensor.ui')\nloadUi(ui_filename, self)\nself.left_slider.valueChanged.connect(self.left_indicator.display)\nself.right_slider.valueChanged.connect(self.r... | <|body_start_0|>
super(GraspSensorSimulator, self).__init__()
package_path = rospkg.RosPack().get_path('test_tools')
ui_filename = os.path.join(package_path, 'resource', 'grasp_sensor.ui')
loadUi(ui_filename, self)
self.left_slider.valueChanged.connect(self.left_indicator.display... | QWidget to simulate the distance sensors on the grippers | GraspSensorSimulator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GraspSensorSimulator:
"""QWidget to simulate the distance sensors on the grippers"""
def __init__(self, robot_name):
"""Constructor :param robot_name: string with robot name"""
<|body_0|>
def _publish_values(self):
"""Publishes the current sensor values (converte... | stack_v2_sparse_classes_75kplus_train_066634 | 2,775 | no_license | [
{
"docstring": "Constructor :param robot_name: string with robot name",
"name": "__init__",
"signature": "def __init__(self, robot_name)"
},
{
"docstring": "Publishes the current sensor values (converted from mm to m)",
"name": "_publish_values",
"signature": "def _publish_values(self)"
... | 2 | stack_v2_sparse_classes_30k_train_035321 | Implement the Python class `GraspSensorSimulator` described below.
Class description:
QWidget to simulate the distance sensors on the grippers
Method signatures and docstrings:
- def __init__(self, robot_name): Constructor :param robot_name: string with robot name
- def _publish_values(self): Publishes the current se... | Implement the Python class `GraspSensorSimulator` described below.
Class description:
QWidget to simulate the distance sensors on the grippers
Method signatures and docstrings:
- def __init__(self, robot_name): Constructor :param robot_name: string with robot name
- def _publish_values(self): Publishes the current se... | 092a354315b9b2c08e32cdc049791d82dfd47745 | <|skeleton|>
class GraspSensorSimulator:
"""QWidget to simulate the distance sensors on the grippers"""
def __init__(self, robot_name):
"""Constructor :param robot_name: string with robot name"""
<|body_0|>
def _publish_values(self):
"""Publishes the current sensor values (converte... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GraspSensorSimulator:
"""QWidget to simulate the distance sensors on the grippers"""
def __init__(self, robot_name):
"""Constructor :param robot_name: string with robot name"""
super(GraspSensorSimulator, self).__init__()
package_path = rospkg.RosPack().get_path('test_tools')
... | the_stack_v2_python_sparse | test_tools/scripts/grasp-sensor-sim | tue-robotics/tue_robocup | train | 39 |
2e764bb05e37ef38e6a6be032a292111d2edaef8 | [
"if n == 1:\n return '1'\ni = 1\nret = '1'\nwhile i < n:\n i += 1\n pre_ret = ret\n pre_c = pre_ret[0]\n cnt = 1\n ret = ''\n for c in pre_ret[1:]:\n if c == pre_c:\n cnt += 1\n else:\n ret += f'{cnt}{pre_c}'\n pre_c = c\n cnt = 1\n r... | <|body_start_0|>
if n == 1:
return '1'
i = 1
ret = '1'
while i < n:
i += 1
pre_ret = ret
pre_c = pre_ret[0]
cnt = 1
ret = ''
for c in pre_ret[1:]:
if c == pre_c:
cnt +=... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def countAndSay2(self, n: int) -> str:
"""CREATED AT: 2022/2/15 30 / 30 test cases passed. Status: Accepted Runtime: 40 ms, faster than 94.24% Memory Usage: 14 MB, less than 78.47% 1 <= n <= 30"""
<|body_0|>
def countAndSay(self, n):
""":type n: int :rtype:... | stack_v2_sparse_classes_75kplus_train_066635 | 1,775 | permissive | [
{
"docstring": "CREATED AT: 2022/2/15 30 / 30 test cases passed. Status: Accepted Runtime: 40 ms, faster than 94.24% Memory Usage: 14 MB, less than 78.47% 1 <= n <= 30",
"name": "countAndSay2",
"signature": "def countAndSay2(self, n: int) -> str"
},
{
"docstring": ":type n: int :rtype: str",
... | 2 | stack_v2_sparse_classes_30k_train_023878 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countAndSay2(self, n: int) -> str: CREATED AT: 2022/2/15 30 / 30 test cases passed. Status: Accepted Runtime: 40 ms, faster than 94.24% Memory Usage: 14 MB, less than 78.47% ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def countAndSay2(self, n: int) -> str: CREATED AT: 2022/2/15 30 / 30 test cases passed. Status: Accepted Runtime: 40 ms, faster than 94.24% Memory Usage: 14 MB, less than 78.47% ... | 4dd1e54d8d08f7e6590bc76abd08ecaacaf775e5 | <|skeleton|>
class Solution:
def countAndSay2(self, n: int) -> str:
"""CREATED AT: 2022/2/15 30 / 30 test cases passed. Status: Accepted Runtime: 40 ms, faster than 94.24% Memory Usage: 14 MB, less than 78.47% 1 <= n <= 30"""
<|body_0|>
def countAndSay(self, n):
""":type n: int :rtype:... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def countAndSay2(self, n: int) -> str:
"""CREATED AT: 2022/2/15 30 / 30 test cases passed. Status: Accepted Runtime: 40 ms, faster than 94.24% Memory Usage: 14 MB, less than 78.47% 1 <= n <= 30"""
if n == 1:
return '1'
i = 1
ret = '1'
while i < n:
... | the_stack_v2_python_sparse | src/38-CountAndSay.py | Jiezhi/myleetcode | train | 1 | |
6c108f0f76fab42b28f5bf6422b5f77b3088d2c7 | [
"x, y = (x.reshape(-1, 1), y.reshape(-1, 1))\nassert x.shape == y.shape, 'Input should have the same shape.'\nreturn np.sqrt(np.sum(np.square(x - y)))",
"x, y = (x.reshape(-1, 1), y.reshape(-1, 1))\nassert x.shape == y.shape, 'Input should have the same shape.'\nreturn np.sum(np.abs(x - y))",
"x, y = (x.reshape... | <|body_start_0|>
x, y = (x.reshape(-1, 1), y.reshape(-1, 1))
assert x.shape == y.shape, 'Input should have the same shape.'
return np.sqrt(np.sum(np.square(x - y)))
<|end_body_0|>
<|body_start_1|>
x, y = (x.reshape(-1, 1), y.reshape(-1, 1))
assert x.shape == y.shape, 'Input shou... | All calculation are accelerated using not-just-in-time compilation Distance measure between two vectors including: (1) Euclidean distance (2) Manhattan distance (3) Chebyshev distance (4) Minkowski distance (5) Cosine distance | Distance | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Distance:
"""All calculation are accelerated using not-just-in-time compilation Distance measure between two vectors including: (1) Euclidean distance (2) Manhattan distance (3) Chebyshev distance (4) Minkowski distance (5) Cosine distance"""
def euclidean(x: np.ndarray, y: np.ndarray) -> Un... | stack_v2_sparse_classes_75kplus_train_066636 | 2,299 | no_license | [
{
"docstring": "D(x, y) = sqrt[sum_i (x_i - y_i)^2]",
"name": "euclidean",
"signature": "def euclidean(x: np.ndarray, y: np.ndarray) -> Union[float, np.ndarray]"
},
{
"docstring": "D(x, y) = sum_i (|x_i - y_i|)",
"name": "manhattan",
"signature": "def manhattan(x: np.ndarray, y: np.ndarr... | 5 | stack_v2_sparse_classes_30k_val_001379 | Implement the Python class `Distance` described below.
Class description:
All calculation are accelerated using not-just-in-time compilation Distance measure between two vectors including: (1) Euclidean distance (2) Manhattan distance (3) Chebyshev distance (4) Minkowski distance (5) Cosine distance
Method signatures... | Implement the Python class `Distance` described below.
Class description:
All calculation are accelerated using not-just-in-time compilation Distance measure between two vectors including: (1) Euclidean distance (2) Manhattan distance (3) Chebyshev distance (4) Minkowski distance (5) Cosine distance
Method signatures... | 1e0857872f6f97056eed4151b0870afec2d4b34e | <|skeleton|>
class Distance:
"""All calculation are accelerated using not-just-in-time compilation Distance measure between two vectors including: (1) Euclidean distance (2) Manhattan distance (3) Chebyshev distance (4) Minkowski distance (5) Cosine distance"""
def euclidean(x: np.ndarray, y: np.ndarray) -> Un... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Distance:
"""All calculation are accelerated using not-just-in-time compilation Distance measure between two vectors including: (1) Euclidean distance (2) Manhattan distance (3) Chebyshev distance (4) Minkowski distance (5) Cosine distance"""
def euclidean(x: np.ndarray, y: np.ndarray) -> Union[float, np... | the_stack_v2_python_sparse | StatisticalLearning/Feature/Distance.py | resummerring/StatisticalLearning | train | 0 |
25d4b8e14d01ece3538c8ec8280c09fcdb4de6b0 | [
"args = get_comment_parser.find_parser.parse_args()\ncomments = CommentModelWorker.get_all_comments(args['get_field'], args['author'], args['article'], args['limit'], args['offset'])\nif 'image' in args['get_field']:\n for comment in comments:\n if comment['image'] is not None:\n comment['image... | <|body_start_0|>
args = get_comment_parser.find_parser.parse_args()
comments = CommentModelWorker.get_all_comments(args['get_field'], args['author'], args['article'], args['limit'], args['offset'])
if 'image' in args['get_field']:
for comment in comments:
if comment['... | Ресурс для взаимодействия с комментариями через API | CommentsListResource | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommentsListResource:
"""Ресурс для взаимодействия с комментариями через API"""
def get(self):
"""Получение списка комментариев"""
<|body_0|>
def post(self):
"""Добавление комментария"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
args = get_co... | stack_v2_sparse_classes_75kplus_train_066637 | 4,217 | no_license | [
{
"docstring": "Получение списка комментариев",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "Добавление комментария",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_047775 | Implement the Python class `CommentsListResource` described below.
Class description:
Ресурс для взаимодействия с комментариями через API
Method signatures and docstrings:
- def get(self): Получение списка комментариев
- def post(self): Добавление комментария | Implement the Python class `CommentsListResource` described below.
Class description:
Ресурс для взаимодействия с комментариями через API
Method signatures and docstrings:
- def get(self): Получение списка комментариев
- def post(self): Добавление комментария
<|skeleton|>
class CommentsListResource:
"""Ресурс дл... | 1bc59640f13ae4fe6582bb10c9093ff3d671aeb1 | <|skeleton|>
class CommentsListResource:
"""Ресурс для взаимодействия с комментариями через API"""
def get(self):
"""Получение списка комментариев"""
<|body_0|>
def post(self):
"""Добавление комментария"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CommentsListResource:
"""Ресурс для взаимодействия с комментариями через API"""
def get(self):
"""Получение списка комментариев"""
args = get_comment_parser.find_parser.parse_args()
comments = CommentModelWorker.get_all_comments(args['get_field'], args['author'], args['article'], ... | the_stack_v2_python_sparse | resources/comments.py | KosenokIvan/articles_website | train | 1 |
5d755d25a57408a713ea354bad709ec6e61f0c12 | [
"super(Discriminator, self).__init__()\nself.conv_dim = conv_dim\nself.conv1 = conv(3, conv_dim, 4, batch_norm=False)\nself.conv2 = conv(conv_dim, conv_dim * 2, 4)\nself.conv3 = conv(conv_dim * 2, conv_dim * 4, 4)\nself.fc = nn.Linear(conv_dim * 4 * 4 * 4, 1)",
"x = F.leaky_relu(self.conv1(x), 0.2)\nx = F.leaky_r... | <|body_start_0|>
super(Discriminator, self).__init__()
self.conv_dim = conv_dim
self.conv1 = conv(3, conv_dim, 4, batch_norm=False)
self.conv2 = conv(conv_dim, conv_dim * 2, 4)
self.conv3 = conv(conv_dim * 2, conv_dim * 4, 4)
self.fc = nn.Linear(conv_dim * 4 * 4 * 4, 1)
<... | Discriminator | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Discriminator:
def __init__(self, conv_dim=32):
"""Initialize the Discriminator Module :param conv_dim: The depth of the first convolutional layer"""
<|body_0|>
def forward(self, x):
"""Forward propagation of the neural network :param x: The input to the neural netwo... | stack_v2_sparse_classes_75kplus_train_066638 | 12,896 | permissive | [
{
"docstring": "Initialize the Discriminator Module :param conv_dim: The depth of the first convolutional layer",
"name": "__init__",
"signature": "def __init__(self, conv_dim=32)"
},
{
"docstring": "Forward propagation of the neural network :param x: The input to the neural network :return: Dis... | 2 | stack_v2_sparse_classes_30k_train_039227 | Implement the Python class `Discriminator` described below.
Class description:
Implement the Discriminator class.
Method signatures and docstrings:
- def __init__(self, conv_dim=32): Initialize the Discriminator Module :param conv_dim: The depth of the first convolutional layer
- def forward(self, x): Forward propaga... | Implement the Python class `Discriminator` described below.
Class description:
Implement the Discriminator class.
Method signatures and docstrings:
- def __init__(self, conv_dim=32): Initialize the Discriminator Module :param conv_dim: The depth of the first convolutional layer
- def forward(self, x): Forward propaga... | b9b54564f94aadfc3c71ff513da0f05ef85d22a8 | <|skeleton|>
class Discriminator:
def __init__(self, conv_dim=32):
"""Initialize the Discriminator Module :param conv_dim: The depth of the first convolutional layer"""
<|body_0|>
def forward(self, x):
"""Forward propagation of the neural network :param x: The input to the neural netwo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Discriminator:
def __init__(self, conv_dim=32):
"""Initialize the Discriminator Module :param conv_dim: The depth of the first convolutional layer"""
super(Discriminator, self).__init__()
self.conv_dim = conv_dim
self.conv1 = conv(3, conv_dim, 4, batch_norm=False)
self.... | the_stack_v2_python_sparse | dl/pytorch/gan/face_gan.py | xta0/Python-Playground | train | 0 | |
86dd948bcd9ed9c93f4cb52026e7f4cf37afc639 | [
"try:\n self.access_token = os.environ['DROPBOX_TOKEN']\n self.dropbox = dropbox.Dropbox(self.access_token)\nexcept Exception as e:\n raise InvalidCredentialsError(e)",
"folder_path = '/' + folder_name\ncheck_if_folder_exist = self.dropbox.files_search(path='', query=self.folder_name)\nif check_if_folder... | <|body_start_0|>
try:
self.access_token = os.environ['DROPBOX_TOKEN']
self.dropbox = dropbox.Dropbox(self.access_token)
except Exception as e:
raise InvalidCredentialsError(e)
<|end_body_0|>
<|body_start_1|>
folder_path = '/' + folder_name
check_if_fo... | Entree Drop Box library. Storage for entree videos. | EntreeStorage | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EntreeStorage:
"""Entree Drop Box library. Storage for entree videos."""
def __init__(self):
"""class instantiated with a dropbox token raise authentication error if token doesnt exist"""
<|body_0|>
def create_folder(self, folder_name):
"""Organisation is key. Al... | stack_v2_sparse_classes_75kplus_train_066639 | 3,491 | no_license | [
{
"docstring": "class instantiated with a dropbox token raise authentication error if token doesnt exist",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Organisation is key. All tutorial should be properly organised in their various folder",
"name": "create_folder"... | 5 | stack_v2_sparse_classes_30k_train_049061 | Implement the Python class `EntreeStorage` described below.
Class description:
Entree Drop Box library. Storage for entree videos.
Method signatures and docstrings:
- def __init__(self): class instantiated with a dropbox token raise authentication error if token doesnt exist
- def create_folder(self, folder_name): Or... | Implement the Python class `EntreeStorage` described below.
Class description:
Entree Drop Box library. Storage for entree videos.
Method signatures and docstrings:
- def __init__(self): class instantiated with a dropbox token raise authentication error if token doesnt exist
- def create_folder(self, folder_name): Or... | 5ab50cc7cccb972edd0e54812aa15e451c9aceba | <|skeleton|>
class EntreeStorage:
"""Entree Drop Box library. Storage for entree videos."""
def __init__(self):
"""class instantiated with a dropbox token raise authentication error if token doesnt exist"""
<|body_0|>
def create_folder(self, folder_name):
"""Organisation is key. Al... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EntreeStorage:
"""Entree Drop Box library. Storage for entree videos."""
def __init__(self):
"""class instantiated with a dropbox token raise authentication error if token doesnt exist"""
try:
self.access_token = os.environ['DROPBOX_TOKEN']
self.dropbox = dropbox.D... | the_stack_v2_python_sparse | application/modules/core/utils/entree_box.py | segedy01/churner | train | 0 |
41696d2af141e5ef644877111d98320e84366192 | [
"try:\n if not authCheck(['12', '515400'], requests.session.get('login')):\n return JsonResponse({'status': False, 'err': '你没有权限'}, status=401)\n param = requests.body\n jsonParams = json.loads(param)\n user = getUser(requests.session.get('login'))\n if Classification.objects.filter(name__exac... | <|body_start_0|>
try:
if not authCheck(['12', '515400'], requests.session.get('login')):
return JsonResponse({'status': False, 'err': '你没有权限'}, status=401)
param = requests.body
jsonParams = json.loads(param)
user = getUser(requests.session.get('lo... | CommodityClassificationView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CommodityClassificationView:
def post(self, requests):
"""新增商品分类 :param requests: :return:"""
<|body_0|>
def get(self, requests):
"""获取商品分类列表 :param requests: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
if not authCheck... | stack_v2_sparse_classes_75kplus_train_066640 | 2,063 | no_license | [
{
"docstring": "新增商品分类 :param requests: :return:",
"name": "post",
"signature": "def post(self, requests)"
},
{
"docstring": "获取商品分类列表 :param requests: :return:",
"name": "get",
"signature": "def get(self, requests)"
}
] | 2 | stack_v2_sparse_classes_30k_train_051820 | Implement the Python class `CommodityClassificationView` described below.
Class description:
Implement the CommodityClassificationView class.
Method signatures and docstrings:
- def post(self, requests): 新增商品分类 :param requests: :return:
- def get(self, requests): 获取商品分类列表 :param requests: :return: | Implement the Python class `CommodityClassificationView` described below.
Class description:
Implement the CommodityClassificationView class.
Method signatures and docstrings:
- def post(self, requests): 新增商品分类 :param requests: :return:
- def get(self, requests): 获取商品分类列表 :param requests: :return:
<|skeleton|>
class... | 526dea540048fc92260bce611c520c50af744e0b | <|skeleton|>
class CommodityClassificationView:
def post(self, requests):
"""新增商品分类 :param requests: :return:"""
<|body_0|>
def get(self, requests):
"""获取商品分类列表 :param requests: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CommodityClassificationView:
def post(self, requests):
"""新增商品分类 :param requests: :return:"""
try:
if not authCheck(['12', '515400'], requests.session.get('login')):
return JsonResponse({'status': False, 'err': '你没有权限'}, status=401)
param = requests.body... | the_stack_v2_python_sparse | apps/market/views/classification/ClassificationInfo.py | DICKQI/ALGYunXS | train | 0 | |
2512e0e6376f2dca1602fda07c7e6c85e7553b5e | [
"parser.add_argument('log_name', help='The name of the log where the log entry will be written.')\nparser.add_argument('message', help='The message to put in the log entry. It can be JSON if you include --payload-type=json.')\nparser.add_argument('--payload-type', choices=Write.PAYLOAD_TYPE, default='text', help='T... | <|body_start_0|>
parser.add_argument('log_name', help='The name of the log where the log entry will be written.')
parser.add_argument('message', help='The message to put in the log entry. It can be JSON if you include --payload-type=json.')
parser.add_argument('--payload-type', choices=Write.PAY... | Writes a log entry. | Write | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Write:
"""Writes a log entry."""
def Args(parser):
"""Register flags for this command."""
<|body_0|>
def Run(self, args):
"""This is what gets called when the user runs this command. Args: args: an argparse namespace. All the arguments that were provided to this ... | stack_v2_sparse_classes_75kplus_train_066641 | 4,144 | permissive | [
{
"docstring": "Register flags for this command.",
"name": "Args",
"signature": "def Args(parser)"
},
{
"docstring": "This is what gets called when the user runs this command. Args: args: an argparse namespace. All the arguments that were provided to this command invocation.",
"name": "Run",... | 2 | null | Implement the Python class `Write` described below.
Class description:
Writes a log entry.
Method signatures and docstrings:
- def Args(parser): Register flags for this command.
- def Run(self, args): This is what gets called when the user runs this command. Args: args: an argparse namespace. All the arguments that w... | Implement the Python class `Write` described below.
Class description:
Writes a log entry.
Method signatures and docstrings:
- def Args(parser): Register flags for this command.
- def Run(self, args): This is what gets called when the user runs this command. Args: args: an argparse namespace. All the arguments that w... | c98b58aeb0994e011df960163541e9379ae7ea06 | <|skeleton|>
class Write:
"""Writes a log entry."""
def Args(parser):
"""Register flags for this command."""
