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values | methods listlengths 2 6 | n_methods int64 2 6 | original_id stringlengths 38 40 ⌀ | prompt stringlengths 153 4.25k | prompted_full_text stringlengths 645 10.7k | revision_id stringlengths 40 40 | skeleton stringlengths 162 4.34k | snapshot_name stringclasses 1
value | snapshot_source_dir stringclasses 1
value | solution stringlengths 302 7.33k | source stringclasses 1
value | source_path stringlengths 4 177 | source_repo stringlengths 6 110 | split stringclasses 1
value | star_events_count int64 0 209k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
9e9a5cbfdd434932d9742249705770a7d795518d | [
"if six.PY2:\n buf = io.BytesIO()\n try:\n json.dump(self.document, buf, cls=ProvJSONEncoder, **kwargs)\n buf.seek(0, 0)\n if isinstance(stream, io.TextIOBase):\n stream.write(buf.read().decode('utf-8'))\n else:\n stream.write(buf.read())\n finally:\n ... | <|body_start_0|>
if six.PY2:
buf = io.BytesIO()
try:
json.dump(self.document, buf, cls=ProvJSONEncoder, **kwargs)
buf.seek(0, 0)
if isinstance(stream, io.TextIOBase):
stream.write(buf.read().decode('utf-8'))
... | PROV-JSON serializer for :class:`~prov.model.ProvDocument` | ProvJSONSerializer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProvJSONSerializer:
"""PROV-JSON serializer for :class:`~prov.model.ProvDocument`"""
def serialize(self, stream, **kwargs):
"""Serializes a :class:`~prov.model.ProvDocument` instance to `PROV-JSON <https://provenance.ecs.soton.ac.uk/prov-json/>`_. :param stream: Where to save the out... | stack_v2_sparse_classes_36k_train_012900 | 13,588 | permissive | [
{
"docstring": "Serializes a :class:`~prov.model.ProvDocument` instance to `PROV-JSON <https://provenance.ecs.soton.ac.uk/prov-json/>`_. :param stream: Where to save the output.",
"name": "serialize",
"signature": "def serialize(self, stream, **kwargs)"
},
{
"docstring": "Deserialize from the `P... | 2 | stack_v2_sparse_classes_30k_train_005165 | Implement the Python class `ProvJSONSerializer` described below.
Class description:
PROV-JSON serializer for :class:`~prov.model.ProvDocument`
Method signatures and docstrings:
- def serialize(self, stream, **kwargs): Serializes a :class:`~prov.model.ProvDocument` instance to `PROV-JSON <https://provenance.ecs.soton.... | Implement the Python class `ProvJSONSerializer` described below.
Class description:
PROV-JSON serializer for :class:`~prov.model.ProvDocument`
Method signatures and docstrings:
- def serialize(self, stream, **kwargs): Serializes a :class:`~prov.model.ProvDocument` instance to `PROV-JSON <https://provenance.ecs.soton.... | 3c3acc55de8ba741e673063378e6cbaf10b64c7a | <|skeleton|>
class ProvJSONSerializer:
"""PROV-JSON serializer for :class:`~prov.model.ProvDocument`"""
def serialize(self, stream, **kwargs):
"""Serializes a :class:`~prov.model.ProvDocument` instance to `PROV-JSON <https://provenance.ecs.soton.ac.uk/prov-json/>`_. :param stream: Where to save the out... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProvJSONSerializer:
"""PROV-JSON serializer for :class:`~prov.model.ProvDocument`"""
def serialize(self, stream, **kwargs):
"""Serializes a :class:`~prov.model.ProvDocument` instance to `PROV-JSON <https://provenance.ecs.soton.ac.uk/prov-json/>`_. :param stream: Where to save the output."""
... | the_stack_v2_python_sparse | env/lib/python3.6/site-packages/prov/serializers/provjson.py | Raniac/NEURO-LEARN | train | 9 |
b8411536625d17745cb8eefb753dcc0a74aaedb0 | [
"try:\n verify_token(request.headers)\nexcept Exception as err:\n ns.abort(401, message=err)\noffset = request.args.get('offset', '0')\nlimit = request.args.get('limit', '10')\norder_by = request.args.get('order_by', 'id')\norder = request.args.get('order', 'ASC')\nper_page = request.args.get('per_page', '10'... | <|body_start_0|>
try:
verify_token(request.headers)
except Exception as err:
ns.abort(401, message=err)
offset = request.args.get('offset', '0')
limit = request.args.get('limit', '10')
order_by = request.args.get('order_by', 'id')
order = request.a... | AuditList | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AuditList:
def get(self):
"""To fetch several audits. On Success it returns two custom headers: X-SOA-Total-Items, X-SOA-Total-Pages"""
<|body_0|>
def post(self):
"""To create an audit"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
try:
... | stack_v2_sparse_classes_36k_train_012901 | 7,183 | no_license | [
{
"docstring": "To fetch several audits. On Success it returns two custom headers: X-SOA-Total-Items, X-SOA-Total-Pages",
"name": "get",
"signature": "def get(self)"
},
{
"docstring": "To create an audit",
"name": "post",
"signature": "def post(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_019258 | Implement the Python class `AuditList` described below.
Class description:
Implement the AuditList class.
Method signatures and docstrings:
- def get(self): To fetch several audits. On Success it returns two custom headers: X-SOA-Total-Items, X-SOA-Total-Pages
- def post(self): To create an audit | Implement the Python class `AuditList` described below.
Class description:
Implement the AuditList class.
Method signatures and docstrings:
- def get(self): To fetch several audits. On Success it returns two custom headers: X-SOA-Total-Items, X-SOA-Total-Pages
- def post(self): To create an audit
<|skeleton|>
class ... | e00610fac26ef3ca078fd037c0649b70fa0e9a09 | <|skeleton|>
class AuditList:
def get(self):
"""To fetch several audits. On Success it returns two custom headers: X-SOA-Total-Items, X-SOA-Total-Pages"""
<|body_0|>
def post(self):
"""To create an audit"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AuditList:
def get(self):
"""To fetch several audits. On Success it returns two custom headers: X-SOA-Total-Items, X-SOA-Total-Pages"""
try:
verify_token(request.headers)
except Exception as err:
ns.abort(401, message=err)
offset = request.args.get('offs... | the_stack_v2_python_sparse | DOS/soa/service/genl/endpoints/audits.py | Telematica/knight-rider | train | 1 | |
b562544176835ff6c5e01f5bbf6eeaac59ff8634 | [
"self.primary = None\nself.secondary = None\nself.initialize(jconfig, kwargs)",
"cachesize = jconfig.get('cachesize', None)\nadminuser = jconfig.get('adminuser', None)\nif 'primary' in jconfig:\n self.primary = self.create_journal(jconfig['primary'], kwargs, cachesize, adminuser)\nif 'secondary' in jconfig:\n ... | <|body_start_0|>
self.primary = None
self.secondary = None
self.initialize(jconfig, kwargs)
<|end_body_0|>
<|body_start_1|>
cachesize = jconfig.get('cachesize', None)
adminuser = jconfig.get('adminuser', None)
if 'primary' in jconfig:
self.primary = self.crea... | Creates journal objects for primary and secondary | Journal | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Journal:
"""Creates journal objects for primary and secondary"""
def __init__(self, jconfig, kwargs):
"""Constructor for journal"""
<|body_0|>
def initialize(self, jconfig, kwargs):
"""creates journal objects"""
<|body_1|>
def create_journal(self, jc... | stack_v2_sparse_classes_36k_train_012902 | 2,954 | permissive | [
{
"docstring": "Constructor for journal",
"name": "__init__",
"signature": "def __init__(self, jconfig, kwargs)"
},
{
"docstring": "creates journal objects",
"name": "initialize",
"signature": "def initialize(self, jconfig, kwargs)"
},
{
"docstring": "get the name and create obj"... | 5 | stack_v2_sparse_classes_30k_train_017762 | Implement the Python class `Journal` described below.
Class description:
Creates journal objects for primary and secondary
Method signatures and docstrings:
- def __init__(self, jconfig, kwargs): Constructor for journal
- def initialize(self, jconfig, kwargs): creates journal objects
- def create_journal(self, jconf,... | Implement the Python class `Journal` described below.
Class description:
Creates journal objects for primary and secondary
Method signatures and docstrings:
- def __init__(self, jconfig, kwargs): Constructor for journal
- def initialize(self, jconfig, kwargs): creates journal objects
- def create_journal(self, jconf,... | a233ad85b56ff43a81544386a0730bee590de8fc | <|skeleton|>
class Journal:
"""Creates journal objects for primary and secondary"""
def __init__(self, jconfig, kwargs):
"""Constructor for journal"""
<|body_0|>
def initialize(self, jconfig, kwargs):
"""creates journal objects"""
<|body_1|>
def create_journal(self, jc... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Journal:
"""Creates journal objects for primary and secondary"""
def __init__(self, jconfig, kwargs):
"""Constructor for journal"""
self.primary = None
self.secondary = None
self.initialize(jconfig, kwargs)
def initialize(self, jconfig, kwargs):
"""creates jou... | the_stack_v2_python_sparse | lib/python/journal/mjournal.py | lisajoseph/journal | train | 0 |
217a341aee4b7786ca130dac10d7d26db2465c58 | [
"ext = []\nif self._is_position(global_step, 'start') or self._is_position(global_step, 'end'):\n ext.append(extensions.BatchGrad())\nreturn ext",
"info = {}\nif pos in ['start', 'end']:\n info['f'] = batch_loss.item()\n info['var_f'] = get_individual_losses(global_step).var().item()\n info['params'] ... | <|body_start_0|>
ext = []
if self._is_position(global_step, 'start') or self._is_position(global_step, 'end'):
ext.append(extensions.BatchGrad())
return ext
<|end_body_0|>
<|body_start_1|>
info = {}
if pos in ['start', 'end']:
info['f'] = batch_loss.item(... | Compute α but requires storing individual gradients. | AlphaExpensive | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AlphaExpensive:
"""Compute α but requires storing individual gradients."""
def extensions(self, global_step):
"""Return list of BackPACK extensions required for the computation. Args: global_step (int): The current iteration number. Returns: list: (Potentially empty) list with requir... | stack_v2_sparse_classes_36k_train_012903 | 16,011 | permissive | [
{
"docstring": "Return list of BackPACK extensions required for the computation. Args: global_step (int): The current iteration number. Returns: list: (Potentially empty) list with required BackPACK quantities.",
"name": "extensions",
"signature": "def extensions(self, global_step)"
},
{
"docstr... | 2 | stack_v2_sparse_classes_30k_train_018631 | Implement the Python class `AlphaExpensive` described below.
Class description:
Compute α but requires storing individual gradients.
Method signatures and docstrings:
- def extensions(self, global_step): Return list of BackPACK extensions required for the computation. Args: global_step (int): The current iteration nu... | Implement the Python class `AlphaExpensive` described below.
Class description:
Compute α but requires storing individual gradients.
Method signatures and docstrings:
- def extensions(self, global_step): Return list of BackPACK extensions required for the computation. Args: global_step (int): The current iteration nu... | 5bd5ab3cda03eda0b0bf276f29d5c28b83d70b06 | <|skeleton|>
class AlphaExpensive:
"""Compute α but requires storing individual gradients."""
def extensions(self, global_step):
"""Return list of BackPACK extensions required for the computation. Args: global_step (int): The current iteration number. Returns: list: (Potentially empty) list with requir... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AlphaExpensive:
"""Compute α but requires storing individual gradients."""
def extensions(self, global_step):
"""Return list of BackPACK extensions required for the computation. Args: global_step (int): The current iteration number. Returns: list: (Potentially empty) list with required BackPACK q... | the_stack_v2_python_sparse | cockpit/quantities/alpha.py | MeNicefellow/cockpit | train | 0 |
456d90e63c256efdb2c3fedddd082180c66e7793 | [
"self.transforms = self.trainer.hps.dataset.transforms\nself.transform_interval = self.trainer.epochs // len(self.transforms[0]['all_para'].keys())\nself.hps = self.trainer.hps",
"config_id = str(epoch // self.transform_interval)\ntransform_list = self.transforms[0]['all_para'][config_id]\nself.hps.dataset.transf... | <|body_start_0|>
self.transforms = self.trainer.hps.dataset.transforms
self.transform_interval = self.trainer.epochs // len(self.transforms[0]['all_para'].keys())
self.hps = self.trainer.hps
<|end_body_0|>
<|body_start_1|>
config_id = str(epoch // self.transform_interval)
transf... | Construct the trainer of Adelaide-EA. | PbaTrainerCallback | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PbaTrainerCallback:
"""Construct the trainer of Adelaide-EA."""
def before_train(self, logs=None):
"""Be called before the training process."""
<|body_0|>
def before_epoch(self, epoch, logs=None):
"""Be called before epoch."""
<|body_1|>
<|end_skeleton|>... | stack_v2_sparse_classes_36k_train_012904 | 1,464 | permissive | [
{
"docstring": "Be called before the training process.",
"name": "before_train",
"signature": "def before_train(self, logs=None)"
},
{
"docstring": "Be called before epoch.",
"name": "before_epoch",
"signature": "def before_epoch(self, epoch, logs=None)"
}
] | 2 | null | Implement the Python class `PbaTrainerCallback` described below.
Class description:
Construct the trainer of Adelaide-EA.
Method signatures and docstrings:
- def before_train(self, logs=None): Be called before the training process.
- def before_epoch(self, epoch, logs=None): Be called before epoch. | Implement the Python class `PbaTrainerCallback` described below.
Class description:
Construct the trainer of Adelaide-EA.
Method signatures and docstrings:
- def before_train(self, logs=None): Be called before the training process.
- def before_epoch(self, epoch, logs=None): Be called before epoch.
<|skeleton|>
clas... | 52b53582fe7df95d7aacc8425013fd18645d079f | <|skeleton|>
class PbaTrainerCallback:
"""Construct the trainer of Adelaide-EA."""
def before_train(self, logs=None):
"""Be called before the training process."""
<|body_0|>
def before_epoch(self, epoch, logs=None):
"""Be called before epoch."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PbaTrainerCallback:
"""Construct the trainer of Adelaide-EA."""
def before_train(self, logs=None):
"""Be called before the training process."""
self.transforms = self.trainer.hps.dataset.transforms
self.transform_interval = self.trainer.epochs // len(self.transforms[0]['all_para']... | the_stack_v2_python_sparse | vega/algorithms/data_augmentation/pba_trainer_callback.py | yiziqi/vega | train | 0 |
d161974b8923897fd21d8e0879fbee9d8dc65081 | [
"auto = input('是否静音(Y/n):').strip()\nif auto in ['y', 'Y', '']:\n OPTIONS().Mute_Audio = True\nelse:\n OPTIONS().Mute_Audio = False",
"headless = input('是否显示自动化过程(y/N):').strip()\nif headless in ['y', 'Y']:\n OPTIONS().Headless = False\nelse:\n OPTIONS().Headless = True",
"token = input('是否持久化登录(Y/n... | <|body_start_0|>
auto = input('是否静音(Y/n):').strip()
if auto in ['y', 'Y', '']:
OPTIONS().Mute_Audio = True
else:
OPTIONS().Mute_Audio = False
<|end_body_0|>
<|body_start_1|>
headless = input('是否显示自动化过程(y/N):').strip()
if headless in ['y', 'Y']:
... | 选项管理类 | OPTIONS_MANAGE | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OPTIONS_MANAGE:
"""选项管理类"""
def __Auto(cls) -> None:
"""__Auto() -> None 禁音选项(默认: True) :return: None"""
<|body_0|>
def __Headless(cls) -> None:
"""__Headless() -> None 显示过程选项(默认: False) :return: None"""
<|body_1|>
def __Token(cls) -> None:
"... | stack_v2_sparse_classes_36k_train_012905 | 3,572 | permissive | [
{
"docstring": "__Auto() -> None 禁音选项(默认: True) :return: None",
"name": "__Auto",
"signature": "def __Auto(cls) -> None"
},
{
"docstring": "__Headless() -> None 显示过程选项(默认: False) :return: None",
"name": "__Headless",
"signature": "def __Headless(cls) -> None"
},
{
"docstring": "_... | 6 | stack_v2_sparse_classes_30k_train_016227 | Implement the Python class `OPTIONS_MANAGE` described below.
Class description:
选项管理类
Method signatures and docstrings:
- def __Auto(cls) -> None: __Auto() -> None 禁音选项(默认: True) :return: None
- def __Headless(cls) -> None: __Headless() -> None 显示过程选项(默认: False) :return: None
- def __Token(cls) -> None: __Token() -> ... | Implement the Python class `OPTIONS_MANAGE` described below.
Class description:
选项管理类
Method signatures and docstrings:
- def __Auto(cls) -> None: __Auto() -> None 禁音选项(默认: True) :return: None
- def __Headless(cls) -> None: __Headless() -> None 显示过程选项(默认: False) :return: None
- def __Token(cls) -> None: __Token() -> ... | 9e2a023917b86460fb02984aed9fe638c3d38dd4 | <|skeleton|>
class OPTIONS_MANAGE:
"""选项管理类"""
def __Auto(cls) -> None:
"""__Auto() -> None 禁音选项(默认: True) :return: None"""
<|body_0|>
def __Headless(cls) -> None:
"""__Headless() -> None 显示过程选项(默认: False) :return: None"""
<|body_1|>
def __Token(cls) -> None:
"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OPTIONS_MANAGE:
"""选项管理类"""
def __Auto(cls) -> None:
"""__Auto() -> None 禁音选项(默认: True) :return: None"""
auto = input('是否静音(Y/n):').strip()
if auto in ['y', 'Y', '']:
OPTIONS().Mute_Audio = True
else:
OPTIONS().Mute_Audio = False
def __Headless... | the_stack_v2_python_sparse | inside/Options/Options_Manage.py | lifansama/learning-power | train | 1 |
7f52605780f16f2091e4ec8303581edb867c3d3a | [
"super().__init__()\nself.every_n_epochs = every_n_epochs\nself.dataloader = dataloader\nself.measures = measures\nself.latest = {measure.name: 0 for measure in measures}",
"if (trainer.current_epoch + 1) % self.every_n_epochs == 0:\n msgs = []\n for sender_imgs, receiver_imgs, target in self.dataloader:\n ... | <|body_start_0|>
super().__init__()
self.every_n_epochs = every_n_epochs
self.dataloader = dataloader
self.measures = measures
self.latest = {measure.name: 0 for measure in measures}
<|end_body_0|>
<|body_start_1|>
if (trainer.current_epoch + 1) % self.every_n_epochs == ... | Creates a plot based around a digit | MeasureCallbacks | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MeasureCallbacks:
"""Creates a plot based around a digit"""
def __init__(self, dataloader, measures, every_n_epochs=1):
"""Inputs: batch_size - Number of images to generate every_n_epochs - Only save those images every N epochs (otherwise tensorboard gets quite large) save_to_disk - ... | stack_v2_sparse_classes_36k_train_012906 | 8,112 | no_license | [
{
"docstring": "Inputs: batch_size - Number of images to generate every_n_epochs - Only save those images every N epochs (otherwise tensorboard gets quite large) save_to_disk - If True, the samples and image means should be saved to disk as well.",
"name": "__init__",
"signature": "def __init__(self, da... | 2 | stack_v2_sparse_classes_30k_train_004518 | Implement the Python class `MeasureCallbacks` described below.
Class description:
Creates a plot based around a digit
Method signatures and docstrings:
- def __init__(self, dataloader, measures, every_n_epochs=1): Inputs: batch_size - Number of images to generate every_n_epochs - Only save those images every N epochs... | Implement the Python class `MeasureCallbacks` described below.
Class description:
Creates a plot based around a digit
Method signatures and docstrings:
- def __init__(self, dataloader, measures, every_n_epochs=1): Inputs: batch_size - Number of images to generate every_n_epochs - Only save those images every N epochs... | 5189b65690da28f6a8118b7fc63e24c809e15c0d | <|skeleton|>
class MeasureCallbacks:
"""Creates a plot based around a digit"""
def __init__(self, dataloader, measures, every_n_epochs=1):
"""Inputs: batch_size - Number of images to generate every_n_epochs - Only save those images every N epochs (otherwise tensorboard gets quite large) save_to_disk - ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MeasureCallbacks:
"""Creates a plot based around a digit"""
def __init__(self, dataloader, measures, every_n_epochs=1):
"""Inputs: batch_size - Number of images to generate every_n_epochs - Only save those images every N epochs (otherwise tensorboard gets quite large) save_to_disk - If True, the ... | the_stack_v2_python_sparse | callbacks/msg_callback.py | gersonfoks/NLP2EmergentLanguage | train | 0 |
22c21443c1937c665d36225b929d2e63180b370a | [
"if not os.path.exists('/home/mziaeefard/nas/human-ai-dialog/vilbert/data2/conceptnet/processed/numberbatch_en.gensim'):\n print(colored('Processing the `Numberbatch` dataset for the first time...', 'yellow'))\n if not os.path.exists('/home/mziaeefard/nas/human-ai-dialog/vilbert/data2/conceptnet/raw/numberbat... | <|body_start_0|>
if not os.path.exists('/home/mziaeefard/nas/human-ai-dialog/vilbert/data2/conceptnet/processed/numberbatch_en.gensim'):
print(colored('Processing the `Numberbatch` dataset for the first time...', 'yellow'))
if not os.path.exists('/home/mziaeefard/nas/human-ai-dialog/vilb... | Class to get the Numberbatch embeddings of words | NumberbatchConverter | [
"MIT",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NumberbatchConverter:
"""Class to get the Numberbatch embeddings of words"""
def __init__(self):
"""Loads the Numberbatch model"""
<|body_0|>
def convert_word_to_embedding(self, word):
"""Given a word, returns its Numberbatch embedding"""
<|body_1|>
<|en... | stack_v2_sparse_classes_36k_train_012907 | 4,555 | permissive | [
{
"docstring": "Loads the Numberbatch model",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Given a word, returns its Numberbatch embedding",
"name": "convert_word_to_embedding",
"signature": "def convert_word_to_embedding(self, word)"
}
] | 2 | stack_v2_sparse_classes_30k_train_020425 | Implement the Python class `NumberbatchConverter` described below.
Class description:
Class to get the Numberbatch embeddings of words
Method signatures and docstrings:
- def __init__(self): Loads the Numberbatch model
- def convert_word_to_embedding(self, word): Given a word, returns its Numberbatch embedding | Implement the Python class `NumberbatchConverter` described below.
Class description:
Class to get the Numberbatch embeddings of words
Method signatures and docstrings:
- def __init__(self): Loads the Numberbatch model
- def convert_word_to_embedding(self, word): Given a word, returns its Numberbatch embedding
<|ske... | 0fb558af7df8c61be47bcf278e30cdf10315b572 | <|skeleton|>
class NumberbatchConverter:
"""Class to get the Numberbatch embeddings of words"""
def __init__(self):
"""Loads the Numberbatch model"""
<|body_0|>
def convert_word_to_embedding(self, word):
"""Given a word, returns its Numberbatch embedding"""
<|body_1|>
<|en... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NumberbatchConverter:
"""Class to get the Numberbatch embeddings of words"""
def __init__(self):
"""Loads the Numberbatch model"""
if not os.path.exists('/home/mziaeefard/nas/human-ai-dialog/vilbert/data2/conceptnet/processed/numberbatch_en.gensim'):
print(colored('Processing ... | the_stack_v2_python_sparse | conceptBert/vilbert/knowledge_graph/create_embedding_files.py | liubo12/ConceptBERT | train | 0 |
51f7383f275e5e661f3bef05fdcf2122d0ab3bb6 | [
"values = []\nfor _ in range(5):\n index = random.randint(low, high)\n values.append((index, seq[index]))\nvalues.sort(key=lambda item: item[1])\nreturn values[2][0]",
"index = self.five_sample(seq, low, high)\nseq[low], seq[index] = (seq[index], seq[low])\ni, j = (low + 1, high)\nval = seq[low]\nwhile 1:\n... | <|body_start_0|>
values = []
for _ in range(5):
index = random.randint(low, high)
values.append((index, seq[index]))
values.sort(key=lambda item: item[1])
return values[2][0]
<|end_body_0|>
<|body_start_1|>
index = self.five_sample(seq, low, high)
... | Quick sort non-recursive version. | QuickSortNonRecursive | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QuickSortNonRecursive:
"""Quick sort non-recursive version."""
def five_sample(self, seq: MutableSequence[CT], low: int, high: int) -> int:
"""Cherry pick median number of randomly picked five numbers between `low` and `high`. Args: seq (MutableSequence[CT]): input array low (int): s... | stack_v2_sparse_classes_36k_train_012908 | 8,934 | no_license | [
{
"docstring": "Cherry pick median number of randomly picked five numbers between `low` and `high`. Args: seq (MutableSequence[CT]): input array low (int): start index high (int): end index Returns: int: index of median number of five numbers",
"name": "five_sample",
"signature": "def five_sample(self, ... | 3 | stack_v2_sparse_classes_30k_train_011201 | Implement the Python class `QuickSortNonRecursive` described below.
Class description:
Quick sort non-recursive version.
Method signatures and docstrings:
- def five_sample(self, seq: MutableSequence[CT], low: int, high: int) -> int: Cherry pick median number of randomly picked five numbers between `low` and `high`. ... | Implement the Python class `QuickSortNonRecursive` described below.
Class description:
Quick sort non-recursive version.
Method signatures and docstrings:
- def five_sample(self, seq: MutableSequence[CT], low: int, high: int) -> int: Cherry pick median number of randomly picked five numbers between `low` and `high`. ... | d3ccd86c93016c7fee270ad02e1a823d205cea80 | <|skeleton|>
class QuickSortNonRecursive:
"""Quick sort non-recursive version."""
def five_sample(self, seq: MutableSequence[CT], low: int, high: int) -> int:
"""Cherry pick median number of randomly picked five numbers between `low` and `high`. Args: seq (MutableSequence[CT]): input array low (int): s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QuickSortNonRecursive:
"""Quick sort non-recursive version."""
def five_sample(self, seq: MutableSequence[CT], low: int, high: int) -> int:
"""Cherry pick median number of randomly picked five numbers between `low` and `high`. Args: seq (MutableSequence[CT]): input array low (int): start index hi... | the_stack_v2_python_sparse | chapter_2/module_2_3.py | ChangeMyUsername/algorithms-sedgewick-python | train | 330 |
9b5f91d8280b5fdfd2751839749f1308b94b103a | [
"from math import e, log\nif x < 2:\n return x\nleft = int(e ** (0.5 * log(x)))\nright = left + 1\nreturn left if right * right > x else right",
"if x < 2:\n return x\nleft, right = (0, x // 2)\nwhile left <= right:\n pivot = left + (right - left) // 2\n num = pivot * pivot\n if num < x:\n l... | <|body_start_0|>
from math import e, log
if x < 2:
return x
left = int(e ** (0.5 * log(x)))
right = left + 1
return left if right * right > x else right
<|end_body_0|>
<|body_start_1|>
if x < 2:
return x
left, right = (0, x // 2)
w... | SquareRoot | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SquareRoot:
def results(self, x: int) -> int:
"""Approach: Pocket Calculator Time Complexity: O(1) Space Complexity: O(1) :param x: :return:"""
<|body_0|>
def result(self, x: int) -> int:
"""Approach: Binary Search 2 to x // 2 Time Complexity: O(log N) Space Complexi... | stack_v2_sparse_classes_36k_train_012909 | 1,829 | no_license | [
{
"docstring": "Approach: Pocket Calculator Time Complexity: O(1) Space Complexity: O(1) :param x: :return:",
"name": "results",
"signature": "def results(self, x: int) -> int"
},
{
"docstring": "Approach: Binary Search 2 to x // 2 Time Complexity: O(log N) Space Complexity: O(1) :param x: :retu... | 3 | null | Implement the Python class `SquareRoot` described below.
Class description:
Implement the SquareRoot class.
Method signatures and docstrings:
- def results(self, x: int) -> int: Approach: Pocket Calculator Time Complexity: O(1) Space Complexity: O(1) :param x: :return:
- def result(self, x: int) -> int: Approach: Bin... | Implement the Python class `SquareRoot` described below.
