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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
f3006ab0a4c9e06489cc4024d6b5e5c7145e9ed0 | [
"self.pred = pred\nself.target = target\nself.is_higher_better = is_higher_better\nself.supported_metrics = {'precision': 0, 'recall': 1, 'mrr': 2, 'map': 3, 'ndcg': 4}\nassert len(pred) == len(target), f'The prediction and groudtruth target should have the same number of queries, while there are {len(pred)... | <|body_start_0|>
self.pred = pred
self.target = target
self.is_higher_better = is_higher_better
self.supported_metrics = {'precision': 0, 'recall': 1, 'mrr': 2, 'map': 3, 'ndcg': 4}
assert len(pred) == len(target), f'The prediction and groudtruth target should have the same numbe... | RankingMetrics | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RankingMetrics:
def __init__(self, pred: Dict[str, Dict], target: Dict[str, Dict], is_higher_better=True):
"""Evaluation Metrics for information retrieval tasks such as document retrieval, image retrieval, etc. Reference: https://www.cs.cornell.edu/courses/cs4300/2013fa/lectures/metrics-... | stack_v2_sparse_classes_36k_train_029800 | 13,643 | permissive | [
{
"docstring": "Evaluation Metrics for information retrieval tasks such as document retrieval, image retrieval, etc. Reference: https://www.cs.cornell.edu/courses/cs4300/2013fa/lectures/metrics-2-4pp.pdf Parameters ---------- pred: the prediction of the ranking model. It has the following form. pred = { 'q1': {... | 3 | null | Implement the Python class `RankingMetrics` described below.
Class description:
Implement the RankingMetrics class.
Method signatures and docstrings:
- def __init__(self, pred: Dict[str, Dict], target: Dict[str, Dict], is_higher_better=True): Evaluation Metrics for information retrieval tasks such as document retriev... | Implement the Python class `RankingMetrics` described below.
Class description:
Implement the RankingMetrics class.
Method signatures and docstrings:
- def __init__(self, pred: Dict[str, Dict], target: Dict[str, Dict], is_higher_better=True): Evaluation Metrics for information retrieval tasks such as document retriev... | 6af92e149491f6e5062495d87306b3625d12d992 | <|skeleton|>
class RankingMetrics:
def __init__(self, pred: Dict[str, Dict], target: Dict[str, Dict], is_higher_better=True):
"""Evaluation Metrics for information retrieval tasks such as document retrieval, image retrieval, etc. Reference: https://www.cs.cornell.edu/courses/cs4300/2013fa/lectures/metrics-... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RankingMetrics:
def __init__(self, pred: Dict[str, Dict], target: Dict[str, Dict], is_higher_better=True):
"""Evaluation Metrics for information retrieval tasks such as document retrieval, image retrieval, etc. Reference: https://www.cs.cornell.edu/courses/cs4300/2013fa/lectures/metrics-2-4pp.pdf Para... | the_stack_v2_python_sparse | multimodal/src/autogluon/multimodal/utils/metric.py | stjordanis/autogluon | train | 0 | |
ac4508c030d3171ba2e3d9f2fc57d133f39a0ae2 | [
"self.submodules: Optional[GitSubmodules] = yaml.get('submodules', None)\nself.lfs: Optional[bool] = yaml.get('lfs', None)\nself.depth: Optional[int] = yaml.get('depth', None)\nself.config: Optional[GitConfig] = yaml.get('config', None)",
"yaml = {}\nif self.submodules is not None:\n yaml['submodules'] = self.... | <|body_start_0|>
self.submodules: Optional[GitSubmodules] = yaml.get('submodules', None)
self.lfs: Optional[bool] = yaml.get('lfs', None)
self.depth: Optional[int] = yaml.get('depth', None)
self.config: Optional[GitConfig] = yaml.get('config', None)
<|end_body_0|>
<|body_start_1|>
... | clowder yaml GitSettings model class :ivar Optional[bool] submodules: Whether to fetch submodules :ivar Optional[bool] lfs: Whether to set up lfs hooks and pull files :ivar Optional[int] depth: Depth to clone git repositories :ivar Optional[GitConfig] config: Custom git config values to set | GitSettings | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GitSettings:
"""clowder yaml GitSettings model class :ivar Optional[bool] submodules: Whether to fetch submodules :ivar Optional[bool] lfs: Whether to set up lfs hooks and pull files :ivar Optional[int] depth: Depth to clone git repositories :ivar Optional[GitConfig] config: Custom git config val... | stack_v2_sparse_classes_36k_train_029801 | 1,480 | permissive | [
{
"docstring": "Source __init__ :param dict yaml: Parsed YAML python object for GitSettings",
"name": "__init__",
"signature": "def __init__(self, yaml: dict)"
},
{
"docstring": "Return python object representation for saving yaml :return: YAML python object",
"name": "get_yaml",
"signat... | 2 | null | Implement the Python class `GitSettings` described below.
Class description:
clowder yaml GitSettings model class :ivar Optional[bool] submodules: Whether to fetch submodules :ivar Optional[bool] lfs: Whether to set up lfs hooks and pull files :ivar Optional[int] depth: Depth to clone git repositories :ivar Optional[G... | Implement the Python class `GitSettings` described below.
Class description:
clowder yaml GitSettings model class :ivar Optional[bool] submodules: Whether to fetch submodules :ivar Optional[bool] lfs: Whether to set up lfs hooks and pull files :ivar Optional[int] depth: Depth to clone git repositories :ivar Optional[G... | 1438fc8b1bb7379de66142ffcb0e20b459b59159 | <|skeleton|>
class GitSettings:
"""clowder yaml GitSettings model class :ivar Optional[bool] submodules: Whether to fetch submodules :ivar Optional[bool] lfs: Whether to set up lfs hooks and pull files :ivar Optional[int] depth: Depth to clone git repositories :ivar Optional[GitConfig] config: Custom git config val... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GitSettings:
"""clowder yaml GitSettings model class :ivar Optional[bool] submodules: Whether to fetch submodules :ivar Optional[bool] lfs: Whether to set up lfs hooks and pull files :ivar Optional[int] depth: Depth to clone git repositories :ivar Optional[GitConfig] config: Custom git config values to set"""... | the_stack_v2_python_sparse | clowder/model/git_settings.py | JrGoodle/clowder | train | 17 |
e191ea38f6e1bcf8755858cd21842eaa506515c8 | [
"log.info('Creating CSRFProtectionMiddleware')\nself.application = application\nself.csrf_token_id = csrf_token_id\nself.clear_env = clear_env\nself.token_env = token_env\nself.auth_state = auth_state",
"request = Request(environ)\nlog.debug('CSRFProtectionMiddleware(%s)' % request.path)\ntoken = environ.get('rep... | <|body_start_0|>
log.info('Creating CSRFProtectionMiddleware')
self.application = application
self.csrf_token_id = csrf_token_id
self.clear_env = clear_env
self.token_env = token_env
self.auth_state = auth_state
<|end_body_0|>
<|body_start_1|>
request = Request(e... | CSRF Protection WSGI Middleware. A layer of WSGI middleware that is responsible for making sure authenticated requests originated from the user inside of the app's domain and not a malicious website. This middleware works with the :mod:`repoze.who` middleware, and requires that it is placed below :mod:`repoze.who` in t... | CSRFProtectionMiddleware | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CSRFProtectionMiddleware:
"""CSRF Protection WSGI Middleware. A layer of WSGI middleware that is responsible for making sure authenticated requests originated from the user inside of the app's domain and not a malicious website. This middleware works with the :mod:`repoze.who` middleware, and req... | stack_v2_sparse_classes_36k_train_029802 | 13,040 | permissive | [
{
"docstring": "Initialize the CSRF Protection WSGI Middleware. :csrf_token_id: The name of the CSRF token variable :clear_env: Variables to clear out of the `environ` on invalid token :token_env: The name of the token variable in the environ :auth_state: The environ key that will be set when we are logging in"... | 2 | stack_v2_sparse_classes_30k_train_013256 | Implement the Python class `CSRFProtectionMiddleware` described below.
Class description:
CSRF Protection WSGI Middleware. A layer of WSGI middleware that is responsible for making sure authenticated requests originated from the user inside of the app's domain and not a malicious website. This middleware works with th... | Implement the Python class `CSRFProtectionMiddleware` described below.
Class description:
CSRF Protection WSGI Middleware. A layer of WSGI middleware that is responsible for making sure authenticated requests originated from the user inside of the app's domain and not a malicious website. This middleware works with th... | 1e45769663f5a2ab80b8251cb633caf1f7328a11 | <|skeleton|>
class CSRFProtectionMiddleware:
"""CSRF Protection WSGI Middleware. A layer of WSGI middleware that is responsible for making sure authenticated requests originated from the user inside of the app's domain and not a malicious website. This middleware works with the :mod:`repoze.who` middleware, and req... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CSRFProtectionMiddleware:
"""CSRF Protection WSGI Middleware. A layer of WSGI middleware that is responsible for making sure authenticated requests originated from the user inside of the app's domain and not a malicious website. This middleware works with the :mod:`repoze.who` middleware, and requires that it... | the_stack_v2_python_sparse | moksha/middleware/csrf.py | ralphbean/moksha | train | 2 |
e0da49cfb02d8e4bb5ddf381e2499a1b40b47a37 | [
"name1 = self.__class__.__name__ + '.' + GetName.get_current_function_name()\nMinePage.Mine(self.driver).click_mine_entry()\nHotPage.Hot(self.driver).click_find()\nHotPage.Hot(self.driver).click_find_hotnews()\ntry:\n HotPage.Hot(self.driver).click_hotnews_hot()\n self.assertTrue(HotPage.Hot(self.driver).find... | <|body_start_0|>
name1 = self.__class__.__name__ + '.' + GetName.get_current_function_name()
MinePage.Mine(self.driver).click_mine_entry()
HotPage.Hot(self.driver).click_find()
HotPage.Hot(self.driver).click_find_hotnews()
try:
HotPage.Hot(self.driver).click_hotnews_h... | nologin_Hot | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class nologin_Hot:
def test_01_hotnews(self):
"""发现热文UI测试"""
<|body_0|>
def test_02_hotman(self):
"""发现红人UI测试"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
name1 = self.__class__.__name__ + '.' + GetName.get_current_function_name()
MinePage.Mine... | stack_v2_sparse_classes_36k_train_029803 | 2,509 | no_license | [
{
"docstring": "发现热文UI测试",
"name": "test_01_hotnews",
"signature": "def test_01_hotnews(self)"
},
{
"docstring": "发现红人UI测试",
"name": "test_02_hotman",
"signature": "def test_02_hotman(self)"
}
] | 2 | null | Implement the Python class `nologin_Hot` described below.
Class description:
Implement the nologin_Hot class.
Method signatures and docstrings:
- def test_01_hotnews(self): 发现热文UI测试
- def test_02_hotman(self): 发现红人UI测试 | Implement the Python class `nologin_Hot` described below.
Class description:
Implement the nologin_Hot class.
Method signatures and docstrings:
- def test_01_hotnews(self): 发现热文UI测试
- def test_02_hotman(self): 发现红人UI测试
<|skeleton|>
class nologin_Hot:
def test_01_hotnews(self):
"""发现热文UI测试"""
<|b... | 7ce47cda6ac03b7eb707929dd2e0428132ff255f | <|skeleton|>
class nologin_Hot:
def test_01_hotnews(self):
"""发现热文UI测试"""
<|body_0|>
def test_02_hotman(self):
"""发现红人UI测试"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class nologin_Hot:
def test_01_hotnews(self):
"""发现热文UI测试"""
name1 = self.__class__.__name__ + '.' + GetName.get_current_function_name()
MinePage.Mine(self.driver).click_mine_entry()
HotPage.Hot(self.driver).click_find()
HotPage.Hot(self.driver).click_find_hotnews()
t... | the_stack_v2_python_sparse | android_warning/android_warning/apptest/TestCase/nologin_testhot.py | xiaominwanglast/uiautomator | train | 0 | |
caa85abe047c7793de7338ce74ab653f8c58fbaf | [
"with db.DBPoolManager().get_connect() as connect:\n cursor = connect.cursor(DictCursor)\n cursor.execute(sql_query, args)\n return cursor.fetchall()",
"with db.DBPoolManager().get_cursor() as cursor:\n cursor.execute(sql_query, args)\n return cursor.fetchall()"
] | <|body_start_0|>
with db.DBPoolManager().get_connect() as connect:
cursor = connect.cursor(DictCursor)
cursor.execute(sql_query, args)
return cursor.fetchall()
<|end_body_0|>
<|body_start_1|>
with db.DBPoolManager().get_cursor() as cursor:
cursor.execute(... | Class for interacting with database using a pool manager. | DbHelper | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DbHelper:
"""Class for interacting with database using a pool manager."""
def _make_select(sql_query, args=None):
"""Makes SELECT SQL request using a pool manager. :param sql_query: sql query of request :param args: args for request :return: list of dicts"""
<|body_0|>
d... | stack_v2_sparse_classes_36k_train_029804 | 1,439 | no_license | [
{
"docstring": "Makes SELECT SQL request using a pool manager. :param sql_query: sql query of request :param args: args for request :return: list of dicts",
"name": "_make_select",
"signature": "def _make_select(sql_query, args=None)"
},
{
"docstring": "Makes INSERT, UPDATE, DELETE SQL requests ... | 2 | stack_v2_sparse_classes_30k_train_003980 | Implement the Python class `DbHelper` described below.
Class description:
Class for interacting with database using a pool manager.
Method signatures and docstrings:
- def _make_select(sql_query, args=None): Makes SELECT SQL request using a pool manager. :param sql_query: sql query of request :param args: args for re... | Implement the Python class `DbHelper` described below.
Class description:
Class for interacting with database using a pool manager.
Method signatures and docstrings:
- def _make_select(sql_query, args=None): Makes SELECT SQL request using a pool manager. :param sql_query: sql query of request :param args: args for re... | 7d8f85323cd553e1b7788b407f84f14d2563bd2b | <|skeleton|>
class DbHelper:
"""Class for interacting with database using a pool manager."""
def _make_select(sql_query, args=None):
"""Makes SELECT SQL request using a pool manager. :param sql_query: sql query of request :param args: args for request :return: list of dicts"""
<|body_0|>
d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DbHelper:
"""Class for interacting with database using a pool manager."""
def _make_select(sql_query, args=None):
"""Makes SELECT SQL request using a pool manager. :param sql_query: sql query of request :param args: args for request :return: list of dicts"""
with db.DBPoolManager().get_co... | the_stack_v2_python_sparse | moneta/src/python/core/db/db_helper.py | lv-386-python/moneta | train | 7 |
f597ec1aa18a314ece4229512b3f8e73dc07b6cc | [
"try:\n sock = socket.socket(31, socket.SOCK_RAW, 1)\n ioctl(sock.fileno(), 1074022602, index)\n sock.close()\nexcept IOError:\n return False\nreturn True",
"try:\n sock = socket.socket(31, socket.SOCK_RAW, index)\n ioctl(sock.fileno(), 1074022603, 0)\n sock.close()\nexcept IOError:\n retu... | <|body_start_0|>
try:
sock = socket.socket(31, socket.SOCK_RAW, 1)
ioctl(sock.fileno(), 1074022602, index)
sock.close()
except IOError:
return False
return True
<|end_body_0|>
<|body_start_1|>
try:
sock = socket.socket(31, sock... | This class allows to easily configure an HCI Interface. | HCIConfig | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HCIConfig:
"""This class allows to easily configure an HCI Interface."""
def down(index):
"""This class method stops an HCI interface. Its role is equivalent to the following command : ``hciconfig hci<index> down`` :param index: index of the HCI interface to stop :type index: integer... | stack_v2_sparse_classes_36k_train_029805 | 1,488 | permissive | [
{
"docstring": "This class method stops an HCI interface. Its role is equivalent to the following command : ``hciconfig hci<index> down`` :param index: index of the HCI interface to stop :type index: integer :Example: >>> HCIConfig.down(0)",
"name": "down",
"signature": "def down(index)"
},
{
"d... | 3 | null | Implement the Python class `HCIConfig` described below.
Class description:
This class allows to easily configure an HCI Interface.
Method signatures and docstrings:
- def down(index): This class method stops an HCI interface. Its role is equivalent to the following command : ``hciconfig hci<index> down`` :param index... | Implement the Python class `HCIConfig` described below.
Class description:
This class allows to easily configure an HCI Interface.
Method signatures and docstrings:
- def down(index): This class method stops an HCI interface. Its role is equivalent to the following command : ``hciconfig hci<index> down`` :param index... | f73f6c4442e4bfd239eb5caf5e1283c125d37db9 | <|skeleton|>
class HCIConfig:
"""This class allows to easily configure an HCI Interface."""
def down(index):
"""This class method stops an HCI interface. Its role is equivalent to the following command : ``hciconfig hci<index> down`` :param index: index of the HCI interface to stop :type index: integer... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HCIConfig:
"""This class allows to easily configure an HCI Interface."""
def down(index):
"""This class method stops an HCI interface. Its role is equivalent to the following command : ``hciconfig hci<index> down`` :param index: index of the HCI interface to stop :type index: integer :Example: >>... | the_stack_v2_python_sparse | mirage/libs/bt_utils/hciconfig.py | RCayre/mirage | train | 199 |
d9f00e0c3732412ad8b06d6c64deac29d47a5d90 | [
"self.val = None\nself.left = None\nself.right = None",
"if self.val == None:\n self.val = word\nif word <= self.val:\n if self.left != None:\n self.left.insert(word)\n else:\n self.left = Trie()\n self.left.val = word\nelif word > self.val:\n if self.right != None:\n self.... | <|body_start_0|>
self.val = None
self.left = None
self.right = None
<|end_body_0|>
<|body_start_1|>
if self.val == None:
self.val = word
if word <= self.val:
if self.left != None:
self.left.insert(word)
else:
se... | Trie | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Trie:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def insert(self, word):
"""Inserts a word into the trie. :type word: str :rtype: void"""
<|body_1|>
def search(self, word):
"""Returns if the word is in the trie. :ty... | stack_v2_sparse_classes_36k_train_029806 | 2,155 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Inserts a word into the trie. :type word: str :rtype: void",
"name": "insert",
"signature": "def insert(self, word)"
},
{
"docstring": "Returns if the w... | 4 | null | Implement the Python class `Trie` described below.
Class description:
Implement the Trie class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def insert(self, word): Inserts a word into the trie. :type word: str :rtype: void
- def search(self, word): Returns if the wor... | Implement the Python class `Trie` described below.
Class description:
Implement the Trie class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def insert(self, word): Inserts a word into the trie. :type word: str :rtype: void
- def search(self, word): Returns if the wor... | 22359005ec5e0791e28294576fc6c40c61e4cbdb | <|skeleton|>
class Trie:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def insert(self, word):
"""Inserts a word into the trie. :type word: str :rtype: void"""
<|body_1|>
def search(self, word):
"""Returns if the word is in the trie. :ty... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Trie:
def __init__(self):
"""Initialize your data structure here."""
self.val = None
self.left = None
self.right = None
def insert(self, word):
"""Inserts a word into the trie. :type word: str :rtype: void"""
if self.val == None:
self.val = word... | the_stack_v2_python_sparse | Day 49/49_Python.py | Skatie7/50DaysOfCode | train | 0 | |
8be088dda6bf281c0a914a1d9b5ca899b01e3fc0 | [
"self.k = k\nself.elements = {}\nself.func_of_freq = lambda x: x ** p\nself.sample_p = sample_p",
"if key in self.elements:\n raise Exception('This implementation works only for aggregated data')\nseed = np.random.exponential(1.0 / value ** self.sample_p)\nself.elements[key] = (seed, value)\nif len(self.elemen... | <|body_start_0|>
self.k = k
self.elements = {}
self.func_of_freq = lambda x: x ** p
self.sample_p = sample_p
<|end_body_0|>
<|body_start_1|>
if key in self.elements:
raise Exception('This implementation works only for aggregated data')
seed = np.random.expone... | A simple implementation of PPSWOR sampling for aggregated data. Used as a benchmark for estimating moments with advice. The sketch assumes input that consists of (key, value) pairs, which is aggregated (each key appears at most once, no guarantees on the output otherwise). The sketch supports sampling keys with weight ... | PpsworSketch | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PpsworSketch:
"""A simple implementation of PPSWOR sampling for aggregated data. Used as a benchmark for estimating moments with advice. The sketch assumes input that consists of (key, value) pairs, which is aggregated (each key appears at most once, no guarantees on the output otherwise). The sk... | stack_v2_sparse_classes_36k_train_029807 | 24,996 | permissive | [
{
"docstring": "Initializes an empty sketch/sample of specified size. Args: k: Sample size p: The moment estimated by the sketch sample_p: The power of values used for the sampling weights, that is, the weight used for sampling an element (key, value) is going to be value ** sample_p.",
"name": "__init__",
... | 4 | stack_v2_sparse_classes_30k_train_005327 | Implement the Python class `PpsworSketch` described below.
Class description:
A simple implementation of PPSWOR sampling for aggregated data. Used as a benchmark for estimating moments with advice. The sketch assumes input that consists of (key, value) pairs, which is aggregated (each key appears at most once, no guar... | Implement the Python class `PpsworSketch` described below.
Class description:
A simple implementation of PPSWOR sampling for aggregated data. Used as a benchmark for estimating moments with advice. The sketch assumes input that consists of (key, value) pairs, which is aggregated (each key appears at most once, no guar... | 727ec399ad17b4dd1f71ce69a26fc3b0371d9fa7 | <|skeleton|>
class PpsworSketch:
"""A simple implementation of PPSWOR sampling for aggregated data. Used as a benchmark for estimating moments with advice. The sketch assumes input that consists of (key, value) pairs, which is aggregated (each key appears at most once, no guarantees on the output otherwise). The sk... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PpsworSketch:
"""A simple implementation of PPSWOR sampling for aggregated data. Used as a benchmark for estimating moments with advice. The sketch assumes input that consists of (key, value) pairs, which is aggregated (each key appears at most once, no guarantees on the output otherwise). The sketch supports... | the_stack_v2_python_sparse | moment_advice/moment_advice.py | Ayoob7/google-research | train | 2 |
1321df16179506d41263107f61f1c95e022cb1ca | [
"dictionary = self.__get_root_words_dict()\nstemmer = Stemmer(dictionary)\nreturn stemmer",
"words = super().get_words_from_file()\ndictionary = ArrayDictionary(words)\nreturn dictionary"
] | <|body_start_0|>
dictionary = self.__get_root_words_dict()
stemmer = Stemmer(dictionary)
return stemmer
<|end_body_0|>
<|body_start_1|>
words = super().get_words_from_file()
dictionary = ArrayDictionary(words)
return dictionary
<|end_body_1|>
| StemmerFactory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StemmerFactory:
def create(self):
"""Membuat Objek Stemmer"""
<|body_0|>
def __get_root_words_dict(self):
"""Mendapatkan Daftar Kata Dasar Default Sastrawi"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
dictionary = self.__get_root_words_dict()
... | stack_v2_sparse_classes_36k_train_029808 | 1,459 | no_license | [
{
"docstring": "Membuat Objek Stemmer",
"name": "create",
"signature": "def create(self)"
},
{
"docstring": "Mendapatkan Daftar Kata Dasar Default Sastrawi",
"name": "__get_root_words_dict",
"signature": "def __get_root_words_dict(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017690 | Implement the Python class `StemmerFactory` described below.
Class description:
Implement the StemmerFactory class.
Method signatures and docstrings:
- def create(self): Membuat Objek Stemmer
- def __get_root_words_dict(self): Mendapatkan Daftar Kata Dasar Default Sastrawi | Implement the Python class `StemmerFactory` described below.
Class description:
Implement the StemmerFactory class.
Method signatures and docstrings:
- def create(self): Membuat Objek Stemmer
- def __get_root_words_dict(self): Mendapatkan Daftar Kata Dasar Default Sastrawi
<|skeleton|>
class StemmerFactory:
def... | 9742c193251303334ef805c8c94eb075afad777f | <|skeleton|>
class StemmerFactory:
def create(self):
"""Membuat Objek Stemmer"""
<|body_0|>
def __get_root_words_dict(self):
"""Mendapatkan Daftar Kata Dasar Default Sastrawi"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StemmerFactory:
def create(self):
"""Membuat Objek Stemmer"""
dictionary = self.__get_root_words_dict()
stemmer = Stemmer(dictionary)
return stemmer
def __get_root_words_dict(self):
"""Mendapatkan Daftar Kata Dasar Default Sastrawi"""
words = super().get_wo... | the_stack_v2_python_sparse | ujian_app/penilaian/pemrosesan_teks/stemmer.py | anh4rs/Aplikasi-Penilaian-Otomatis-Esai-BI | train | 0 | |
0911aecfae2a7fe78165764280f29550ee1bbca7 | [
"QItemDelegate.__init__(self, parent)\nself.itemsDict = itemsDict\nself.column = column",
"if index.column() == self.column:\n cbo = QComboBox(parent)\n for item in self.itemsDict:\n cbo.addItem(item, self.itemsDict[item])\n return cbo\nreturn QItemDelegate.createEditor(self, parent, option, index... | <|body_start_0|>
QItemDelegate.__init__(self, parent)
self.itemsDict = itemsDict
self.column = column
<|end_body_0|>
<|body_start_1|>
if index.column() == self.column:
cbo = QComboBox(parent)
for item in self.itemsDict:
cbo.addItem(item, self.item... | ComboBoxDelegate | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ComboBoxDelegate:
def __init__(self, parent, itemsDict, column):
"""Constructor"""
<|body_0|>
def createEditor(self, parent, option, index):
"""Creates a custom editor to edit value map data"""
<|body_1|>
def setEditorData(self, editor, index):
"... | stack_v2_sparse_classes_36k_train_029809 | 16,608 | no_license | [
{
"docstring": "Constructor",
"name": "__init__",
"signature": "def __init__(self, parent, itemsDict, column)"
},
{
"docstring": "Creates a custom editor to edit value map data",
"name": "createEditor",
"signature": "def createEditor(self, parent, option, index)"
},
{
"docstring"... | 4 | null | Implement the Python class `ComboBoxDelegate` described below.
Class description:
Implement the ComboBoxDelegate class.
Method signatures and docstrings:
- def __init__(self, parent, itemsDict, column): Constructor
- def createEditor(self, parent, option, index): Creates a custom editor to edit value map data
- def s... | Implement the Python class `ComboBoxDelegate` described below.
Class description:
Implement the ComboBoxDelegate class.
Method signatures and docstrings:
- def __init__(self, parent, itemsDict, column): Constructor
- def createEditor(self, parent, option, index): Creates a custom editor to edit value map data
- def s... | edff378f356db3c0577ce34e618c5ae493d296ba | <|skeleton|>
class ComboBoxDelegate:
def __init__(self, parent, itemsDict, column):
"""Constructor"""
<|body_0|>
def createEditor(self, parent, option, index):
"""Creates a custom editor to edit value map data"""
<|body_1|>
def setEditorData(self, editor, index):
"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ComboBoxDelegate:
def __init__(self, parent, itemsDict, column):
"""Constructor"""
QItemDelegate.__init__(self, parent)
self.itemsDict = itemsDict
self.column = column
def createEditor(self, parent, option, index):
"""Creates a custom editor to edit value map data"... | the_stack_v2_python_sparse | ComplexTools/manageComplex.py | euriconicacio/DsgTools | train | 0 | |
d764cb7bd2c69d7ee18c303fd60e86d5d5b505af | [
"super().__init__(**kwargs)\ndiscriminator = []\nassert len(kernel_sizes) == 2\nassert kernel_sizes[0] % 2 == 1\nassert kernel_sizes[1] % 2 == 1\ndiscriminator = [TFReflectionPad1d((np.prod(kernel_sizes) - 1) // 2, padding_type=padding_type), tf.keras.layers.Conv1D(filters=filters, kernel_size=int(np.prod(kernel_si... | <|body_start_0|>
super().__init__(**kwargs)
discriminator = []
assert len(kernel_sizes) == 2
assert kernel_sizes[0] % 2 == 1
assert kernel_sizes[1] % 2 == 1
discriminator = [TFReflectionPad1d((np.prod(kernel_sizes) - 1) // 2, padding_type=padding_type), tf.keras.layers.Co... | Tensorflow MelGAN generator module. | TFMelGANDiscriminator | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TFMelGANDiscriminator:
"""Tensorflow MelGAN generator module."""
def __init__(self, out_channels=1, kernel_sizes=[5, 3], filters=16, max_downsample_filters=1024, use_bias=True, downsample_scales=[4, 4, 4, 4], nonlinear_activation='LeakyReLU', nonlinear_activation_params={'alpha': 0.2}, paddi... | stack_v2_sparse_classes_36k_train_029810 | 17,807 | permissive | [
{
"docstring": "Initilize MelGAN discriminator module. Args: out_channels (int): Number of output channels. kernel_sizes (list): List of two kernel sizes. The prod will be used for the first conv layer, and the first and the second kernel sizes will be used for the last two layers. For example if kernel_sizes =... | 3 | stack_v2_sparse_classes_30k_train_012219 | Implement the Python class `TFMelGANDiscriminator` described below.
Class description:
Tensorflow MelGAN generator module.
Method signatures and docstrings:
- def __init__(self, out_channels=1, kernel_sizes=[5, 3], filters=16, max_downsample_filters=1024, use_bias=True, downsample_scales=[4, 4, 4, 4], nonlinear_activ... | Implement the Python class `TFMelGANDiscriminator` described below.
Class description:
Tensorflow MelGAN generator module.
Method signatures and docstrings:
- def __init__(self, out_channels=1, kernel_sizes=[5, 3], filters=16, max_downsample_filters=1024, use_bias=True, downsample_scales=[4, 4, 4, 4], nonlinear_activ... | 136877136355c82d7ba474ceb7a8f133bd84767e | <|skeleton|>
class TFMelGANDiscriminator:
"""Tensorflow MelGAN generator module."""
def __init__(self, out_channels=1, kernel_sizes=[5, 3], filters=16, max_downsample_filters=1024, use_bias=True, downsample_scales=[4, 4, 4, 4], nonlinear_activation='LeakyReLU', nonlinear_activation_params={'alpha': 0.2}, paddi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TFMelGANDiscriminator:
"""Tensorflow MelGAN generator module."""
def __init__(self, out_channels=1, kernel_sizes=[5, 3], filters=16, max_downsample_filters=1024, use_bias=True, downsample_scales=[4, 4, 4, 4], nonlinear_activation='LeakyReLU', nonlinear_activation_params={'alpha': 0.2}, padding_type='REFL... | the_stack_v2_python_sparse | tensorflow_tts/models/melgan.py | TensorSpeech/TensorFlowTTS | train | 2,889 |
9a1a1b57b859eb1da0152c377adea0856fd9cd79 | [
"if l1 is None:\n return l2\nif l2 is None:\n return l1\ncur = ListNode(None)\nnewHead = cur\nwhile l1 is not None or l2 is not None:\n if l1.val <= l2.val:\n cur.next = l1\n l1 = l1.next\n else:\n cur.next = l2\n l2 = l2.next\n cur = cur.next\n if l1 is None:\n ... | <|body_start_0|>
if l1 is None:
return l2
if l2 is None:
return l1
cur = ListNode(None)
newHead = cur
while l1 is not None or l2 is not None:
if l1.val <= l2.val:
cur.next = l1
l1 = l1.next
else:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def mergeTwoLists(self, l1, l2):
""":type l1: ListNode :type l2: ListNode :rtype: ListNode"""
<|body_0|>
def mergeKListsSecond(self, lists):
""":type lists: List[ListNode] :rtype: ListNode"""
<|body_1|>
def mergeKLists(self, lists):
"""... | stack_v2_sparse_classes_36k_train_029811 | 1,955 | no_license | [
{
"docstring": ":type l1: ListNode :type l2: ListNode :rtype: ListNode",
"name": "mergeTwoLists",
"signature": "def mergeTwoLists(self, l1, l2)"
},
{
"docstring": ":type lists: List[ListNode] :rtype: ListNode",
"name": "mergeKListsSecond",
"signature": "def mergeKListsSecond(self, lists)... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeTwoLists(self, l1, l2): :type l1: ListNode :type l2: ListNode :rtype: ListNode
- def mergeKListsSecond(self, lists): :type lists: List[ListNode] :rtype: ListNode
- def m... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def mergeTwoLists(self, l1, l2): :type l1: ListNode :type l2: ListNode :rtype: ListNode
- def mergeKListsSecond(self, lists): :type lists: List[ListNode] :rtype: ListNode
- def m... | 88da6b274e49ce97d432e1f4d4de8efa55593836 | <|skeleton|>
class Solution:
def mergeTwoLists(self, l1, l2):
""":type l1: ListNode :type l2: ListNode :rtype: ListNode"""
<|body_0|>
def mergeKListsSecond(self, lists):
""":type lists: List[ListNode] :rtype: ListNode"""
<|body_1|>
def mergeKLists(self, lists):
"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def mergeTwoLists(self, l1, l2):
""":type l1: ListNode :type l2: ListNode :rtype: ListNode"""
if l1 is None:
return l2
if l2 is None:
return l1
cur = ListNode(None)
newHead = cur
while l1 is not None or l2 is not None:
... | the_stack_v2_python_sparse | 2nd/homework_7/id_52/mergeKLists_52.py | StuQAlgorithm/AlgorithmHomework | train | 6 | |
f8ff757a323ec25d1817f971a1a39e71a0de3287 | [
"res = []\nnums.sort()\nfor i, num in enumerate(nums[0:-2]):\n l = i + 1\n r = len(nums) - 1\n if nums[l] + nums[l + 1] + num > target:\n res.append(nums[l] + nums[l + 1] + num)\n elif nums[r] + nums[r - 1] + num < target:\n res.append(nums[r] + nums[r - 1] + num)\n else:\n while... | <|body_start_0|>
res = []
nums.sort()
for i, num in enumerate(nums[0:-2]):
l = i + 1
r = len(nums) - 1
if nums[l] + nums[l + 1] + num > target:
res.append(nums[l] + nums[l + 1] + num)
elif nums[r] + nums[r - 1] + num < target:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def threeSumClosest(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_0|>
def threeSumClosest_myfirst(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|... | stack_v2_sparse_classes_36k_train_029812 | 1,894 | no_license | [
{
"docstring": ":type nums: List[int] :type target: int :rtype: int",
"name": "threeSumClosest",
"signature": "def threeSumClosest(self, nums, target)"
},
{
"docstring": ":type nums: List[int] :type target: int :rtype: int",
"name": "threeSumClosest_myfirst",
"signature": "def threeSumCl... | 2 | stack_v2_sparse_classes_30k_train_011267 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def threeSumClosest(self, nums, target): :type nums: List[int] :type target: int :rtype: int
- def threeSumClosest_myfirst(self, nums, target): :type nums: List[int] :type target... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def threeSumClosest(self, nums, target): :type nums: List[int] :type target: int :rtype: int
- def threeSumClosest_myfirst(self, nums, target): :type nums: List[int] :type target... | f0d9070fa292ca36971a465a805faddb12025482 | <|skeleton|>
class Solution:
def threeSumClosest(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_0|>
def threeSumClosest_myfirst(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def threeSumClosest(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
res = []
nums.sort()
for i, num in enumerate(nums[0:-2]):
l = i + 1
r = len(nums) - 1
if nums[l] + nums[l + 1] + num > target:
... | the_stack_v2_python_sparse | 16.3SumClosest.py | JerryRoc/leetcode | train | 0 | |
3ea752b496dd506b0ef584709aefc59c05417052 | [
"if not root:\n return json.dumps([])\narr = []\nqueue = [[root, -1]]\nwhile queue:\n tmp = queue.pop(0)\n cur, parentIdx = (tmp[0], tmp[1])\n arr.append([cur.val, parentIdx])\n if cur.left:\n queue.append([cur.left, len(arr) - 1])\n if cur.right:\n queue.append([cur.right, len(arr) ... | <|body_start_0|>
if not root:
return json.dumps([])
arr = []
queue = [[root, -1]]
while queue:
tmp = queue.pop(0)
cur, parentIdx = (tmp[0], tmp[1])
arr.append([cur.val, parentIdx])
if cur.left:
queue.append([cur.... | Codec | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not root:
... | stack_v2_sparse_classes_36k_train_029813 | 1,317 | no_license | [
{
"docstring": "Encodes a tree to a single string.",
"name": "serialize",
"signature": "def serialize(self, root: TreeNode) -> str"
},
{
"docstring": "Decodes your encoded data to tree.",
"name": "deserialize",
"signature": "def deserialize(self, data: str) -> TreeNode"
}
] | 2 | stack_v2_sparse_classes_30k_train_010385 | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree. | Implement the Python class `Codec` described below.