<|body_0|>
def Run(self, args):
"""This is what gets called when the user runs this command. Args: args: an argparse namespace. All the arguments that were provided to this ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Write:
"""Writes a log entry."""
def Args(parser):
"""Register flags for this command."""
parser.add_argument('log_name', help='The name of the log where the log entry will be written.')
parser.add_argument('message', help='The message to put in the log entry. It can be JSON if yo... | the_stack_v2_python_sparse | google-cloud-sdk/lib/surface/logging/write.py | KaranToor/MA450 | train | 1 |
0f29dfbeb8b6a0df5cb497b266db133252027762 | [
"def backtrack(nums, size, start, path):\n res.append(path[:])\n for i in range(start, size):\n path.append(nums[i])\n backtrack(nums, size, i + 1, path)\n path.pop()\nres = []\nsize = len(nums)\nbacktrack(nums, size, 0, [])\nreturn res",
"if len(nums) == 0:\n return [[]]\nlast = num... | <|body_start_0|>
def backtrack(nums, size, start, path):
res.append(path[:])
for i in range(start, size):
path.append(nums[i])
backtrack(nums, size, i + 1, path)
path.pop()
res = []
size = len(nums)
backtrack(nums, s... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def subsets(self, nums: List[int]) -> List[List[int]]:
"""题解：https://leetcode-cn.com/problems/subsets/solution/c-zong-jie-liao-hui-su-wen-ti-lei-xing-dai-ni-gao-/"""
<|body_0|>
def subsets1(self, nums: List[int]) -> List[List[int]]:
"""数学归纳递归：subset([1,2,3]... | stack_v2_sparse_classes_75kplus_train_066642 | 3,816 | permissive | [
{
"docstring": "题解：https://leetcode-cn.com/problems/subsets/solution/c-zong-jie-liao-hui-su-wen-ti-lei-xing-dai-ni-gao-/",
"name": "subsets",
"signature": "def subsets(self, nums: List[int]) -> List[List[int]]"
},
{
"docstring": "数学归纳递归：subset([1,2,3]) = A + [A[i].add(3) for i = 1..len(A)] https... | 5 | stack_v2_sparse_classes_30k_train_029634 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def subsets(self, nums: List[int]) -> List[List[int]]: 题解：https://leetcode-cn.com/problems/subsets/solution/c-zong-jie-liao-hui-su-wen-ti-lei-xing-dai-ni-gao-/
- def subsets1(sel... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def subsets(self, nums: List[int]) -> List[List[int]]: 题解：https://leetcode-cn.com/problems/subsets/solution/c-zong-jie-liao-hui-su-wen-ti-lei-xing-dai-ni-gao-/
- def subsets1(sel... | e8a1c6cae6547cbcb6e8494be6df685f3e7c837c | <|skeleton|>
class Solution:
def subsets(self, nums: List[int]) -> List[List[int]]:
"""题解：https://leetcode-cn.com/problems/subsets/solution/c-zong-jie-liao-hui-su-wen-ti-lei-xing-dai-ni-gao-/"""
<|body_0|>
def subsets1(self, nums: List[int]) -> List[List[int]]:
"""数学归纳递归：subset([1,2,3]... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def subsets(self, nums: List[int]) -> List[List[int]]:
"""题解：https://leetcode-cn.com/problems/subsets/solution/c-zong-jie-liao-hui-su-wen-ti-lei-xing-dai-ni-gao-/"""
def backtrack(nums, size, start, path):
res.append(path[:])
for i in range(start, size):
... | the_stack_v2_python_sparse | 78-subsets.py | yuenliou/leetcode | train | 0 | |
063be949ac4483b2b6a04ece1dfab82262dabbcc | [
"if not nums:\n return 0\nlength = len(nums)\nif nums[length - 1] < target:\n return length\nif nums[0] >= target:\n return 0\nfor i in range(0, length - 1):\n if nums[i] < target and nums[i + 1] >= target:\n return i + 1\nreturn -1",
"if not nums:\n return 0\nif nums[0] >= target:\n retu... | <|body_start_0|>
if not nums:
return 0
length = len(nums)
if nums[length - 1] < target:
return length
if nums[0] >= target:
return 0
for i in range(0, length - 1):
if nums[i] < target and nums[i + 1] >= target:
retur... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def search_insert(self, nums: List[int], target: int) -> int:
"""返回元素插入位置 Args: nums: 数组 target: 目标值 Returns: 返回需要插入的位置"""
<|body_0|>
def search_insert2(self, nums: List[int], target: int) -> int:
"""返回元素插入位置 Args: nums: 数组 target: 目标值 Returns: 返回需要插入的位置"""... | stack_v2_sparse_classes_75kplus_train_066643 | 3,290 | permissive | [
{
"docstring": "返回元素插入位置 Args: nums: 数组 target: 目标值 Returns: 返回需要插入的位置",
"name": "search_insert",
"signature": "def search_insert(self, nums: List[int], target: int) -> int"
},
{
"docstring": "返回元素插入位置 Args: nums: 数组 target: 目标值 Returns: 返回需要插入的位置",
"name": "search_insert2",
"signature":... | 3 | stack_v2_sparse_classes_30k_train_032785 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def search_insert(self, nums: List[int], target: int) -> int: 返回元素插入位置 Args: nums: 数组 target: 目标值 Returns: 返回需要插入的位置
- def search_insert2(self, nums: List[int], target: int) -> i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def search_insert(self, nums: List[int], target: int) -> int: 返回元素插入位置 Args: nums: 数组 target: 目标值 Returns: 返回需要插入的位置
- def search_insert2(self, nums: List[int], target: int) -> i... | 50f35eef6a0ad63173efed10df3c835b1dceaa3f | <|skeleton|>
class Solution:
def search_insert(self, nums: List[int], target: int) -> int:
"""返回元素插入位置 Args: nums: 数组 target: 目标值 Returns: 返回需要插入的位置"""
<|body_0|>
def search_insert2(self, nums: List[int], target: int) -> int:
"""返回元素插入位置 Args: nums: 数组 target: 目标值 Returns: 返回需要插入的位置"""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def search_insert(self, nums: List[int], target: int) -> int:
"""返回元素插入位置 Args: nums: 数组 target: 目标值 Returns: 返回需要插入的位置"""
if not nums:
return 0
length = len(nums)
if nums[length - 1] < target:
return length
if nums[0] >= target:
... | the_stack_v2_python_sparse | src/leetcodepython/array/search_insert_position_35.py | zhangyu345293721/leetcode | train | 101 | |
370d0f94ff61a18f421e45617d057132a602a760 | [
"helpMessage = 'Exec into the running Docker container'\nargHelp = 'Volume map the working directory onto the container'\nparser = subparsers.add_parser('exec', help=helpMessage)\nparser.add_argument('-m', '--map', action='store_true', help=argHelp)\nreturn subparsers",
"mappings = []\nif args.map:\n mappings.... | <|body_start_0|>
helpMessage = 'Exec into the running Docker container'
argHelp = 'Volume map the working directory onto the container'
parser = subparsers.add_parser('exec', help=helpMessage)
parser.add_argument('-m', '--map', action='store_true', help=argHelp)
return subparsers... | Docker Exec Class Provides a command to access the project container via bash prompt with the option volume map the contents of the project into the container so that they can be modified as root | Dexec | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Dexec:
"""Docker Exec Class Provides a command to access the project container via bash prompt with the option volume map the contents of the project into the container so that they can be modified as root"""
def addParsers(self, subparsers):
"""SkeleParser Hook Adds a parser for the... | stack_v2_sparse_classes_75kplus_train_066644 | 1,545 | permissive | [
{
"docstring": "SkeleParser Hook Adds a parser for the exec command that allows for bash access to the project container along with full project volume mapping support via an optional parameter flag",
"name": "addParsers",
"signature": "def addParsers(self, subparsers)"
},
{
"docstring": "Execut... | 2 | stack_v2_sparse_classes_30k_train_020398 | Implement the Python class `Dexec` described below.
Class description:
Docker Exec Class Provides a command to access the project container via bash prompt with the option volume map the contents of the project into the container so that they can be modified as root
Method signatures and docstrings:
- def addParsers(... | Implement the Python class `Dexec` described below.
Class description:
Docker Exec Class Provides a command to access the project container via bash prompt with the option volume map the contents of the project into the container so that they can be modified as root
Method signatures and docstrings:
- def addParsers(... | c4299702994cdd55738de4591e85f4dc2a424d19 | <|skeleton|>
class Dexec:
"""Docker Exec Class Provides a command to access the project container via bash prompt with the option volume map the contents of the project into the container so that they can be modified as root"""
def addParsers(self, subparsers):
"""SkeleParser Hook Adds a parser for the... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Dexec:
"""Docker Exec Class Provides a command to access the project container via bash prompt with the option volume map the contents of the project into the container so that they can be modified as root"""
def addParsers(self, subparsers):
"""SkeleParser Hook Adds a parser for the exec command... | the_stack_v2_python_sparse | skelebot/components/dexec.py | carsdotcom/skelebot | train | 37 |
91257403a677e0b43a69877e47486942f19b07c4 | [
"self._buf = record\nself.mandatory_header = _unpack_from_buf(self._buf, 0, UF_MANDATORY_HEADER)\nself.optional_header = None\nif self.mandatory_header['offset_optional_header'] != 0:\n offset = (self.mandatory_header['offset_optional_header'] - 1) * 2\n self.optional_header = _unpack_from_buf(self._buf, offs... | <|body_start_0|>
self._buf = record
self.mandatory_header = _unpack_from_buf(self._buf, 0, UF_MANDATORY_HEADER)
self.optional_header = None
if self.mandatory_header['offset_optional_header'] != 0:
offset = (self.mandatory_header['offset_optional_header'] - 1) * 2
... | A class for reading data from a single ray (record) in a UF file. Parameters ---------- record : str Byte string containing the binary data for a UF ray. Attributes ---------- mandatory_header : dic Mandatory header. optional_header : dic or None Optional header or None if no optional header exists in the record. data_... | UFRay | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UFRay:
"""A class for reading data from a single ray (record) in a UF file. Parameters ---------- record : str Byte string containing the binary data for a UF ray. Attributes ---------- mandatory_header : dic Mandatory header. optional_header : dic or None Optional header or None if no optional h... | stack_v2_sparse_classes_75kplus_train_066645 | 19,352 | permissive | [
{
"docstring": "Initalize the object.",
"name": "__init__",
"signature": "def __init__(self, record)"
},
{
"docstring": "Return array of raw data for a particular field in the ray. Field header is appended to the list in the field_headers attribute.",
"name": "get_field_data",
"signature... | 4 | stack_v2_sparse_classes_30k_train_000905 | Implement the Python class `UFRay` described below.
Class description:
A class for reading data from a single ray (record) in a UF file. Parameters ---------- record : str Byte string containing the binary data for a UF ray. Attributes ---------- mandatory_header : dic Mandatory header. optional_header : dic or None O... | Implement the Python class `UFRay` described below.
Class description:
A class for reading data from a single ray (record) in a UF file. Parameters ---------- record : str Byte string containing the binary data for a UF ray. Attributes ---------- mandatory_header : dic Mandatory header. optional_header : dic or None O... | 172bbcf1cf3bcdb953c76ebae72c27c95dc2e606 | <|skeleton|>
class UFRay:
"""A class for reading data from a single ray (record) in a UF file. Parameters ---------- record : str Byte string containing the binary data for a UF ray. Attributes ---------- mandatory_header : dic Mandatory header. optional_header : dic or None Optional header or None if no optional h... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UFRay:
"""A class for reading data from a single ray (record) in a UF file. Parameters ---------- record : str Byte string containing the binary data for a UF ray. Attributes ---------- mandatory_header : dic Mandatory header. optional_header : dic or None Optional header or None if no optional header exists ... | the_stack_v2_python_sparse | pyart/io/uffile.py | ARM-DOE/pyart | train | 455 |
1132e744796fce7f11ab14cb21a3ae2973d69374 | [
"log.info(f\"{'Getting osd configurations'}\")\ncmd = f'ceph config get osd {param}'\nout = super().run_ceph_command(cmd=cmd)\nreturn out",
"cmd = f'ceph config set osd {param} {value}'\nout, err = self.node.shell([cmd])\nactual_value = self.get_osd_configuration(param)\nif actual_value == value:\n log.info(... | <|body_start_0|>
log.info(f"{'Getting osd configurations'}")
cmd = f'ceph config get osd {param}'
out = super().run_ceph_command(cmd=cmd)
return out
<|end_body_0|>
<|body_start_1|>
cmd = f'ceph config set osd {param} {value}'
out, err = self.node.shell([cmd])
a... | RadosScrubber | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RadosScrubber:
def get_osd_configuration(self, param):
"""Used to get the osd parameter value Args: params : Parameter to get the value Returns : parameter value"""
<|body_0|>
def set_osd_configuration(self, param, value):
"""Used to set the configuration parametrs t... | stack_v2_sparse_classes_75kplus_train_066646 | 6,245 | permissive | [
{
"docstring": "Used to get the osd parameter value Args: params : Parameter to get the value Returns : parameter value",
"name": "get_osd_configuration",
"signature": "def get_osd_configuration(self, param)"
},
{
"docstring": "Used to set the configuration parametrs to the OSD's. Args: params :... | 6 | null | Implement the Python class `RadosScrubber` described below.
Class description:
Implement the RadosScrubber class.
Method signatures and docstrings:
- def get_osd_configuration(self, param): Used to get the osd parameter value Args: params : Parameter to get the value Returns : parameter value
- def set_osd_configurat... | Implement the Python class `RadosScrubber` described below.
Class description:
Implement the RadosScrubber class.
Method signatures and docstrings:
- def get_osd_configuration(self, param): Used to get the osd parameter value Args: params : Parameter to get the value Returns : parameter value
- def set_osd_configurat... | 0691fbaf8fca2a9cd051c5049c83758c65301654 | <|skeleton|>
class RadosScrubber:
def get_osd_configuration(self, param):
"""Used to get the osd parameter value Args: params : Parameter to get the value Returns : parameter value"""
<|body_0|>
def set_osd_configuration(self, param, value):
"""Used to set the configuration parametrs t... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RadosScrubber:
def get_osd_configuration(self, param):
"""Used to get the osd parameter value Args: params : Parameter to get the value Returns : parameter value"""
log.info(f"{'Getting osd configurations'}")
cmd = f'ceph config get osd {param}'
out = super().run_ceph_command(... | the_stack_v2_python_sparse | ceph/rados/rados_scrub.py | red-hat-storage/cephci | train | 28 | |
19f3d75afccca7ed2b5fce7e8c3562179220b31d | [
"sig = inspect.signature(cls)\nclskwds = {}\nfor name, param in list(sig.parameters.items()):\n if param.kind in (param.POSITIONAL_OR_KEYWORD, param.KEYWORD_ONLY):\n try:\n clskwds[name] = kwargs.pop(name)\n except KeyError:\n pass\nreturn (cls(*args, **clskwds), kwargs)",
"... | <|body_start_0|>
sig = inspect.signature(cls)
clskwds = {}
for name, param in list(sig.parameters.items()):
if param.kind in (param.POSITIONAL_OR_KEYWORD, param.KEYWORD_ONLY):
try:
clskwds[name] = kwargs.pop(name)
except KeyError:
... | A base class for composable components. This class helps propagating, sharing, and intercepting arguments (initialization parameters) in a unified manner so that classes can pass arguments to their sub-components reliably. For a basic usage, `BaseComponent` only requires its subclass to *not* have keyword arguments (``... | BaseComponent | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseComponent:
"""A base class for composable components. This class helps propagating, sharing, and intercepting arguments (initialization parameters) in a unified manner so that classes can pass arguments to their sub-components reliably. For a basic usage, `BaseComponent` only requires its sub... | stack_v2_sparse_classes_75kplus_train_066647 | 8,935 | permissive | [
{
"docstring": "Instantiate `cls` using a subset of `kwargs` and return the rest. Returns ------- self : cls The result of ``cls(*args, **clskwds)`` where `clskwds` is a subset of `kwargs`. It is determined by the call signature of `cls.__init__`. rest : dict A subset of `kwargs` not used by `cls.__init__`; i.e... | 3 | stack_v2_sparse_classes_30k_train_016232 | Implement the Python class `BaseComponent` described below.
Class description:
A base class for composable components. This class helps propagating, sharing, and intercepting arguments (initialization parameters) in a unified manner so that classes can pass arguments to their sub-components reliably. For a basic usage... | Implement the Python class `BaseComponent` described below.
Class description:
A base class for composable components. This class helps propagating, sharing, and intercepting arguments (initialization parameters) in a unified manner so that classes can pass arguments to their sub-components reliably. For a basic usage... | 06c549e8ae74bc6af62fddeed698565ea1f548c5 | <|skeleton|>
class BaseComponent:
"""A base class for composable components. This class helps propagating, sharing, and intercepting arguments (initialization parameters) in a unified manner so that classes can pass arguments to their sub-components reliably. For a basic usage, `BaseComponent` only requires its sub... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BaseComponent:
"""A base class for composable components. This class helps propagating, sharing, and intercepting arguments (initialization parameters) in a unified manner so that classes can pass arguments to their sub-components reliably. For a basic usage, `BaseComponent` only requires its subclass to *not... | the_stack_v2_python_sparse | tc_gan/core.py | ahmadianlab/tc-gan | train | 4 |
1d33c339a471d73df0253d0cda5ebe5e059f8fc7 | [
"length = len(nums)\nif length > 0:\n maxSoFar = nums[0]\n maxEndingHere = nums[0]\n for i in range(1, length):\n maxEndingHere = max(maxEndingHere + nums[i], nums[i])\n maxSoFar = max(maxSoFar, maxEndingHere)\n return maxSoFar\nelse:\n return 0",
"count = len(nums)\nif count == 0:\n ... | <|body_start_0|>
length = len(nums)
if length > 0:
maxSoFar = nums[0]
maxEndingHere = nums[0]
for i in range(1, length):
maxEndingHere = max(maxEndingHere + nums[i], nums[i])
maxSoFar = max(maxSoFar, maxEndingHere)
return ma... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def maxSubArray_self(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
length = len(nums)
if length > 0... | stack_v2_sparse_classes_75kplus_train_066648 | 896 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "maxSubArray",
"signature": "def maxSubArray(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "maxSubArray_self",
"signature": "def maxSubArray_self(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_053833 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray(self, nums): :type nums: List[int] :rtype: int
- def maxSubArray_self(self, nums): :type nums: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray(self, nums): :type nums: List[int] :rtype: int
- def maxSubArray_self(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def maxSub... | ea492ec864b50547214ecbbb2cdeeac21e70229b | <|skeleton|>
class Solution:
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def maxSubArray_self(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def maxSubArray(self, nums):
""":type nums: List[int] :rtype: int"""
length = len(nums)
if length > 0:
maxSoFar = nums[0]
maxEndingHere = nums[0]
for i in range(1, length):
maxEndingHere = max(maxEndingHere + nums[i], nums[i... | the_stack_v2_python_sparse | 53_maximum_subarray/sol.py | lianke123321/leetcode_sol | train | 0 | |
598a5947b5edcd6e71016e7959d700f4e2e34524 | [
"queryset = get_object_or_404(Upload, pk=pk)\nserializer = UploadSerializer(queryset)\nreturn Response(serializer.data)",
"queryset = get_object_or_404(Upload, pk=pk)\nserializer = UploadSerializer(queryset, data=request.data)\nif serializer.is_valid():\n serializer.save()\n return Response(serializer.data,... | <|body_start_0|>
queryset = get_object_or_404(Upload, pk=pk)
serializer = UploadSerializer(queryset)
return Response(serializer.data)
<|end_body_0|>
<|body_start_1|>
queryset = get_object_or_404(Upload, pk=pk)
serializer = UploadSerializer(queryset, data=request.data)
if... | UploadDetailView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UploadDetailView:
def get(self, request, pk):
"""Lista detalhes de um upload * É preciso estar autenticado para visualizar."""
<|body_0|>
def put(self, request, pk):
"""Altera todos os dados do upload * É preciso estar autenticado para editar."""
<|body_1|>
... | stack_v2_sparse_classes_75kplus_train_066649 | 4,003 | no_license | [
{
"docstring": "Lista detalhes de um upload * É preciso estar autenticado para visualizar.",
"name": "get",
"signature": "def get(self, request, pk)"
},
{
"docstring": "Altera todos os dados do upload * É preciso estar autenticado para editar.",
"name": "put",
"signature": "def put(self,... | 4 | stack_v2_sparse_classes_30k_train_020147 | Implement the Python class `UploadDetailView` described below.
Class description:
Implement the UploadDetailView class.
Method signatures and docstrings:
- def get(self, request, pk): Lista detalhes de um upload * É preciso estar autenticado para visualizar.
- def put(self, request, pk): Altera todos os dados do uplo... | Implement the Python class `UploadDetailView` described below.
Class description:
Implement the UploadDetailView class.
Method signatures and docstrings:
- def get(self, request, pk): Lista detalhes de um upload * É preciso estar autenticado para visualizar.
- def put(self, request, pk): Altera todos os dados do uplo... | 06d7632eccdc013262e8c1476d2b6a7052bd3c52 | <|skeleton|>
class UploadDetailView:
def get(self, request, pk):
"""Lista detalhes de um upload * É preciso estar autenticado para visualizar."""
<|body_0|>
def put(self, request, pk):
"""Altera todos os dados do upload * É preciso estar autenticado para editar."""
<|body_1|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UploadDetailView:
def get(self, request, pk):
"""Lista detalhes de um upload * É preciso estar autenticado para visualizar."""
queryset = get_object_or_404(Upload, pk=pk)
serializer = UploadSerializer(queryset)
return Response(serializer.data)
def put(self, request, pk):
... | the_stack_v2_python_sparse | upload/views.py | foschieraanderson/gallery-django-react | train | 0 | |
194a1abd2cf1e239502d52793b94d386d5390892 | [
"today = timezone.now().date()\ncount = user.threads.filter(started__gte=today).count()\nreturn count",
"timestamp = Negotiation.get_timestamp(timezone.now().date())\ncount = user.negotiations_made.filter(time__gte=timestamp).count()\nreturn count",
"from scoop.messaging.models import Message\ntimestamp = Messa... | <|body_start_0|>
today = timezone.now().date()
count = user.threads.filter(started__gte=today).count()
return count
<|end_body_0|>
<|body_start_1|>
timestamp = Negotiation.get_timestamp(timezone.now().date())
count = user.negotiations_made.filter(time__gte=timestamp).count()
... | Manager des quotas | QuotaManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuotaManager:
"""Manager des quotas"""
def get_threads_today_by(self, user):
"""Renvoyer le nombre de fils créés aujourd'hui par un utilisateur"""
<|body_0|>
def get_negotiations_today_by(self, user):
"""Renvoyer le nombre de négociations envoyées aujourd'hui par... | stack_v2_sparse_classes_75kplus_train_066650 | 3,706 | no_license | [
{
"docstring": "Renvoyer le nombre de fils créés aujourd'hui par un utilisateur",
"name": "get_threads_today_by",
"signature": "def get_threads_today_by(self, user)"
},
{
"docstring": "Renvoyer le nombre de négociations envoyées aujourd'hui par un utilisateur",
"name": "get_negotiations_toda... | 5 | stack_v2_sparse_classes_30k_train_011107 | Implement the Python class `QuotaManager` described below.
Class description:
Manager des quotas
Method signatures and docstrings:
- def get_threads_today_by(self, user): Renvoyer le nombre de fils créés aujourd'hui par un utilisateur
- def get_negotiations_today_by(self, user): Renvoyer le nombre de négociations env... | Implement the Python class `QuotaManager` described below.
Class description:
Manager des quotas
Method signatures and docstrings:
- def get_threads_today_by(self, user): Renvoyer le nombre de fils créés aujourd'hui par un utilisateur
- def get_negotiations_today_by(self, user): Renvoyer le nombre de négociations env... | 8cef6f6e89c1990e2b25f83e54e0c3481d83b6d7 | <|skeleton|>
class QuotaManager:
"""Manager des quotas"""
def get_threads_today_by(self, user):
"""Renvoyer le nombre de fils créés aujourd'hui par un utilisateur"""
<|body_0|>
def get_negotiations_today_by(self, user):
"""Renvoyer le nombre de négociations envoyées aujourd'hui par... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class QuotaManager:
"""Manager des quotas"""
def get_threads_today_by(self, user):
"""Renvoyer le nombre de fils créés aujourd'hui par un utilisateur"""
today = timezone.now().date()
count = user.threads.filter(started__gte=today).count()
return count
def get_negotiations_t... | the_stack_v2_python_sparse | scoop/messaging/models/quota.py | artscoop/scoop | train | 0 |
4549b28bd76b451d26d9af6d5fb7ab6ebf431162 | [
"self.model = model\nself.dataloader = dataloader\nself.loss = loss_function()\nself.optimizer = optimizer\nself.epochs = epochs\nself.lr_scheduler = lr_scheduler\nself.device = device\nself.log_step = log_step\nself.checkpoints_dir_path = checkpoints_dir_path\nself.validator = BaseTester(val_dataloader, loss_funct... | <|body_start_0|>
self.model = model
self.dataloader = dataloader
self.loss = loss_function()
self.optimizer = optimizer
self.epochs = epochs
self.lr_scheduler = lr_scheduler
self.device = device
self.log_step = log_step
self.checkpoints_dir_path = ... | The class implements the base trainer pipeline. | BaseTrainer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseTrainer:
"""The class implements the base trainer pipeline."""
def __init__(self, model, dataloader, loss_function, optimizer, epochs, lr_scheduler=None, val_dataloader=None, device='cuda', log_step=50, checkpoints_dir_path=None):
"""Constructor, the function initializes the trai... | stack_v2_sparse_classes_75kplus_train_066651 | 4,215 | permissive | [
{
"docstring": "Constructor, the function initializes the training related parameters. :param model: The model to train :param dataloader: The dataloader to get training samples from :param loss_function: The loss function :param optimizer: The optimizer to be used for training :param epochs: Number of epochs :... | 3 | stack_v2_sparse_classes_30k_train_025892 | Implement the Python class `BaseTrainer` described below.