Class description:
Implement the SquareRoot class.
Method signatures and docstrings:
- def results(self, x: int) -> int: Approach: Pocket Calculator Time Complexity: O(1) Space Complexity: O(1) :param x: :return:
- def result(self, x: int) -> int: Approach: Bin... | 65cc78b5afa0db064f9fe8f06597e3e120f7363d | <|skeleton|>
class SquareRoot:
def results(self, x: int) -> int:
"""Approach: Pocket Calculator Time Complexity: O(1) Space Complexity: O(1) :param x: :return:"""
<|body_0|>
def result(self, x: int) -> int:
"""Approach: Binary Search 2 to x // 2 Time Complexity: O(log N) Space Complexi... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SquareRoot:
def results(self, x: int) -> int:
"""Approach: Pocket Calculator Time Complexity: O(1) Space Complexity: O(1) :param x: :return:"""
from math import e, log
if x < 2:
return x
left = int(e ** (0.5 * log(x)))
right = left + 1
return left if... | the_stack_v2_python_sparse | revisited/math_and_strings/math/square_root_x.py | Shiv2157k/leet_code | train | 1 | |
82b276e49de0b47e14b4404a108cc2cab7923b18 | [
"self.key = 'unknown scr'\nself.interval = 100\nself.start_delay = True\nself.persistent = True",
"from evennia.utils.utils import calledby\ncallback = self.db.callback\nif callback:\n callback()\nseconds = real_seconds_until(**self.db.gametime)\nself.start(interval=seconds, force_restart=True)"
] | <|body_start_0|>
self.key = 'unknown scr'
self.interval = 100
self.start_delay = True
self.persistent = True
<|end_body_0|>
<|body_start_1|>
from evennia.utils.utils import calledby
callback = self.db.callback
if callback:
callback()
seconds =... | Gametime-sensitive script. | GametimeScript | [
"BSD-3-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GametimeScript:
"""Gametime-sensitive script."""
def at_script_creation(self):
"""The script is created."""
<|body_0|>
def at_repeat(self):
"""Call the callback and reset interval."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.key = 'unkn... | stack_v2_sparse_classes_36k_train_012910 | 10,390 | permissive | [
{
"docstring": "The script is created.",
"name": "at_script_creation",
"signature": "def at_script_creation(self)"
},
{
"docstring": "Call the callback and reset interval.",
"name": "at_repeat",
"signature": "def at_repeat(self)"
}
] | 2 | null | Implement the Python class `GametimeScript` described below.
Class description:
Gametime-sensitive script.
Method signatures and docstrings:
- def at_script_creation(self): The script is created.
- def at_repeat(self): Call the callback and reset interval. | Implement the Python class `GametimeScript` described below.
Class description:
Gametime-sensitive script.
Method signatures and docstrings:
- def at_script_creation(self): The script is created.
- def at_repeat(self): Call the callback and reset interval.
<|skeleton|>
class GametimeScript:
"""Gametime-sensitive... | b3ca58b5c1325a3bf57051dfe23560a08d2947b7 | <|skeleton|>
class GametimeScript:
"""Gametime-sensitive script."""
def at_script_creation(self):
"""The script is created."""
<|body_0|>
def at_repeat(self):
"""Call the callback and reset interval."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GametimeScript:
"""Gametime-sensitive script."""
def at_script_creation(self):
"""The script is created."""
self.key = 'unknown scr'
self.interval = 100
self.start_delay = True
self.persistent = True
def at_repeat(self):
"""Call the callback and reset ... | the_stack_v2_python_sparse | evennia/contrib/base_systems/custom_gametime/custom_gametime.py | evennia/evennia | train | 1,781 |
01c98ece8d020e1daf205954a6ccbdcf2414de3a | [
"super(PlotsMenuEntry, self).__init__(**params)\nself.plotgroup = plotgroup\nif isinstance(self.plotgroup, FeatureCurvePlotGroup):\n class_ = plotpanel_classes.get(self.plotgroup.name, FeatureCurvePanel)\nself.class_ = plotpanel_classes.get(self.plotgroup.name, class_)",
"new_plotgroup = copy.deepcopy(self.plo... | <|body_start_0|>
super(PlotsMenuEntry, self).__init__(**params)
self.plotgroup = plotgroup
if isinstance(self.plotgroup, FeatureCurvePlotGroup):
class_ = plotpanel_classes.get(self.plotgroup.name, FeatureCurvePanel)
self.class_ = plotpanel_classes.get(self.plotgroup.name, cla... | Stores information about a Plots menu command (including the command itself, and the plotgroup template). | PlotsMenuEntry | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause",
"LicenseRef-scancode-free-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PlotsMenuEntry:
"""Stores information about a Plots menu command (including the command itself, and the plotgroup template)."""
def __init__(self, plotgroup, class_=TemplatePlotGroupPanel, **params):
"""Store the template, and set the class that will be created by this menu entry If ... | stack_v2_sparse_classes_36k_train_012911 | 29,423 | permissive | [
{
"docstring": "Store the template, and set the class that will be created by this menu entry If users want to extend the Plot Panel classes, then they should add entries to the plotpanel_classes dictionary. If no entry is defined there, then the default class is used. The class_ is overridden for any special c... | 2 | stack_v2_sparse_classes_30k_train_000908 | Implement the Python class `PlotsMenuEntry` described below.
Class description:
Stores information about a Plots menu command (including the command itself, and the plotgroup template).
Method signatures and docstrings:
- def __init__(self, plotgroup, class_=TemplatePlotGroupPanel, **params): Store the template, and ... | Implement the Python class `PlotsMenuEntry` described below.
Class description:
Stores information about a Plots menu command (including the command itself, and the plotgroup template).
Method signatures and docstrings:
- def __init__(self, plotgroup, class_=TemplatePlotGroupPanel, **params): Store the template, and ... | 1e097e2df9938a6ce9f48cefbf25672cbbf9a4db | <|skeleton|>
class PlotsMenuEntry:
"""Stores information about a Plots menu command (including the command itself, and the plotgroup template)."""
def __init__(self, plotgroup, class_=TemplatePlotGroupPanel, **params):
"""Store the template, and set the class that will be created by this menu entry If ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PlotsMenuEntry:
"""Stores information about a Plots menu command (including the command itself, and the plotgroup template)."""
def __init__(self, plotgroup, class_=TemplatePlotGroupPanel, **params):
"""Store the template, and set the class that will be created by this menu entry If users want to... | the_stack_v2_python_sparse | topo/tkgui/topoconsole.py | ioam/topographica | train | 43 |
150d86011742bac399d67bd7567753291e52d81f | [
"self.left = []\nself.right = []\nself.lc, self.rc = (0, 0)",
"if self.lc == 0:\n heappush(self.left, -num)\n self.lc += 1\nelif num <= -self.left[0] and self.lc == self.rc:\n heappush(self.left, -num)\n self.lc += 1\nelif num <= -self.left[0] and self.lc == self.rc + 1:\n heappush(self.left, -num)... | <|body_start_0|>
self.left = []
self.right = []
self.lc, self.rc = (0, 0)
<|end_body_0|>
<|body_start_1|>
if self.lc == 0:
heappush(self.left, -num)
self.lc += 1
elif num <= -self.left[0] and self.lc == self.rc:
heappush(self.left, -num)
... | MedianFinder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MedianFinder:
def __init__(self):
"""initialize your data structure here."""
<|body_0|>
def addNum(self, num):
""":type num: int :rtype: void"""
<|body_1|>
def findMedian(self):
""":rtype: float"""
<|body_2|>
<|end_skeleton|>
<|body_sta... | stack_v2_sparse_classes_36k_train_012912 | 1,378 | no_license | [
{
"docstring": "initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": ":type num: int :rtype: void",
"name": "addNum",
"signature": "def addNum(self, num)"
},
{
"docstring": ":rtype: float",
"name": "findMedian",
"s... | 3 | null | Implement the Python class `MedianFinder` described below.
Class description:
Implement the MedianFinder class.
Method signatures and docstrings:
- def __init__(self): initialize your data structure here.
- def addNum(self, num): :type num: int :rtype: void
- def findMedian(self): :rtype: float | Implement the Python class `MedianFinder` described below.
Class description:
Implement the MedianFinder class.
Method signatures and docstrings:
- def __init__(self): initialize your data structure here.
- def addNum(self, num): :type num: int :rtype: void
- def findMedian(self): :rtype: float
<|skeleton|>
class Me... | 3bfee704adb1d94efc8e531b732cf06c4f8aef0f | <|skeleton|>
class MedianFinder:
def __init__(self):
"""initialize your data structure here."""
<|body_0|>
def addNum(self, num):
""":type num: int :rtype: void"""
<|body_1|>
def findMedian(self):
""":rtype: float"""
<|body_2|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MedianFinder:
def __init__(self):
"""initialize your data structure here."""
self.left = []
self.right = []
self.lc, self.rc = (0, 0)
def addNum(self, num):
""":type num: int :rtype: void"""
if self.lc == 0:
heappush(self.left, -num)
... | the_stack_v2_python_sparse | stream_median.py | zopepy/leetcode | train | 0 | |
4f4f530cda1eff18842990d24468d879711a7aa1 | [
"self.input_type = input_type\nif self.input_type == 'file':\n self.raw_EEG_obj = mne.io.read_raw_fif(file_path, preload=True)\n max_time = self.raw_EEG_obj.times.max()\n self.raw_EEG_obj.crop(28, max_time)\n self.raw_EEG_obj\n self.timestamp = 0.0\n cal_raw = self.raw_EEG_obj.copy()\n cal_raw ... | <|body_start_0|>
self.input_type = input_type
if self.input_type == 'file':
self.raw_EEG_obj = mne.io.read_raw_fif(file_path, preload=True)
max_time = self.raw_EEG_obj.times.max()
self.raw_EEG_obj.crop(28, max_time)
self.raw_EEG_obj
self.timest... | This class is used to return the EEG data in real time. Attribute: raw_EEG_obj: the data for file input. MNE object. timestamp: the current time. how much second. features: the EEG features. | EEGReader | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EEGReader:
"""This class is used to return the EEG data in real time. Attribute: raw_EEG_obj: the data for file input. MNE object. timestamp: the current time. how much second. features: the EEG features."""
def __init__(self, input_type, file_path=None):
"""Arguments: input_type: 'f... | stack_v2_sparse_classes_36k_train_012913 | 16,328 | permissive | [
{
"docstring": "Arguments: input_type: 'file' indicates that the stream is from file. In other case, the stream will from the 'Emotiv insight' device.",
"name": "__init__",
"signature": "def __init__(self, input_type, file_path=None)"
},
{
"docstring": "Return: EEG data: the EEG data timestamp: ... | 2 | stack_v2_sparse_classes_30k_train_001879 | Implement the Python class `EEGReader` described below.
Class description:
This class is used to return the EEG data in real time. Attribute: raw_EEG_obj: the data for file input. MNE object. timestamp: the current time. how much second. features: the EEG features.
Method signatures and docstrings:
- def __init__(sel... | Implement the Python class `EEGReader` described below.
Class description:
This class is used to return the EEG data in real time. Attribute: raw_EEG_obj: the data for file input. MNE object. timestamp: the current time. how much second. features: the EEG features.
Method signatures and docstrings:
- def __init__(sel... | 531f646dcb493dce2575af3b9d77403ebc1f4a35 | <|skeleton|>
class EEGReader:
"""This class is used to return the EEG data in real time. Attribute: raw_EEG_obj: the data for file input. MNE object. timestamp: the current time. how much second. features: the EEG features."""
def __init__(self, input_type, file_path=None):
"""Arguments: input_type: 'f... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EEGReader:
"""This class is used to return the EEG data in real time. Attribute: raw_EEG_obj: the data for file input. MNE object. timestamp: the current time. how much second. features: the EEG features."""
def __init__(self, input_type, file_path=None):
"""Arguments: input_type: 'file' indicate... | the_stack_v2_python_sparse | MindLink-Eumpy/real_time_detection/GUI/MLE_tool/tool.py | wozu-dichter/MindLink-Explorer | train | 0 |
3e9ec4b03d342eeccacfef72c5a9b35ab1b56fe5 | [
"for member in [self.team1_admin, self.team1_member, self.common_member]:\n self.client.force_login(member)\n response = self.client.get(self.list_url)\n self.assertContains(response, 'Categories for %s' % self.team1.name, status_code=200)\n for category in self.team1.categories.all():\n self.ass... | <|body_start_0|>
for member in [self.team1_admin, self.team1_member, self.common_member]:
self.client.force_login(member)
response = self.client.get(self.list_url)
self.assertContains(response, 'Categories for %s' % self.team1.name, status_code=200)
for category i... | Test CategoryListView | CategoryListViewTest | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CategoryListViewTest:
"""Test CategoryListView"""
def test_category_list_member(self):
"""Assert that all the right categories are listed for the team admin and regular members"""
<|body_0|>
def test_category_list_nonmember(self):
"""Assert that non-members can n... | stack_v2_sparse_classes_36k_train_012914 | 9,408 | permissive | [
{
"docstring": "Assert that all the right categories are listed for the team admin and regular members",
"name": "test_category_list_member",
"signature": "def test_category_list_member(self)"
},
{
"docstring": "Assert that non-members can not list categories",
"name": "test_category_list_no... | 2 | stack_v2_sparse_classes_30k_train_010612 | Implement the Python class `CategoryListViewTest` described below.
Class description:
Test CategoryListView
Method signatures and docstrings:
- def test_category_list_member(self): Assert that all the right categories are listed for the team admin and regular members
- def test_category_list_nonmember(self): Assert t... | Implement the Python class `CategoryListViewTest` described below.
Class description:
Test CategoryListView
Method signatures and docstrings:
- def test_category_list_member(self): Assert that all the right categories are listed for the team admin and regular members
- def test_category_list_nonmember(self): Assert t... | b3a61462d46d33de25fb96c029b2bd822001b669 | <|skeleton|>
class CategoryListViewTest:
"""Test CategoryListView"""
def test_category_list_member(self):
"""Assert that all the right categories are listed for the team admin and regular members"""
<|body_0|>
def test_category_list_nonmember(self):
"""Assert that non-members can n... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CategoryListViewTest:
"""Test CategoryListView"""
def test_category_list_member(self):
"""Assert that all the right categories are listed for the team admin and regular members"""
for member in [self.team1_admin, self.team1_member, self.common_member]:
self.client.force_login(... | the_stack_v2_python_sparse | src/category/tests.py | tykling/socialrating | train | 3 |
10629a5bc786ff7bf58c5ff8c27ddcbe824853a8 | [
"startTime = datetime.datetime.now()\nclient = dml.pymongo.MongoClient()\nrepo = client.repo\nrepo.authenticate('kobesay', 'kobesay')\nrepo.dropCollection('regionincome')\nrepo.createCollection('regionincome')\nitems = {}\nincome2013 = repo.kobesay.income2013.find()\nincome2014 = repo.kobesay.income2014.find()\nfor... | <|body_start_0|>
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('kobesay', 'kobesay')
repo.dropCollection('regionincome')
repo.createCollection('regionincome')
items = {}
income2013 = repo.kobesa... | trans_income | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class trans_income:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything ... | stack_v2_sparse_classes_36k_train_012915 | 4,374 | no_license | [
{
"docstring": "Retrieve some data sets (not using the API here for the sake of simplicity).",
"name": "execute",
"signature": "def execute(trial=False)"
},
{
"docstring": "Create the provenance document describing everything happening in this script. Each run of the script will generate a new d... | 2 | null | Implement the Python class `trans_income` described below.
Class description:
Implement the trans_income class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=None, end... | Implement the Python class `trans_income` described below.
Class description:
Implement the trans_income class.
Method signatures and docstrings:
- def execute(trial=False): Retrieve some data sets (not using the API here for the sake of simplicity).
- def provenance(doc=prov.model.ProvDocument(), startTime=None, end... | 0df485d0469c5451ebdcd684bed2a0960ba3ab84 | <|skeleton|>
class trans_income:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
<|body_0|>
def provenance(doc=prov.model.ProvDocument(), startTime=None, endTime=None):
"""Create the provenance document describing everything ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class trans_income:
def execute(trial=False):
"""Retrieve some data sets (not using the API here for the sake of simplicity)."""
startTime = datetime.datetime.now()
client = dml.pymongo.MongoClient()
repo = client.repo
repo.authenticate('kobesay', 'kobesay')
repo.drop... | the_stack_v2_python_sparse | kobesay/trans_income.py | lingyigu/course-2017-spr-proj | train | 0 | |
4fb616f1eff0b81462979b726a9daecb203ac7b6 | [
"self.url = url\nself.vary_headers = vary_headers\nself.max_age = max_age\nself.etag = etag\nself.local_date = local_date\nself.last_modified = last_modified\nself.mime_type = mime_type\nself.item_mime_type = item_mime_type\nself.response_body = response_body",
"if self.vary_headers:\n for header, value in six... | <|body_start_0|>
self.url = url
self.vary_headers = vary_headers
self.max_age = max_age
self.etag = etag
self.local_date = local_date
self.last_modified = last_modified
self.mime_type = mime_type
self.item_mime_type = item_mime_type
self.response_b... | An entry in the API Cache. | CacheEntry | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CacheEntry:
"""An entry in the API Cache."""
def __init__(self, url, vary_headers, max_age, etag, local_date, last_modified, mime_type, item_mime_type, response_body):
"""Create a new cache entry."""
<|body_0|>
def matches_request(self, request):
"""Determine if ... | stack_v2_sparse_classes_36k_train_012916 | 22,967 | permissive | [
{
"docstring": "Create a new cache entry.",
"name": "__init__",
"signature": "def __init__(self, url, vary_headers, max_age, etag, local_date, last_modified, mime_type, item_mime_type, response_body)"
},
{
"docstring": "Determine if the cache entry matches the given request. This is done by comp... | 3 | null | Implement the Python class `CacheEntry` described below.
Class description:
An entry in the API Cache.
Method signatures and docstrings:
- def __init__(self, url, vary_headers, max_age, etag, local_date, last_modified, mime_type, item_mime_type, response_body): Create a new cache entry.
- def matches_request(self, re... | Implement the Python class `CacheEntry` described below.
Class description:
An entry in the API Cache.
Method signatures and docstrings:
- def __init__(self, url, vary_headers, max_age, etag, local_date, last_modified, mime_type, item_mime_type, response_body): Create a new cache entry.
- def matches_request(self, re... | b106c84c274c59f7944ba5bf7706d865c78a3408 | <|skeleton|>
class CacheEntry:
"""An entry in the API Cache."""
def __init__(self, url, vary_headers, max_age, etag, local_date, last_modified, mime_type, item_mime_type, response_body):
"""Create a new cache entry."""
<|body_0|>
def matches_request(self, request):
"""Determine if ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CacheEntry:
"""An entry in the API Cache."""
def __init__(self, url, vary_headers, max_age, etag, local_date, last_modified, mime_type, item_mime_type, response_body):
"""Create a new cache entry."""
self.url = url
self.vary_headers = vary_headers
self.max_age = max_age
... | the_stack_v2_python_sparse | rbtools/api/cache.py | anirudha-banerjee/rbtools | train | 1 |
689753e528cb848070184d6cf67cc9fefa97ba26 | [
"player_index = 11\nconst.CENTER_SEER_PROB = 1\ngame_roles = list(large_game_roles)\nexpected = (Statement('I am a Seer and I saw that Center 1 was a Insomniac and that Center 0 was a Troublemaker.', ((11, frozenset({Role.SEER})), (13, frozenset({Role.INSOMNIAC})), (12, frozenset({Role.TROUBLEMAKER})))),)\nseer = S... | <|body_start_0|>
player_index = 11
const.CENTER_SEER_PROB = 1
game_roles = list(large_game_roles)
expected = (Statement('I am a Seer and I saw that Center 1 was a Insomniac and that Center 0 was a Troublemaker.', ((11, frozenset({Role.SEER})), (13, frozenset({Role.INSOMNIAC})), (12, froz... | Tests for the Seer player class. | TestSeer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestSeer:
"""Tests for the Seer player class."""
def test_awake_init_center_choice(large_game_roles: tuple[Role, ...]) -> None:
"""Should initialize a Seer. Note that the player_index of the Seer is not necessarily the index where the true Seer is located."""
<|body_0|>
... | stack_v2_sparse_classes_36k_train_012917 | 5,203 | permissive | [
{
"docstring": "Should initialize a Seer. Note that the player_index of the Seer is not necessarily the index where the true Seer is located.",
"name": "test_awake_init_center_choice",
"signature": "def test_awake_init_center_choice(large_game_roles: tuple[Role, ...]) -> None"
},
{
"docstring": ... | 4 | stack_v2_sparse_classes_30k_train_007844 | Implement the Python class `TestSeer` described below.
Class description:
Tests for the Seer player class.
Method signatures and docstrings:
- def test_awake_init_center_choice(large_game_roles: tuple[Role, ...]) -> None: Should initialize a Seer. Note that the player_index of the Seer is not necessarily the index wh... | Implement the Python class `TestSeer` described below.
Class description:
Tests for the Seer player class.
Method signatures and docstrings:
- def test_awake_init_center_choice(large_game_roles: tuple[Role, ...]) -> None: Should initialize a Seer. Note that the player_index of the Seer is not necessarily the index wh... | 6e91c2f24e72f9374c4f703bd966963ea6626e8e | <|skeleton|>
class TestSeer:
"""Tests for the Seer player class."""
def test_awake_init_center_choice(large_game_roles: tuple[Role, ...]) -> None:
"""Should initialize a Seer. Note that the player_index of the Seer is not necessarily the index where the true Seer is located."""
<|body_0|>
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestSeer:
"""Tests for the Seer player class."""
def test_awake_init_center_choice(large_game_roles: tuple[Role, ...]) -> None:
"""Should initialize a Seer. Note that the player_index of the Seer is not necessarily the index where the true Seer is located."""
player_index = 11
con... | the_stack_v2_python_sparse | unit_test/roles/village/seer_test.py | srijan-deepsource/wolfbot | train | 0 |
cb73cea591e0d168961d515e34ec60e34661ebfb | [
"if not string or len(string) != 2:\n return None\nvalue, suit = (string[0], string[1])\nmapped_value = self.VALUE_MAP.get(value)\nif not mapped_value:\n mapped_value = int(value)\nmapped_suit = self.SUIT_MAP.get(suit)\ntry:\n return Card(mapped_value, mapped_suit)\nexcept:\n return None",
"if not tok... | <|body_start_0|>
if not string or len(string) != 2:
return None
value, suit = (string[0], string[1])
mapped_value = self.VALUE_MAP.get(value)
if not mapped_value:
mapped_value = int(value)
mapped_suit = self.SUIT_MAP.get(suit)
try:
retu... | Creates our internal cards from text strings | CardBuilder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CardBuilder:
"""Creates our internal cards from text strings"""
def from_2char(self, string):
"""Returns a Card from a 2-char token like 9c"""
<|body_0|>
def from_list(self, token_string):
"""Returns a list of Cards from a string token like [Ah,9d]"""
<|b... | stack_v2_sparse_classes_36k_train_012918 | 8,250 | permissive | [
{
"docstring": "Returns a Card from a 2-char token like 9c",
"name": "from_2char",
"signature": "def from_2char(self, string)"
},
{
"docstring": "Returns a list of Cards from a string token like [Ah,9d]",
"name": "from_list",
"signature": "def from_list(self, token_string)"
},
{
... | 3 | stack_v2_sparse_classes_30k_train_011830 | Implement the Python class `CardBuilder` described below.
Class description:
Creates our internal cards from text strings
Method signatures and docstrings:
- def from_2char(self, string): Returns a Card from a 2-char token like 9c
- def from_list(self, token_string): Returns a list of Cards from a string token like [... | Implement the Python class `CardBuilder` described below.
Class description:
Creates our internal cards from text strings
Method signatures and docstrings:
- def from_2char(self, string): Returns a Card from a 2-char token like 9c
- def from_list(self, token_string): Returns a list of Cards from a string token like [... | 5e7241efac1b0757f39c28f6d485f4d79960095b | <|skeleton|>
class CardBuilder:
"""Creates our internal cards from text strings"""
def from_2char(self, string):
"""Returns a Card from a 2-char token like 9c"""
<|body_0|>
def from_list(self, token_string):
"""Returns a list of Cards from a string token like [Ah,9d]"""
<|b... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CardBuilder:
"""Creates our internal cards from text strings"""
def from_2char(self, string):
"""Returns a Card from a 2-char token like 9c"""
if not string or len(string) != 2:
return None
value, suit = (string[0], string[1])
mapped_value = self.VALUE_MAP.get(... | the_stack_v2_python_sparse | pokeher/theaigame.py | gnmerritt/poker | train | 5 |
312ccc24cdc8f42b27148182b20509d11ae9afc8 | [
"self.orgnr_field = orgnr_field\nself.status_kode_field = status_kode_field\nself.status_tekst_field = status_tekst_field\nself.status_dato_field = APIHelper.RFC3339DateTime(status_dato_field) if status_dato_field else None\nself.navn_field = navn_field\nself.selsk_form_field = selsk_form_field\nself.rolle_field = ... | <|body_start_0|>
self.orgnr_field = orgnr_field
self.status_kode_field = status_kode_field
self.status_tekst_field = status_tekst_field
self.status_dato_field = APIHelper.RFC3339DateTime(status_dato_field) if status_dato_field else None
self.navn_field = navn_field
self.s... | Implementation of the 'Person.NaringsInteresser' model. TODO: type model description here. Attributes: orgnr_field (int): TODO: type description here. status_kode_field (string): TODO: type description here. status_tekst_field (string): TODO: type description here. status_dato_field (datetime): TODO: type description h... | PersonNaringsInteresser | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class PersonNaringsInteresser:
"""Implementation of the 'Person.NaringsInteresser' model. TODO: type model description here. Attributes: orgnr_field (int): TODO: type description here. status_kode_field (string): TODO: type description here. status_tekst_field (string): TODO: type description here. sta... | stack_v2_sparse_classes_36k_train_012919 | 4,712 | permissive | [
{
"docstring": "Constructor for the PersonNaringsInteresser class",
"name": "__init__",
"signature": "def __init__(self, orgnr_field=None, status_kode_field=None, status_tekst_field=None, status_dato_field=None, navn_field=None, selsk_form_field=None, rolle_field=None, eierandel_field=None, verv_kode_fi... | 2 | null | Implement the Python class `PersonNaringsInteresser` described below.
Class description:
Implementation of the 'Person.NaringsInteresser' model. TODO: type model description here. Attributes: orgnr_field (int): TODO: type description here. status_kode_field (string): TODO: type description here. status_tekst_field (st... | Implement the Python class `PersonNaringsInteresser` described below.