Class description:
Implement the Codec class.
Method signatures and docstrings:
- def serialize(self, root: TreeNode) -> str: Encodes a tree to a single string.
- def deserialize(self, data: str) -> TreeNode: Decodes your encoded data to tree.
<|skeleton|>
class Co... | 6c716ee37fcb82387f050422f578daa142926101 | <|skeleton|>
class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
<|body_0|>
def deserialize(self, data: str) -> TreeNode:
"""Decodes your encoded data to tree."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Codec:
def serialize(self, root: TreeNode) -> str:
"""Encodes a tree to a single string."""
if not root:
return json.dumps([])
arr = []
queue = [[root, -1]]
while queue:
tmp = queue.pop(0)
cur, parentIdx = (tmp[0], tmp[1])
... | the_stack_v2_python_sparse | src/449.py | yibwu/leetcode | train | 0 | |
3eeb547f8ffd63a2dab465ddb5379577eaac4a1a | [
"fname = '{}/{}-test.csv'.format(lang, lang)\nfpath = os.path.join(self.data_dir, fname)\nreturn self._create_examples(self.read_csv(fpath), 'dev')",
"filename = '{}/{}-train.csv'.format(lang, lang)\nlines = self.read_csv(os.path.join(self.data_dir, filename))\nlabels = map(lambda l: l[2], lines)\nlabels = list(s... | <|body_start_0|>
fname = '{}/{}-test.csv'.format(lang, lang)
fpath = os.path.join(self.data_dir, fname)
return self._create_examples(self.read_csv(fpath), 'dev')
<|end_body_0|>
<|body_start_1|>
filename = '{}/{}-train.csv'.format(lang, lang)
lines = self.read_csv(os.path.join(se... | AmritaParaphraseExact | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AmritaParaphraseExact:
def get_dev_examples(self, lang):
"""See base class."""
<|body_0|>
def get_labels(self, lang):
"""See base class."""
<|body_1|>
def _create_examples(self, lines, set_type):
"""Creates examples for the training and dev sets.... | stack_v2_sparse_classes_36k_train_029814 | 17,110 | permissive | [
{
"docstring": "See base class.",
"name": "get_dev_examples",
"signature": "def get_dev_examples(self, lang)"
},
{
"docstring": "See base class.",
"name": "get_labels",
"signature": "def get_labels(self, lang)"
},
{
"docstring": "Creates examples for the training and dev sets.",
... | 3 | stack_v2_sparse_classes_30k_val_000119 | Implement the Python class `AmritaParaphraseExact` described below.
Class description:
Implement the AmritaParaphraseExact class.
Method signatures and docstrings:
- def get_dev_examples(self, lang): See base class.
- def get_labels(self, lang): See base class.
- def _create_examples(self, lines, set_type): Creates e... | Implement the Python class `AmritaParaphraseExact` described below.
Class description:
Implement the AmritaParaphraseExact class.
Method signatures and docstrings:
- def get_dev_examples(self, lang): See base class.
- def get_labels(self, lang): See base class.
- def _create_examples(self, lines, set_type): Creates e... | 83f37bf46822f87d0b4c2fc7566568675c6d006e | <|skeleton|>
class AmritaParaphraseExact:
def get_dev_examples(self, lang):
"""See base class."""
<|body_0|>
def get_labels(self, lang):
"""See base class."""
<|body_1|>
def _create_examples(self, lines, set_type):
"""Creates examples for the training and dev sets.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AmritaParaphraseExact:
def get_dev_examples(self, lang):
"""See base class."""
fname = '{}/{}-test.csv'.format(lang, lang)
fpath = os.path.join(self.data_dir, fname)
return self._create_examples(self.read_csv(fpath), 'dev')
def get_labels(self, lang):
"""See base c... | the_stack_v2_python_sparse | fine_tune/data/processors.py | euihyeonmoon/indic-bert | train | 0 | |
2f2627fd229e5362574970057b40fbdaca755406 | [
"sc_table = parse_table_name(sc_table, wait=wait, db_host=db_host, db_user=db_user, db_pass=db_pass, db_port=db_port)\nreeds_build = parse_table_name(reeds_build, wait=wait, db_host=db_host, db_user=db_user, db_pass=db_pass, db_port=db_port)\nsc_table = DataCleaner.rename_cols(sc_table, name_map=DataCleaner.REV_NAM... | <|body_start_0|>
sc_table = parse_table_name(sc_table, wait=wait, db_host=db_host, db_user=db_user, db_pass=db_pass, db_port=db_port)
reeds_build = parse_table_name(reeds_build, wait=wait, db_host=db_host, db_user=db_user, db_pass=db_pass, db_port=db_port)
sc_table = DataCleaner.rename_cols(sc_t... | Class to handle project GIDs for a plexos project. Can be used to make gid superset project points for 5min data. | ProjectGidHandler | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProjectGidHandler:
"""Class to handle project GIDs for a plexos project. Can be used to make gid superset project points for 5min data."""
def get_resource_gids(sc_table, reeds_build, wait=300, db_host='gds_edit.nrel.gov', db_user=None, db_pass=None, db_port=5432):
"""Get resource gi... | stack_v2_sparse_classes_36k_train_029815 | 18,002 | permissive | [
{
"docstring": "Get resource gids from a single reeds supply curve build Parameters ---------- sc_table : str | pd.DataFrame reV supply curve results (CSV file path or database.schema.name) reeds_build : str | pd.DataFrame REEDS buildout file with wait : int Integer seconds to wait for DB connection to become a... | 2 | stack_v2_sparse_classes_30k_train_001136 | Implement the Python class `ProjectGidHandler` described below.
Class description:
Class to handle project GIDs for a plexos project. Can be used to make gid superset project points for 5min data.
Method signatures and docstrings:
- def get_resource_gids(sc_table, reeds_build, wait=300, db_host='gds_edit.nrel.gov', d... | Implement the Python class `ProjectGidHandler` described below.
Class description:
Class to handle project GIDs for a plexos project. Can be used to make gid superset project points for 5min data.
Method signatures and docstrings:
- def get_resource_gids(sc_table, reeds_build, wait=300, db_host='gds_edit.nrel.gov', d... | 2dd05402c9c05ca0bf7f0e5bc2849ede0d0bc3cb | <|skeleton|>
class ProjectGidHandler:
"""Class to handle project GIDs for a plexos project. Can be used to make gid superset project points for 5min data."""
def get_resource_gids(sc_table, reeds_build, wait=300, db_host='gds_edit.nrel.gov', db_user=None, db_pass=None, db_port=5432):
"""Get resource gi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProjectGidHandler:
"""Class to handle project GIDs for a plexos project. Can be used to make gid superset project points for 5min data."""
def get_resource_gids(sc_table, reeds_build, wait=300, db_host='gds_edit.nrel.gov', db_user=None, db_pass=None, db_port=5432):
"""Get resource gids from a sin... | the_stack_v2_python_sparse | reVX/plexos/utilities.py | NREL/reVX | train | 10 |
b31dbddd2fb70acb1c19b2dfb5bfb8219b8e90b8 | [
"self.variables: List[V] = variables\nself.domains: Dict[V, List[D]] = domains\nself.constraints: Dict[V, List[Constraint[V, D]]] = {}\nfor variable in self.variables:\n self.constraints[variable] = []\n if variable not in self.domains:\n raise LookupError('Every variable should have a domain assigned ... | <|body_start_0|>
self.variables: List[V] = variables
self.domains: Dict[V, List[D]] = domains
self.constraints: Dict[V, List[Constraint[V, D]]] = {}
for variable in self.variables:
self.constraints[variable] = []
if variable not in self.domains:
ra... | A constraint satisfaction problem consists of variables of type V that have ranges of values known as domains of type D and constraints that determine whether a particular variable's domain selection is valid. | CSP | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CSP:
"""A constraint satisfaction problem consists of variables of type V that have ranges of values known as domains of type D and constraints that determine whether a particular variable's domain selection is valid."""
def __init__(self, variables: List[V], domains: Dict[V, List[D]]) -> No... | stack_v2_sparse_classes_36k_train_029816 | 10,604 | no_license | [
{
"docstring": "Constructor for CSP class.",
"name": "__init__",
"signature": "def __init__(self, variables: List[V], domains: Dict[V, List[D]]) -> None"
},
{
"docstring": "This method adds constraint to variables as per their domains.",
"name": "add_constraint",
"signature": "def add_co... | 4 | stack_v2_sparse_classes_30k_test_000277 | Implement the Python class `CSP` described below.
Class description:
A constraint satisfaction problem consists of variables of type V that have ranges of values known as domains of type D and constraints that determine whether a particular variable's domain selection is valid.
Method signatures and docstrings:
- def... | Implement the Python class `CSP` described below.
Class description:
A constraint satisfaction problem consists of variables of type V that have ranges of values known as domains of type D and constraints that determine whether a particular variable's domain selection is valid.
Method signatures and docstrings:
- def... | 892d9c25b9712bf3bbfd7f29529eca8b47fb8039 | <|skeleton|>
class CSP:
"""A constraint satisfaction problem consists of variables of type V that have ranges of values known as domains of type D and constraints that determine whether a particular variable's domain selection is valid."""
def __init__(self, variables: List[V], domains: Dict[V, List[D]]) -> No... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CSP:
"""A constraint satisfaction problem consists of variables of type V that have ranges of values known as domains of type D and constraints that determine whether a particular variable's domain selection is valid."""
def __init__(self, variables: List[V], domains: Dict[V, List[D]]) -> None:
"... | the_stack_v2_python_sparse | sem-4/Lab7_15_2/Lab7_GraphColoringProblem_ConstraintSatisfactionAlgorithm.py | B-Tech-AI-Python/Class-assignments | train | 0 |
5dc4e213daef57cb10919bb09b98075aeb004d7a | [
"if not lists:\n return None\nleft, right = (0, len(lists) - 1)\nwhile right > 0:\n if left >= right:\n left = 0\n else:\n lists[left] = self.merge_two(lists[left], lists[right])\n left += 1\n right -= 1\nreturn lists[0]",
"curr = dummy = ListNode('X')\nwhile l1 and l2:\n i... | <|body_start_0|>
if not lists:
return None
left, right = (0, len(lists) - 1)
while right > 0:
if left >= right:
left = 0
else:
lists[left] = self.merge_two(lists[left], lists[right])
left += 1
rig... | Solution_STD | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution_STD:
def mergeKLists(self, lists: List[ListNode]) -> ListNode:
"""Improved from C1 这个方法采用首尾合并, 这样能显著减少重复流经的节点 首尾相遇后, 重置首为0, 尾不变(因为已经都被合并到前面去了)"""
<|body_0|>
def merge_two(self, l1: ListNode, l2: ListNode) -> ListNode:
"""Helper for Solution C1 and C2 (now se... | stack_v2_sparse_classes_36k_train_029817 | 4,145 | permissive | [
{
"docstring": "Improved from C1 这个方法采用首尾合并, 这样能显著减少重复流经的节点 首尾相遇后, 重置首为0, 尾不变(因为已经都被合并到前面去了)",
"name": "mergeKLists",
"signature": "def mergeKLists(self, lists: List[ListNode]) -> ListNode"
},
{
"docstring": "Helper for Solution C1 and C2 (now set out side of the Solution) merge two sorted linke... | 2 | stack_v2_sparse_classes_30k_train_018431 | Implement the Python class `Solution_STD` described below.
Class description:
Implement the Solution_STD class.
Method signatures and docstrings:
- def mergeKLists(self, lists: List[ListNode]) -> ListNode: Improved from C1 这个方法采用首尾合并, 这样能显著减少重复流经的节点 首尾相遇后, 重置首为0, 尾不变(因为已经都被合并到前面去了)
- def merge_two(self, l1: ListNode,... | Implement the Python class `Solution_STD` described below.
Class description:
Implement the Solution_STD class.
Method signatures and docstrings:
- def mergeKLists(self, lists: List[ListNode]) -> ListNode: Improved from C1 这个方法采用首尾合并, 这样能显著减少重复流经的节点 首尾相遇后, 重置首为0, 尾不变(因为已经都被合并到前面去了)
- def merge_two(self, l1: ListNode,... | 143422321cbc3715ca08f6c3af8f960a55887ced | <|skeleton|>
class Solution_STD:
def mergeKLists(self, lists: List[ListNode]) -> ListNode:
"""Improved from C1 这个方法采用首尾合并, 这样能显著减少重复流经的节点 首尾相遇后, 重置首为0, 尾不变(因为已经都被合并到前面去了)"""
<|body_0|>
def merge_two(self, l1: ListNode, l2: ListNode) -> ListNode:
"""Helper for Solution C1 and C2 (now se... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution_STD:
def mergeKLists(self, lists: List[ListNode]) -> ListNode:
"""Improved from C1 这个方法采用首尾合并, 这样能显著减少重复流经的节点 首尾相遇后, 重置首为0, 尾不变(因为已经都被合并到前面去了)"""
if not lists:
return None
left, right = (0, len(lists) - 1)
while right > 0:
if left >= right:
... | the_stack_v2_python_sparse | LeetCode/LC023_merge_k_sorted_list.py | jxie0755/Learning_Python | train | 0 | |
6c003d885c6f3e5640b9007dfd07ad17d5e3461f | [
"field_name, rest = _get_field_name_and_rest(field)\ntry:\n field = model._meta.get_field(field_name)\n if isinstance(field, OneToOneRel):\n return self.is_valid_field(field.related_model, rest)\n if field.rel and rest:\n return self.is_valid_field(field.rel.to, rest)\n return True\nexcept... | <|body_start_0|>
field_name, rest = _get_field_name_and_rest(field)
try:
field = model._meta.get_field(field_name)
if isinstance(field, OneToOneRel):
return self.is_valid_field(field.related_model, rest)
if field.rel and rest:
return se... | Extends OrderingFilter to support ordering by fields in related models using Django orm '__'. This class is copied and changed from the patch of the github issue. https://github.com/encode/django-rest-framework/issues/1005#issuecomment-289555282 This is based on rest_framework 3.2.5 because pdc-server is using this ver... | RelatedNestedOrderingFilter | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RelatedNestedOrderingFilter:
"""Extends OrderingFilter to support ordering by fields in related models using Django orm '__'. This class is copied and changed from the patch of the github issue. https://github.com/encode/django-rest-framework/issues/1005#issuecomment-289555282 This is based on re... | stack_v2_sparse_classes_36k_train_029818 | 4,416 | permissive | [
{
"docstring": "Return true if the field exists within the model (or in the related model specified using the Django ORM __ notation)",
"name": "is_valid_field",
"signature": "def is_valid_field(self, model, field)"
},
{
"docstring": "Rewrite the remove_invalid_fields methods and add the nested ... | 2 | stack_v2_sparse_classes_30k_train_006722 | Implement the Python class `RelatedNestedOrderingFilter` described below.
Class description:
Extends OrderingFilter to support ordering by fields in related models using Django orm '__'. This class is copied and changed from the patch of the github issue. https://github.com/encode/django-rest-framework/issues/1005#iss... | Implement the Python class `RelatedNestedOrderingFilter` described below.
Class description:
Extends OrderingFilter to support ordering by fields in related models using Django orm '__'. This class is copied and changed from the patch of the github issue. https://github.com/encode/django-rest-framework/issues/1005#iss... | af79f73c30fa5f5709ba03d584b7a49b83166b81 | <|skeleton|>
class RelatedNestedOrderingFilter:
"""Extends OrderingFilter to support ordering by fields in related models using Django orm '__'. This class is copied and changed from the patch of the github issue. https://github.com/encode/django-rest-framework/issues/1005#issuecomment-289555282 This is based on re... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RelatedNestedOrderingFilter:
"""Extends OrderingFilter to support ordering by fields in related models using Django orm '__'. This class is copied and changed from the patch of the github issue. https://github.com/encode/django-rest-framework/issues/1005#issuecomment-289555282 This is based on rest_framework ... | the_stack_v2_python_sparse | pdc/apps/utils/utils.py | product-definition-center/product-definition-center | train | 19 |
292264cfc982b8615c66907afe2794555183e64b | [
"if head == None or head.next == None:\n return head\ndummy = ListNode(-1000)\ndummy.next = head\nslow = dummy\nfast = dummy.next\nwhile fast:\n if fast.next and fast.next.val == fast.val:\n tmp = fast.val\n while fast and tmp == fast.val:\n fast = fast.next\n else:\n slow.n... | <|body_start_0|>
if head == None or head.next == None:
return head
dummy = ListNode(-1000)
dummy.next = head
slow = dummy
fast = dummy.next
while fast:
if fast.next and fast.next.val == fast.val:
tmp = fast.val
while... | Solution | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def deleteDuplicates(self, head: ListNode) -> ListNode:
"""迭代 :param head: :return:"""
<|body_0|>
def deleteDuplicates2(self, head: ListNode) -> ListNode:
"""感觉会用到两个循环 假设第一个virtual_node为自己创建的，node后面跟head 快指针指向head.next 慢指针指向head 当 head存在，循环遍历head.next 如果存在，... | stack_v2_sparse_classes_36k_train_029819 | 2,768 | permissive | [
{
"docstring": "迭代 :param head: :return:",
"name": "deleteDuplicates",
"signature": "def deleteDuplicates(self, head: ListNode) -> ListNode"
},
{
"docstring": "感觉会用到两个循环 假设第一个virtual_node为自己创建的，node后面跟head 快指针指向head.next 慢指针指向head 当 head存在，循环遍历head.next 如果存在，判断是否相等。如果不等，head为head.next 慢指针指向head ... | 4 | stack_v2_sparse_classes_30k_train_006045 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def deleteDuplicates(self, head: ListNode) -> ListNode: 迭代 :param head: :return:
- def deleteDuplicates2(self, head: ListNode) -> ListNode: 感觉会用到两个循环 假设第一个virtual_node为自己创建的，node... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def deleteDuplicates(self, head: ListNode) -> ListNode: 迭代 :param head: :return:
- def deleteDuplicates2(self, head: ListNode) -> ListNode: 感觉会用到两个循环 假设第一个virtual_node为自己创建的，node... | 41f4b8b557cf15cbd602f187f6550184b3a108ec | <|skeleton|>
class Solution:
def deleteDuplicates(self, head: ListNode) -> ListNode:
"""迭代 :param head: :return:"""
<|body_0|>
def deleteDuplicates2(self, head: ListNode) -> ListNode:
"""感觉会用到两个循环 假设第一个virtual_node为自己创建的，node后面跟head 快指针指向head.next 慢指针指向head 当 head存在，循环遍历head.next 如果存在，... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def deleteDuplicates(self, head: ListNode) -> ListNode:
"""迭代 :param head: :return:"""
if head == None or head.next == None:
return head
dummy = ListNode(-1000)
dummy.next = head
slow = dummy
fast = dummy.next
while fast:
... | the_stack_v2_python_sparse | leetcode/82. 删除排序链表中的重复元素 II.py | zhongmb/suanfa | train | 0 | |
d283d7777f0a055648dbbd3de345dcc0b327d241 | [
"login_page.LoginPage(self.driver).login()\nsleep(2)\nlandlord_nav_page.LandlordNavPage(self.driver).Iamlandlord()\nsleep(2)\nlandlord_nav_page.LandlordNavPage(self.driver).close_weiChat()\nsleep(2)\nlandlord_nav_page.LandlordNavPage(self.driver).activitymanager()\nsleep(1)\nlandlord_nav_page.LandlordNavPage(self.d... | <|body_start_0|>
login_page.LoginPage(self.driver).login()
sleep(2)
landlord_nav_page.LandlordNavPage(self.driver).Iamlandlord()
sleep(2)
landlord_nav_page.LandlordNavPage(self.driver).close_weiChat()
sleep(2)
landlord_nav_page.LandlordNavPage(self.driver).activit... | 活动设置 | TestActivity | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestActivity:
"""活动设置"""
def test_active_good(self):
"""活动好处"""
<|body_0|>
def test_regular_desc(self):
"""活动规则"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
login_page.LoginPage(self.driver).login()
sleep(2)
landlord_nav_page.... | stack_v2_sparse_classes_36k_train_029820 | 1,807 | permissive | [
{
"docstring": "活动好处",
"name": "test_active_good",
"signature": "def test_active_good(self)"
},
{
"docstring": "活动规则",
"name": "test_regular_desc",
"signature": "def test_regular_desc(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012113 | Implement the Python class `TestActivity` described below.
Class description:
活动设置
Method signatures and docstrings:
- def test_active_good(self): 活动好处
- def test_regular_desc(self): 活动规则 | Implement the Python class `TestActivity` described below.
Class description:
活动设置
Method signatures and docstrings:
- def test_active_good(self): 活动好处
- def test_regular_desc(self): 活动规则
<|skeleton|>
class TestActivity:
"""活动设置"""
def test_active_good(self):
"""活动好处"""
<|body_0|>
def t... | 192c70c49a8e9e072b9d0d0136f02c653c589410 | <|skeleton|>
class TestActivity:
"""活动设置"""
def test_active_good(self):
"""活动好处"""
<|body_0|>
def test_regular_desc(self):
"""活动规则"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestActivity:
"""活动设置"""
def test_active_good(self):
"""活动好处"""
login_page.LoginPage(self.driver).login()
sleep(2)
landlord_nav_page.LandlordNavPage(self.driver).Iamlandlord()
sleep(2)
landlord_nav_page.LandlordNavPage(self.driver).close_weiChat()
s... | the_stack_v2_python_sparse | mayi/test_case/test_landlord_activity.py | 18701016443/mayi | train | 0 |
446f93db141f6f425732417fb84e211bbd69465d | [
"super().__init__()\nself.mha = MultiHeadAttention(dm, h)\nself.ffn = point_wise_feed_forward_network(dm, hidden)\nself.layernorm1 = tf.keras.layers.LayerNormalization(epsilon=1e-06)\nself.layernorm2 = tf.keras.layers.LayerNormalization(epsilon=1e-06)\nself.dropout1 = tf.keras.layers.Dropout(drop_rate)\nself.dropou... | <|body_start_0|>
super().__init__()
self.mha = MultiHeadAttention(dm, h)
self.ffn = point_wise_feed_forward_network(dm, hidden)
self.layernorm1 = tf.keras.layers.LayerNormalization(epsilon=1e-06)
self.layernorm2 = tf.keras.layers.LayerNormalization(epsilon=1e-06)
self.dro... | class Encoder block | EncoderBlock | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EncoderBlock:
"""class Encoder block"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""* dm - the dimensionality of the model * h - the number of heads * hidden - the number of hidden units in the fully connected layer * drop_rate - the dropout rate Sets the following public in... | stack_v2_sparse_classes_36k_train_029821 | 18,002 | no_license | [
{
"docstring": "* dm - the dimensionality of the model * h - the number of heads * hidden - the number of hidden units in the fully connected layer * drop_rate - the dropout rate Sets the following public instance attributes: * mha - a MultiHeadAttention layer * dense_hidden - the hidden dense layer with hidden... | 2 | stack_v2_sparse_classes_30k_train_008533 | Implement the Python class `EncoderBlock` described below.
Class description:
class Encoder block
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1): * dm - the dimensionality of the model * h - the number of heads * hidden - the number of hidden units in the fully connected layer * ... | Implement the Python class `EncoderBlock` described below.
Class description:
class Encoder block
Method signatures and docstrings:
- def __init__(self, dm, h, hidden, drop_rate=0.1): * dm - the dimensionality of the model * h - the number of heads * hidden - the number of hidden units in the fully connected layer * ... | 8ad4c2594ff78b345dbd92e9d54d2a143ac4071a | <|skeleton|>
class EncoderBlock:
"""class Encoder block"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""* dm - the dimensionality of the model * h - the number of heads * hidden - the number of hidden units in the fully connected layer * drop_rate - the dropout rate Sets the following public in... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EncoderBlock:
"""class Encoder block"""
def __init__(self, dm, h, hidden, drop_rate=0.1):
"""* dm - the dimensionality of the model * h - the number of heads * hidden - the number of hidden units in the fully connected layer * drop_rate - the dropout rate Sets the following public instance attrib... | the_stack_v2_python_sparse | supervised_learning/0x12-transformer_apps/5-transformer.py | jorgezafra94/holbertonschool-machine_learning | train | 1 |
9adef181bfce5395e5aa881bb040f1f7620e49ab | [
"config = mock.Mock()\nconfig.workspace = 'workspace'\nconfig.benchmark_method_patterns = ['new_foo.BenchmarkClass.filter:bench.*']\nbenchmark_runner = benchmark.BenchmarkRunner(config)\nmock_benchmark_class = mock.Mock()\nmock_benchmark_class.benchmark_method_1 = 'foo'\nmock_module = mock.Mock()\nsys.modules['new_... | <|body_start_0|>
config = mock.Mock()
config.workspace = 'workspace'
config.benchmark_method_patterns = ['new_foo.BenchmarkClass.filter:bench.*']
benchmark_runner = benchmark.BenchmarkRunner(config)
mock_benchmark_class = mock.Mock()
mock_benchmark_class.benchmark_method_... | TestBenchmarkRunner | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestBenchmarkRunner:
def test_get_benchmark_methods_filter(self):
"""Tests returning methods on a class based on a filter."""
<|body_0|>
def test_get_benchmark_methods_exact_match(self):
"""Tests returning methods on a class based on a filter."""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_029822 | 2,160 | permissive | [
{
"docstring": "Tests returning methods on a class based on a filter.",
"name": "test_get_benchmark_methods_filter",
"signature": "def test_get_benchmark_methods_filter(self)"
},
{
"docstring": "Tests returning methods on a class based on a filter.",
"name": "test_get_benchmark_methods_exact... | 2 | stack_v2_sparse_classes_30k_train_014447 | Implement the Python class `TestBenchmarkRunner` described below.
Class description:
Implement the TestBenchmarkRunner class.
Method signatures and docstrings:
- def test_get_benchmark_methods_filter(self): Tests returning methods on a class based on a filter.
- def test_get_benchmark_methods_exact_match(self): Tests... | Implement the Python class `TestBenchmarkRunner` described below.
Class description:
Implement the TestBenchmarkRunner class.
Method signatures and docstrings:
- def test_get_benchmark_methods_filter(self): Tests returning methods on a class based on a filter.
- def test_get_benchmark_methods_exact_match(self): Tests... | c8e97df0d4d3d0c1020b98391c526df12371fc30 | <|skeleton|>
class TestBenchmarkRunner:
def test_get_benchmark_methods_filter(self):
"""Tests returning methods on a class based on a filter."""
<|body_0|>
def test_get_benchmark_methods_exact_match(self):
"""Tests returning methods on a class based on a filter."""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestBenchmarkRunner:
def test_get_benchmark_methods_filter(self):
"""Tests returning methods on a class based on a filter."""
config = mock.Mock()
config.workspace = 'workspace'
config.benchmark_method_patterns = ['new_foo.BenchmarkClass.filter:bench.*']
benchmark_runne... | the_stack_v2_python_sparse | perfzero/lib/benchmark_test.py | tensorflow/benchmarks | train | 1,182 | |
5bc70628e80e7745f4ccd4caf5a7e25e799ec366 | [
"return True\nif not attendee:\n return True\nevent = attendee.event\ndisable_ack_email = event.owner.groups.filter(name__iexact='disable ack email').count()\nif disable_ack_email:\n return True\nuser = attendee.attendee\nif user:\n email_template('[%s] Thanks for registering!' % settings.UI_SETTINGS['UI_S... | <|body_start_0|>
return True
if not attendee:
return True
event = attendee.event
disable_ack_email = event.owner.groups.filter(name__iexact='disable ack email').count()
if disable_ack_email:
return True
user = attendee.attendee
if user:
... | AttendeeProcessor | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AttendeeProcessor:
def ack_attendee(self, attendee):
"""Send an email to the fan who registered for an event. Don't send email if the event owner belongs to the group 'Disable ack email'."""
<|body_0|>
def event_faved(self, attendee):
"""Email users when a friend fav... | stack_v2_sparse_classes_36k_train_029823 | 7,085 | no_license | [
{
"docstring": "Send an email to the fan who registered for an event. Don't send email if the event owner belongs to the group 'Disable ack email'.",
"name": "ack_attendee",
"signature": "def ack_attendee(self, attendee)"
},
{
"docstring": "Email users when a friend favorites an event they've fa... | 2 | null | Implement the Python class `AttendeeProcessor` described below.
Class description:
Implement the AttendeeProcessor class.
Method signatures and docstrings:
- def ack_attendee(self, attendee): Send an email to the fan who registered for an event. Don't send email if the event owner belongs to the group 'Disable ack em... | Implement the Python class `AttendeeProcessor` described below.
Class description:
Implement the AttendeeProcessor class.
Method signatures and docstrings:
- def ack_attendee(self, attendee): Send an email to the fan who registered for an event. Don't send email if the event owner belongs to the group 'Disable ack em... | 0992126edf1469f6d348f5064e42d38229a35637 | <|skeleton|>
class AttendeeProcessor:
def ack_attendee(self, attendee):
"""Send an email to the fan who registered for an event. Don't send email if the event owner belongs to the group 'Disable ack email'."""
<|body_0|>
def event_faved(self, attendee):
"""Email users when a friend fav... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AttendeeProcessor:
def ack_attendee(self, attendee):
"""Send an email to the fan who registered for an event. Don't send email if the event owner belongs to the group 'Disable ack email'."""
return True
if not attendee:
return True
event = attendee.event
dis... | the_stack_v2_python_sparse | django-apps/event/queue_processor.py | kabirh/riotvine | train | 1 | |
7ce419484239945874650041c5a0fe02f16a476d | [
"if len(prices) == 0:\n return 0\nbuy = [0] * len(prices)\nsell = buy.copy()\nstop = buy.copy()\nbuy[0], sell[0], stop[0] = (-prices[0], 0, 0)\nfor i in range(1, len(prices)):\n buy[i] = max(stop[i - 1] - prices[i], buy[i - 1])\n sell[i] = buy[i - 1] + prices[i]\n stop[i] = max(stop[i - 1], sell[i - 1])... | <|body_start_0|>
if len(prices) == 0:
return 0
buy = [0] * len(prices)
sell = buy.copy()
stop = buy.copy()
buy[0], sell[0], stop[0] = (-prices[0], 0, 0)
for i in range(1, len(prices)):
buy[i] = max(stop[i - 1] - prices[i], buy[i - 1])
s... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxProfit(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_0|>
def maxProfit_old(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if len(prices) == 0:
retu... | stack_v2_sparse_classes_36k_train_029824 | 1,097 | permissive | [
{
"docstring": ":type prices: List[int] :rtype: int",
"name": "maxProfit",
"signature": "def maxProfit(self, prices)"
},
{
"docstring": ":type prices: List[int] :rtype: int",
"name": "maxProfit_old",
"signature": "def maxProfit_old(self, prices)"
}
] | 2 | stack_v2_sparse_classes_30k_train_018826 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices): :type prices: List[int] :rtype: int
- def maxProfit_old(self, prices): :type prices: List[int] :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxProfit(self, prices): :type prices: List[int] :rtype: int
- def maxProfit_old(self, prices): :type prices: List[int] :rtype: int
<|skeleton|>
class Solution:
def max... | d203aecd1afe1af13a0384a9c657c8424aab322d | <|skeleton|>
class Solution:
def maxProfit(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_0|>
def maxProfit_old(self, prices):
""":type prices: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxProfit(self, prices):
""":type prices: List[int] :rtype: int"""
if len(prices) == 0:
return 0
buy = [0] * len(prices)
sell = buy.copy()
stop = buy.copy()
buy[0], sell[0], stop[0] = (-prices[0], 0, 0)
for i in range(1, len(pri... | the_stack_v2_python_sparse | medium/Q309_BestTimeToBuyAndSellStockWithCooldown.py | Kaciras/leetcode | train | 0 | |
5b37a4471322a633d7ad60d4606ad9a5f6aaca7a | [
"self.maze = maze\nself.rat_1 = rat_1\nself.rat_2 = rat_2\nself.num_sprouts_left = 0\nfor i in range(len(self.maze)):\n row = self.maze[i]\n self.num_sprouts_left += row.count('@')",
"if self.maze[row][col] == '#':\n return True\nelse:\n return False",
"if row == self.rat_1.row and col == self.rat_1... | <|body_start_0|>
self.maze = maze
self.rat_1 = rat_1
self.rat_2 = rat_2
self.num_sprouts_left = 0
for i in range(len(self.maze)):
row = self.maze[i]
self.num_sprouts_left += row.count('@')
<|end_body_0|>
<|body_start_1|>
if self.maze[row][col] == ... | A 2D maze. | Maze | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Maze:
"""A 2D maze."""
def __init__(self, maze, rat_1, rat_2):
"""(Maze, list of list of str, Rat, Rat) -> NoneType Initialize a maze with two rats. Args: maze (list of list of str): a maze with contents. rat_1 (object): the first rat in the maze. rat_2 (object): the second rat in th... | stack_v2_sparse_classes_36k_train_029825 | 6,001 | permissive | [
{
"docstring": "(Maze, list of list of str, Rat, Rat) -> NoneType Initialize a maze with two rats. Args: maze (list of list of str): a maze with contents. rat_1 (object): the first rat in the maze. rat_2 (object): the second rat in the maze. Example call: Maze([['#', '#', '#', '#', '#', '#', '#'], ['#', '.', '.... | 5 | stack_v2_sparse_classes_30k_train_010375 | Implement the Python class `Maze` described below.