Class description:
The class implements the base trainer pipeline.
Method signatures and docstrings:
- def __init__(self, model, dataloader, loss_function, optimizer, epochs, lr_scheduler=None, val_dataloader=None, device='cuda', log_step=50, checkpoints_dir_p... | Implement the Python class `BaseTrainer` described below.
Class description:
The class implements the base trainer pipeline.
Method signatures and docstrings:
- def __init__(self, model, dataloader, loss_function, optimizer, epochs, lr_scheduler=None, val_dataloader=None, device='cuda', log_step=50, checkpoints_dir_p... | 9a4bf0a112b818caca8794868a903dc736839a43 | <|skeleton|>
class BaseTrainer:
"""The class implements the base trainer pipeline."""
def __init__(self, model, dataloader, loss_function, optimizer, epochs, lr_scheduler=None, val_dataloader=None, device='cuda', log_step=50, checkpoints_dir_path=None):
"""Constructor, the function initializes the trai... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BaseTrainer:
"""The class implements the base trainer pipeline."""
def __init__(self, model, dataloader, loss_function, optimizer, epochs, lr_scheduler=None, val_dataloader=None, device='cuda', log_step=50, checkpoints_dir_path=None):
"""Constructor, the function initializes the training related ... | the_stack_v2_python_sparse | train/base_trainer.py | Niousha12/ssl_for_fgvc | train | 0 |
21c7e669f0e518f3a8ed6f3c6b34e36540504332 | [
"sigmas, norms = get_sigmas_and_norms(**kwargs)\nm = MultiGauss2D(sigmas=sigmas, norms=norms)\nm.normalize()\ncontainment = m.containment_fraction(rad)\nreturn containment",
"sigmas, norms = get_sigmas_and_norms(**kwargs)\nm = MultiGauss2D(sigmas=sigmas, norms=norms)\nm.normalize()\nreturn m(rad)"
] | <|body_start_0|>
sigmas, norms = get_sigmas_and_norms(**kwargs)
m = MultiGauss2D(sigmas=sigmas, norms=norms)
m.normalize()
containment = m.containment_fraction(rad)
return containment
<|end_body_0|>
<|body_start_1|>
sigmas, norms = get_sigmas_and_norms(**kwargs)
... | Triple Gauss analytical PSF depending on true energy and offset. Parameters ---------- axes : list of `MapAxis` Required axes are ["energy_true", "offset"] data : `~numpy.recarray` Data array meta : dict Meta data Examples -------- Plot R68 of the PSF vs. offset and true energy: .. plot:: :include-source: import matplo... | EnergyDependentMultiGaussPSF | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EnergyDependentMultiGaussPSF:
"""Triple Gauss analytical PSF depending on true energy and offset. Parameters ---------- axes : list of `MapAxis` Required axes are ["energy_true", "offset"] data : `~numpy.recarray` Data array meta : dict Meta data Examples -------- Plot R68 of the PSF vs. offset a... | stack_v2_sparse_classes_75kplus_train_066652 | 12,422 | permissive | [
{
"docstring": "Containment of the PSF at given axes coordinates Parameters ---------- rad : `~astropy.units.Quantity` Rad value **kwargs : dict Parameters, see `required_parameters` Returns ------- containment : `~numpy.ndarray` Containment",
"name": "evaluate_containment",
"signature": "def evaluate_c... | 2 | null | Implement the Python class `EnergyDependentMultiGaussPSF` described below.
Class description:
Triple Gauss analytical PSF depending on true energy and offset. Parameters ---------- axes : list of `MapAxis` Required axes are ["energy_true", "offset"] data : `~numpy.recarray` Data array meta : dict Meta data Examples --... | Implement the Python class `EnergyDependentMultiGaussPSF` described below.
Class description:
Triple Gauss analytical PSF depending on true energy and offset. Parameters ---------- axes : list of `MapAxis` Required axes are ["energy_true", "offset"] data : `~numpy.recarray` Data array meta : dict Meta data Examples --... | 60f03adb8fc7851b9f3ca039512c03a669e3fe10 | <|skeleton|>
class EnergyDependentMultiGaussPSF:
"""Triple Gauss analytical PSF depending on true energy and offset. Parameters ---------- axes : list of `MapAxis` Required axes are ["energy_true", "offset"] data : `~numpy.recarray` Data array meta : dict Meta data Examples -------- Plot R68 of the PSF vs. offset a... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EnergyDependentMultiGaussPSF:
"""Triple Gauss analytical PSF depending on true energy and offset. Parameters ---------- axes : list of `MapAxis` Required axes are ["energy_true", "offset"] data : `~numpy.recarray` Data array meta : dict Meta data Examples -------- Plot R68 of the PSF vs. offset and true energ... | the_stack_v2_python_sparse | gammapy/irf/psf/parametric.py | gammapy/gammapy | train | 204 |
a9eab2ef4b94851019af2eb8818ad7dd47e983e0 | [
"form = ResearchInfoGetForm(request.args)\nif form.validate():\n try:\n all_research_info = ResearchInformation.query.filter(ResearchInformation.user_id == form.user_id.data).all()\n except:\n return make_response(jsonify({'error': 'Database Connection Problem'}), 500)\n research_list = [{'id... | <|body_start_0|>
form = ResearchInfoGetForm(request.args)
if form.validate():
try:
all_research_info = ResearchInformation.query.filter(ResearchInformation.user_id == form.user_id.data).all()
except:
return make_response(jsonify({'error': 'Database... | Research Information Functionality is implemented in this class | ResearchInformationAPI | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResearchInformationAPI:
"""Research Information Functionality is implemented in this class"""
def get(user_id, self):
"""Returns all research information of a user"""
<|body_0|>
def post(user_id, self):
"""Adds new Research Information"""
<|body_1|>
... | stack_v2_sparse_classes_75kplus_train_066653 | 22,916 | no_license | [
{
"docstring": "Returns all research information of a user",
"name": "get",
"signature": "def get(user_id, self)"
},
{
"docstring": "Adds new Research Information",
"name": "post",
"signature": "def post(user_id, self)"
},
{
"docstring": "Updates a Research Information",
"nam... | 4 | stack_v2_sparse_classes_30k_val_001702 | Implement the Python class `ResearchInformationAPI` described below.
Class description:
Research Information Functionality is implemented in this class
Method signatures and docstrings:
- def get(user_id, self): Returns all research information of a user
- def post(user_id, self): Adds new Research Information
- def ... | Implement the Python class `ResearchInformationAPI` described below.
Class description:
Research Information Functionality is implemented in this class
Method signatures and docstrings:
- def get(user_id, self): Returns all research information of a user
- def post(user_id, self): Adds new Research Information
- def ... | f7aebee17a0a79e8d3c2927733bce8015b4a9da3 | <|skeleton|>
class ResearchInformationAPI:
"""Research Information Functionality is implemented in this class"""
def get(user_id, self):
"""Returns all research information of a user"""
<|body_0|>
def post(user_id, self):
"""Adds new Research Information"""
<|body_1|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ResearchInformationAPI:
"""Research Information Functionality is implemented in this class"""
def get(user_id, self):
"""Returns all research information of a user"""
form = ResearchInfoGetForm(request.args)
if form.validate():
try:
all_research_info = ... | the_stack_v2_python_sparse | platon/backend/app/profile_management/views.py | bounswe/bounswe2020group7 | train | 18 |
b4084bc0d7b769058e26c19c10430fffc3b2b790 | [
"super().__init__()\nself.finetuning = finetuning\nModel, Tokenizer, weight = LANG_MODELS[arch]\nbert = Model.from_pretrained(weight, output_hidden_states=True)\nif not pretrained:\n bert.init_weights()\nif not self.finetuning:\n for param in bert.parameters():\n param.requires_grad = False\nbackbone_d... | <|body_start_0|>
super().__init__()
self.finetuning = finetuning
Model, Tokenizer, weight = LANG_MODELS[arch]
bert = Model.from_pretrained(weight, output_hidden_states=True)
if not pretrained:
bert.init_weights()
if not self.finetuning:
for param i... | LangModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LangModel:
def __init__(self, dim, arch='BERT', layers=(-1,), pretrained=True, finetuning=False):
""":param dim: dimension of the output :param arch: backbone architecture, :param aggregate: one of 'last4', :param pretrained: load feature with pre-trained vector :param finetuning: finetu... | stack_v2_sparse_classes_75kplus_train_066654 | 11,314 | permissive | [
{
"docstring": ":param dim: dimension of the output :param arch: backbone architecture, :param aggregate: one of 'last4', :param pretrained: load feature with pre-trained vector :param finetuning: finetune the model",
"name": "__init__",
"signature": "def __init__(self, dim, arch='BERT', layers=(-1,), p... | 2 | stack_v2_sparse_classes_30k_train_013282 | Implement the Python class `LangModel` described below.
Class description:
Implement the LangModel class.
Method signatures and docstrings:
- def __init__(self, dim, arch='BERT', layers=(-1,), pretrained=True, finetuning=False): :param dim: dimension of the output :param arch: backbone architecture, :param aggregate:... | Implement the Python class `LangModel` described below.
Class description:
Implement the LangModel class.
Method signatures and docstrings:
- def __init__(self, dim, arch='BERT', layers=(-1,), pretrained=True, finetuning=False): :param dim: dimension of the output :param arch: backbone architecture, :param aggregate:... | 51ac07d1de564c26fbf038b07031a55660bbcb27 | <|skeleton|>
class LangModel:
def __init__(self, dim, arch='BERT', layers=(-1,), pretrained=True, finetuning=False):
""":param dim: dimension of the output :param arch: backbone architecture, :param aggregate: one of 'last4', :param pretrained: load feature with pre-trained vector :param finetuning: finetu... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LangModel:
def __init__(self, dim, arch='BERT', layers=(-1,), pretrained=True, finetuning=False):
""":param dim: dimension of the output :param arch: backbone architecture, :param aggregate: one of 'last4', :param pretrained: load feature with pre-trained vector :param finetuning: finetune the model""... | the_stack_v2_python_sparse | retrieval_model/xmatching/model.py | CJJ2923/Maria | train | 0 | |
089a08ebd1c0f88313aca00dca8fb6b2aabc7f09 | [
"self.temp_path = mkdtemp(prefix='pelicantests.')\nself.temp_cache = mkdtemp(prefix='pelican_cache.')\nos.chdir(TEST_DATA_DIR)",
"rmtree(self.temp_path)\nrmtree(self.temp_cache)\nos.chdir(PLUGIN_DIR)",
"base_path = os.path.dirname(os.path.abspath(__file__))\nbase_path = os.path.join(base_path, 'test_data')\ncon... | <|body_start_0|>
self.temp_path = mkdtemp(prefix='pelicantests.')
self.temp_cache = mkdtemp(prefix='pelican_cache.')
os.chdir(TEST_DATA_DIR)
<|end_body_0|>
<|body_start_1|>
rmtree(self.temp_path)
rmtree(self.temp_cache)
os.chdir(PLUGIN_DIR)
<|end_body_1|>
<|body_start_2... | Test running Pelican with the Plugin | TestFullRun | [
"AGPL-3.0-only",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestFullRun:
"""Test running Pelican with the Plugin"""
def setUp(self):
"""Create temporary output and cache folders"""
<|body_0|>
def tearDown(self):
"""Remove output and cache folders"""
<|body_1|>
def test_generate_with_ipython3(self):
""... | stack_v2_sparse_classes_75kplus_train_066655 | 3,556 | permissive | [
{
"docstring": "Create temporary output and cache folders",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Remove output and cache folders",
"name": "tearDown",
"signature": "def tearDown(self)"
},
{
"docstring": "Test generation of site with the plugin.",
... | 4 | stack_v2_sparse_classes_30k_train_001161 | Implement the Python class `TestFullRun` described below.
Class description:
Test running Pelican with the Plugin
Method signatures and docstrings:
- def setUp(self): Create temporary output and cache folders
- def tearDown(self): Remove output and cache folders
- def test_generate_with_ipython3(self): Test generatio... | Implement the Python class `TestFullRun` described below.
Class description:
Test running Pelican with the Plugin
Method signatures and docstrings:
- def setUp(self): Create temporary output and cache folders
- def tearDown(self): Remove output and cache folders
- def test_generate_with_ipython3(self): Test generatio... | b5d68070b6f15677a183424c84e30440e128e1ea | <|skeleton|>
class TestFullRun:
"""Test running Pelican with the Plugin"""
def setUp(self):
"""Create temporary output and cache folders"""
<|body_0|>
def tearDown(self):
"""Remove output and cache folders"""
<|body_1|>
def test_generate_with_ipython3(self):
""... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TestFullRun:
"""Test running Pelican with the Plugin"""
def setUp(self):
"""Create temporary output and cache folders"""
self.temp_path = mkdtemp(prefix='pelicantests.')
self.temp_cache = mkdtemp(prefix='pelican_cache.')
os.chdir(TEST_DATA_DIR)
def tearDown(self):
... | the_stack_v2_python_sparse | plugins/liquid_tags/test_generation.py | JackMcKew/jackmckew.dev | train | 15 |
01f69e4541f9144b164c9c5256d6c2e6a1317b49 | [
"super(PairedDataset, self).__init__(preprocess)\nself.dataroot = dataroot\nself.data_infos = self.prepare_data_infos()",
"data_infos = []\npair_paths = sorted(self.scan_folder(self.dataroot))\nfor pair_path in pair_paths:\n data_infos.append(dict(pair_path=pair_path))\nreturn data_infos"
] | <|body_start_0|>
super(PairedDataset, self).__init__(preprocess)
self.dataroot = dataroot
self.data_infos = self.prepare_data_infos()
<|end_body_0|>
<|body_start_1|>
data_infos = []
pair_paths = sorted(self.scan_folder(self.dataroot))
for pair_path in pair_paths:
... | A dataset class for paired image dataset. | PairedDataset | [
"MIT",
"Apache-2.0",
"Python-2.0",
"LicenseRef-scancode-generic-cla"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PairedDataset:
"""A dataset class for paired image dataset."""
def __init__(self, dataroot, preprocess):
"""Initialize this dataset class. Args: dataroot (str): Directory of dataset. preprocess (list[dict]): A sequence of data preprocess config."""
<|body_0|>
def prepare... | stack_v2_sparse_classes_75kplus_train_066656 | 1,546 | permissive | [
{
"docstring": "Initialize this dataset class. Args: dataroot (str): Directory of dataset. preprocess (list[dict]): A sequence of data preprocess config.",
"name": "__init__",
"signature": "def __init__(self, dataroot, preprocess)"
},
{
"docstring": "Load paired image paths. Returns: list[dict]:... | 2 | stack_v2_sparse_classes_30k_train_046469 | Implement the Python class `PairedDataset` described below.
Class description:
A dataset class for paired image dataset.
Method signatures and docstrings:
- def __init__(self, dataroot, preprocess): Initialize this dataset class. Args: dataroot (str): Directory of dataset. preprocess (list[dict]): A sequence of data ... | Implement the Python class `PairedDataset` described below.
Class description:
A dataset class for paired image dataset.
Method signatures and docstrings:
- def __init__(self, dataroot, preprocess): Initialize this dataset class. Args: dataroot (str): Directory of dataset. preprocess (list[dict]): A sequence of data ... | 038fb5afe017b82334ad39a256531d2c4e9e1e1a | <|skeleton|>
class PairedDataset:
"""A dataset class for paired image dataset."""
def __init__(self, dataroot, preprocess):
"""Initialize this dataset class. Args: dataroot (str): Directory of dataset. preprocess (list[dict]): A sequence of data preprocess config."""
<|body_0|>
def prepare... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PairedDataset:
"""A dataset class for paired image dataset."""
def __init__(self, dataroot, preprocess):
"""Initialize this dataset class. Args: dataroot (str): Directory of dataset. preprocess (list[dict]): A sequence of data preprocess config."""
super(PairedDataset, self).__init__(prep... | the_stack_v2_python_sparse | 15.PaddleGAN/PaddleGAN/ppgan/datasets/paired_dataset.py | yingshaoxo/ML | train | 5 |
b68d51c273f030eebfd77ada31517e4924f96b20 | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('ajr10_williami', 'ajr10_williami')\nrepo.dropCollection('ajr10_williami.area_spaces_cambridge')\nrepo.createCollection('ajr10_williami.area_spaces_cambridge')\nrepo.dropCollection('ajr10_williami.area_sp... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('ajr10_williami', 'ajr10_williami')
repo.dropCollection('ajr10_williami.area_spaces_cambridge')
repo.createCollection('ajr10_williami.area_spaces_c... | get_area | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class get_area:
def execute(trial=False):
"""Retrieve some data sets and store in mongodb collections."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything happening in this scrip... | stack_v2_sparse_classes_75kplus_train_066657 | 5,300 | no_license | [
{
"docstring": "Retrieve some data sets and store in mongodb collections.",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new document describing ... | 2 | stack_v2_sparse_classes_30k_train_052699 | Implement the Python class `get_area` described below.
Class description:
Implement the get_area class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets and store in mongodb collections.
- def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None): Create the prov... | Implement the Python class `get_area` described below.
Class description:
Implement the get_area class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets and store in mongodb collections.
- def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None): Create the prov... | 0df485d0469c5451ebdcd684bed2a0960ba3ab84 | <|skeleton|>
class get_area:
def execute(trial=False):
"""Retrieve some data sets and store in mongodb collections."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything happening in this scrip... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class get_area:
def execute(trial=False):
"""Retrieve some data sets and store in mongodb collections."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('ajr10_williami', 'ajr10_williami')
repo.dropCollectio... | the_stack_v2_python_sparse | ajr10_williami/get_area.py | lingyigu/course-2017-spr-proj | train | 0 | |
b13cbaa8cbf23031d36150bc90eb0dd2a2fa87bb | [
"dict.__init__(self, *args, **kwargs)\nself.__dict__ = self\nself.__depth__ = dict_depth(self.__dict__)\nself.__getstr__ = ['dict.get(self,key[0],None)']\nif self.__depth__ > 1:\n for d in range(2, self.__depth__ + 1):\n self.__getstr__.append(self.__getstr__[d - 2].replace('None', '{}') + '.get(key[' + s... | <|body_start_0|>
dict.__init__(self, *args, **kwargs)
self.__dict__ = self
self.__depth__ = dict_depth(self.__dict__)
self.__getstr__ = ['dict.get(self,key[0],None)']
if self.__depth__ > 1:
for d in range(2, self.__depth__ + 1):
self.__getstr__.append(... | Gets items from nested dictionaries. Parameters ---------- dict: python dictionary. - For simple dictionaries: ``smart_dict(dict)[key]`` - For nested dictionaries up to n levels 1. First level: can declare key as single element or in list e.g. ``smart_dict(dict)[[key]]``, ``smart_dict(dict)[key]`` 2. Successive levels:... | smart_dict | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class smart_dict:
"""Gets items from nested dictionaries. Parameters ---------- dict: python dictionary. - For simple dictionaries: ``smart_dict(dict)[key]`` - For nested dictionaries up to n levels 1. First level: can declare key as single element or in list e.g. ``smart_dict(dict)[[key]]``, ``smart_d... | stack_v2_sparse_classes_75kplus_train_066658 | 8,899 | no_license | [
{
"docstring": "NEEDS DOCUMENTING Parameters ---------- args kwargs",
"name": "__init__",
"signature": "def __init__(self, *args, **kwargs)"
},
{
"docstring": "NEEDS DOCUMENTING Parameters ---------- self: key: Returns ------- val:",
"name": "__getitem__",
"signature": "def __getitem__(s... | 2 | stack_v2_sparse_classes_30k_train_024400 | Implement the Python class `smart_dict` described below.
Class description:
Gets items from nested dictionaries. Parameters ---------- dict: python dictionary. - For simple dictionaries: ``smart_dict(dict)[key]`` - For nested dictionaries up to n levels 1. First level: can declare key as single element or in list e.g.... | Implement the Python class `smart_dict` described below.
Class description:
Gets items from nested dictionaries. Parameters ---------- dict: python dictionary. - For simple dictionaries: ``smart_dict(dict)[key]`` - For nested dictionaries up to n levels 1. First level: can declare key as single element or in list e.g.... | d4ef13e4933cba0d2c1dd70730f03c8575e2f7a1 | <|skeleton|>
class smart_dict:
"""Gets items from nested dictionaries. Parameters ---------- dict: python dictionary. - For simple dictionaries: ``smart_dict(dict)[key]`` - For nested dictionaries up to n levels 1. First level: can declare key as single element or in list e.g. ``smart_dict(dict)[[key]]``, ``smart_d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class smart_dict:
"""Gets items from nested dictionaries. Parameters ---------- dict: python dictionary. - For simple dictionaries: ``smart_dict(dict)[key]`` - For nested dictionaries up to n levels 1. First level: can declare key as single element or in list e.g. ``smart_dict(dict)[[key]]``, ``smart_dict(dict)[key... | the_stack_v2_python_sparse | cdm/lib/mappings/mappings_hdlr.py | glamod/cdm_mapper_documentation | train | 0 |
85182c4a9c40d01d4891430db90c7d7ad716eb0e | [
"self.label = label\nself.weight = weight\nself._get_field_widget = get_field",
"lbl = Label()\nlbl.text = self.label\nlbl.size_hint_x = self.weight\nreturn lbl",
"w = self._get_field_widget(data)\nw.size_hint_x = self.weight\nw.size_hint_max_y = row_height\nreturn w"
] | <|body_start_0|>
self.label = label
self.weight = weight
self._get_field_widget = get_field
<|end_body_0|>
<|body_start_1|>
lbl = Label()
lbl.text = self.label
lbl.size_hint_x = self.weight
return lbl
<|end_body_1|>
<|body_start_2|>
w = self._get_field_w... | Represents a field modeled in a table | TableField | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TableField:
"""Represents a field modeled in a table"""
def __init__(self, label: str, weight: float, get_field: Callable[[object], Widget]):
"""Initialise table field :param label: The name of the field :param weight: The width sizing percentage :param get_field: A method to create ... | stack_v2_sparse_classes_75kplus_train_066659 | 5,221 | no_license | [
{
"docstring": "Initialise table field :param label: The name of the field :param weight: The width sizing percentage :param get_field: A method to create the table cell widget",
"name": "__init__",
"signature": "def __init__(self, label: str, weight: float, get_field: Callable[[object], Widget])"
},
... | 3 | null | Implement the Python class `TableField` described below.