Class description:
Implementation of the 'Person.NaringsInteresser' model. TODO: type model description here. Attributes: orgnr_field (int): TODO: type description here. status_kode_field (string): TODO: type description here. status_tekst_field (st... | fa3918a6c54ea0eedb9146578645b7eb1755b642 | <|skeleton|>
class PersonNaringsInteresser:
"""Implementation of the 'Person.NaringsInteresser' model. TODO: type model description here. Attributes: orgnr_field (int): TODO: type description here. status_kode_field (string): TODO: type description here. status_tekst_field (string): TODO: type description here. sta... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class PersonNaringsInteresser:
"""Implementation of the 'Person.NaringsInteresser' model. TODO: type model description here. Attributes: orgnr_field (int): TODO: type description here. status_kode_field (string): TODO: type description here. status_tekst_field (string): TODO: type description here. status_dato_fiel... | the_stack_v2_python_sparse | idfy_rest_client/models/person_narings_interesser.py | dealflowteam/Idfy | train | 0 |
3248b044a38f8f177a84c24d2eda205f09e9c038 | [
"diagnostic = DuctStaticAIRCx()\nif isinstance(diagnostic, DuctStaticAIRCx):\n assert True\nelse:\n assert False",
"diagnostic = DuctStaticAIRCx()\ndata_window = td(minutes=1)\ndiagnostic.set_class_values({}, 1, data_window, False, {}, 4.0, 4.0, {}, {}, {}, 3, 'test', 'test_c', [])\nassert diagnostic.data_w... | <|body_start_0|>
diagnostic = DuctStaticAIRCx()
if isinstance(diagnostic, DuctStaticAIRCx):
assert True
else:
assert False
<|end_body_0|>
<|body_start_1|>
diagnostic = DuctStaticAIRCx()
data_window = td(minutes=1)
diagnostic.set_class_values({}, 1... | Contains all the tests for DuctStaticAIRCx Diagnostic | TestDiagnosticsDuctStaticAIRCx | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestDiagnosticsDuctStaticAIRCx:
"""Contains all the tests for DuctStaticAIRCx Diagnostic"""
def test_duct_static_dx_creation(self):
"""test the creation of duct static diagnostic class"""
<|body_0|>
def test_duct_static_dx_set_class_values(self):
"""test the crea... | stack_v2_sparse_classes_36k_train_012920 | 14,928 | permissive | [
{
"docstring": "test the creation of duct static diagnostic class",
"name": "test_duct_static_dx_creation",
"signature": "def test_duct_static_dx_creation(self)"
},
{
"docstring": "test the creation of duct static diagnostic class",
"name": "test_duct_static_dx_set_class_values",
"signat... | 6 | null | Implement the Python class `TestDiagnosticsDuctStaticAIRCx` described below.
Class description:
Contains all the tests for DuctStaticAIRCx Diagnostic
Method signatures and docstrings:
- def test_duct_static_dx_creation(self): test the creation of duct static diagnostic class
- def test_duct_static_dx_set_class_values... | Implement the Python class `TestDiagnosticsDuctStaticAIRCx` described below.
Class description:
Contains all the tests for DuctStaticAIRCx Diagnostic
Method signatures and docstrings:
- def test_duct_static_dx_creation(self): test the creation of duct static diagnostic class
- def test_duct_static_dx_set_class_values... | 24d50729aef8d91036cc13b0f5c03be76f3237ed | <|skeleton|>
class TestDiagnosticsDuctStaticAIRCx:
"""Contains all the tests for DuctStaticAIRCx Diagnostic"""
def test_duct_static_dx_creation(self):
"""test the creation of duct static diagnostic class"""
<|body_0|>
def test_duct_static_dx_set_class_values(self):
"""test the crea... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestDiagnosticsDuctStaticAIRCx:
"""Contains all the tests for DuctStaticAIRCx Diagnostic"""
def test_duct_static_dx_creation(self):
"""test the creation of duct static diagnostic class"""
diagnostic = DuctStaticAIRCx()
if isinstance(diagnostic, DuctStaticAIRCx):
assert... | the_stack_v2_python_sparse | EnergyEfficiency/AirsideRCxAgent/airside/test.py | shwethanidd/volttron-pnnl-applications-2 | train | 0 |
04164599d53bdbebca30700f26d746cfa9a95deb | [
"l = len(xy)\nif l > 1:\n raise Exception('too many points provided\\ninstance should only be located at one point')\nelif l < 1:\n raise Exception('no point provided\\ninstance should be located at a point')\nself.layer = layer\nself.textType = textType\nself.xy = xy[0]\nself.string = string\nself.strans = 0... | <|body_start_0|>
l = len(xy)
if l > 1:
raise Exception('too many points provided\ninstance should only be located at one point')
elif l < 1:
raise Exception('no point provided\ninstance should be located at a point')
self.layer = layer
self.textType = text... | Text object for GDSIO | Text | [
"BSD-3-Clause",
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Text:
"""Text object for GDSIO"""
def __init__(self, layer, textType, xy, string, textHeight=100):
"""Initialize Text object Parameters ---------- layer : int Layer id textType : int I'm not really sure what this is xy : array xy coordinates for Text Object string : str Text object d... | stack_v2_sparse_classes_36k_train_012921 | 18,791 | permissive | [
{
"docstring": "Initialize Text object Parameters ---------- layer : int Layer id textType : int I'm not really sure what this is xy : array xy coordinates for Text Object string : str Text object display string",
"name": "__init__",
"signature": "def __init__(self, layer, textType, xy, string, textHeig... | 2 | null | Implement the Python class `Text` described below.
Class description:
Text object for GDSIO
Method signatures and docstrings:
- def __init__(self, layer, textType, xy, string, textHeight=100): Initialize Text object Parameters ---------- layer : int Layer id textType : int I'm not really sure what this is xy : array ... | Implement the Python class `Text` described below.
Class description:
Text object for GDSIO
Method signatures and docstrings:
- def __init__(self, layer, textType, xy, string, textHeight=100): Initialize Text object Parameters ---------- layer : int Layer id textType : int I'm not really sure what this is xy : array ... | 8f62ec1971480cb27cb592421fd97f590379cff9 | <|skeleton|>
class Text:
"""Text object for GDSIO"""
def __init__(self, layer, textType, xy, string, textHeight=100):
"""Initialize Text object Parameters ---------- layer : int Layer id textType : int I'm not really sure what this is xy : array xy coordinates for Text Object string : str Text object d... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Text:
"""Text object for GDSIO"""
def __init__(self, layer, textType, xy, string, textHeight=100):
"""Initialize Text object Parameters ---------- layer : int Layer id textType : int I'm not really sure what this is xy : array xy coordinates for Text Object string : str Text object display string... | the_stack_v2_python_sparse | GDSIO.py | ucb-art/laygo | train | 24 |
8afbcf0cd7c8848a88f3a9e7f9f17a090479c30d | [
"category = Category.objects.all()\nserializer = CategorySerializer(category, many=True)\nreturn Response(serializer.data)",
"serializer = CategorySerializer(data=request.data)\nif serializer.is_valid():\n serializer.save()\n return Response(serializer.data, status=status.HTTP_201_CREATED)\nreturn Response(... | <|body_start_0|>
category = Category.objects.all()
serializer = CategorySerializer(category, many=True)
return Response(serializer.data)
<|end_body_0|>
<|body_start_1|>
serializer = CategorySerializer(data=request.data)
if serializer.is_valid():
serializer.save()
... | List all categories, or create a new category. | CategoryList | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CategoryList:
"""List all categories, or create a new category."""
def get(self, request, format=None):
"""The default get method, i.e on page load"""
<|body_0|>
def post(self, request, format=None):
"""The default post method."""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_36k_train_012922 | 4,310 | permissive | [
{
"docstring": "The default get method, i.e on page load",
"name": "get",
"signature": "def get(self, request, format=None)"
},
{
"docstring": "The default post method.",
"name": "post",
"signature": "def post(self, request, format=None)"
}
] | 2 | stack_v2_sparse_classes_30k_train_017646 | Implement the Python class `CategoryList` described below.
Class description:
List all categories, or create a new category.
Method signatures and docstrings:
- def get(self, request, format=None): The default get method, i.e on page load
- def post(self, request, format=None): The default post method. | Implement the Python class `CategoryList` described below.
Class description:
List all categories, or create a new category.
Method signatures and docstrings:
- def get(self, request, format=None): The default get method, i.e on page load
- def post(self, request, format=None): The default post method.
<|skeleton|>
... | b0635e72338e14dad24f1ee0329212cd60a3e83a | <|skeleton|>
class CategoryList:
"""List all categories, or create a new category."""
def get(self, request, format=None):
"""The default get method, i.e on page load"""
<|body_0|>
def post(self, request, format=None):
"""The default post method."""
<|body_1|>
<|end_skelet... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CategoryList:
"""List all categories, or create a new category."""
def get(self, request, format=None):
"""The default get method, i.e on page load"""
category = Category.objects.all()
serializer = CategorySerializer(category, many=True)
return Response(serializer.data)
... | the_stack_v2_python_sparse | links/views.py | faisaltheparttimecoder/carelogBackend | train | 1 |
edcf493c7fba8c06cb7cb56c049b26e05fe694bc | [
"super().__init__(env, learner_config, session_config)\nself._ob = None\nself.n_step = self.learner_config.algo.n_step\nself.stride = self.learner_config.algo.stride\nif self.stride < 1:\n raise ConfigError('stride {} for experience generation cannot be less than 1'.format(self.learner_config.algo.stride))\nself... | <|body_start_0|>
super().__init__(env, learner_config, session_config)
self._ob = None
self.n_step = self.learner_config.algo.n_step
self.stride = self.learner_config.algo.stride
if self.stride < 1:
raise ConfigError('stride {} for experience generation cannot be less... | Base class for all classes that send experience in format { 'obs': [state_1, ..., state_n] 'obs_next': [state_{n + 1}] 'actions': [action_1, ...], 'rewards': [reward_1, ...], 'dones': [done_1, ...], 'persistent_infos': [infolist_1, ...], 'onetime_infos': [infos], 'infos': [info_1, ...], 'n_step': n } Note: distinction ... | ExpSenderWrapperMultiStepMovingWindowWithInfo | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ExpSenderWrapperMultiStepMovingWindowWithInfo:
"""Base class for all classes that send experience in format { 'obs': [state_1, ..., state_n] 'obs_next': [state_{n + 1}] 'actions': [action_1, ...], 'rewards': [reward_1, ...], 'dones': [done_1, ...], 'persistent_infos': [infolist_1, ...], 'onetime_... | stack_v2_sparse_classes_36k_train_012923 | 11,762 | permissive | [
{
"docstring": "Consturctor for ExpSenderWrapperMultiStepMovingWindowWithInfo class Important Attributes: _ob: holds the state at current timestep n_step: maximum number of previous states to keep stride: stride for moving window last_n: queue of max size n_step to hold previous states env: environment to inter... | 4 | stack_v2_sparse_classes_30k_train_010749 | Implement the Python class `ExpSenderWrapperMultiStepMovingWindowWithInfo` described below.
Class description:
Base class for all classes that send experience in format { 'obs': [state_1, ..., state_n] 'obs_next': [state_{n + 1}] 'actions': [action_1, ...], 'rewards': [reward_1, ...], 'dones': [done_1, ...], 'persiste... | Implement the Python class `ExpSenderWrapperMultiStepMovingWindowWithInfo` described below.
Class description:
Base class for all classes that send experience in format { 'obs': [state_1, ..., state_n] 'obs_next': [state_{n + 1}] 'actions': [action_1, ...], 'rewards': [reward_1, ...], 'dones': [done_1, ...], 'persiste... | 2556bd9c362a53e0a94da914ba59b5d4621c4081 | <|skeleton|>
class ExpSenderWrapperMultiStepMovingWindowWithInfo:
"""Base class for all classes that send experience in format { 'obs': [state_1, ..., state_n] 'obs_next': [state_{n + 1}] 'actions': [action_1, ...], 'rewards': [reward_1, ...], 'dones': [done_1, ...], 'persistent_infos': [infolist_1, ...], 'onetime_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ExpSenderWrapperMultiStepMovingWindowWithInfo:
"""Base class for all classes that send experience in format { 'obs': [state_1, ..., state_n] 'obs_next': [state_{n + 1}] 'actions': [action_1, ...], 'rewards': [reward_1, ...], 'dones': [done_1, ...], 'persistent_infos': [infolist_1, ...], 'onetime_infos': [info... | the_stack_v2_python_sparse | surreal/env/exp_sender_wrapper.py | PeihongYu/surreal | train | 0 |
7586fb2707608a5bf00216bc9b9672e78b73bddc | [
"bdm = block_matrix.BlockDiagonalMatrix(block_shape=(2, 3), block_rows=3)\nself.assertEqual(bdm.num_blocks, 3)\nself.assertEqual(bdm.block_size, 6)\nself.assertEqual(bdm.input_size, 18)\noutput = bdm(create_input(bdm.input_size))\nwith self.test_session() as sess:\n result = sess.run(output)\nexpected = np.array... | <|body_start_0|>
bdm = block_matrix.BlockDiagonalMatrix(block_shape=(2, 3), block_rows=3)
self.assertEqual(bdm.num_blocks, 3)
self.assertEqual(bdm.block_size, 6)
self.assertEqual(bdm.input_size, 18)
output = bdm(create_input(bdm.input_size))
with self.test_session() as se... | BlockDiagonalMatrixTest | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BlockDiagonalMatrixTest:
def test_default(self):
"""Tests BlockDiagonalMatrix."""
<|body_0|>
def test_properties(self):
"""Tests properties of BlockDiagonalMatrix."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
bdm = block_matrix.BlockDiagonalMatri... | stack_v2_sparse_classes_36k_train_012924 | 6,567 | permissive | [
{
"docstring": "Tests BlockDiagonalMatrix.",
"name": "test_default",
"signature": "def test_default(self)"
},
{
"docstring": "Tests properties of BlockDiagonalMatrix.",
"name": "test_properties",
"signature": "def test_properties(self)"
}
] | 2 | null | Implement the Python class `BlockDiagonalMatrixTest` described below.
Class description:
Implement the BlockDiagonalMatrixTest class.
Method signatures and docstrings:
- def test_default(self): Tests BlockDiagonalMatrix.
- def test_properties(self): Tests properties of BlockDiagonalMatrix. | Implement the Python class `BlockDiagonalMatrixTest` described below.
Class description:
Implement the BlockDiagonalMatrixTest class.
Method signatures and docstrings:
- def test_default(self): Tests BlockDiagonalMatrix.
- def test_properties(self): Tests properties of BlockDiagonalMatrix.
<|skeleton|>
class BlockDi... | 4e28fdf2ffd0eaefc0d23049106609421c9290b0 | <|skeleton|>
class BlockDiagonalMatrixTest:
def test_default(self):
"""Tests BlockDiagonalMatrix."""
<|body_0|>
def test_properties(self):
"""Tests properties of BlockDiagonalMatrix."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BlockDiagonalMatrixTest:
def test_default(self):
"""Tests BlockDiagonalMatrix."""
bdm = block_matrix.BlockDiagonalMatrix(block_shape=(2, 3), block_rows=3)
self.assertEqual(bdm.num_blocks, 3)
self.assertEqual(bdm.block_size, 6)
self.assertEqual(bdm.input_size, 18)
... | the_stack_v2_python_sparse | sunset/sunset/python/modules/block_matrix_test.py | SynthAI/SynthAI | train | 3 | |
5b9818a598ab106f3ecb355efacb3e99c5cf1a75 | [
"num_rows = args.get('rows') or 100\nquery = g.db.query(MachineGroup)\nif args.get('name'):\n query = query.filter(MachineGroup.name == args['name'])\nquery = query.order_by(-MachineGroup.machinegroup_id)\nquery = query.limit(num_rows)\nrows = query.all()\nret = []\nfor row in rows:\n record = row.as_dict()\n... | <|body_start_0|>
num_rows = args.get('rows') or 100
query = g.db.query(MachineGroup)
if args.get('name'):
query = query.filter(MachineGroup.name == args['name'])
query = query.order_by(-MachineGroup.machinegroup_id)
query = query.limit(num_rows)
rows = query.a... | MachineGroupsAPI | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MachineGroupsAPI:
def get(self, args):
"""Get a list of machine groups"""
<|body_0|>
def post(self, args):
"""Create machine group"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
num_rows = args.get('rows') or 100
query = g.db.query(MachineG... | stack_v2_sparse_classes_36k_train_012925 | 4,597 | permissive | [
{
"docstring": "Get a list of machine groups",
"name": "get",
"signature": "def get(self, args)"
},
{
"docstring": "Create machine group",
"name": "post",
"signature": "def post(self, args)"
}
] | 2 | stack_v2_sparse_classes_30k_train_003458 | Implement the Python class `MachineGroupsAPI` described below.
Class description:
Implement the MachineGroupsAPI class.
Method signatures and docstrings:
- def get(self, args): Get a list of machine groups
- def post(self, args): Create machine group | Implement the Python class `MachineGroupsAPI` described below.
Class description:
Implement the MachineGroupsAPI class.
Method signatures and docstrings:
- def get(self, args): Get a list of machine groups
- def post(self, args): Create machine group
<|skeleton|>
class MachineGroupsAPI:
def get(self, args):
... | 2771bb46db7fd331448f9db3cfb257fab7f89bcc | <|skeleton|>
class MachineGroupsAPI:
def get(self, args):
"""Get a list of machine groups"""
<|body_0|>
def post(self, args):
"""Create machine group"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MachineGroupsAPI:
def get(self, args):
"""Get a list of machine groups"""
num_rows = args.get('rows') or 100
query = g.db.query(MachineGroup)
if args.get('name'):
query = query.filter(MachineGroup.name == args['name'])
query = query.order_by(-MachineGroup.ma... | the_stack_v2_python_sparse | driftbase/api/machinegroups.py | directivegames/drift-base | train | 1 | |
4d2f34ae516b50bcbba723eda24108ad92f8ce14 | [
"if not board or len(board) != 9 or len(board[0]) != 9:\n return False\nfor i in range(9):\n rowFlag = set([])\n colFlag = set([])\n for j in range(9):\n if board[i][j] != '.':\n if board[i][j] in rowFlag:\n return False\n else:\n rowFlag.add(bo... | <|body_start_0|>
if not board or len(board) != 9 or len(board[0]) != 9:
return False
for i in range(9):
rowFlag = set([])
colFlag = set([])
for j in range(9):
if board[i][j] != '.':
if board[i][j] in rowFlag:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isValidSudoku(self, board):
""":type board: List[List[str]] :rtype: bool 暴力统计Sudoku的两个条件 1. 每一行每一列都不能有相同的数字 2. 每个3*3 的格子不能有相同的数字"""
<|body_0|>
def isValidSudoku2(self, board):
""":type board: List[List[str]] :rtype: bool 暴力统计Sudoku的两个条件 1. 每一行每一列都不能有相同的... | stack_v2_sparse_classes_36k_train_012926 | 2,678 | no_license | [
{
"docstring": ":type board: List[List[str]] :rtype: bool 暴力统计Sudoku的两个条件 1. 每一行每一列都不能有相同的数字 2. 每个3*3 的格子不能有相同的数字",
"name": "isValidSudoku",
"signature": "def isValidSudoku(self, board)"
},
{
"docstring": ":type board: List[List[str]] :rtype: bool 暴力统计Sudoku的两个条件 1. 每一行每一列都不能有相同的数字 2. 每个3*3 的格子不... | 2 | stack_v2_sparse_classes_30k_train_005530 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValidSudoku(self, board): :type board: List[List[str]] :rtype: bool 暴力统计Sudoku的两个条件 1. 每一行每一列都不能有相同的数字 2. 每个3*3 的格子不能有相同的数字
- def isValidSudoku2(self, board): :type board: ... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValidSudoku(self, board): :type board: List[List[str]] :rtype: bool 暴力统计Sudoku的两个条件 1. 每一行每一列都不能有相同的数字 2. 每个3*3 的格子不能有相同的数字
- def isValidSudoku2(self, board): :type board: ... | 96adb6c04c344e792e35dc70dc45eb76b5402008 | <|skeleton|>
class Solution:
def isValidSudoku(self, board):
""":type board: List[List[str]] :rtype: bool 暴力统计Sudoku的两个条件 1. 每一行每一列都不能有相同的数字 2. 每个3*3 的格子不能有相同的数字"""
<|body_0|>
def isValidSudoku2(self, board):
""":type board: List[List[str]] :rtype: bool 暴力统计Sudoku的两个条件 1. 每一行每一列都不能有相同的... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isValidSudoku(self, board):
""":type board: List[List[str]] :rtype: bool 暴力统计Sudoku的两个条件 1. 每一行每一列都不能有相同的数字 2. 每个3*3 的格子不能有相同的数字"""
if not board or len(board) != 9 or len(board[0]) != 9:
return False
for i in range(9):
rowFlag = set([])
... | the_stack_v2_python_sparse | JiQiang/leetcode_py/regular/ValidSudoku36.py | Hearen/AlgorithmHackers | train | 10 | |
9ccc326414214310c4e2855ff3a295810c1abcac | [
"text = err_text\nif not fixable:\n option = 'unfixable'\nif option in ['warn', 'exception']:\n pass\nelif option == 'unfixable':\n text = 'Unfixable error: %s' % text\nelse:\n if fix:\n fix()\n text += ' ' + fix_text\nreturn text",
"opt = option.lower()\nif opt not in ['fix', 'silentfix', ... | <|body_start_0|>
text = err_text
if not fixable:
option = 'unfixable'
if option in ['warn', 'exception']:
pass
elif option == 'unfixable':
text = 'Unfixable error: %s' % text
else:
if fix:
fix()
text += '... | Shared methods for verification. | _Verify | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class _Verify:
"""Shared methods for verification."""
def run_option(self, option='warn', err_text='', fix_text='Fixed.', fix=None, fixable=True):
"""Execute the verification with selected option."""
<|body_0|>
def verify(self, option='warn'):
"""Verify all values in t... | stack_v2_sparse_classes_36k_train_012927 | 3,589 | permissive | [
{
"docstring": "Execute the verification with selected option.",
"name": "run_option",
"signature": "def run_option(self, option='warn', err_text='', fix_text='Fixed.', fix=None, fixable=True)"
},
{
"docstring": "Verify all values in the instance. Parameters ---------- option : str Output verifi... | 2 | stack_v2_sparse_classes_30k_train_010124 | Implement the Python class `_Verify` described below.
Class description:
Shared methods for verification.
Method signatures and docstrings:
- def run_option(self, option='warn', err_text='', fix_text='Fixed.', fix=None, fixable=True): Execute the verification with selected option.
- def verify(self, option='warn'): V... | Implement the Python class `_Verify` described below.
Class description:
Shared methods for verification.
Method signatures and docstrings:
- def run_option(self, option='warn', err_text='', fix_text='Fixed.', fix=None, fixable=True): Execute the verification with selected option.
- def verify(self, option='warn'): V... | 8876e902f5efa02a3fc27d82fe15c16001d4df5e | <|skeleton|>
class _Verify:
"""Shared methods for verification."""
def run_option(self, option='warn', err_text='', fix_text='Fixed.', fix=None, fixable=True):
"""Execute the verification with selected option."""
<|body_0|>
def verify(self, option='warn'):
"""Verify all values in t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class _Verify:
"""Shared methods for verification."""
def run_option(self, option='warn', err_text='', fix_text='Fixed.', fix=None, fixable=True):
"""Execute the verification with selected option."""
text = err_text
if not fixable:
option = 'unfixable'
if option in [... | the_stack_v2_python_sparse | astropy/io/fits/verify.py | xiaomi1122/astropy | train | 0 |
95267be1237e8d6ef46e64da9f04253cf00d8c79 | [
"sum_a = sum(A)\nsum_b = sum(B)\ndiff = (sum_a - sum_b) // 2\nfor i in A:\n if i - diff in B:\n return [i, i - diff]",
"sum_a = sum(A)\nsum_b = sum(B)\nd = {}\ndiff = (sum_a - sum_b) // 2\nfor i in A:\n d[i - diff] = i\nfor j in B:\n if j in d:\n return [d[j], j]"
] | <|body_start_0|>
sum_a = sum(A)
sum_b = sum(B)
diff = (sum_a - sum_b) // 2
for i in A:
if i - diff in B:
return [i, i - diff]
<|end_body_0|>
<|body_start_1|>
sum_a = sum(A)
sum_b = sum(B)
d = {}
diff = (sum_a - sum_b) // 2
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def fairCandySwap(self, A, B):
""":type A: List[int] :type B: List[int] :rtype: List[int] TLE"""
<|body_0|>
def fairCandySwap2(self, A, B):
""":type A: List[int] :type B: List[int] :rtype: List[int] 88ms beats: ?"""
<|body_1|>
<|end_skeleton|>
<|b... | stack_v2_sparse_classes_36k_train_012928 | 730 | no_license | [
{
"docstring": ":type A: List[int] :type B: List[int] :rtype: List[int] TLE",
"name": "fairCandySwap",
"signature": "def fairCandySwap(self, A, B)"
},
{
"docstring": ":type A: List[int] :type B: List[int] :rtype: List[int] 88ms beats: ?",
"name": "fairCandySwap2",
"signature": "def fairC... | 2 | stack_v2_sparse_classes_30k_train_015714 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fairCandySwap(self, A, B): :type A: List[int] :type B: List[int] :rtype: List[int] TLE
- def fairCandySwap2(self, A, B): :type A: List[int] :type B: List[int] :rtype: List[in... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fairCandySwap(self, A, B): :type A: List[int] :type B: List[int] :rtype: List[int] TLE
- def fairCandySwap2(self, A, B): :type A: List[int] :type B: List[int] :rtype: List[in... | 624975f767f6efa1d7361cc077eaebc344d57210 | <|skeleton|>
class Solution:
def fairCandySwap(self, A, B):
""":type A: List[int] :type B: List[int] :rtype: List[int] TLE"""
<|body_0|>
def fairCandySwap2(self, A, B):
""":type A: List[int] :type B: List[int] :rtype: List[int] 88ms beats: ?"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def fairCandySwap(self, A, B):
""":type A: List[int] :type B: List[int] :rtype: List[int] TLE"""
sum_a = sum(A)
sum_b = sum(B)
diff = (sum_a - sum_b) // 2
for i in A:
if i - diff in B:
return [i, i - diff]
def fairCandySwap2(se... | the_stack_v2_python_sparse | 888. 公平的糖果交换.py | dx19910707/LeetCode | train | 0 | |
45da954dc536c1850bf94b989c475679d214e3f6 | [
"ComponentWrapper.__init__(self, tag, xmldoc, tarsqi_instance)\nself.component_name = BLINKER\nself.CREATION_EXTENSION = 'bli.i'\nself.RETRIEVAL_EXTENSION = 'bli.o'",
"for fragment in self.fragments:\n base = fragment[0]\n infile = '%s%s%s.%s' % (self.DIR_DATA, os.sep, base, self.CREATION_EXTENSION)\n ou... | <|body_start_0|>
ComponentWrapper.__init__(self, tag, xmldoc, tarsqi_instance)
self.component_name = BLINKER
self.CREATION_EXTENSION = 'bli.i'
self.RETRIEVAL_EXTENSION = 'bli.o'
<|end_body_0|>
<|body_start_1|>
for fragment in self.fragments:
base = fragment[0]
... | Wrapper for Blinker. See ComponentWrapper for more details on how component wrappers work and on the instance variables. | BlinkerWrapper | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BlinkerWrapper:
"""Wrapper for Blinker. See ComponentWrapper for more details on how component wrappers work and on the instance variables."""
def __init__(self, tag, xmldoc, tarsqi_instance):
"""Calls __init__ of the base class and sets component_name, CREATION_EXTENSION and RETRIEV... | stack_v2_sparse_classes_36k_train_012929 | 1,286 | no_license | [
{
"docstring": "Calls __init__ of the base class and sets component_name, CREATION_EXTENSION and RETRIEVAL_EXTENSION.",
"name": "__init__",
"signature": "def __init__(self, tag, xmldoc, tarsqi_instance)"
},
{
"docstring": "Apply the Blinker parser to each fragment. No arguments and no return val... | 2 | stack_v2_sparse_classes_30k_train_014464 | Implement the Python class `BlinkerWrapper` described below.
Class description:
Wrapper for Blinker. See ComponentWrapper for more details on how component wrappers work and on the instance variables.
Method signatures and docstrings:
- def __init__(self, tag, xmldoc, tarsqi_instance): Calls __init__ of the base clas... | Implement the Python class `BlinkerWrapper` described below.
Class description:
Wrapper for Blinker. See ComponentWrapper for more details on how component wrappers work and on the instance variables.