Class description:
A 2D maze.
Method signatures and docstrings:
- def __init__(self, maze, rat_1, rat_2): (Maze, list of list of str, Rat, Rat) -> NoneType Initialize a maze with two rats. Args: maze (list of list of str): a maze with contents. rat_1 (object): the fi... | Implement the Python class `Maze` described below.
Class description:
A 2D maze.
Method signatures and docstrings:
- def __init__(self, maze, rat_1, rat_2): (Maze, list of list of str, Rat, Rat) -> NoneType Initialize a maze with two rats. Args: maze (list of list of str): a maze with contents. rat_1 (object): the fi... | ff265343635a0109b6deab31f2a112d304d020cb | <|skeleton|>
class Maze:
"""A 2D maze."""
def __init__(self, maze, rat_1, rat_2):
"""(Maze, list of list of str, Rat, Rat) -> NoneType Initialize a maze with two rats. Args: maze (list of list of str): a maze with contents. rat_1 (object): the first rat in the maze. rat_2 (object): the second rat in th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Maze:
"""A 2D maze."""
def __init__(self, maze, rat_1, rat_2):
"""(Maze, list of list of str, Rat, Rat) -> NoneType Initialize a maze with two rats. Args: maze (list of list of str): a maze with contents. rat_1 (object): the first rat in the maze. rat_2 (object): the second rat in the maze. Examp... | the_stack_v2_python_sparse | Crafting_Quality_Code_UniToronto/week5_functions/assignment/a2.py | bounty030/Coursera | train | 1 |
fce59d35390e58115b540b80fb507735f53a267c | [
"valid, message = json_validate(nrange, {'type': 'object', 'properties': {'lower': {'$ref': '#/pScheduler/Numeric'}, 'upper': {'$ref': '#/pScheduler/Numeric'}}, 'additionalProperties': False, 'required': ['lower', 'upper']})\nif not valid:\n raise ValueError('Invalid numeric range: %s' % message)\nlower = nrange... | <|body_start_0|>
valid, message = json_validate(nrange, {'type': 'object', 'properties': {'lower': {'$ref': '#/pScheduler/Numeric'}, 'upper': {'$ref': '#/pScheduler/Numeric'}}, 'additionalProperties': False, 'required': ['lower', 'upper']})
if not valid:
raise ValueError('Invalid numeric ran... | Range of numbers | NumericRange | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumericRange:
"""Range of numbers"""
def __init__(self, nrange):
"""Construct a range from a JSON NumericRange."""
<|body_0|>
def __contains__(self, number):
"""See if the range contains the specified number, which can be any Numeric."""
<|body_1|>
d... | stack_v2_sparse_classes_36k_train_029826 | 2,607 | permissive | [
{
"docstring": "Construct a range from a JSON NumericRange.",
"name": "__init__",
"signature": "def __init__(self, nrange)"
},
{
"docstring": "See if the range contains the specified number, which can be any Numeric.",
"name": "__contains__",
"signature": "def __contains__(self, number)"... | 3 | stack_v2_sparse_classes_30k_train_001348 | Implement the Python class `NumericRange` described below.
Class description:
Range of numbers
Method signatures and docstrings:
- def __init__(self, nrange): Construct a range from a JSON NumericRange.
- def __contains__(self, number): See if the range contains the specified number, which can be any Numeric.
- def c... | Implement the Python class `NumericRange` described below.
Class description:
Range of numbers
Method signatures and docstrings:
- def __init__(self, nrange): Construct a range from a JSON NumericRange.
- def __contains__(self, number): See if the range contains the specified number, which can be any Numeric.
- def c... | f6d04c0455e5be4d490df16ec1acb377f9025d9f | <|skeleton|>
class NumericRange:
"""Range of numbers"""
def __init__(self, nrange):
"""Construct a range from a JSON NumericRange."""
<|body_0|>
def __contains__(self, number):
"""See if the range contains the specified number, which can be any Numeric."""
<|body_1|>
d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NumericRange:
"""Range of numbers"""
def __init__(self, nrange):
"""Construct a range from a JSON NumericRange."""
valid, message = json_validate(nrange, {'type': 'object', 'properties': {'lower': {'$ref': '#/pScheduler/Numeric'}, 'upper': {'$ref': '#/pScheduler/Numeric'}}, 'additionalPro... | the_stack_v2_python_sparse | python-pscheduler/pscheduler/pscheduler/numericrange.py | perfsonar/pscheduler | train | 53 |
70c84f975ee6d31b632aa6e6ab35d66871b98887 | [
"self.min_date = min([d for d, c in data]).date()\nself.max_date = max([d for d, c in data]).date()\nself.day_count = (self.max_date - self.min_date).days + 1\nself.dates = [self.min_date + timedelta(n) for n in range(self.day_count)]\nself.cameras = sorted(set([c for d, c in data]))\nself.per_camera = {c: {} for c... | <|body_start_0|>
self.min_date = min([d for d, c in data]).date()
self.max_date = max([d for d, c in data]).date()
self.day_count = (self.max_date - self.min_date).days + 1
self.dates = [self.min_date + timedelta(n) for n in range(self.day_count)]
self.cameras = sorted(set([c for... | Encapsulates a set of measured data for one or more cameras. | CameraData | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CameraData:
"""Encapsulates a set of measured data for one or more cameras."""
def __init__(self, data):
"""Initializes from a list of (datetime, camera) email tuples."""
<|body_0|>
def createPlot(self):
"""Creates a comprehensive graphical output using current d... | stack_v2_sparse_classes_36k_train_029827 | 9,251 | permissive | [
{
"docstring": "Initializes from a list of (datetime, camera) email tuples.",
"name": "__init__",
"signature": "def __init__(self, data)"
},
{
"docstring": "Creates a comprehensive graphical output using current data.",
"name": "createPlot",
"signature": "def createPlot(self)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_003831 | Implement the Python class `CameraData` described below.
Class description:
Encapsulates a set of measured data for one or more cameras.
Method signatures and docstrings:
- def __init__(self, data): Initializes from a list of (datetime, camera) email tuples.
- def createPlot(self): Creates a comprehensive graphical o... | Implement the Python class `CameraData` described below.
Class description:
Encapsulates a set of measured data for one or more cameras.
Method signatures and docstrings:
- def __init__(self, data): Initializes from a list of (datetime, camera) email tuples.
- def createPlot(self): Creates a comprehensive graphical o... | cec8fae0c1872bbd91b244775bee18d5db831581 | <|skeleton|>
class CameraData:
"""Encapsulates a set of measured data for one or more cameras."""
def __init__(self, data):
"""Initializes from a list of (datetime, camera) email tuples."""
<|body_0|>
def createPlot(self):
"""Creates a comprehensive graphical output using current d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CameraData:
"""Encapsulates a set of measured data for one or more cameras."""
def __init__(self, data):
"""Initializes from a list of (datetime, camera) email tuples."""
self.min_date = min([d for d, c in data]).date()
self.max_date = max([d for d, c in data]).date()
self... | the_stack_v2_python_sparse | camera_event_trending.py | jodysankey/scripts | train | 0 |
489f02def2ac5b3e94619dd971be18c8e82a4d98 | [
"super(MySQLCompaniesTable, self).__init__(db_dict, dbtype, verbose)\nself.connectdb(db_dict, verbose)\nself._load_table()",
"cursor = self.connection.cursor()\nsql = 'INSERT INTO Companies (CompanyName) VALUES (%s)'\ndata = company_name\ntry:\n cursor.execute(sql, (data,))\n self.connection.commit()\n a... | <|body_start_0|>
super(MySQLCompaniesTable, self).__init__(db_dict, dbtype, verbose)
self.connectdb(db_dict, verbose)
self._load_table()
<|end_body_0|>
<|body_start_1|>
cursor = self.connection.cursor()
sql = 'INSERT INTO Companies (CompanyName) VALUES (%s)'
data = compa... | Class representing the connection with a mysql database | MySQLCompaniesTable | [
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MySQLCompaniesTable:
"""Class representing the connection with a mysql database"""
def __init__(self, db_dict, dbtype, verbose):
"""Read the input file into a dictionary."""
<|body_0|>
def insert(self, company_name):
"""Write a new record to the programs table of... | stack_v2_sparse_classes_36k_train_029828 | 9,313 | permissive | [
{
"docstring": "Read the input file into a dictionary.",
"name": "__init__",
"signature": "def __init__(self, db_dict, dbtype, verbose)"
},
{
"docstring": "Write a new record to the programs table of the database at the end of the database. Exceptions: Exception TODO clarify valid exceptions.",
... | 4 | stack_v2_sparse_classes_30k_train_007795 | Implement the Python class `MySQLCompaniesTable` described below.
Class description:
Class representing the connection with a mysql database
Method signatures and docstrings:
- def __init__(self, db_dict, dbtype, verbose): Read the input file into a dictionary.
- def insert(self, company_name): Write a new record to ... | Implement the Python class `MySQLCompaniesTable` described below.
Class description:
Class representing the connection with a mysql database
Method signatures and docstrings:
- def __init__(self, db_dict, dbtype, verbose): Read the input file into a dictionary.
- def insert(self, company_name): Write a new record to ... | 9c60b3489f02592bd9099b8719ca23ae43a9eaa5 | <|skeleton|>
class MySQLCompaniesTable:
"""Class representing the connection with a mysql database"""
def __init__(self, db_dict, dbtype, verbose):
"""Read the input file into a dictionary."""
<|body_0|>
def insert(self, company_name):
"""Write a new record to the programs table of... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MySQLCompaniesTable:
"""Class representing the connection with a mysql database"""
def __init__(self, db_dict, dbtype, verbose):
"""Read the input file into a dictionary."""
super(MySQLCompaniesTable, self).__init__(db_dict, dbtype, verbose)
self.connectdb(db_dict, verbose)
... | the_stack_v2_python_sparse | smipyping/_companiestable.py | KSchopmeyer/smipyping | train | 0 |
e7c145dec3201b54e8f76bfbe8dc8c2d1f8c36a7 | [
"if cls._is_tuple_or_list(model.exclude_compartments) and all((compartment in analysis_model.COMPARTMENTS for compartment in model.exclude_compartments)):\n return True\nreturn model.FIELD_TYPES.exclude_compartments",
"if cls._is_tuple_or_list(model.exclude_measures) and all((measure in analysis_model.MEASURES... | <|body_start_0|>
if cls._is_tuple_or_list(model.exclude_compartments) and all((compartment in analysis_model.COMPARTMENTS for compartment in model.exclude_compartments)):
return True
return model.FIELD_TYPES.exclude_compartments
<|end_body_0|>
<|body_start_1|>
if cls._is_tuple_or_li... | XMLModelFactory | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class XMLModelFactory:
def _validate_exclude_compartments(cls, model):
""":type model: scanomatic.models.analysis_model.XMLModel"""
<|body_0|>
def _validate_exclude_measures(cls, model):
""":type model: scanomatic.models.analysis_model.XMLModel"""
<|body_1|>
d... | stack_v2_sparse_classes_36k_train_029829 | 12,241 | no_license | [
{
"docstring": ":type model: scanomatic.models.analysis_model.XMLModel",
"name": "_validate_exclude_compartments",
"signature": "def _validate_exclude_compartments(cls, model)"
},
{
"docstring": ":type model: scanomatic.models.analysis_model.XMLModel",
"name": "_validate_exclude_measures",
... | 5 | null | Implement the Python class `XMLModelFactory` described below.
Class description:
Implement the XMLModelFactory class.
Method signatures and docstrings:
- def _validate_exclude_compartments(cls, model): :type model: scanomatic.models.analysis_model.XMLModel
- def _validate_exclude_measures(cls, model): :type model: sc... | Implement the Python class `XMLModelFactory` described below.
Class description:
Implement the XMLModelFactory class.
Method signatures and docstrings:
- def _validate_exclude_compartments(cls, model): :type model: scanomatic.models.analysis_model.XMLModel
- def _validate_exclude_measures(cls, model): :type model: sc... | db5dd2e8501d9db8fb0fd8fbf5c9ddd652ae8fdf | <|skeleton|>
class XMLModelFactory:
def _validate_exclude_compartments(cls, model):
""":type model: scanomatic.models.analysis_model.XMLModel"""
<|body_0|>
def _validate_exclude_measures(cls, model):
""":type model: scanomatic.models.analysis_model.XMLModel"""
<|body_1|>
d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class XMLModelFactory:
def _validate_exclude_compartments(cls, model):
""":type model: scanomatic.models.analysis_model.XMLModel"""
if cls._is_tuple_or_list(model.exclude_compartments) and all((compartment in analysis_model.COMPARTMENTS for compartment in model.exclude_compartments)):
re... | the_stack_v2_python_sparse | scanomatic/models/factories/analysis_factories.py | StenbergSimon/scanomatic | train | 0 | |
91b6ee9a49216fe43b30c0d9fd23df2cb65dd2b1 | [
"if v2_data is not None:\n assert_equal(consensusBranchId, NU5_BRANCH_ID)\n orchard_root = v2_data[0]\n orchard_tx_count = v2_data[1]\nelse:\n orchard_root = None\n orchard_tx_count = None\nnode = Z()\nnode.left_child = None\nnode.right_child = None\nnode.hashSubtreeCommitment = ser_uint256(block.reh... | <|body_start_0|>
if v2_data is not None:
assert_equal(consensusBranchId, NU5_BRANCH_ID)
orchard_root = v2_data[0]
orchard_tx_count = v2_data[1]
else:
orchard_root = None
orchard_tx_count = None
node = Z()
node.left_child = None
... | ZcashMMRNode | [
"MIT",
"AGPL-3.0-only",
"LicenseRef-scancode-unknown-license-reference",
"LicenseRef-scancode-warranty-disclaimer"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ZcashMMRNode:
def from_block(Z, block: CBlockHeader, height, sapling_root, sapling_tx_count, consensusBranchId, v2_data=None) -> 'ZcashMMRNode':
"""Create a leaf node from a block"""
<|body_0|>
def serialize(self) -> bytes:
"""serializes a node"""
<|body_1|>
... | stack_v2_sparse_classes_36k_train_029830 | 7,791 | permissive | [
{
"docstring": "Create a leaf node from a block",
"name": "from_block",
"signature": "def from_block(Z, block: CBlockHeader, height, sapling_root, sapling_tx_count, consensusBranchId, v2_data=None) -> 'ZcashMMRNode'"
},
{
"docstring": "serializes a node",
"name": "serialize",
"signature"... | 2 | stack_v2_sparse_classes_30k_train_005029 | Implement the Python class `ZcashMMRNode` described below.
Class description:
Implement the ZcashMMRNode class.
Method signatures and docstrings:
- def from_block(Z, block: CBlockHeader, height, sapling_root, sapling_tx_count, consensusBranchId, v2_data=None) -> 'ZcashMMRNode': Create a leaf node from a block
- def s... | Implement the Python class `ZcashMMRNode` described below.
Class description:
Implement the ZcashMMRNode class.
Method signatures and docstrings:
- def from_block(Z, block: CBlockHeader, height, sapling_root, sapling_tx_count, consensusBranchId, v2_data=None) -> 'ZcashMMRNode': Create a leaf node from a block
- def s... | e3c9773eead914811aaa12fc0c4abedd65c38647 | <|skeleton|>
class ZcashMMRNode:
def from_block(Z, block: CBlockHeader, height, sapling_root, sapling_tx_count, consensusBranchId, v2_data=None) -> 'ZcashMMRNode':
"""Create a leaf node from a block"""
<|body_0|>
def serialize(self) -> bytes:
"""serializes a node"""
<|body_1|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ZcashMMRNode:
def from_block(Z, block: CBlockHeader, height, sapling_root, sapling_tx_count, consensusBranchId, v2_data=None) -> 'ZcashMMRNode':
"""Create a leaf node from a block"""
if v2_data is not None:
assert_equal(consensusBranchId, NU5_BRANCH_ID)
orchard_root = v... | the_stack_v2_python_sparse | qa/rpc-tests/test_framework/flyclient.py | KotoDevelopers/koto | train | 29 | |
9edfe7b6b6975679d226626fc0f2427c66629949 | [
"if not nums:\n return 0\nelif len(nums) <= 2:\n return max(nums)\ngems = [[] for _ in range(len(nums))]\nfor index, num in enumerate(nums):\n if index < 1:\n gems[index] = [1, num]\n elif index < 2:\n if gems[index - 1][1] > num:\n gems[index] = gems[index - 1]\n else:\n... | <|body_start_0|>
if not nums:
return 0
elif len(nums) <= 2:
return max(nums)
gems = [[] for _ in range(len(nums))]
for index, num in enumerate(nums):
if index < 1:
gems[index] = [1, num]
elif index < 2:
if ge... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def _rob(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def rob(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if not nums:
return 0
elif len(nums) <= ... | stack_v2_sparse_classes_36k_train_029831 | 3,627 | permissive | [
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "_rob",
"signature": "def _rob(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: int",
"name": "rob",
"signature": "def rob(self, nums)"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def _rob(self, nums): :type nums: List[int] :rtype: int
- def rob(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 _rob(self, nums): :type nums: List[int] :rtype: int
- def rob(self, nums): :type nums: List[int] :rtype: int
<|skeleton|>
class Solution:
def _rob(self, nums):
... | 0dd67edca4e0b0323cb5a7239f02ea46383cd15a | <|skeleton|>
class Solution:
def _rob(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_0|>
def rob(self, nums):
""":type nums: List[int] :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def _rob(self, nums):
""":type nums: List[int] :rtype: int"""
if not nums:
return 0
elif len(nums) <= 2:
return max(nums)
gems = [[] for _ in range(len(nums))]
for index, num in enumerate(nums):
if index < 1:
... | the_stack_v2_python_sparse | 213.house-robber-ii.py | windard/leeeeee | train | 0 | |
eb23d06501f372fbb7791eb29f62afb13092a295 | [
"with open(sql_filename, 'r') as sql_file:\n sql = sql_file.read()\nwith connection.cursor() as cursor:\n cursor.execute(sql, params)\n desc = cursor.description\n data = [dict(zip([col[0] for col in desc], row)) for row in cursor.fetchall()]\nreturn data",
"unique_dict = {}\nunique_fields = self.get_... | <|body_start_0|>
with open(sql_filename, 'r') as sql_file:
sql = sql_file.read()
with connection.cursor() as cursor:
cursor.execute(sql, params)
desc = cursor.description
data = [dict(zip([col[0] for col in desc], row)) for row in cursor.fetchall()]
... | ApiHelper | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ApiHelper:
def run_query(self, sql_filename=None, params=None):
"""Run query from a given sql file using the given parameters"""
<|body_0|>
def get_unique_dict(self, obj, data):
"""Get a sict of <field_name>: <field_value> Fields of the given object with a unique con... | stack_v2_sparse_classes_36k_train_029832 | 1,392 | no_license | [
{
"docstring": "Run query from a given sql file using the given parameters",
"name": "run_query",
"signature": "def run_query(self, sql_filename=None, params=None)"
},
{
"docstring": "Get a sict of <field_name>: <field_value> Fields of the given object with a unique constraint and supplied data"... | 2 | stack_v2_sparse_classes_30k_val_000146 | Implement the Python class `ApiHelper` described below.
Class description:
Implement the ApiHelper class.
Method signatures and docstrings:
- def run_query(self, sql_filename=None, params=None): Run query from a given sql file using the given parameters
- def get_unique_dict(self, obj, data): Get a sict of <field_nam... | Implement the Python class `ApiHelper` described below.
Class description:
Implement the ApiHelper class.
Method signatures and docstrings:
- def run_query(self, sql_filename=None, params=None): Run query from a given sql file using the given parameters
- def get_unique_dict(self, obj, data): Get a sict of <field_nam... | 351532fcfad8cb93658f333be95c70b53eab9171 | <|skeleton|>
class ApiHelper:
def run_query(self, sql_filename=None, params=None):
"""Run query from a given sql file using the given parameters"""
<|body_0|>
def get_unique_dict(self, obj, data):
"""Get a sict of <field_name>: <field_value> Fields of the given object with a unique con... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ApiHelper:
def run_query(self, sql_filename=None, params=None):
"""Run query from a given sql file using the given parameters"""
with open(sql_filename, 'r') as sql_file:
sql = sql_file.read()
with connection.cursor() as cursor:
cursor.execute(sql, params)
... | the_stack_v2_python_sparse | cbmsapi/apis/apihelper.py | dmostroff/cbmsapi | train | 0 | |
4288fa7532d098a3554ed69b536c8d502f0b6f9b | [
"flags.AddNodePoolNameArg(parser, 'The name of the node pool to delete.')\nparser.add_argument('--timeout', type=int, default=1800, hidden=True, help='THIS ARGUMENT NEEDS HELP TEXT.')\nflags.AddAsyncFlag(parser)\nflags.AddNodePoolClusterFlag(parser, 'The cluster from which to delete the node pool.')",
"adapter = ... | <|body_start_0|>
flags.AddNodePoolNameArg(parser, 'The name of the node pool to delete.')
parser.add_argument('--timeout', type=int, default=1800, hidden=True, help='THIS ARGUMENT NEEDS HELP TEXT.')
flags.AddAsyncFlag(parser)
flags.AddNodePoolClusterFlag(parser, 'The cluster from which t... | Delete an existing node pool in a running cluster. | Delete | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Delete:
"""Delete an existing node pool in a running cluster."""
def Args(parser):
"""Register flags for this command. Args: parser: An argparse.ArgumentParser-like object. It is mocked out in order to capture some information, but behaves like an ArgumentParser."""
<|body_0|... | stack_v2_sparse_classes_36k_train_029833 | 3,844 | permissive | [
{
"docstring": "Register flags for this command. Args: parser: An argparse.ArgumentParser-like object. It is mocked out in order to capture some information, but behaves like an ArgumentParser.",
"name": "Args",
"signature": "def Args(parser)"
},
{
"docstring": "This is what gets called when the... | 2 | null | Implement the Python class `Delete` described below.
Class description:
Delete an existing node pool in a running cluster.
Method signatures and docstrings:
- def Args(parser): Register flags for this command. Args: parser: An argparse.ArgumentParser-like object. It is mocked out in order to capture some information,... | Implement the Python class `Delete` described below.
Class description:
Delete an existing node pool in a running cluster.
Method signatures and docstrings:
- def Args(parser): Register flags for this command. Args: parser: An argparse.ArgumentParser-like object. It is mocked out in order to capture some information,... | 85bb264e273568b5a0408f733b403c56373e2508 | <|skeleton|>
class Delete:
"""Delete an existing node pool in a running cluster."""
def Args(parser):
"""Register flags for this command. Args: parser: An argparse.ArgumentParser-like object. It is mocked out in order to capture some information, but behaves like an ArgumentParser."""
<|body_0|... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Delete:
"""Delete an existing node pool in a running cluster."""
def Args(parser):
"""Register flags for this command. Args: parser: An argparse.ArgumentParser-like object. It is mocked out in order to capture some information, but behaves like an ArgumentParser."""
flags.AddNodePoolNameA... | the_stack_v2_python_sparse | google-cloud-sdk/lib/surface/container/node_pools/delete.py | bopopescu/socialliteapp | train | 0 |
30e99d032647863d6611bb9a2c3834a91ea5a965 | [
"self.x = x\nself.y = y\nself.r = r\nself.dx = dx\nself.dy = dy\nself.color = color",
"glPushMatrix()\nglColor4f(*self.color)\nglTranslatef(self.x, self.y, 0)\nq = gluNewQuadric()\nslices = min(360, 6 * self.r)\ngluDisk(q, 0, self.r, slices, 1)\nglPopMatrix()\nreturn",
"if self.y - self.r < 0:\n game_info.ov... | <|body_start_0|>
self.x = x
self.y = y
self.r = r
self.dx = dx
self.dy = dy
self.color = color
<|end_body_0|>
<|body_start_1|>
glPushMatrix()
glColor4f(*self.color)
glTranslatef(self.x, self.y, 0)
q = gluNewQuadric()
slices = min(3... | Ball object that knows how to draw itself | Ball | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Ball:
"""Ball object that knows how to draw itself"""
def __init__(self, x, y, r, dx=120, dy=120, color=(1.0, 1.0, 1.0, 1.0)):
"""circle of radius r centered at (x, y) and opaque white by default"""
<|body_0|>
def draw(self):
"""draws a circle"""
<|body_1... | stack_v2_sparse_classes_36k_train_029834 | 2,406 | no_license | [
{
"docstring": "circle of radius r centered at (x, y) and opaque white by default",
"name": "__init__",
"signature": "def __init__(self, x, y, r, dx=120, dy=120, color=(1.0, 1.0, 1.0, 1.0))"
},
{
"docstring": "draws a circle",
"name": "draw",
"signature": "def draw(self)"
},
{
"d... | 3 | null | Implement the Python class `Ball` described below.
Class description:
Ball object that knows how to draw itself
Method signatures and docstrings:
- def __init__(self, x, y, r, dx=120, dy=120, color=(1.0, 1.0, 1.0, 1.0)): circle of radius r centered at (x, y) and opaque white by default
- def draw(self): draws a circl... | Implement the Python class `Ball` described below.
Class description:
Ball object that knows how to draw itself
Method signatures and docstrings:
- def __init__(self, x, y, r, dx=120, dy=120, color=(1.0, 1.0, 1.0, 1.0)): circle of radius r centered at (x, y) and opaque white by default
- def draw(self): draws a circl... | dd721e096f8445aee48e69c3a3ebf6501aecc95b | <|skeleton|>
class Ball:
"""Ball object that knows how to draw itself"""
def __init__(self, x, y, r, dx=120, dy=120, color=(1.0, 1.0, 1.0, 1.0)):
"""circle of radius r centered at (x, y) and opaque white by default"""
<|body_0|>
def draw(self):
"""draws a circle"""
<|body_1... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Ball:
"""Ball object that knows how to draw itself"""
def __init__(self, x, y, r, dx=120, dy=120, color=(1.0, 1.0, 1.0, 1.0)):
"""circle of radius r centered at (x, y) and opaque white by default"""
self.x = x
self.y = y
self.r = r
self.dx = dx
self.dy = dy... | the_stack_v2_python_sparse | game_tut/breakout_py/break6.py | aroberge/py-fun | train | 0 |
beb3aa7398d745119f4e74b9b240dfcc23efad51 | [
"self.name = 'connectome_stage'\nself.bids_dir = bids_dir\nself.output_dir = output_dir\nself.config = ConnectomeConfig()\nself.inputs = ['roi_volumes_registered', 'func_file', 'FD', 'DVARS', 'parcellation_scheme', 'atlas_info', 'roi_graphMLs']\nself.outputs = ['connectivity_matrices', 'avg_timeseries']",
"cmtk_c... | <|body_start_0|>
self.name = 'connectome_stage'
self.bids_dir = bids_dir
self.output_dir = output_dir
self.config = ConnectomeConfig()
self.inputs = ['roi_volumes_registered', 'func_file', 'FD', 'DVARS', 'parcellation_scheme', 'atlas_info', 'roi_graphMLs']
self.outputs = ... | Class that represents the connectome building stage of a :class:`~cmp.pipelines.functional.fMRI.fMRIPipeline`. Methods ------- create_workflow() Create the workflow of the fMRI `ConnectomeStage` See Also -------- cmp.pipelines.functional.fMRI.fMRIPipeline cmp.stages.connectome.fmri_connectome.ConnectomeConfig | ConnectomeStage | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ConnectomeStage:
"""Class that represents the connectome building stage of a :class:`~cmp.pipelines.functional.fMRI.fMRIPipeline`. Methods ------- create_workflow() Create the workflow of the fMRI `ConnectomeStage` See Also -------- cmp.pipelines.functional.fMRI.fMRIPipeline cmp.stages.connectome... | stack_v2_sparse_classes_36k_train_029835 | 7,737 | permissive | [
{
"docstring": "Constructor of a :class:`~cmp.stages.connectome.fmri_connectome.Connectome` instance.",
"name": "__init__",
"signature": "def __init__(self, bids_dir, output_dir)"
},
{
"docstring": "Create the stage worflow. Parameters ---------- flow : nipype.pipeline.engine.Workflow The nipype... | 3 | stack_v2_sparse_classes_30k_test_000309 | Implement the Python class `ConnectomeStage` described below.
Class description:
Class that represents the connectome building stage of a :class:`~cmp.pipelines.functional.fMRI.fMRIPipeline`. Methods ------- create_workflow() Create the workflow of the fMRI `ConnectomeStage` See Also -------- cmp.pipelines.functional.... | Implement the Python class `ConnectomeStage` described below.
Class description:
Class that represents the connectome building stage of a :class:`~cmp.pipelines.functional.fMRI.fMRIPipeline`. Methods ------- create_workflow() Create the workflow of the fMRI `ConnectomeStage` See Also -------- cmp.pipelines.functional.... | 35cb2ee7be2e73896061359a6cd0a10503fadd42 | <|skeleton|>
class ConnectomeStage:
"""Class that represents the connectome building stage of a :class:`~cmp.pipelines.functional.fMRI.fMRIPipeline`. Methods ------- create_workflow() Create the workflow of the fMRI `ConnectomeStage` See Also -------- cmp.pipelines.functional.fMRI.fMRIPipeline cmp.stages.connectome... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ConnectomeStage:
"""Class that represents the connectome building stage of a :class:`~cmp.pipelines.functional.fMRI.fMRIPipeline`. Methods ------- create_workflow() Create the workflow of the fMRI `ConnectomeStage` See Also -------- cmp.pipelines.functional.fMRI.fMRIPipeline cmp.stages.connectome.fmri_connect... | the_stack_v2_python_sparse | cmp/stages/connectome/fmri_connectome.py | jwirsich/connectomemapper3 | train | 0 |
6d5deed41066b7f42ebcd288c69b8c86b4a7e95e | [
"self.allowed_url_patterns = allowed_url_patterns\nself.blocked_url_patterns = blocked_url_patterns\nself.blocked_url_categories = blocked_url_categories\nself.url_category_list_size = url_category_list_size",
"if dictionary is None:\n return None\nallowed_url_patterns = dictionary.get('allowedUrlPatterns')\nb... | <|body_start_0|>
self.allowed_url_patterns = allowed_url_patterns
self.blocked_url_patterns = blocked_url_patterns
self.blocked_url_categories = blocked_url_categories
self.url_category_list_size = url_category_list_size
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
... | Implementation of the 'updateNetworkContentFiltering' model. TODO: type model description here. Attributes: allowed_url_patterns (list of string): A whitelist of URL patterns to allow blocked_url_patterns (list of string): A blacklist of URL patterns to block blocked_url_categories (list of string): A list of URL categ... | UpdateNetworkContentFilteringModel | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UpdateNetworkContentFilteringModel:
"""Implementation of the 'updateNetworkContentFiltering' model. TODO: type model description here. Attributes: allowed_url_patterns (list of string): A whitelist of URL patterns to allow blocked_url_patterns (list of string): A blacklist of URL patterns to bloc... | stack_v2_sparse_classes_36k_train_029836 | 2,755 | permissive | [
{
"docstring": "Constructor for the UpdateNetworkContentFilteringModel class",
"name": "__init__",
"signature": "def __init__(self, allowed_url_patterns=None, blocked_url_patterns=None, blocked_url_categories=None, url_category_list_size=None)"
},
{
"docstring": "Creates an instance of this mode... | 2 | null | Implement the Python class `UpdateNetworkContentFilteringModel` described below.
Class description:
Implementation of the 'updateNetworkContentFiltering' model. TODO: type model description here. Attributes: allowed_url_patterns (list of string): A whitelist of URL patterns to allow blocked_url_patterns (list of strin... | Implement the Python class `UpdateNetworkContentFilteringModel` described below.
Class description:
Implementation of the 'updateNetworkContentFiltering' model. TODO: type model description here. Attributes: allowed_url_patterns (list of string): A whitelist of URL patterns to allow blocked_url_patterns (list of strin... | 9894089eb013318243ae48869cc5130eb37f80c0 | <|skeleton|>
class UpdateNetworkContentFilteringModel:
"""Implementation of the 'updateNetworkContentFiltering' model. TODO: type model description here. Attributes: allowed_url_patterns (list of string): A whitelist of URL patterns to allow blocked_url_patterns (list of string): A blacklist of URL patterns to bloc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UpdateNetworkContentFilteringModel:
"""Implementation of the 'updateNetworkContentFiltering' model. TODO: type model description here. Attributes: allowed_url_patterns (list of string): A whitelist of URL patterns to allow blocked_url_patterns (list of string): A blacklist of URL patterns to block blocked_url... | the_stack_v2_python_sparse | meraki_sdk/models/update_network_content_filtering_model.py | RaulCatalano/meraki-python-sdk | train | 1 |
ae5cbd882c78ebb5413b5c645474fa006abb3c63 | [
"model = MEGNet(n_node_features=n_node_features, n_edge_features=n_edge_features, n_global_features=n_global_features, n_blocks=n_blocks, is_undirected=is_undirected, residual_connection=residual_connection, mode=mode, n_classes=n_classes, n_tasks=n_tasks)\nif mode == 'regression':\n loss: Loss = L2Loss()\n o... | <|body_start_0|>
model = MEGNet(n_node_features=n_node_features, n_edge_features=n_edge_features, n_global_features=n_global_features, n_blocks=n_blocks, is_undirected=is_undirected, residual_connection=residual_connection, mode=mode, n_classes=n_classes, n_tasks=n_tasks)
if mode == 'regression':
... | MatErials Graph Network for Molecules and Crystals MatErials Graph Network [1]_ are Graph Networks [2]_ which are used for property prediction in molecules and crystals. The model implements multiple layers of Graph Network as MEGNetBlocks and then combines the node properties and edge properties of all nodes and edges... | MEGNetModel | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MEGNetModel:
"""MatErials Graph Network for Molecules and Crystals MatErials Graph Network [1]_ are Graph Networks [2]_ which are used for property prediction in molecules and crystals. The model implements multiple layers of Graph Network as MEGNetBlocks and then combines the node properties and... | stack_v2_sparse_classes_36k_train_029837 | 11,170 | permissive | [
{
"docstring": "Parameters ---------- n_node_features: int Number of features in a node n_edge_features: int Number of features in a edge n_global_features: int Number of global features n_blocks: int Number of GraphNetworks block to use in update is_undirected: bool, optional (default True) True when the model... | 2 | stack_v2_sparse_classes_30k_train_005746 | Implement the Python class `MEGNetModel` described below.