Class description:
Represents a field modeled in a table
Method signatures and docstrings:
- def __init__(self, label: str, weight: float, get_field: Callable[[object], Widget]): Initialise table field :param label: The name of the field :param weight: The widt... | Implement the Python class `TableField` described below.
Class description:
Represents a field modeled in a table
Method signatures and docstrings:
- def __init__(self, label: str, weight: float, get_field: Callable[[object], Widget]): Initialise table field :param label: The name of the field :param weight: The widt... | 7be0791d8bc0ba30c984d6c99a1094c5267479e6 | <|skeleton|>
class TableField:
"""Represents a field modeled in a table"""
def __init__(self, label: str, weight: float, get_field: Callable[[object], Widget]):
"""Initialise table field :param label: The name of the field :param weight: The width sizing percentage :param get_field: A method to create ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TableField:
"""Represents a field modeled in a table"""
def __init__(self, label: str, weight: float, get_field: Callable[[object], Widget]):
"""Initialise table field :param label: The name of the field :param weight: The width sizing percentage :param get_field: A method to create the table cel... | the_stack_v2_python_sparse | widgets/table.py | eperegrine/ECM2429-StockManager | train | 1 |
a4bd136857769352d181965d0072472887e8c4bd | [
"self.xinput = xinput\nself.var_scope = var_scope\nself.critic_layers = critic_layers\nself.clusters_no = clusters_no\nself.input_clusters = input_clusters\nself.reuse = reuse\nself.dist = dist",
"with tf.variable_scope(var_scope, reuse=reuse):\n for i_lay, output_size in enumerate(critic_layers):\n wit... | <|body_start_0|>
self.xinput = xinput
self.var_scope = var_scope
self.critic_layers = critic_layers
self.clusters_no = clusters_no
self.input_clusters = input_clusters
self.reuse = reuse
self.dist = dist
<|end_body_0|>
<|body_start_1|>
with tf.variable_sc... | Generic class for the Critic network | Critic | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Critic:
"""Generic class for the Critic network"""
def __init__(self, xinput, dist, var_scope, critic_layers, input_clusters=None, clusters_no=None, reuse=None):
"""Default constructor. Parameters ---------- xinput : Tensor Tensor containing the input cells. dist : Tensor Tensor cont... | stack_v2_sparse_classes_75kplus_train_066660 | 29,633 | permissive | [
{
"docstring": "Default constructor. Parameters ---------- xinput : Tensor Tensor containing the input cells. dist : Tensor Tensor containing the output of the Critic (e.g. the Wasserstein distance). var_scope : str Variable scope used for the created tensors. critic_layers : list List of integers corresponding... | 4 | stack_v2_sparse_classes_30k_train_000675 | Implement the Python class `Critic` described below.
Class description:
Generic class for the Critic network
Method signatures and docstrings:
- def __init__(self, xinput, dist, var_scope, critic_layers, input_clusters=None, clusters_no=None, reuse=None): Default constructor. Parameters ---------- xinput : Tensor Ten... | Implement the Python class `Critic` described below.
Class description:
Generic class for the Critic network
Method signatures and docstrings:
- def __init__(self, xinput, dist, var_scope, critic_layers, input_clusters=None, clusters_no=None, reuse=None): Default constructor. Parameters ---------- xinput : Tensor Ten... | a06f8ccd6a071d57e591dacd6164c9f78987a794 | <|skeleton|>
class Critic:
"""Generic class for the Critic network"""
def __init__(self, xinput, dist, var_scope, critic_layers, input_clusters=None, clusters_no=None, reuse=None):
"""Default constructor. Parameters ---------- xinput : Tensor Tensor containing the input cells. dist : Tensor Tensor cont... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Critic:
"""Generic class for the Critic network"""
def __init__(self, xinput, dist, var_scope, critic_layers, input_clusters=None, clusters_no=None, reuse=None):
"""Default constructor. Parameters ---------- xinput : Tensor Tensor containing the input cells. dist : Tensor Tensor containing the ou... | the_stack_v2_python_sparse | estimators/utilities.py | imsb-uke/scGAN | train | 73 |
fe92d06a52de1b051d244e5cb360594f948fe353 | [
"url = self.ip + '/api/scm/auth/scm/scmPoD/detailList.do'\nparams = {'status': 'NotReceived', 'poCode': order_no}\nr = self.s.post(url=url, params=params)\nreturn r.json()",
"url = self.ip + '/api/scm//auth/scm/scmPoD/receive.do'\nparams = {'status': 'Received', 'deliveryDay': get_future_date(7), 'ids': ids}\nr =... | <|body_start_0|>
url = self.ip + '/api/scm/auth/scm/scmPoD/detailList.do'
params = {'status': 'NotReceived', 'poCode': order_no}
r = self.s.post(url=url, params=params)
return r.json()
<|end_body_0|>
<|body_start_1|>
url = self.ip + '/api/scm//auth/scm/scmPoD/receive.do'
... | B2BPurchaseOrder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class B2BPurchaseOrder:
def purchase_order_search_by_no(self, order_no):
"""通过采购订单号查询采购订单明细 :param order_no: 采购订单号 :return:"""
<|body_0|>
def receive_purchase_order(self, ids):
"""供应商订单确认 :param ids: 明细id :return:"""
<|body_1|>
def return_purchase_order(self, ... | stack_v2_sparse_classes_75kplus_train_066661 | 2,159 | no_license | [
{
"docstring": "通过采购订单号查询采购订单明细 :param order_no: 采购订单号 :return:",
"name": "purchase_order_search_by_no",
"signature": "def purchase_order_search_by_no(self, order_no)"
},
{
"docstring": "供应商订单确认 :param ids: 明细id :return:",
"name": "receive_purchase_order",
"signature": "def receive_purch... | 4 | stack_v2_sparse_classes_30k_train_014046 | Implement the Python class `B2BPurchaseOrder` described below.
Class description:
Implement the B2BPurchaseOrder class.
Method signatures and docstrings:
- def purchase_order_search_by_no(self, order_no): 通过采购订单号查询采购订单明细 :param order_no: 采购订单号 :return:
- def receive_purchase_order(self, ids): 供应商订单确认 :param ids: 明细id... | Implement the Python class `B2BPurchaseOrder` described below.
Class description:
Implement the B2BPurchaseOrder class.
Method signatures and docstrings:
- def purchase_order_search_by_no(self, order_no): 通过采购订单号查询采购订单明细 :param order_no: 采购订单号 :return:
- def receive_purchase_order(self, ids): 供应商订单确认 :param ids: 明细id... | 26d2ae773a999fd8446e18f9c0719d46402b19aa | <|skeleton|>
class B2BPurchaseOrder:
def purchase_order_search_by_no(self, order_no):
"""通过采购订单号查询采购订单明细 :param order_no: 采购订单号 :return:"""
<|body_0|>
def receive_purchase_order(self, ids):
"""供应商订单确认 :param ids: 明细id :return:"""
<|body_1|>
def return_purchase_order(self, ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class B2BPurchaseOrder:
def purchase_order_search_by_no(self, order_no):
"""通过采购订单号查询采购订单明细 :param order_no: 采购订单号 :return:"""
url = self.ip + '/api/scm/auth/scm/scmPoD/detailList.do'
params = {'status': 'NotReceived', 'poCode': order_no}
r = self.s.post(url=url, params=params)
... | the_stack_v2_python_sparse | api/B2B_purchase_order_api.py | Leofighting/dimi_api_test | train | 0 | |
09daefadd62d7cd18f007346ed627bd2468cc59c | [
"from ..misc import RelativePath\nsuper(CallProcess, self).__init__(maxtrials=maxtrials)\nself.functional = functional\n' Functional to execute. '\ntry:\n self.functional = self.functional\nexcept:\n pass\nself.outdir = RelativePath(outdir)\n' Execution directory of the folder. '\nself.outdir = RelativePath(o... | <|body_start_0|>
from ..misc import RelativePath
super(CallProcess, self).__init__(maxtrials=maxtrials)
self.functional = functional
' Functional to execute. '
try:
self.functional = self.functional
except:
pass
self.outdir = RelativePath(o... | Calls functional in child python process. This process pickles_ a callable and its arguments and executes it in a child python process. .. _pickles: http://docs.python.org/library/pickle.html | CallProcess | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CallProcess:
"""Calls functional in child python process. This process pickles_ a callable and its arguments and executes it in a child python process. .. _pickles: http://docs.python.org/library/pickle.html"""
def __init__(self, functional, outdir, stdout=None, stderr=None, maxtrials=1, dom... | stack_v2_sparse_classes_75kplus_train_066662 | 5,576 | no_license | [
{
"docstring": "Initializes a process. :param functional: A python callable. It should also be pickle-able. :param str outdir: Path where the python child process should be executed. :param str stdout: Optional path to an output file where the callable's output shall be streamed. :param str stderr: Optional pat... | 6 | stack_v2_sparse_classes_30k_train_046385 | Implement the Python class `CallProcess` described below.
Class description:
Calls functional in child python process. This process pickles_ a callable and its arguments and executes it in a child python process. .. _pickles: http://docs.python.org/library/pickle.html
Method signatures and docstrings:
- def __init__(... | Implement the Python class `CallProcess` described below.
Class description:
Calls functional in child python process. This process pickles_ a callable and its arguments and executes it in a child python process. .. _pickles: http://docs.python.org/library/pickle.html
Method signatures and docstrings:
- def __init__(... | 9c0ab667f94dc4629404a8ec99cbeaa323f0c8b3 | <|skeleton|>
class CallProcess:
"""Calls functional in child python process. This process pickles_ a callable and its arguments and executes it in a child python process. .. _pickles: http://docs.python.org/library/pickle.html"""
def __init__(self, functional, outdir, stdout=None, stderr=None, maxtrials=1, dom... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CallProcess:
"""Calls functional in child python process. This process pickles_ a callable and its arguments and executes it in a child python process. .. _pickles: http://docs.python.org/library/pickle.html"""
def __init__(self, functional, outdir, stdout=None, stderr=None, maxtrials=1, dompi=False, **k... | the_stack_v2_python_sparse | process/call.py | Shibu778/LaDa | train | 0 |
344ec2bed37c4f8b21332c7078f4da2649f2c825 | [
"super(ConvGRU, self).__init__()\nself.input_size = input_size\nif type(hidden_sizes) != list:\n self.hidden_sizes = [hidden_sizes] * n_layers\nelse:\n assert len(hidden_sizes) == n_layers, '`hidden_sizes` must have the same length as n_layers'\n self.hidden_sizes = hidden_sizes\nif type(kernel_sizes) != l... | <|body_start_0|>
super(ConvGRU, self).__init__()
self.input_size = input_size
if type(hidden_sizes) != list:
self.hidden_sizes = [hidden_sizes] * n_layers
else:
assert len(hidden_sizes) == n_layers, '`hidden_sizes` must have the same length as n_layers'
... | ConvGRU | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConvGRU:
def __init__(self, input_size, hidden_sizes, kernel_sizes, n_layers):
"""Generates a multi-layer convolutional GRU. Preserves spatial dimensions across cells, only altering depth. Parameters ---------- input_size : integer. depth dimension of input tensors. hidden_sizes : intege... | stack_v2_sparse_classes_75kplus_train_066663 | 4,783 | permissive | [
{
"docstring": "Generates a multi-layer convolutional GRU. Preserves spatial dimensions across cells, only altering depth. Parameters ---------- input_size : integer. depth dimension of input tensors. hidden_sizes : integer or list. depth dimensions of hidden state. if integer, the same hidden size is used for ... | 2 | stack_v2_sparse_classes_30k_train_039105 | Implement the Python class `ConvGRU` described below.
Class description:
Implement the ConvGRU class.
Method signatures and docstrings:
- def __init__(self, input_size, hidden_sizes, kernel_sizes, n_layers): Generates a multi-layer convolutional GRU. Preserves spatial dimensions across cells, only altering depth. Par... | Implement the Python class `ConvGRU` described below.
Class description:
Implement the ConvGRU class.
Method signatures and docstrings:
- def __init__(self, input_size, hidden_sizes, kernel_sizes, n_layers): Generates a multi-layer convolutional GRU. Preserves spatial dimensions across cells, only altering depth. Par... | 3efa944031e65d4a9fc6dee27381e73e446bb16d | <|skeleton|>
class ConvGRU:
def __init__(self, input_size, hidden_sizes, kernel_sizes, n_layers):
"""Generates a multi-layer convolutional GRU. Preserves spatial dimensions across cells, only altering depth. Parameters ---------- input_size : integer. depth dimension of input tensors. hidden_sizes : intege... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ConvGRU:
def __init__(self, input_size, hidden_sizes, kernel_sizes, n_layers):
"""Generates a multi-layer convolutional GRU. Preserves spatial dimensions across cells, only altering depth. Parameters ---------- input_size : integer. depth dimension of input tensors. hidden_sizes : integer or list. dep... | the_stack_v2_python_sparse | gen_models/convgru.py | KamyarGh/rl_swiss | train | 61 | |
b0c7a2a0e4d9995cd85ca72d42762fd98785276b | [
"tempDictionary = {}\ntempDictionary['date'] = datetime.datetime.utcnow()\ntempDictionary['state'] = 'Confirm'\ntempDictionary['material'] = raw_material\ntempDictionary['name'] = new_product\ntempDictionary['quantity'] = quantity\ntempDictionary['price'] = price\norder = list(sorted(self.manufacture_details.keys()... | <|body_start_0|>
tempDictionary = {}
tempDictionary['date'] = datetime.datetime.utcnow()
tempDictionary['state'] = 'Confirm'
tempDictionary['material'] = raw_material
tempDictionary['name'] = new_product
tempDictionary['quantity'] = quantity
tempDictionary['price'... | It is used to manufacture products | Manufacture | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Manufacture:
"""It is used to manufacture products"""
def create_manufacture_order(self, new_product, raw_material, quantity, price):
"""func :- Manufactures new product. params :- new product name - string params :- raw material name and quantity - dictionary params :- quantity - in... | stack_v2_sparse_classes_75kplus_train_066664 | 2,479 | no_license | [
{
"docstring": "func :- Manufactures new product. params :- new product name - string params :- raw material name and quantity - dictionary params :- quantity - integer returns :- Manufacture order number",
"name": "create_manufacture_order",
"signature": "def create_manufacture_order(self, new_product,... | 3 | stack_v2_sparse_classes_30k_train_043063 | Implement the Python class `Manufacture` described below.
Class description:
It is used to manufacture products
Method signatures and docstrings:
- def create_manufacture_order(self, new_product, raw_material, quantity, price): func :- Manufactures new product. params :- new product name - string params :- raw materi... | Implement the Python class `Manufacture` described below.
Class description:
It is used to manufacture products
Method signatures and docstrings:
- def create_manufacture_order(self, new_product, raw_material, quantity, price): func :- Manufactures new product. params :- new product name - string params :- raw materi... | 08668c834bdb4aee3abafdedc9126bba7aa041b8 | <|skeleton|>
class Manufacture:
"""It is used to manufacture products"""
def create_manufacture_order(self, new_product, raw_material, quantity, price):
"""func :- Manufactures new product. params :- new product name - string params :- raw material name and quantity - dictionary params :- quantity - in... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Manufacture:
"""It is used to manufacture products"""
def create_manufacture_order(self, new_product, raw_material, quantity, price):
"""func :- Manufactures new product. params :- new product name - string params :- raw material name and quantity - dictionary params :- quantity - integer returns... | the_stack_v2_python_sparse | Test1/manufacture.py | maulikb-emipro/Python-Training | train | 0 |
02b5fe596c17b30103bbad8534de74176de1dcb2 | [
"idx_sorted = sorted(range(len(height)), key=lambda x: (height[x], -weight[x]))\nweight_sorted = [weight[idx] for idx in idx_sorted]\ndp = [0] * len(weight_sorted)\ndp[0] = 1\nmax_ans = 0\nfor i in range(1, len(weight_sorted)):\n max_val = 0\n for j in range(i):\n if weight_sorted[i] > weight_sorted[j]... | <|body_start_0|>
idx_sorted = sorted(range(len(height)), key=lambda x: (height[x], -weight[x]))
weight_sorted = [weight[idx] for idx in idx_sorted]
dp = [0] * len(weight_sorted)
dp[0] = 1
max_ans = 0
for i in range(1, len(weight_sorted)):
max_val = 0
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def bestSeqAtIndex(self, height, weight):
"""input| height: List[int], weight: List[int] output| int"""
<|body_0|>
def bestSeqAtIndex_bisect(self, height, weight):
"""input| height: List[int], weight: List[int] output| int"""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_75kplus_train_066665 | 3,006 | no_license | [
{
"docstring": "input| height: List[int], weight: List[int] output| int",
"name": "bestSeqAtIndex",
"signature": "def bestSeqAtIndex(self, height, weight)"
},
{
"docstring": "input| height: List[int], weight: List[int] output| int",
"name": "bestSeqAtIndex_bisect",
"signature": "def best... | 2 | stack_v2_sparse_classes_30k_test_002533 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def bestSeqAtIndex(self, height, weight): input| height: List[int], weight: List[int] output| int
- def bestSeqAtIndex_bisect(self, height, weight): input| height: List[int], wei... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def bestSeqAtIndex(self, height, weight): input| height: List[int], weight: List[int] output| int
- def bestSeqAtIndex_bisect(self, height, weight): input| height: List[int], wei... | 8290ad1c763d9f7c7f7bed63426b4769b34fd2fc | <|skeleton|>
class Solution:
def bestSeqAtIndex(self, height, weight):
"""input| height: List[int], weight: List[int] output| int"""
<|body_0|>
def bestSeqAtIndex_bisect(self, height, weight):
"""input| height: List[int], weight: List[int] output| int"""
<|body_1|>
<|end_skele... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def bestSeqAtIndex(self, height, weight):
"""input| height: List[int], weight: List[int] output| int"""
idx_sorted = sorted(range(len(height)), key=lambda x: (height[x], -weight[x]))
weight_sorted = [weight[idx] for idx in idx_sorted]
dp = [0] * len(weight_sorted)
... | the_stack_v2_python_sparse | sort_mian17_08_bestSeqAtIndex.py | screnary/Algorithm_python | train | 0 | |
3dd5fa027d9ced006a4c21257c1b9de26b552a9c | [
"self.queryFile = os.path.realpath(queryFile)\nself.resultsDir = os.path.realpath(resultsDir)\nself.evalue = 0.05\nif os.path.isdir(resultsDir) == False or len(os.listdir(resultsDir)) == 0:\n raise Exception('The results directory does not exist')",
"print('...parsing', resultsFilePath)\nparser = ParseBlast(re... | <|body_start_0|>
self.queryFile = os.path.realpath(queryFile)
self.resultsDir = os.path.realpath(resultsDir)
self.evalue = 0.05
if os.path.isdir(resultsDir) == False or len(os.listdir(resultsDir)) == 0:
raise Exception('The results directory does not exist')
<|end_body_0|>
<... | ParseParallelBlast | [
"BSD-3-Clause",
"LicenseRef-scancode-public-domain",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParseParallelBlast:
def __init__(self, queryFile, resultsDir=os.path.join('.', 'cluster')):
"""Constructor queryFile - is a fasta file of sequences resultsDir - is a directory that is purged and filled"""
<|body_0|>
def parse_file(self, resultsFilePath):
"""use Parse... | stack_v2_sparse_classes_75kplus_train_066666 | 3,238 | permissive | [
{
"docstring": "Constructor queryFile - is a fasta file of sequences resultsDir - is a directory that is purged and filled",
"name": "__init__",
"signature": "def __init__(self, queryFile, resultsDir=os.path.join('.', 'cluster'))"
},
{
"docstring": "use ParseBlast to parse a given xml formatted ... | 3 | null | Implement the Python class `ParseParallelBlast` described below.
Class description:
Implement the ParseParallelBlast class.
Method signatures and docstrings:
- def __init__(self, queryFile, resultsDir=os.path.join('.', 'cluster')): Constructor queryFile - is a fasta file of sequences resultsDir - is a directory that ... | Implement the Python class `ParseParallelBlast` described below.
Class description:
Implement the ParseParallelBlast class.
Method signatures and docstrings:
- def __init__(self, queryFile, resultsDir=os.path.join('.', 'cluster')): Constructor queryFile - is a fasta file of sequences resultsDir - is a directory that ... | a343aff9b833979b4f5d4ba6d16fc2b65d8ccfc1 | <|skeleton|>
class ParseParallelBlast:
def __init__(self, queryFile, resultsDir=os.path.join('.', 'cluster')):
"""Constructor queryFile - is a fasta file of sequences resultsDir - is a directory that is purged and filled"""
<|body_0|>
def parse_file(self, resultsFilePath):
"""use Parse... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class ParseParallelBlast:
def __init__(self, queryFile, resultsDir=os.path.join('.', 'cluster')):
"""Constructor queryFile - is a fasta file of sequences resultsDir - is a directory that is purged and filled"""
self.queryFile = os.path.realpath(queryFile)
self.resultsDir = os.path.realpath(r... | the_stack_v2_python_sparse | htsint/blast/ParseParallelBlast.py | changanla/htsint | train | 0 | |
00c14cb5bd0632b595243826eff880a6fc1add65 | [
"self.pump = Pump('127.0.0.1', 8000)\nself.decider = Decider(100, 0.05)\nself.sensor = Sensor('127.0.0.1', '8001')\nself.controller = Controller(self.sensor, self.pump, self.decider)\nself.actions = self.controller.actions",
"self.assertEqual(self.decider.decide(90, self.actions['PUMP_OFF'], self.actions), self.a... | <|body_start_0|>
self.pump = Pump('127.0.0.1', 8000)
self.decider = Decider(100, 0.05)
self.sensor = Sensor('127.0.0.1', '8001')
self.controller = Controller(self.sensor, self.pump, self.decider)
self.actions = self.controller.actions
<|end_body_0|>
<|body_start_1|>
self... | Unit tests for the Decider class | DeciderTests | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DeciderTests:
"""Unit tests for the Decider class"""
def setUp(self):
"""setup"""
<|body_0|>
def test_decider(self):
"""Decider tests"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.pump = Pump('127.0.0.1', 8000)
self.decider = Deci... | stack_v2_sparse_classes_75kplus_train_066667 | 3,712 | no_license | [
{
"docstring": "setup",
"name": "setUp",
"signature": "def setUp(self)"
},
{
"docstring": "Decider tests",
"name": "test_decider",
"signature": "def test_decider(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_046628 | Implement the Python class `DeciderTests` described below.
Class description:
Unit tests for the Decider class
Method signatures and docstrings:
- def setUp(self): setup
- def test_decider(self): Decider tests | Implement the Python class `DeciderTests` described below.