Method signatures and docstrings:
- def __init__(self, tag, xmldoc, tarsqi_instance): Calls __init__ of the base clas... | efb55fa054e2313fd710939330a4fbda5634cb41 | <|skeleton|>
class BlinkerWrapper:
"""Wrapper for Blinker. See ComponentWrapper for more details on how component wrappers work and on the instance variables."""
def __init__(self, tag, xmldoc, tarsqi_instance):
"""Calls __init__ of the base class and sets component_name, CREATION_EXTENSION and RETRIEV... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BlinkerWrapper:
"""Wrapper for Blinker. See ComponentWrapper for more details on how component wrappers work and on the instance variables."""
def __init__(self, tag, xmldoc, tarsqi_instance):
"""Calls __init__ of the base class and sets component_name, CREATION_EXTENSION and RETRIEVAL_EXTENSION.... | the_stack_v2_python_sparse | code/components/blinker/wrapper.py | tankle/TARSQI | train | 1 |
493b5ebb86f39fa11f2df305496426af85eb74ee | [
"size = _reset_df_and_get_size(df)\nwith tf.python_io.TFRecordWriter(path) as writer, get_tqdm(total=size) as pbar:\n for dp in df:\n writer.write(dumps(dp))\n pbar.update()",
"gen = tf.python_io.tf_record_iterator(path)\nds = DataFromGenerator(gen)\nds = MapData(ds, loads)\nif size is not None:\... | <|body_start_0|>
size = _reset_df_and_get_size(df)
with tf.python_io.TFRecordWriter(path) as writer, get_tqdm(total=size) as pbar:
for dp in df:
writer.write(dumps(dp))
pbar.update()
<|end_body_0|>
<|body_start_1|>
gen = tf.python_io.tf_record_iterato... | Serialize datapoints to bytes (by tensorpack's default serializer) and write to a TFRecord file. Note that TFRecord does not support random access and is in fact not very performant. It's better to use :class:`LMDBSerializer`. | TFRecordSerializer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TFRecordSerializer:
"""Serialize datapoints to bytes (by tensorpack's default serializer) and write to a TFRecord file. Note that TFRecord does not support random access and is in fact not very performant. It's better to use :class:`LMDBSerializer`."""
def save(df, path):
"""Args: df... | stack_v2_sparse_classes_36k_train_012930 | 10,978 | permissive | [
{
"docstring": "Args: df (DataFlow): the DataFlow to serialize. path (str): output tfrecord file.",
"name": "save",
"signature": "def save(df, path)"
},
{
"docstring": "Args: size (int): total number of records. If not provided, the returned dataflow will have no `__len__()`. It's needed because... | 2 | null | Implement the Python class `TFRecordSerializer` described below.
Class description:
Serialize datapoints to bytes (by tensorpack's default serializer) and write to a TFRecord file. Note that TFRecord does not support random access and is in fact not very performant. It's better to use :class:`LMDBSerializer`.
Method ... | Implement the Python class `TFRecordSerializer` described below.
Class description:
Serialize datapoints to bytes (by tensorpack's default serializer) and write to a TFRecord file. Note that TFRecord does not support random access and is in fact not very performant. It's better to use :class:`LMDBSerializer`.
Method ... | 1547a54e8546494614ca31c984a1bfd1d0e24b77 | <|skeleton|>
class TFRecordSerializer:
"""Serialize datapoints to bytes (by tensorpack's default serializer) and write to a TFRecord file. Note that TFRecord does not support random access and is in fact not very performant. It's better to use :class:`LMDBSerializer`."""
def save(df, path):
"""Args: df... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TFRecordSerializer:
"""Serialize datapoints to bytes (by tensorpack's default serializer) and write to a TFRecord file. Note that TFRecord does not support random access and is in fact not very performant. It's better to use :class:`LMDBSerializer`."""
def save(df, path):
"""Args: df (DataFlow): ... | the_stack_v2_python_sparse | tensorpack/dataflow/serialize.py | tensorpack/tensorpack | train | 4,600 |
8e09b3c90ae813ea92a0fea935d9497c4608d498 | [
"super(Encoder, self).__init__()\nself.layers = clones(layer, N)\nself.norm = LayerNorm(layer.size)",
"for layer in self.layers:\n x = layer(x, mask)\nreturn self.norm(x)"
] | <|body_start_0|>
super(Encoder, self).__init__()
self.layers = clones(layer, N)
self.norm = LayerNorm(layer.size)
<|end_body_0|>
<|body_start_1|>
for layer in self.layers:
x = layer(x, mask)
return self.norm(x)
<|end_body_1|>
| Encoder | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Encoder:
def __init__(self, layer, N):
"""param layer: layer to use for Encoer param N: number of layers"""
<|body_0|>
def forward(self, x, mask):
"""Encodes the input using self attention param qry_embs: query embeddings param cnd_emb: candidate embedding param qry_... | stack_v2_sparse_classes_36k_train_012931 | 11,359 | no_license | [
{
"docstring": "param layer: layer to use for Encoer param N: number of layers",
"name": "__init__",
"signature": "def __init__(self, layer, N)"
},
{
"docstring": "Encodes the input using self attention param qry_embs: query embeddings param cnd_emb: candidate embedding param qry_mask: query mas... | 2 | stack_v2_sparse_classes_30k_train_006635 | Implement the Python class `Encoder` described below.
Class description:
Implement the Encoder class.
Method signatures and docstrings:
- def __init__(self, layer, N): param layer: layer to use for Encoer param N: number of layers
- def forward(self, x, mask): Encodes the input using self attention param qry_embs: qu... | Implement the Python class `Encoder` described below.
Class description:
Implement the Encoder class.
Method signatures and docstrings:
- def __init__(self, layer, N): param layer: layer to use for Encoer param N: number of layers
- def forward(self, x, mask): Encodes the input using self attention param qry_embs: qu... | c0b2f83a7d4c0d5fa5effb7584e0e0acc6f877a0 | <|skeleton|>
class Encoder:
def __init__(self, layer, N):
"""param layer: layer to use for Encoer param N: number of layers"""
<|body_0|>
def forward(self, x, mask):
"""Encodes the input using self attention param qry_embs: query embeddings param cnd_emb: candidate embedding param qry_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Encoder:
def __init__(self, layer, N):
"""param layer: layer to use for Encoer param N: number of layers"""
super(Encoder, self).__init__()
self.layers = clones(layer, N)
self.norm = LayerNorm(layer.size)
def forward(self, x, mask):
"""Encodes the input using self ... | the_stack_v2_python_sparse | src/main/base_models/architectures/Transformer.py | iesl/institution_hierarchies | train | 3 | |
1ff5cf19221fcaf3017c0cc3f48325da8afe2ce5 | [
"try:\n db.show_by_id(show_id, session=session)\nexcept NoResultFound:\n raise NotFoundError('show with ID %s not found' % show_id)\ntry:\n episode = db.episode_by_id(ep_id, session)\nexcept NoResultFound:\n raise NotFoundError('episode with ID %s not found' % ep_id)\nif not db.episode_in_show(show_id, ... | <|body_start_0|>
try:
db.show_by_id(show_id, session=session)
except NoResultFound:
raise NotFoundError('show with ID %s not found' % show_id)
try:
episode = db.episode_by_id(ep_id, session)
except NoResultFound:
raise NotFoundError('episod... | SeriesEpisodeAPI | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SeriesEpisodeAPI:
def get(self, show_id, ep_id, session):
"""Get episode by show ID and episode ID"""
<|body_0|>
def delete(self, show_id, ep_id, session):
"""Forgets episode by show ID and episode ID"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
... | stack_v2_sparse_classes_36k_train_012932 | 47,001 | permissive | [
{
"docstring": "Get episode by show ID and episode ID",
"name": "get",
"signature": "def get(self, show_id, ep_id, session)"
},
{
"docstring": "Forgets episode by show ID and episode ID",
"name": "delete",
"signature": "def delete(self, show_id, ep_id, session)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013740 | Implement the Python class `SeriesEpisodeAPI` described below.
Class description:
Implement the SeriesEpisodeAPI class.
Method signatures and docstrings:
- def get(self, show_id, ep_id, session): Get episode by show ID and episode ID
- def delete(self, show_id, ep_id, session): Forgets episode by show ID and episode ... | Implement the Python class `SeriesEpisodeAPI` described below.
Class description:
Implement the SeriesEpisodeAPI class.
Method signatures and docstrings:
- def get(self, show_id, ep_id, session): Get episode by show ID and episode ID
- def delete(self, show_id, ep_id, session): Forgets episode by show ID and episode ... | ea95ff60041beaea9aacbc2d93549e3a6b981dc5 | <|skeleton|>
class SeriesEpisodeAPI:
def get(self, show_id, ep_id, session):
"""Get episode by show ID and episode ID"""
<|body_0|>
def delete(self, show_id, ep_id, session):
"""Forgets episode by show ID and episode ID"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SeriesEpisodeAPI:
def get(self, show_id, ep_id, session):
"""Get episode by show ID and episode ID"""
try:
db.show_by_id(show_id, session=session)
except NoResultFound:
raise NotFoundError('show with ID %s not found' % show_id)
try:
episode =... | the_stack_v2_python_sparse | flexget/components/series/api.py | BrutuZ/Flexget | train | 1 | |
22594d9ac41c808537f74574c0e23af762d5b436 | [
"num = [i for i in range(n)]\nstart = 0\nwhile len(num) > 1:\n idx = (start + m - 1) % len(num)\n num.pop(idx)\n start = idx\nreturn num[0]",
"def f(n, m):\n if n == 1:\n return 0\n x = f(n - 1, m)\n return (m + x) % n\nreturn f(n, m)",
"x = 0\nfor i in range(2, n + 1):\n x = (m + x)... | <|body_start_0|>
num = [i for i in range(n)]
start = 0
while len(num) > 1:
idx = (start + m - 1) % len(num)
num.pop(idx)
start = idx
return num[0]
<|end_body_0|>
<|body_start_1|>
def f(n, m):
if n == 1:
return 0
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def lastRemaining(self, n: int, m: int) -> int:
"""构建数组，计算索引依次删除，时间复杂度较高，待优化"""
<|body_0|>
def lastRemaining_2(self, n: int, m: int) -> int:
"""数学+递归"""
<|body_1|>
def lastRemaining_3(self, n: int, m: int) -> int:
"""数学+迭代：基于方法2优化而来，节省了... | stack_v2_sparse_classes_36k_train_012933 | 1,505 | no_license | [
{
"docstring": "构建数组，计算索引依次删除，时间复杂度较高，待优化",
"name": "lastRemaining",
"signature": "def lastRemaining(self, n: int, m: int) -> int"
},
{
"docstring": "数学+递归",
"name": "lastRemaining_2",
"signature": "def lastRemaining_2(self, n: int, m: int) -> int"
},
{
"docstring": "数学+迭代：基于方法2优... | 3 | stack_v2_sparse_classes_30k_train_021674 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lastRemaining(self, n: int, m: int) -> int: 构建数组，计算索引依次删除，时间复杂度较高，待优化
- def lastRemaining_2(self, n: int, m: int) -> int: 数学+递归
- def lastRemaining_3(self, n: int, m: int) ->... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def lastRemaining(self, n: int, m: int) -> int: 构建数组，计算索引依次删除，时间复杂度较高，待优化
- def lastRemaining_2(self, n: int, m: int) -> int: 数学+递归
- def lastRemaining_3(self, n: int, m: int) ->... | 0ec1a89e5b1e3d32af4da9693e9e5c36d4cd42eb | <|skeleton|>
class Solution:
def lastRemaining(self, n: int, m: int) -> int:
"""构建数组，计算索引依次删除，时间复杂度较高，待优化"""
<|body_0|>
def lastRemaining_2(self, n: int, m: int) -> int:
"""数学+递归"""
<|body_1|>
def lastRemaining_3(self, n: int, m: int) -> int:
"""数学+迭代：基于方法2优化而来，节省了... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def lastRemaining(self, n: int, m: int) -> int:
"""构建数组，计算索引依次删除，时间复杂度较高，待优化"""
num = [i for i in range(n)]
start = 0
while len(num) > 1:
idx = (start + m - 1) % len(num)
num.pop(idx)
start = idx
return num[0]
def lastR... | the_stack_v2_python_sparse | offer/62.py | zhiweiguo/my_leetcode | train | 1 | |
656ec15ad24980c88a29429dab8f883bb5d70b9c | [
"self.excluded_disks = excluded_disks\nself.fallback_to_crash_consistent = fallback_to_crash_consistent\nself.skip_physical_rdm_disks = skip_physical_rdm_disks",
"if dictionary is None:\n return None\nexcluded_disks = None\nif dictionary.get('excludedDisks') != None:\n excluded_disks = list()\n for struc... | <|body_start_0|>
self.excluded_disks = excluded_disks
self.fallback_to_crash_consistent = fallback_to_crash_consistent
self.skip_physical_rdm_disks = skip_physical_rdm_disks
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
excluded_disks = None
... | Implementation of the 'VmwareEnvJobParameters' model. Specifies job parameters applicable for all 'kVMware' Environment type Protection Sources in a Protection Job. Attributes: excluded_disks (list of DiskUnit): Specifies the list of Disks to be excluded from backing up. These disks are excluded from all Protection Sou... | VmwareEnvJobParameters | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class VmwareEnvJobParameters:
"""Implementation of the 'VmwareEnvJobParameters' model. Specifies job parameters applicable for all 'kVMware' Environment type Protection Sources in a Protection Job. Attributes: excluded_disks (list of DiskUnit): Specifies the list of Disks to be excluded from backing up... | stack_v2_sparse_classes_36k_train_012934 | 2,853 | permissive | [
{
"docstring": "Constructor for the VmwareEnvJobParameters class",
"name": "__init__",
"signature": "def __init__(self, excluded_disks=None, fallback_to_crash_consistent=None, skip_physical_rdm_disks=None)"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary (... | 2 | null | Implement the Python class `VmwareEnvJobParameters` described below.
Class description:
Implementation of the 'VmwareEnvJobParameters' model. Specifies job parameters applicable for all 'kVMware' Environment type Protection Sources in a Protection Job. Attributes: excluded_disks (list of DiskUnit): Specifies the list ... | Implement the Python class `VmwareEnvJobParameters` described below.
Class description:
Implementation of the 'VmwareEnvJobParameters' model. Specifies job parameters applicable for all 'kVMware' Environment type Protection Sources in a Protection Job. Attributes: excluded_disks (list of DiskUnit): Specifies the list ... | e4973dfeb836266904d0369ea845513c7acf261e | <|skeleton|>
class VmwareEnvJobParameters:
"""Implementation of the 'VmwareEnvJobParameters' model. Specifies job parameters applicable for all 'kVMware' Environment type Protection Sources in a Protection Job. Attributes: excluded_disks (list of DiskUnit): Specifies the list of Disks to be excluded from backing up... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class VmwareEnvJobParameters:
"""Implementation of the 'VmwareEnvJobParameters' model. Specifies job parameters applicable for all 'kVMware' Environment type Protection Sources in a Protection Job. Attributes: excluded_disks (list of DiskUnit): Specifies the list of Disks to be excluded from backing up. These disks... | the_stack_v2_python_sparse | cohesity_management_sdk/models/vmware_env_job_parameters.py | cohesity/management-sdk-python | train | 24 |
1a2d789c1e15c6edd14e23f3f8e02d9ff93a6dc4 | [
"self.jsonld = {'@type': 'ssn-ext:ObservationCollection', 'hasFeatureOfInterest': 'http://example.org/Sample_2', 'madeBySensor': 'http://example.org/s4', 'observedProperty': 'http://example.org/op2', 'phenomenonTime': '_:b13', 'usedProcedure': 'http://example.org/p3', 'hasMember': ['http://example.org/O5', 'http://... | <|body_start_0|>
self.jsonld = {'@type': 'ssn-ext:ObservationCollection', 'hasFeatureOfInterest': 'http://example.org/Sample_2', 'madeBySensor': 'http://example.org/s4', 'observedProperty': 'http://example.org/op2', 'phenomenonTime': '_:b13', 'usedProcedure': 'http://example.org/p3', 'hasMember': ['http://examp... | Create SSN-EXT Observation Collection | ObservationCollection | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ObservationCollection:
"""Create SSN-EXT Observation Collection"""
def __init__(self, comment):
"""instantiating Observation Collection Args: label, comment (literal): label and comment for the observation collection Returns: an observation collection: a collection of all observation... | stack_v2_sparse_classes_36k_train_012935 | 2,121 | permissive | [
{
"docstring": "instantiating Observation Collection Args: label, comment (literal): label and comment for the observation collection Returns: an observation collection: a collection of all observations performed",
"name": "__init__",
"signature": "def __init__(self, comment)"
},
{
"docstring": ... | 2 | stack_v2_sparse_classes_30k_test_000298 | Implement the Python class `ObservationCollection` described below.
Class description:
Create SSN-EXT Observation Collection
Method signatures and docstrings:
- def __init__(self, comment): instantiating Observation Collection Args: label, comment (literal): label and comment for the observation collection Returns: a... | Implement the Python class `ObservationCollection` described below.
Class description:
Create SSN-EXT Observation Collection
Method signatures and docstrings:
- def __init__(self, comment): instantiating Observation Collection Args: label, comment (literal): label and comment for the observation collection Returns: a... | 1993668bd75bc882286da818955a40dd01d2f7c6 | <|skeleton|>
class ObservationCollection:
"""Create SSN-EXT Observation Collection"""
def __init__(self, comment):
"""instantiating Observation Collection Args: label, comment (literal): label and comment for the observation collection Returns: an observation collection: a collection of all observation... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ObservationCollection:
"""Create SSN-EXT Observation Collection"""
def __init__(self, comment):
"""instantiating Observation Collection Args: label, comment (literal): label and comment for the observation collection Returns: an observation collection: a collection of all observations performed""... | the_stack_v2_python_sparse | PySOSA/ObservationCollection.py | landrs-toolkit/PySOSA | train | 1 |
863777be6a8136dd8144abda04eea8a9265533b8 | [
"data = {}\nif command is not None:\n data['_command'] = command\nfor size, name, _opt in payload_option:\n if size == SMPayloadType.PACKET and name in values:\n data[name] = values[name].json\n continue\n if isinstance(size.value, int):\n default = 0\n else:\n default = size... | <|body_start_0|>
data = {}
if command is not None:
data['_command'] = command
for size, name, _opt in payload_option:
if size == SMPayloadType.PACKET and name in values:
data[name] = values[name].json
continue
if isinstance(size... | JSON encoder to encode data in the stepmania protocol | JSONEncoder | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JSONEncoder:
"""JSON encoder to encode data in the stepmania protocol"""
def encode(cls, values, payload_option, command=None):
"""Encode values in a correct json payload"""
<|body_0|>
def decode(cls, payload, payload_option):
"""Decode a payload in a valid dict ... | stack_v2_sparse_classes_36k_train_012936 | 14,049 | permissive | [
{
"docstring": "Encode values in a correct json payload",
"name": "encode",
"signature": "def encode(cls, values, payload_option, command=None)"
},
{
"docstring": "Decode a payload in a valid dict given the payload option",
"name": "decode",
"signature": "def decode(cls, payload, payload... | 2 | stack_v2_sparse_classes_30k_train_010343 | Implement the Python class `JSONEncoder` described below.
Class description:
JSON encoder to encode data in the stepmania protocol
Method signatures and docstrings:
- def encode(cls, values, payload_option, command=None): Encode values in a correct json payload
- def decode(cls, payload, payload_option): Decode a pay... | Implement the Python class `JSONEncoder` described below.
Class description:
JSON encoder to encode data in the stepmania protocol
Method signatures and docstrings:
- def encode(cls, values, payload_option, command=None): Encode values in a correct json payload
- def decode(cls, payload, payload_option): Decode a pay... | cf20b363ed3d7bcb75101b17870e876a857ecd66 | <|skeleton|>
class JSONEncoder:
"""JSON encoder to encode data in the stepmania protocol"""
def encode(cls, values, payload_option, command=None):
"""Encode values in a correct json payload"""
<|body_0|>
def decode(cls, payload, payload_option):
"""Decode a payload in a valid dict ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JSONEncoder:
"""JSON encoder to encode data in the stepmania protocol"""
def encode(cls, values, payload_option, command=None):
"""Encode values in a correct json payload"""
data = {}
if command is not None:
data['_command'] = command
for size, name, _opt in pa... | the_stack_v2_python_sparse | smserver/smutils/smpacket/smencoder.py | Moutix/stepmania-server | train | 4 |
86ad86dc5c5dd74a17fd41fd0ddb73160d3f284f | [
"result = ''\nfor ch in mystring:\n if ch.isdigit() or ch == '-':\n result += ch\nreturn result",
"schools_urls_xpath = '//*[@id=\"phmain_0_AllResults\"]/ul/li/span[1]/a/@href'\nschools_urls = response.xpath(schools_urls_xpath).extract()\nfor url in schools_urls:\n yield scrapy.Request(response.urljo... | <|body_start_0|>
result = ''
for ch in mystring:
if ch.isdigit() or ch == '-':
result += ch
return result
<|end_body_0|>
<|body_start_1|>
schools_urls_xpath = '//*[@id="phmain_0_AllResults"]/ul/li/span[1]/a/@href'
schools_urls = response.xpath(schools... | a scrapy spider to crawl csmb.qc.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found | MontrealCsmbSpider | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MontrealCsmbSpider:
"""a scrapy spider to crawl csmb.qc.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found"""
def digits_only(self, mystring):
"""it ta... | stack_v2_sparse_classes_36k_train_012937 | 3,988 | no_license | [
{
"docstring": "it takes a sting conains some digits then return the only digits",
"name": "digits_only",
"signature": "def digits_only(self, mystring)"
},
{
"docstring": "get all schools urls then yield a Request for each one.",
"name": "parse",
"signature": "def parse(self, response)"
... | 3 | stack_v2_sparse_classes_30k_train_011228 | Implement the Python class `MontrealCsmbSpider` described below.
Class description:
a scrapy spider to crawl csmb.qc.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found
Method signatures... | Implement the Python class `MontrealCsmbSpider` described below.
Class description:
a scrapy spider to crawl csmb.qc.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found
Method signatures... | 350264cf6da323692c2838d8cb235ef61085851b | <|skeleton|>
class MontrealCsmbSpider:
"""a scrapy spider to crawl csmb.qc.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found"""
def digits_only(self, mystring):
"""it ta... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MontrealCsmbSpider:
"""a scrapy spider to crawl csmb.qc.ca domain to get school_name street_address city province postal_code phone_number school_url school_grades school_language school_type school_board response_url for each school found"""
def digits_only(self, mystring):
"""it takes a sting c... | the_stack_v2_python_sparse | school_scraping/spiders/montreal_csmb.py | ramadanmostafa/canada_school_scraping | train | 0 |
e3d08c81142929b34f52d3bab71457e6b8894706 | [
"idx1, idx2 = (-1, -1)\nrst = len(words)\nfor idx, word in enumerate(words):\n if word == word1:\n idx1 = idx\n if idx2 != -1:\n rst = min(rst, abs(idx1 - idx2))\n elif word == word2:\n idx2 = idx\n if idx1 != -1:\n rst = min(rst, abs(idx1 - idx2))\nreturn rst... | <|body_start_0|>
idx1, idx2 = (-1, -1)
rst = len(words)
for idx, word in enumerate(words):
if word == word1:
idx1 = idx
if idx2 != -1:
rst = min(rst, abs(idx1 - idx2))
elif word == word2:
idx2 = idx
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def shortestDistance(self, words, word1, word2):
""":type words: List[str] :type word1: str :type word2: str :rtype: int"""
<|body_0|>
def shortestDistance2(self, words, word1, word2):
""":type words: List[str] :type word1: str :type word2: str :rtype: int"... | stack_v2_sparse_classes_36k_train_012938 | 1,628 | no_license | [
{
"docstring": ":type words: List[str] :type word1: str :type word2: str :rtype: int",
"name": "shortestDistance",
"signature": "def shortestDistance(self, words, word1, word2)"
},
{
"docstring": ":type words: List[str] :type word1: str :type word2: str :rtype: int",
"name": "shortestDistanc... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def shortestDistance(self, words, word1, word2): :type words: List[str] :type word1: str :type word2: str :rtype: int
- def shortestDistance2(self, words, word1, word2): :type wo... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def shortestDistance(self, words, word1, word2): :type words: List[str] :type word1: str :type word2: str :rtype: int
- def shortestDistance2(self, words, word1, word2): :type wo... | 41365b549f1e6b04aac9f1632a66e71c1e05b322 | <|skeleton|>
class Solution:
def shortestDistance(self, words, word1, word2):
""":type words: List[str] :type word1: str :type word2: str :rtype: int"""
<|body_0|>
def shortestDistance2(self, words, word1, word2):
""":type words: List[str] :type word1: str :type word2: str :rtype: int"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def shortestDistance(self, words, word1, word2):
""":type words: List[str] :type word1: str :type word2: str :rtype: int"""
idx1, idx2 = (-1, -1)
rst = len(words)
for idx, word in enumerate(words):
if word == word1:
idx1 = idx
... | the_stack_v2_python_sparse | python practice/Array/243_shortest_word_distance.py | SuzyWu2014/coding-practice | train | 1 | |
4eb8ea7c1b562ff154bfa60141a6834c119fc649 | [
"i, j = (0, len(node_list) - 1)\nwhile i < j:\n if node_list[i] != node_list[j]:\n return False\n i += 1\n j -= 1\nreturn True",
"node_list = []\nif not head:\n return True\nwhile head:\n node_list.append(head.val)\n head = head.next\nreturn self.is_palindrome_list(node_list)"
] | <|body_start_0|>
i, j = (0, len(node_list) - 1)
while i < j:
if node_list[i] != node_list[j]:
return False
i += 1
j -= 1
return True
<|end_body_0|>
<|body_start_1|>
node_list = []
if not head:
return True
wh... | Solution | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def is_palindrome_list(self, node_list: ListNode) -> bool:
"""判断链表是否是回文串 Args: node_list: node链表 Returns: 布尔值"""
<|body_0|>
def is_palindrome(self, head: ListNode) -> bool:
"""返回交点 Args: head: 节点head Returns: 布尔值"""
<|body_1|>
<|end_skeleton|>
<|b... | stack_v2_sparse_classes_36k_train_012939 | 2,023 | permissive | [
{
"docstring": "判断链表是否是回文串 Args: node_list: node链表 Returns: 布尔值",
"name": "is_palindrome_list",
"signature": "def is_palindrome_list(self, node_list: ListNode) -> bool"
},
{
"docstring": "返回交点 Args: head: 节点head Returns: 布尔值",
"name": "is_palindrome",
"signature": "def is_palindrome(self... | 2 | stack_v2_sparse_classes_30k_train_013249 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def is_palindrome_list(self, node_list: ListNode) -> bool: 判断链表是否是回文串 Args: node_list: node链表 Returns: 布尔值
- def is_palindrome(self, head: ListNode) -> bool: 返回交点 Args: head: 节点h... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def is_palindrome_list(self, node_list: ListNode) -> bool: 判断链表是否是回文串 Args: node_list: node链表 Returns: 布尔值
- def is_palindrome(self, head: ListNode) -> bool: 返回交点 Args: head: 节点h... | 50f35eef6a0ad63173efed10df3c835b1dceaa3f | <|skeleton|>
class Solution:
def is_palindrome_list(self, node_list: ListNode) -> bool:
"""判断链表是否是回文串 Args: node_list: node链表 Returns: 布尔值"""
<|body_0|>
def is_palindrome(self, head: ListNode) -> bool:
"""返回交点 Args: head: 节点head Returns: 布尔值"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def is_palindrome_list(self, node_list: ListNode) -> bool:
"""判断链表是否是回文串 Args: node_list: node链表 Returns: 布尔值"""
i, j = (0, len(node_list) - 1)
while i < j:
if node_list[i] != node_list[j]:
return False
i += 1
j -= 1
... | the_stack_v2_python_sparse | src/leetcodepython/list/palindrome_linked_list_234.py | zhangyu345293721/leetcode | train | 101 | |
ed4a8d4e4bac5645ff2541d4a57d40adafd1545b | [
"self.graph_creator = create_molecular_torch_geometric_graph\nsuper().__init__(data_path, properties=properties, sanitize=sanitize, file_geometries=file_geometries, optimize_molecule=optimize_molecule)\nself.dataset = TorchGeometricGraphDataset(self.molecular_graphs)\nself.data_loader_fun = tg.data.DataLoader",
"... | <|body_start_0|>
self.graph_creator = create_molecular_torch_geometric_graph
super().__init__(data_path, properties=properties, sanitize=sanitize, file_geometries=file_geometries, optimize_molecule=optimize_molecule)
self.dataset = TorchGeometricGraphDataset(self.molecular_graphs)
self.d... | Data loader for graph data. | TorchGeometricGraphData | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TorchGeometricGraphData:
"""Data loader for graph data."""
def __init__(self, data_path: PathLike, properties: Optional[Union[str, List[str]]]=None, sanitize: bool=True, file_geometries: Optional[PathLike]=None, optimize_molecule: bool=False) -> None:
"""Generate a dataset using grap... | stack_v2_sparse_classes_36k_train_012940 | 3,077 | permissive | [
{
"docstring": "Generate a dataset using graphs Parameters ---------- data_path path of the csv file properties Labels names sanitize Check that molecules have a valid conformer file_geometries Path to a file with the geometries in PDB format optimize_molecule Optimize the geometry if the ``file_geometries`` is... | 2 | stack_v2_sparse_classes_30k_train_002527 | Implement the Python class `TorchGeometricGraphData` described below.