Class description:
MatErials Graph Network for Molecules and Crystals MatErials Graph Network [1]_ are Graph Networks [2]_ which are used for property prediction in molecules and crystals. The model implements multiple layers of Graph Network as MEGNetBlocks an... | Implement the Python class `MEGNetModel` described below.
Class description:
MatErials Graph Network for Molecules and Crystals MatErials Graph Network [1]_ are Graph Networks [2]_ which are used for property prediction in molecules and crystals. The model implements multiple layers of Graph Network as MEGNetBlocks an... | ee6e67ebcf7bf04259cf13aff6388e2b791fea3d | <|skeleton|>
class MEGNetModel:
"""MatErials Graph Network for Molecules and Crystals MatErials Graph Network [1]_ are Graph Networks [2]_ which are used for property prediction in molecules and crystals. The model implements multiple layers of Graph Network as MEGNetBlocks and then combines the node properties and... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MEGNetModel:
"""MatErials Graph Network for Molecules and Crystals MatErials Graph Network [1]_ are Graph Networks [2]_ which are used for property prediction in molecules and crystals. The model implements multiple layers of Graph Network as MEGNetBlocks and then combines the node properties and edge propert... | the_stack_v2_python_sparse | deepchem/models/torch_models/megnet.py | deepchem/deepchem | train | 4,876 |
ffb8724a648d8cc3de42663942e08dc2404c46f3 | [
"self.flag = flag\nif city == '北京':\n self.city = 'beijing'\nelif city == '上海':\n self.city = 'shanghai'\nelse:\n self.city = 'guangzhou'\nself.real_time = 'https://api.seniverse.com/v3/weather/now.json?key=******=' + self.city + '&language=zh-Hans&unit=c'\nself.nearly_3_days = 'https://api.seniverse.com/v... | <|body_start_0|>
self.flag = flag
if city == '北京':
self.city = 'beijing'
elif city == '上海':
self.city = 'shanghai'
else:
self.city = 'guangzhou'
self.real_time = 'https://api.seniverse.com/v3/weather/now.json?key=******=' + self.city + '&langua... | 使用API获取天气 | GetWeatherInfo | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetWeatherInfo:
"""使用API获取天气"""
def __init__(self, flag, city):
"""一些初始设置"""
<|body_0|>
def getweather(self):
"""根据API的返回值，以及究竟是实时天气还是近三天天气，返回给调用该函数变量"""
<|body_1|>
def internet(self, url):
"""requests库访问API，获取天气信息"""
<|body_2|>
<|en... | stack_v2_sparse_classes_36k_train_029838 | 2,226 | no_license | [
{
"docstring": "一些初始设置",
"name": "__init__",
"signature": "def __init__(self, flag, city)"
},
{
"docstring": "根据API的返回值，以及究竟是实时天气还是近三天天气，返回给调用该函数变量",
"name": "getweather",
"signature": "def getweather(self)"
},
{
"docstring": "requests库访问API，获取天气信息",
"name": "internet",
"... | 3 | null | Implement the Python class `GetWeatherInfo` described below.
Class description:
使用API获取天气
Method signatures and docstrings:
- def __init__(self, flag, city): 一些初始设置
- def getweather(self): 根据API的返回值，以及究竟是实时天气还是近三天天气，返回给调用该函数变量
- def internet(self, url): requests库访问API，获取天气信息 | Implement the Python class `GetWeatherInfo` described below.
Class description:
使用API获取天气
Method signatures and docstrings:
- def __init__(self, flag, city): 一些初始设置
- def getweather(self): 根据API的返回值，以及究竟是实时天气还是近三天天气，返回给调用该函数变量
- def internet(self, url): requests库访问API，获取天气信息
<|skeleton|>
class GetWeatherInfo:
""... | 4d4c44365d5d0bf3d9fd94922a13d0b50f17a95c | <|skeleton|>
class GetWeatherInfo:
"""使用API获取天气"""
def __init__(self, flag, city):
"""一些初始设置"""
<|body_0|>
def getweather(self):
"""根据API的返回值，以及究竟是实时天气还是近三天天气，返回给调用该函数变量"""
<|body_1|>
def internet(self, url):
"""requests库访问API，获取天气信息"""
<|body_2|>
<|en... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GetWeatherInfo:
"""使用API获取天气"""
def __init__(self, flag, city):
"""一些初始设置"""
self.flag = flag
if city == '北京':
self.city = 'beijing'
elif city == '上海':
self.city = 'shanghai'
else:
self.city = 'guangzhou'
self.real_time =... | the_stack_v2_python_sparse | PyQt5All/PyQt550/getweather.py | redmorningcn/PyQT5Example | train | 1 |
871d8ce3c2c6b715da49ecae34b674ca09abe802 | [
"if m == 1 or n == 1:\n return 1\nreturn self.uniquePaths(m - 1, n) + self.uniquePaths(m, n - 1)",
"ans = [[1 for _ in range(n)] for _ in range(m)]\nfor row in range(1, m):\n for col in range(1, n):\n ans[row][col] = ans[row - 1][col] + ans[row][col - 1]\nreturn ans[-1][-1]"
] | <|body_start_0|>
if m == 1 or n == 1:
return 1
return self.uniquePaths(m - 1, n) + self.uniquePaths(m, n - 1)
<|end_body_0|>
<|body_start_1|>
ans = [[1 for _ in range(n)] for _ in range(m)]
for row in range(1, m):
for col in range(1, n):
ans[row][... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def uniquePaths(self, m: int, n: int) -> int:
"""递归的思想，不过注意使用缓存，不然会大量重复计算，超时 :param m: :param n: :return:"""
<|body_0|>
def uniquePaths_2(self, m: int, n: int) -> int:
"""动态规划思想 :param m: :param n: :return:"""
<|body_1|>
<|end_skeleton|>
<|body_st... | stack_v2_sparse_classes_36k_train_029839 | 919 | no_license | [
{
"docstring": "递归的思想，不过注意使用缓存，不然会大量重复计算，超时 :param m: :param n: :return:",
"name": "uniquePaths",
"signature": "def uniquePaths(self, m: int, n: int) -> int"
},
{
"docstring": "动态规划思想 :param m: :param n: :return:",
"name": "uniquePaths_2",
"signature": "def uniquePaths_2(self, m: int, n:... | 2 | stack_v2_sparse_classes_30k_train_009346 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniquePaths(self, m: int, n: int) -> int: 递归的思想，不过注意使用缓存，不然会大量重复计算，超时 :param m: :param n: :return:
- def uniquePaths_2(self, m: int, n: int) -> int: 动态规划思想 :param m: :param n... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def uniquePaths(self, m: int, n: int) -> int: 递归的思想，不过注意使用缓存，不然会大量重复计算，超时 :param m: :param n: :return:
- def uniquePaths_2(self, m: int, n: int) -> int: 动态规划思想 :param m: :param n... | f2c162654a83c51495ebd161f42a1d0b69caf72d | <|skeleton|>
class Solution:
def uniquePaths(self, m: int, n: int) -> int:
"""递归的思想，不过注意使用缓存，不然会大量重复计算，超时 :param m: :param n: :return:"""
<|body_0|>
def uniquePaths_2(self, m: int, n: int) -> int:
"""动态规划思想 :param m: :param n: :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def uniquePaths(self, m: int, n: int) -> int:
"""递归的思想，不过注意使用缓存，不然会大量重复计算，超时 :param m: :param n: :return:"""
if m == 1 or n == 1:
return 1
return self.uniquePaths(m - 1, n) + self.uniquePaths(m, n - 1)
def uniquePaths_2(self, m: int, n: int) -> int:
"... | the_stack_v2_python_sparse | 62 uniquePaths.py | ABenxj/leetcode | train | 1 | |
4967435a522581d9c1b420c57066b42bcd8a4ab1 | [
"self._bucket_capacity = 997\nself._capacity = 10 ** 6\nself._no_of_buckets = math.ceil(self._capacity / self._bucket_capacity)\nself._buckets = [Node(None) for _ in range(self._no_of_buckets)]",
"bucket = self._buckets[key % self._bucket_capacity]\nnode = bucket\nprev = None\nwhile node:\n if node.val and nod... | <|body_start_0|>
self._bucket_capacity = 997
self._capacity = 10 ** 6
self._no_of_buckets = math.ceil(self._capacity / self._bucket_capacity)
self._buckets = [Node(None) for _ in range(self._no_of_buckets)]
<|end_body_0|>
<|body_start_1|>
bucket = self._buckets[key % self._bucke... | MyHashMap | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyHashMap:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def put(self, key: int, value: int) -> None:
"""value will always be non-negative."""
<|body_1|>
def get(self, key: int) -> int:
"""Returns the value to which th... | stack_v2_sparse_classes_36k_train_029840 | 1,953 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "value will always be non-negative.",
"name": "put",
"signature": "def put(self, key: int, value: int) -> None"
},
{
"docstring": "Returns the value to w... | 4 | stack_v2_sparse_classes_30k_train_017541 | Implement the Python class `MyHashMap` described below.
Class description:
Implement the MyHashMap class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def put(self, key: int, value: int) -> None: value will always be non-negative.
- def get(self, key: int) -> int: Ret... | Implement the Python class `MyHashMap` described below.
Class description:
Implement the MyHashMap class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def put(self, key: int, value: int) -> None: value will always be non-negative.
- def get(self, key: int) -> int: Ret... | b7d3b9e2f45ba68a121951c0ca138bf94f035b26 | <|skeleton|>
class MyHashMap:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def put(self, key: int, value: int) -> None:
"""value will always be non-negative."""
<|body_1|>
def get(self, key: int) -> int:
"""Returns the value to which th... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyHashMap:
def __init__(self):
"""Initialize your data structure here."""
self._bucket_capacity = 997
self._capacity = 10 ** 6
self._no_of_buckets = math.ceil(self._capacity / self._bucket_capacity)
self._buckets = [Node(None) for _ in range(self._no_of_buckets)]
d... | the_stack_v2_python_sparse | hash/design_hashmap.py | uma-c/CodingProblemSolving | train | 0 | |
b48b3e974502844fdaa550616e7897dff20d0d27 | [
"M = len(nums1)\nN = len(nums2)\nif (N + M) % 2 == 0:\n K1 = (M + N) / 2\n K2 = (M + N) / 2 + 1\n val1 = self.find_k_Largest(nums1, nums2, K1)\n val2 = self.find_k_Largest(nums1, nums2, K2)\n return (val1 + val2) / 2.0\nelse:\n K = (M + N - 1) / 2 + 1\n return self.find_k_Largest(nums1, nums2, ... | <|body_start_0|>
M = len(nums1)
N = len(nums2)
if (N + M) % 2 == 0:
K1 = (M + N) / 2
K2 = (M + N) / 2 + 1
val1 = self.find_k_Largest(nums1, nums2, K1)
val2 = self.find_k_Largest(nums1, nums2, K2)
return (val1 + val2) / 2.0
else:... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def findMedianSortedArrays(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: float"""
<|body_0|>
def find_k_Largest(self, nums1, nums2, k):
"""if len(nums1) > k: nums1 = list(nums1[:k]) if len(nums2) > k: nums2 = list(nums2[:k])"... | stack_v2_sparse_classes_36k_train_029841 | 1,672 | permissive | [
{
"docstring": ":type nums1: List[int] :type nums2: List[int] :rtype: float",
"name": "findMedianSortedArrays",
"signature": "def findMedianSortedArrays(self, nums1, nums2)"
},
{
"docstring": "if len(nums1) > k: nums1 = list(nums1[:k]) if len(nums2) > k: nums2 = list(nums2[:k])",
"name": "fi... | 2 | stack_v2_sparse_classes_30k_test_000430 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMedianSortedArrays(self, nums1, nums2): :type nums1: List[int] :type nums2: List[int] :rtype: float
- def find_k_Largest(self, nums1, nums2, k): if len(nums1) > k: nums1 ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def findMedianSortedArrays(self, nums1, nums2): :type nums1: List[int] :type nums2: List[int] :rtype: float
- def find_k_Largest(self, nums1, nums2, k): if len(nums1) > k: nums1 ... | c8633ea7a36d97e4b5e45f33f8c339660e9c2d87 | <|skeleton|>
class Solution:
def findMedianSortedArrays(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: float"""
<|body_0|>
def find_k_Largest(self, nums1, nums2, k):
"""if len(nums1) > k: nums1 = list(nums1[:k]) if len(nums2) > k: nums2 = list(nums2[:k])"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def findMedianSortedArrays(self, nums1, nums2):
""":type nums1: List[int] :type nums2: List[int] :rtype: float"""
M = len(nums1)
N = len(nums2)
if (N + M) % 2 == 0:
K1 = (M + N) / 2
K2 = (M + N) / 2 + 1
val1 = self.find_k_Largest(nu... | the_stack_v2_python_sparse | Algorithms/#4 Median of Two Sorted Arrays/PythonCode.py | yingcuhk/LeetCode | train | 3 | |
c4fc4e689e78eeb136fe092005f8c4d275915ec8 | [
"left = node.left != None\nright = node.right != None\nif not left and (not right):\n if cur_sum == node.val:\n foundSoFar.append(pathSoFar)\n return\nif left:\n self.helper(node.left, cur_sum - node.val, pathSoFar + [node.left.val], foundSoFar)\nif right:\n self.helper(node.right, cur_sum - node... | <|body_start_0|>
left = node.left != None
right = node.right != None
if not left and (not right):
if cur_sum == node.val:
foundSoFar.append(pathSoFar)
return
if left:
self.helper(node.left, cur_sum - node.val, pathSoFar + [node.left.val... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def helper(self, node, cur_sum, pathSoFar, foundSoFar):
""":type node: TreeNode :type cur_sum: int :type pathSoFar: List[int] :type foundSoFar: List[List[int]] :rtype: None? List[List[int]]?"""
<|body_0|>
def pathSum(self, root, cur_sum):
""":type root: Tre... | stack_v2_sparse_classes_36k_train_029842 | 1,181 | no_license | [
{
"docstring": ":type node: TreeNode :type cur_sum: int :type pathSoFar: List[int] :type foundSoFar: List[List[int]] :rtype: None? List[List[int]]?",
"name": "helper",
"signature": "def helper(self, node, cur_sum, pathSoFar, foundSoFar)"
},
{
"docstring": ":type root: TreeNode :type cur_sum: int... | 2 | stack_v2_sparse_classes_30k_train_005268 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def helper(self, node, cur_sum, pathSoFar, foundSoFar): :type node: TreeNode :type cur_sum: int :type pathSoFar: List[int] :type foundSoFar: List[List[int]] :rtype: None? List[Li... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def helper(self, node, cur_sum, pathSoFar, foundSoFar): :type node: TreeNode :type cur_sum: int :type pathSoFar: List[int] :type foundSoFar: List[List[int]] :rtype: None? List[Li... | dcf9768aeb120f3ad9925e407193e1a4b282a0a2 | <|skeleton|>
class Solution:
def helper(self, node, cur_sum, pathSoFar, foundSoFar):
""":type node: TreeNode :type cur_sum: int :type pathSoFar: List[int] :type foundSoFar: List[List[int]] :rtype: None? List[List[int]]?"""
<|body_0|>
def pathSum(self, root, cur_sum):
""":type root: Tre... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def helper(self, node, cur_sum, pathSoFar, foundSoFar):
""":type node: TreeNode :type cur_sum: int :type pathSoFar: List[int] :type foundSoFar: List[List[int]] :rtype: None? List[List[int]]?"""
left = node.left != None
right = node.right != None
if not left and (not r... | the_stack_v2_python_sparse | Path_Sum_II_Optimized.py | O5-2/leetcode | train | 0 | |
a3c111459cf3f0212eb01ce9b102df34c0464bc8 | [
"test_zipped_file = './test/test.zip'\ndesired_dir = os.path.join(CFG_TMPSHAREDDIR, 'apsharvest')\nunzipped_folder = unzip(test_zipped_file, desired_dir)\nself.assertTrue(unzipped_folder.startswith(desired_dir), 'Unzipped folder is located in the wrong place %s!' % unzipped_folder)\nunzipped_folder = unzip(test_zip... | <|body_start_0|>
test_zipped_file = './test/test.zip'
desired_dir = os.path.join(CFG_TMPSHAREDDIR, 'apsharvest')
unzipped_folder = unzip(test_zipped_file, desired_dir)
self.assertTrue(unzipped_folder.startswith(desired_dir), 'Unzipped folder is located in the wrong place %s!' % unzipped_... | FileTest | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileTest:
def test_unzip(self):
"""Test uncompressing function."""
<|body_0|>
def test_md5_check(self):
"""Test md5 checking done by APS Harvester."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
test_zipped_file = './test/test.zip'
desired_... | stack_v2_sparse_classes_36k_train_029843 | 5,627 | no_license | [
{
"docstring": "Test uncompressing function.",
"name": "test_unzip",
"signature": "def test_unzip(self)"
},
{
"docstring": "Test md5 checking done by APS Harvester.",
"name": "test_md5_check",
"signature": "def test_md5_check(self)"
}
] | 2 | null | Implement the Python class `FileTest` described below.
Class description:
Implement the FileTest class.
Method signatures and docstrings:
- def test_unzip(self): Test uncompressing function.
- def test_md5_check(self): Test md5 checking done by APS Harvester. | Implement the Python class `FileTest` described below.
Class description:
Implement the FileTest class.
Method signatures and docstrings:
- def test_unzip(self): Test uncompressing function.
- def test_md5_check(self): Test md5 checking done by APS Harvester.
<|skeleton|>
class FileTest:
def test_unzip(self):
... | 37c905be9a569a6c25ced045eb84545ddb7ac3a5 | <|skeleton|>
class FileTest:
def test_unzip(self):
"""Test uncompressing function."""
<|body_0|>
def test_md5_check(self):
"""Test md5 checking done by APS Harvester."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FileTest:
def test_unzip(self):
"""Test uncompressing function."""
test_zipped_file = './test/test.zip'
desired_dir = os.path.join(CFG_TMPSHAREDDIR, 'apsharvest')
unzipped_folder = unzip(test_zipped_file, desired_dir)
self.assertTrue(unzipped_folder.startswith(desired_d... | the_stack_v2_python_sparse | apsharvest/apsharvest_tests.py | inspirehep/inspire | train | 9 | |
da9012b62dcc44372a39f460f223ed897f219f94 | [
"url = 'os-agents'\nif params:\n url += '?%s' % urllib.urlencode(params)\nresp, body = self.get(url)\nbody = json.loads(body)\nself.validate_response(schema.list_agents, resp, body)\nreturn rest_client.ResponseBody(resp, body)",
"post_body = json.dumps({'agent': kwargs})\nresp, body = self.post('os-agents', po... | <|body_start_0|>
url = 'os-agents'
if params:
url += '?%s' % urllib.urlencode(params)
resp, body = self.get(url)
body = json.loads(body)
self.validate_response(schema.list_agents, resp, body)
return rest_client.ResponseBody(resp, body)
<|end_body_0|>
<|body_s... | Tests Agents API | AgentsClient | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AgentsClient:
"""Tests Agents API"""
def list_agents(self, **params):
"""List all agent builds. For a full list of available parameters, please refer to the official API reference: https://docs.openstack.org/api-ref/compute/#list-agent-builds"""
<|body_0|>
def create_age... | stack_v2_sparse_classes_36k_train_029844 | 3,003 | permissive | [
{
"docstring": "List all agent builds. For a full list of available parameters, please refer to the official API reference: https://docs.openstack.org/api-ref/compute/#list-agent-builds",
"name": "list_agents",
"signature": "def list_agents(self, **params)"
},
{
"docstring": "Create an agent bui... | 4 | stack_v2_sparse_classes_30k_train_005451 | Implement the Python class `AgentsClient` described below.
Class description:
Tests Agents API
Method signatures and docstrings:
- def list_agents(self, **params): List all agent builds. For a full list of available parameters, please refer to the official API reference: https://docs.openstack.org/api-ref/compute/#li... | Implement the Python class `AgentsClient` described below.
Class description:
Tests Agents API
Method signatures and docstrings:
- def list_agents(self, **params): List all agent builds. For a full list of available parameters, please refer to the official API reference: https://docs.openstack.org/api-ref/compute/#li... | 3932a799e620a20d7abf7b89e21b520683a1809b | <|skeleton|>
class AgentsClient:
"""Tests Agents API"""
def list_agents(self, **params):
"""List all agent builds. For a full list of available parameters, please refer to the official API reference: https://docs.openstack.org/api-ref/compute/#list-agent-builds"""
<|body_0|>
def create_age... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AgentsClient:
"""Tests Agents API"""
def list_agents(self, **params):
"""List all agent builds. For a full list of available parameters, please refer to the official API reference: https://docs.openstack.org/api-ref/compute/#list-agent-builds"""
url = 'os-agents'
if params:
... | the_stack_v2_python_sparse | tempest/lib/services/compute/agents_client.py | openstack/tempest | train | 270 |
9e7614e4486fb6efd46ab43ba0dc495849ab9872 | [
"if isinstance(data, PropertyData):\n pdata = data\nelif isinstance(data, list):\n pdata = PropertyData(data)\nelse:\n raise TypeError('list or PropertyData object required')\nsuper(PropertyTable, self).__init__(data=pdata, **kwargs)",
"fp = get_file(file_or_path)\nd = json.load(fp)\nPropertyTable._valid... | <|body_start_0|>
if isinstance(data, PropertyData):
pdata = data
elif isinstance(data, list):
pdata = PropertyData(data)
else:
raise TypeError('list or PropertyData object required')
super(PropertyTable, self).__init__(data=pdata, **kwargs)
<|end_body_... | Property data and metadata together (at last!) | PropertyTable | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PropertyTable:
"""Property data and metadata together (at last!)"""
def __init__(self, data=None, **kwargs):
"""Constructor."""
<|body_0|>
def load(cls, file_or_path, validate=True):
"""Create PropertyTable from JSON input. Args: file_or_path (file or str): Filen... | stack_v2_sparse_classes_36k_train_029845 | 18,955 | permissive | [
{
"docstring": "Constructor.",
"name": "__init__",
"signature": "def __init__(self, data=None, **kwargs)"
},
{
"docstring": "Create PropertyTable from JSON input. Args: file_or_path (file or str): Filename or file object from which to read the JSON-formatted data. validate (bool): If true, apply... | 2 | null | Implement the Python class `PropertyTable` described below.
Class description:
Property data and metadata together (at last!)
Method signatures and docstrings:
- def __init__(self, data=None, **kwargs): Constructor.
- def load(cls, file_or_path, validate=True): Create PropertyTable from JSON input. Args: file_or_path... | Implement the Python class `PropertyTable` described below.
Class description:
Property data and metadata together (at last!)
Method signatures and docstrings:
- def __init__(self, data=None, **kwargs): Constructor.
- def load(cls, file_or_path, validate=True): Create PropertyTable from JSON input. Args: file_or_path... | afec89b8273fcc17a0b5f08ea9b97b5fc98d2a31 | <|skeleton|>
class PropertyTable:
"""Property data and metadata together (at last!)"""
def __init__(self, data=None, **kwargs):
"""Constructor."""
<|body_0|>
def load(cls, file_or_path, validate=True):
"""Create PropertyTable from JSON input. Args: file_or_path (file or str): Filen... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PropertyTable:
"""Property data and metadata together (at last!)"""
def __init__(self, data=None, **kwargs):
"""Constructor."""
if isinstance(data, PropertyData):
pdata = data
elif isinstance(data, list):
pdata = PropertyData(data)
else:
... | the_stack_v2_python_sparse | idaes/dmf/propdata.py | JackaChou/idaes-pse | train | 1 |
04569dc67a6203e38376f57751e863878eb75d0b | [
"self.index_name = index_name\nself._rule = kwargs.get('rule')\nsuper().__init__(index_name, sketch_id, timeline_id=timeline_id)",
"if not tag_list:\n tag_list = []\nreturn_fields = []\ntagged_events_counter = 0\nevents = self.event_stream(query_string=query, return_fields=return_fields)\nfor event in events:\... | <|body_start_0|>
self.index_name = index_name
self._rule = kwargs.get('rule')
super().__init__(index_name, sketch_id, timeline_id=timeline_id)
<|end_body_0|>
<|body_start_1|>
if not tag_list:
tag_list = []
return_fields = []
tagged_events_counter = 0
... | Analyzer for Sigma Rules. | SigmaPlugin | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SigmaPlugin:
"""Analyzer for Sigma Rules."""
def __init__(self, index_name, sketch_id, timeline_id=None, **kwargs):
"""Initialize The Sigma Analyzer. Args: index_name: OpenSearch index name sketch_id: Sketch ID timeline_id: The ID of the timeline."""
<|body_0|>
def run_s... | stack_v2_sparse_classes_36k_train_029846 | 4,728 | permissive | [
{
"docstring": "Initialize The Sigma Analyzer. Args: index_name: OpenSearch index name sketch_id: Sketch ID timeline_id: The ID of the timeline.",
"name": "__init__",
"signature": "def __init__(self, index_name, sketch_id, timeline_id=None, **kwargs)"
},
{
"docstring": "Runs a sigma rule and app... | 4 | null | Implement the Python class `SigmaPlugin` described below.
Class description:
Analyzer for Sigma Rules.
Method signatures and docstrings:
- def __init__(self, index_name, sketch_id, timeline_id=None, **kwargs): Initialize The Sigma Analyzer. Args: index_name: OpenSearch index name sketch_id: Sketch ID timeline_id: The... | Implement the Python class `SigmaPlugin` described below.
Class description:
Analyzer for Sigma Rules.
Method signatures and docstrings:
- def __init__(self, index_name, sketch_id, timeline_id=None, **kwargs): Initialize The Sigma Analyzer. Args: index_name: OpenSearch index name sketch_id: Sketch ID timeline_id: The... | 24f471b58ca4a87cb053961b5f05c07a544ca7b8 | <|skeleton|>
class SigmaPlugin:
"""Analyzer for Sigma Rules."""
def __init__(self, index_name, sketch_id, timeline_id=None, **kwargs):
"""Initialize The Sigma Analyzer. Args: index_name: OpenSearch index name sketch_id: Sketch ID timeline_id: The ID of the timeline."""
<|body_0|>
def run_s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SigmaPlugin:
"""Analyzer for Sigma Rules."""
def __init__(self, index_name, sketch_id, timeline_id=None, **kwargs):
"""Initialize The Sigma Analyzer. Args: index_name: OpenSearch index name sketch_id: Sketch ID timeline_id: The ID of the timeline."""
self.index_name = index_name
s... | the_stack_v2_python_sparse | timesketch/lib/analyzers/sigma_tagger.py | google/timesketch | train | 2,263 |
311ebc902bf5f7729c3ad898f353e3e7bf855b5a | [
"func = self._module.locally_linear_embedding\ny, squared_error = func(self._data.values, n_neighbors, n_components, *args, **kwargs)\ny = self._constructor(y, index=self._df.index)\nreturn (y, squared_error)",
"func = self._module.spectral_embedding\ndata = self._data\nembedding = func(data.values, *args, **kwar... | <|body_start_0|>
func = self._module.locally_linear_embedding
y, squared_error = func(self._data.values, n_neighbors, n_components, *args, **kwargs)
y = self._constructor(y, index=self._df.index)
return (y, squared_error)
<|end_body_0|>
<|body_start_1|>
func = self._module.spect... | Accessor to ``sklearn.manifold``. | ManifoldMethods | [
"Python-2.0",
"Apache-2.0",
"BSD-3-Clause",
"LicenseRef-scancode-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ManifoldMethods:
"""Accessor to ``sklearn.manifold``."""
def locally_linear_embedding(self, n_neighbors, n_components, *args, **kwargs):
"""Call ``sklearn.manifold.locally_linear_embedding`` using automatic mapping. - ``X``: ``ModelFrame.data``"""
<|body_0|>
def spectral... | stack_v2_sparse_classes_36k_train_029847 | 1,167 | permissive | [
{
"docstring": "Call ``sklearn.manifold.locally_linear_embedding`` using automatic mapping. - ``X``: ``ModelFrame.data``",
"name": "locally_linear_embedding",
"signature": "def locally_linear_embedding(self, n_neighbors, n_components, *args, **kwargs)"
},
{
"docstring": "Call ``sklearn.manifold.... | 2 | stack_v2_sparse_classes_30k_train_011571 | Implement the Python class `ManifoldMethods` described below.
Class description:
Accessor to ``sklearn.manifold``.
Method signatures and docstrings:
- def locally_linear_embedding(self, n_neighbors, n_components, *args, **kwargs): Call ``sklearn.manifold.locally_linear_embedding`` using automatic mapping. - ``X``: ``... | Implement the Python class `ManifoldMethods` described below.
Class description:
Accessor to ``sklearn.manifold``.
Method signatures and docstrings:
- def locally_linear_embedding(self, n_neighbors, n_components, *args, **kwargs): Call ``sklearn.manifold.locally_linear_embedding`` using automatic mapping. - ``X``: ``... | 2c9002f16bb5c265e0d14f4a2314c86eeaa35cb6 | <|skeleton|>
class ManifoldMethods:
"""Accessor to ``sklearn.manifold``."""
def locally_linear_embedding(self, n_neighbors, n_components, *args, **kwargs):
"""Call ``sklearn.manifold.locally_linear_embedding`` using automatic mapping. - ``X``: ``ModelFrame.data``"""
<|body_0|>
def spectral... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ManifoldMethods:
"""Accessor to ``sklearn.manifold``."""
def locally_linear_embedding(self, n_neighbors, n_components, *args, **kwargs):
"""Call ``sklearn.manifold.locally_linear_embedding`` using automatic mapping. - ``X``: ``ModelFrame.data``"""
func = self._module.locally_linear_embedd... | the_stack_v2_python_sparse | lib/python2.7/site-packages/pandas_ml/skaccessors/manifold.py | wangyum/Anaconda | train | 11 |
936f7860f120f92e44392776ddd14df0400fd61c | [
"f = getattr(loc, self.algorithm).batch\nopts = self.options\n\ndef ret(image):\n lc = f(image, **opts)\n return lc\nreturn ret",
"for i in range(self.dataset.rowCount()):\n file = self.dataset.get(i, 'key')\n ld = self.dataset.get(i, 'locData')\n io.save(file.with_suffix('.h5'), ld)\n with file... | <|body_start_0|>
f = getattr(loc, self.algorithm).batch
opts = self.options
def ret(image):
lc = f(image, **opts)
return lc
return ret
<|end_body_0|>
<|body_start_1|>
for i in range(self.dataset.rowCount()):
file = self.dataset.get(i, 'key')
... | Locator | [
"BSD-3-Clause",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Locator:
def getLocateFunc(self) -> Callable[[Iterable[np.ndarray]], pd.DataFrame]:
"""Get a function that runs localization algorithm on image sequence Returns ------- The function takes an iterable of 2D arrays and will run the currently selected algorithm with currently selected optio... | stack_v2_sparse_classes_36k_train_029848 | 4,039 | permissive | [
{
"docstring": "Get a function that runs localization algorithm on image sequence Returns ------- The function takes an iterable of 2D arrays and will run the currently selected algorithm with currently selected options on this. See :py:func:`sdt.loc.daostorm_3d.batch` and :py:func:`sdt.loc.cg.batch`.",
"na... | 2 | null | Implement the Python class `Locator` described below.
Class description:
Implement the Locator class.
Method signatures and docstrings:
- def getLocateFunc(self) -> Callable[[Iterable[np.ndarray]], pd.DataFrame]: Get a function that runs localization algorithm on image sequence Returns ------- The function takes an i... | Implement the Python class `Locator` described below.
Class description:
Implement the Locator class.
Method signatures and docstrings:
- def getLocateFunc(self) -> Callable[[Iterable[np.ndarray]], pd.DataFrame]: Get a function that runs localization algorithm on image sequence Returns ------- The function takes an i... | 2f953e553f32118c3ad1f244481e5a0ac6c533f0 | <|skeleton|>
class Locator:
def getLocateFunc(self) -> Callable[[Iterable[np.ndarray]], pd.DataFrame]:
"""Get a function that runs localization algorithm on image sequence Returns ------- The function takes an iterable of 2D arrays and will run the currently selected algorithm with currently selected optio... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Locator:
def getLocateFunc(self) -> Callable[[Iterable[np.ndarray]], pd.DataFrame]:
"""Get a function that runs localization algorithm on image sequence Returns ------- The function takes an iterable of 2D arrays and will run the currently selected algorithm with currently selected options on this. Se... | the_stack_v2_python_sparse | sdt/gui/locator.py | schuetzgroup/sdt-python | train | 31 | |
4697393de6c2fd3186c5942b3a0c7255edf69a67 | [
"self._N = N\nself._g = g\nself._salt = salt\nself._A = A\nself._b = b\nself._u = u\nself._hmac = hmac\nself._id = identifier\nsuper().__init__()",
"xH = utils.sha256_mac(b'', utils.rawstr2bytes(str(self._salt) + password))\nx = int(xH.hex(), 16)\nv = pow(self._g, x, self._N)\nSb = self._A * pow(v, self._u, self.... | <|body_start_0|>
self._N = N
self._g = g
self._salt = salt
self._A = A
self._b = b
self._u = u
self._hmac = hmac
self._id = identifier
super().__init__()
<|end_body_0|>
<|body_start_1|>
xH = utils.sha256_mac(b'', utils.rawstr2bytes(str(sel... | The thread used for the password breaking. | PasswordBreaker | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PasswordBreaker:
"""The thread used for the password breaking."""
def __init__(self, N, g, salt, A, b, u, hmac, identifier):
"""The constructor: gathers the elements required for breaking the password."""
<|body_0|>
def get_password_hmac(self, password):
"""Compu... | stack_v2_sparse_classes_36k_train_029849 | 10,843 | permissive | [
{
"docstring": "The constructor: gathers the elements required for breaking the password.",
"name": "__init__",
"signature": "def __init__(self, N, g, salt, A, b, u, hmac, identifier)"
},
{
"docstring": "Compute the HMAC if the password would be 'password'.",
"name": "get_password_hmac",
... | 3 | null | Implement the Python class `PasswordBreaker` described below.
Class description:
The thread used for the password breaking.