Class description:
Unit tests for the Decider class
Method signatures and docstrings:
- def setUp(self): setup
- def test_decider(self): Decider tests
<|skeleton|>
class DeciderTests:
"""Unit tests for the Decider class"""
def setUp(self):
"... | 263685ca90110609bfd05d621516727f8cd0028f | <|skeleton|>
class DeciderTests:
"""Unit tests for the Decider class"""
def setUp(self):
"""setup"""
<|body_0|>
def test_decider(self):
"""Decider tests"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DeciderTests:
"""Unit tests for the Decider class"""
def setUp(self):
"""setup"""
self.pump = Pump('127.0.0.1', 8000)
self.decider = Decider(100, 0.05)
self.sensor = Sensor('127.0.0.1', '8001')
self.controller = Controller(self.sensor, self.pump, self.decider)
... | the_stack_v2_python_sparse | students/msirisha/lesson06/water-regulation/waterregulation/tests.py | aurel1212/Sp2018-Online | train | 0 |
b9cc01d7479efafc02f59f278ea99e283ab9ad3d | [
"super(PublicAPIv3, self).__init__(**connkw)\nself.pairs = pairs\nif not self.pairs:\n self.pairs = self.call('info')['pairs'].items()\nif not isinstance(self.pairs, str):\n self.pairs = '-'.join(self.pairs)",
"if method == 'info':\n url = '/api/3/{}'.format(method)\nelse:\n url = '/api/3/{}/{}'.forma... | <|body_start_0|>
super(PublicAPIv3, self).__init__(**connkw)
self.pairs = pairs
if not self.pairs:
self.pairs = self.call('info')['pairs'].items()
if not isinstance(self.pairs, str):
self.pairs = '-'.join(self.pairs)
<|end_body_0|>
<|body_start_1|>
if met... | BTC-E Public API v3 <https://btc-e.com/api/3/docs>. | PublicAPIv3 | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PublicAPIv3:
"""BTC-E Public API v3 <https://btc-e.com/api/3/docs>."""
def __init__(self, *pairs, **connkw):
"""Initialization of the BTC-E Public API v3. @param *pairs: [btc_usd[-btc_rur[-...]]] or arguments @param **connkw: ... (see: 'BTCEConnection' class)"""
<|body_0|>
... | stack_v2_sparse_classes_75kplus_train_066668 | 12,827 | permissive | [
{
"docstring": "Initialization of the BTC-E Public API v3. @param *pairs: [btc_usd[-btc_rur[-...]]] or arguments @param **connkw: ... (see: 'BTCEConnection' class)",
"name": "__init__",
"signature": "def __init__(self, *pairs, **connkw)"
},
{
"docstring": "Create query to the BTC-E Public API v3... | 2 | stack_v2_sparse_classes_30k_train_007536 | Implement the Python class `PublicAPIv3` described below.
Class description:
BTC-E Public API v3 <https://btc-e.com/api/3/docs>.
Method signatures and docstrings:
- def __init__(self, *pairs, **connkw): Initialization of the BTC-E Public API v3. @param *pairs: [btc_usd[-btc_rur[-...]]] or arguments @param **connkw: .... | Implement the Python class `PublicAPIv3` described below.
Class description:
BTC-E Public API v3 <https://btc-e.com/api/3/docs>.
Method signatures and docstrings:
- def __init__(self, *pairs, **connkw): Initialization of the BTC-E Public API v3. @param *pairs: [btc_usd[-btc_rur[-...]]] or arguments @param **connkw: .... | b4910e26abe849b42ab932af805d01ee435320fa | <|skeleton|>
class PublicAPIv3:
"""BTC-E Public API v3 <https://btc-e.com/api/3/docs>."""
def __init__(self, *pairs, **connkw):
"""Initialization of the BTC-E Public API v3. @param *pairs: [btc_usd[-btc_rur[-...]]] or arguments @param **connkw: ... (see: 'BTCEConnection' class)"""
<|body_0|>
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PublicAPIv3:
"""BTC-E Public API v3 <https://btc-e.com/api/3/docs>."""
def __init__(self, *pairs, **connkw):
"""Initialization of the BTC-E Public API v3. @param *pairs: [btc_usd[-btc_rur[-...]]] or arguments @param **connkw: ... (see: 'BTCEConnection' class)"""
super(PublicAPIv3, self)._... | the_stack_v2_python_sparse | server/btcelib.py | ErDmKo/trade-bot | train | 1 |
8540a210be87afc9bdffa6fc858fdf078ac941c5 | [
"if img.ndim == 5:\n img = img.view(-1, *img.shape[2:])\n gt_label = gt_label.view(-1)\nx = self.extract_feat(img)\nhead_outputs = self.head.forward_train(x[0])\nlosses = dict()\nreid_loss = self.head.loss(gt_label, *head_outputs)\nlosses.update(reid_loss)\nreturn losses",
"if img.nelement() > 0:\n x = s... | <|body_start_0|>
if img.ndim == 5:
img = img.view(-1, *img.shape[2:])
gt_label = gt_label.view(-1)
x = self.extract_feat(img)
head_outputs = self.head.forward_train(x[0])
losses = dict()
reid_loss = self.head.loss(gt_label, *head_outputs)
losses.up... | Base class for re-identification. | BaseReID | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BaseReID:
"""Base class for re-identification."""
def forward_train(self, img, gt_label, **kwargs):
""""Training forward function."""
<|body_0|>
def simple_test(self, img, **kwargs):
"""Test without augmentation."""
<|body_1|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_75kplus_train_066669 | 1,292 | permissive | [
{
"docstring": "\"Training forward function.",
"name": "forward_train",
"signature": "def forward_train(self, img, gt_label, **kwargs)"
},
{
"docstring": "Test without augmentation.",
"name": "simple_test",
"signature": "def simple_test(self, img, **kwargs)"
}
] | 2 | null | Implement the Python class `BaseReID` described below.
Class description:
Base class for re-identification.
Method signatures and docstrings:
- def forward_train(self, img, gt_label, **kwargs): "Training forward function.
- def simple_test(self, img, **kwargs): Test without augmentation. | Implement the Python class `BaseReID` described below.
Class description:
Base class for re-identification.
Method signatures and docstrings:
- def forward_train(self, img, gt_label, **kwargs): "Training forward function.
- def simple_test(self, img, **kwargs): Test without augmentation.
<|skeleton|>
class BaseReID:... | e79491ec8f0b8c86fda947fbaaa824c66ab2a991 | <|skeleton|>
class BaseReID:
"""Base class for re-identification."""
def forward_train(self, img, gt_label, **kwargs):
""""Training forward function."""
<|body_0|>
def simple_test(self, img, **kwargs):
"""Test without augmentation."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BaseReID:
"""Base class for re-identification."""
def forward_train(self, img, gt_label, **kwargs):
""""Training forward function."""
if img.ndim == 5:
img = img.view(-1, *img.shape[2:])
gt_label = gt_label.view(-1)
x = self.extract_feat(img)
head_o... | the_stack_v2_python_sparse | mmtrack/models/reid/base_reid.py | open-mmlab/mmtracking | train | 3,263 |
67347296046b45bd31aeaef3c0ca45b1f6fb8ec3 | [
"self.model = model\nself.beta = beta\nself.S0 = S0\nself.iso = iso",
"odf_matrix = self.model.cache_get('odf_matrix', key=sphere)\nif odf_matrix is None:\n odf_matrix = sfm_design_matrix(sphere, self.model.sphere, self.model.response, mode='odf')\n self.model.cache_set('odf_matrix', key=sphere, value=odf_m... | <|body_start_0|>
self.model = model
self.beta = beta
self.S0 = S0
self.iso = iso
<|end_body_0|>
<|body_start_1|>
odf_matrix = self.model.cache_get('odf_matrix', key=sphere)
if odf_matrix is None:
odf_matrix = sfm_design_matrix(sphere, self.model.sphere, self.... | SparseFascicleFit | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SparseFascicleFit:
def __init__(self, model, beta, S0, iso):
"""Initalize a SparseFascicleFit class instance Parameters ---------- model : a SparseFascicleModel object. beta : ndarray The parameters of fit to data. S0 : ndarray The mean non-diffusion-weighted signal. iso : IsotropicFit c... | stack_v2_sparse_classes_75kplus_train_066670 | 20,499 | permissive | [
{
"docstring": "Initalize a SparseFascicleFit class instance Parameters ---------- model : a SparseFascicleModel object. beta : ndarray The parameters of fit to data. S0 : ndarray The mean non-diffusion-weighted signal. iso : IsotropicFit class instance A representation of the isotropic signal, together with pa... | 3 | stack_v2_sparse_classes_30k_test_002887 | Implement the Python class `SparseFascicleFit` described below.
Class description:
Implement the SparseFascicleFit class.
Method signatures and docstrings:
- def __init__(self, model, beta, S0, iso): Initalize a SparseFascicleFit class instance Parameters ---------- model : a SparseFascicleModel object. beta : ndarra... | Implement the Python class `SparseFascicleFit` described below.
Class description:
Implement the SparseFascicleFit class.
Method signatures and docstrings:
- def __init__(self, model, beta, S0, iso): Initalize a SparseFascicleFit class instance Parameters ---------- model : a SparseFascicleModel object. beta : ndarra... | 3c3acc55de8ba741e673063378e6cbaf10b64c7a | <|skeleton|>
class SparseFascicleFit:
def __init__(self, model, beta, S0, iso):
"""Initalize a SparseFascicleFit class instance Parameters ---------- model : a SparseFascicleModel object. beta : ndarray The parameters of fit to data. S0 : ndarray The mean non-diffusion-weighted signal. iso : IsotropicFit c... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class SparseFascicleFit:
def __init__(self, model, beta, S0, iso):
"""Initalize a SparseFascicleFit class instance Parameters ---------- model : a SparseFascicleModel object. beta : ndarray The parameters of fit to data. S0 : ndarray The mean non-diffusion-weighted signal. iso : IsotropicFit class instance ... | the_stack_v2_python_sparse | env/lib/python3.6/site-packages/dipy/reconst/sfm.py | Raniac/NEURO-LEARN | train | 9 | |
53bb256c7a103a37a3425c7143ff2715d3936639 | [
"content_type = ContentType.objects.get_for_model(model_admin.model)\ntags = TaggedItem.objects.filter(content_type=content_type).values('tag__name').distinct().order_by('tag__name')\ntags_list = []\nfor tag in tags:\n tags_list.append((tag['tag__name'], tag['tag__name']))\nreturn tuple(tags_list)",
"if self.v... | <|body_start_0|>
content_type = ContentType.objects.get_for_model(model_admin.model)
tags = TaggedItem.objects.filter(content_type=content_type).values('tag__name').distinct().order_by('tag__name')
tags_list = []
for tag in tags:
tags_list.append((tag['tag__name'], tag['tag__... | TagsFilter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TagsFilter:
def lookups(self, request, model_admin):
"""Returns a list of tuples. The first element in each tuple is the coded value for the option that will appear in the URL query. The second element is the human-readable name for the option that will appear in the right sidebar."""
... | stack_v2_sparse_classes_75kplus_train_066671 | 9,844 | no_license | [
{
"docstring": "Returns a list of tuples. The first element in each tuple is the coded value for the option that will appear in the URL query. The second element is the human-readable name for the option that will appear in the right sidebar.",
"name": "lookups",
"signature": "def lookups(self, request,... | 2 | stack_v2_sparse_classes_30k_train_004643 | Implement the Python class `TagsFilter` described below.
Class description:
Implement the TagsFilter class.
Method signatures and docstrings:
- def lookups(self, request, model_admin): Returns a list of tuples. The first element in each tuple is the coded value for the option that will appear in the URL query. The se... | Implement the Python class `TagsFilter` described below.
Class description:
Implement the TagsFilter class.
Method signatures and docstrings:
- def lookups(self, request, model_admin): Returns a list of tuples. The first element in each tuple is the coded value for the option that will appear in the URL query. The se... | f2ac4ecc076b223c262f2cde4fa3b35b4a5cd54e | <|skeleton|>
class TagsFilter:
def lookups(self, request, model_admin):
"""Returns a list of tuples. The first element in each tuple is the coded value for the option that will appear in the URL query. The second element is the human-readable name for the option that will appear in the right sidebar."""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TagsFilter:
def lookups(self, request, model_admin):
"""Returns a list of tuples. The first element in each tuple is the coded value for the option that will appear in the URL query. The second element is the human-readable name for the option that will appear in the right sidebar."""
content_... | the_stack_v2_python_sparse | tendenci/apps/perms/admin.py | chendong0444/ams | train | 0 | |
9200670f5aa145cdfc3e09ac977d446ec918501e | [
"if CustomerLogic.is_customer(request) and request.method == 'GET':\n return True\nif obj.stylist == request.user:\n return True\nelse:\n return False",
"if CustomerLogic.is_customer(request) and request.method != 'GET':\n return False\nif request.user.is_anonymous:\n return False\nelse:\n retur... | <|body_start_0|>
if CustomerLogic.is_customer(request) and request.method == 'GET':
return True
if obj.stylist == request.user:
return True
else:
return False
<|end_body_0|>
<|body_start_1|>
if CustomerLogic.is_customer(request) and request.method != ... | Permission for Haircut View - checks for the owner of the haircut. | IsOwnerOfHaircut | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class IsOwnerOfHaircut:
"""Permission for Haircut View - checks for the owner of the haircut."""
def has_object_permission(self, request, view, obj):
"""Returns True if the Stylist is the owner of the haircut. Or if the method is GET and the user is a customer."""
<|body_0|>
d... | stack_v2_sparse_classes_75kplus_train_066672 | 4,431 | no_license | [
{
"docstring": "Returns True if the Stylist is the owner of the haircut. Or if the method is GET and the user is a customer.",
"name": "has_object_permission",
"signature": "def has_object_permission(self, request, view, obj)"
},
{
"docstring": "Returns True if the user is not anonymous.",
"... | 2 | null | Implement the Python class `IsOwnerOfHaircut` described below.
Class description:
Permission for Haircut View - checks for the owner of the haircut.
Method signatures and docstrings:
- def has_object_permission(self, request, view, obj): Returns True if the Stylist is the owner of the haircut. Or if the method is GET... | Implement the Python class `IsOwnerOfHaircut` described below.
Class description:
Permission for Haircut View - checks for the owner of the haircut.
Method signatures and docstrings:
- def has_object_permission(self, request, view, obj): Returns True if the Stylist is the owner of the haircut. Or if the method is GET... | a3d5f0b83afa1b66ad3c3d7665088c88f6f7eb9d | <|skeleton|>
class IsOwnerOfHaircut:
"""Permission for Haircut View - checks for the owner of the haircut."""
def has_object_permission(self, request, view, obj):
"""Returns True if the Stylist is the owner of the haircut. Or if the method is GET and the user is a customer."""
<|body_0|>
d... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class IsOwnerOfHaircut:
"""Permission for Haircut View - checks for the owner of the haircut."""
def has_object_permission(self, request, view, obj):
"""Returns True if the Stylist is the owner of the haircut. Or if the method is GET and the user is a customer."""
if CustomerLogic.is_customer(r... | the_stack_v2_python_sparse | api/permissions.py | eric85254/Clippr | train | 1 |
1d5f1f9def0a3fd4e2a88bb517d31e4cd5c6e885 | [
"dt = self.timestep\nif agent.isCar:\n lon_controller = PIDLongitudinalController(K_P=0.5, K_D=0.1, K_I=0.7, dt=dt)\n lat_controller = PIDLateralController(K_P=0.2, K_D=0.1, K_I=0.0, dt=dt)\nelse:\n lon_controller = PIDLongitudinalController(K_P=0.25, K_D=0.025, K_I=0.0, dt=dt)\n lat_controller = PIDLat... | <|body_start_0|>
dt = self.timestep
if agent.isCar:
lon_controller = PIDLongitudinalController(K_P=0.5, K_D=0.1, K_I=0.7, dt=dt)
lat_controller = PIDLateralController(K_P=0.2, K_D=0.1, K_I=0.0, dt=dt)
else:
lon_controller = PIDLongitudinalController(K_P=0.25, ... | A `Simulation` with a simulator supporting the driving domain. This subclass of `Simulation` provides no special behavior by itself; it just provides convenience methods for creating controllers to be used by `FollowLaneBehavior` and related behaviors, so that the parameters of these controllers can be customized for d... | DrivingSimulation | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DrivingSimulation:
"""A `Simulation` with a simulator supporting the driving domain. This subclass of `Simulation` provides no special behavior by itself; it just provides convenience methods for creating controllers to be used by `FollowLaneBehavior` and related behaviors, so that the parameters... | stack_v2_sparse_classes_75kplus_train_066673 | 3,017 | permissive | [
{
"docstring": "Get longitudinal and lateral controllers for lane following. The default controllers are simple PID controllers with parameters that work reasonably well for cars in simulators with realistic physics. See the classes `PIDLongitudinalController` and `PIDLateralController` for details, and `Newton... | 3 | stack_v2_sparse_classes_30k_train_028503 | Implement the Python class `DrivingSimulation` described below.
Class description:
A `Simulation` with a simulator supporting the driving domain. This subclass of `Simulation` provides no special behavior by itself; it just provides convenience methods for creating controllers to be used by `FollowLaneBehavior` and re... | Implement the Python class `DrivingSimulation` described below.
Class description:
A `Simulation` with a simulator supporting the driving domain. This subclass of `Simulation` provides no special behavior by itself; it just provides convenience methods for creating controllers to be used by `FollowLaneBehavior` and re... | b397042601218ee77c82e3e835fa26820184245e | <|skeleton|>
class DrivingSimulation:
"""A `Simulation` with a simulator supporting the driving domain. This subclass of `Simulation` provides no special behavior by itself; it just provides convenience methods for creating controllers to be used by `FollowLaneBehavior` and related behaviors, so that the parameters... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DrivingSimulation:
"""A `Simulation` with a simulator supporting the driving domain. This subclass of `Simulation` provides no special behavior by itself; it just provides convenience methods for creating controllers to be used by `FollowLaneBehavior` and related behaviors, so that the parameters of these con... | the_stack_v2_python_sparse | src/scenic/domains/driving/simulators.py | BerkeleyLearnVerify/Scenic | train | 207 |
69d86528506dcd6bd4ba6c8b111bf7c5bcc68e39 | [
"self.criteria = got3.manager.TweetCriteria()\nself.manager = got3.manager.TweetManager()\nself.helper = Utility.Helper(rootPath)",
"if username:\n criteria = self.criteria.setUsername(username)\nelse:\n criteria = self.criteria.setQuerySearch(query).setSince(start).setUntil(end).setMaxTweets(maxTweets)\nre... | <|body_start_0|>
self.criteria = got3.manager.TweetCriteria()
self.manager = got3.manager.TweetManager()
self.helper = Utility.Helper(rootPath)
<|end_body_0|>
<|body_start_1|>
if username:
criteria = self.criteria.setUsername(username)
else:
criteria = se... | Use GetOldTweets-python to crawl the Twitter data. | GetTwitterData | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetTwitterData:
"""Use GetOldTweets-python to crawl the Twitter data."""
def __init__(self, rootPath):
"""Initialize the Parameters. Parameters: criteria (object): the criteria object for got module manager (object): the manager object for got module helper (object): the helper objec... | stack_v2_sparse_classes_75kplus_train_066674 | 2,216 | no_license | [
{
"docstring": "Initialize the Parameters. Parameters: criteria (object): the criteria object for got module manager (object): the manager object for got module helper (object): the helper object for Utility.Helper module",
"name": "__init__",
"signature": "def __init__(self, rootPath)"
},
{
"do... | 3 | stack_v2_sparse_classes_30k_train_051592 | Implement the Python class `GetTwitterData` described below.
Class description:
Use GetOldTweets-python to crawl the Twitter data.
Method signatures and docstrings:
- def __init__(self, rootPath): Initialize the Parameters. Parameters: criteria (object): the criteria object for got module manager (object): the manage... | Implement the Python class `GetTwitterData` described below.
Class description:
Use GetOldTweets-python to crawl the Twitter data.
Method signatures and docstrings:
- def __init__(self, rootPath): Initialize the Parameters. Parameters: criteria (object): the criteria object for got module manager (object): the manage... | e2cdf786fd11f0fc3dbd393cad02383d3a206bf7 | <|skeleton|>
class GetTwitterData:
"""Use GetOldTweets-python to crawl the Twitter data."""
def __init__(self, rootPath):
"""Initialize the Parameters. Parameters: criteria (object): the criteria object for got module manager (object): the manager object for got module helper (object): the helper objec... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class GetTwitterData:
"""Use GetOldTweets-python to crawl the Twitter data."""
def __init__(self, rootPath):
"""Initialize the Parameters. Parameters: criteria (object): the criteria object for got module manager (object): the manager object for got module helper (object): the helper object for Utility... | the_stack_v2_python_sparse | Twitter/GetTwitterData.py | sxhmilyoyo/Rudetect34 | train | 0 |
4ce2032791c170146566e578e657e4795bf4e126 | [
"if id is not None:\n self.id = id\nelse:\n Base.__nb_objects += 1\n self.id = Base.__nb_objects",
"if list_dictionaries is None or list_dictionaries == {}:\n return '[]'\nelse:\n return json.dumps(list_dictionaries)",
"file = cls.__name__ + '.json'\nwith open(file, 'w') as ofile:\n if list_ob... | <|body_start_0|>
if id is not None:
self.id = id
else:
Base.__nb_objects += 1
self.id = Base.__nb_objects
<|end_body_0|>
<|body_start_1|>
if list_dictionaries is None or list_dictionaries == {}:
return '[]'
else:
return json.du... | Base class for other classes in project | Base | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Base:
"""Base class for other classes in project"""
def __init__(self, id=None):
"""Initializer for Base class"""
<|body_0|>
def to_json_string(list_dictionaries):
"""Method that returns JSON string representation of dictionary"""
<|body_1|>
def save... | stack_v2_sparse_classes_75kplus_train_066675 | 1,920 | no_license | [
{
"docstring": "Initializer for Base class",
"name": "__init__",
"signature": "def __init__(self, id=None)"
},
{
"docstring": "Method that returns JSON string representation of dictionary",
"name": "to_json_string",
"signature": "def to_json_string(list_dictionaries)"
},
{
"docst... | 6 | stack_v2_sparse_classes_30k_train_000292 | Implement the Python class `Base` described below.
Class description:
Base class for other classes in project
Method signatures and docstrings:
- def __init__(self, id=None): Initializer for Base class
- def to_json_string(list_dictionaries): Method that returns JSON string representation of dictionary
- def save_to_... | Implement the Python class `Base` described below.