Class description:
Data loader for graph data.
Method signatures and docstrings:
- def __init__(self, data_path: PathLike, properties: Optional[Union[str, List[str]]]=None, sanitize: bool=True, file_geometries: Optional[PathLike]=None, optimize_mol... | Implement the Python class `TorchGeometricGraphData` described below.
Class description:
Data loader for graph data.
Method signatures and docstrings:
- def __init__(self, data_path: PathLike, properties: Optional[Union[str, List[str]]]=None, sanitize: bool=True, file_geometries: Optional[PathLike]=None, optimize_mol... | 4edc9dc363ce901b1fcc19444bec42fc5930c4b9 | <|skeleton|>
class TorchGeometricGraphData:
"""Data loader for graph data."""
def __init__(self, data_path: PathLike, properties: Optional[Union[str, List[str]]]=None, sanitize: bool=True, file_geometries: Optional[PathLike]=None, optimize_molecule: bool=False) -> None:
"""Generate a dataset using grap... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TorchGeometricGraphData:
"""Data loader for graph data."""
def __init__(self, data_path: PathLike, properties: Optional[Union[str, List[str]]]=None, sanitize: bool=True, file_geometries: Optional[PathLike]=None, optimize_molecule: bool=False) -> None:
"""Generate a dataset using graphs Parameters... | the_stack_v2_python_sparse | swan/dataset/torch_geometric_graph_data.py | nlesc-nano/swan | train | 15 |
581ec5db4a01dac41a9d66756a7b5da45b83e275 | [
"namespaces = {'xsi': LT_XSI_NS}\nschemaLocation = etree.QName(LT_XSI_NS, 'schemaLocation')\npayload = etree.Element('RTML', {schemaLocation: LT_SCHEMA_LOCATION}, xmlns=LT_XML_NS, mode='request', uid=format(str(request.id)), version='3.1a', nsmap=namespaces)\nreturn payload",
"altdata = request.allocation.altdata... | <|body_start_0|>
namespaces = {'xsi': LT_XSI_NS}
schemaLocation = etree.QName(LT_XSI_NS, 'schemaLocation')
payload = etree.Element('RTML', {schemaLocation: LT_SCHEMA_LOCATION}, xmlns=LT_XML_NS, mode='request', uid=format(str(request.id)), version='3.1a', nsmap=namespaces)
return payload
... | An XML structure for LT requests. | LTRequest | [
"BSD-3-Clause",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LTRequest:
"""An XML structure for LT requests."""
def _build_prolog(self, request):
"""Payload outline for all LT queue requests. Returns ---------- payload: etree.Element payload outline for LT requests."""
<|body_0|>
def _build_project(self, payload, request):
... | stack_v2_sparse_classes_36k_train_012941 | 27,052 | permissive | [
{
"docstring": "Payload outline for all LT queue requests. Returns ---------- payload: etree.Element payload outline for LT requests.",
"name": "_build_prolog",
"signature": "def _build_prolog(self, request)"
},
{
"docstring": "Payload header for all LT queue requests. Parameters ---------- payl... | 4 | null | Implement the Python class `LTRequest` described below.
Class description:
An XML structure for LT requests.
Method signatures and docstrings:
- def _build_prolog(self, request): Payload outline for all LT queue requests. Returns ---------- payload: etree.Element payload outline for LT requests.
- def _build_project(... | Implement the Python class `LTRequest` described below.
Class description:
An XML structure for LT requests.
Method signatures and docstrings:
- def _build_prolog(self, request): Payload outline for all LT queue requests. Returns ---------- payload: etree.Element payload outline for LT requests.
- def _build_project(... | 161d3532ba3ba059446addcdac58ca96f39e9636 | <|skeleton|>
class LTRequest:
"""An XML structure for LT requests."""
def _build_prolog(self, request):
"""Payload outline for all LT queue requests. Returns ---------- payload: etree.Element payload outline for LT requests."""
<|body_0|>
def _build_project(self, payload, request):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LTRequest:
"""An XML structure for LT requests."""
def _build_prolog(self, request):
"""Payload outline for all LT queue requests. Returns ---------- payload: etree.Element payload outline for LT requests."""
namespaces = {'xsi': LT_XSI_NS}
schemaLocation = etree.QName(LT_XSI_NS, ... | the_stack_v2_python_sparse | skyportal/facility_apis/lt.py | skyportal/skyportal | train | 80 |
fae61a9443a2b013bfcaf57539c0c6bbbdfacb38 | [
"self.users = {}\nself.tweetTime = {}\nself.recentMax = 0\nself.time = 0",
"if userId not in self.users.keys():\n self.users[userId] = user()\nself.users[userId].tweets.append(tweetId)\nself.tweetTime[tweetId] = self.time\nself.time += 1",
"if userId not in self.users.keys():\n return []\nmine = self.user... | <|body_start_0|>
self.users = {}
self.tweetTime = {}
self.recentMax = 0
self.time = 0
<|end_body_0|>
<|body_start_1|>
if userId not in self.users.keys():
self.users[userId] = user()
self.users[userId].tweets.append(tweetId)
self.tweetTime[tweetId] = s... | Twitter | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Twitter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def postTweet(self, userId: int, tweetId: int) -> None:
"""Compose a new tweet."""
<|body_1|>
def getNewsFeed(self, userId: int) -> List[int]:
"""Retrieve the 10 m... | stack_v2_sparse_classes_36k_train_012942 | 3,131 | no_license | [
{
"docstring": "Initialize your data structure here.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Compose a new tweet.",
"name": "postTweet",
"signature": "def postTweet(self, userId: int, tweetId: int) -> None"
},
{
"docstring": "Retrieve the 10 mos... | 5 | stack_v2_sparse_classes_30k_train_015150 | Implement the Python class `Twitter` described below.
Class description:
Implement the Twitter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def postTweet(self, userId: int, tweetId: int) -> None: Compose a new tweet.
- def getNewsFeed(self, userId: int) -> List... | Implement the Python class `Twitter` described below.
Class description:
Implement the Twitter class.
Method signatures and docstrings:
- def __init__(self): Initialize your data structure here.
- def postTweet(self, userId: int, tweetId: int) -> None: Compose a new tweet.
- def getNewsFeed(self, userId: int) -> List... | 6b24a99e5ce87bca5ec487a996fea80991380293 | <|skeleton|>
class Twitter:
def __init__(self):
"""Initialize your data structure here."""
<|body_0|>
def postTweet(self, userId: int, tweetId: int) -> None:
"""Compose a new tweet."""
<|body_1|>
def getNewsFeed(self, userId: int) -> List[int]:
"""Retrieve the 10 m... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Twitter:
def __init__(self):
"""Initialize your data structure here."""
self.users = {}
self.tweetTime = {}
self.recentMax = 0
self.time = 0
def postTweet(self, userId: int, tweetId: int) -> None:
"""Compose a new tweet."""
if userId not in self.use... | the_stack_v2_python_sparse | 355设计推特.py | Frodoooo/MyLeetCode | train | 0 | |
16d5c13fe9713e83a50b237a68bcdfce220bbacc | [
"scheduler_instance = getattr(self, self._scheduler_field, None)\nif scheduler_instance is None:\n raise WechatyPluginError('there is an error')\nassert isinstance(scheduler_instance, AsyncIOScheduler)\nreturn scheduler_instance",
"if getattr(self, self._scheduler_field, None) is not None:\n raise WechatyPu... | <|body_start_0|>
scheduler_instance = getattr(self, self._scheduler_field, None)
if scheduler_instance is None:
raise WechatyPluginError('there is an error')
assert isinstance(scheduler_instance, AsyncIOScheduler)
return scheduler_instance
<|end_body_0|>
<|body_start_1|>
... | scheduler mixin for wechaty | WechatySchedulerMixin | [
"Apache-2.0",
"LicenseRef-scancode-free-unknown"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WechatySchedulerMixin:
"""scheduler mixin for wechaty"""
def scheduler(self) -> AsyncIOScheduler:
"""get the scheduler"""
<|body_0|>
def scheduler(self, scheduler_instance: AsyncIOScheduler) -> None:
"""set the scheduler Args: scheduler_instance (AsyncIOScheduler... | stack_v2_sparse_classes_36k_train_012943 | 35,609 | permissive | [
{
"docstring": "get the scheduler",
"name": "scheduler",
"signature": "def scheduler(self) -> AsyncIOScheduler"
},
{
"docstring": "set the scheduler Args: scheduler_instance (AsyncIOScheduler): the instance of the scheduler",
"name": "scheduler",
"signature": "def scheduler(self, schedul... | 4 | stack_v2_sparse_classes_30k_train_017196 | Implement the Python class `WechatySchedulerMixin` described below.
Class description:
scheduler mixin for wechaty
Method signatures and docstrings:
- def scheduler(self) -> AsyncIOScheduler: get the scheduler
- def scheduler(self, scheduler_instance: AsyncIOScheduler) -> None: set the scheduler Args: scheduler_insta... | Implement the Python class `WechatySchedulerMixin` described below.
Class description:
scheduler mixin for wechaty
Method signatures and docstrings:
- def scheduler(self) -> AsyncIOScheduler: get the scheduler
- def scheduler(self, scheduler_instance: AsyncIOScheduler) -> None: set the scheduler Args: scheduler_insta... | e9a04a98a3b01f287760e2d2a4514e4a80ecd15f | <|skeleton|>
class WechatySchedulerMixin:
"""scheduler mixin for wechaty"""
def scheduler(self) -> AsyncIOScheduler:
"""get the scheduler"""
<|body_0|>
def scheduler(self, scheduler_instance: AsyncIOScheduler) -> None:
"""set the scheduler Args: scheduler_instance (AsyncIOScheduler... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WechatySchedulerMixin:
"""scheduler mixin for wechaty"""
def scheduler(self) -> AsyncIOScheduler:
"""get the scheduler"""
scheduler_instance = getattr(self, self._scheduler_field, None)
if scheduler_instance is None:
raise WechatyPluginError('there is an error')
... | the_stack_v2_python_sparse | src/wechaty/plugin.py | wechaty/python-wechaty | train | 1,266 |
387472346d0461269a4b94016b8f09059d456161 | [
"self.w = w\nself.total = sum(w)\nself.l = len(w)",
"seed = random.randint(1, self.total)\ncur = 0\nfor i in range(self.l):\n cur += self.w[i]\n if cur >= seed:\n return i"
] | <|body_start_0|>
self.w = w
self.total = sum(w)
self.l = len(w)
<|end_body_0|>
<|body_start_1|>
seed = random.randint(1, self.total)
cur = 0
for i in range(self.l):
cur += self.w[i]
if cur >= seed:
return i
<|end_body_1|>
| Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
self.w = w
self.total = sum(w)
self.l = len(w)
<|end_body_0|>
<|body_start_1|>
... | stack_v2_sparse_classes_36k_train_012944 | 1,297 | no_license | [
{
"docstring": ":type w: List[int]",
"name": "__init__",
"signature": "def __init__(self, w)"
},
{
"docstring": ":rtype: int",
"name": "pickIndex",
"signature": "def pickIndex(self)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012985 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def __init__(self, w): :type w: List[int]
- def pickIndex(self): :rtype: int
<|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|... | fd310ec0a989e003242f1840230aaac150f006f0 | <|skeleton|>
class Solution:
def __init__(self, w):
""":type w: List[int]"""
<|body_0|>
def pickIndex(self):
""":rtype: int"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def __init__(self, w):
""":type w: List[int]"""
self.w = w
self.total = sum(w)
self.l = len(w)
def pickIndex(self):
""":rtype: int"""
seed = random.randint(1, self.total)
cur = 0
for i in range(self.l):
cur += self.w[i]... | the_stack_v2_python_sparse | 900plus/RandomPickwithWeight528.py | jing1988a/python_fb | train | 0 | |
04a36bcdfda888677e735b3eb761cf5833ed0641 | [
"self.v_deprecate = v_deprecate\nself.v_remove = v_remove\nself.v_current = v_current\nself.details = details\nif self.v_deprecate is None and self.v_remove is not None:\n raise TypeError('Cannot set `v_remove` without also setting `v_deprecate`')\nself.is_deprecated = False\nself.is_unsupported = False\nif self... | <|body_start_0|>
self.v_deprecate = v_deprecate
self.v_remove = v_remove
self.v_current = v_current
self.details = details
if self.v_deprecate is None and self.v_remove is not None:
raise TypeError('Cannot set `v_remove` without also setting `v_deprecate`')
se... | Deprecated | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Deprecated:
def __init__(self, v_deprecate=None, v_remove=None, v_current=None, details=''):
"""Decorator to mark a function or class as deprecated. Issue warning when the function is called or the class is instantiated, and add a warning to the docstring. The optional `details` argument... | stack_v2_sparse_classes_36k_train_012945 | 16,173 | permissive | [
{
"docstring": "Decorator to mark a function or class as deprecated. Issue warning when the function is called or the class is instantiated, and add a warning to the docstring. The optional `details` argument will be appended to the deprecation message and the docstring Parameters ---------- v_deprecate: String... | 6 | stack_v2_sparse_classes_30k_train_013915 | Implement the Python class `Deprecated` described below.
Class description:
Implement the Deprecated class.
Method signatures and docstrings:
- def __init__(self, v_deprecate=None, v_remove=None, v_current=None, details=''): Decorator to mark a function or class as deprecated. Issue warning when the function is calle... | Implement the Python class `Deprecated` described below.
Class description:
Implement the Deprecated class.
Method signatures and docstrings:
- def __init__(self, v_deprecate=None, v_remove=None, v_current=None, details=''): Decorator to mark a function or class as deprecated. Issue warning when the function is calle... | 3709d5e97dd23efa0df1b79982ae029789e1af57 | <|skeleton|>
class Deprecated:
def __init__(self, v_deprecate=None, v_remove=None, v_current=None, details=''):
"""Decorator to mark a function or class as deprecated. Issue warning when the function is called or the class is instantiated, and add a warning to the docstring. The optional `details` argument... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Deprecated:
def __init__(self, v_deprecate=None, v_remove=None, v_current=None, details=''):
"""Decorator to mark a function or class as deprecated. Issue warning when the function is called or the class is instantiated, and add a warning to the docstring. The optional `details` argument will be appen... | the_stack_v2_python_sparse | hyperparameter_hunter/utils/version_utils.py | shaoeric/hyperparameter_hunter | train | 0 | |
04c66899a1645a2cd689f3fc5b87d142256ecd7e | [
"def get_mix_max(node):\n l_min_v = r_max_v = node.val\n if node.left:\n is_bst, l_min_v, l_max_v = get_mix_max(node.left)\n if not is_bst or l_max_v >= node.val:\n return (False, 0, 0)\n if node.right:\n is_bst, r_min_v, r_max_v = get_mix_max(node.right)\n if not is_... | <|body_start_0|>
def get_mix_max(node):
l_min_v = r_max_v = node.val
if node.left:
is_bst, l_min_v, l_max_v = get_mix_max(node.left)
if not is_bst or l_max_v >= node.val:
return (False, 0, 0)
if node.right:
i... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def isValidBST1(self, root: TreeNode) -> bool:
"""执行用时： 52 ms , 在所有 Python3 提交中击败了 75.68% 的用户 内存消耗： 17.8 MB , 在所有 Python3 提交中击败了 13.91% 的用户"""
<|body_0|>
def isValidBST(self, root: TreeNode) -> bool:
"""执行用时： 56 ms , 在所有 Python3 提交中击败了 54.71% 的用户 内存消耗： 17.8... | stack_v2_sparse_classes_36k_train_012946 | 3,014 | no_license | [
{
"docstring": "执行用时： 52 ms , 在所有 Python3 提交中击败了 75.68% 的用户 内存消耗： 17.8 MB , 在所有 Python3 提交中击败了 13.91% 的用户",
"name": "isValidBST1",
"signature": "def isValidBST1(self, root: TreeNode) -> bool"
},
{
"docstring": "执行用时： 56 ms , 在所有 Python3 提交中击败了 54.71% 的用户 内存消耗： 17.8 MB , 在所有 Python3 提交中击败了 18.29%... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValidBST1(self, root: TreeNode) -> bool: 执行用时： 52 ms , 在所有 Python3 提交中击败了 75.68% 的用户 内存消耗： 17.8 MB , 在所有 Python3 提交中击败了 13.91% 的用户
- def isValidBST(self, root: TreeNode) ->... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def isValidBST1(self, root: TreeNode) -> bool: 执行用时： 52 ms , 在所有 Python3 提交中击败了 75.68% 的用户 内存消耗： 17.8 MB , 在所有 Python3 提交中击败了 13.91% 的用户
- def isValidBST(self, root: TreeNode) ->... | d613ed8a5a2c15ace7d513965b372d128845d66a | <|skeleton|>
class Solution:
def isValidBST1(self, root: TreeNode) -> bool:
"""执行用时： 52 ms , 在所有 Python3 提交中击败了 75.68% 的用户 内存消耗： 17.8 MB , 在所有 Python3 提交中击败了 13.91% 的用户"""
<|body_0|>
def isValidBST(self, root: TreeNode) -> bool:
"""执行用时： 56 ms , 在所有 Python3 提交中击败了 54.71% 的用户 内存消耗： 17.8... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def isValidBST1(self, root: TreeNode) -> bool:
"""执行用时： 52 ms , 在所有 Python3 提交中击败了 75.68% 的用户 内存消耗： 17.8 MB , 在所有 Python3 提交中击败了 13.91% 的用户"""
def get_mix_max(node):
l_min_v = r_max_v = node.val
if node.left:
is_bst, l_min_v, l_max_v = get_mix_... | the_stack_v2_python_sparse | 验证二叉搜索树.py | nomboy/leetcode | train | 0 | |
02774c1261595edc12f3a21ea68dcdbe2bf3c05f | [
"identities = {'identity-uuid': {'uuid': 'identity-uuid'}}\nprocess_optout(identities, 'identity-uuid', datetime.datetime(2020, 1, 1), 'babyloss')\nself.assertEqual(identities, {'identity-uuid': {'uuid': 'identity-uuid', 'optout_timestamp': '2020-01-01T00:00:00', 'optout_reason': 'babyloss'}})",
"identities = {'i... | <|body_start_0|>
identities = {'identity-uuid': {'uuid': 'identity-uuid'}}
process_optout(identities, 'identity-uuid', datetime.datetime(2020, 1, 1), 'babyloss')
self.assertEqual(identities, {'identity-uuid': {'uuid': 'identity-uuid', 'optout_timestamp': '2020-01-01T00:00:00', 'optout_reason': '... | ProcessOptOutTests | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProcessOptOutTests:
def test_optout_added(self):
"""Adds the optout to the identity if there is none"""
<|body_0|>
def test_replace_optout(self):
"""If this optout is newer than the one on the identity, it should be replaced"""
<|body_1|>
def test_skip_o... | stack_v2_sparse_classes_36k_train_012947 | 17,808 | permissive | [
{
"docstring": "Adds the optout to the identity if there is none",
"name": "test_optout_added",
"signature": "def test_optout_added(self)"
},
{
"docstring": "If this optout is newer than the one on the identity, it should be replaced",
"name": "test_replace_optout",
"signature": "def tes... | 3 | stack_v2_sparse_classes_30k_val_000851 | Implement the Python class `ProcessOptOutTests` described below.
Class description:
Implement the ProcessOptOutTests class.
Method signatures and docstrings:
- def test_optout_added(self): Adds the optout to the identity if there is none
- def test_replace_optout(self): If this optout is newer than the one on the ide... | Implement the Python class `ProcessOptOutTests` described below.
Class description:
Implement the ProcessOptOutTests class.
Method signatures and docstrings:
- def test_optout_added(self): Adds the optout to the identity if there is none
- def test_replace_optout(self): If this optout is newer than the one on the ide... | e1ea0beaf079f4f4d5f9562fb9d9a4f0670f459f | <|skeleton|>
class ProcessOptOutTests:
def test_optout_added(self):
"""Adds the optout to the identity if there is none"""
<|body_0|>
def test_replace_optout(self):
"""If this optout is newer than the one on the identity, it should be replaced"""
<|body_1|>
def test_skip_o... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProcessOptOutTests:
def test_optout_added(self):
"""Adds the optout to the identity if there is none"""
identities = {'identity-uuid': {'uuid': 'identity-uuid'}}
process_optout(identities, 'identity-uuid', datetime.datetime(2020, 1, 1), 'babyloss')
self.assertEqual(identities, ... | the_stack_v2_python_sparse | scripts/migrate_to_rapidpro/test_collect_information.py | praekeltfoundation/ndoh-hub | train | 0 | |
e02af291c7ac26f913dcba28c1949fa44d17c552 | [
"self.X = X\nself.y = y\nself.pipeline_map = pipeline_map",
"if any([isinstance(item, CategoricalEncoder) for item in transforms]):\n categories = dict()\n for cat_col in columns:\n cats = X[~X[cat_col].isnull()][cat_col].unique().tolist()\n categories.update({cat_col: cats})\n transforms =... | <|body_start_0|>
self.X = X
self.y = y
self.pipeline_map = pipeline_map
<|end_body_0|>
<|body_start_1|>
if any([isinstance(item, CategoricalEncoder) for item in transforms]):
categories = dict()
for cat_col in columns:
cats = X[~X[cat_col].isnull(... | DataFrameTransformer | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DataFrameTransformer:
def __init__(self, X, pipeline_map, y=None):
""":param X: a Pandas DataFrame object. :param pipeline_map: :param y:"""
<|body_0|>
def column_transformer(self, X, columns, transforms):
"""Perform fit-and-transform on `columns` of DataFrame `X` ac... | stack_v2_sparse_classes_36k_train_012948 | 4,618 | permissive | [
{
"docstring": ":param X: a Pandas DataFrame object. :param pipeline_map: :param y:",
"name": "__init__",
"signature": "def __init__(self, X, pipeline_map, y=None)"
},
{
"docstring": "Perform fit-and-transform on `columns` of DataFrame `X` according to `transforms`, returns the transformed DataF... | 3 | stack_v2_sparse_classes_30k_train_004784 | Implement the Python class `DataFrameTransformer` described below.
Class description:
Implement the DataFrameTransformer class.
Method signatures and docstrings:
- def __init__(self, X, pipeline_map, y=None): :param X: a Pandas DataFrame object. :param pipeline_map: :param y:
- def column_transformer(self, X, columns... | Implement the Python class `DataFrameTransformer` described below.
Class description:
Implement the DataFrameTransformer class.
Method signatures and docstrings:
- def __init__(self, X, pipeline_map, y=None): :param X: a Pandas DataFrame object. :param pipeline_map: :param y:
- def column_transformer(self, X, columns... | 1121443bef901fc6c9ed9f7d3ac60a0885189753 | <|skeleton|>
class DataFrameTransformer:
def __init__(self, X, pipeline_map, y=None):
""":param X: a Pandas DataFrame object. :param pipeline_map: :param y:"""
<|body_0|>
def column_transformer(self, X, columns, transforms):
"""Perform fit-and-transform on `columns` of DataFrame `X` ac... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DataFrameTransformer:
def __init__(self, X, pipeline_map, y=None):
""":param X: a Pandas DataFrame object. :param pipeline_map: :param y:"""
self.X = X
self.y = y
self.pipeline_map = pipeline_map
def column_transformer(self, X, columns, transforms):
"""Perform fit-... | the_stack_v2_python_sparse | titanic/sk_util.py | comsaint/Data-Practice | train | 0 | |
99a588fd1b3c8e7defae24d01c4ae7e08c5fb5c1 | [
"if num_pixels is None and quantile is None:\n raise ValueError('either num_pixels or quantile must be given')\nself.num_pixels: float = num_pixels\n'Number of pixels with highest values to set to one.'\nself.quantile: float = quantile\n'Quantile of pixels to set to one, rest is set to 0;\\n overridden by... | <|body_start_0|>
if num_pixels is None and quantile is None:
raise ValueError('either num_pixels or quantile must be given')
self.num_pixels: float = num_pixels
'Number of pixels with highest values to set to one.'
self.quantile: float = quantile
'Quantile of pixels t... | Set all but the given highest number of pixels / q-th quantile in an image to zero, rest to 1. Mind for RGB images: A pixel here means a pixel in one channel. | BinarizeByQuantile | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BinarizeByQuantile:
"""Set all but the given highest number of pixels / q-th quantile in an image to zero, rest to 1. Mind for RGB images: A pixel here means a pixel in one channel."""
def __init__(self, quantile: float=None, num_pixels: int=None):
"""Init. :param quantile: quantile ... | stack_v2_sparse_classes_36k_train_012949 | 14,707 | permissive | [
{
"docstring": "Init. :param quantile: quantile of pixels to set to 1, rest is set to 0; overridden by ``num_pixels`` :param num_pixels: number of pixels with highest value to set to one, rest is set to 0",
"name": "__init__",
"signature": "def __init__(self, quantile: float=None, num_pixels: int=None)"... | 3 | stack_v2_sparse_classes_30k_train_009952 | Implement the Python class `BinarizeByQuantile` described below.
Class description:
Set all but the given highest number of pixels / q-th quantile in an image to zero, rest to 1. Mind for RGB images: A pixel here means a pixel in one channel.
Method signatures and docstrings:
- def __init__(self, quantile: float=None... | Implement the Python class `BinarizeByQuantile` described below.
Class description:
Set all but the given highest number of pixels / q-th quantile in an image to zero, rest to 1. Mind for RGB images: A pixel here means a pixel in one channel.
Method signatures and docstrings:
- def __init__(self, quantile: float=None... | 37b9fc83d7b14902dfe92e0c45071c150bcf3779 | <|skeleton|>
class BinarizeByQuantile:
"""Set all but the given highest number of pixels / q-th quantile in an image to zero, rest to 1. Mind for RGB images: A pixel here means a pixel in one channel."""
def __init__(self, quantile: float=None, num_pixels: int=None):
"""Init. :param quantile: quantile ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BinarizeByQuantile:
"""Set all but the given highest number of pixels / q-th quantile in an image to zero, rest to 1. Mind for RGB images: A pixel here means a pixel in one channel."""
def __init__(self, quantile: float=None, num_pixels: int=None):
"""Init. :param quantile: quantile of pixels to ... | the_stack_v2_python_sparse | hybrid_learning/datasets/transforms/image_transforms.py | JohnnyZhang917/hybrid_learning | train | 0 |
5b35ea4a5af61cc3193bbce9aee11e51dc5aa233 | [
"subscription.is_active = self.instance.expiration_time > timezone.now()\nsubscription.save()\nself.instance.subscription = subscription\nself.instance.save()",
"self.instance = self.instance or models.AppleReceipt()\nself.instance.receipt_data = data['receipt_data']\ntry:\n self.instance.update_info()\nexcept... | <|body_start_0|>
subscription.is_active = self.instance.expiration_time > timezone.now()
subscription.save()
self.instance.subscription = subscription
self.instance.save()
<|end_body_0|>
<|body_start_1|>
self.instance = self.instance or models.AppleReceipt()
self.instanc... | Serializer for an Apple receipt. | AppleReceiptSerializer | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AppleReceiptSerializer:
"""Serializer for an Apple receipt."""
def save(self, subscription):
"""Save the :class:`AppleReceipt` instance associated with the serializer. Args: subscription: The subscription to associate the Apple receipt being saved with."""