Method signatures and docstrings:
- def __init__(self, N, g, salt, A, b, u, hmac, identifier): The constructor: gathers the elements required for breaking the password.
- def get_password_hmac(s... | Implement the Python class `PasswordBreaker` described below.
Class description:
The thread used for the password breaking.
Method signatures and docstrings:
- def __init__(self, N, g, salt, A, b, u, hmac, identifier): The constructor: gathers the elements required for breaking the password.
- def get_password_hmac(s... | d322930cc94cfde28239b9738e8cd36e304532ea | <|skeleton|>
class PasswordBreaker:
"""The thread used for the password breaking."""
def __init__(self, N, g, salt, A, b, u, hmac, identifier):
"""The constructor: gathers the elements required for breaking the password."""
<|body_0|>
def get_password_hmac(self, password):
"""Compu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PasswordBreaker:
"""The thread used for the password breaking."""
def __init__(self, N, g, salt, A, b, u, hmac, identifier):
"""The constructor: gathers the elements required for breaking the password."""
self._N = N
self._g = g
self._salt = salt
self._A = A
... | the_stack_v2_python_sparse | src/cp_test_c38_attacker.py | rjpdasilva/cryptopals | train | 0 |
5e42760a034b71e1e46b4c0890349b7fb4ab2ac6 | [
"for name, c in inspect.getmembers(spaces):\n if inspect.isclass(c):\n cls.classes.append(c)",
"for c in self.classes:\n if c not in class_arguments:\n assert False",
"for c in self.classes:\n if c in class_arguments:\n check = partial(self.check_contains)\n check.descriptio... | <|body_start_0|>
for name, c in inspect.getmembers(spaces):
if inspect.isclass(c):
cls.classes.append(c)
<|end_body_0|>
<|body_start_1|>
for c in self.classes:
if c not in class_arguments:
assert False
<|end_body_1|>
<|body_start_2|>
for ... | Wrap spaces tests. | TestSpaces | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSpaces:
"""Wrap spaces tests."""
def setUpClass(cls):
"""Initialize classes list."""
<|body_0|>
def exhaustive_tests(self):
"""Check: Spaces tests initial values for testing."""
<|body_1|>
def generate_tests(self):
"""Generate tests for s... | stack_v2_sparse_classes_36k_train_029850 | 1,519 | permissive | [
{
"docstring": "Initialize classes list.",
"name": "setUpClass",
"signature": "def setUpClass(cls)"
},
{
"docstring": "Check: Spaces tests initial values for testing.",
"name": "exhaustive_tests",
"signature": "def exhaustive_tests(self)"
},
{
"docstring": "Generate tests for spa... | 4 | null | Implement the Python class `TestSpaces` described below.
Class description:
Wrap spaces tests.
Method signatures and docstrings:
- def setUpClass(cls): Initialize classes list.
- def exhaustive_tests(self): Check: Spaces tests initial values for testing.
- def generate_tests(self): Generate tests for spaces implement... | Implement the Python class `TestSpaces` described below.
Class description:
Wrap spaces tests.
Method signatures and docstrings:
- def setUpClass(cls): Initialize classes list.
- def exhaustive_tests(self): Check: Spaces tests initial values for testing.
- def generate_tests(self): Generate tests for spaces implement... | 8500c8dd90a2b59a91b988a3c83e529f6c69332f | <|skeleton|>
class TestSpaces:
"""Wrap spaces tests."""
def setUpClass(cls):
"""Initialize classes list."""
<|body_0|>
def exhaustive_tests(self):
"""Check: Spaces tests initial values for testing."""
<|body_1|>
def generate_tests(self):
"""Generate tests for s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestSpaces:
"""Wrap spaces tests."""
def setUpClass(cls):
"""Initialize classes list."""
for name, c in inspect.getmembers(spaces):
if inspect.isclass(c):
cls.classes.append(c)
def exhaustive_tests(self):
"""Check: Spaces tests initial values for t... | the_stack_v2_python_sparse | Safe-RL/Safe-RL-Benchmark/SafeRLBench/spaces/test.py | chauncygu/Safe-Reinforcement-Learning-Baselines | train | 233 |
eec0a00e433fb077ca8eae8947517c709b44cbec | [
"def adjs(i, j):\n for x, y in [(i + 1, j), (i - 1, j), (i, j + 1), (i, j - 1)]:\n if 0 <= x < len(A) and 0 <= y < len(A[0]):\n yield (x, y)\ncurr = deque()\nseen = set()\nfor i, row in enumerate(A):\n for j, space in enumerate(row):\n if space:\n break\n if space:\n ... | <|body_start_0|>
def adjs(i, j):
for x, y in [(i + 1, j), (i - 1, j), (i, j + 1), (i, j - 1)]:
if 0 <= x < len(A) and 0 <= y < len(A[0]):
yield (x, y)
curr = deque()
seen = set()
for i, row in enumerate(A):
for j, space in enume... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def shortestBridge(self, A: List[List[int]]) -> int:
"""Implementation using BFS and `set`, which is cleaner syntax-wise in my opinion:"""
<|body_0|>
def shortestBridge(self, A: List[List[int]]) -> int:
"""Solution using a 2D array for `seen`, which uses le... | stack_v2_sparse_classes_36k_train_029851 | 2,482 | no_license | [
{
"docstring": "Implementation using BFS and `set`, which is cleaner syntax-wise in my opinion:",
"name": "shortestBridge",
"signature": "def shortestBridge(self, A: List[List[int]]) -> int"
},
{
"docstring": "Solution using a 2D array for `seen`, which uses less memory:",
"name": "shortestB... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def shortestBridge(self, A: List[List[int]]) -> int: Implementation using BFS and `set`, which is cleaner syntax-wise in my opinion:
- def shortestBridge(self, A: List[List[int]]... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def shortestBridge(self, A: List[List[int]]) -> int: Implementation using BFS and `set`, which is cleaner syntax-wise in my opinion:
- def shortestBridge(self, A: List[List[int]]... | f4cd43f082b58d4410008af49325770bc84d3aba | <|skeleton|>
class Solution:
def shortestBridge(self, A: List[List[int]]) -> int:
"""Implementation using BFS and `set`, which is cleaner syntax-wise in my opinion:"""
<|body_0|>
def shortestBridge(self, A: List[List[int]]) -> int:
"""Solution using a 2D array for `seen`, which uses le... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def shortestBridge(self, A: List[List[int]]) -> int:
"""Implementation using BFS and `set`, which is cleaner syntax-wise in my opinion:"""
def adjs(i, j):
for x, y in [(i + 1, j), (i - 1, j), (i, j + 1), (i, j - 1)]:
if 0 <= x < len(A) and 0 <= y < len(A[0... | the_stack_v2_python_sparse | 934.Shortest_Bridge.py | welsny/solutions | train | 1 | |
355193ea49364cb2f24d7d7a5c9175078dc6dea6 | [
"current_app.logger.info('<AccountStatementsSettings.get')\ncheck_auth(business_identifier=None, account_id=account_id, contains_role=EDIT_ROLE, is_premium=True)\nresponse, status = (StatementSettingsService.find_by_account_id(account_id), HTTPStatus.OK)\ncurrent_app.logger.debug('>AccountStatementsSettings.get')\n... | <|body_start_0|>
current_app.logger.info('<AccountStatementsSettings.get')
check_auth(business_identifier=None, account_id=account_id, contains_role=EDIT_ROLE, is_premium=True)
response, status = (StatementSettingsService.find_by_account_id(account_id), HTTPStatus.OK)
current_app.logger.... | Endpoint resource for statements. | AccountStatementsSettings | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AccountStatementsSettings:
"""Endpoint resource for statements."""
def get(account_id):
"""Get all statements records for an account."""
<|body_0|>
def post(account_id):
"""Update the statement settings ."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_029852 | 3,037 | permissive | [
{
"docstring": "Get all statements records for an account.",
"name": "get",
"signature": "def get(account_id)"
},
{
"docstring": "Update the statement settings .",
"name": "post",
"signature": "def post(account_id)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009441 | Implement the Python class `AccountStatementsSettings` described below.
Class description:
Endpoint resource for statements.
Method signatures and docstrings:
- def get(account_id): Get all statements records for an account.
- def post(account_id): Update the statement settings . | Implement the Python class `AccountStatementsSettings` described below.
Class description:
Endpoint resource for statements.
Method signatures and docstrings:
- def get(account_id): Get all statements records for an account.
- def post(account_id): Update the statement settings .
<|skeleton|>
class AccountStatements... | 0d71d37b0e08d11f6b6d9f59a4b202dfabc98fc1 | <|skeleton|>
class AccountStatementsSettings:
"""Endpoint resource for statements."""
def get(account_id):
"""Get all statements records for an account."""
<|body_0|>
def post(account_id):
"""Update the statement settings ."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AccountStatementsSettings:
"""Endpoint resource for statements."""
def get(account_id):
"""Get all statements records for an account."""
current_app.logger.info('<AccountStatementsSettings.get')
check_auth(business_identifier=None, account_id=account_id, contains_role=EDIT_ROLE, i... | the_stack_v2_python_sparse | pay-api/src/pay_api/resources/account_statements_settings.py | bcgov/sbc-pay | train | 6 |
2e303c43098f5dbb41096616a5f2fe2682d33b78 | [
"super(GaussianProcessClassifier, self).__init__(kernel=kernel, sigma=sigma, a=a, b=b, h=h, theta=theta)\nClassifier.__init__(self)\nself.alpha = alpha\nself.gamma = gamma\nself.max_iter = max_iter\nself.threshold = threshold",
"y = self._onehot_to_label(y)\ny = y.reshape(-1, 1)\nself.X = X\nself.y = y\nC = self.... | <|body_start_0|>
super(GaussianProcessClassifier, self).__init__(kernel=kernel, sigma=sigma, a=a, b=b, h=h, theta=theta)
Classifier.__init__(self)
self.alpha = alpha
self.gamma = gamma
self.max_iter = max_iter
self.threshold = threshold
<|end_body_0|>
<|body_start_1|>
... | GaussianProcessClassifier Attributes: kernel_func (function) : kernel function k(x,y) gram_func (function) : function which make gram matrix alpha (float) : hyperparameter gamma (float) : noise parameter to ensure C is positive definite | GaussianProcessClassifier | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GaussianProcessClassifier:
"""GaussianProcessClassifier Attributes: kernel_func (function) : kernel function k(x,y) gram_func (function) : function which make gram matrix alpha (float) : hyperparameter gamma (float) : noise parameter to ensure C is positive definite"""
def __init__(self, alp... | stack_v2_sparse_classes_36k_train_029853 | 10,708 | permissive | [
{
"docstring": "Args: alpha (float) : hyperparameter gamma (float) : noise parameter to ensure C is positive definite max_iter (int) : max iteration for parameter optimization threshold (float) : threshold for optimizint parameters kernel (string) : kernel type (default \"Linear\"). you can choose \"Linear\",\"... | 3 | stack_v2_sparse_classes_30k_train_012186 | Implement the Python class `GaussianProcessClassifier` described below.
Class description:
GaussianProcessClassifier Attributes: kernel_func (function) : kernel function k(x,y) gram_func (function) : function which make gram matrix alpha (float) : hyperparameter gamma (float) : noise parameter to ensure C is positive ... | Implement the Python class `GaussianProcessClassifier` described below.
Class description:
GaussianProcessClassifier Attributes: kernel_func (function) : kernel function k(x,y) gram_func (function) : function which make gram matrix alpha (float) : hyperparameter gamma (float) : noise parameter to ensure C is positive ... | 992f2c07e88b2bad331e08303bdba84684f04d40 | <|skeleton|>
class GaussianProcessClassifier:
"""GaussianProcessClassifier Attributes: kernel_func (function) : kernel function k(x,y) gram_func (function) : function which make gram matrix alpha (float) : hyperparameter gamma (float) : noise parameter to ensure C is positive definite"""
def __init__(self, alp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GaussianProcessClassifier:
"""GaussianProcessClassifier Attributes: kernel_func (function) : kernel function k(x,y) gram_func (function) : function which make gram matrix alpha (float) : hyperparameter gamma (float) : noise parameter to ensure C is positive definite"""
def __init__(self, alpha=1.0, gamma... | the_stack_v2_python_sparse | prml/kernel_method.py | hedwig100/PRML | train | 1 |
e70cb27efe800d73073f6aefb7e93d4dc533c8be | [
"if not nums:\n return -1\nelse:\n max_sum = nums[0]\n sum = 0\n for num in nums:\n if sum > 0:\n sum = sum + num\n else:\n sum = num\n max_sum = max(max_sum, sum)\n return max_sum",
"n = len(nums)\nmax_sum = nums[0]\nfor i in range(1, n):\n if nums[i -... | <|body_start_0|>
if not nums:
return -1
else:
max_sum = nums[0]
sum = 0
for num in nums:
if sum > 0:
sum = sum + num
else:
sum = num
max_sum = max(max_sum, sum)
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def maxSubArray(self, nums: [int]) -> int:
"""贪心.使用单个数组作为输入来查找最大（或最小）元素（或总和）的问题，贪心算法是可以在线性时间解决的方法之一。 每一步都选择最佳方案，到最后就是全局最优的方案。 :param nums: :return:"""
<|body_0|>
def maxSubArray1(self, nums: [int]) -> int:
"""动态规划。 在整个数组或在固定大小的滑动窗口中找到总和或最大值或最小值的问题可以通过动态规划（D... | stack_v2_sparse_classes_36k_train_029854 | 1,515 | no_license | [
{
"docstring": "贪心.使用单个数组作为输入来查找最大（或最小）元素（或总和）的问题，贪心算法是可以在线性时间解决的方法之一。 每一步都选择最佳方案，到最后就是全局最优的方案。 :param nums: :return:",
"name": "maxSubArray",
"signature": "def maxSubArray(self, nums: [int]) -> int"
},
{
"docstring": "动态规划。 在整个数组或在固定大小的滑动窗口中找到总和或最大值或最小值的问题可以通过动态规划（DP）在线性时间内解决。 有两种标准 DP 方法适用于数组：... | 2 | stack_v2_sparse_classes_30k_train_015867 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray(self, nums: [int]) -> int: 贪心.使用单个数组作为输入来查找最大（或最小）元素（或总和）的问题，贪心算法是可以在线性时间解决的方法之一。 每一步都选择最佳方案，到最后就是全局最优的方案。 :param nums: :return:
- def maxSubArray1(self, nums: [i... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def maxSubArray(self, nums: [int]) -> int: 贪心.使用单个数组作为输入来查找最大（或最小）元素（或总和）的问题，贪心算法是可以在线性时间解决的方法之一。 每一步都选择最佳方案，到最后就是全局最优的方案。 :param nums: :return:
- def maxSubArray1(self, nums: [i... | 4328382a65ac612aa4dc397f475c1d7db25c7723 | <|skeleton|>
class Solution:
def maxSubArray(self, nums: [int]) -> int:
"""贪心.使用单个数组作为输入来查找最大（或最小）元素（或总和）的问题，贪心算法是可以在线性时间解决的方法之一。 每一步都选择最佳方案，到最后就是全局最优的方案。 :param nums: :return:"""
<|body_0|>
def maxSubArray1(self, nums: [int]) -> int:
"""动态规划。 在整个数组或在固定大小的滑动窗口中找到总和或最大值或最小值的问题可以通过动态规划（D... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def maxSubArray(self, nums: [int]) -> int:
"""贪心.使用单个数组作为输入来查找最大（或最小）元素（或总和）的问题，贪心算法是可以在线性时间解决的方法之一。 每一步都选择最佳方案，到最后就是全局最优的方案。 :param nums: :return:"""
if not nums:
return -1
else:
max_sum = nums[0]
sum = 0
for num in nums:
... | the_stack_v2_python_sparse | thor/array/ac_53.py | duangduangda/Thor | train | 0 | |
1d052e68851bfbee35867cf6718e181321af9c24 | [
"stack = [root] if root else []\nall_nodes = {}\nwhile stack:\n new_stack = []\n for node in stack:\n for child in (node.left, node.right):\n if child:\n all_nodes[child] = node\n new_stack.append(child)\n if not new_stack:\n break\n stack = new_sta... | <|body_start_0|>
stack = [root] if root else []
all_nodes = {}
while stack:
new_stack = []
for node in stack:
for child in (node.left, node.right):
if child:
all_nodes[child] = node
new_st... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def subtreeWithAllDeepest(self, root):
""":type root: TreeNode :rtype: TreeNode"""
<|body_0|>
def subtreeWithAllDeepest(self, root):
""":type root: TreeNode :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
stack = [root] if... | stack_v2_sparse_classes_36k_train_029855 | 1,261 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: TreeNode",
"name": "subtreeWithAllDeepest",
"signature": "def subtreeWithAllDeepest(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: TreeNode",
"name": "subtreeWithAllDeepest",
"signature": "def subtreeWithAllDeepest(self, root)"
... | 2 | stack_v2_sparse_classes_30k_train_007431 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def subtreeWithAllDeepest(self, root): :type root: TreeNode :rtype: TreeNode
- def subtreeWithAllDeepest(self, root): :type root: TreeNode :rtype: TreeNode | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def subtreeWithAllDeepest(self, root): :type root: TreeNode :rtype: TreeNode
- def subtreeWithAllDeepest(self, root): :type root: TreeNode :rtype: TreeNode
<|skeleton|>
class So... | 16e4343922041929bc3021e152093425066620bb | <|skeleton|>
class Solution:
def subtreeWithAllDeepest(self, root):
""":type root: TreeNode :rtype: TreeNode"""
<|body_0|>
def subtreeWithAllDeepest(self, root):
""":type root: TreeNode :rtype: TreeNode"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def subtreeWithAllDeepest(self, root):
""":type root: TreeNode :rtype: TreeNode"""
stack = [root] if root else []
all_nodes = {}
while stack:
new_stack = []
for node in stack:
for child in (node.left, node.right):
... | the_stack_v2_python_sparse | 865_subtreeWithAllDeepest.py | zzz686970/leetcode-2018 | train | 3 | |
73cd8cd59396e908a3db3efd064b6c56c542892a | [
"super().__init__()\nself.depth = depth\nself.tag = tag\nself._checked = False\nself.toggle_active()\nself.setEditable(False)\nrgb = color.replace(')', '').replace(' ', '').split('(')[-1].split(',')\nself.setForeground(QColor(*[int(r) for r in rgb]))\nself.setText(txt)",
"fnt = QFont('Roboto', 14)\nif self._check... | <|body_start_0|>
super().__init__()
self.depth = depth
self.tag = tag
self._checked = False
self.toggle_active()
self.setEditable(False)
rgb = color.replace(')', '').replace(' ', '').split('(')[-1].split(',')
self.setForeground(QColor(*[int(r) for r in rgb... | StandardItem | [
"BSD-3-Clause",
"GPL-3.0-only"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StandardItem:
def __init__(self, txt='', tag=None, depth=0, color=None):
"""Items in the tree list with some extended functionality to specify/update their look."""
<|body_0|>
def toggle_active(self):
"""When a mesh corresponding to the item's region get's rendered, ... | stack_v2_sparse_classes_36k_train_029856 | 1,232 | permissive | [
{
"docstring": "Items in the tree list with some extended functionality to specify/update their look.",
"name": "__init__",
"signature": "def __init__(self, txt='', tag=None, depth=0, color=None)"
},
{
"docstring": "When a mesh corresponding to the item's region get's rendered, change the font t... | 2 | null | Implement the Python class `StandardItem` described below.
Class description:
Implement the StandardItem class.
Method signatures and docstrings:
- def __init__(self, txt='', tag=None, depth=0, color=None): Items in the tree list with some extended functionality to specify/update their look.
- def toggle_active(self)... | Implement the Python class `StandardItem` described below.
Class description:
Implement the StandardItem class.
Method signatures and docstrings:
- def __init__(self, txt='', tag=None, depth=0, color=None): Items in the tree list with some extended functionality to specify/update their look.
- def toggle_active(self)... | a14ead80c1dbc75f20a145a49394dc467c4f7bf1 | <|skeleton|>
class StandardItem:
def __init__(self, txt='', tag=None, depth=0, color=None):
"""Items in the tree list with some extended functionality to specify/update their look."""
<|body_0|>
def toggle_active(self):
"""When a mesh corresponding to the item's region get's rendered, ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StandardItem:
def __init__(self, txt='', tag=None, depth=0, color=None):
"""Items in the tree list with some extended functionality to specify/update their look."""
super().__init__()
self.depth = depth
self.tag = tag
self._checked = False
self.toggle_active()
... | the_stack_v2_python_sparse | brainrender/gui/widgets/tree.py | brainglobe/brainrender | train | 345 | |
b5d588c6f95481853b9d658933d0ec48620f8d7e | [
"L = step.levels[level_number]\nL.sweep.compute_end_point()\nu_ref = L.prob.u_exact(t=L.time + L.dt)\nself.add_to_stats(process=step.status.slot, time=L.time + L.dt, level=L.level_index, iter=step.status.iter, sweep=L.status.sweep, type=f'e_global{suffix}', value=abs(u_ref - L.uend))\nself.add_to_stats(process=step... | <|body_start_0|>
L = step.levels[level_number]
L.sweep.compute_end_point()
u_ref = L.prob.u_exact(t=L.time + L.dt)
self.add_to_stats(process=step.status.slot, time=L.time + L.dt, level=L.level_index, iter=step.status.iter, sweep=L.status.sweep, type=f'e_global{suffix}', value=abs(u_ref -... | Base class with functions to add the local and global error to the stats, which can be inherited by hooks logging these at specific places. Errors are computed with respect to `u_exact` defined in the problem class. Be aware that this requires the problems to be compatible with this. We need some kind of "exact" soluti... | LogError | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LogError:
"""Base class with functions to add the local and global error to the stats, which can be inherited by hooks logging these at specific places. Errors are computed with respect to `u_exact` defined in the problem class. Be aware that this requires the problems to be compatible with this.... | stack_v2_sparse_classes_36k_train_029857 | 7,407 | permissive | [
{
"docstring": "Function to add the global error to the stats Args: step (pySDC.Step.step): The current step level_number (int): The index of the level suffix (str): Suffix for naming the variable in stats Returns: None",
"name": "log_global_error",
"signature": "def log_global_error(self, step, level_n... | 2 | null | Implement the Python class `LogError` described below.
Class description:
Base class with functions to add the local and global error to the stats, which can be inherited by hooks logging these at specific places. Errors are computed with respect to `u_exact` defined in the problem class. Be aware that this requires t... | Implement the Python class `LogError` described below.
Class description:
Base class with functions to add the local and global error to the stats, which can be inherited by hooks logging these at specific places. Errors are computed with respect to `u_exact` defined in the problem class. Be aware that this requires t... | 1a51834bedffd4472e344bed28f4d766614b1537 | <|skeleton|>
class LogError:
"""Base class with functions to add the local and global error to the stats, which can be inherited by hooks logging these at specific places. Errors are computed with respect to `u_exact` defined in the problem class. Be aware that this requires the problems to be compatible with this.... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LogError:
"""Base class with functions to add the local and global error to the stats, which can be inherited by hooks logging these at specific places. Errors are computed with respect to `u_exact` defined in the problem class. Be aware that this requires the problems to be compatible with this. We need some... | the_stack_v2_python_sparse | pySDC/implementations/hooks/log_errors.py | Parallel-in-Time/pySDC | train | 30 |
d897c9ca13ebcfaa38c8b439461ccd66128ae5dc | [
"self.serializer = instance_serializer\nkwargs['source'] = '*'\nsuper().__init__(**kwargs)",
"if data == self.parent.context['request'].user.id:\n raise serializers.ValidationError('Cannot be friend with self.')\nreturn {'friend': User.objects.get(id=data)}",
"if self.parent.context['request'].user == value.... | <|body_start_0|>
self.serializer = instance_serializer
kwargs['source'] = '*'
super().__init__(**kwargs)
<|end_body_0|>
<|body_start_1|>
if data == self.parent.context['request'].user.id:
raise serializers.ValidationError('Cannot be friend with self.')
return {'frien... | Field for a friend. This will check the `from_account` and `to_account` values and will return the one that is not the current user. :param instance_serializer: serializer used to serialize the friend :param kwargs: additional arguments to pass to the `Field` constructor | FriendField | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FriendField:
"""Field for a friend. This will check the `from_account` and `to_account` values and will return the one that is not the current user. :param instance_serializer: serializer used to serialize the friend :param kwargs: additional arguments to pass to the `Field` constructor"""
d... | stack_v2_sparse_classes_36k_train_029858 | 14,729 | no_license | [
{
"docstring": "Override the default constructor of field to force the `source` to be the whole object. This also sets the serializer used internally :param kwargs: arguments to pass to the parent constructor",
"name": "__init__",
"signature": "def __init__(self, instance_serializer, **kwargs)"
},
{... | 3 | stack_v2_sparse_classes_30k_train_005627 | Implement the Python class `FriendField` described below.
Class description:
Field for a friend. This will check the `from_account` and `to_account` values and will return the one that is not the current user. :param instance_serializer: serializer used to serialize the friend :param kwargs: additional arguments to pa... | Implement the Python class `FriendField` described below.
Class description:
Field for a friend. This will check the `from_account` and `to_account` values and will return the one that is not the current user. :param instance_serializer: serializer used to serialize the friend :param kwargs: additional arguments to pa... | 38f0b29e6fc737756ae21a8c193a110876bc221c | <|skeleton|>
class FriendField:
"""Field for a friend. This will check the `from_account` and `to_account` values and will return the one that is not the current user. :param instance_serializer: serializer used to serialize the friend :param kwargs: additional arguments to pass to the `Field` constructor"""
d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FriendField:
"""Field for a friend. This will check the `from_account` and `to_account` values and will return the one that is not the current user. :param instance_serializer: serializer used to serialize the friend :param kwargs: additional arguments to pass to the `Field` constructor"""
def __init__(s... | the_stack_v2_python_sparse | backend/user/serializers.py | BenjaminSchubert/HEIG_VD_2016_PDG | train | 0 |
4e7359131ee5b830ecc832ac28de4bbb34d8e130 | [
"client = test_client.TestClient(context.node['baseurl'])\nlog_records = client.getLogRecords(context.TOKEN, datetime.datetime(1800, 1, 1), event='create')\nassert log_records.total == context.object_total",
"client = test_client.TestClient(context.node['baseurl'])\nlog_records = client.getLogRecords(context.TOKE... | <|body_start_0|>
client = test_client.TestClient(context.node['baseurl'])
log_records = client.getLogRecords(context.TOKEN, datetime.datetime(1800, 1, 1), event='create')
assert log_records.total == context.object_total
<|end_body_0|>
<|body_start_1|>
client = test_client.TestClient(con... | Test040GetLogRecords | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Test040GetLogRecords:
def test_010_create_events(self):
"""Event log contains the correct number of create events."""
<|body_0|>
def test_020_get_total_events(self):
"""Get total number of events."""
<|body_1|>
def xevent_log_contains_create_events(self)... | stack_v2_sparse_classes_36k_train_029859 | 2,896 | permissive | [
{
"docstring": "Event log contains the correct number of create events.",
"name": "test_010_create_events",
"signature": "def test_010_create_events(self)"
},
{
"docstring": "Get total number of events.",
"name": "test_020_get_total_events",
"signature": "def test_020_get_total_events(se... | 3 | stack_v2_sparse_classes_30k_train_010043 | Implement the Python class `Test040GetLogRecords` described below.
Class description:
Implement the Test040GetLogRecords class.
Method signatures and docstrings:
- def test_010_create_events(self): Event log contains the correct number of create events.
- def test_020_get_total_events(self): Get total number of event... | Implement the Python class `Test040GetLogRecords` described below.
Class description:
Implement the Test040GetLogRecords class.
Method signatures and docstrings:
- def test_010_create_events(self): Event log contains the correct number of create events.
- def test_020_get_total_events(self): Get total number of event... | d72a9461894d9be7d71178fb7310101b8ef9066a | <|skeleton|>
class Test040GetLogRecords:
def test_010_create_events(self):
"""Event log contains the correct number of create events."""
<|body_0|>
def test_020_get_total_events(self):
"""Get total number of events."""
<|body_1|>
def xevent_log_contains_create_events(self)... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Test040GetLogRecords:
def test_010_create_events(self):
"""Event log contains the correct number of create events."""
client = test_client.TestClient(context.node['baseurl'])
log_records = client.getLogRecords(context.TOKEN, datetime.datetime(1800, 1, 1), event='create')
assert... | the_stack_v2_python_sparse | test_utilities/src/d1_test/stress_tester/projects/_unit_test_bases_for_stress_tests/tier_1_mn_core_getlogrecords.py | DataONEorg/d1_python | train | 15 | |
dc8bf709c0bf2a6cd0d51a2fac2525abc58f1d1f | [
"v = 3.0 * np.sqrt(2) * self.eps * self.dw\nself.uext[0] = 0.5 * (1 + np.tanh((self.interval[0] - v * t) / (np.sqrt(2) * self.eps)))\nself.uext[-1] = 0.5 * (1 + np.tanh((self.interval[1] - v * t) / (np.sqrt(2) * self.eps)))\nself.uext[1:-1] = u[:]\nf = self.dtype_f(self.init)\nf.impl[:] = self.A.dot(self.uext)[1:-1... | <|body_start_0|>
v = 3.0 * np.sqrt(2) * self.eps * self.dw
self.uext[0] = 0.5 * (1 + np.tanh((self.interval[0] - v * t) / (np.sqrt(2) * self.eps)))
self.uext[-1] = 0.5 * (1 + np.tanh((self.interval[1] - v * t) / (np.sqrt(2) * self.eps)))
self.uext[1:-1] = u[:]
f = self.dtype_f(se... | Example implementing the Allen-Cahn equation in 1D with finite differences and inhomogeneous Dirichlet-BC, with driving force, 0-1 formulation (Bayreuth example), semi-implicit time-stepping Attributes ---------- A : scipy.diags Second-order FD discretization of the 1D laplace operator. dx : float Distance between two ... | allencahn_front_semiimplicit | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class allencahn_front_semiimplicit:
"""Example implementing the Allen-Cahn equation in 1D with finite differences and inhomogeneous Dirichlet-BC, with driving force, 0-1 formulation (Bayreuth example), semi-implicit time-stepping Attributes ---------- A : scipy.diags Second-order FD discretization of t... | stack_v2_sparse_classes_36k_train_029860 | 26,441 | permissive | [
{
"docstring": "Parameters ---------- u : dtype_u Current values of the numerical solution. t : float Current time of the numerical solution is computed. Returns ------- f : dtype_f The right-hand side of the problem.",
"name": "eval_f",
"signature": "def eval_f(self, u, t)"
},
{
"docstring": "S... | 2 | null | Implement the Python class `allencahn_front_semiimplicit` described below.
Class description:
Example implementing the Allen-Cahn equation in 1D with finite differences and inhomogeneous Dirichlet-BC, with driving force, 0-1 formulation (Bayreuth example), semi-implicit time-stepping Attributes ---------- A : scipy.di... | Implement the Python class `allencahn_front_semiimplicit` described below.
Class description:
Example implementing the Allen-Cahn equation in 1D with finite differences and inhomogeneous Dirichlet-BC, with driving force, 0-1 formulation (Bayreuth example), semi-implicit time-stepping Attributes ---------- A : scipy.di... | 1a51834bedffd4472e344bed28f4d766614b1537 | <|skeleton|>
class allencahn_front_semiimplicit:
"""Example implementing the Allen-Cahn equation in 1D with finite differences and inhomogeneous Dirichlet-BC, with driving force, 0-1 formulation (Bayreuth example), semi-implicit time-stepping Attributes ---------- A : scipy.diags Second-order FD discretization of t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class allencahn_front_semiimplicit:
"""Example implementing the Allen-Cahn equation in 1D with finite differences and inhomogeneous Dirichlet-BC, with driving force, 0-1 formulation (Bayreuth example), semi-implicit time-stepping Attributes ---------- A : scipy.diags Second-order FD discretization of the 1D laplace... | the_stack_v2_python_sparse | pySDC/implementations/problem_classes/AllenCahn_1D_FD.py | Parallel-in-Time/pySDC | train | 30 |
a3e8841245ad8fbd3b72cc134cc8810b782b138e | [
"self.num_critical_alerts = num_critical_alerts\nself.num_critical_alerts_categories = num_critical_alerts_categories\nself.num_data_service_alerts = num_data_service_alerts\nself.num_data_service_critical_alerts = num_data_service_critical_alerts\nself.num_data_service_info_alerts = num_data_service_info_alerts\ns... | <|body_start_0|>
self.num_critical_alerts = num_critical_alerts
self.num_critical_alerts_categories = num_critical_alerts_categories
self.num_data_service_alerts = num_data_service_alerts
self.num_data_service_critical_alerts = num_data_service_critical_alerts
self.num_data_servi... | Implementation of the 'ActiveAlertsStats' model. Specifies the active alert statistics details. Attributes: num_critical_alerts (long|int): Specifies the count of active critical Alerts excluding alerts that belong to other bucket. num_critical_alerts_categories (long|int): Specifies the count of active critical alerts... | ActiveAlertsStats | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ActiveAlertsStats:
"""Implementation of the 'ActiveAlertsStats' model. Specifies the active alert statistics details. Attributes: num_critical_alerts (long|int): Specifies the count of active critical Alerts excluding alerts that belong to other bucket. num_critical_alerts_categories (long|int): ... | stack_v2_sparse_classes_36k_train_029861 | 10,192 | permissive | [
{
"docstring": "Constructor for the ActiveAlertsStats class",
"name": "__init__",
"signature": "def __init__(self, num_critical_alerts=None, num_critical_alerts_categories=None, num_data_service_alerts=None, num_data_service_critical_alerts=None, num_data_service_info_alerts=None, num_data_service_warni... | 2 | null | Implement the Python class `ActiveAlertsStats` described below.
Class description:
Implementation of the 'ActiveAlertsStats' model. Specifies the active alert statistics details. Attributes: num_critical_alerts (long|int): Specifies the count of active critical Alerts excluding alerts that belong to other bucket. num_... | Implement the Python class `ActiveAlertsStats` described below.