Class description:
Base class for other classes in project
Method signatures and docstrings:
- def __init__(self, id=None): Initializer for Base class
- def to_json_string(list_dictionaries): Method that returns JSON string representation of dictionary
- def save_to_... | 10b97c5a938747bbb3df10fd057863c7889415db | <|skeleton|>
class Base:
"""Base class for other classes in project"""
def __init__(self, id=None):
"""Initializer for Base class"""
<|body_0|>
def to_json_string(list_dictionaries):
"""Method that returns JSON string representation of dictionary"""
<|body_1|>
def save... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Base:
"""Base class for other classes in project"""
def __init__(self, id=None):
"""Initializer for Base class"""
if id is not None:
self.id = id
else:
Base.__nb_objects += 1
self.id = Base.__nb_objects
def to_json_string(list_dictionaries)... | the_stack_v2_python_sparse | 0x0C-python-almost_a_circle/models/base.py | ranicholson/holbertonschool-higher_level_programming | train | 0 |
decfd7ec78ab4e5082a1b1d29fa2585ce8da4bb1 | [
"domain = domains.FixedLengthDiscreteDomain(vocab=domains.Vocabulary(tokens=range(3), include_bos=True), length=2)\ntrain_data = np.array([[0, 1], [1, 0]])\ntrain_ds = tf.data.Dataset.from_tensor_slices((train_data,))\neb = evaluation.EmpiricalBaseline(domain, train_ds, alpha=0)\nself.assertAllEqual(eb._empirical_d... | <|body_start_0|>
domain = domains.FixedLengthDiscreteDomain(vocab=domains.Vocabulary(tokens=range(3), include_bos=True), length=2)
train_data = np.array([[0, 1], [1, 0]])
train_ds = tf.data.Dataset.from_tensor_slices((train_data,))
eb = evaluation.EmpiricalBaseline(domain, train_ds, alph... | EvaluationTest | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EvaluationTest:
def test_empirical_baseline_construction(self):
"""Tests that EmpiricalBaseline construction is correct."""
<|body_0|>
def test_empirical_baseline_evaluation(self):
"""Tests that EmpiricalBaseline evaluation is correct."""
<|body_1|>
def ... | stack_v2_sparse_classes_75kplus_train_066676 | 2,681 | permissive | [
{
"docstring": "Tests that EmpiricalBaseline construction is correct.",
"name": "test_empirical_baseline_construction",
"signature": "def test_empirical_baseline_construction(self)"
},
{
"docstring": "Tests that EmpiricalBaseline evaluation is correct.",
"name": "test_empirical_baseline_eval... | 3 | stack_v2_sparse_classes_30k_train_027926 | Implement the Python class `EvaluationTest` described below.
Class description:
Implement the EvaluationTest class.
Method signatures and docstrings:
- def test_empirical_baseline_construction(self): Tests that EmpiricalBaseline construction is correct.
- def test_empirical_baseline_evaluation(self): Tests that Empir... | Implement the Python class `EvaluationTest` described below.
Class description:
Implement the EvaluationTest class.
Method signatures and docstrings:
- def test_empirical_baseline_construction(self): Tests that EmpiricalBaseline construction is correct.
- def test_empirical_baseline_evaluation(self): Tests that Empir... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class EvaluationTest:
def test_empirical_baseline_construction(self):
"""Tests that EmpiricalBaseline construction is correct."""
<|body_0|>
def test_empirical_baseline_evaluation(self):
"""Tests that EmpiricalBaseline evaluation is correct."""
<|body_1|>
def ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EvaluationTest:
def test_empirical_baseline_construction(self):
"""Tests that EmpiricalBaseline construction is correct."""
domain = domains.FixedLengthDiscreteDomain(vocab=domains.Vocabulary(tokens=range(3), include_bos=True), length=2)
train_data = np.array([[0, 1], [1, 0]])
... | the_stack_v2_python_sparse | protein_lm/evaluation_test.py | Jimmy-INL/google-research | train | 1 | |
653e5f4e373186ad630615eb450ef9685c6732e5 | [
"left = 0\nright = len(nums) - 1\nwhile left <= right:\n if nums[left] + nums[right] > target:\n right -= 1\n elif nums[left] + nums[right] < target:\n left += 1\n elif nums[left] + nums[right] == target:\n return [nums[left], nums[right]]\nreturn []",
"num_tar = {target - i for i in... | <|body_start_0|>
left = 0
right = len(nums) - 1
while left <= right:
if nums[left] + nums[right] > target:
right -= 1
elif nums[left] + nums[right] < target:
left += 1
elif nums[left] + nums[right] == target:
ret... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def twoSum(self, nums, target: int):
"""双指针方法，利用有序特性，分别从前后扫描"""
<|body_0|>
def twoSum_hash(self, nums, target: int):
"""利用哈希表复杂度O(n)空间复杂度O(n)"""
<|body_1|>
def twoSum_bin(self, nums, target: int):
"""二分查找解法，复杂度O(nlogn)会超时"""
<|b... | stack_v2_sparse_classes_75kplus_train_066677 | 2,505 | no_license | [
{
"docstring": "双指针方法，利用有序特性，分别从前后扫描",
"name": "twoSum",
"signature": "def twoSum(self, nums, target: int)"
},
{
"docstring": "利用哈希表复杂度O(n)空间复杂度O(n)",
"name": "twoSum_hash",
"signature": "def twoSum_hash(self, nums, target: int)"
},
{
"docstring": "二分查找解法，复杂度O(nlogn)会超时",
"na... | 4 | stack_v2_sparse_classes_30k_train_034701 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, nums, target: int): 双指针方法，利用有序特性，分别从前后扫描
- def twoSum_hash(self, nums, target: int): 利用哈希表复杂度O(n)空间复杂度O(n)
- def twoSum_bin(self, nums, target: int): 二分查找解法，复杂度O... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSum(self, nums, target: int): 双指针方法，利用有序特性，分别从前后扫描
- def twoSum_hash(self, nums, target: int): 利用哈希表复杂度O(n)空间复杂度O(n)
- def twoSum_bin(self, nums, target: int): 二分查找解法，复杂度O... | c9eed637887753eb28d78cf252ea3763231e23a2 | <|skeleton|>
class Solution:
def twoSum(self, nums, target: int):
"""双指针方法，利用有序特性，分别从前后扫描"""
<|body_0|>
def twoSum_hash(self, nums, target: int):
"""利用哈希表复杂度O(n)空间复杂度O(n)"""
<|body_1|>
def twoSum_bin(self, nums, target: int):
"""二分查找解法，复杂度O(nlogn)会超时"""
<|b... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def twoSum(self, nums, target: int):
"""双指针方法，利用有序特性，分别从前后扫描"""
left = 0
right = len(nums) - 1
while left <= right:
if nums[left] + nums[right] > target:
right -= 1
elif nums[left] + nums[right] < target:
left +=... | the_stack_v2_python_sparse | CODE/剑指 Offer 57. 和为s的两个数字.py | moshlwx/leetcode | train | 5 | |
a28dc7f61ec7a6be90ac4aaacef76a6046b7000a | [
"super(EncoderRNN, self).__init__()\nself.hidden_size = hidden_size\nself.input_size = input_size\nself.num_directions = 1\nif bidirectional:\n self.num_directions = 2\nself.num_layers = n_layers\nself.batch_size = batch_size\nself.embedding = backend.nn.Embedding(input_size, hidden_size, padding_idx=padding_ind... | <|body_start_0|>
super(EncoderRNN, self).__init__()
self.hidden_size = hidden_size
self.input_size = input_size
self.num_directions = 1
if bidirectional:
self.num_directions = 2
self.num_layers = n_layers
self.batch_size = batch_size
self.embed... | EncoderRNN | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncoderRNN:
def __init__(self, input_size: int, hidden_size: int, bidirectional: bool, n_layers: int=1, batch_size: int=1, padding_index=-1):
""":param input_size: the input size of the encoder which is expected to be the size of the source vocabulary :param hidden_size: the output size ... | stack_v2_sparse_classes_75kplus_train_066678 | 2,681 | permissive | [
{
"docstring": ":param input_size: the input size of the encoder which is expected to be the size of the source vocabulary :param hidden_size: the output size of the encoder hidden layer which is used as input in the decoder :param bidirectional: a flag indicating whether the encoder has been operating bidirect... | 3 | stack_v2_sparse_classes_30k_train_038475 | Implement the Python class `EncoderRNN` described below.
Class description:
Implement the EncoderRNN class.
Method signatures and docstrings:
- def __init__(self, input_size: int, hidden_size: int, bidirectional: bool, n_layers: int=1, batch_size: int=1, padding_index=-1): :param input_size: the input size of the enc... | Implement the Python class `EncoderRNN` described below.
Class description:
Implement the EncoderRNN class.
Method signatures and docstrings:
- def __init__(self, input_size: int, hidden_size: int, bidirectional: bool, n_layers: int=1, batch_size: int=1, padding_index=-1): :param input_size: the input size of the enc... | 0f61fac7a8decccd30c622b2080961ed7fec733f | <|skeleton|>
class EncoderRNN:
def __init__(self, input_size: int, hidden_size: int, bidirectional: bool, n_layers: int=1, batch_size: int=1, padding_index=-1):
""":param input_size: the input size of the encoder which is expected to be the size of the source vocabulary :param hidden_size: the output size ... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class EncoderRNN:
def __init__(self, input_size: int, hidden_size: int, bidirectional: bool, n_layers: int=1, batch_size: int=1, padding_index=-1):
""":param input_size: the input size of the encoder which is expected to be the size of the source vocabulary :param hidden_size: the output size of the encoder... | the_stack_v2_python_sparse | src/translate/learning/modules/rnn/encoder.py | py4/SFUTranslate | train | 0 | |
292cc44589b94002f3d30c5cbac43bd23454bdfe | [
"N = len(points)\nans = float('-inf')\nq = deque()\nfor xj, yj in points:\n while q and xj - q[0][1] > k:\n q.popleft()\n if q:\n ans = max(ans, q[0][0] + yj + xj)\n while q and q[-1][0] < yj - xj:\n q.pop()\n q.append((yj - xj, xj))\nreturn ans",
"ans = float('-inf')\nN = len(poi... | <|body_start_0|>
N = len(points)
ans = float('-inf')
q = deque()
for xj, yj in points:
while q and xj - q[0][1] > k:
q.popleft()
if q:
ans = max(ans, q[0][0] + yj + xj)
while q and q[-1][0] < yj - xj:
q.p... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMaxValueOfEquation(self, points: List[List[int]], k: int) -> int:
"""yi + yj + |xi - xj| = (yi - xi) + (yj + xj) stack를 쓰면서 yi - xi 값을 작아지는 값만 저장해나아가고, 큰값은 이전값들을 덮어버림. 비교는 맨앞에 값과만 비교함. # O(N) / O(N) REMIND: Trapping rain water 방법을 쓰는 문제."""
<|body_0|>
def f... | stack_v2_sparse_classes_75kplus_train_066679 | 1,404 | no_license | [
{
"docstring": "yi + yj + |xi - xj| = (yi - xi) + (yj + xj) stack를 쓰면서 yi - xi 값을 작아지는 값만 저장해나아가고, 큰값은 이전값들을 덮어버림. 비교는 맨앞에 값과만 비교함. # O(N) / O(N) REMIND: Trapping rain water 방법을 쓰는 문제.",
"name": "findMaxValueOfEquation",
"signature": "def findMaxValueOfEquation(self, points: List[List[int]], k: int) -> ... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMaxValueOfEquation(self, points: List[List[int]], k: int) -> int: yi + yj + |xi - xj| = (yi - xi) + (yj + xj) stack를 쓰면서 yi - xi 값을 작아지는 값만 저장해나아가고, 큰값은 이전값들을 덮어버림. 비교는 맨... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMaxValueOfEquation(self, points: List[List[int]], k: int) -> int: yi + yj + |xi - xj| = (yi - xi) + (yj + xj) stack를 쓰면서 yi - xi 값을 작아지는 값만 저장해나아가고, 큰값은 이전값들을 덮어버림. 비교는 맨... | c26aef2a59e5cc2d9b0658b9c7386a43267ff8a1 | <|skeleton|>
class Solution:
def findMaxValueOfEquation(self, points: List[List[int]], k: int) -> int:
"""yi + yj + |xi - xj| = (yi - xi) + (yj + xj) stack를 쓰면서 yi - xi 값을 작아지는 값만 저장해나아가고, 큰값은 이전값들을 덮어버림. 비교는 맨앞에 값과만 비교함. # O(N) / O(N) REMIND: Trapping rain water 방법을 쓰는 문제."""
<|body_0|>
def f... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def findMaxValueOfEquation(self, points: List[List[int]], k: int) -> int:
"""yi + yj + |xi - xj| = (yi - xi) + (yj + xj) stack를 쓰면서 yi - xi 값을 작아지는 값만 저장해나아가고, 큰값은 이전값들을 덮어버림. 비교는 맨앞에 값과만 비교함. # O(N) / O(N) REMIND: Trapping rain water 방법을 쓰는 문제."""
N = len(points)
ans = float... | the_stack_v2_python_sparse | Leetcode/1499.py | hanwgyu/algorithm_problem_solving | train | 5 | |
dc7c082da76ead298ccbcb1cac104e2f0ae5a092 | [
"if not a:\n return 0\np = deque()\nq = deque()\nt = float('-inf')\nm = float('-inf')\nn = len(a)\nfor i in range(0, n, 1):\n if not q or a[i] > q[-1]:\n p.append(i)\n q.append(a[i])\n elif a[i] < q[-1]:\n while q and a[i] < q[-1]:\n x = p.pop()\n y = q.pop()\n ... | <|body_start_0|>
if not a:
return 0
p = deque()
q = deque()
t = float('-inf')
m = float('-inf')
n = len(a)
for i in range(0, n, 1):
if not q or a[i] > q[-1]:
p.append(i)
q.append(a[i])
elif a[i] <... | Iteration over all array elements. Interpolates greedy algorithm. Reference: https://www.youtube.com/watch?v=VNbkzsnllsU Time complexity: O(n) - Iterate over all array indicies and collected index-height pairs Space complexity: O(n) - Amortized collect all array elements and indicies in stacks | Solution | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
"""Iteration over all array elements. Interpolates greedy algorithm. Reference: https://www.youtube.com/watch?v=VNbkzsnllsU Time complexity: O(n) - Iterate over all array indicies and collected index-height pairs Space complexity: O(n) - Amortized collect all array elements and indicies... | stack_v2_sparse_classes_75kplus_train_066680 | 4,337 | permissive | [
{
"docstring": "Determines area of maximum rectangle in histogram. :param list[int] a: list of height values in histogram :return: area of maximum rectangle :rtype: int",
"name": "largest_rectangle_area",
"signature": "def largest_rectangle_area(self, a)"
},
{
"docstring": "Calculates maximum ar... | 2 | stack_v2_sparse_classes_30k_train_039213 | Implement the Python class `Solution` described below.
Class description:
Iteration over all array elements. Interpolates greedy algorithm. Reference: https://www.youtube.com/watch?v=VNbkzsnllsU Time complexity: O(n) - Iterate over all array indicies and collected index-height pairs Space complexity: O(n) - Amortized ... | Implement the Python class `Solution` described below.
Class description:
Iteration over all array elements. Interpolates greedy algorithm. Reference: https://www.youtube.com/watch?v=VNbkzsnllsU Time complexity: O(n) - Iterate over all array indicies and collected index-height pairs Space complexity: O(n) - Amortized ... | 69f90877c5466927e8b081c4268cbcda074813ec | <|skeleton|>
class Solution:
"""Iteration over all array elements. Interpolates greedy algorithm. Reference: https://www.youtube.com/watch?v=VNbkzsnllsU Time complexity: O(n) - Iterate over all array indicies and collected index-height pairs Space complexity: O(n) - Amortized collect all array elements and indicies... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
"""Iteration over all array elements. Interpolates greedy algorithm. Reference: https://www.youtube.com/watch?v=VNbkzsnllsU Time complexity: O(n) - Iterate over all array indicies and collected index-height pairs Space complexity: O(n) - Amortized collect all array elements and indicies in stacks"""... | the_stack_v2_python_sparse | 0084_largest_rectangle_histogram/python_source.py | arthurdysart/LeetCode | train | 0 |
fb03ecb94a86755265923fb1638a6c57a51e1b70 | [
"for filepaths in trainfiles:\n with open(filepaths, 'r') as text:\n sent_list = tokenize_sentence(text.read())\n for sentences in sent_list:\n word_list = sentence_to_word(sentences)\n for index, words in enumerate(word_list):\n if words not in self.token_list:... | <|body_start_0|>
for filepaths in trainfiles:
with open(filepaths, 'r') as text:
sent_list = tokenize_sentence(text.read())
for sentences in sent_list:
word_list = sentence_to_word(sentences)
for index, words in enumerate(word_l... | BigramModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BigramModel:
def init(self, trainfiles):
"""builds a bigram language model from the text found in a list of plain text files specified in trainfiles. :param trainfiles: list of filenames, given with absolute paths."""
<|body_0|>
def logprob(self, prior_context, target_word):... | stack_v2_sparse_classes_75kplus_train_066681 | 2,815 | no_license | [
{
"docstring": "builds a bigram language model from the text found in a list of plain text files specified in trainfiles. :param trainfiles: list of filenames, given with absolute paths.",
"name": "init",
"signature": "def init(self, trainfiles)"
},
{
"docstring": "returns the base-2 log probabi... | 2 | stack_v2_sparse_classes_30k_train_038019 | Implement the Python class `BigramModel` described below.
Class description:
Implement the BigramModel class.
Method signatures and docstrings:
- def init(self, trainfiles): builds a bigram language model from the text found in a list of plain text files specified in trainfiles. :param trainfiles: list of filenames, ... | Implement the Python class `BigramModel` described below.
Class description:
Implement the BigramModel class.
Method signatures and docstrings:
- def init(self, trainfiles): builds a bigram language model from the text found in a list of plain text files specified in trainfiles. :param trainfiles: list of filenames, ... | a6e81e33f966a629df6eab3258603a027035db80 | <|skeleton|>
class BigramModel:
def init(self, trainfiles):
"""builds a bigram language model from the text found in a list of plain text files specified in trainfiles. :param trainfiles: list of filenames, given with absolute paths."""
<|body_0|>
def logprob(self, prior_context, target_word):... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class BigramModel:
def init(self, trainfiles):
"""builds a bigram language model from the text found in a list of plain text files specified in trainfiles. :param trainfiles: list of filenames, given with absolute paths."""
for filepaths in trainfiles:
with open(filepaths, 'r') as text:
... | the_stack_v2_python_sparse | Language-Model/build_language_model.py | qiburger/Natural-Language-Processing | train | 1 | |
aec969b731903727efc45465d9e924c0b693a11f | [
"stretch = ell - control_input\nFs = self.params['k'] * stretch\nFd = self.params['c'] * dot_ell\nF = Fs + Fd\nF_rect = F if np.greater_equal(F, 0) else 0\nreturn F_rect",
"stretch = self.get_length(point_pos) - control_input\nif stretch <= 0:\n raise Exception('Negative stretch length, Uf is undefined, exitin... | <|body_start_0|>
stretch = ell - control_input
Fs = self.params['k'] * stretch
Fd = self.params['c'] * dot_ell
F = Fs + Fd
F_rect = F if np.greater_equal(F, 0) else 0
return F_rect
<|end_body_0|>
<|body_start_1|>
stretch = self.get_length(point_pos) - control_inp... | PiecewiseLinearCable3D | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PiecewiseLinearCable3D:
def scalar_force(self, ell, dot_ell, control_input):
"""linear spring force, linear damping force. Input is rest length. But, passed through max(force, 0) to rectify the (final) output force."""
<|body_0|>
def get_Uf(self, point_pos, control_input):
... | stack_v2_sparse_classes_75kplus_train_066682 | 3,747 | no_license | [
{
"docstring": "linear spring force, linear damping force. Input is rest length. But, passed through max(force, 0) to rectify the (final) output force.",
"name": "scalar_force",
"signature": "def scalar_force(self, ell, dot_ell, control_input)"
},
{
"docstring": "It would be hard to implement th... | 4 | null | Implement the Python class `PiecewiseLinearCable3D` described below.
Class description:
Implement the PiecewiseLinearCable3D class.
Method signatures and docstrings:
- def scalar_force(self, ell, dot_ell, control_input): linear spring force, linear damping force. Input is rest length. But, passed through max(force, 0... | Implement the Python class `PiecewiseLinearCable3D` described below.
Class description:
Implement the PiecewiseLinearCable3D class.
Method signatures and docstrings:
- def scalar_force(self, ell, dot_ell, control_input): linear spring force, linear damping force. Input is rest length. But, passed through max(force, 0... | 06f13008c4415e348b4500373152221a2bdc1adf | <|skeleton|>
class PiecewiseLinearCable3D:
def scalar_force(self, ell, dot_ell, control_input):
"""linear spring force, linear damping force. Input is rest length. But, passed through max(force, 0) to rectify the (final) output force."""
<|body_0|>
def get_Uf(self, point_pos, control_input):
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class PiecewiseLinearCable3D:
def scalar_force(self, ell, dot_ell, control_input):
"""linear spring force, linear damping force. Input is rest length. But, passed through max(force, 0) to rectify the (final) output force."""
stretch = ell - control_input
Fs = self.params['k'] * stretch
... | the_stack_v2_python_sparse | python/cable_models/cable_piecewise3D.py | apsabelhaus/cable-slackness-dynamics | train | 0 | |
a9dce177d3cd3af959eb9335d171e07a4e86adef | [
"self._engine = create_engine('sqlite:///a.db')\nBase.metadata.drop_all(self._engine)\nBase.metadata.create_all(self._engine)\nself.__session = None",
"if self.__session is None:\n DBSession = sessionmaker(bind=self._engine)\n self.__session = DBSession()\nreturn self.__session",
"n_user = User(email=emai... | <|body_start_0|>
self._engine = create_engine('sqlite:///a.db')
Base.metadata.drop_all(self._engine)
Base.metadata.create_all(self._engine)
self.__session = None
<|end_body_0|>
<|body_start_1|>
if self.__session is None:
DBSession = sessionmaker(bind=self._engine)
... | Data Base with SQLAlchemy | DB | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DB:
"""Data Base with SQLAlchemy"""
def __init__(self):
"""auto call"""
<|body_0|>
def _session(self):
"""Create session"""
<|body_1|>
def add_user(self, email: str, hashed_password: str) -> User:
"""Add a user instance to the session DB"""
... | stack_v2_sparse_classes_75kplus_train_066683 | 1,908 | no_license | [
{
"docstring": "auto call",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Create session",
"name": "_session",
"signature": "def _session(self)"
},
{
"docstring": "Add a user instance to the session DB",
"name": "add_user",
"signature": "def add... | 5 | stack_v2_sparse_classes_30k_train_032737 | Implement the Python class `DB` described below.
Class description:
Data Base with SQLAlchemy
Method signatures and docstrings:
- def __init__(self): auto call
- def _session(self): Create session
- def add_user(self, email: str, hashed_password: str) -> User: Add a user instance to the session DB
- def find_user_by(... | Implement the Python class `DB` described below.