<|body_0|>
def... | stack_v2_sparse_classes_36k_train_012950 | 8,796 | permissive | [
{
"docstring": "Save the :class:`AppleReceipt` instance associated with the serializer. Args: subscription: The subscription to associate the Apple receipt being saved with.",
"name": "save",
"signature": "def save(self, subscription)"
},
{
"docstring": "Validate that the provided receipt data c... | 2 | stack_v2_sparse_classes_30k_train_012359 | Implement the Python class `AppleReceiptSerializer` described below.
Class description:
Serializer for an Apple receipt.
Method signatures and docstrings:
- def save(self, subscription): Save the :class:`AppleReceipt` instance associated with the serializer. Args: subscription: The subscription to associate the Apple... | Implement the Python class `AppleReceiptSerializer` described below.
Class description:
Serializer for an Apple receipt.
Method signatures and docstrings:
- def save(self, subscription): Save the :class:`AppleReceipt` instance associated with the serializer. Args: subscription: The subscription to associate the Apple... | e4b72484c42e88a6c0087c9b1d5fef240e66cbb0 | <|skeleton|>
class AppleReceiptSerializer:
"""Serializer for an Apple receipt."""
def save(self, subscription):
"""Save the :class:`AppleReceipt` instance associated with the serializer. Args: subscription: The subscription to associate the Apple receipt being saved with."""
<|body_0|>
def... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AppleReceiptSerializer:
"""Serializer for an Apple receipt."""
def save(self, subscription):
"""Save the :class:`AppleReceipt` instance associated with the serializer. Args: subscription: The subscription to associate the Apple receipt being saved with."""
subscription.is_active = self.in... | the_stack_v2_python_sparse | km_api/know_me/serializers/subscription_serializers.py | knowmetools/km-api | train | 4 |
e7e6af78d8ff9f7292f929d08e326a621a8b1fdc | [
"asserts.type_of(job_api, JobApiModel)\njob_dto = JobDto()\nmap_props(job_dto, job_api, JobDto._props)\nreturn job_dto",
"asserts.type_of(job_dto, JobDto)\njob_api = JobApiModel()\nmap_props(job_api, job_dto, JobDto._props)\nreturn job_api.ToMessage()"
] | <|body_start_0|>
asserts.type_of(job_api, JobApiModel)
job_dto = JobDto()
map_props(job_dto, job_api, JobDto._props)
return job_dto
<|end_body_0|>
<|body_start_1|>
asserts.type_of(job_dto, JobDto)
job_api = JobApiModel()
map_props(job_api, job_dto, JobDto._props)... | Represents job details. `selected_applicant` and `applicants` are only populated when the job owner makes a request. | JobApiModel | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class JobApiModel:
"""Represents job details. `selected_applicant` and `applicants` are only populated when the job owner makes a request."""
def to_job_dto(cls, job_api):
"""Translates the given JobApiModel to a JobDto. :param job_api: (api.jobs.JobApiModel) :return: (dto.jobs.JobDto)"""
... | stack_v2_sparse_classes_36k_train_012951 | 1,781 | no_license | [
{
"docstring": "Translates the given JobApiModel to a JobDto. :param job_api: (api.jobs.JobApiModel) :return: (dto.jobs.JobDto)",
"name": "to_job_dto",
"signature": "def to_job_dto(cls, job_api)"
},
{
"docstring": "Translates the given JobDto to an JobApiModel. :param job_dto: (dto.jobs.JobDto) ... | 2 | null | Implement the Python class `JobApiModel` described below.
Class description:
Represents job details. `selected_applicant` and `applicants` are only populated when the job owner makes a request.
Method signatures and docstrings:
- def to_job_dto(cls, job_api): Translates the given JobApiModel to a JobDto. :param job_a... | Implement the Python class `JobApiModel` described below.
Class description:
Represents job details. `selected_applicant` and `applicants` are only populated when the job owner makes a request.
Method signatures and docstrings:
- def to_job_dto(cls, job_api): Translates the given JobApiModel to a JobDto. :param job_a... | 1d6522069da3e5a6de41ce948b04872d0a994cca | <|skeleton|>
class JobApiModel:
"""Represents job details. `selected_applicant` and `applicants` are only populated when the job owner makes a request."""
def to_job_dto(cls, job_api):
"""Translates the given JobApiModel to a JobDto. :param job_api: (api.jobs.JobApiModel) :return: (dto.jobs.JobDto)"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class JobApiModel:
"""Represents job details. `selected_applicant` and `applicants` are only populated when the job owner makes a request."""
def to_job_dto(cls, job_api):
"""Translates the given JobApiModel to a JobDto. :param job_api: (api.jobs.JobApiModel) :return: (dto.jobs.JobDto)"""
asser... | the_stack_v2_python_sparse | models/api/jobs.py | venvadlamani/HumanLink | train | 0 |
f3a4d41e75f6def5ca56c1e955dc41618d7087d8 | [
"self.safe_update(**kwargs)\nif butler is not None:\n self.log.warn('Ignoring butler in extract()')\ndtables = stack_summary_table(data, self, tablename='outliers', keep_cols=['nbad_total', 'nbad_rows', 'nbad_cols', 'slot', 'amp'])\nreturn dtables",
"self.safe_update(**kwargs)\nconfig_table = get_run_config_ta... | <|body_start_0|>
self.safe_update(**kwargs)
if butler is not None:
self.log.warn('Ignoring butler in extract()')
dtables = stack_summary_table(data, self, tablename='outliers', keep_cols=['nbad_total', 'nbad_rows', 'nbad_cols', 'slot', 'amp'])
return dtables
<|end_body_0|>
<... | Summarize the results for the superbias outlier analysis | SuperbiasOutlierSummaryTask | [
"BSD-2-Clause",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SuperbiasOutlierSummaryTask:
"""Summarize the results for the superbias outlier analysis"""
def extract(self, butler, data, **kwargs):
"""Make a summry table of the bias FFT data Parameters ---------- butler : `Butler` The data butler data : `dict` Dictionary (or other structure) con... | stack_v2_sparse_classes_36k_train_012952 | 15,893 | permissive | [
{
"docstring": "Make a summry table of the bias FFT data Parameters ---------- butler : `Butler` The data butler data : `dict` Dictionary (or other structure) contain the input data kwargs Used to override default configuration Returns ------- dtables : `TableDict` The resulting data",
"name": "extract",
... | 2 | stack_v2_sparse_classes_30k_train_016552 | Implement the Python class `SuperbiasOutlierSummaryTask` described below.
Class description:
Summarize the results for the superbias outlier analysis
Method signatures and docstrings:
- def extract(self, butler, data, **kwargs): Make a summry table of the bias FFT data Parameters ---------- butler : `Butler` The data... | Implement the Python class `SuperbiasOutlierSummaryTask` described below.
Class description:
Summarize the results for the superbias outlier analysis
Method signatures and docstrings:
- def extract(self, butler, data, **kwargs): Make a summry table of the bias FFT data Parameters ---------- butler : `Butler` The data... | 28418284fdaf2b2fb0afbeccd4324f7ad3e676c8 | <|skeleton|>
class SuperbiasOutlierSummaryTask:
"""Summarize the results for the superbias outlier analysis"""
def extract(self, butler, data, **kwargs):
"""Make a summry table of the bias FFT data Parameters ---------- butler : `Butler` The data butler data : `dict` Dictionary (or other structure) con... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SuperbiasOutlierSummaryTask:
"""Summarize the results for the superbias outlier analysis"""
def extract(self, butler, data, **kwargs):
"""Make a summry table of the bias FFT data Parameters ---------- butler : `Butler` The data butler data : `dict` Dictionary (or other structure) contain the inpu... | the_stack_v2_python_sparse | python/lsst/eo_utils/bias/superbias.py | lsst-camera-dh/EO-utilities | train | 2 |
f7c0bbb599f37d27466eb0c58d11d34cd7dd0d74 | [
"super(RemoteMonitor, self).__init__()\nif requests is None:\n raise ImportError(\"RemoteMonitor requires the 'requests' library.Run pip install requests.\")\nself.root = root\nself.path = path\nself.field = field\nself.headers = headers\nself.monitors = monitors\nself.send_as_json = send_as_json",
"monitors =... | <|body_start_0|>
super(RemoteMonitor, self).__init__()
if requests is None:
raise ImportError("RemoteMonitor requires the 'requests' library.Run pip install requests.")
self.root = root
self.path = path
self.field = field
self.headers = headers
self.mo... | Callback to stream training events to a server with the same interface as Keras RemoteMonitor. | RemoteMonitor | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class RemoteMonitor:
"""Callback to stream training events to a server with the same interface as Keras RemoteMonitor."""
def __init__(self, root='http://localhost:9000', path='/publish/epoch/end/', field='data', headers=None, send_as_json=False, monitors=None):
"""Constructor Arguments: r... | stack_v2_sparse_classes_36k_train_012953 | 2,291 | permissive | [
{
"docstring": "Constructor Arguments: root (str): Root server url path (str): Relative path to root to post events field (str): Json field of post data headers (str): Http headers send_as_json (bool): If false sends data as plain json. Otherwise sends as json. monitors (list): List of monitors names to include... | 2 | stack_v2_sparse_classes_30k_val_001075 | Implement the Python class `RemoteMonitor` described below.
Class description:
Callback to stream training events to a server with the same interface as Keras RemoteMonitor.
Method signatures and docstrings:
- def __init__(self, root='http://localhost:9000', path='/publish/epoch/end/', field='data', headers=None, sen... | Implement the Python class `RemoteMonitor` described below.
Class description:
Callback to stream training events to a server with the same interface as Keras RemoteMonitor.
Method signatures and docstrings:
- def __init__(self, root='http://localhost:9000', path='/publish/epoch/end/', field='data', headers=None, sen... | d1440b7a9c3ab2c1d3abbb282abb9ee1ea240797 | <|skeleton|>
class RemoteMonitor:
"""Callback to stream training events to a server with the same interface as Keras RemoteMonitor."""
def __init__(self, root='http://localhost:9000', path='/publish/epoch/end/', field='data', headers=None, send_as_json=False, monitors=None):
"""Constructor Arguments: r... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class RemoteMonitor:
"""Callback to stream training events to a server with the same interface as Keras RemoteMonitor."""
def __init__(self, root='http://localhost:9000', path='/publish/epoch/end/', field='data', headers=None, send_as_json=False, monitors=None):
"""Constructor Arguments: root (str): Ro... | the_stack_v2_python_sparse | torchero/callbacks/remote.py | juancruzsosa/torchero | train | 10 |
283747594be99f60c67c39cedfd101a9d2d4dd78 | [
"self.input_type = input_type\nself.input_shape = input_shape\nself.channel_axes = channel_axes",
"if self.per_channel and (self.input_shape is None or self.channel_axes is None):\n raise ValueError('The `input_shape` and `channel_axes` arguments are required when using per-channel quantization.')\nprefix = se... | <|body_start_0|>
self.input_type = input_type
self.input_shape = input_shape
self.channel_axes = channel_axes
<|end_body_0|>
<|body_start_1|>
if self.per_channel and (self.input_shape is None or self.channel_axes is None):
raise ValueError('The `input_shape` and `channel_axe... | AsymmetricQuantizerV2 | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class AsymmetricQuantizerV2:
def set_input_spec(self, input_type: str, input_shape: Optional[List[int]]=None, channel_axes: Optional[List[int]]=None):
"""Sets input tensor specification for the quantizer. :param input_type: Indicates the type of input tensor: `inputs` or `weights`. :param inpu... | stack_v2_sparse_classes_36k_train_012954 | 5,442 | permissive | [
{
"docstring": "Sets input tensor specification for the quantizer. :param input_type: Indicates the type of input tensor: `inputs` or `weights`. :param input_shape: Shape of the input tensor for which the quantization is applied. Required only for per-channel quantization. :param channel_axes: Axes numbers of t... | 2 | null | Implement the Python class `AsymmetricQuantizerV2` described below.
Class description:
Implement the AsymmetricQuantizerV2 class.
Method signatures and docstrings:
- def set_input_spec(self, input_type: str, input_shape: Optional[List[int]]=None, channel_axes: Optional[List[int]]=None): Sets input tensor specificatio... | Implement the Python class `AsymmetricQuantizerV2` described below.
Class description:
Implement the AsymmetricQuantizerV2 class.
Method signatures and docstrings:
- def set_input_spec(self, input_type: str, input_shape: Optional[List[int]]=None, channel_axes: Optional[List[int]]=None): Sets input tensor specificatio... | c027c8b43c4865d46b8de01d8350dd338ec5a874 | <|skeleton|>
class AsymmetricQuantizerV2:
def set_input_spec(self, input_type: str, input_shape: Optional[List[int]]=None, channel_axes: Optional[List[int]]=None):
"""Sets input tensor specification for the quantizer. :param input_type: Indicates the type of input tensor: `inputs` or `weights`. :param inpu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class AsymmetricQuantizerV2:
def set_input_spec(self, input_type: str, input_shape: Optional[List[int]]=None, channel_axes: Optional[List[int]]=None):
"""Sets input tensor specification for the quantizer. :param input_type: Indicates the type of input tensor: `inputs` or `weights`. :param input_shape: Shape... | the_stack_v2_python_sparse | nncf/experimental/tensorflow/quantization/quantizers.py | openvinotoolkit/nncf | train | 558 | |
b9d3e235d9f24444f8a5c3ab2580c9e007696479 | [
"if not TTS:\n raise ImportError('TextToSpeech pipeline is not available - install \"pipeline\" extra to enable')\npath = path if path else 'neuml/ljspeech-jets-onnx'\nconfig = hf_hub_download(path, filename='config.yaml')\nmodel = hf_hub_download(path, filename='model.onnx')\nwith open(config, 'r', encoding='ut... | <|body_start_0|>
if not TTS:
raise ImportError('TextToSpeech pipeline is not available - install "pipeline" extra to enable')
path = path if path else 'neuml/ljspeech-jets-onnx'
config = hf_hub_download(path, filename='config.yaml')
model = hf_hub_download(path, filename='mod... | Generates speech from text | TextToSpeech | [
"Apache-2.0",
"LicenseRef-scancode-proprietary-license"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TextToSpeech:
"""Generates speech from text"""
def __init__(self, path=None, maxtokens=512):
"""Creates a new TextToSpeech pipeline. Args: path: optional Hugging Face model hub id maxtokens: maximum number of tokens model can process, defaults to 512"""
<|body_0|>
def __... | stack_v2_sparse_classes_36k_train_012955 | 3,823 | permissive | [
{
"docstring": "Creates a new TextToSpeech pipeline. Args: path: optional Hugging Face model hub id maxtokens: maximum number of tokens model can process, defaults to 512",
"name": "__init__",
"signature": "def __init__(self, path=None, maxtokens=512)"
},
{
"docstring": "Generates speech from te... | 4 | null | Implement the Python class `TextToSpeech` described below.
Class description:
Generates speech from text
Method signatures and docstrings:
- def __init__(self, path=None, maxtokens=512): Creates a new TextToSpeech pipeline. Args: path: optional Hugging Face model hub id maxtokens: maximum number of tokens model can p... | Implement the Python class `TextToSpeech` described below.
Class description:
Generates speech from text
Method signatures and docstrings:
- def __init__(self, path=None, maxtokens=512): Creates a new TextToSpeech pipeline. Args: path: optional Hugging Face model hub id maxtokens: maximum number of tokens model can p... | 789a4555cb60ee9cdfa69afae5a5236d197e2b07 | <|skeleton|>
class TextToSpeech:
"""Generates speech from text"""
def __init__(self, path=None, maxtokens=512):
"""Creates a new TextToSpeech pipeline. Args: path: optional Hugging Face model hub id maxtokens: maximum number of tokens model can process, defaults to 512"""
<|body_0|>
def __... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TextToSpeech:
"""Generates speech from text"""
def __init__(self, path=None, maxtokens=512):
"""Creates a new TextToSpeech pipeline. Args: path: optional Hugging Face model hub id maxtokens: maximum number of tokens model can process, defaults to 512"""
if not TTS:
raise Impor... | the_stack_v2_python_sparse | src/python/txtai/pipeline/audio/texttospeech.py | neuml/txtai | train | 4,804 |
f0349ce7de8159d47191604fab68f67922246401 | [
"for prop in self.__dict__.values():\n if issubclass(prop.__class__, JobPropertyContainer) and 'signatures' in prop.__dict__.keys():\n prop.setL2()",
"for prop in self.__dict__.values():\n if issubclass(prop.__class__, JobPropertyContainer) and 'signatures' in prop.__dict__.keys():\n prop.setE... | <|body_start_0|>
for prop in self.__dict__.values():
if issubclass(prop.__class__, JobPropertyContainer) and 'signatures' in prop.__dict__.keys():
prop.setL2()
<|end_body_0|>
<|body_start_1|>
for prop in self.__dict__.values():
if issubclass(prop.__class__, JobPr... | Trigger top flags | Trigger | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Trigger:
"""Trigger top flags"""
def Slices_LVL2_setOn(self):
"""Runs setL2 flags in all slices. Effectivelly enable LVL2."""
<|body_0|>
def Slices_EF_setOn(self):
"""Runs setEF flags in all slices. Effectivelly enable EF."""
<|body_1|>
def Slices_al... | stack_v2_sparse_classes_36k_train_012956 | 43,775 | permissive | [
{
"docstring": "Runs setL2 flags in all slices. Effectivelly enable LVL2.",
"name": "Slices_LVL2_setOn",
"signature": "def Slices_LVL2_setOn(self)"
},
{
"docstring": "Runs setEF flags in all slices. Effectivelly enable EF.",
"name": "Slices_EF_setOn",
"signature": "def Slices_EF_setOn(se... | 6 | stack_v2_sparse_classes_30k_test_000647 | Implement the Python class `Trigger` described below.
Class description:
Trigger top flags
Method signatures and docstrings:
- def Slices_LVL2_setOn(self): Runs setL2 flags in all slices. Effectivelly enable LVL2.
- def Slices_EF_setOn(self): Runs setEF flags in all slices. Effectivelly enable EF.
- def Slices_all_se... | Implement the Python class `Trigger` described below.
Class description:
Trigger top flags
Method signatures and docstrings:
- def Slices_LVL2_setOn(self): Runs setL2 flags in all slices. Effectivelly enable LVL2.
- def Slices_EF_setOn(self): Runs setEF flags in all slices. Effectivelly enable EF.
- def Slices_all_se... | 354f92551294f7be678aebcd7b9d67d2c4448176 | <|skeleton|>
class Trigger:
"""Trigger top flags"""
def Slices_LVL2_setOn(self):
"""Runs setL2 flags in all slices. Effectivelly enable LVL2."""
<|body_0|>
def Slices_EF_setOn(self):
"""Runs setEF flags in all slices. Effectivelly enable EF."""
<|body_1|>
def Slices_al... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Trigger:
"""Trigger top flags"""
def Slices_LVL2_setOn(self):
"""Runs setL2 flags in all slices. Effectivelly enable LVL2."""
for prop in self.__dict__.values():
if issubclass(prop.__class__, JobPropertyContainer) and 'signatures' in prop.__dict__.keys():
prop.... | the_stack_v2_python_sparse | Trigger/TriggerCommon/TriggerJobOpts/python/TriggerFlags.py | strigazi/athena | train | 0 |
a5fd758fbb082befc19b53f8003cf2fdbbe2b7c8 | [
"if rng is None:\n self.rng = np.random.RandomState(np.random.randint(0, 10000))\nelse:\n self.rng = rng\nself.scale = scale",
"if np.any(theta == 0.0):\n return np.inf\nwith np.errstate(divide='ignore'):\n return np.log(np.log(1 + 3.0 * (self.scale / np.exp(theta)) ** 2))",
"lamda = np.abs(self.rng... | <|body_start_0|>
if rng is None:
self.rng = np.random.RandomState(np.random.randint(0, 10000))
else:
self.rng = rng
self.scale = scale
<|end_body_0|>
<|body_start_1|>
if np.any(theta == 0.0):
return np.inf
with np.errstate(divide='ignore'):
... | HorseshoePrior | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class HorseshoePrior:
def __init__(self, scale=0.1, rng=None):
"""Horseshoe Prior as it is used in spearmint :param scale: Scaling parameter. See below how it is influenced the distribution. :type scale: float :param rng: Random number generator :type rng: np.random.RandomState"""
<|bo... | stack_v2_sparse_classes_36k_train_012957 | 11,290 | no_license | [
{
"docstring": "Horseshoe Prior as it is used in spearmint :param scale: Scaling parameter. See below how it is influenced the distribution. :type scale: float :param rng: Random number generator :type rng: np.random.RandomState",
"name": "__init__",
"signature": "def __init__(self, scale=0.1, rng=None)... | 4 | stack_v2_sparse_classes_30k_train_002320 | Implement the Python class `HorseshoePrior` described below.
Class description:
Implement the HorseshoePrior class.
Method signatures and docstrings:
- def __init__(self, scale=0.1, rng=None): Horseshoe Prior as it is used in spearmint :param scale: Scaling parameter. See below how it is influenced the distribution. ... | Implement the Python class `HorseshoePrior` described below.
Class description:
Implement the HorseshoePrior class.
Method signatures and docstrings:
- def __init__(self, scale=0.1, rng=None): Horseshoe Prior as it is used in spearmint :param scale: Scaling parameter. See below how it is influenced the distribution. ... | 5e2a2996bdae632c92a3bb8f891cfac81c65380d | <|skeleton|>
class HorseshoePrior:
def __init__(self, scale=0.1, rng=None):
"""Horseshoe Prior as it is used in spearmint :param scale: Scaling parameter. See below how it is influenced the distribution. :type scale: float :param rng: Random number generator :type rng: np.random.RandomState"""
<|bo... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class HorseshoePrior:
def __init__(self, scale=0.1, rng=None):
"""Horseshoe Prior as it is used in spearmint :param scale: Scaling parameter. See below how it is influenced the distribution. :type scale: float :param rng: Random number generator :type rng: np.random.RandomState"""
if rng is None:
... | the_stack_v2_python_sparse | photonai/optimization/fabolas/Priors.py | bcottman/photon | train | 7 | |
6cfee43b0338e9d172c4ca80bc8a6451963240fd | [
"super(FeatureFusionBlock, self).__init__()\nself.resConfUnit1 = ResidualConvUnit(features)\nself.resConfUnit2 = ResidualConvUnit(features)",
"output = xs[0]\nif len(xs) == 2:\n output += self.resConfUnit1(xs[1])\noutput = self.resConfUnit2(output)\noutput = nn.functional.interpolate(output, scale_factor=2, mo... | <|body_start_0|>
super(FeatureFusionBlock, self).__init__()
self.resConfUnit1 = ResidualConvUnit(features)
self.resConfUnit2 = ResidualConvUnit(features)
<|end_body_0|>
<|body_start_1|>
output = xs[0]
if len(xs) == 2:
output += self.resConfUnit1(xs[1])
output... | Feature fusion block. | FeatureFusionBlock | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FeatureFusionBlock:
"""Feature fusion block."""
def __init__(self, features):
"""Init. Args: features (int): number of features"""
<|body_0|>
def forward(self, *xs):
"""Forward pass. Returns: tensor: output"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|... | stack_v2_sparse_classes_36k_train_012958 | 17,410 | permissive | [
{
"docstring": "Init. Args: features (int): number of features",
"name": "__init__",
"signature": "def __init__(self, features)"
},
{
"docstring": "Forward pass. Returns: tensor: output",
"name": "forward",
"signature": "def forward(self, *xs)"
}
] | 2 | null | Implement the Python class `FeatureFusionBlock` described below.
Class description:
Feature fusion block.
Method signatures and docstrings:
- def __init__(self, features): Init. Args: features (int): number of features
- def forward(self, *xs): Forward pass. Returns: tensor: output | Implement the Python class `FeatureFusionBlock` described below.
Class description:
Feature fusion block.
Method signatures and docstrings:
- def __init__(self, features): Init. Args: features (int): number of features
- def forward(self, *xs): Forward pass. Returns: tensor: output
<|skeleton|>
class FeatureFusionBl... | a00c3619bf4042e446e1919087f0b09fe9fa3a65 | <|skeleton|>
class FeatureFusionBlock:
"""Feature fusion block."""
def __init__(self, features):
"""Init. Args: features (int): number of features"""
<|body_0|>
def forward(self, *xs):
"""Forward pass. Returns: tensor: output"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FeatureFusionBlock:
"""Feature fusion block."""
def __init__(self, features):
"""Init. Args: features (int): number of features"""
super(FeatureFusionBlock, self).__init__()
self.resConfUnit1 = ResidualConvUnit(features)
self.resConfUnit2 = ResidualConvUnit(features)
... | the_stack_v2_python_sparse | nasws/cnn/search_space/monodepth/models/blocks.py | kcyu2014/nas-landmarkreg | train | 10 |
25de847bee622f603c90072a90a519b5c01b37b2 | [
"if mode == 'python':\n from ..python.tags import tag_manager as tmgr\n return tmgr.register(tag_class_or_alias)\n\ndef decorator(tag_class):\n \"\"\"The decorator for the tag class\"\"\"\n name = tag_class.__name__\n if name.startswith('Tag'):\n name = name[3:]\n if not name.isupper():... | <|body_start_0|>
if mode == 'python':
from ..python.tags import tag_manager as tmgr
return tmgr.register(tag_class_or_alias)
def decorator(tag_class):
"""The decorator for the tag class"""
name = tag_class.__name__
if name.startswith('Tag'):
... | The tag manager Attributes: INSTANCE: The instance of this singleton class tags: The tags database | TagManager | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TagManager:
"""The tag manager Attributes: INSTANCE: The instance of this singleton class tags: The tags database"""
def register(self, tag_class_or_alias=None, mode='standard'):
"""Register a tag This can be worked as a decorator Args: tag_class_or_alias: The tag class or the alias ... | stack_v2_sparse_classes_36k_train_012959 | 3,349 | permissive | [
{
"docstring": "Register a tag This can be worked as a decorator Args: tag_class_or_alias: The tag class or the alias for the tag class to decorate mode: Whether do it for given mode Returns: The decorator or the decorated class",
"name": "register",
"signature": "def register(self, tag_class_or_alias=N... | 3 | stack_v2_sparse_classes_30k_train_011318 | Implement the Python class `TagManager` described below.
Class description:
The tag manager Attributes: INSTANCE: The instance of this singleton class tags: The tags database
Method signatures and docstrings:
- def register(self, tag_class_or_alias=None, mode='standard'): Register a tag This can be worked as a decora... | Implement the Python class `TagManager` described below.
Class description:
The tag manager Attributes: INSTANCE: The instance of this singleton class tags: The tags database
Method signatures and docstrings:
- def register(self, tag_class_or_alias=None, mode='standard'): Register a tag This can be worked as a decora... | bf84d631a2ecab0c020ba883bf2a09042715f772 | <|skeleton|>
class TagManager:
"""The tag manager Attributes: INSTANCE: The instance of this singleton class tags: The tags database"""
def register(self, tag_class_or_alias=None, mode='standard'):
"""Register a tag This can be worked as a decorator Args: tag_class_or_alias: The tag class or the alias ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TagManager:
"""The tag manager Attributes: INSTANCE: The instance of this singleton class tags: The tags database"""
def register(self, tag_class_or_alias=None, mode='standard'):
"""Register a tag This can be worked as a decorator Args: tag_class_or_alias: The tag class or the alias for the tag c... | the_stack_v2_python_sparse | liquid/tags/manager.py | lingfromSh/liquidpy | train | 0 |
e25b931e66355b4617b284a97d6995df088166b1 | [
"self._logger = logger\nself._aliases = aliases\nself._model_context = model_context",
"model_path_tokens = self._parse_model_path(model_path)\nfolder_path = '/'.join(model_path_tokens[1:])\nmodel_path = '%s:/%s' % (model_path_tokens[0], folder_path)\nprint('')\nif control_option == ControlOptions.RECURSIVE:\n ... | <|body_start_0|>
self._logger = logger
self._aliases = aliases
self._model_context = model_context
<|end_body_0|>
<|body_start_1|>
model_path_tokens = self._parse_model_path(model_path)
folder_path = '/'.join(model_path_tokens[1:])
model_path = '%s:/%s' % (model_path_tok... | Class for printing the recognized model metadata to STDOUT. | ModelHelpPrinter | [
"UPL-1.0",
"LicenseRef-scancode-other-copyleft",
"MIT",
"GPL-2.0-only",
"Classpath-exception-2.0",
"Apache-2.0",
"CDDL-1.1"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ModelHelpPrinter:
"""Class for printing the recognized model metadata to STDOUT."""
def __init__(self, model_context, aliases, logger):
""":param model_context: The model context :param aliases: A reference to an Aliases class instance :param logger: A reference to the platform logge... | stack_v2_sparse_classes_36k_train_012960 | 6,818 | permissive | [
{
"docstring": ":param model_context: The model context :param aliases: A reference to an Aliases class instance :param logger: A reference to the platform logger to write to, if a log entry needs to be made",
"name": "__init__",
"signature": "def __init__(self, model_context, aliases, logger)"
},
{... | 4 | null | Implement the Python class `ModelHelpPrinter` described below.