Class description:
Implementation of the 'ActiveAlertsStats' model. Specifies the active alert statistics details. Attributes: num_critical_alerts (long|int): Specifies the count of active critical Alerts excluding alerts that belong to other bucket. num_... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class ActiveAlertsStats:
"""Implementation of the 'ActiveAlertsStats' model. Specifies the active alert statistics details. Attributes: num_critical_alerts (long|int): Specifies the count of active critical Alerts excluding alerts that belong to other bucket. num_critical_alerts_categories (long|int): ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ActiveAlertsStats:
"""Implementation of the 'ActiveAlertsStats' model. Specifies the active alert statistics details. Attributes: num_critical_alerts (long|int): Specifies the count of active critical Alerts excluding alerts that belong to other bucket. num_critical_alerts_categories (long|int): Specifies the... | the_stack_v2_python_sparse | cohesity_management_sdk/models/active_alerts_stats.py | cohesity/management-sdk-python | train | 24 |
d74ccc4fa9c99342a90721896edd07550d2a2735 | [
"dirs, files = default_storage.listdir(path)\nfilenames = []\nfor filename in files:\n if filename.endswith('csv'):\n filenames.append(filename)\nlogging.debug(f\"Found the following bucket files: {','.join(filenames)}\")\nreturn filenames",
"files = []\nfor filename in self.get_files_list():\n sis_t... | <|body_start_0|>
dirs, files = default_storage.listdir(path)
filenames = []
for filename in files:
if filename.endswith('csv'):
filenames.append(filename)
logging.debug(f"Found the following bucket files: {','.join(filenames)}")
return filenames
<|end_... | StorageDao | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StorageDao:
def get_files_list(self, path=''):
"""Returns list of file names at the given path. :param path: Path to list files at :type path: str"""
<|body_0|>
def get_latest_file(self):
"""Return latest RAD file in bucket"""
<|body_1|>
def download_fro... | stack_v2_sparse_classes_36k_train_029862 | 11,160 | permissive | [
{
"docstring": "Returns list of file names at the given path. :param path: Path to list files at :type path: str",
"name": "get_files_list",
"signature": "def get_files_list(self, path='')"
},
{
"docstring": "Return latest RAD file in bucket",
"name": "get_latest_file",
"signature": "def... | 3 | stack_v2_sparse_classes_30k_train_004323 | Implement the Python class `StorageDao` described below.
Class description:
Implement the StorageDao class.
Method signatures and docstrings:
- def get_files_list(self, path=''): Returns list of file names at the given path. :param path: Path to list files at :type path: str
- def get_latest_file(self): Return latest... | Implement the Python class `StorageDao` described below.
Class description:
Implement the StorageDao class.
Method signatures and docstrings:
- def get_files_list(self, path=''): Returns list of file names at the given path. :param path: Path to list files at :type path: str
- def get_latest_file(self): Return latest... | bb81bf9a729f0919c47750909045ddd7bbe4d990 | <|skeleton|>
class StorageDao:
def get_files_list(self, path=''):
"""Returns list of file names at the given path. :param path: Path to list files at :type path: str"""
<|body_0|>
def get_latest_file(self):
"""Return latest RAD file in bucket"""
<|body_1|>
def download_fro... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StorageDao:
def get_files_list(self, path=''):
"""Returns list of file names at the given path. :param path: Path to list files at :type path: str"""
dirs, files = default_storage.listdir(path)
filenames = []
for filename in files:
if filename.endswith('csv'):
... | the_stack_v2_python_sparse | retention_dashboard/dao/admin.py | uw-it-aca/retention-dashboard | train | 0 | |
0eb3423f2f00ffed3d61433f4323e621f4ddc6e0 | [
"super(Plato2, self).__init__()\nargs = self.setup_args()\nif args.num_layers == 24:\n n_head = 16\n hidden_size = 1024\nelif args.num_layers == 32:\n n_head = 32\n hidden_size = 2048\nelse:\n raise ValueError('The pre-trained model only support 24 or 32 layers, but received num_layers=%d.' % args.nu... | <|body_start_0|>
super(Plato2, self).__init__()
args = self.setup_args()
if args.num_layers == 24:
n_head = 16
hidden_size = 1024
elif args.num_layers == 32:
n_head = 32
hidden_size = 2048
else:
raise ValueError('The pre... | Plato2 | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Plato2:
def __init__(self):
"""initialize with the necessary elements"""
<|body_0|>
def setup_args(self):
"""Setup arguments."""
<|body_1|>
def generate(self, texts):
"""Get the robot responses of the input texts. Args: texts(list or str): If not... | stack_v2_sparse_classes_36k_train_029863 | 6,991 | permissive | [
{
"docstring": "initialize with the necessary elements",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Setup arguments.",
"name": "setup_args",
"signature": "def setup_args(self)"
},
{
"docstring": "Get the robot responses of the input texts. Args: text... | 5 | null | Implement the Python class `Plato2` described below.
Class description:
Implement the Plato2 class.
Method signatures and docstrings:
- def __init__(self): initialize with the necessary elements
- def setup_args(self): Setup arguments.
- def generate(self, texts): Get the robot responses of the input texts. Args: tex... | Implement the Python class `Plato2` described below.
Class description:
Implement the Plato2 class.
Method signatures and docstrings:
- def __init__(self): initialize with the necessary elements
- def setup_args(self): Setup arguments.
- def generate(self, texts): Get the robot responses of the input texts. Args: tex... | b402610a6f0b382a978e82473b541ea1fc6cf09a | <|skeleton|>
class Plato2:
def __init__(self):
"""initialize with the necessary elements"""
<|body_0|>
def setup_args(self):
"""Setup arguments."""
<|body_1|>
def generate(self, texts):
"""Get the robot responses of the input texts. Args: texts(list or str): If not... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Plato2:
def __init__(self):
"""initialize with the necessary elements"""
super(Plato2, self).__init__()
args = self.setup_args()
if args.num_layers == 24:
n_head = 16
hidden_size = 1024
elif args.num_layers == 32:
n_head = 32
... | the_stack_v2_python_sparse | modules/text/text_generation/plato2_en_large/module.py | PaddlePaddle/PaddleHub | train | 12,914 | |
64c2d34275e82de1920fa87b88c8f5db79128076 | [
"def driver(start, target, cnt):\n res = []\n if cnt == 0 and target > 0:\n res.append([])\n for i in range(start, len(nums)):\n subsets = driver(i + 1, target - nums[i], cnt - 1)\n for subset in subsets:\n subset.append(i)\n res.extend(subsets)\n return res\nres =... | <|body_start_0|>
def driver(start, target, cnt):
res = []
if cnt == 0 and target > 0:
res.append([])
for i in range(start, len(nums)):
subsets = driver(i + 1, target - nums[i], cnt - 1)
for subset in subsets:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def threeSumSmaller(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_0|>
def threeSumSmaller2(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_1|>
def threeSumSmallerTwoP... | stack_v2_sparse_classes_36k_train_029864 | 2,140 | no_license | [
{
"docstring": ":type nums: List[int] :type target: int :rtype: int",
"name": "threeSumSmaller",
"signature": "def threeSumSmaller(self, nums, target)"
},
{
"docstring": ":type nums: List[int] :type target: int :rtype: int",
"name": "threeSumSmaller2",
"signature": "def threeSumSmaller2(... | 3 | stack_v2_sparse_classes_30k_train_009964 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def threeSumSmaller(self, nums, target): :type nums: List[int] :type target: int :rtype: int
- def threeSumSmaller2(self, nums, target): :type nums: List[int] :type target: int :... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def threeSumSmaller(self, nums, target): :type nums: List[int] :type target: int :rtype: int
- def threeSumSmaller2(self, nums, target): :type nums: List[int] :type target: int :... | 11d6bf2ba7b50c07e048df37c4e05c8f46b92241 | <|skeleton|>
class Solution:
def threeSumSmaller(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_0|>
def threeSumSmaller2(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
<|body_1|>
def threeSumSmallerTwoP... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def threeSumSmaller(self, nums, target):
""":type nums: List[int] :type target: int :rtype: int"""
def driver(start, target, cnt):
res = []
if cnt == 0 and target > 0:
res.append([])
for i in range(start, len(nums)):
... | the_stack_v2_python_sparse | LeetCodes/Google/3Sum Smaller.py | chutianwen/LeetCodes | train | 0 | |
e0817766a0d19fdfe180f923a6272bf25f8c1b8d | [
"n_qubits = n_qubits or count_qubits(qubit_operator)\nn_hilbert = 2 ** n_qubits\nsuper(ParallelLinearQubitOperator, self).__init__(shape=(n_hilbert, n_hilbert), dtype=complex)\nself.qubit_operator = qubit_operator\nself.n_qubits = n_qubits\nself.options = options or LinearQubitOperatorOptions()\nself.qubit_operator... | <|body_start_0|>
n_qubits = n_qubits or count_qubits(qubit_operator)
n_hilbert = 2 ** n_qubits
super(ParallelLinearQubitOperator, self).__init__(shape=(n_hilbert, n_hilbert), dtype=complex)
self.qubit_operator = qubit_operator
self.n_qubits = n_qubits
self.options = optio... | A LinearOperator from a QubitOperator with multiple processors. | ParallelLinearQubitOperator | [
"LicenseRef-scancode-generic-cla",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParallelLinearQubitOperator:
"""A LinearOperator from a QubitOperator with multiple processors."""
def __init__(self, qubit_operator, n_qubits=None, options=None):
"""Args: qubit_operator(QubitOperator): A qubit operator to be applied on vectors. n_qubits(int): The total number of qu... | stack_v2_sparse_classes_36k_train_029865 | 8,329 | permissive | [
{
"docstring": "Args: qubit_operator(QubitOperator): A qubit operator to be applied on vectors. n_qubits(int): The total number of qubits options(LinearQubitOperatorOptions): Options for the LinearOperator.",
"name": "__init__",
"signature": "def __init__(self, qubit_operator, n_qubits=None, options=Non... | 2 | null | Implement the Python class `ParallelLinearQubitOperator` described below.
Class description:
A LinearOperator from a QubitOperator with multiple processors.
Method signatures and docstrings:
- def __init__(self, qubit_operator, n_qubits=None, options=None): Args: qubit_operator(QubitOperator): A qubit operator to be ... | Implement the Python class `ParallelLinearQubitOperator` described below.
Class description:
A LinearOperator from a QubitOperator with multiple processors.
Method signatures and docstrings:
- def __init__(self, qubit_operator, n_qubits=None, options=None): Args: qubit_operator(QubitOperator): A qubit operator to be ... | 788481753c798a72c5cb3aa9f2aa9da3ce3190b0 | <|skeleton|>
class ParallelLinearQubitOperator:
"""A LinearOperator from a QubitOperator with multiple processors."""
def __init__(self, qubit_operator, n_qubits=None, options=None):
"""Args: qubit_operator(QubitOperator): A qubit operator to be applied on vectors. n_qubits(int): The total number of qu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ParallelLinearQubitOperator:
"""A LinearOperator from a QubitOperator with multiple processors."""
def __init__(self, qubit_operator, n_qubits=None, options=None):
"""Args: qubit_operator(QubitOperator): A qubit operator to be applied on vectors. n_qubits(int): The total number of qubits options(... | the_stack_v2_python_sparse | src/openfermion/linalg/linear_qubit_operator.py | quantumlib/OpenFermion | train | 1,481 |
9a24c9335ef51e078bb970aa7705783607e06e86 | [
"Editeur.__init__(self, pere, objet, attribut)\nself.ajouter_option('n', self.opt_creer_etat)\nself.ajouter_option('d', self.opt_supprimer_etat)",
"prototype = self.objet\nmsg = '| |tit|' + 'Edition des états de {}'.format(prototype).ljust(76)\nmsg += '|ff||\\n' + self.opts.separateur + '\\n'\nmsg += 'Options :\\... | <|body_start_0|>
Editeur.__init__(self, pere, objet, attribut)
self.ajouter_option('n', self.opt_creer_etat)
self.ajouter_option('d', self.opt_supprimer_etat)
<|end_body_0|>
<|body_start_1|>
prototype = self.objet
msg = '| |tit|' + 'Edition des états de {}'.format(prototype).lju... | Contexte-éditeur d'édition des états. | EdtEtats | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EdtEtats:
"""Contexte-éditeur d'édition des états."""
def __init__(self, pere, objet=None, attribut=None):
"""Constructeur de l'éditeur"""
<|body_0|>
def accueil(self):
"""Message d'accueil du contexte"""
<|body_1|>
def opt_creer_etat(self, arguments... | stack_v2_sparse_classes_36k_train_029866 | 4,367 | permissive | [
{
"docstring": "Constructeur de l'éditeur",
"name": "__init__",
"signature": "def __init__(self, pere, objet=None, attribut=None)"
},
{
"docstring": "Message d'accueil du contexte",
"name": "accueil",
"signature": "def accueil(self)"
},
{
"docstring": "Crée un nouvel état. Syntax... | 5 | stack_v2_sparse_classes_30k_train_014590 | Implement the Python class `EdtEtats` described below.
Class description:
Contexte-éditeur d'édition des états.
Method signatures and docstrings:
- def __init__(self, pere, objet=None, attribut=None): Constructeur de l'éditeur
- def accueil(self): Message d'accueil du contexte
- def opt_creer_etat(self, arguments): C... | Implement the Python class `EdtEtats` described below.
Class description:
Contexte-éditeur d'édition des états.
Method signatures and docstrings:
- def __init__(self, pere, objet=None, attribut=None): Constructeur de l'éditeur
- def accueil(self): Message d'accueil du contexte
- def opt_creer_etat(self, arguments): C... | 7e93bff08cdf891352efba587e89c40f3b4a2301 | <|skeleton|>
class EdtEtats:
"""Contexte-éditeur d'édition des états."""
def __init__(self, pere, objet=None, attribut=None):
"""Constructeur de l'éditeur"""
<|body_0|>
def accueil(self):
"""Message d'accueil du contexte"""
<|body_1|>
def opt_creer_etat(self, arguments... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EdtEtats:
"""Contexte-éditeur d'édition des états."""
def __init__(self, pere, objet=None, attribut=None):
"""Constructeur de l'éditeur"""
Editeur.__init__(self, pere, objet, attribut)
self.ajouter_option('n', self.opt_creer_etat)
self.ajouter_option('d', self.opt_supprime... | the_stack_v2_python_sparse | src/primaires/salle/editeurs/sbedit/edt_etats.py | vincent-lg/tsunami | train | 5 |
274d4086461a02d0f7413b391359524619e32c4c | [
"if not root:\n return []\nstack = []\nres = []\ncur = root\nstack.append(cur)\nwhile stack:\n cur = stack.pop()\n res.append(cur.val)\n if cur.right:\n stack.append(cur.right)\n if cur.left:\n stack.append(cur.left)\nreturn res",
"if root is None:\n return []\nres = []\n\ndef trav... | <|body_start_0|>
if not root:
return []
stack = []
res = []
cur = root
stack.append(cur)
while stack:
cur = stack.pop()
res.append(cur.val)
if cur.right:
stack.append(cur.right)
if cur.left:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def preorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int] 算法：迭代 基本思想： 前序遍历顺序：中左右 所以先将root节点入栈，然后出栈并保存， 再将其右节点入栈，左节点入栈，然后依次pop并保存"""
<|body_0|>
def preorderTraversal1(self, root):
""":type root: TreeNode :rtype: List[int] 算法：递归"""
... | stack_v2_sparse_classes_36k_train_029867 | 1,705 | no_license | [
{
"docstring": ":type root: TreeNode :rtype: List[int] 算法：迭代 基本思想： 前序遍历顺序：中左右 所以先将root节点入栈，然后出栈并保存， 再将其右节点入栈，左节点入栈，然后依次pop并保存",
"name": "preorderTraversal",
"signature": "def preorderTraversal(self, root)"
},
{
"docstring": ":type root: TreeNode :rtype: List[int] 算法：递归",
"name": "preorderTra... | 2 | stack_v2_sparse_classes_30k_train_017972 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preorderTraversal(self, root): :type root: TreeNode :rtype: List[int] 算法：迭代 基本思想： 前序遍历顺序：中左右 所以先将root节点入栈，然后出栈并保存， 再将其右节点入栈，左节点入栈，然后依次pop并保存
- def preorderTraversal1(self, ro... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def preorderTraversal(self, root): :type root: TreeNode :rtype: List[int] 算法：迭代 基本思想： 前序遍历顺序：中左右 所以先将root节点入栈，然后出栈并保存， 再将其右节点入栈，左节点入栈，然后依次pop并保存
- def preorderTraversal1(self, ro... | 6e18c5d257840489cc3fb1079ae3804c743982a4 | <|skeleton|>
class Solution:
def preorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int] 算法：迭代 基本思想： 前序遍历顺序：中左右 所以先将root节点入栈，然后出栈并保存， 再将其右节点入栈，左节点入栈，然后依次pop并保存"""
<|body_0|>
def preorderTraversal1(self, root):
""":type root: TreeNode :rtype: List[int] 算法：递归"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def preorderTraversal(self, root):
""":type root: TreeNode :rtype: List[int] 算法：迭代 基本思想： 前序遍历顺序：中左右 所以先将root节点入栈，然后出栈并保存， 再将其右节点入栈，左节点入栈，然后依次pop并保存"""
if not root:
return []
stack = []
res = []
cur = root
stack.append(cur)
while sta... | the_stack_v2_python_sparse | out/production/leetcode/144.二叉树的前序遍历.py | yangyuxiang1996/leetcode | train | 0 | |
0ae879cbc727ebe8f4ab547c54b9fbe2fa08f7bf | [
"stack_name = data_utils.rand_name('heat')\ntemplate = self.read_template('random_string')\nenvironment = {'parameters': {'random_length': 20}}\nstack_identifier = self.create_stack(stack_name, template, environment=environment)\nself.client.wait_for_stack_status(stack_identifier, 'CREATE_COMPLETE')\nrandom_len = s... | <|body_start_0|>
stack_name = data_utils.rand_name('heat')
template = self.read_template('random_string')
environment = {'parameters': {'random_length': 20}}
stack_identifier = self.create_stack(stack_name, template, environment=environment)
self.client.wait_for_stack_status(stac... | StackEnvironmentTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class StackEnvironmentTest:
def test_environment_parameter(self):
"""Test passing a stack parameter via the environment."""
<|body_0|>
def test_environment_provider_resource(self):
"""Test passing resource_registry defining a provider resource."""
<|body_1|>
d... | stack_v2_sparse_classes_36k_train_029868 | 3,986 | permissive | [
{
"docstring": "Test passing a stack parameter via the environment.",
"name": "test_environment_parameter",
"signature": "def test_environment_parameter(self)"
},
{
"docstring": "Test passing resource_registry defining a provider resource.",
"name": "test_environment_provider_resource",
... | 3 | null | Implement the Python class `StackEnvironmentTest` described below.
Class description:
Implement the StackEnvironmentTest class.
Method signatures and docstrings:
- def test_environment_parameter(self): Test passing a stack parameter via the environment.
- def test_environment_provider_resource(self): Test passing res... | Implement the Python class `StackEnvironmentTest` described below.
Class description:
Implement the StackEnvironmentTest class.
Method signatures and docstrings:
- def test_environment_parameter(self): Test passing a stack parameter via the environment.
- def test_environment_provider_resource(self): Test passing res... | ae7e033fef80f2a4728a13bba18123f6fe32839a | <|skeleton|>
class StackEnvironmentTest:
def test_environment_parameter(self):
"""Test passing a stack parameter via the environment."""
<|body_0|>
def test_environment_provider_resource(self):
"""Test passing resource_registry defining a provider resource."""
<|body_1|>
d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class StackEnvironmentTest:
def test_environment_parameter(self):
"""Test passing a stack parameter via the environment."""
stack_name = data_utils.rand_name('heat')
template = self.read_template('random_string')
environment = {'parameters': {'random_length': 20}}
stack_ident... | the_stack_v2_python_sparse | tempest/api/orchestration/stacks/test_environment.py | Mirantis/tempest | train | 3 | |
fbba8018f1d961854ca82b15ad62cfc3088ff181 | [
"getpermsessages = getpermsessage()\nif getpermsessages:\n self.uri = getpermsessages.get('zabbixurl', '')\n self.zabbixuser = getpermsessages.get('zabbixuser', '')\n self.zabbixpassword = encrypt_and_decode().decrypted_text(getpermsessages.get('zabbixpassword', ''))\nif zabbixurl:\n self.uri = zabbixur... | <|body_start_0|>
getpermsessages = getpermsessage()
if getpermsessages:
self.uri = getpermsessages.get('zabbixurl', '')
self.zabbixuser = getpermsessages.get('zabbixuser', '')
self.zabbixpassword = encrypt_and_decode().decrypted_text(getpermsessages.get('zabbixpasswor... | Zabbix API类 | ZabbixApi | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ZabbixApi:
"""Zabbix API类"""
def __init__(self, encode='utf-8', zabbixurl=None, zabbixuser=None, zabbixpassword=None):
"""构造函数 :param request_id:JSON-RPC请求标识符"""
<|body_0|>
def call(self, method, params, AUTH=None):
"""ZabbixAPI请求程序 :param method: Zabbix API方法名称 ... | stack_v2_sparse_classes_36k_train_029869 | 21,075 | no_license | [
{
"docstring": "构造函数 :param request_id:JSON-RPC请求标识符",
"name": "__init__",
"signature": "def __init__(self, encode='utf-8', zabbixurl=None, zabbixuser=None, zabbixpassword=None)"
},
{
"docstring": "ZabbixAPI请求程序 :param method: Zabbix API方法名称 :param params: Zabbix API方法参数 :param through_authentic... | 3 | stack_v2_sparse_classes_30k_train_017372 | Implement the Python class `ZabbixApi` described below.
Class description:
Zabbix API类
Method signatures and docstrings:
- def __init__(self, encode='utf-8', zabbixurl=None, zabbixuser=None, zabbixpassword=None): 构造函数 :param request_id:JSON-RPC请求标识符
- def call(self, method, params, AUTH=None): ZabbixAPI请求程序 :param me... | Implement the Python class `ZabbixApi` described below.
Class description:
Zabbix API类
Method signatures and docstrings:
- def __init__(self, encode='utf-8', zabbixurl=None, zabbixuser=None, zabbixpassword=None): 构造函数 :param request_id:JSON-RPC请求标识符
- def call(self, method, params, AUTH=None): ZabbixAPI请求程序 :param me... | 5552af663ed2c668a16b9c687c2a50ed02595a01 | <|skeleton|>
class ZabbixApi:
"""Zabbix API类"""
def __init__(self, encode='utf-8', zabbixurl=None, zabbixuser=None, zabbixpassword=None):
"""构造函数 :param request_id:JSON-RPC请求标识符"""
<|body_0|>
def call(self, method, params, AUTH=None):
"""ZabbixAPI请求程序 :param method: Zabbix API方法名称 ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ZabbixApi:
"""Zabbix API类"""
def __init__(self, encode='utf-8', zabbixurl=None, zabbixuser=None, zabbixpassword=None):
"""构造函数 :param request_id:JSON-RPC请求标识符"""
getpermsessages = getpermsessage()
if getpermsessages:
self.uri = getpermsessages.get('zabbixurl', '')
... | the_stack_v2_python_sparse | ADapi/zapi.py | openitsystem/itops | train | 144 |
d0076b53aa907cac14adbf074e95388152652485 | [
"super().__init__(z3_mask=z3_mask)\nself.edge_length = edge_length\nself.window_size = window_size",
"z3_mask, result = self._optimize()\nmask = np.zeros((self.edge_length, self.edge_length))\nnum_masks_along_row = math.ceil(self.edge_length / self.window_size)\nfor row in range(self.edge_length):\n for column... | <|body_start_0|>
super().__init__(z3_mask=z3_mask)
self.edge_length = edge_length
self.window_size = window_size
<|end_body_0|>
<|body_start_1|>
z3_mask, result = self._optimize()
mask = np.zeros((self.edge_length, self.edge_length))
num_masks_along_row = math.ceil(self.... | Creates a solver by using z3 solver. Attributes: edge_length: int, side length of the 2D array (image) whose pixels are to be masked. window_size: int, side length of the square mask. | ImageOptimizer | [
"Apache-2.0",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ImageOptimizer:
"""Creates a solver by using z3 solver. Attributes: edge_length: int, side length of the 2D array (image) whose pixels are to be masked. window_size: int, side length of the square mask."""
def __init__(self, z3_mask, window_size, edge_length):
"""Initializer. Args: z... | stack_v2_sparse_classes_36k_train_029870 | 39,568 | permissive | [
{
"docstring": "Initializer. Args: z3_mask: list, contains mask bits as z3 vars. window_size: int, side length of the square mask. edge_length: int, side length of the 2D array (image) whose pixels are to be masked.",
"name": "__init__",
"signature": "def __init__(self, z3_mask, window_size, edge_length... | 2 | stack_v2_sparse_classes_30k_val_001145 | Implement the Python class `ImageOptimizer` described below.
Class description:
Creates a solver by using z3 solver. Attributes: edge_length: int, side length of the 2D array (image) whose pixels are to be masked. window_size: int, side length of the square mask.
Method signatures and docstrings:
- def __init__(self,... | Implement the Python class `ImageOptimizer` described below.
Class description:
Creates a solver by using z3 solver. Attributes: edge_length: int, side length of the 2D array (image) whose pixels are to be masked. window_size: int, side length of the square mask.
Method signatures and docstrings:
- def __init__(self,... | 5573d9c5822f4e866b6692769963ae819cb3f10d | <|skeleton|>
class ImageOptimizer:
"""Creates a solver by using z3 solver. Attributes: edge_length: int, side length of the 2D array (image) whose pixels are to be masked. window_size: int, side length of the square mask."""
def __init__(self, z3_mask, window_size, edge_length):
"""Initializer. Args: z... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ImageOptimizer:
"""Creates a solver by using z3 solver. Attributes: edge_length: int, side length of the 2D array (image) whose pixels are to be masked. window_size: int, side length of the square mask."""
def __init__(self, z3_mask, window_size, edge_length):
"""Initializer. Args: z3_mask: list,... | the_stack_v2_python_sparse | smug_saliency/utils.py | Jimmy-INL/google-research | train | 1 |
ff6878f3ed141a0b8bc18682be39bbe98d4f8cb4 | [
"self.sync_data = QboSyncData.get_by_id(org_uid) or QboSyncData(id=org_uid, stage_index=0)\nself.stage = STAGES[self.sync_data.stage_index](org_uid)\nlogging.info('running stage {}: {}'.format(self.sync_data.stage_index, type(self.stage).__name__))",
"stage_complete, next_payload = self.stage.next(payload)\nif st... | <|body_start_0|>
self.sync_data = QboSyncData.get_by_id(org_uid) or QboSyncData(id=org_uid, stage_index=0)
self.stage = STAGES[self.sync_data.stage_index](org_uid)
logging.info('running stage {}: {}'.format(self.sync_data.stage_index, type(self.stage).__name__))
<|end_body_0|>
<|body_start_1|>
... | Sync management class for a QBO org. This class gets repeatedly instantiated (with the org_uid) by the adapter, and its next method gets called. This class calls QBO APIs, stores the items retrieved via call to sync_utils, and does the bookkeeping so it knows what API to call next when the next method is called by the ... | QboSyncState | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QboSyncState:
"""Sync management class for a QBO org. This class gets repeatedly instantiated (with the org_uid) by the adapter, and its next method gets called. This class calls QBO APIs, stores the items retrieved via call to sync_utils, and does the bookkeeping so it knows what API to call nex... | stack_v2_sparse_classes_36k_train_029871 | 2,380 | no_license | [
{
"docstring": "Class initialiser. Retrieves stage of the sync which is in progress. Args: org_uid(str): org identifier",
"name": "__init__",
"signature": "def __init__(self, org_uid)"
},
{
"docstring": "Function which gets repeatedly called by the adapter. Delegates the call to the appropriate ... | 2 | stack_v2_sparse_classes_30k_val_000129 | Implement the Python class `QboSyncState` described below.
Class description:
Sync management class for a QBO org. This class gets repeatedly instantiated (with the org_uid) by the adapter, and its next method gets called. This class calls QBO APIs, stores the items retrieved via call to sync_utils, and does the bookk... | Implement the Python class `QboSyncState` described below.
Class description:
Sync management class for a QBO org. This class gets repeatedly instantiated (with the org_uid) by the adapter, and its next method gets called. This class calls QBO APIs, stores the items retrieved via call to sync_utils, and does the bookk... | eeb4b2e879a5cb2492d4511d05aa5047d56892ad | <|skeleton|>
class QboSyncState:
"""Sync management class for a QBO org. This class gets repeatedly instantiated (with the org_uid) by the adapter, and its next method gets called. This class calls QBO APIs, stores the items retrieved via call to sync_utils, and does the bookkeeping so it knows what API to call nex... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QboSyncState:
"""Sync management class for a QBO org. This class gets repeatedly instantiated (with the org_uid) by the adapter, and its next method gets called. This class calls QBO APIs, stores the items retrieved via call to sync_utils, and does the bookkeeping so it knows what API to call next when the ne... | the_stack_v2_python_sparse | app/sync_states/qbo/sync_state.py | SoulMen007/acuit-gl-ingester-zuora | train | 0 |
d4c039cd805d97c83472227e72dbae3b0861883e | [
"username = username if username is not None else self.normalize_email(email)\nuser = self.model(username=username, email=self.normalize_email(email))\nuser.set_password(password)\nuser.save(using=self._db)\nreturn user",
"user = self.create_user(username=email, email=email, password=password)\nuser.is_admin = Tr... | <|body_start_0|>
username = username if username is not None else self.normalize_email(email)
user = self.model(username=username, email=self.normalize_email(email))
user.set_password(password)
user.save(using=self._db)
return user
<|end_body_0|>
<|body_start_1|>
user = ... | MyUserManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MyUserManager:
def create_user(self, email='', password=None, username=None):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, email, password):
"""Creates and saves a superuser with the given emai... | stack_v2_sparse_classes_36k_train_029872 | 3,480 | no_license | [
{
"docstring": "Creates and saves a User with the given email, date of birth and password.",
"name": "create_user",
"signature": "def create_user(self, email='', password=None, username=None)"
},
{
"docstring": "Creates and saves a superuser with the given email, date of birth and password.",
... | 2 | stack_v2_sparse_classes_30k_train_019443 | Implement the Python class `MyUserManager` described below.
Class description:
Implement the MyUserManager class.
Method signatures and docstrings:
- def create_user(self, email='', password=None, username=None): Creates and saves a User with the given email, date of birth and password.
- def create_superuser(self, e... | Implement the Python class `MyUserManager` described below.
Class description:
Implement the MyUserManager class.
Method signatures and docstrings:
- def create_user(self, email='', password=None, username=None): Creates and saves a User with the given email, date of birth and password.
- def create_superuser(self, e... | 3fd9d8e7ece11848ff5026845dbfa41d2a017270 | <|skeleton|>
class MyUserManager:
def create_user(self, email='', password=None, username=None):
"""Creates and saves a User with the given email, date of birth and password."""
<|body_0|>
def create_superuser(self, email, password):
"""Creates and saves a superuser with the given emai... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MyUserManager:
def create_user(self, email='', password=None, username=None):
"""Creates and saves a User with the given email, date of birth and password."""
username = username if username is not None else self.normalize_email(email)
user = self.model(username=username, email=self.no... | the_stack_v2_python_sparse | users/models.py | fabiogelbcke/direitoemtela | train | 1 | |
cbb24778f2380ac7ebddb317b14761a8b48f67e1 | [
"super(OneLayerNN, self).__init__()\nself.n_in = n_in\nself.hidden = nn.Linear(n_in, 1)\nself.dropout = nn.Dropout(dropout)\nself.relu = nn.ReLU()",
"y = x.view(-1, self.n_in)\ny = self.hidden(y)\ny = self.dropout(y)\ny = self.relu(y)\nreturn y"
] | <|body_start_0|>
super(OneLayerNN, self).__init__()
self.n_in = n_in
self.hidden = nn.Linear(n_in, 1)
self.dropout = nn.Dropout(dropout)
self.relu = nn.ReLU()
<|end_body_0|>
<|body_start_1|>
y = x.view(-1, self.n_in)
y = self.hidden(y)
y = self.dropout(y)... | OneLayerNN | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OneLayerNN:
def __init__(self, n_in, n_h=1, dropout=0.0):
"""FIXME! briefly describe function :param n_in: :param n_h: :param n_layers: :param dropout: :returns: :rtype:"""
<|body_0|>
def forward(self, x):
"""FIXME! briefly describe function :param x: :returns: :rtyp... | stack_v2_sparse_classes_36k_train_029873 | 1,740 | permissive | [
{
"docstring": "FIXME! briefly describe function :param n_in: :param n_h: :param n_layers: :param dropout: :returns: :rtype:",
"name": "__init__",
"signature": "def __init__(self, n_in, n_h=1, dropout=0.0)"
},
{
"docstring": "FIXME! briefly describe function :param x: :returns: :rtype:",
"na... | 2 | stack_v2_sparse_classes_30k_train_015930 | Implement the Python class `OneLayerNN` described below.
Class description:
Implement the OneLayerNN class.
Method signatures and docstrings:
- def __init__(self, n_in, n_h=1, dropout=0.0): FIXME! briefly describe function :param n_in: :param n_h: :param n_layers: :param dropout: :returns: :rtype:
- def forward(self,... | Implement the Python class `OneLayerNN` described below.
Class description:
Implement the OneLayerNN class.
Method signatures and docstrings:
- def __init__(self, n_in, n_h=1, dropout=0.0): FIXME! briefly describe function :param n_in: :param n_h: :param n_layers: :param dropout: :returns: :rtype:
- def forward(self,... | fc3fd121fbffb630e3652bacdc74d1b1bddab50e | <|skeleton|>
class OneLayerNN:
def __init__(self, n_in, n_h=1, dropout=0.0):
"""FIXME! briefly describe function :param n_in: :param n_h: :param n_layers: :param dropout: :returns: :rtype:"""
<|body_0|>
def forward(self, x):
"""FIXME! briefly describe function :param x: :returns: :rtyp... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OneLayerNN:
def __init__(self, n_in, n_h=1, dropout=0.0):
"""FIXME! briefly describe function :param n_in: :param n_h: :param n_layers: :param dropout: :returns: :rtype:"""
super(OneLayerNN, self).__init__()
self.n_in = n_in
self.hidden = nn.Linear(n_in, 1)
self.dropout... | the_stack_v2_python_sparse | src/classicalgsg/nn_models/models.py | kyrarivest/ACRES_REU_Project_2021 | train | 0 | |
aeb07c5d93da7b5207309c512f4625c85e24e871 | [
"self.variance.gradient = gradients[0]\nself.wavelengths.gradient = gradients[1]\nself.lengthscales.gradient = gradients[2]",
"N = 7\nw0 = 2 * np.pi / self.wavelengths\nlengthscales = 2 * self.lengthscales\n[q2, dq2l] = seriescoeff(N, lengthscales, self.variance)\ndq2l = 2 * dq2l\nif np.any(np.isfinite(q2) == Fal... | <|body_start_0|>
self.variance.gradient = gradients[0]
self.wavelengths.gradient = gradients[1]
self.lengthscales.gradient = gradients[2]
<|end_body_0|>
<|body_start_1|>
N = 7
w0 = 2 * np.pi / self.wavelengths
lengthscales = 2 * self.lengthscales
[q2, dq2l] = ser... | Class provide extra functionality to transfer this covariance function into SDE form. Standard Periodic kernel: .. math:: k(x,y) = heta_1 \\exp \\left[ - rac{1}{2} {}\\sum_{i=1}^{input\\_dim} \\left( rac{\\sin( rac{\\pi}{\\lambda_i} (x_i - y_i) )}{l_i} ight)^2 ight] } | sde_StdPeriodic | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class sde_StdPeriodic:
"""Class provide extra functionality to transfer this covariance function into SDE form. Standard Periodic kernel: .. math:: k(x,y) = heta_1 \\exp \\left[ - rac{1}{2} {}\\sum_{i=1}^{input\\_dim} \\left( rac{\\sin( rac{\\pi}{\\lambda_i} (x_i - y_i) )}{l_i} ight)^2 ight] }"""
... | stack_v2_sparse_classes_36k_train_029874 | 6,203 | permissive | [
{
"docstring": "Update gradient in the order in which parameters are represented in the kernel",
"name": "sde_update_gradient_full",
"signature": "def sde_update_gradient_full(self, gradients)"
},
{
"docstring": "Return the state space representation of the covariance. ! Note: one must constrain... | 2 | stack_v2_sparse_classes_30k_train_010692 | Implement the Python class `sde_StdPeriodic` described below.