Class description:
Data Base with SQLAlchemy
Method signatures and docstrings:
- def __init__(self): auto call
- def _session(self): Create session
- def add_user(self, email: str, hashed_password: str) -> User: Add a user instance to the session DB
- def find_user_by(... | 251d28c9b555096c61a7112ada43dc65576d03c5 | <|skeleton|>
class DB:
"""Data Base with SQLAlchemy"""
def __init__(self):
"""auto call"""
<|body_0|>
def _session(self):
"""Create session"""
<|body_1|>
def add_user(self, email: str, hashed_password: str) -> User:
"""Add a user instance to the session DB"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DB:
"""Data Base with SQLAlchemy"""
def __init__(self):
"""auto call"""
self._engine = create_engine('sqlite:///a.db')
Base.metadata.drop_all(self._engine)
Base.metadata.create_all(self._engine)
self.__session = None
def _session(self):
"""Create sessi... | the_stack_v2_python_sparse | 0x08-user_authentication_service/db.py | dgquintero/holbertonschool-web_back_end | train | 0 |
3850c0b40115edd2a99b20cc72cda902cdab49b7 | [
"DBFormatter.__init__(self, logger, dbi)\nself.logger = logger\nself.owner = '%s.' % owner if not owner in ('', '__MYSQL__') else ''\nself.sql = 'UPDATE %sBLOCKS SET OPEN_FOR_WRITING = :open_for_writing , LAST_MODIFIED_BY=:myuser,\\nLAST_MODIFICATION_DATE = :ltime where BLOCK_NAME = :block_name' % self.owner",
"i... | <|body_start_0|>
DBFormatter.__init__(self, logger, dbi)
self.logger = logger
self.owner = '%s.' % owner if not owner in ('', '__MYSQL__') else ''
self.sql = 'UPDATE %sBLOCKS SET OPEN_FOR_WRITING = :open_for_writing , LAST_MODIFIED_BY=:myuser,\nLAST_MODIFICATION_DATE = :ltime where BLOCK... | Block Update Status DAO class. | UpdateStatus | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateStatus:
"""Block Update Status DAO class."""
def __init__(self, logger, dbi, owner):
"""Add schema owner and sql."""
<|body_0|>
def execute(self, conn, block_name, open_for_writing, ltime, transaction=False):
"""for a given file"""
<|body_1|>
<|end... | stack_v2_sparse_classes_75kplus_train_066684 | 1,356 | permissive | [
{
"docstring": "Add schema owner and sql.",
"name": "__init__",
"signature": "def __init__(self, logger, dbi, owner)"
},
{
"docstring": "for a given file",
"name": "execute",
"signature": "def execute(self, conn, block_name, open_for_writing, ltime, transaction=False)"
}
] | 2 | stack_v2_sparse_classes_30k_train_044296 | Implement the Python class `UpdateStatus` described below.
Class description:
Block Update Status DAO class.
Method signatures and docstrings:
- def __init__(self, logger, dbi, owner): Add schema owner and sql.
- def execute(self, conn, block_name, open_for_writing, ltime, transaction=False): for a given file | Implement the Python class `UpdateStatus` described below.
Class description:
Block Update Status DAO class.
Method signatures and docstrings:
- def __init__(self, logger, dbi, owner): Add schema owner and sql.
- def execute(self, conn, block_name, open_for_writing, ltime, transaction=False): for a given file
<|skel... | 14df8bbe8ee8f874fe423399b18afef911fe78c7 | <|skeleton|>
class UpdateStatus:
"""Block Update Status DAO class."""
def __init__(self, logger, dbi, owner):
"""Add schema owner and sql."""
<|body_0|>
def execute(self, conn, block_name, open_for_writing, ltime, transaction=False):
"""for a given file"""
<|body_1|>
<|end... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class UpdateStatus:
"""Block Update Status DAO class."""
def __init__(self, logger, dbi, owner):
"""Add schema owner and sql."""
DBFormatter.__init__(self, logger, dbi)
self.logger = logger
self.owner = '%s.' % owner if not owner in ('', '__MYSQL__') else ''
self.sql = '... | the_stack_v2_python_sparse | Server/Python/src/dbs/dao/Oracle/Block/UpdateStatus.py | vkuznet/DBS | train | 0 |
8117d728d2792f5e316aaffed7e09c5954657638 | [
"def bsearch(wanted):\n start = 0\n end = len(numbers) - 1\n while start + 1 < end:\n mid = start + (end - start) / 2\n if numbers[mid] == wanted:\n return mid\n elif numbers[mid] > wanted:\n end = mid\n else:\n start = mid\n if numbers[start]... | <|body_start_0|>
def bsearch(wanted):
start = 0
end = len(numbers) - 1
while start + 1 < end:
mid = start + (end - start) / 2
if numbers[mid] == wanted:
return mid
elif numbers[mid] > wanted:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def twoSumBinarySearch(self, numbers, target):
""":type numbers: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def twoSum(self, numbers, target):
""":type numbers: List[int] :type target: int :rtype: List[int]"""
<|body_1|>
<|end_skel... | stack_v2_sparse_classes_75kplus_train_066685 | 2,237 | no_license | [
{
"docstring": ":type numbers: List[int] :type target: int :rtype: List[int]",
"name": "twoSumBinarySearch",
"signature": "def twoSumBinarySearch(self, numbers, target)"
},
{
"docstring": ":type numbers: List[int] :type target: int :rtype: List[int]",
"name": "twoSum",
"signature": "def ... | 2 | stack_v2_sparse_classes_30k_train_014841 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSumBinarySearch(self, numbers, target): :type numbers: List[int] :type target: int :rtype: List[int]
- def twoSum(self, numbers, target): :type numbers: List[int] :type ta... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def twoSumBinarySearch(self, numbers, target): :type numbers: List[int] :type target: int :rtype: List[int]
- def twoSum(self, numbers, target): :type numbers: List[int] :type ta... | d1666d44226274f13af25cf878cd63a24e1c5528 | <|skeleton|>
class Solution:
def twoSumBinarySearch(self, numbers, target):
""":type numbers: List[int] :type target: int :rtype: List[int]"""
<|body_0|>
def twoSum(self, numbers, target):
""":type numbers: List[int] :type target: int :rtype: List[int]"""
<|body_1|>
<|end_skel... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def twoSumBinarySearch(self, numbers, target):
""":type numbers: List[int] :type target: int :rtype: List[int]"""
def bsearch(wanted):
start = 0
end = len(numbers) - 1
while start + 1 < end:
mid = start + (end - start) / 2
... | the_stack_v2_python_sparse | DP/LeetCode167_TwoSumII_InputArrayIsSorted.py | rexhzhang/LeetCodeProbelms | train | 0 | |
88aed54edc0b139701b0940f0d2a45156f248298 | [
"article = self.get_object()\narticle.like(request.user)\nreturn Response(self.get_response('You like this article.'), status=status.HTTP_201_CREATED)",
"article = self.get_object()\narticle.un_like(request.user)\nreturn Response(self.get_response('You no longer like this article.'), status=status.HTTP_200_OK)"
] | <|body_start_0|>
article = self.get_object()
article.like(request.user)
return Response(self.get_response('You like this article.'), status=status.HTTP_201_CREATED)
<|end_body_0|>
<|body_start_1|>
article = self.get_object()
article.un_like(request.user)
return Response(... | This view enables liking and un-liking articles. | LikeAPIView | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LikeAPIView:
"""This view enables liking and un-liking articles."""
def post(self, request, **kwargs):
"""Like an article."""
<|body_0|>
def delete(self, request, **kwargs):
"""Un-like an article."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_75kplus_train_066686 | 34,279 | permissive | [
{
"docstring": "Like an article.",
"name": "post",
"signature": "def post(self, request, **kwargs)"
},
{
"docstring": "Un-like an article.",
"name": "delete",
"signature": "def delete(self, request, **kwargs)"
}
] | 2 | stack_v2_sparse_classes_30k_train_048927 | Implement the Python class `LikeAPIView` described below.
Class description:
This view enables liking and un-liking articles.
Method signatures and docstrings:
- def post(self, request, **kwargs): Like an article.
- def delete(self, request, **kwargs): Un-like an article. | Implement the Python class `LikeAPIView` described below.
Class description:
This view enables liking and un-liking articles.
Method signatures and docstrings:
- def post(self, request, **kwargs): Like an article.
- def delete(self, request, **kwargs): Un-like an article.
<|skeleton|>
class LikeAPIView:
"""This ... | 20993253c2fb72608f21e2a19e999fbd85db904d | <|skeleton|>
class LikeAPIView:
"""This view enables liking and un-liking articles."""
def post(self, request, **kwargs):
"""Like an article."""
<|body_0|>
def delete(self, request, **kwargs):
"""Un-like an article."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class LikeAPIView:
"""This view enables liking and un-liking articles."""
def post(self, request, **kwargs):
"""Like an article."""
article = self.get_object()
article.like(request.user)
return Response(self.get_response('You like this article.'), status=status.HTTP_201_CREATED)... | the_stack_v2_python_sparse | authors/apps/articles/views.py | andela/ah-code-blooded | train | 3 |
c39c395f30e35b9fa92d1dd9c556153e9b8ddf5c | [
"NamedObject.__init__(self, root, definitions)\npmd = Metadata()\npmd.wrappers = dict(element=repr, type=repr)\nself.__metadata__.__print__ = pmd\ntns = definitions.tns\nself.element = self.__getref('element', tns)\nself.type = self.__getref('type', tns)",
"s = self.root.get(a)\nif s is None:\n return s\nelse:... | <|body_start_0|>
NamedObject.__init__(self, root, definitions)
pmd = Metadata()
pmd.wrappers = dict(element=repr, type=repr)
self.__metadata__.__print__ = pmd
tns = definitions.tns
self.element = self.__getref('element', tns)
self.type = self.__getref('type', tns)... | Represents <message><part/></message>. @ivar element: The value of the {element} attribute. Stored as a I{qref} as converted by L{suds.xsd.qualify}. @type element: str @ivar type: The value of the {type} attribute. Stored as a I{qref} as converted by L{suds.xsd.qualify}. @type type: str | Part | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Part:
"""Represents <message><part/></message>. @ivar element: The value of the {element} attribute. Stored as a I{qref} as converted by L{suds.xsd.qualify}. @type element: str @ivar type: The value of the {type} attribute. Stored as a I{qref} as converted by L{suds.xsd.qualify}. @type type: str"... | stack_v2_sparse_classes_75kplus_train_066687 | 30,914 | permissive | [
{
"docstring": "@param root: An XML root element. @type root: L{Element} @param definitions: A definitions object. @type definitions: L{Definitions}",
"name": "__init__",
"signature": "def __init__(self, root, definitions)"
},
{
"docstring": "Get the qualified value of attribute named 'a'.",
... | 2 | stack_v2_sparse_classes_30k_train_022345 | Implement the Python class `Part` described below.
Class description:
Represents <message><part/></message>. @ivar element: The value of the {element} attribute. Stored as a I{qref} as converted by L{suds.xsd.qualify}. @type element: str @ivar type: The value of the {type} attribute. Stored as a I{qref} as converted b... | Implement the Python class `Part` described below.
Class description:
Represents <message><part/></message>. @ivar element: The value of the {element} attribute. Stored as a I{qref} as converted by L{suds.xsd.qualify}. @type element: str @ivar type: The value of the {type} attribute. Stored as a I{qref} as converted b... | 7d8843fcdfe179f018af2038f813795f7182b714 | <|skeleton|>
class Part:
"""Represents <message><part/></message>. @ivar element: The value of the {element} attribute. Stored as a I{qref} as converted by L{suds.xsd.qualify}. @type element: str @ivar type: The value of the {type} attribute. Stored as a I{qref} as converted by L{suds.xsd.qualify}. @type type: str"... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Part:
"""Represents <message><part/></message>. @ivar element: The value of the {element} attribute. Stored as a I{qref} as converted by L{suds.xsd.qualify}. @type element: str @ivar type: The value of the {type} attribute. Stored as a I{qref} as converted by L{suds.xsd.qualify}. @type type: str"""
def _... | the_stack_v2_python_sparse | suds/wsdl.py | CybernetiX-S3C/interactive-tutorials | train | 1 |
b7d8de726930c839831a25cec79986f0d595a689 | [
"_ = ax.hist(self.d_ij, **kwargs)\nax.set_ylabel('Num. pairs')\nax.set_xlabel('Separation distance')",
"_ = ax.hist(self.C_ij, **kwargs)\nax.set_ylabel('Num. pairs')\nax.set_xlabel('Fluctuation')",
"d = self.d_ij\nC = self.C_ij\nif null_model:\n d = np.random.choice(d, self.num_fluctuations, replace=False)\n... | <|body_start_0|>
_ = ax.hist(self.d_ij, **kwargs)
ax.set_ylabel('Num. pairs')
ax.set_xlabel('Separation distance')
<|end_body_0|>
<|body_start_1|>
_ = ax.hist(self.C_ij, **kwargs)
ax.set_ylabel('Num. pairs')
ax.set_xlabel('Fluctuation')
<|end_body_1|>
<|body_start_2|>
... | Visualization methods for SpatialCorrelation. | CorrelationVisualization | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CorrelationVisualization:
"""Visualization methods for SpatialCorrelation."""
def histogram_distances(self, ax=None, **kwargs):
"""Plot histogram of pairwise distances between measurements."""
<|body_0|>
def histogram_fluctuations(self, ax=None, **kwargs):
"""Plo... | stack_v2_sparse_classes_75kplus_train_066688 | 8,963 | permissive | [
{
"docstring": "Plot histogram of pairwise distances between measurements.",
"name": "histogram_distances",
"signature": "def histogram_distances(self, ax=None, **kwargs)"
},
{
"docstring": "Plot histogram of pairwise fluctuations between measurements.",
"name": "histogram_fluctuations",
... | 3 | stack_v2_sparse_classes_30k_train_049688 | Implement the Python class `CorrelationVisualization` described below.
Class description:
Visualization methods for SpatialCorrelation.
Method signatures and docstrings:
- def histogram_distances(self, ax=None, **kwargs): Plot histogram of pairwise distances between measurements.
- def histogram_fluctuations(self, ax... | Implement the Python class `CorrelationVisualization` described below.
Class description:
Visualization methods for SpatialCorrelation.
Method signatures and docstrings:
- def histogram_distances(self, ax=None, **kwargs): Plot histogram of pairwise distances between measurements.
- def histogram_fluctuations(self, ax... | 4a622c3f5fed4456c3b9240f5a96428789fde9bd | <|skeleton|>
class CorrelationVisualization:
"""Visualization methods for SpatialCorrelation."""
def histogram_distances(self, ax=None, **kwargs):
"""Plot histogram of pairwise distances between measurements."""
<|body_0|>
def histogram_fluctuations(self, ax=None, **kwargs):
"""Plo... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class CorrelationVisualization:
"""Visualization methods for SpatialCorrelation."""
def histogram_distances(self, ax=None, **kwargs):
"""Plot histogram of pairwise distances between measurements."""
_ = ax.hist(self.d_ij, **kwargs)
ax.set_ylabel('Num. pairs')
ax.set_xlabel('Sepa... | the_stack_v2_python_sparse | flyqma/annotation/spatial/correlation.py | sbernasek/flyqma | train | 1 |
5ae89a8fa0c4cba15798460fb6ed0a0dc5b31505 | [
"def in_order(root):\n if not root:\n return []\n return in_order(root.left) + [root.val] + in_order(root.right)\nvals = in_order(root)\nres = 0\nflag = False\nfor i in vals:\n if flag:\n res += i\n if i == R:\n break\n elif i == L:\n res += i\n flag = True\... | <|body_start_0|>
def in_order(root):
if not root:
return []
return in_order(root.left) + [root.val] + in_order(root.right)
vals = in_order(root)
res = 0
flag = False
for i in vals:
if flag:
res += i
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def rangeSumBST(self, root, L, R):
""":type root: TreeNode :type L: int :type R: int :rtype: int 460ms, beats: 5.62%"""
<|body_0|>
def rangeSumBST2(self, root, L, R):
""":type root: TreeNode :type L: int :type R: int :rtype: int 384ms, beats: 34.83%"""
... | stack_v2_sparse_classes_75kplus_train_066689 | 1,274 | no_license | [
{
"docstring": ":type root: TreeNode :type L: int :type R: int :rtype: int 460ms, beats: 5.62%",
"name": "rangeSumBST",
"signature": "def rangeSumBST(self, root, L, R)"
},
{
"docstring": ":type root: TreeNode :type L: int :type R: int :rtype: int 384ms, beats: 34.83%",
"name": "rangeSumBST2"... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rangeSumBST(self, root, L, R): :type root: TreeNode :type L: int :type R: int :rtype: int 460ms, beats: 5.62%
- def rangeSumBST2(self, root, L, R): :type root: TreeNode :type... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def rangeSumBST(self, root, L, R): :type root: TreeNode :type L: int :type R: int :rtype: int 460ms, beats: 5.62%
- def rangeSumBST2(self, root, L, R): :type root: TreeNode :type... | 624975f767f6efa1d7361cc077eaebc344d57210 | <|skeleton|>
class Solution:
def rangeSumBST(self, root, L, R):
""":type root: TreeNode :type L: int :type R: int :rtype: int 460ms, beats: 5.62%"""
<|body_0|>
def rangeSumBST2(self, root, L, R):
""":type root: TreeNode :type L: int :type R: int :rtype: int 384ms, beats: 34.83%"""
... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Solution:
def rangeSumBST(self, root, L, R):
""":type root: TreeNode :type L: int :type R: int :rtype: int 460ms, beats: 5.62%"""
def in_order(root):
if not root:
return []
return in_order(root.left) + [root.val] + in_order(root.right)
vals = in_... | the_stack_v2_python_sparse | 938. 二叉搜索树的范围和.py | dx19910707/LeetCode | train | 0 | |
4cde60505d4564395914d09667c851ff3c4de3fe | [
"super().__init__()\nself.encoder = Encoder(N, dm, h, hidden, input_vocab, max_seq_input, drop_rate)\nself.decoder = Decoder(N, dm, h, hidden, target_vocab, max_seq_target, drop_rate)\nself.linear = tf.keras.layers.Dense(target_vocab)",
"enco_output = self.encoder(inputs, training, encoder_mask)\ndeco_output = se... | <|body_start_0|>
super().__init__()
self.encoder = Encoder(N, dm, h, hidden, input_vocab, max_seq_input, drop_rate)
self.decoder = Decoder(N, dm, h, hidden, target_vocab, max_seq_target, drop_rate)
self.linear = tf.keras.layers.Dense(target_vocab)
<|end_body_0|>
<|body_start_1|>
... | transformer network | Transformer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Transformer:
"""transformer network"""
def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1):
"""N - the number of blocks in the encoder and decoder dm - the dimensionality of the model h - the number of heads hidden - the numbe... | stack_v2_sparse_classes_75kplus_train_066690 | 1,678 | no_license | [
{
"docstring": "N - the number of blocks in the encoder and decoder dm - the dimensionality of the model h - the number of heads hidden - the number of hidden units in the fully connected layers input_vocab - the size of the input vocabulary target_vocab - the size of the target vocabulary max_seq_input - the m... | 2 | stack_v2_sparse_classes_30k_val_000643 | Implement the Python class `Transformer` described below.
Class description:
transformer network
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1): N - the number of blocks in the encoder and decoder dm - the dimensionalit... | Implement the Python class `Transformer` described below.
Class description:
transformer network
Method signatures and docstrings:
- def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1): N - the number of blocks in the encoder and decoder dm - the dimensionalit... | b0c18df889d8bd0c24d4bdbbd69be06bc5c0a918 | <|skeleton|>
class Transformer:
"""transformer network"""
def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1):
"""N - the number of blocks in the encoder and decoder dm - the dimensionality of the model h - the number of heads hidden - the numbe... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Transformer:
"""transformer network"""
def __init__(self, N, dm, h, hidden, input_vocab, target_vocab, max_seq_input, max_seq_target, drop_rate=0.1):
"""N - the number of blocks in the encoder and decoder dm - the dimensionality of the model h - the number of heads hidden - the number of hidden u... | the_stack_v2_python_sparse | supervised_learning/0x11-attention/11-transformer.py | Gaspela/holbertonschool-machine_learning | train | 0 |
5a3594c6ce1d9e8d2b27284ac945c75270e9c50a | [
"if not issubclass(type(pins), list):\n pins = [pins]\nsuper(DLGMLayer, self).__init__()\nself.hidden_module = MLP.get_hidden_layers(pins, phidden=phidden, nn_lin=nn_lin, name=name)\nif issubclass(type(pouts), list):\n self.out_module = nn.ModuleList()\n self.cov_module = nn.ModuleList()\n for pout in p... | <|body_start_0|>
if not issubclass(type(pins), list):
pins = [pins]
super(DLGMLayer, self).__init__()
self.hidden_module = MLP.get_hidden_layers(pins, phidden=phidden, nn_lin=nn_lin, name=name)
if issubclass(type(pouts), list):
self.out_module = nn.ModuleList()
... | Specific decoding module for Deep Latent Gaussian Models | DLGMLayer | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DLGMLayer:
"""Specific decoding module for Deep Latent Gaussian Models"""
def __init__(self, pins, pouts, phidden={'dim': 800, 'nlayers': 2}, nn_lin='ReLU', name=''):
""":param pins: parameters of the above layer :type pins: dict :param pouts: parameters of the ouput distribution :ty... | stack_v2_sparse_classes_75kplus_train_066691 | 10,368 | no_license | [
{
"docstring": ":param pins: parameters of the above layer :type pins: dict :param pouts: parameters of the ouput distribution :type pouts: dict :param phidden: parameters of the hidden layer(s) :type phidden: dict :param nn_lin: non-linearity name :type nn_lin: str :param name: name of module :type name: str",... | 2 | stack_v2_sparse_classes_30k_train_006672 | Implement the Python class `DLGMLayer` described below.
Class description:
Specific decoding module for Deep Latent Gaussian Models
Method signatures and docstrings:
- def __init__(self, pins, pouts, phidden={'dim': 800, 'nlayers': 2}, nn_lin='ReLU', name=''): :param pins: parameters of the above layer :type pins: di... | Implement the Python class `DLGMLayer` described below.