Class description:
Class for printing the recognized model metadata to STDOUT.
Method signatures and docstrings:
- def __init__(self, model_context, aliases, logger): :param model_context: The model context :param aliases: A reference to an Aliases class ... | Implement the Python class `ModelHelpPrinter` described below.
Class description:
Class for printing the recognized model metadata to STDOUT.
Method signatures and docstrings:
- def __init__(self, model_context, aliases, logger): :param model_context: The model context :param aliases: A reference to an Aliases class ... | 9fd74ae578a5b1353662facb0405e5672ecc5191 | <|skeleton|>
class ModelHelpPrinter:
"""Class for printing the recognized model metadata to STDOUT."""
def __init__(self, model_context, aliases, logger):
""":param model_context: The model context :param aliases: A reference to an Aliases class instance :param logger: A reference to the platform logge... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ModelHelpPrinter:
"""Class for printing the recognized model metadata to STDOUT."""
def __init__(self, model_context, aliases, logger):
""":param model_context: The model context :param aliases: A reference to an Aliases class instance :param logger: A reference to the platform logger to write to... | the_stack_v2_python_sparse | core/src/main/python/wlsdeploy/tool/modelhelp/model_help_printer.py | oracle/weblogic-deploy-tooling | train | 148 |
79c6fd96ee3fa40e17e393494783294e2869252f | [
"if not any(values.values()):\n values['eia860'] = Eia860Settings()\n values['eia861'] = Eia861Settings()\n values['eia923'] = Eia923Settings()\nreturn values",
"eia923 = values.get('eia923')\neia860 = values.get('eia860')\nif not eia923 and eia860:\n values['eia923'] = Eia923Settings(years=eia860.yea... | <|body_start_0|>
if not any(values.values()):
values['eia860'] = Eia860Settings()
values['eia861'] = Eia861Settings()
values['eia923'] = Eia923Settings()
return values
<|end_body_0|>
<|body_start_1|>
eia923 = values.get('eia923')
eia860 = values.get('... | An immutable pydantic model to validate EIA datasets settings. Args: eia860: Immutable pydantic model to validate eia860 settings. eia923: Immutable pydantic model to validate eia923 settings. | EiaSettings | [
"CC-BY-4.0",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EiaSettings:
"""An immutable pydantic model to validate EIA datasets settings. Args: eia860: Immutable pydantic model to validate eia860 settings. eia923: Immutable pydantic model to validate eia923 settings."""
def default_load_all(cls, values):
"""If no datasets are specified defau... | stack_v2_sparse_classes_36k_train_012961 | 24,804 | permissive | [
{
"docstring": "If no datasets are specified default to all. Args: values (Dict[str, BaseModel]): dataset settings. Returns: values (Dict[str, BaseModel]): dataset settings.",
"name": "default_load_all",
"signature": "def default_load_all(cls, values)"
},
{
"docstring": "Make sure the dependenci... | 2 | stack_v2_sparse_classes_30k_train_016808 | Implement the Python class `EiaSettings` described below.
Class description:
An immutable pydantic model to validate EIA datasets settings. Args: eia860: Immutable pydantic model to validate eia860 settings. eia923: Immutable pydantic model to validate eia923 settings.
Method signatures and docstrings:
- def default_... | Implement the Python class `EiaSettings` described below.
Class description:
An immutable pydantic model to validate EIA datasets settings. Args: eia860: Immutable pydantic model to validate eia860 settings. eia923: Immutable pydantic model to validate eia923 settings.
Method signatures and docstrings:
- def default_... | 6afae8aade053408f23ac4332d5cbb438ab72dc6 | <|skeleton|>
class EiaSettings:
"""An immutable pydantic model to validate EIA datasets settings. Args: eia860: Immutable pydantic model to validate eia860 settings. eia923: Immutable pydantic model to validate eia923 settings."""
def default_load_all(cls, values):
"""If no datasets are specified defau... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EiaSettings:
"""An immutable pydantic model to validate EIA datasets settings. Args: eia860: Immutable pydantic model to validate eia860 settings. eia923: Immutable pydantic model to validate eia923 settings."""
def default_load_all(cls, values):
"""If no datasets are specified default to all. Ar... | the_stack_v2_python_sparse | src/pudl/settings.py | catalyst-cooperative/pudl | train | 382 |
de929544ed0a313e8ec5677b900bf543f2addd8a | [
"elem = self.root.find(\"./data[@category='%s']/%s\" % (category, setting))\nif elem is not None:\n text = elem.text\n if text is not None:\n if type == 'str':\n return text\n elif type == 'int':\n return int(text)\n elif type == 'float':\n return float(te... | <|body_start_0|>
elem = self.root.find("./data[@category='%s']/%s" % (category, setting))
if elem is not None:
text = elem.text
if text is not None:
if type == 'str':
return text
elif type == 'int':
return in... | Manipulates XML database to store job settings. Inherits XMLData class. | Metadata | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Metadata:
"""Manipulates XML database to store job settings. Inherits XMLData class."""
def get_attr(self, category, setting, type='str'):
"""Get the specified value. 'type' can be specified in order to return a value of a given type, valid values are 'str', 'int', 'float', 'bool'.""... | stack_v2_sparse_classes_36k_train_012962 | 3,485 | permissive | [
{
"docstring": "Get the specified value. 'type' can be specified in order to return a value of a given type, valid values are 'str', 'int', 'float', 'bool'.",
"name": "get_attr",
"signature": "def get_attr(self, category, setting, type='str')"
},
{
"docstring": "Set value. Create elements if the... | 4 | stack_v2_sparse_classes_30k_train_016260 | Implement the Python class `Metadata` described below.
Class description:
Manipulates XML database to store job settings. Inherits XMLData class.
Method signatures and docstrings:
- def get_attr(self, category, setting, type='str'): Get the specified value. 'type' can be specified in order to return a value of a give... | Implement the Python class `Metadata` described below.
Class description:
Manipulates XML database to store job settings. Inherits XMLData class.
Method signatures and docstrings:
- def get_attr(self, category, setting, type='str'): Get the specified value. 'type' can be specified in order to return a value of a give... | a05abc916f0b6a9ee2c00e9f9b3dec12c09e6abe | <|skeleton|>
class Metadata:
"""Manipulates XML database to store job settings. Inherits XMLData class."""
def get_attr(self, category, setting, type='str'):
"""Get the specified value. 'type' can be specified in order to return a value of a given type, valid values are 'str', 'int', 'float', 'bool'.""... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Metadata:
"""Manipulates XML database to store job settings. Inherits XMLData class."""
def get_attr(self, category, setting, type='str'):
"""Get the specified value. 'type' can be specified in order to return a value of a given type, valid values are 'str', 'int', 'float', 'bool'."""
ele... | the_stack_v2_python_sparse | shared/xml_metadata.py | mjbonnington/icarus-gps | train | 0 |
a9188772bdeaf566e1306eed78f49340149fae17 | [
"self._server = server\nself._port = port\nself._timeout = timeout\nself._sender = sender\nself.encryption = encryption\nself.username = username\nself.password = password\nself.recipients = recipients\nself._sender_name = sender_name\nself.debug = debug\nself._verify_ssl = verify_ssl\nself.tries = 2",
"ssl_conte... | <|body_start_0|>
self._server = server
self._port = port
self._timeout = timeout
self._sender = sender
self.encryption = encryption
self.username = username
self.password = password
self.recipients = recipients
self._sender_name = sender_name
... | Implement the notification service for E-mail messages. | MailNotificationService | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class MailNotificationService:
"""Implement the notification service for E-mail messages."""
def __init__(self, server, port, timeout, sender, encryption, username, password, recipients, sender_name, debug, verify_ssl):
"""Initialize the SMTP service."""
<|body_0|>
def connect... | stack_v2_sparse_classes_36k_train_012963 | 9,634 | permissive | [
{
"docstring": "Initialize the SMTP service.",
"name": "__init__",
"signature": "def __init__(self, server, port, timeout, sender, encryption, username, password, recipients, sender_name, debug, verify_ssl)"
},
{
"docstring": "Connect/authenticate to SMTP Server.",
"name": "connect",
"si... | 5 | null | Implement the Python class `MailNotificationService` described below.
Class description:
Implement the notification service for E-mail messages.
Method signatures and docstrings:
- def __init__(self, server, port, timeout, sender, encryption, username, password, recipients, sender_name, debug, verify_ssl): Initialize... | Implement the Python class `MailNotificationService` described below.
Class description:
Implement the notification service for E-mail messages.
Method signatures and docstrings:
- def __init__(self, server, port, timeout, sender, encryption, username, password, recipients, sender_name, debug, verify_ssl): Initialize... | 80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743 | <|skeleton|>
class MailNotificationService:
"""Implement the notification service for E-mail messages."""
def __init__(self, server, port, timeout, sender, encryption, username, password, recipients, sender_name, debug, verify_ssl):
"""Initialize the SMTP service."""
<|body_0|>
def connect... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class MailNotificationService:
"""Implement the notification service for E-mail messages."""
def __init__(self, server, port, timeout, sender, encryption, username, password, recipients, sender_name, debug, verify_ssl):
"""Initialize the SMTP service."""
self._server = server
self._port... | the_stack_v2_python_sparse | homeassistant/components/smtp/notify.py | home-assistant/core | train | 35,501 |
471d2f791f86f996fa061967d95ecb388b1d6f8f | [
"self.algorithm = algorithm\nself._input_length = input_length\nself.hash_algorithm = hash_algorithm",
"if self._input_length is None:\n return encryption.data_key_length\nreturn self._input_length"
] | <|body_start_0|>
self.algorithm = algorithm
self._input_length = input_length
self.hash_algorithm = hash_algorithm
<|end_body_0|>
<|body_start_1|>
if self._input_length is None:
return encryption.data_key_length
return self._input_length
<|end_body_1|>
| Static definition of key derivation algorithm details. .. warning:: These members must only be used as part of an AlgorithmSuite. :param algorithm: KDF algorithm to use :type algorithm: cryptography.io KDF object :param int input_length: Number of bytes of input data to feed into KDF function :param hash_algorithm: Has... | KDFSuite | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class KDFSuite:
"""Static definition of key derivation algorithm details. .. warning:: These members must only be used as part of an AlgorithmSuite. :param algorithm: KDF algorithm to use :type algorithm: cryptography.io KDF object :param int input_length: Number of bytes of input data to feed into KDF... | stack_v2_sparse_classes_36k_train_012964 | 14,661 | permissive | [
{
"docstring": "Prepare a new KDFSuite.",
"name": "__init__",
"signature": "def __init__(self, algorithm, input_length, hash_algorithm)"
},
{
"docstring": "Determine the correct KDF input value length for this KDFSuite when used with a specific EncryptionSuite. :param encryption: EncryptionSuite... | 2 | stack_v2_sparse_classes_30k_train_015803 | Implement the Python class `KDFSuite` described below.
Class description:
Static definition of key derivation algorithm details. .. warning:: These members must only be used as part of an AlgorithmSuite. :param algorithm: KDF algorithm to use :type algorithm: cryptography.io KDF object :param int input_length: Number ... | Implement the Python class `KDFSuite` described below.
Class description:
Static definition of key derivation algorithm details. .. warning:: These members must only be used as part of an AlgorithmSuite. :param algorithm: KDF algorithm to use :type algorithm: cryptography.io KDF object :param int input_length: Number ... | 3ba8019681ed95c41bb9448f0c3897d1aecc7559 | <|skeleton|>
class KDFSuite:
"""Static definition of key derivation algorithm details. .. warning:: These members must only be used as part of an AlgorithmSuite. :param algorithm: KDF algorithm to use :type algorithm: cryptography.io KDF object :param int input_length: Number of bytes of input data to feed into KDF... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class KDFSuite:
"""Static definition of key derivation algorithm details. .. warning:: These members must only be used as part of an AlgorithmSuite. :param algorithm: KDF algorithm to use :type algorithm: cryptography.io KDF object :param int input_length: Number of bytes of input data to feed into KDF function :pa... | the_stack_v2_python_sparse | src/aws_encryption_sdk/identifiers.py | aws/aws-encryption-sdk-python | train | 137 |
ccf07ef6681043d2cfc58b36c44047761c2ec5bc | [
"if rowIndex == 0:\n return [1]\nresults = [1, 1]\ni = 2\nwhile i <= rowIndex:\n results.append(results[0])\n for j in range(1, len(results) - 1):\n results[j], results[-1] = (results[-1] + results[j], results[j])\n i += 1\nreturn results",
"results = [0 for i in range(rowIndex + 1)]\nresults[0... | <|body_start_0|>
if rowIndex == 0:
return [1]
results = [1, 1]
i = 2
while i <= rowIndex:
results.append(results[0])
for j in range(1, len(results) - 1):
results[j], results[-1] = (results[-1] + results[j], results[j])
i += ... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def getRow(self, rowIndex):
""":type rowIndex: int :rtype: List[int]"""
<|body_0|>
def getRow1(self, rowIndex):
""":type rowIndex: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
if rowIndex == 0:
return [... | stack_v2_sparse_classes_36k_train_012965 | 1,237 | no_license | [
{
"docstring": ":type rowIndex: int :rtype: List[int]",
"name": "getRow",
"signature": "def getRow(self, rowIndex)"
},
{
"docstring": ":type rowIndex: int :rtype: List[int]",
"name": "getRow1",
"signature": "def getRow1(self, rowIndex)"
}
] | 2 | stack_v2_sparse_classes_30k_train_012349 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getRow(self, rowIndex): :type rowIndex: int :rtype: List[int]
- def getRow1(self, rowIndex): :type rowIndex: int :rtype: List[int] | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def getRow(self, rowIndex): :type rowIndex: int :rtype: List[int]
- def getRow1(self, rowIndex): :type rowIndex: int :rtype: List[int]
<|skeleton|>
class Solution:
def getR... | eedf73b5f167025a97f0905d3718b6eab2ee3e09 | <|skeleton|>
class Solution:
def getRow(self, rowIndex):
""":type rowIndex: int :rtype: List[int]"""
<|body_0|>
def getRow1(self, rowIndex):
""":type rowIndex: int :rtype: List[int]"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def getRow(self, rowIndex):
""":type rowIndex: int :rtype: List[int]"""
if rowIndex == 0:
return [1]
results = [1, 1]
i = 2
while i <= rowIndex:
results.append(results[0])
for j in range(1, len(results) - 1):
... | the_stack_v2_python_sparse | Array/119_Pascal's_Triangle_II.py | xiaomojie/LeetCode | train | 0 | |
690d8df99963f2c2fb15488e5f0c9ed73244cbd1 | [
"prev_control_input = self.system.control_input\ncloud_node = self.system.cloud_node\nselected_nodes = None\nsolution = None\nif prev_control_input is None:\n solution, selected_nodes = MOGAOperator._decode_part_1(self, individual)\nelse:\n solution = OptSolution.create_empty(self.system)\n selected_nodes ... | <|body_start_0|>
prev_control_input = self.system.control_input
cloud_node = self.system.cloud_node
selected_nodes = None
solution = None
if prev_control_input is None:
solution, selected_nodes = MOGAOperator._decode_part_1(self, individual)
else:
... | No Migration GA Operator | NoMigrationGAOperator | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NoMigrationGAOperator:
"""No Migration GA Operator"""
def _decode_part_1(self, individual):
"""Decode Part I. It selects candidate nodes to host applications Args: individual (GAIndividual): individual Returns: (OptSolution, dict): solution, list of selected nodes per application"""
... | stack_v2_sparse_classes_36k_train_012966 | 5,124 | no_license | [
{
"docstring": "Decode Part I. It selects candidate nodes to host applications Args: individual (GAIndividual): individual Returns: (OptSolution, dict): solution, list of selected nodes per application",
"name": "_decode_part_1",
"signature": "def _decode_part_1(self, individual)"
},
{
"docstrin... | 3 | stack_v2_sparse_classes_30k_val_000754 | Implement the Python class `NoMigrationGAOperator` described below.
Class description:
No Migration GA Operator
Method signatures and docstrings:
- def _decode_part_1(self, individual): Decode Part I. It selects candidate nodes to host applications Args: individual (GAIndividual): individual Returns: (OptSolution, di... | Implement the Python class `NoMigrationGAOperator` described below.
Class description:
No Migration GA Operator
Method signatures and docstrings:
- def _decode_part_1(self, individual): Decode Part I. It selects candidate nodes to host applications Args: individual (GAIndividual): individual Returns: (OptSolution, di... | ce7045918f60c92ce1ed5ca4389b969bf28e6b82 | <|skeleton|>
class NoMigrationGAOperator:
"""No Migration GA Operator"""
def _decode_part_1(self, individual):
"""Decode Part I. It selects candidate nodes to host applications Args: individual (GAIndividual): individual Returns: (OptSolution, dict): solution, list of selected nodes per application"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NoMigrationGAOperator:
"""No Migration GA Operator"""
def _decode_part_1(self, individual):
"""Decode Part I. It selects candidate nodes to host applications Args: individual (GAIndividual): individual Returns: (OptSolution, dict): solution, list of selected nodes per application"""
prev_... | the_stack_v2_python_sparse | sp/system_controller/optimizer/no_migration.py | adysonmaia/phd-sp-dynamic | train | 0 |
7a567786be016aa8e52f9996d18bbae469960405 | [
"import pandas as pd\nraw_data = pd.read_excel(filename_1, sheet_name)\nself.df1 = raw_data[raw_data[' Whether or not metasomatism'] == 1].drop(['Whether or not metasomatism', 'CITATION'], axis=1)\nself.df2 = raw_data[raw_data['Whether or not metasomatism'] == -1].drop(['Whether or not metasomatism', 'CITATION'], a... | <|body_start_0|>
import pandas as pd
raw_data = pd.read_excel(filename_1, sheet_name)
self.df1 = raw_data[raw_data[' Whether or not metasomatism'] == 1].drop(['Whether or not metasomatism', 'CITATION'], axis=1)
self.df2 = raw_data[raw_data['Whether or not metasomatism'] == -1].drop(['Whe... | ElementsInCurve | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ElementsInCurve:
def __init__(self, filename_1, filename_2, sheet_name):
"""Input the file containing the elements data :param filename_1: Trace elements total 700 + data :param filename_2: trace Standardized values (ppm) :param sheet_name: 0 = Rare earth elements; 1 = Trace multi elemen... | stack_v2_sparse_classes_36k_train_012967 | 3,811 | permissive | [
{
"docstring": "Input the file containing the elements data :param filename_1: Trace elements total 700 + data :param filename_2: trace Standardized values (ppm) :param sheet_name: 0 = Rare earth elements; 1 = Trace multi element",
"name": "__init__",
"signature": "def __init__(self, filename_1, filenam... | 2 | stack_v2_sparse_classes_30k_train_016488 | Implement the Python class `ElementsInCurve` described below.
Class description:
Implement the ElementsInCurve class.
Method signatures and docstrings:
- def __init__(self, filename_1, filename_2, sheet_name): Input the file containing the elements data :param filename_1: Trace elements total 700 + data :param filena... | Implement the Python class `ElementsInCurve` described below.
Class description:
Implement the ElementsInCurve class.
Method signatures and docstrings:
- def __init__(self, filename_1, filename_2, sheet_name): Input the file containing the elements data :param filename_1: Trace elements total 700 + data :param filena... | ca0f220598ee156028646fbefccde08b2ece62ea | <|skeleton|>
class ElementsInCurve:
def __init__(self, filename_1, filename_2, sheet_name):
"""Input the file containing the elements data :param filename_1: Trace elements total 700 + data :param filename_2: trace Standardized values (ppm) :param sheet_name: 0 = Rare earth elements; 1 = Trace multi elemen... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ElementsInCurve:
def __init__(self, filename_1, filename_2, sheet_name):
"""Input the file containing the elements data :param filename_1: Trace elements total 700 + data :param filename_2: trace Standardized values (ppm) :param sheet_name: 0 = Rare earth elements; 1 = Trace multi element"""
i... | the_stack_v2_python_sparse | english/others/Elements_in_Curve.py | Lyuyangdaisy/DS_package | train | 0 | |
d6afcc23d03e1975bdc65ebe37b80153f54ddd14 | [
"res = super(stock_move, self)._create_chained_picking(cr, uid, pick_name, picking, purchase_type, move, context=context)\nif picking.purchase_id:\n self.pool.get('stock.picking').write(cr, uid, [res], {'purchase_id': picking.purchase_id.id})\n self.pool.get('stock.picking').write(cr, uid, [res], {'invoice_st... | <|body_start_0|>
res = super(stock_move, self)._create_chained_picking(cr, uid, pick_name, picking, purchase_type, move, context=context)
if picking.purchase_id:
self.pool.get('stock.picking').write(cr, uid, [res], {'purchase_id': picking.purchase_id.id})
self.pool.get('stock.pic... | TO remove pricelist | stock_move | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class stock_move:
"""TO remove pricelist"""
def _create_chained_picking(self, cr, uid, pick_name, picking, purchase_type, move, context=None):
"""This method creates chained picking and fix the problem of adding accounts for picking. @param pick_name: The name from the picking which is cre... | stack_v2_sparse_classes_36k_train_012968 | 5,611 | no_license | [
{
"docstring": "This method creates chained picking and fix the problem of adding accounts for picking. @param pick_name: The name from the picking which is created @param picking: The id of the picking which is created @param purchase_type: Purchase type @param move: The move id @return: id of creating picking... | 2 | stack_v2_sparse_classes_30k_test_001189 | Implement the Python class `stock_move` described below.
Class description:
TO remove pricelist
Method signatures and docstrings:
- def _create_chained_picking(self, cr, uid, pick_name, picking, purchase_type, move, context=None): This method creates chained picking and fix the problem of adding accounts for picking.... | Implement the Python class `stock_move` described below.
Class description:
TO remove pricelist
Method signatures and docstrings:
- def _create_chained_picking(self, cr, uid, pick_name, picking, purchase_type, move, context=None): This method creates chained picking and fix the problem of adding accounts for picking.... | 0b997095c260d58b026440967fea3a202bef7efb | <|skeleton|>
class stock_move:
"""TO remove pricelist"""
def _create_chained_picking(self, cr, uid, pick_name, picking, purchase_type, move, context=None):
"""This method creates chained picking and fix the problem of adding accounts for picking. @param pick_name: The name from the picking which is cre... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class stock_move:
"""TO remove pricelist"""
def _create_chained_picking(self, cr, uid, pick_name, picking, purchase_type, move, context=None):
"""This method creates chained picking and fix the problem of adding accounts for picking. @param pick_name: The name from the picking which is created @param p... | the_stack_v2_python_sparse | v_7/GDS/shamil_v3/purchase_no_pricelist/stock.py | musabahmed/baba | train | 0 |
efaf94f3c6b79f9294ae7f7e7a070a7902cf9c12 | [
"@wraps(self)\ndef decorated(*args, **kwargs):\n token = None\n if 'token' in request.headers:\n token = request.headers['token']\n if not token:\n return (jsonify({'message': 'Token is missing!'}), 401)\n try:\n data = jwt.decode(token, app.config['SECRET_KEY'])\n User.query... | <|body_start_0|>
@wraps(self)
def decorated(*args, **kwargs):
token = None
if 'token' in request.headers:
token = request.headers['token']
if not token:
return (jsonify({'message': 'Token is missing!'}), 401)
try:
... | Search_note | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Search_note:
def token_required(self):
"""Decorator meant to check if the token exists or not If the token exists check if it is valid"""
<|body_0|>
def get_user_by_token(self):
""":param token: has to be a jwt token :return: the user based on the public_id supplied ... | stack_v2_sparse_classes_36k_train_012969 | 8,581 | permissive | [
{
"docstring": "Decorator meant to check if the token exists or not If the token exists check if it is valid",
"name": "token_required",
"signature": "def token_required(self)"
},
{
"docstring": ":param token: has to be a jwt token :return: the user based on the public_id supplied by the token",... | 3 | stack_v2_sparse_classes_30k_train_018154 | Implement the Python class `Search_note` described below.
Class description:
Implement the Search_note class.
Method signatures and docstrings:
- def token_required(self): Decorator meant to check if the token exists or not If the token exists check if it is valid
- def get_user_by_token(self): :param token: has to b... | Implement the Python class `Search_note` described below.
Class description:
Implement the Search_note class.
Method signatures and docstrings:
- def token_required(self): Decorator meant to check if the token exists or not If the token exists check if it is valid
- def get_user_by_token(self): :param token: has to b... | db351b2053be5e9568d731006fd2af7002a40ca0 | <|skeleton|>
class Search_note:
def token_required(self):
"""Decorator meant to check if the token exists or not If the token exists check if it is valid"""
<|body_0|>
def get_user_by_token(self):
""":param token: has to be a jwt token :return: the user based on the public_id supplied ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Search_note:
def token_required(self):
"""Decorator meant to check if the token exists or not If the token exists check if it is valid"""
@wraps(self)
def decorated(*args, **kwargs):
token = None
if 'token' in request.headers:
token = request.hea... | the_stack_v2_python_sparse | server2/api/endpoints/stand_alone_views.py | Terkea/beds-uni-hackathon-4-notes | train | 0 | |
3113ed14b9c409e7465a6ae34adf6e61968ac811 | [
"self.eps0_inv_diag = None\nself.eps_inv_diag = None\nself.eps0_file = None\nself.eps_file = None",
"tmp = DielectricMatrix()\ntmp.read_from_hdf5_db(eps0, eps, mode)\nreturn tmp",
"from netCDF4 import Dataset\nf = Dataset(fname, 'r')\ndata = f.variables['matrix-diagonal'][:, :, :]\nf.close()\nif data.shape[2] =... | <|body_start_0|>
self.eps0_inv_diag = None
self.eps_inv_diag = None
self.eps0_file = None
self.eps_file = None
<|end_body_0|>
<|body_start_1|>
tmp = DielectricMatrix()
tmp.read_from_hdf5_db(eps0, eps, mode)
return tmp
<|end_body_1|>
<|body_start_2|>
from... | Dielectric matrix epsilon_GG'(q,omega) Provides interface to data stored in eps0mat.h5 and epsmat.h5 | DielectricMatrix | [
"LGPL-2.1-or-later",
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class DielectricMatrix:
"""Dielectric matrix epsilon_GG'(q,omega) Provides interface to data stored in eps0mat.h5 and epsmat.h5"""
def __init__(self):
"""Set up dielectric matrix ."""
<|body_0|>
def from_hdf5_db(cls, eps0=None, eps=None, mode='diagonal'):
"""Load diele... | stack_v2_sparse_classes_36k_train_012970 | 11,705 | permissive | [
{
"docstring": "Set up dielectric matrix .",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Load dielectric matrix from eps0mat.h5 file These files are written by epsilon.x",
"name": "from_hdf5_db",
"signature": "def from_hdf5_db(cls, eps0=None, eps=None, mode='... | 5 | null | Implement the Python class `DielectricMatrix` described below.