Class description:
Class provide extra functionality to transfer this covariance function into SDE form. Standard Periodic kernel: .. math:: k(x,y) = heta_1 \\exp \\left[ - rac{1}{2} {}\\sum_{i=1}^{input\\_dim} \\left( rac{\\sin( rac{\\pi}{\\lambda_i} (x_i ... | Implement the Python class `sde_StdPeriodic` described below.
Class description:
Class provide extra functionality to transfer this covariance function into SDE form. Standard Periodic kernel: .. math:: k(x,y) = heta_1 \\exp \\left[ - rac{1}{2} {}\\sum_{i=1}^{input\\_dim} \\left( rac{\\sin( rac{\\pi}{\\lambda_i} (x_i ... | 4fb8af1d51e74e3cf3bee5dabd641857b8cf8100 | <|skeleton|>
class sde_StdPeriodic:
"""Class provide extra functionality to transfer this covariance function into SDE form. Standard Periodic kernel: .. math:: k(x,y) = heta_1 \\exp \\left[ - rac{1}{2} {}\\sum_{i=1}^{input\\_dim} \\left( rac{\\sin( rac{\\pi}{\\lambda_i} (x_i - y_i) )}{l_i} ight)^2 ight] }"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class sde_StdPeriodic:
"""Class provide extra functionality to transfer this covariance function into SDE form. Standard Periodic kernel: .. math:: k(x,y) = heta_1 \\exp \\left[ - rac{1}{2} {}\\sum_{i=1}^{input\\_dim} \\left( rac{\\sin( rac{\\pi}{\\lambda_i} (x_i - y_i) )}{l_i} ight)^2 ight] }"""
def sde_updat... | the_stack_v2_python_sparse | bopl/aux_software/GPy/kern/_src/sde_standard_periodic.py | RaulAstudillo06/BOPL | train | 3 |
456fe908a6e60f51a0dd4cd89d9186e91d668309 | [
"intervals.append(newInterval)\nintervals.sort(key=lambda x: x.start)\nans = []\nfor i in range(len(intervals)):\n if ans == []:\n ans.append(intervals[i])\n elif ans[-1].start <= intervals[i].start <= ans[-1].end:\n ans[-1].end = max(ans[-1].end, intervals[i].end)\n else:\n ans.append... | <|body_start_0|>
intervals.append(newInterval)
intervals.sort(key=lambda x: x.start)
ans = []
for i in range(len(intervals)):
if ans == []:
ans.append(intervals[i])
elif ans[-1].start <= intervals[i].start <= ans[-1].end:
ans[-1].en... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def insert(self, intervals, newInterval):
""":type intervals: List[Interval] :type newInterval: Interval :rtype: List[Interval]"""
<|body_0|>
def insert_no_class(self, intervals, newInterval):
""":type intervals: List[Interval] :type newInterval: Interval :... | stack_v2_sparse_classes_36k_train_029875 | 3,075 | no_license | [
{
"docstring": ":type intervals: List[Interval] :type newInterval: Interval :rtype: List[Interval]",
"name": "insert",
"signature": "def insert(self, intervals, newInterval)"
},
{
"docstring": ":type intervals: List[Interval] :type newInterval: Interval :rtype: List[Interval]",
"name": "inse... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def insert(self, intervals, newInterval): :type intervals: List[Interval] :type newInterval: Interval :rtype: List[Interval]
- def insert_no_class(self, intervals, newInterval): ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def insert(self, intervals, newInterval): :type intervals: List[Interval] :type newInterval: Interval :rtype: List[Interval]
- def insert_no_class(self, intervals, newInterval): ... | 2d5fa4cd696d5035ea8859befeadc5cc436959c9 | <|skeleton|>
class Solution:
def insert(self, intervals, newInterval):
""":type intervals: List[Interval] :type newInterval: Interval :rtype: List[Interval]"""
<|body_0|>
def insert_no_class(self, intervals, newInterval):
""":type intervals: List[Interval] :type newInterval: Interval :... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def insert(self, intervals, newInterval):
""":type intervals: List[Interval] :type newInterval: Interval :rtype: List[Interval]"""
intervals.append(newInterval)
intervals.sort(key=lambda x: x.start)
ans = []
for i in range(len(intervals)):
if ans =... | the_stack_v2_python_sparse | SourceCode/Python/Problem/00057.Insert Interval.py | roger6blog/LeetCode | train | 0 | |
57b9fc03cd07705e7a03f717af91c5c3a89a16a1 | [
"self.delimiter = delimiter\nself.exclude_cols = exclude_cols\nself.fieldnames = fieldnames",
"with open(file, 'r') as f:\n reader = csv.DictReader(f, delimiter=self.delimiter, fieldnames=self.fieldnames)\n ncols = np.arange(len(reader.fieldnames))\n include_cols = np.delete(ncols, self.exclude_cols)\n ... | <|body_start_0|>
self.delimiter = delimiter
self.exclude_cols = exclude_cols
self.fieldnames = fieldnames
<|end_body_0|>
<|body_start_1|>
with open(file, 'r') as f:
reader = csv.DictReader(f, delimiter=self.delimiter, fieldnames=self.fieldnames)
ncols = np.arange... | FileReader | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FileReader:
def __init__(self, delimiter: str=',', exclude_cols: list=[], fieldnames: list=None):
"""Initialize object class to read a file. Args: delimiter (str): Delimiter used in the file (default `,`). exclude_cols (list): Exclude column in the file (default `None`). fieldnames (list... | stack_v2_sparse_classes_36k_train_029876 | 1,550 | permissive | [
{
"docstring": "Initialize object class to read a file. Args: delimiter (str): Delimiter used in the file (default `,`). exclude_cols (list): Exclude column in the file (default `None`). fieldnames (list): Names of the column in the file (default `None`).",
"name": "__init__",
"signature": "def __init__... | 2 | stack_v2_sparse_classes_30k_train_021169 | Implement the Python class `FileReader` described below.
Class description:
Implement the FileReader class.
Method signatures and docstrings:
- def __init__(self, delimiter: str=',', exclude_cols: list=[], fieldnames: list=None): Initialize object class to read a file. Args: delimiter (str): Delimiter used in the fil... | Implement the Python class `FileReader` described below.
Class description:
Implement the FileReader class.
Method signatures and docstrings:
- def __init__(self, delimiter: str=',', exclude_cols: list=[], fieldnames: list=None): Initialize object class to read a file. Args: delimiter (str): Delimiter used in the fil... | 29657c0b0f3952dd2e817bdfe8253f76800c2342 | <|skeleton|>
class FileReader:
def __init__(self, delimiter: str=',', exclude_cols: list=[], fieldnames: list=None):
"""Initialize object class to read a file. Args: delimiter (str): Delimiter used in the file (default `,`). exclude_cols (list): Exclude column in the file (default `None`). fieldnames (list... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FileReader:
def __init__(self, delimiter: str=',', exclude_cols: list=[], fieldnames: list=None):
"""Initialize object class to read a file. Args: delimiter (str): Delimiter used in the file (default `,`). exclude_cols (list): Exclude column in the file (default `None`). fieldnames (list): Names of th... | the_stack_v2_python_sparse | end2you/data_generator/file_reader.py | end2you/end2you | train | 101 | |
8ebeb0f1da1bd23a06aef38c935911eeae9e4654 | [
"if not root:\n return True\nreturn self.search_helper(root.left, root.right)",
"if not t1 and (not t2):\n return True\nif not t1 or not t2:\n return False\nif t1.val != t2.val:\n return False\nreturn self.search_helper(t1.left, t2.right) and self.search_helper(t1.right, t2.left)",
"queue = []\nqueu... | <|body_start_0|>
if not root:
return True
return self.search_helper(root.left, root.right)
<|end_body_0|>
<|body_start_1|>
if not t1 and (not t2):
return True
if not t1 or not t2:
return False
if t1.val != t2.val:
return False
... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def is_symmetric(self, root: TreeNode) -> bool:
"""判断两棵树是否相同 Args: root: 根节点 Returns: 布尔值"""
<|body_0|>
def search_helper(self, t1: TreeNode, t2: TreeNode) -> bool:
"""判断是否是对称二叉树 Args: t1: 二叉树t1 t2: 二叉树t2 Returns: 布尔值"""
<|body_1|>
def is_symme... | stack_v2_sparse_classes_36k_train_029877 | 2,784 | permissive | [
{
"docstring": "判断两棵树是否相同 Args: root: 根节点 Returns: 布尔值",
"name": "is_symmetric",
"signature": "def is_symmetric(self, root: TreeNode) -> bool"
},
{
"docstring": "判断是否是对称二叉树 Args: t1: 二叉树t1 t2: 二叉树t2 Returns: 布尔值",
"name": "search_helper",
"signature": "def search_helper(self, t1: TreeNod... | 3 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def is_symmetric(self, root: TreeNode) -> bool: 判断两棵树是否相同 Args: root: 根节点 Returns: 布尔值
- def search_helper(self, t1: TreeNode, t2: TreeNode) -> bool: 判断是否是对称二叉树 Args: t1: 二叉树t1 t... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def is_symmetric(self, root: TreeNode) -> bool: 判断两棵树是否相同 Args: root: 根节点 Returns: 布尔值
- def search_helper(self, t1: TreeNode, t2: TreeNode) -> bool: 判断是否是对称二叉树 Args: t1: 二叉树t1 t... | 50f35eef6a0ad63173efed10df3c835b1dceaa3f | <|skeleton|>
class Solution:
def is_symmetric(self, root: TreeNode) -> bool:
"""判断两棵树是否相同 Args: root: 根节点 Returns: 布尔值"""
<|body_0|>
def search_helper(self, t1: TreeNode, t2: TreeNode) -> bool:
"""判断是否是对称二叉树 Args: t1: 二叉树t1 t2: 二叉树t2 Returns: 布尔值"""
<|body_1|>
def is_symme... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def is_symmetric(self, root: TreeNode) -> bool:
"""判断两棵树是否相同 Args: root: 根节点 Returns: 布尔值"""
if not root:
return True
return self.search_helper(root.left, root.right)
def search_helper(self, t1: TreeNode, t2: TreeNode) -> bool:
"""判断是否是对称二叉树 Args: t1:... | the_stack_v2_python_sparse | src/leetcodepython/tree/symmetric_tree_101.py | zhangyu345293721/leetcode | train | 101 | |
04e54ace2cb9f52486ec8f7881b1a7e5c7bc0ecc | [
"context = dict(form=UpLoadForm())\ncontext.update(setMenus())\nreturn render_template('webapp/datain.html', **context)",
"_value = int(request.json.get('value'))\ncontext = dict(form=UpLoadForm())\ncontext.update(setMenus())\ntemplate_name = 'webapp/form/register.html'\nreturn jsonify(body=render_template(templa... | <|body_start_0|>
context = dict(form=UpLoadForm())
context.update(setMenus())
return render_template('webapp/datain.html', **context)
<|end_body_0|>
<|body_start_1|>
_value = int(request.json.get('value'))
context = dict(form=UpLoadForm())
context.update(setMenus())
... | CDHChange | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CDHChange:
def get(self):
"""用于 列表翻页 的刷新 :return:"""
<|body_0|>
def post(self):
"""请求来自于：1）页面切换；2）定时器 :return:"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
context = dict(form=UpLoadForm())
context.update(setMenus())
return render... | stack_v2_sparse_classes_36k_train_029878 | 4,507 | no_license | [
{
"docstring": "用于 列表翻页 的刷新 :return:",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "请求来自于：1）页面切换；2）定时器 :return:",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011232 | Implement the Python class `CDHChange` described below.
Class description:
Implement the CDHChange class.
Method signatures and docstrings:
- def get(self): 用于 列表翻页 的刷新 :return:
- def post(self): 请求来自于：1）页面切换；2）定时器 :return: | Implement the Python class `CDHChange` described below.
Class description:
Implement the CDHChange class.
Method signatures and docstrings:
- def get(self): 用于 列表翻页 的刷新 :return:
- def post(self): 请求来自于：1）页面切换；2）定时器 :return:
<|skeleton|>
class CDHChange:
def get(self):
"""用于 列表翻页 的刷新 :return:"""
... | f085ad50e52b6bbfd23d1afba2a7a86aae52e099 | <|skeleton|>
class CDHChange:
def get(self):
"""用于 列表翻页 的刷新 :return:"""
<|body_0|>
def post(self):
"""请求来自于：1）页面切换；2）定时器 :return:"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CDHChange:
def get(self):
"""用于 列表翻页 的刷新 :return:"""
context = dict(form=UpLoadForm())
context.update(setMenus())
return render_template('webapp/datain.html', **context)
def post(self):
"""请求来自于：1）页面切换；2）定时器 :return:"""
_value = int(request.json.get('value'... | the_stack_v2_python_sparse | nebula/portal/views/portal/hadoop/hadoop.py | shenwei0329/nebula | train | 1 | |
19445d8c1c6defe77a7d69523a592a9457c22cea | [
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"context.set_code(grpc.StatusCode.UNIMPLEMENTED)\ncontext.set_details('Method not implemented!')\nraise NotImplementedError('Method not implemented!')",
"conte... | <|body_start_0|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
<|end_body_0|>
<|body_start_1|>
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not im... | Missing associated documentation comment in .proto file. | JobServiceServicer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JobServiceServicer:
"""Missing associated documentation comment in .proto file."""
def ClaimStatus(self, request, context):
"""Claims status for the specified job."""
<|body_0|>
def Get(self, request, context):
"""Returns the job for the specified agent."""
... | stack_v2_sparse_classes_36k_train_029879 | 8,636 | permissive | [
{
"docstring": "Claims status for the specified job.",
"name": "ClaimStatus",
"signature": "def ClaimStatus(self, request, context)"
},
{
"docstring": "Returns the job for the specified agent.",
"name": "Get",
"signature": "def Get(self, request, context)"
},
{
"docstring": "Retu... | 4 | stack_v2_sparse_classes_30k_train_018962 | Implement the Python class `JobServiceServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def ClaimStatus(self, request, context): Claims status for the specified job.
- def Get(self, request, context): Returns the job for the spec... | Implement the Python class `JobServiceServicer` described below.
Class description:
Missing associated documentation comment in .proto file.
Method signatures and docstrings:
- def ClaimStatus(self, request, context): Claims status for the specified job.
- def Get(self, request, context): Returns the job for the spec... | b906a014dd893e2697864e1e48e814a8d9fbc48c | <|skeleton|>
class JobServiceServicer:
"""Missing associated documentation comment in .proto file."""
def ClaimStatus(self, request, context):
"""Claims status for the specified job."""
<|body_0|>
def Get(self, request, context):
"""Returns the job for the specified agent."""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JobServiceServicer:
"""Missing associated documentation comment in .proto file."""
def ClaimStatus(self, request, context):
"""Claims status for the specified job."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotIm... | the_stack_v2_python_sparse | yandex/cloud/loadtesting/agent/v1/job_service_pb2_grpc.py | yandex-cloud/python-sdk | train | 63 |
ca39b775b45deb6d54c875baa82deec85a352da4 | [
"professional_id = request.GET.get('id')\nprofessional_user = request.GET.get('user')\nif professional_id and professional_id is not None:\n queryset = queryset.filter(id=professional_id)\nif professional_user and professional_user is not None:\n queryset = queryset.filter(user=professional_user)\nqueryset = ... | <|body_start_0|>
professional_id = request.GET.get('id')
professional_user = request.GET.get('user')
if professional_id and professional_id is not None:
queryset = queryset.filter(id=professional_id)
if professional_user and professional_user is not None:
queryset... | Professional View | ProfessionalView | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProfessionalView:
"""Professional View"""
def filter(self, request, queryset):
"""Filter queryset from request argument"""
<|body_0|>
def post_save(self, request, instance, professional_data, created):
"""Save professional's M2M field"""
<|body_1|>
<|end... | stack_v2_sparse_classes_36k_train_029880 | 5,417 | no_license | [
{
"docstring": "Filter queryset from request argument",
"name": "filter",
"signature": "def filter(self, request, queryset)"
},
{
"docstring": "Save professional's M2M field",
"name": "post_save",
"signature": "def post_save(self, request, instance, professional_data, created)"
}
] | 2 | null | Implement the Python class `ProfessionalView` described below.
Class description:
Professional View
Method signatures and docstrings:
- def filter(self, request, queryset): Filter queryset from request argument
- def post_save(self, request, instance, professional_data, created): Save professional's M2M field | Implement the Python class `ProfessionalView` described below.
Class description:
Professional View
Method signatures and docstrings:
- def filter(self, request, queryset): Filter queryset from request argument
- def post_save(self, request, instance, professional_data, created): Save professional's M2M field
<|skel... | 95d21cd6036a99c5f399b700a5426e9e2e17e878 | <|skeleton|>
class ProfessionalView:
"""Professional View"""
def filter(self, request, queryset):
"""Filter queryset from request argument"""
<|body_0|>
def post_save(self, request, instance, professional_data, created):
"""Save professional's M2M field"""
<|body_1|>
<|end... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProfessionalView:
"""Professional View"""
def filter(self, request, queryset):
"""Filter queryset from request argument"""
professional_id = request.GET.get('id')
professional_user = request.GET.get('user')
if professional_id and professional_id is not None:
qu... | the_stack_v2_python_sparse | listepro/views/professional_view.py | alexandrenorman/mixeur | train | 0 |
5bfbaf23dbc7bae816032633e63f2c8bd25b395a | [
"from ibc.client import InteractiveBrokersClient\nself.client: InteractiveBrokersClient = ib_client\nself.session: InteractiveBrokersSession = ib_session",
"if isinstance(frequency, Enum):\n frequency = frequency.value\npayload = {'acctIds': account_ids, 'freq': frequency}\ncontent = self.session.make_request(... | <|body_start_0|>
from ibc.client import InteractiveBrokersClient
self.client: InteractiveBrokersClient = ib_client
self.session: InteractiveBrokersSession = ib_session
<|end_body_0|>
<|body_start_1|>
if isinstance(frequency, Enum):
frequency = frequency.value
payload... | PortfolioAnalysis | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PortfolioAnalysis:
def __init__(self, ib_client: object, ib_session: InteractiveBrokersSession) -> None:
"""Initializes the `PortfolioAnalysis` client. ### Parameters ---- ib_client : object The `InteractiveBrokersClient` Python Client. ib_session : InteractiveBrokersSession The IB sessi... | stack_v2_sparse_classes_36k_train_029881 | 3,507 | permissive | [
{
"docstring": "Initializes the `PortfolioAnalysis` client. ### Parameters ---- ib_client : object The `InteractiveBrokersClient` Python Client. ib_session : InteractiveBrokersSession The IB session handler.",
"name": "__init__",
"signature": "def __init__(self, ib_client: object, ib_session: Interactiv... | 4 | null | Implement the Python class `PortfolioAnalysis` described below.
Class description:
Implement the PortfolioAnalysis class.
Method signatures and docstrings:
- def __init__(self, ib_client: object, ib_session: InteractiveBrokersSession) -> None: Initializes the `PortfolioAnalysis` client. ### Parameters ---- ib_client ... | Implement the Python class `PortfolioAnalysis` described below.
Class description:
Implement the PortfolioAnalysis class.
Method signatures and docstrings:
- def __init__(self, ib_client: object, ib_session: InteractiveBrokersSession) -> None: Initializes the `PortfolioAnalysis` client. ### Parameters ---- ib_client ... | a5b02ea914d6cd7683aff30cd38547e6150dc374 | <|skeleton|>
class PortfolioAnalysis:
def __init__(self, ib_client: object, ib_session: InteractiveBrokersSession) -> None:
"""Initializes the `PortfolioAnalysis` client. ### Parameters ---- ib_client : object The `InteractiveBrokersClient` Python Client. ib_session : InteractiveBrokersSession The IB sessi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PortfolioAnalysis:
def __init__(self, ib_client: object, ib_session: InteractiveBrokersSession) -> None:
"""Initializes the `PortfolioAnalysis` client. ### Parameters ---- ib_client : object The `InteractiveBrokersClient` Python Client. ib_session : InteractiveBrokersSession The IB session handler."""... | the_stack_v2_python_sparse | ibc/rest/portfolio_analysis.py | xuelee85/interactive-brokers-api | train | 0 | |
b93ccbbeb49e048b9f874a28c38bd084eca037d4 | [
"context = request.environ['cinder.context']\ntrimmed = dict(id=group_type.get('id'), name=group_type.get('name'), description=group_type.get('description'), is_public=group_type.get('is_public'))\nif context.authorize(policy.SHOW_ACCESS_POLICY, fatal=False):\n trimmed['group_specs'] = group_type.get('group_spec... | <|body_start_0|>
context = request.environ['cinder.context']
trimmed = dict(id=group_type.get('id'), name=group_type.get('name'), description=group_type.get('description'), is_public=group_type.get('is_public'))
if context.authorize(policy.SHOW_ACCESS_POLICY, fatal=False):
trimmed['g... | ViewBuilder | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ViewBuilder:
def show(self, request, group_type, brief=False):
"""Trim away extraneous group type attributes."""
<|body_0|>
def index(self, request, group_types):
"""Index over trimmed group types."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
con... | stack_v2_sparse_classes_36k_train_029882 | 1,894 | permissive | [
{
"docstring": "Trim away extraneous group type attributes.",
"name": "show",
"signature": "def show(self, request, group_type, brief=False)"
},
{
"docstring": "Index over trimmed group types.",
"name": "index",
"signature": "def index(self, request, group_types)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021124 | Implement the Python class `ViewBuilder` described below.
Class description:
Implement the ViewBuilder class.
Method signatures and docstrings:
- def show(self, request, group_type, brief=False): Trim away extraneous group type attributes.
- def index(self, request, group_types): Index over trimmed group types. | Implement the Python class `ViewBuilder` described below.
Class description:
Implement the ViewBuilder class.
Method signatures and docstrings:
- def show(self, request, group_type, brief=False): Trim away extraneous group type attributes.
- def index(self, request, group_types): Index over trimmed group types.
<|sk... | 04a5d6b8c28271f6aefe2bbae6a1e16c1c235835 | <|skeleton|>
class ViewBuilder:
def show(self, request, group_type, brief=False):
"""Trim away extraneous group type attributes."""
<|body_0|>
def index(self, request, group_types):
"""Index over trimmed group types."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ViewBuilder:
def show(self, request, group_type, brief=False):
"""Trim away extraneous group type attributes."""
context = request.environ['cinder.context']
trimmed = dict(id=group_type.get('id'), name=group_type.get('name'), description=group_type.get('description'), is_public=group_t... | the_stack_v2_python_sparse | cinder/api/v3/views/group_types.py | LINBIT/openstack-cinder | train | 9 | |
f50eb6a7798f814239a85228d8b9e9d3e2ec7974 | [
"identity = flask_jwt.get_jwt_identity() or {}\ntry:\n app = identity.get('app')\n return session.Session(save=False, profile=session.SessionProfile(**identity['profile']), groups=[groups.Group(**g) for g in identity['groups'] or []], app=app if app is None else session.SessionApp(**app), default_object_perms... | <|body_start_0|>
identity = flask_jwt.get_jwt_identity() or {}
try:
app = identity.get('app')
return session.Session(save=False, profile=session.SessionProfile(**identity['profile']), groups=[groups.Group(**g) for g in identity['groups'] or []], app=app if app is None else sessio... | Hooks up our JWT tokens to the session interface so we can use flask the way it was intended but also get the benefit of JWTs. Sessions in this system are immutable, and may only be written by an application server | JWTSessionInterface | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JWTSessionInterface:
"""Hooks up our JWT tokens to the session interface so we can use flask the way it was intended but also get the benefit of JWTs. Sessions in this system are immutable, and may only be written by an application server"""
def open_session(self, app, request):
"""P... | stack_v2_sparse_classes_36k_train_029883 | 4,373 | no_license | [
{
"docstring": "Populate the session from the JWT cookies at the start of a request",
"name": "open_session",
"signature": "def open_session(self, app, request)"
},
{
"docstring": "Save the session at the end of a request if it's new and we are the auth server",
"name": "save_session",
"... | 2 | stack_v2_sparse_classes_30k_train_017026 | Implement the Python class `JWTSessionInterface` described below.
Class description:
Hooks up our JWT tokens to the session interface so we can use flask the way it was intended but also get the benefit of JWTs. Sessions in this system are immutable, and may only be written by an application server
Method signatures ... | Implement the Python class `JWTSessionInterface` described below.
Class description:
Hooks up our JWT tokens to the session interface so we can use flask the way it was intended but also get the benefit of JWTs. Sessions in this system are immutable, and may only be written by an application server
Method signatures ... | dbba9f3b292ffef6ea924608fa54237171f0aaeb | <|skeleton|>
class JWTSessionInterface:
"""Hooks up our JWT tokens to the session interface so we can use flask the way it was intended but also get the benefit of JWTs. Sessions in this system are immutable, and may only be written by an application server"""
def open_session(self, app, request):
"""P... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JWTSessionInterface:
"""Hooks up our JWT tokens to the session interface so we can use flask the way it was intended but also get the benefit of JWTs. Sessions in this system are immutable, and may only be written by an application server"""
def open_session(self, app, request):
"""Populate the s... | the_stack_v2_python_sparse | lib/python/core/directorofme/flask/jwt.py | DirectorOfMe/directorof.me | train | 0 |
1dc03d57bf97e65736e66f3c2212d4af0f916cab | [
"length = self.config.max_time_series_length(dataset_config)\nif length is not None:\n dataset = [{**item, 'target': item['target'][-length:]} for item in dataset_split.gluonts()]\nelse:\n dataset = dataset_split.gluonts()\nfor i, predictor in enumerate(self.predictors):\n logging.info('Evaluating predicto... | <|body_start_0|>
length = self.config.max_time_series_length(dataset_config)
if length is not None:
dataset = [{**item, 'target': item['target'][-length:]} for item in dataset_split.gluonts()]
else:
dataset = dataset_split.gluonts()
for i, predictor in enumerate(s... | A result object obtained when fitting a model. | FitResult | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FitResult:
"""A result object obtained when fitting a model."""
def evaluate_predictors(self, dataset_config: DatasetConfig, dataset_split: DatasetSplit, directory: Path, validation: bool=False) -> None:
"""Evaluates the given predictors on the specified dataset, logs the resulting m... | stack_v2_sparse_classes_36k_train_029884 | 4,949 | permissive | [
{
"docstring": "Evaluates the given predictors on the specified dataset, logs the resulting metrics and stores the forecasts in the given directory. The forecasts of predictor `i` are stored in the subdirectory `model_<i>`. Args: dataset_config: The configuration of the dataset to make predictions for. dataset_... | 2 | null | Implement the Python class `FitResult` described below.
Class description:
A result object obtained when fitting a model.
Method signatures and docstrings:
- def evaluate_predictors(self, dataset_config: DatasetConfig, dataset_split: DatasetSplit, directory: Path, validation: bool=False) -> None: Evaluates the given ... | Implement the Python class `FitResult` described below.
Class description:
A result object obtained when fitting a model.
Method signatures and docstrings:
- def evaluate_predictors(self, dataset_config: DatasetConfig, dataset_split: DatasetSplit, directory: Path, validation: bool=False) -> None: Evaluates the given ... | 57ae07f571ff123eac04af077870c1f216f99d5c | <|skeleton|>
class FitResult:
"""A result object obtained when fitting a model."""
def evaluate_predictors(self, dataset_config: DatasetConfig, dataset_split: DatasetSplit, directory: Path, validation: bool=False) -> None:
"""Evaluates the given predictors on the specified dataset, logs the resulting m... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FitResult:
"""A result object obtained when fitting a model."""
def evaluate_predictors(self, dataset_config: DatasetConfig, dataset_split: DatasetSplit, directory: Path, validation: bool=False) -> None:
"""Evaluates the given predictors on the specified dataset, logs the resulting metrics and st... | the_stack_v2_python_sparse | src/gluonts/nursery/tsbench/src/tsbench/evaluations/training/evaluate.py | canerturkmen/gluon-ts | train | 1 |
8440b2c052a1363681053e1727822455995c5f99 | [
"value = 0\nfor tribe in tribes:\n value |= 1 << tribe.value\nreturn value",
"tribes = []\nfor tribe in Tribe:\n if value & 1 << tribe.value:\n tribes.append(tribe)\nreturn TribeList(tribes)"
] | <|body_start_0|>
value = 0
for tribe in tribes:
value |= 1 << tribe.value
return value
<|end_body_0|>
<|body_start_1|>
tribes = []
for tribe in Tribe:
if value & 1 << tribe.value:
tribes.append(tribe)
return TribeList(tribes)
<|end... | A field to store a list of tribes. | TribeListField | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TribeListField:
"""A field to store a list of tribes."""
def db_value(self, tribes: TribeList) -> int:
"""Convert a list of tribe enum instances to a series of bit flags."""
<|body_0|>
def python_value(self, value: int) -> TribeList:
"""Convert a series of bit fl... | stack_v2_sparse_classes_36k_train_029885 | 4,521 | no_license | [
{
"docstring": "Convert a list of tribe enum instances to a series of bit flags.",
"name": "db_value",
"signature": "def db_value(self, tribes: TribeList) -> int"
},
{
"docstring": "Convert a series of bit flags to a list of tribe enum instances.",
"name": "python_value",
"signature": "d... | 2 | stack_v2_sparse_classes_30k_train_007612 | Implement the Python class `TribeListField` described below.
Class description:
A field to store a list of tribes.
Method signatures and docstrings:
- def db_value(self, tribes: TribeList) -> int: Convert a list of tribe enum instances to a series of bit flags.
- def python_value(self, value: int) -> TribeList: Conve... | Implement the Python class `TribeListField` described below.
Class description:
A field to store a list of tribes.
Method signatures and docstrings:
- def db_value(self, tribes: TribeList) -> int: Convert a list of tribe enum instances to a series of bit flags.
- def python_value(self, value: int) -> TribeList: Conve... | 05b2689fa191a10feea77afa94320f0b1d088dc0 | <|skeleton|>
class TribeListField:
"""A field to store a list of tribes."""
def db_value(self, tribes: TribeList) -> int:
"""Convert a list of tribe enum instances to a series of bit flags."""
<|body_0|>
def python_value(self, value: int) -> TribeList:
"""Convert a series of bit fl... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TribeListField:
"""A field to store a list of tribes."""
def db_value(self, tribes: TribeList) -> int:
"""Convert a list of tribe enum instances to a series of bit flags."""
value = 0
for tribe in tribes:
value |= 1 << tribe.value
return value
def python_v... | the_stack_v2_python_sparse | diplo-bot/main/tribes.py | Artemis21/polybots | train | 3 |
0a20d5263876121c511f022dac4f67cbc546c89e | [
"def is_rep(a) -> bool:\n a_filtered = a[a != '.']\n a_filtered = a[np.where(a != '.')]\n return len(set(a_filtered)) != len(a_filtered)\nboard = np.array(board)\ncheck_col = np.apply_along_axis(is_rep, 0, board)\ncheck_row = np.apply_along_axis(is_rep, 1, board)\nif any(check_col) or any(check_row):\n ... | <|body_start_0|>
def is_rep(a) -> bool:
a_filtered = a[a != '.']
a_filtered = a[np.where(a != '.')]
return len(set(a_filtered)) != len(a_filtered)
board = np.array(board)
check_col = np.apply_along_axis(is_rep, 0, board)
check_row = np.apply_along_axis... | Solution | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isValidSudoku1(self, board) -> bool:
"""A numpy-style solution Runtime: 220ms"""
<|body_0|>
def isValidSudoku2(self, board) -> bool:
"""Three loops Runtime: 88ms"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
def is_rep(a) -> bool:
... | stack_v2_sparse_classes_36k_train_029886 | 3,702 | permissive | [
{
"docstring": "A numpy-style solution Runtime: 220ms",
"name": "isValidSudoku1",
"signature": "def isValidSudoku1(self, board) -> bool"
},
{
"docstring": "Three loops Runtime: 88ms",
"name": "isValidSudoku2",
"signature": "def isValidSudoku2(self, board) -> bool"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValidSudoku1(self, board) -> bool: A numpy-style solution Runtime: 220ms
- def isValidSudoku2(self, board) -> bool: Three loops Runtime: 88ms | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValidSudoku1(self, board) -> bool: A numpy-style solution Runtime: 220ms
- def isValidSudoku2(self, board) -> bool: Three loops Runtime: 88ms
<|skeleton|>
class Solution:
... | 49a0b03c55d8a702785888d473ef96539265ce9c | <|skeleton|>
class Solution:
def isValidSudoku1(self, board) -> bool:
"""A numpy-style solution Runtime: 220ms"""
<|body_0|>
def isValidSudoku2(self, board) -> bool:
"""Three loops Runtime: 88ms"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isValidSudoku1(self, board) -> bool:
"""A numpy-style solution Runtime: 220ms"""
def is_rep(a) -> bool:
a_filtered = a[a != '.']
a_filtered = a[np.where(a != '.')]
return len(set(a_filtered)) != len(a_filtered)
board = np.array(board)
... | the_stack_v2_python_sparse | leetcode/0036_valid_sudoku.py | chaosWsF/Python-Practice | train | 1 | |
86d6b5be8acf6d2622af1a2082c2e73ac74413ea | [
"with create_session() as session:\n parkinglot = session.query(ParkingLot).filter(ParkingLot.plate == plate).one()\n entity = ParkingSpaceMapper.to_entity(record=parkinglot)\n raise Return(entity)",
"with create_session() as session:\n parking_space.validate()\n _parking_space = ParkingSpaceMapper... | <|body_start_0|>
with create_session() as session:
parkinglot = session.query(ParkingLot).filter(ParkingLot.plate == plate).one()
entity = ParkingSpaceMapper.to_entity(record=parkinglot)
raise Return(entity)
<|end_body_0|>
<|body_start_1|>
with create_session() as se... | ParkingLotRepository | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ParkingLotRepository:
def read_one(cls, plate):
"""Read one by plate :param str plate: :return: <ParkingSpace>: :raises noResultFound: vehicle with given plate is not in the parking lot"""
<|body_0|>
def insert(cls, parking_space):
"""Insert a parking space to the pa... | stack_v2_sparse_classes_36k_train_029887 | 1,886 | no_license | [
{
"docstring": "Read one by plate :param str plate: :return: <ParkingSpace>: :raises noResultFound: vehicle with given plate is not in the parking lot",
"name": "read_one",
"signature": "def read_one(cls, plate)"
},
{
"docstring": "Insert a parking space to the parking lot :return ParkingSpace:"... | 3 | null | Implement the Python class `ParkingLotRepository` described below.