Class description:
Specific decoding module for Deep Latent Gaussian Models
Method signatures and docstrings:
- def __init__(self, pins, pouts, phidden={'dim': 800, 'nlayers': 2}, nn_lin='ReLU', name=''): :param pins: parameters of the above layer :type pins: di... | b1894f1a3bb9368c266c86666c62d94cf26d9a61 | <|skeleton|>
class DLGMLayer:
"""Specific decoding module for Deep Latent Gaussian Models"""
def __init__(self, pins, pouts, phidden={'dim': 800, 'nlayers': 2}, nn_lin='ReLU', name=''):
""":param pins: parameters of the above layer :type pins: dict :param pouts: parameters of the ouput distribution :ty... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class DLGMLayer:
"""Specific decoding module for Deep Latent Gaussian Models"""
def __init__(self, pins, pouts, phidden={'dim': 800, 'nlayers': 2}, nn_lin='ReLU', name=''):
""":param pins: parameters of the above layer :type pins: dict :param pouts: parameters of the ouput distribution :type pouts: dic... | the_stack_v2_python_sparse | models/modules/modules_bottleneck.py | dhockaday/variational-timbre | train | 0 |
80e645d717c6819b5ce1d03dc638fa7acb73cf42 | [
"result = _parseIso8601(input)\nif not result:\n result = _parseSimple(input)\nif result is not None:\n return result\nelse:\n raise ParameterError('Invalid time delta - could not parse %s' % input)",
"weeks = x.days // 7\ndays = x.days % 7\nhours = x.seconds // 3600\nminutes = x.seconds % 3600 // 60\nse... | <|body_start_0|>
result = _parseIso8601(input)
if not result:
result = _parseSimple(input)
if result is not None:
return result
else:
raise ParameterError('Invalid time delta - could not parse %s' % input)
<|end_body_0|>
<|body_start_1|>
weeks... | Class that maps to timedelta using strings in any of the following forms: * ``n {w[eek[s]]|d[ay[s]]|h[our[s]]|m[inute[s]|s[second[s]]}`` (e.g. "1 week 2 days" or "1 h") Note: multiple arguments must be supplied in longest to shortest unit order * ISO 8601 duration ``PnDTnHnMnS`` (each field optional, years and months n... | TimeDeltaValueType | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimeDeltaValueType:
"""Class that maps to timedelta using strings in any of the following forms: * ``n {w[eek[s]]|d[ay[s]]|h[our[s]]|m[inute[s]|s[second[s]]}`` (e.g. "1 week 2 days" or "1 h") Note: multiple arguments must be supplied in longest to shortest unit order * ISO 8601 duration ``PnDTnHn... | stack_v2_sparse_classes_75kplus_train_066692 | 4,446 | permissive | [
{
"docstring": "Parses a time delta from the input. See :py:class:`TimeDeltaValueType` for details on supported formats.",
"name": "parse_from_str",
"signature": "def parse_from_str(self, input)"
},
{
"docstring": "Converts datetime.timedelta to a string :param x: the value to serialize.",
"... | 2 | stack_v2_sparse_classes_30k_train_046306 | Implement the Python class `TimeDeltaValueType` described below.
Class description:
Class that maps to timedelta using strings in any of the following forms: * ``n {w[eek[s]]|d[ay[s]]|h[our[s]]|m[inute[s]|s[second[s]]}`` (e.g. "1 week 2 days" or "1 h") Note: multiple arguments must be supplied in longest to shortest u... | Implement the Python class `TimeDeltaValueType` described below.
Class description:
Class that maps to timedelta using strings in any of the following forms: * ``n {w[eek[s]]|d[ay[s]]|h[our[s]]|m[inute[s]|s[second[s]]}`` (e.g. "1 week 2 days" or "1 h") Note: multiple arguments must be supplied in longest to shortest u... | d59c99dcdcd280d7eec36a693dd80f8c8c831ea2 | <|skeleton|>
class TimeDeltaValueType:
"""Class that maps to timedelta using strings in any of the following forms: * ``n {w[eek[s]]|d[ay[s]]|h[our[s]]|m[inute[s]|s[second[s]]}`` (e.g. "1 week 2 days" or "1 h") Note: multiple arguments must be supplied in longest to shortest unit order * ISO 8601 duration ``PnDTnHn... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TimeDeltaValueType:
"""Class that maps to timedelta using strings in any of the following forms: * ``n {w[eek[s]]|d[ay[s]]|h[our[s]]|m[inute[s]|s[second[s]]}`` (e.g. "1 week 2 days" or "1 h") Note: multiple arguments must be supplied in longest to shortest unit order * ISO 8601 duration ``PnDTnHnMnS`` (each f... | the_stack_v2_python_sparse | modules/dbnd/src/targets/values/timedelta_value.py | databand-ai/dbnd | train | 257 |
f45d61edd358166da0202b1464d5b7afba4c6e40 | [
"i_begin = 0\nhkl_ref = reflections[0].get('miller_index_asymmetric')\nfor i in range(len(reflections)):\n hkl = reflections[i].get('miller_index_asymmetric')\n if hkl == hkl_ref:\n continue\n else:\n yield reflections[i_begin:i]\n i_begin = i\n hkl_ref = hkl\nyield reflections[... | <|body_start_0|>
i_begin = 0
hkl_ref = reflections[0].get('miller_index_asymmetric')
for i in range(len(reflections)):
hkl = reflections[i].get('miller_index_asymmetric')
if hkl == hkl_ref:
continue
else:
yield reflections[i_beg... | reflection_table_utils | [
"BSD-3-Clause-LBNL"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class reflection_table_utils:
def get_next_hkl_reflection_table(reflections):
"""Generate asu hkl slices from an asu hkl-sorted reflection table"""
<|body_0|>
def select_odd_experiment_reflections(reflections):
"""Select reflections from experiments with odd ids. An experi... | stack_v2_sparse_classes_75kplus_train_066693 | 1,280 | permissive | [
{
"docstring": "Generate asu hkl slices from an asu hkl-sorted reflection table",
"name": "get_next_hkl_reflection_table",
"signature": "def get_next_hkl_reflection_table(reflections)"
},
{
"docstring": "Select reflections from experiments with odd ids. An experiment id must be a string represen... | 3 | stack_v2_sparse_classes_30k_train_017474 | Implement the Python class `reflection_table_utils` described below.
Class description:
Implement the reflection_table_utils class.
Method signatures and docstrings:
- def get_next_hkl_reflection_table(reflections): Generate asu hkl slices from an asu hkl-sorted reflection table
- def select_odd_experiment_reflection... | Implement the Python class `reflection_table_utils` described below.
Class description:
Implement the reflection_table_utils class.
Method signatures and docstrings:
- def get_next_hkl_reflection_table(reflections): Generate asu hkl slices from an asu hkl-sorted reflection table
- def select_odd_experiment_reflection... | 644090f9432d9afc22cfb542fc3ab78ca8e15e5d | <|skeleton|>
class reflection_table_utils:
def get_next_hkl_reflection_table(reflections):
"""Generate asu hkl slices from an asu hkl-sorted reflection table"""
<|body_0|>
def select_odd_experiment_reflections(reflections):
"""Select reflections from experiments with odd ids. An experi... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class reflection_table_utils:
def get_next_hkl_reflection_table(reflections):
"""Generate asu hkl slices from an asu hkl-sorted reflection table"""
i_begin = 0
hkl_ref = reflections[0].get('miller_index_asymmetric')
for i in range(len(reflections)):
hkl = reflections[i].g... | the_stack_v2_python_sparse | xfel/merging/application/reflection_table_utils.py | rimmartin/cctbx_project | train | 0 | |
93146077f13d0a2bce212592ae6c1f5250a085d6 | [
"self.time = collections.defaultdict(list)\nself.value = collections.defaultdict(list)\nself.max = collections.defaultdict(int)",
"self.time[key].append(timestamp)\nself.value[key].append(value)\nself.max[key] = max(self.max[key], timestamp)",
"if key not in self.time:\n return ''\nif timestamp >= self.max[k... | <|body_start_0|>
self.time = collections.defaultdict(list)
self.value = collections.defaultdict(list)
self.max = collections.defaultdict(int)
<|end_body_0|>
<|body_start_1|>
self.time[key].append(timestamp)
self.value[key].append(value)
self.max[key] = max(self.max[key],... | TimeMap | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TimeMap:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def set(self, key, value, timestamp):
""":type key: str :type value: str :type timestamp: int :rtype: None"""
<|body_1|>
def get(self, key, timestamp):
""":type ke... | stack_v2_sparse_classes_75kplus_train_066694 | 1,146 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": ":type key: str :type value: str :type timestamp: int :rtype: None",
"name": "set",
"signature": "def set(self, key, value, timestamp)"
},
{
"docstring":... | 3 | stack_v2_sparse_classes_30k_train_048110 | Implement the Python class `TimeMap` described below.
Class description:
Implement the TimeMap class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def set(self, key, value, timestamp): :type key: str :type value: str :type timestamp: int :rtype: None
- def get(self, k... | Implement the Python class `TimeMap` described below.
Class description:
Implement the TimeMap class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def set(self, key, value, timestamp): :type key: str :type value: str :type timestamp: int :rtype: None
- def get(self, k... | 8cdb97bc7588b96b91b1c550afd84e976c1926e0 | <|skeleton|>
class TimeMap:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def set(self, key, value, timestamp):
""":type key: str :type value: str :type timestamp: int :rtype: None"""
<|body_1|>
def get(self, key, timestamp):
""":type ke... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class TimeMap:
def __init__(self):
"""Initialize your data structure here."""
self.time = collections.defaultdict(list)
self.value = collections.defaultdict(list)
self.max = collections.defaultdict(int)
def set(self, key, value, timestamp):
""":type key: str :type value:... | the_stack_v2_python_sparse | BinarySearch/981_BS_TImeBasedKeyValueStore.py | ZhengLiangliang1996/Leetcode_ML_Daily | train | 1 | |
e48765a96366f7dc03be40cc294177f215eb3ff4 | [
"VDriveCommand.__init__(self, controller, command_args)\nself.check_command_arguments(self.SupportedArgs)\nreturn",
"input_args = self._commandArgsDict.keys()\nfor arg_key in input_args:\n if arg_key not in RunsInfoQuery.SupportedArgs:\n raise KeyError('INFO argument {} is not recognized. Supported arg... | <|body_start_0|>
VDriveCommand.__init__(self, controller, command_args)
self.check_command_arguments(self.SupportedArgs)
return
<|end_body_0|>
<|body_start_1|>
input_args = self._commandArgsDict.keys()
for arg_key in input_args:
if arg_key not in RunsInfoQuery.Suppor... | Process command MERGE | RunsInfoQuery | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RunsInfoQuery:
"""Process command MERGE"""
def __init__(self, controller, command_args):
"""Initialization"""
<|body_0|>
def exec_cmd(self):
"""Execute input command"""
<|body_1|>
def format_list_to_str(info_dict_list, keys):
"""format the ru... | stack_v2_sparse_classes_75kplus_train_066695 | 5,215 | no_license | [
{
"docstring": "Initialization",
"name": "__init__",
"signature": "def __init__(self, controller, command_args)"
},
{
"docstring": "Execute input command",
"name": "exec_cmd",
"signature": "def exec_cmd(self)"
},
{
"docstring": "format the run information dictionary list into nic... | 4 | stack_v2_sparse_classes_30k_train_009846 | Implement the Python class `RunsInfoQuery` described below.
Class description:
Process command MERGE
Method signatures and docstrings:
- def __init__(self, controller, command_args): Initialization
- def exec_cmd(self): Execute input command
- def format_list_to_str(info_dict_list, keys): format the run information d... | Implement the Python class `RunsInfoQuery` described below.
Class description:
Process command MERGE
Method signatures and docstrings:
- def __init__(self, controller, command_args): Initialization
- def exec_cmd(self): Execute input command
- def format_list_to_str(info_dict_list, keys): format the run information d... | 875a5b99a7a6f51129844bf8052fc6f231497d71 | <|skeleton|>
class RunsInfoQuery:
"""Process command MERGE"""
def __init__(self, controller, command_args):
"""Initialization"""
<|body_0|>
def exec_cmd(self):
"""Execute input command"""
<|body_1|>
def format_list_to_str(info_dict_list, keys):
"""format the ru... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class RunsInfoQuery:
"""Process command MERGE"""
def __init__(self, controller, command_args):
"""Initialization"""
VDriveCommand.__init__(self, controller, command_args)
self.check_command_arguments(self.SupportedArgs)
return
def exec_cmd(self):
"""Execute input co... | the_stack_v2_python_sparse | pyvdrive/interface/vdrive_commands/show_info.py | neutrons/PyVDrive | train | 2 |
f65c362b60fea43c304948dc4fdb6578b7b99b1b | [
"self.adj_list: List[List[Tuple[int, int]]] = [[] for _ in range(n)]\nself.adj_list_creator(mat)\nself.visited: List[bool] = [False] * n\nself.q: List[Tuple[int, int]] = []\nself.src: int = src\nself.D: List[int] = [MAXINT] * n",
"for i in range(len(mat)):\n v1, v2 = mat[i]\n self.adj_list[v1].append(v2)\n ... | <|body_start_0|>
self.adj_list: List[List[Tuple[int, int]]] = [[] for _ in range(n)]
self.adj_list_creator(mat)
self.visited: List[bool] = [False] * n
self.q: List[Tuple[int, int]] = []
self.src: int = src
self.D: List[int] = [MAXINT] * n
<|end_body_0|>
<|body_start_1|>
... | Graph | [
"Unlicense"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Graph:
def __init__(self, n: int, mat: List[List[int]], src: int=0):
"""Create the adjacency list for the given matrix :param n: no of nodes :param mat: given matrix (m x 3)"""
<|body_0|>
def adj_list_creator(self, mat: List[List[int]]):
"""Creates the adjacency list... | stack_v2_sparse_classes_75kplus_train_066696 | 1,956 | permissive | [
{
"docstring": "Create the adjacency list for the given matrix :param n: no of nodes :param mat: given matrix (m x 3)",
"name": "__init__",
"signature": "def __init__(self, n: int, mat: List[List[int]], src: int=0)"
},
{
"docstring": "Creates the adjacency list for given matrix in the format: [[... | 3 | stack_v2_sparse_classes_30k_train_022913 | Implement the Python class `Graph` described below.
Class description:
Implement the Graph class.
Method signatures and docstrings:
- def __init__(self, n: int, mat: List[List[int]], src: int=0): Create the adjacency list for the given matrix :param n: no of nodes :param mat: given matrix (m x 3)
- def adj_list_creat... | Implement the Python class `Graph` described below.
Class description:
Implement the Graph class.
Method signatures and docstrings:
- def __init__(self, n: int, mat: List[List[int]], src: int=0): Create the adjacency list for the given matrix :param n: no of nodes :param mat: given matrix (m x 3)
- def adj_list_creat... | 92543c954801e5006a5059c1213d7b833b290e2e | <|skeleton|>
class Graph:
def __init__(self, n: int, mat: List[List[int]], src: int=0):
"""Create the adjacency list for the given matrix :param n: no of nodes :param mat: given matrix (m x 3)"""
<|body_0|>
def adj_list_creator(self, mat: List[List[int]]):
"""Creates the adjacency list... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Graph:
def __init__(self, n: int, mat: List[List[int]], src: int=0):
"""Create the adjacency list for the given matrix :param n: no of nodes :param mat: given matrix (m x 3)"""
self.adj_list: List[List[Tuple[int, int]]] = [[] for _ in range(n)]
self.adj_list_creator(mat)
self.v... | the_stack_v2_python_sparse | Graphs/bfs.py | shreykhare/LeetCodeSolutions | train | 0 | |
2a6364254e39dea44a5ab33903969832729834b3 | [
"if request.session.uid:\n request.session.uid = False\nif request.session.login:\n request.session.login = False\ndata = {'code_maxlength': 6}\nreturn request.render('sms_base.sms_login_signup', data)",
"values = request.params.copy()\nuser_phone = values.get('user_phone')\nif not user_phone:\n return j... | <|body_start_0|>
if request.session.uid:
request.session.uid = False
if request.session.login:
request.session.login = False
data = {'code_maxlength': 6}
return request.render('sms_base.sms_login_signup', data)
<|end_body_0|>
<|body_start_1|>
values = req... | OAuthController | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OAuthController:
def web_odoo_sms_login(self, **kw):
"""短信登录入口,点击后返回到验证码界面 :param kw: :return:"""
<|body_0|>
def web_sms_send_code(self, **kw):
"""发送验证码 :param kw: :return:"""
<|body_1|>
def web_sms_user_login(self, **kw):
"""验证登录验证码 :param kw: :... | stack_v2_sparse_classes_75kplus_train_066697 | 5,794 | permissive | [
{
"docstring": "短信登录入口,点击后返回到验证码界面 :param kw: :return:",
"name": "web_odoo_sms_login",
"signature": "def web_odoo_sms_login(self, **kw)"
},
{
"docstring": "发送验证码 :param kw: :return:",
"name": "web_sms_send_code",
"signature": "def web_sms_send_code(self, **kw)"
},
{
"docstring": ... | 4 | null | Implement the Python class `OAuthController` described below.
Class description:
Implement the OAuthController class.
Method signatures and docstrings:
- def web_odoo_sms_login(self, **kw): 短信登录入口,点击后返回到验证码界面 :param kw: :return:
- def web_sms_send_code(self, **kw): 发送验证码 :param kw: :return:
- def web_sms_user_login(s... | Implement the Python class `OAuthController` described below.
Class description:
Implement the OAuthController class.
Method signatures and docstrings:
- def web_odoo_sms_login(self, **kw): 短信登录入口,点击后返回到验证码界面 :param kw: :return:
- def web_sms_send_code(self, **kw): 发送验证码 :param kw: :return:
- def web_sms_user_login(s... | 8608aaeae7a8c86d53b68ce26b7b308f779c3dd8 | <|skeleton|>
class OAuthController:
def web_odoo_sms_login(self, **kw):
"""短信登录入口,点击后返回到验证码界面 :param kw: :return:"""
<|body_0|>
def web_sms_send_code(self, **kw):
"""发送验证码 :param kw: :return:"""
<|body_1|>
def web_sms_user_login(self, **kw):
"""验证登录验证码 :param kw: :... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class OAuthController:
def web_odoo_sms_login(self, **kw):
"""短信登录入口,点击后返回到验证码界面 :param kw: :return:"""
if request.session.uid:
request.session.uid = False
if request.session.login:
request.session.login = False
data = {'code_maxlength': 6}
return requ... | the_stack_v2_python_sparse | sms_base/controllers/sms_controller.py | niulinlnc/odooExtModel | train | 4 | |
61f61444cc0309097ced00faefc503d3a7bd51c2 | [
"self.vehtype = vehtype\nself.speed = speed\nself.acce = acce\nself.weight = weight\nself.space = space\nself.datetime = datetime\nif lane == 1:\n self.x = 90\n self.y = 720\nelse:\n self.x = 960 - 90 - 345\n self.y = -100\nself.color = (255, 255, 255)",
"self.str1 = u'车型: {0}轴车 时间: {1}'.format(self.v... | <|body_start_0|>
self.vehtype = vehtype
self.speed = speed
self.acce = acce
self.weight = weight
self.space = space
self.datetime = datetime
if lane == 1:
self.x = 90
self.y = 720
else:
self.x = 960 - 90 - 345
... | Veh class, each will print a veh's info | Veh | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Veh:
"""Veh class, each will print a veh's info"""
def __init__(self, vehtype, speed, acce, lane, weight, space, datetime):
"""Init object A para's expamle: vehtype: 1 (int) speed: 65 (int) acce: 939 (int) lane: 1 (int) weight: (790, 770) (tuple of int) space: 2564 (int) datetime: (a... | stack_v2_sparse_classes_75kplus_train_066698 | 3,873 | no_license | [
{
"docstring": "Init object A para's expamle: vehtype: 1 (int) speed: 65 (int) acce: 939 (int) lane: 1 (int) weight: (790, 770) (tuple of int) space: 2564 (int) datetime: (a standard datetime object)",
"name": "__init__",
"signature": "def __init__(self, vehtype, speed, acce, lane, weight, space, dateti... | 5 | stack_v2_sparse_classes_30k_train_022089 | Implement the Python class `Veh` described below.
Class description:
Veh class, each will print a veh's info
Method signatures and docstrings:
- def __init__(self, vehtype, speed, acce, lane, weight, space, datetime): Init object A para's expamle: vehtype: 1 (int) speed: 65 (int) acce: 939 (int) lane: 1 (int) weight:... | Implement the Python class `Veh` described below.
Class description:
Veh class, each will print a veh's info
Method signatures and docstrings:
- def __init__(self, vehtype, speed, acce, lane, weight, space, datetime): Init object A para's expamle: vehtype: 1 (int) speed: 65 (int) acce: 939 (int) lane: 1 (int) weight:... | 038497eb9b2119769ecb85e023156eeff375d0e3 | <|skeleton|>
class Veh:
"""Veh class, each will print a veh's info"""
def __init__(self, vehtype, speed, acce, lane, weight, space, datetime):
"""Init object A para's expamle: vehtype: 1 (int) speed: 65 (int) acce: 939 (int) lane: 1 (int) weight: (790, 770) (tuple of int) space: 2564 (int) datetime: (a... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Veh:
"""Veh class, each will print a veh's info"""
def __init__(self, vehtype, speed, acce, lane, weight, space, datetime):
"""Init object A para's expamle: vehtype: 1 (int) speed: 65 (int) acce: 939 (int) lane: 1 (int) weight: (790, 770) (tuple of int) space: 2564 (int) datetime: (a standard dat... | the_stack_v2_python_sparse | Veh.py | MatheMatrix/realtimewatcher | train | 1 |
dbd69a82dbca2f03b73915a09b6563b00224e8b5 | [
"self.p1 = p1\nself.p2 = p2\nself.width = width\nself.centervalx = (p1.x + p2.x) / 2\nself.centervaly = (p1.y + p2.y) / 2\nself.center = Point(self.centervalx, self.centervaly)\nself.area = self.width / 2\nif self.centervaly == self.p1.y:\n self.b = math.sqrt(math.pow(self.area, 2) - math.pow(self.p1.x - self.ce... | <|body_start_0|>
self.p1 = p1
self.p2 = p2
self.width = width
self.centervalx = (p1.x + p2.x) / 2
self.centervaly = (p1.y + p2.y) / 2
self.center = Point(self.centervalx, self.centervaly)
self.area = self.width / 2
if self.centervaly == self.p1.y:
... | Create an ellipse class | Ellipse | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ellipse:
"""Create an ellipse class"""
def __init__(self, p1, p2, width):
"""A constructore class of ellipse class initializing values"""
<|body_0|>
def valueinellipse(self, point):
"""Fucntion to check if the point is in the ellipse"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_75kplus_train_066699 | 8,980 | no_license | [
{
"docstring": "A constructore class of ellipse class initializing values",
"name": "__init__",
"signature": "def __init__(self, p1, p2, width)"
},
{
"docstring": "Fucntion to check if the point is in the ellipse",
"name": "valueinellipse",
"signature": "def valueinellipse(self, point)"
... | 2 | stack_v2_sparse_classes_30k_test_000999 | Implement the Python class `Ellipse` described below.
Class description:
Create an ellipse class
Method signatures and docstrings:
- def __init__(self, p1, p2, width): A constructore class of ellipse class initializing values
- def valueinellipse(self, point): Fucntion to check if the point is in the ellipse | Implement the Python class `Ellipse` described below.
Class description:
Create an ellipse class
Method signatures and docstrings:
- def __init__(self, p1, p2, width): A constructore class of ellipse class initializing values
- def valueinellipse(self, point): Fucntion to check if the point is in the ellipse
<|skele... | 2c06bf5c11452b9f16b5ef96d0e8d106534035b0 | <|skeleton|>
class Ellipse:
"""Create an ellipse class"""
def __init__(self, p1, p2, width):
"""A constructore class of ellipse class initializing values"""
<|body_0|>
def valueinellipse(self, point):
"""Fucntion to check if the point is in the ellipse"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_75kplus | data/stack_v2_sparse_classes_30k | 75,829 | class Ellipse:
"""Create an ellipse class"""
def __init__(self, p1, p2, width):
"""A constructore class of ellipse class initializing values"""
self.p1 = p1
self.p2 = p2
self.width = width
self.centervalx = (p1.x + p2.x) / 2
self.centervaly = (p1.y + p2.y) / 2
... | the_stack_v2_python_sparse | overlapEllipses.py | monishgowda77/PythonPrograms | train | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.