Class description:
Implement the ParkingLotRepository class.
Method signatures and docstrings:
- def read_one(cls, plate): Read one by plate :param str plate: :return: <ParkingSpace>: :raises noResultFound: vehicle with given plate is not in the parki... | Implement the Python class `ParkingLotRepository` described below.
Class description:
Implement the ParkingLotRepository class.
Method signatures and docstrings:
- def read_one(cls, plate): Read one by plate :param str plate: :return: <ParkingSpace>: :raises noResultFound: vehicle with given plate is not in the parki... | fd759c16b9864f6b1b47b1ba3f1af77f8d08af20 | <|skeleton|>
class ParkingLotRepository:
def read_one(cls, plate):
"""Read one by plate :param str plate: :return: <ParkingSpace>: :raises noResultFound: vehicle with given plate is not in the parking lot"""
<|body_0|>
def insert(cls, parking_space):
"""Insert a parking space to the pa... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ParkingLotRepository:
def read_one(cls, plate):
"""Read one by plate :param str plate: :return: <ParkingSpace>: :raises noResultFound: vehicle with given plate is not in the parking lot"""
with create_session() as session:
parkinglot = session.query(ParkingLot).filter(ParkingLot.pl... | the_stack_v2_python_sparse | ParkingFinder/repositories/parking_lot.py | Big-Lemon/ParkingFinder | train | 2 | |
b011a76b9dff61ef9b00366ea198f2463a6044fa | [
"result = query_case_zip(case_id=case_id)\nif not result:\n return api_result(code=400, message='用例id:{}不存在'.format(case_id))\nreturn api_result(code=200, message='操作成功', data=result)",
"data = request.get_json()\ncase_name = data.get('case_name')\nrequest_method = data.get('request_method')\nrequest_base_url ... | <|body_start_0|>
result = query_case_zip(case_id=case_id)
if not result:
return api_result(code=400, message='用例id:{}不存在'.format(case_id))
return api_result(code=200, message='操作成功', data=result)
<|end_body_0|>
<|body_start_1|>
data = request.get_json()
case_name = d... | 用例Api GET: 用例详情 POST: 用例新增 PUT: 用例编辑 DELETE: 用例删除 | CaseApi | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CaseApi:
"""用例Api GET: 用例详情 POST: 用例新增 PUT: 用例编辑 DELETE: 用例删除"""
def get(self, case_id):
"""用例详情"""
<|body_0|>
def post(self):
"""用例新增"""
<|body_1|>
def put(self):
"""用例编辑"""
<|body_2|>
def delete(self):
"""用例删除"""
... | stack_v2_sparse_classes_36k_train_029888 | 5,985 | no_license | [
{
"docstring": "用例详情",
"name": "get",
"signature": "def get(self, case_id)"
},
{
"docstring": "用例新增",
"name": "post",
"signature": "def post(self)"
},
{
"docstring": "用例编辑",
"name": "put",
"signature": "def put(self)"
},
{
"docstring": "用例删除",
"name": "delete"... | 4 | stack_v2_sparse_classes_30k_train_000722 | Implement the Python class `CaseApi` described below.
Class description:
用例Api GET: 用例详情 POST: 用例新增 PUT: 用例编辑 DELETE: 用例删除
Method signatures and docstrings:
- def get(self, case_id): 用例详情
- def post(self): 用例新增
- def put(self): 用例编辑
- def delete(self): 用例删除 | Implement the Python class `CaseApi` described below.
Class description:
用例Api GET: 用例详情 POST: 用例新增 PUT: 用例编辑 DELETE: 用例删除
Method signatures and docstrings:
- def get(self, case_id): 用例详情
- def post(self): 用例新增
- def put(self): 用例编辑
- def delete(self): 用例删除
<|skeleton|>
class CaseApi:
"""用例Api GET: 用例详情 POST: 用例... | df76812885d7d7f3a5269e3f7c652db6a9f3c3ad | <|skeleton|>
class CaseApi:
"""用例Api GET: 用例详情 POST: 用例新增 PUT: 用例编辑 DELETE: 用例删除"""
def get(self, case_id):
"""用例详情"""
<|body_0|>
def post(self):
"""用例新增"""
<|body_1|>
def put(self):
"""用例编辑"""
<|body_2|>
def delete(self):
"""用例删除"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CaseApi:
"""用例Api GET: 用例详情 POST: 用例新增 PUT: 用例编辑 DELETE: 用例删除"""
def get(self, case_id):
"""用例详情"""
result = query_case_zip(case_id=case_id)
if not result:
return api_result(code=400, message='用例id:{}不存在'.format(case_id))
return api_result(code=200, message='操作... | the_stack_v2_python_sparse | app/api/case_api/case_api.py | chengzizhen/ExileTestPlatformServer | train | 0 |
7de0ac8c0746f4f26ca096f17215ff6248f9c3e7 | [
"self.active = active\nself.mfrom = mfrom\nself.to = to",
"if dictionary is None:\n return None\nactive = dictionary.get('active')\nmfrom = dictionary.get('from')\nto = dictionary.get('to')\nreturn cls(active, mfrom, to)"
] | <|body_start_0|>
self.active = active
self.mfrom = mfrom
self.to = to
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
active = dictionary.get('active')
mfrom = dictionary.get('from')
to = dictionary.get('to')
return cls(acti... | Implementation of the 'Monday' model. The schedule object for Monday. Attributes: active (bool): Whether the schedule is active (true) or inactive (false) during the time specified between 'from' and 'to'. Defaults to true. mfrom (string): The time, from '00:00' to '24:00'. Must be less than the time specified in 'to'.... | MondayModel | [
"MIT",
"Python-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MondayModel:
"""Implementation of the 'Monday' model. The schedule object for Monday. Attributes: active (bool): Whether the schedule is active (true) or inactive (false) during the time specified between 'from' and 'to'. Defaults to true. mfrom (string): The time, from '00:00' to '24:00'. Must b... | stack_v2_sparse_classes_36k_train_029889 | 2,170 | permissive | [
{
"docstring": "Constructor for the MondayModel class",
"name": "__init__",
"signature": "def __init__(self, active=None, mfrom=None, to=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (dictionary): A dictionary representation of the object as obtai... | 2 | stack_v2_sparse_classes_30k_train_002062 | Implement the Python class `MondayModel` described below.
Class description:
Implementation of the 'Monday' model. The schedule object for Monday. Attributes: active (bool): Whether the schedule is active (true) or inactive (false) during the time specified between 'from' and 'to'. Defaults to true. mfrom (string): Th... | Implement the Python class `MondayModel` described below.
Class description:
Implementation of the 'Monday' model. The schedule object for Monday. Attributes: active (bool): Whether the schedule is active (true) or inactive (false) during the time specified between 'from' and 'to'. Defaults to true. mfrom (string): Th... | 9894089eb013318243ae48869cc5130eb37f80c0 | <|skeleton|>
class MondayModel:
"""Implementation of the 'Monday' model. The schedule object for Monday. Attributes: active (bool): Whether the schedule is active (true) or inactive (false) during the time specified between 'from' and 'to'. Defaults to true. mfrom (string): The time, from '00:00' to '24:00'. Must b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MondayModel:
"""Implementation of the 'Monday' model. The schedule object for Monday. Attributes: active (bool): Whether the schedule is active (true) or inactive (false) during the time specified between 'from' and 'to'. Defaults to true. mfrom (string): The time, from '00:00' to '24:00'. Must be less than t... | the_stack_v2_python_sparse | meraki_sdk/models/monday_model.py | RaulCatalano/meraki-python-sdk | train | 1 |
a00d5ddef611e1319e745dbe5ae4f910280cd417 | [
"super(ClassificationHead, self).__init__()\nself.dense1 = PointNetDenseLayer(512, momentum)\nself.dense2 = PointNetDenseLayer(256, momentum)\nself.dropout = tf.keras.layers.Dropout(dropout_rate)\nself.dense3 = tf.keras.layers.Dense(num_classes, activation='linear')",
"x = self.dense1(inputs, training)\nx = self.... | <|body_start_0|>
super(ClassificationHead, self).__init__()
self.dense1 = PointNetDenseLayer(512, momentum)
self.dense2 = PointNetDenseLayer(256, momentum)
self.dropout = tf.keras.layers.Dropout(dropout_rate)
self.dense3 = tf.keras.layers.Dense(num_classes, activation='linear')
<... | The PointNet classification head. The head consists of 2x PointNetDenseLayer layers (512 and 256 channels) followed by a dropout layer (drop rate=30%) a dense linear layer producing the logits of the num_classes classes. | ClassificationHead | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClassificationHead:
"""The PointNet classification head. The head consists of 2x PointNetDenseLayer layers (512 and 256 channels) followed by a dropout layer (drop rate=30%) a dense linear layer producing the logits of the num_classes classes."""
def __init__(self, num_classes: int=40, momen... | stack_v2_sparse_classes_36k_train_029890 | 9,332 | permissive | [
{
"docstring": "Constructor. Args: num_classes: the number of classes to classify. momentum: the momentum used for the batch normalization layer. dropout_rate: the dropout rate for fully connected layer",
"name": "__init__",
"signature": "def __init__(self, num_classes: int=40, momentum: float=0.5, drop... | 2 | stack_v2_sparse_classes_30k_train_006195 | Implement the Python class `ClassificationHead` described below.
Class description:
The PointNet classification head. The head consists of 2x PointNetDenseLayer layers (512 and 256 channels) followed by a dropout layer (drop rate=30%) a dense linear layer producing the logits of the num_classes classes.
Method signat... | Implement the Python class `ClassificationHead` described below.
Class description:
The PointNet classification head. The head consists of 2x PointNetDenseLayer layers (512 and 256 channels) followed by a dropout layer (drop rate=30%) a dense linear layer producing the logits of the num_classes classes.
Method signat... | 1b0203eb538f2b6a1013ec7736d0d548416f059a | <|skeleton|>
class ClassificationHead:
"""The PointNet classification head. The head consists of 2x PointNetDenseLayer layers (512 and 256 channels) followed by a dropout layer (drop rate=30%) a dense linear layer producing the logits of the num_classes classes."""
def __init__(self, num_classes: int=40, momen... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ClassificationHead:
"""The PointNet classification head. The head consists of 2x PointNetDenseLayer layers (512 and 256 channels) followed by a dropout layer (drop rate=30%) a dense linear layer producing the logits of the num_classes classes."""
def __init__(self, num_classes: int=40, momentum: float=0.... | the_stack_v2_python_sparse | tensorflow_graphics/nn/layer/pointnet.py | tensorflow/graphics | train | 2,920 |
8c55713a797b0ebe55c1d24fbfe4095e4abb83b0 | [
"if self._body is None:\n self._body = self.stream.read(self.content_length or 0)\nreturn self._body",
"if self._json is None:\n self._json = json.loads(self.body)\nreturn self._json"
] | <|body_start_0|>
if self._body is None:
self._body = self.stream.read(self.content_length or 0)
return self._body
<|end_body_0|>
<|body_start_1|>
if self._json is None:
self._json = json.loads(self.body)
return self._json
<|end_body_1|>
| Helper methods for falcon Request class | HTTPRequest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HTTPRequest:
"""Helper methods for falcon Request class"""
def body(self):
"""Keeps body available for future calls Returns: str: request body"""
<|body_0|>
def json(self):
"""Loads JSON object from body. Returns: dict: JSON object"""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_36k_train_029891 | 673 | permissive | [
{
"docstring": "Keeps body available for future calls Returns: str: request body",
"name": "body",
"signature": "def body(self)"
},
{
"docstring": "Loads JSON object from body. Returns: dict: JSON object",
"name": "json",
"signature": "def json(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_009552 | Implement the Python class `HTTPRequest` described below.
Class description:
Helper methods for falcon Request class
Method signatures and docstrings:
- def body(self): Keeps body available for future calls Returns: str: request body
- def json(self): Loads JSON object from body. Returns: dict: JSON object | Implement the Python class `HTTPRequest` described below.
Class description:
Helper methods for falcon Request class
Method signatures and docstrings:
- def body(self): Keeps body available for future calls Returns: str: request body
- def json(self): Loads JSON object from body. Returns: dict: JSON object
<|skeleto... | 4849d75906ae54fd383c3def31284e96964b2912 | <|skeleton|>
class HTTPRequest:
"""Helper methods for falcon Request class"""
def body(self):
"""Keeps body available for future calls Returns: str: request body"""
<|body_0|>
def json(self):
"""Loads JSON object from body. Returns: dict: JSON object"""
<|body_1|>
<|end_sk... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HTTPRequest:
"""Helper methods for falcon Request class"""
def body(self):
"""Keeps body available for future calls Returns: str: request body"""
if self._body is None:
self._body = self.stream.read(self.content_length or 0)
return self._body
def json(self):
... | the_stack_v2_python_sparse | src/clustaar/webhook/falcon/http_request.py | Clustaar/clustaar.webhook | train | 4 |
686f1521e5922df9ba2dc5d8009f1997401c16b0 | [
"length = len(nums)\nsum_num = sum(nums)\nif sum_num % 2 == 1:\n return False\nhalf = sum_num // 2\ndp = [[False for _ in range(half + 1)] for _ in range(length)]\nfor c in range(half + 1):\n if c == nums[0]:\n dp[0][c] = True\nfor i in range(1, length):\n for c in range(half + 1):\n if nums[... | <|body_start_0|>
length = len(nums)
sum_num = sum(nums)
if sum_num % 2 == 1:
return False
half = sum_num // 2
dp = [[False for _ in range(half + 1)] for _ in range(length)]
for c in range(half + 1):
if c == nums[0]:
dp[0][c] = True
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def canPartition(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def _canPartition(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
length = len(nums)
sum_num = sum... | stack_v2_sparse_classes_36k_train_029892 | 1,953 | no_license | [
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "canPartition",
"signature": "def canPartition(self, nums)"
},
{
"docstring": ":type nums: List[int] :rtype: bool",
"name": "_canPartition",
"signature": "def _canPartition(self, nums)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000703 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canPartition(self, nums): :type nums: List[int] :rtype: bool
- def _canPartition(self, nums): :type nums: List[int] :rtype: bool | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def canPartition(self, nums): :type nums: List[int] :rtype: bool
- def _canPartition(self, nums): :type nums: List[int] :rtype: bool
<|skeleton|>
class Solution:
def canPar... | 1d1ffe25d8b49832acc1791261c959ce436a6362 | <|skeleton|>
class Solution:
def canPartition(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_0|>
def _canPartition(self, nums):
""":type nums: List[int] :rtype: bool"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def canPartition(self, nums):
""":type nums: List[int] :rtype: bool"""
length = len(nums)
sum_num = sum(nums)
if sum_num % 2 == 1:
return False
half = sum_num // 2
dp = [[False for _ in range(half + 1)] for _ in range(length)]
for c... | the_stack_v2_python_sparse | 00-每日一题/20200325_416.py | qiaozhi827/leetcode-1 | train | 0 | |
744b85f377a0d84048fbf5c614a594194706623f | [
"processed = 0\nfor base in queryset:\n base.ResetNames()\n processed += 1\nself.message_user(request, '%s reset.' % GetMessageBit(processed))",
"processed = 0\nfor base in queryset:\n base.stateManaged = 'new'\n base.ResetNames()\n processed += 1\nself.message_user(request, '%s reset and marked as... | <|body_start_0|>
processed = 0
for base in queryset:
base.ResetNames()
processed += 1
self.message_user(request, '%s reset.' % GetMessageBit(processed))
<|end_body_0|>
<|body_start_1|>
processed = 0
for base in queryset:
base.stateManaged = 'n... | XrumerBaseSpamAdmin | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class XrumerBaseSpamAdmin:
def ResetNames(self, request, queryset):
"""Сбрасываем имена"""
<|body_0|>
def ResetNamesAndNew(self, request, queryset):
"""Сбрасываем имена и помечаем как новые"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
processed = 0
... | stack_v2_sparse_classes_36k_train_029893 | 29,849 | no_license | [
{
"docstring": "Сбрасываем имена",
"name": "ResetNames",
"signature": "def ResetNames(self, request, queryset)"
},
{
"docstring": "Сбрасываем имена и помечаем как новые",
"name": "ResetNamesAndNew",
"signature": "def ResetNamesAndNew(self, request, queryset)"
}
] | 2 | stack_v2_sparse_classes_30k_train_021125 | Implement the Python class `XrumerBaseSpamAdmin` described below.
Class description:
Implement the XrumerBaseSpamAdmin class.
Method signatures and docstrings:
- def ResetNames(self, request, queryset): Сбрасываем имена
- def ResetNamesAndNew(self, request, queryset): Сбрасываем имена и помечаем как новые | Implement the Python class `XrumerBaseSpamAdmin` described below.
Class description:
Implement the XrumerBaseSpamAdmin class.
Method signatures and docstrings:
- def ResetNames(self, request, queryset): Сбрасываем имена
- def ResetNamesAndNew(self, request, queryset): Сбрасываем имена и помечаем как новые
<|skeleton... | d2771bf04aa187dda6d468883a5a167237589369 | <|skeleton|>
class XrumerBaseSpamAdmin:
def ResetNames(self, request, queryset):
"""Сбрасываем имена"""
<|body_0|>
def ResetNamesAndNew(self, request, queryset):
"""Сбрасываем имена и помечаем как новые"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class XrumerBaseSpamAdmin:
def ResetNames(self, request, queryset):
"""Сбрасываем имена"""
processed = 0
for base in queryset:
base.ResetNames()
processed += 1
self.message_user(request, '%s reset.' % GetMessageBit(processed))
def ResetNamesAndNew(self, r... | the_stack_v2_python_sparse | doorsadmin/admin.py | cash2one/doorscenter | train | 0 | |
f81bdd355f12ad8cd4609d8fcf14c8e3a3c4f349 | [
"self.username: str = config[CONF_USERNAME]\nself.api_key: str = config[CONF_API_KEY]\nself.recipients: list[str] = config[CONF_RECIPIENT]\nself.sender: str = config[CONF_SENDER]",
"data: dict[str, Any] = {'messages': []}\nfor recipient in self.recipients:\n data['messages'].append({'source': 'hass.notify', 'f... | <|body_start_0|>
self.username: str = config[CONF_USERNAME]
self.api_key: str = config[CONF_API_KEY]
self.recipients: list[str] = config[CONF_RECIPIENT]
self.sender: str = config[CONF_SENDER]
<|end_body_0|>
<|body_start_1|>
data: dict[str, Any] = {'messages': []}
for rec... | Implementation of a notification service for the ClickSend service. | ClicksendNotificationService | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ClicksendNotificationService:
"""Implementation of a notification service for the ClickSend service."""
def __init__(self, config: ConfigType) -> None:
"""Initialize the service."""
<|body_0|>
def send_message(self, message: str='', **kwargs: Any) -> None:
"""Sen... | stack_v2_sparse_classes_36k_train_029894 | 3,372 | permissive | [
{
"docstring": "Initialize the service.",
"name": "__init__",
"signature": "def __init__(self, config: ConfigType) -> None"
},
{
"docstring": "Send a message to a user.",
"name": "send_message",
"signature": "def send_message(self, message: str='', **kwargs: Any) -> None"
}
] | 2 | null | Implement the Python class `ClicksendNotificationService` described below.
Class description:
Implementation of a notification service for the ClickSend service.
Method signatures and docstrings:
- def __init__(self, config: ConfigType) -> None: Initialize the service.
- def send_message(self, message: str='', **kwar... | Implement the Python class `ClicksendNotificationService` described below.
Class description:
Implementation of a notification service for the ClickSend service.
Method signatures and docstrings:
- def __init__(self, config: ConfigType) -> None: Initialize the service.
- def send_message(self, message: str='', **kwar... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class ClicksendNotificationService:
"""Implementation of a notification service for the ClickSend service."""
def __init__(self, config: ConfigType) -> None:
"""Initialize the service."""
<|body_0|>
def send_message(self, message: str='', **kwargs: Any) -> None:
"""Sen... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ClicksendNotificationService:
"""Implementation of a notification service for the ClickSend service."""
def __init__(self, config: ConfigType) -> None:
"""Initialize the service."""
self.username: str = config[CONF_USERNAME]
self.api_key: str = config[CONF_API_KEY]
self.re... | the_stack_v2_python_sparse | homeassistant/components/clicksend/notify.py | home-assistant/core | train | 35,501 |
a4401c75dab0fe9545bfa85f58324434cabd49fc | [
"seriesMap = {}\nfor index, _ in enumerate(series):\n name, serie = series[index]\n seriesId = '{}_{}'.format(name, uid)\n seriesMap.update({seriesId: {'label': name, 'data': zip(range(0, len(serie)), serie), 'points': {'show': True}, 'lines': {'show': True}}})\nreturn seriesMap",
"constituentNames = ['{... | <|body_start_0|>
seriesMap = {}
for index, _ in enumerate(series):
name, serie = series[index]
seriesId = '{}_{}'.format(name, uid)
seriesMap.update({seriesId: {'label': name, 'data': zip(range(0, len(serie)), serie), 'points': {'show': True}, 'lines': {'show': True}}... | Builds chart visualization for a delta series collections from current profile session and benchmarks The flot builder creates charts with txnId in x-axis and duration (micro seconds) in y-axis The builder creates a line chart for delta series, from each pair of probes in the timeline | FlotBuilder | [
"MIT",
"BSD-3-Clause",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FlotBuilder:
"""Builds chart visualization for a delta series collections from current profile session and benchmarks The flot builder creates charts with txnId in x-axis and duration (micro seconds) in y-axis The builder creates a line chart for delta series, from each pair of probes in the time... | stack_v2_sparse_classes_36k_train_029895 | 7,581 | permissive | [
{
"docstring": "Builds a map with data and options for creating visualizations :param series: the collection of series to be plotted",
"name": "buildFlotSeriesMap",
"signature": "def buildFlotSeriesMap(series, uid)"
},
{
"docstring": "Builds markup to render title for txn visualizations :param c... | 5 | stack_v2_sparse_classes_30k_train_014544 | Implement the Python class `FlotBuilder` described below.
Class description:
Builds chart visualization for a delta series collections from current profile session and benchmarks The flot builder creates charts with txnId in x-axis and duration (micro seconds) in y-axis The builder creates a line chart for delta serie... | Implement the Python class `FlotBuilder` described below.
Class description:
Builds chart visualization for a delta series collections from current profile session and benchmarks The flot builder creates charts with txnId in x-axis and duration (micro seconds) in y-axis The builder creates a line chart for delta serie... | d6b67e98d4b640c98499a373425f1f009e5b9061 | <|skeleton|>
class FlotBuilder:
"""Builds chart visualization for a delta series collections from current profile session and benchmarks The flot builder creates charts with txnId in x-axis and duration (micro seconds) in y-axis The builder creates a line chart for delta series, from each pair of probes in the time... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FlotBuilder:
"""Builds chart visualization for a delta series collections from current profile session and benchmarks The flot builder creates charts with txnId in x-axis and duration (micro seconds) in y-axis The builder creates a line chart for delta series, from each pair of probes in the timeline"""
... | the_stack_v2_python_sparse | scripts/lib/xpedite/report/flot.py | dendisuhubdy/Xpedite | train | 1 |
82e9c8562484bee33918ba3d2b6f01b622fba4bb | [
"request_id = http.request.env['hr.holidays.request'].sudo().browse(int(kw['id']))\nif request_id.sudo().access_token != kw['token']:\n return http.request.render('hr_paysheet.message_template', {'message': 'Error de suplantación', 'type': 'error'})\nif request_id.sudo().state in ('OK', 'REJ'):\n return http.... | <|body_start_0|>
request_id = http.request.env['hr.holidays.request'].sudo().browse(int(kw['id']))
if request_id.sudo().access_token != kw['token']:
return http.request.render('hr_paysheet.message_template', {'message': 'Error de suplantación', 'type': 'error'})
if request_id.sudo().... | HRLeaveRequestManager | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HRLeaveRequestManager:
def holidays_accept_action(self, **kw):
"""Accept holidas request. @returns: :class:`werkzeug.wrappers.Response`"""
<|body_0|>
def holidays_decline_action(self, **kw):
"""Decline holidas request. @returns: :class:`werkzeug.wrappers.Response`"""... | stack_v2_sparse_classes_36k_train_029896 | 4,327 | no_license | [
{
"docstring": "Accept holidas request. @returns: :class:`werkzeug.wrappers.Response`",
"name": "holidays_accept_action",
"signature": "def holidays_accept_action(self, **kw)"
},
{
"docstring": "Decline holidas request. @returns: :class:`werkzeug.wrappers.Response`",
"name": "holidays_declin... | 4 | null | Implement the Python class `HRLeaveRequestManager` described below.
Class description:
Implement the HRLeaveRequestManager class.
Method signatures and docstrings:
- def holidays_accept_action(self, **kw): Accept holidas request. @returns: :class:`werkzeug.wrappers.Response`
- def holidays_decline_action(self, **kw):... | Implement the Python class `HRLeaveRequestManager` described below.
Class description:
Implement the HRLeaveRequestManager class.
Method signatures and docstrings:
- def holidays_accept_action(self, **kw): Accept holidas request. @returns: :class:`werkzeug.wrappers.Response`
- def holidays_decline_action(self, **kw):... | 778dcd6e4247949daae3a40e64025b3aaf014373 | <|skeleton|>
class HRLeaveRequestManager:
def holidays_accept_action(self, **kw):
"""Accept holidas request. @returns: :class:`werkzeug.wrappers.Response`"""
<|body_0|>
def holidays_decline_action(self, **kw):
"""Decline holidas request. @returns: :class:`werkzeug.wrappers.Response`"""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HRLeaveRequestManager:
def holidays_accept_action(self, **kw):
"""Accept holidas request. @returns: :class:`werkzeug.wrappers.Response`"""
request_id = http.request.env['hr.holidays.request'].sudo().browse(int(kw['id']))
if request_id.sudo().access_token != kw['token']:
ret... | the_stack_v2_python_sparse | hr_paysheet/controllers/hr_requests.py | cardona18/ifaco | train | 0 | |
70edcb73239287b25b55f3bf69d90b40addb98ae | [
"self.other_field_name = other_field_name\nself.values = values\nself.message = message",
"try:\n other_field = getattr(form, self.other_field_name)\n other_val = other_field.data\n for v in self.values:\n if callable(v) and v(other_val) or other_val == v:\n if not field.data or (isinst... | <|body_start_0|>
self.other_field_name = other_field_name
self.values = values
self.message = message
<|end_body_0|>
<|body_start_1|>
try:
other_field = getattr(form, self.other_field_name)
other_val = other_field.data
for v in self.values:
... | Require field if value of another field is set to a certain value. | RequiredIf | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RequiredIf:
"""Require field if value of another field is set to a certain value."""
def __init__(self, other_field_name, values, message=None):
"""Initialize the validator."""
<|body_0|>
def __call__(self, form, field):
"""Validate."""
<|body_1|>
<|end_... | stack_v2_sparse_classes_36k_train_029897 | 11,750 | no_license | [
{
"docstring": "Initialize the validator.",
"name": "__init__",
"signature": "def __init__(self, other_field_name, values, message=None)"
},
{
"docstring": "Validate.",
"name": "__call__",
"signature": "def __call__(self, form, field)"
}
] | 2 | stack_v2_sparse_classes_30k_train_011360 | Implement the Python class `RequiredIf` described below.
Class description:
Require field if value of another field is set to a certain value.
Method signatures and docstrings:
- def __init__(self, other_field_name, values, message=None): Initialize the validator.
- def __call__(self, form, field): Validate. | Implement the Python class `RequiredIf` described below.
Class description:
Require field if value of another field is set to a certain value.
Method signatures and docstrings:
- def __init__(self, other_field_name, values, message=None): Initialize the validator.
- def __call__(self, form, field): Validate.
<|skele... | 4de8910fff569fc9028300c70b63200da521ddb9 | <|skeleton|>
class RequiredIf:
"""Require field if value of another field is set to a certain value."""
def __init__(self, other_field_name, values, message=None):
"""Initialize the validator."""
<|body_0|>
def __call__(self, form, field):
"""Validate."""
<|body_1|>
<|end_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RequiredIf:
"""Require field if value of another field is set to a certain value."""
def __init__(self, other_field_name, values, message=None):
"""Initialize the validator."""
self.other_field_name = other_field_name
self.values = values
self.message = message
def __... | the_stack_v2_python_sparse | inspirehep/modules/forms/validation_utils.py | nikpap/inspire-next | train | 1 |
0c7e2ee88918a40dc36e041c36e65c899828e54b | [
"l1, l2 = (len(word1), len(word2))\nprev = [j for j in range(l2 + 1)]\nfor i in range(1, l1 + 1, 1):\n curr = [i] + [0] * l2\n for j in range(1, l2 + 1, 1):\n if word1[i - 1] == word2[j - 1]:\n curr[j] = prev[j - 1]\n else:\n curr[j] = min(prev[j - 1], prev[j], curr[j - 1])... | <|body_start_0|>
l1, l2 = (len(word1), len(word2))
prev = [j for j in range(l2 + 1)]
for i in range(1, l1 + 1, 1):
curr = [i] + [0] * l2
for j in range(1, l2 + 1, 1):
if word1[i - 1] == word2[j - 1]:
curr[j] = prev[j - 1]
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def minDistance_1d(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_0|>
def minDistance_2d(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_029898 | 2,885 | no_license | [
{
"docstring": ":type word1: str :type word2: str :rtype: int",
"name": "minDistance_1d",
"signature": "def minDistance_1d(self, word1, word2)"
},
{
"docstring": ":type word1: str :type word2: str :rtype: int",
"name": "minDistance_2d",
"signature": "def minDistance_2d(self, word1, word2... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minDistance_1d(self, word1, word2): :type word1: str :type word2: str :rtype: int
- def minDistance_2d(self, word1, word2): :type word1: str :type word2: str :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def minDistance_1d(self, word1, word2): :type word1: str :type word2: str :rtype: int
- def minDistance_2d(self, word1, word2): :type word1: str :type word2: str :rtype: int
<|s... | 9ac54720f571a4bea09d0cceb0039381a78df9e8 | <|skeleton|>
class Solution:
def minDistance_1d(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_0|>
def minDistance_2d(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def minDistance_1d(self, word1, word2):
""":type word1: str :type word2: str :rtype: int"""
l1, l2 = (len(word1), len(word2))
prev = [j for j in range(l2 + 1)]
for i in range(1, l1 + 1, 1):
curr = [i] + [0] * l2
for j in range(1, l2 + 1, 1):
... | the_stack_v2_python_sparse | code/072_edit-distance.py | linhdvu14/leetcode-solutions | train | 2 | |
dc7a40aa501886d94fdf854acb0c349d95acd0b7 | [
"self.fc = fc\nself.arrival_time = empty_value\nself.bearing = empty_value\nself.fs = fs\nself.timestamp = None\nself.recorded_data = None\nself.num_step = None\nself.dx = 0.0185\nself.c = 1480\nself.threshold = 1\nself.dead_time = 0.2\nself.num_snapshots = 4\nnum_look = 300\nself.look_directions = np.arange(num_lo... | <|body_start_0|>
self.fc = fc
self.arrival_time = empty_value
self.bearing = empty_value
self.fs = fs
self.timestamp = None
self.recorded_data = None
self.num_step = None
self.dx = 0.0185
self.c = 1480
self.threshold = 1
self.dead_t... | Download sound information from beaglebone, beamform at each ping | AcousticsNode | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AcousticsNode:
"""Download sound information from beaglebone, beamform at each ping"""
def __init__(self, fc):
"""This node requires an external source of acoustic data"""
<|body_0|>
def is_active(self, to_arm):
"""Startup and shut down communication with beagle ... | stack_v2_sparse_classes_36k_train_029899 | 5,974 | no_license | [
{
"docstring": "This node requires an external source of acoustic data",
"name": "__init__",
"signature": "def __init__(self, fc)"
},
{
"docstring": "Startup and shut down communication with beagle over lcm",
"name": "is_active",
"signature": "def is_active(self, to_arm)"
},
{
"d... | 5 | stack_v2_sparse_classes_30k_train_004326 | Implement the Python class `AcousticsNode` described below.
Class description:
Download sound information from beaglebone, beamform at each ping
Method signatures and docstrings:
- def __init__(self, fc): This node requires an external source of acoustic data
- def is_active(self, to_arm): Startup and shut down commu... | Implement the Python class `AcousticsNode` described below.
Class description:
Download sound information from beaglebone, beamform at each ping
Method signatures and docstrings:
- def __init__(self, fc): This node requires an external source of acoustic data
- def is_active(self, to_arm): Startup and shut down commu... | bfdd911d328dc730b1f6d0548bfb6a267b5e51af | <|skeleton|>
class AcousticsNode:
"""Download sound information from beaglebone, beamform at each ping"""
def __init__(self, fc):
"""This node requires an external source of acoustic data"""
<|body_0|>
def is_active(self, to_arm):
"""Startup and shut down communication with beagle ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AcousticsNode:
"""Download sound information from beaglebone, beamform at each ping"""
def __init__(self, fc):
"""This node requires an external source of acoustic data"""
self.fc = fc
self.arrival_time = empty_value
self.bearing = empty_value
self.fs = fs
... | the_stack_v2_python_sparse | zoidberg/acoustics/acoustics_node.py | sdcityrobotics/zoidberg | train | 2 |
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