Class description:
Dielectric matrix epsilon_GG'(q,omega) Provides interface to data stored in eps0mat.h5 and epsmat.h5
Method signatures and docstrings:
- def __init__(self): Set up dielectric matrix .
- def from_hdf5_db(cls, eps0=None, eps=None, mode='d... | Implement the Python class `DielectricMatrix` described below.
Class description:
Dielectric matrix epsilon_GG'(q,omega) Provides interface to data stored in eps0mat.h5 and epsmat.h5
Method signatures and docstrings:
- def __init__(self): Set up dielectric matrix .
- def from_hdf5_db(cls, eps0=None, eps=None, mode='d... | bdb31934a5eb49d601e492fc98078d27f5dd2ebd | <|skeleton|>
class DielectricMatrix:
"""Dielectric matrix epsilon_GG'(q,omega) Provides interface to data stored in eps0mat.h5 and epsmat.h5"""
def __init__(self):
"""Set up dielectric matrix ."""
<|body_0|>
def from_hdf5_db(cls, eps0=None, eps=None, mode='diagonal'):
"""Load diele... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class DielectricMatrix:
"""Dielectric matrix epsilon_GG'(q,omega) Provides interface to data stored in eps0mat.h5 and epsmat.h5"""
def __init__(self):
"""Set up dielectric matrix ."""
self.eps0_inv_diag = None
self.eps_inv_diag = None
self.eps0_file = None
self.eps_file ... | the_stack_v2_python_sparse | asetk/format/bgw.py | ltalirz/asetk | train | 20 |
aaef45a115598a156e2f341e07867bcefa8d3cea | [
"conn = SFTPOnlyClient.from_ssh_client(gateway.ssh_connect())\nif gateway.timeout:\n conn.get_channel().settimeout(gateway.timeout)\nreturn closing(conn)",
"Attachment = self.env['ir.attachment']\ninputs = Attachment.browse()\nattachment_data = []\nmin_date = datetime.now() - timedelta(hours=path.age_window)\n... | <|body_start_0|>
conn = SFTPOnlyClient.from_ssh_client(gateway.ssh_connect())
if gateway.timeout:
conn.get_channel().settimeout(gateway.timeout)
return closing(conn)
<|end_body_0|>
<|body_start_1|>
Attachment = self.env['ir.attachment']
inputs = Attachment.browse()
... | EDI SFTP connection An EDI SFTP connection is a remote SFTP server used to send and receive EDI documents. | EdiConnectionSFTP | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class EdiConnectionSFTP:
"""EDI SFTP connection An EDI SFTP connection is a remote SFTP server used to send and receive EDI documents."""
def connect(self, gateway):
"""Connect to SFTP server"""
<|body_0|>
def receive_inputs(self, conn, path, transfer):
"""Receive inpu... | stack_v2_sparse_classes_36k_train_012971 | 6,375 | no_license | [
{
"docstring": "Connect to SFTP server",
"name": "connect",
"signature": "def connect(self, gateway)"
},
{
"docstring": "Receive input attachments",
"name": "receive_inputs",
"signature": "def receive_inputs(self, conn, path, transfer)"
},
{
"docstring": "Send output attachments"... | 3 | stack_v2_sparse_classes_30k_train_012768 | Implement the Python class `EdiConnectionSFTP` described below.
Class description:
EDI SFTP connection An EDI SFTP connection is a remote SFTP server used to send and receive EDI documents.
Method signatures and docstrings:
- def connect(self, gateway): Connect to SFTP server
- def receive_inputs(self, conn, path, tr... | Implement the Python class `EdiConnectionSFTP` described below.
Class description:
EDI SFTP connection An EDI SFTP connection is a remote SFTP server used to send and receive EDI documents.
Method signatures and docstrings:
- def connect(self, gateway): Connect to SFTP server
- def receive_inputs(self, conn, path, tr... | d6d55fbf8abecb0b8201384921833868ae849920 | <|skeleton|>
class EdiConnectionSFTP:
"""EDI SFTP connection An EDI SFTP connection is a remote SFTP server used to send and receive EDI documents."""
def connect(self, gateway):
"""Connect to SFTP server"""
<|body_0|>
def receive_inputs(self, conn, path, transfer):
"""Receive inpu... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class EdiConnectionSFTP:
"""EDI SFTP connection An EDI SFTP connection is a remote SFTP server used to send and receive EDI documents."""
def connect(self, gateway):
"""Connect to SFTP server"""
conn = SFTPOnlyClient.from_ssh_client(gateway.ssh_connect())
if gateway.timeout:
... | the_stack_v2_python_sparse | addons/edi/models/edi_connection_sftp.py | unipartdigital/odoo-edi | train | 9 |
c927c73f329f7c4f7f12be770ff908959f3ee8ce | [
"if not self.early_payment_discount:\n self.early_payment_disc_total = self.amount_total\n self.early_payment_disc_tax = self.amount_tax\n self.early_payment_disc_untaxed = self.amount_untaxed\nelse:\n cur = self.pricelist_id.currency_id\n val = val1 = 0\n for line in self.order_line:\n if ... | <|body_start_0|>
if not self.early_payment_discount:
self.early_payment_disc_total = self.amount_total
self.early_payment_disc_tax = self.amount_tax
self.early_payment_disc_untaxed = self.amount_untaxed
else:
cur = self.pricelist_id.currency_id
... | Inherit sale_order to add early payment discount | sale_order | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class sale_order:
"""Inherit sale_order to add early payment discount"""
def _amount_all2(self):
"""calculates functions amount fields"""
<|body_0|>
def onchange_partner_id2(self, cr, uid, ids, part, early_payment_discount=False, payment_term=False, context=None):
"""e... | stack_v2_sparse_classes_36k_train_012972 | 7,334 | no_license | [
{
"docstring": "calculates functions amount fields",
"name": "_amount_all2",
"signature": "def _amount_all2(self)"
},
{
"docstring": "extend this event for delete early payment discount if it isn't valid to new partner or add new early payment discount",
"name": "onchange_partner_id2",
"... | 4 | null | Implement the Python class `sale_order` described below.
Class description:
Inherit sale_order to add early payment discount
Method signatures and docstrings:
- def _amount_all2(self): calculates functions amount fields
- def onchange_partner_id2(self, cr, uid, ids, part, early_payment_discount=False, payment_term=Fa... | Implement the Python class `sale_order` described below.
Class description:
Inherit sale_order to add early payment discount
Method signatures and docstrings:
- def _amount_all2(self): calculates functions amount fields
- def onchange_partner_id2(self, cr, uid, ids, part, early_payment_discount=False, payment_term=Fa... | 9718281e31b4a4f6395d8bed54adf02799df6221 | <|skeleton|>
class sale_order:
"""Inherit sale_order to add early payment discount"""
def _amount_all2(self):
"""calculates functions amount fields"""
<|body_0|>
def onchange_partner_id2(self, cr, uid, ids, part, early_payment_discount=False, payment_term=False, context=None):
"""e... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class sale_order:
"""Inherit sale_order to add early payment discount"""
def _amount_all2(self):
"""calculates functions amount fields"""
if not self.early_payment_discount:
self.early_payment_disc_total = self.amount_total
self.early_payment_disc_tax = self.amount_tax
... | the_stack_v2_python_sparse | sale_early_payment_discount/sale.py | Comunitea/external_modules | train | 4 |
3e97f3df502a08a310f38c2e66a9b2485b07fa82 | [
"self.org_number = org_number\nself.prokura = prokura\nself.signature = signature\nself.signatures = signatures\nself.additional_properties = additional_properties",
"if dictionary is None:\n return None\norg_number = dictionary.get('OrgNumber')\nprokura = dictionary.get('Prokura')\nsignature = dictionary.get(... | <|body_start_0|>
self.org_number = org_number
self.prokura = prokura
self.signature = signature
self.signatures = signatures
self.additional_properties = additional_properties
<|end_body_0|>
<|body_start_1|>
if dictionary is None:
return None
org_numb... | Implementation of the 'OrganizationRequest' model. TODO: type model description here. Attributes: org_number (string): TODO: type description here. prokura (bool): TODO: type description here. signature (bool): TODO: type description here. signatures (list of CheckSignature): TODO: type description here. | OrganizationRequest | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class OrganizationRequest:
"""Implementation of the 'OrganizationRequest' model. TODO: type model description here. Attributes: org_number (string): TODO: type description here. prokura (bool): TODO: type description here. signature (bool): TODO: type description here. signatures (list of CheckSignatur... | stack_v2_sparse_classes_36k_train_012973 | 2,864 | permissive | [
{
"docstring": "Constructor for the OrganizationRequest class",
"name": "__init__",
"signature": "def __init__(self, org_number=None, prokura=None, signature=None, signatures=None, additional_properties={})"
},
{
"docstring": "Creates an instance of this model from a dictionary Args: dictionary ... | 2 | stack_v2_sparse_classes_30k_train_013210 | Implement the Python class `OrganizationRequest` described below.
Class description:
Implementation of the 'OrganizationRequest' model. TODO: type model description here. Attributes: org_number (string): TODO: type description here. prokura (bool): TODO: type description here. signature (bool): TODO: type description ... | Implement the Python class `OrganizationRequest` described below.
Class description:
Implementation of the 'OrganizationRequest' model. TODO: type model description here. Attributes: org_number (string): TODO: type description here. prokura (bool): TODO: type description here. signature (bool): TODO: type description ... | fa3918a6c54ea0eedb9146578645b7eb1755b642 | <|skeleton|>
class OrganizationRequest:
"""Implementation of the 'OrganizationRequest' model. TODO: type model description here. Attributes: org_number (string): TODO: type description here. prokura (bool): TODO: type description here. signature (bool): TODO: type description here. signatures (list of CheckSignatur... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class OrganizationRequest:
"""Implementation of the 'OrganizationRequest' model. TODO: type model description here. Attributes: org_number (string): TODO: type description here. prokura (bool): TODO: type description here. signature (bool): TODO: type description here. signatures (list of CheckSignature): TODO: typ... | the_stack_v2_python_sparse | idfy_rest_client/models/organization_request.py | dealflowteam/Idfy | train | 0 |
4466336ade31863df97c6abec9e3c2a2f0a10fca | [
"pkgs_changed = []\nif not action.keys():\n log.debug('No gems specified')\n return pkgs_changed\nfor pkg in action:\n installed = False\n if not action[pkg]:\n installed = self._install_gem(pkg)\n elif isinstance(action[pkg], basestring):\n installed = self._install_gem(pkg, action[pkg... | <|body_start_0|>
pkgs_changed = []
if not action.keys():
log.debug('No gems specified')
return pkgs_changed
for pkg in action:
installed = False
if not action[pkg]:
installed = self._install_gem(pkg)
elif isinstance(acti... | Installs packages via rubygems | GemTool | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GemTool:
"""Installs packages via rubygems"""
def apply(self, action, auth_config=None):
"""Install a set of packages via rubygems, returning the packages actually installed or updated. Arguments: action -- a dict of package name to version; version can be empty, a single string or a... | stack_v2_sparse_classes_36k_train_012974 | 5,320 | no_license | [
{
"docstring": "Install a set of packages via rubygems, returning the packages actually installed or updated. Arguments: action -- a dict of package name to version; version can be empty, a single string or a list of strings Exceptions: ToolError -- on expected failures (such as a non-zero exit code)",
"nam... | 3 | null | Implement the Python class `GemTool` described below.
Class description:
Installs packages via rubygems
Method signatures and docstrings:
- def apply(self, action, auth_config=None): Install a set of packages via rubygems, returning the packages actually installed or updated. Arguments: action -- a dict of package na... | Implement the Python class `GemTool` described below.
Class description:
Installs packages via rubygems
Method signatures and docstrings:
- def apply(self, action, auth_config=None): Install a set of packages via rubygems, returning the packages actually installed or updated. Arguments: action -- a dict of package na... | a473d0d389612e53a2ad6fe8a18d984474c44623 | <|skeleton|>
class GemTool:
"""Installs packages via rubygems"""
def apply(self, action, auth_config=None):
"""Install a set of packages via rubygems, returning the packages actually installed or updated. Arguments: action -- a dict of package name to version; version can be empty, a single string or a... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GemTool:
"""Installs packages via rubygems"""
def apply(self, action, auth_config=None):
"""Install a set of packages via rubygems, returning the packages actually installed or updated. Arguments: action -- a dict of package name to version; version can be empty, a single string or a list of stri... | the_stack_v2_python_sparse | p/dist-packages/cfnbootstrap/lang_package_tools.py | joshg111/craigslist_kbb | train | 7 |
99a588fd1b3c8e7defae24d01c4ae7e08c5fb5c1 | [
"if not callable(trafo):\n raise ValueError('trafo is not callable, but of type {}'.format(type(trafo)))\nsuper(WithThresh, self).__init__()\nself.batch_wise: bool = batch_wise\n'Whether to assume a batch of masks is given (``True``) or a\\n single mask (``False``).'\nself.trafo: Callable[[torch.Tensor], ... | <|body_start_0|>
if not callable(trafo):
raise ValueError('trafo is not callable, but of type {}'.format(type(trafo)))
super(WithThresh, self).__init__()
self.batch_wise: bool = batch_wise
'Whether to assume a batch of masks is given (``True``) or a\n single mask (``Fa... | Wrap a batch transformation with binarizing (and unsqueezing) before and after. The transformation should accept a tensor holding a masks (respectively a batch of masks if :py:attr:`~hybrid_learning.datasets.transforms.image_transforms.WithThresh.batch_wise` is ``True``) and return a transformed batch. If given, ``pre_... | WithThresh | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class WithThresh:
"""Wrap a batch transformation with binarizing (and unsqueezing) before and after. The transformation should accept a tensor holding a masks (respectively a batch of masks if :py:attr:`~hybrid_learning.datasets.transforms.image_transforms.WithThresh.batch_wise` is ``True``) and return... | stack_v2_sparse_classes_36k_train_012975 | 14,707 | permissive | [
{
"docstring": "Init. :param trafo: the transformation instance to wrap :param pre_thresh: if not ``None``, the tensors to be modified are binarized to 0 and 1 values with threshold ``pre_thresh`` before modification :param post_thresh: if not ``None``, the tensors to be modified are binarized to 0 and 1 values... | 3 | stack_v2_sparse_classes_30k_train_015065 | Implement the Python class `WithThresh` described below.
Class description:
Wrap a batch transformation with binarizing (and unsqueezing) before and after. The transformation should accept a tensor holding a masks (respectively a batch of masks if :py:attr:`~hybrid_learning.datasets.transforms.image_transforms.WithThr... | Implement the Python class `WithThresh` described below.
Class description:
Wrap a batch transformation with binarizing (and unsqueezing) before and after. The transformation should accept a tensor holding a masks (respectively a batch of masks if :py:attr:`~hybrid_learning.datasets.transforms.image_transforms.WithThr... | 37b9fc83d7b14902dfe92e0c45071c150bcf3779 | <|skeleton|>
class WithThresh:
"""Wrap a batch transformation with binarizing (and unsqueezing) before and after. The transformation should accept a tensor holding a masks (respectively a batch of masks if :py:attr:`~hybrid_learning.datasets.transforms.image_transforms.WithThresh.batch_wise` is ``True``) and return... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class WithThresh:
"""Wrap a batch transformation with binarizing (and unsqueezing) before and after. The transformation should accept a tensor holding a masks (respectively a batch of masks if :py:attr:`~hybrid_learning.datasets.transforms.image_transforms.WithThresh.batch_wise` is ``True``) and return a transforme... | the_stack_v2_python_sparse | hybrid_learning/datasets/transforms/image_transforms.py | JohnnyZhang917/hybrid_learning | train | 0 |
48c919946ce879045c6ff2cda93ebb08923bb76c | [
"try:\n release = Release.objects.get(project=project, version=version)\nexcept Release.DoesNotExist:\n raise ResourceDoesNotExist\nfile_list = ReleaseFile.objects.filter(release=release).select_related('file').order_by('name')\nreturn self.paginate(request=request, queryset=file_list, order_by='name', pagina... | <|body_start_0|>
try:
release = Release.objects.get(project=project, version=version)
except Release.DoesNotExist:
raise ResourceDoesNotExist
file_list = ReleaseFile.objects.filter(release=release).select_related('file').order_by('name')
return self.paginate(reque... | ReleaseFilesEndpoint | [
"BSD-2-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ReleaseFilesEndpoint:
def get(self, request, project, version):
"""List a Release's Files `````````````````````` Retrieve a list of files for a given release. :pparam string organization_slug: the slug of the organization the release belongs to. :pparam string project_slug: the slug of t... | stack_v2_sparse_classes_36k_train_012976 | 6,460 | permissive | [
{
"docstring": "List a Release's Files `````````````````````` Retrieve a list of files for a given release. :pparam string organization_slug: the slug of the organization the release belongs to. :pparam string project_slug: the slug of the project to list the release files of. :pparam string version: the versio... | 2 | null | Implement the Python class `ReleaseFilesEndpoint` described below.
Class description:
Implement the ReleaseFilesEndpoint class.
Method signatures and docstrings:
- def get(self, request, project, version): List a Release's Files `````````````````````` Retrieve a list of files for a given release. :pparam string organ... | Implement the Python class `ReleaseFilesEndpoint` described below.
Class description:
Implement the ReleaseFilesEndpoint class.
Method signatures and docstrings:
- def get(self, request, project, version): List a Release's Files `````````````````````` Retrieve a list of files for a given release. :pparam string organ... | cddc3b643a13b52ac6d07ff22e4bd5d69ecbad90 | <|skeleton|>
class ReleaseFilesEndpoint:
def get(self, request, project, version):
"""List a Release's Files `````````````````````` Retrieve a list of files for a given release. :pparam string organization_slug: the slug of the organization the release belongs to. :pparam string project_slug: the slug of t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ReleaseFilesEndpoint:
def get(self, request, project, version):
"""List a Release's Files `````````````````````` Retrieve a list of files for a given release. :pparam string organization_slug: the slug of the organization the release belongs to. :pparam string project_slug: the slug of the project to ... | the_stack_v2_python_sparse | src/sentry/api/endpoints/release_files.py | mitsuhiko/sentry | train | 4 | |
420fabc4c13777bf3a4a7a4796063b42e8a8e741 | [
"self.num_elem = self.kwargs['num_elem']\nnum_pts = self.num_elem + 1\nind_pts = range(num_pts)\nself._declare_variable('rho', size=num_pts, lower=0.001)\nself._declare_argument('Temp', indices=ind_pts)",
"pvec = self.vec['p']\nuvec = self.vec['u']\ntemp = pvec('Temp') * 100.0\nrho = uvec('rho')\nrho[:] = 1.225 *... | <|body_start_0|>
self.num_elem = self.kwargs['num_elem']
num_pts = self.num_elem + 1
ind_pts = range(num_pts)
self._declare_variable('rho', size=num_pts, lower=0.001)
self._declare_argument('Temp', indices=ind_pts)
<|end_body_0|>
<|body_start_1|>
pvec = self.vec['p']
... | density model using the linear temperature std atm model | SysRhoOld | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SysRhoOld:
"""density model using the linear temperature std atm model"""
def _declare(self):
"""owned variable: rho (density) dependencies: temp (temperature)"""
<|body_0|>
def apply_G(self):
"""Density model extracted from the standard atmosphere. Only dependen... | stack_v2_sparse_classes_36k_train_012977 | 17,488 | no_license | [
{
"docstring": "owned variable: rho (density) dependencies: temp (temperature)",
"name": "_declare",
"signature": "def _declare(self)"
},
{
"docstring": "Density model extracted from the standard atmosphere. Only dependence on temperature, with indirect dependence on altitude. Temperature model ... | 3 | stack_v2_sparse_classes_30k_train_007122 | Implement the Python class `SysRhoOld` described below.
Class description:
density model using the linear temperature std atm model
Method signatures and docstrings:
- def _declare(self): owned variable: rho (density) dependencies: temp (temperature)
- def apply_G(self): Density model extracted from the standard atmo... | Implement the Python class `SysRhoOld` described below.
Class description:
density model using the linear temperature std atm model
Method signatures and docstrings:
- def _declare(self): owned variable: rho (density) dependencies: temp (temperature)
- def apply_G(self): Density model extracted from the standard atmo... | f5b1ce287c6692540b738a7e9ec85be645f4947a | <|skeleton|>
class SysRhoOld:
"""density model using the linear temperature std atm model"""
def _declare(self):
"""owned variable: rho (density) dependencies: temp (temperature)"""
<|body_0|>
def apply_G(self):
"""Density model extracted from the standard atmosphere. Only dependen... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SysRhoOld:
"""density model using the linear temperature std atm model"""
def _declare(self):
"""owned variable: rho (density) dependencies: temp (temperature)"""
self.num_elem = self.kwargs['num_elem']
num_pts = self.num_elem + 1
ind_pts = range(num_pts)
self._dec... | the_stack_v2_python_sparse | cmf_original_code/atmospherics.py | naylor-b/pyMission | train | 0 |
cd8554dcfd6144db0c9af331596613c981fac1e4 | [
"if not matrix:\n return False\nif not matrix[0]:\n return False\nfor i in range(len(matrix[0]) - 1, -1, -1):\n if matrix[0][i] <= target:\n for j in range(len(matrix)):\n if matrix[j][i] >= target:\n small_matrix = matrix[j:][:i + 1]\n for x in small_matrix:... | <|body_start_0|>
if not matrix:
return False
if not matrix[0]:
return False
for i in range(len(matrix[0]) - 1, -1, -1):
if matrix[0][i] <= target:
for j in range(len(matrix)):
if matrix[j][i] >= target:
... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def searchMatrix1(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
<|body_0|>
def searchMatrix2(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
<|body_1|>
<|end_skel... | stack_v2_sparse_classes_36k_train_012978 | 1,598 | no_license | [
{
"docstring": ":type matrix: List[List[int]] :type target: int :rtype: bool",
"name": "searchMatrix1",
"signature": "def searchMatrix1(self, matrix, target)"
},
{
"docstring": ":type matrix: List[List[int]] :type target: int :rtype: bool",
"name": "searchMatrix2",
"signature": "def sear... | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchMatrix1(self, matrix, target): :type matrix: List[List[int]] :type target: int :rtype: bool
- def searchMatrix2(self, matrix, target): :type matrix: List[List[int]] :ty... | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def searchMatrix1(self, matrix, target): :type matrix: List[List[int]] :type target: int :rtype: bool
- def searchMatrix2(self, matrix, target): :type matrix: List[List[int]] :ty... | 8fb6c1d947046dabd58ff8482b2c0b41f39aa988 | <|skeleton|>
class Solution:
def searchMatrix1(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
<|body_0|>
def searchMatrix2(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
<|body_1|>
<|end_skel... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def searchMatrix1(self, matrix, target):
""":type matrix: List[List[int]] :type target: int :rtype: bool"""
if not matrix:
return False
if not matrix[0]:
return False
for i in range(len(matrix[0]) - 1, -1, -1):
if matrix[0][i] <= ta... | the_stack_v2_python_sparse | Python/LeetCode/74.py | czx94/Algorithms-Collection | train | 2 | |
a8a14cc306ad15a2bec7353415321668c425c07c | [
"self.event_str = event_str\nself.date = calendar_util.convert_str_to_date(date_str)\nself.start_time_str = start_time_str\nself.end_time_str = end_time_str",
"date_str = datetime.datetime.strftime(self.date, calendar_util.DATE_STR_FMT)\nret = ' '.join([self.event_str, 'on', date_str])\nif self.start_time_str:\n ... | <|body_start_0|>
self.event_str = event_str
self.date = calendar_util.convert_str_to_date(date_str)
self.start_time_str = start_time_str
self.end_time_str = end_time_str
<|end_body_0|>
<|body_start_1|>
date_str = datetime.datetime.strftime(self.date, calendar_util.DATE_STR_FMT)
... | Class for storing calendar event information. | CalendarEvent | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CalendarEvent:
"""Class for storing calendar event information."""
def __init__(self, event_str: str='', date_str: str='', start_time_str: str='', end_time_str: str=''):
"""Initialize this CalendarEvent instance."""
<|body_0|>
def __str__(self):
"""Returns the st... | stack_v2_sparse_classes_36k_train_012979 | 1,047 | permissive | [
{
"docstring": "Initialize this CalendarEvent instance.",
"name": "__init__",
"signature": "def __init__(self, event_str: str='', date_str: str='', start_time_str: str='', end_time_str: str='')"
},
{
"docstring": "Returns the string representation of this CalendarEvent.",
"name": "__str__",
... | 2 | stack_v2_sparse_classes_30k_train_010915 | Implement the Python class `CalendarEvent` described below.
Class description:
Class for storing calendar event information.
Method signatures and docstrings:
- def __init__(self, event_str: str='', date_str: str='', start_time_str: str='', end_time_str: str=''): Initialize this CalendarEvent instance.
- def __str__(... | Implement the Python class `CalendarEvent` described below.
Class description:
Class for storing calendar event information.
Method signatures and docstrings:
- def __init__(self, event_str: str='', date_str: str='', start_time_str: str='', end_time_str: str=''): Initialize this CalendarEvent instance.
- def __str__(... | 9fdf2f2b4861450fbed64b90b8c7c69b0173e052 | <|skeleton|>
class CalendarEvent:
"""Class for storing calendar event information."""
def __init__(self, event_str: str='', date_str: str='', start_time_str: str='', end_time_str: str=''):
"""Initialize this CalendarEvent instance."""
<|body_0|>
def __str__(self):
"""Returns the st... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CalendarEvent:
"""Class for storing calendar event information."""
def __init__(self, event_str: str='', date_str: str='', start_time_str: str='', end_time_str: str=''):
"""Initialize this CalendarEvent instance."""
self.event_str = event_str
self.date = calendar_util.convert_str_... | the_stack_v2_python_sparse | LTUAssistantPlus/services/calendar/calendar_event.py | Xyaneon/LTUAssistantPlus | train | 0 |
3e0fa2e54938d72afe0ee795890c28920402d6dc | [
"wx.Menu.__init__(self)\nself._callbacks = {}\nfor i in menu:\n menuid = wx.NewId()\n item = wx.MenuItem(self, menuid, i[0])\n self._callbacks[menuid] = i[1]\n self.Append(item)\n self.Bind(wx.EVT_MENU, self.on_callback, item)",
"menuid = event.GetId()\nself._callbacks[menuid](event)\nevent.Skip()"... | <|body_start_0|>
wx.Menu.__init__(self)
self._callbacks = {}
for i in menu:
menuid = wx.NewId()
item = wx.MenuItem(self, menuid, i[0])
self._callbacks[menuid] = i[1]
self.Append(item)
self.Bind(wx.EVT_MENU, self.on_callback, item)
<|end... | Context Menu. | ContextMenu | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ContextMenu:
"""Context Menu."""
def __init__(self, menu):
"""Attach the context menu to to the parent with the defined items."""
<|body_0|>
def on_callback(self, event):
"""Execute the menu item callback."""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>... | stack_v2_sparse_classes_36k_train_012980 | 9,581 | permissive | [
{
"docstring": "Attach the context menu to to the parent with the defined items.",
"name": "__init__",
"signature": "def __init__(self, menu)"
},
{
"docstring": "Execute the menu item callback.",
"name": "on_callback",
"signature": "def on_callback(self, event)"
}
] | 2 | stack_v2_sparse_classes_30k_train_013390 | Implement the Python class `ContextMenu` described below.
Class description:
Context Menu.
Method signatures and docstrings:
- def __init__(self, menu): Attach the context menu to to the parent with the defined items.
- def on_callback(self, event): Execute the menu item callback. | Implement the Python class `ContextMenu` described below.
Class description:
Context Menu.
Method signatures and docstrings:
- def __init__(self, menu): Attach the context menu to to the parent with the defined items.
- def on_callback(self, event): Execute the menu item callback.
<|skeleton|>
class ContextMenu:
... | 95129ca054384a4c59a4effdb3fe32a7a66af6ff | <|skeleton|>
class ContextMenu:
"""Context Menu."""
def __init__(self, menu):
"""Attach the context menu to to the parent with the defined items."""
<|body_0|>
def on_callback(self, event):
"""Execute the menu item callback."""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ContextMenu:
"""Context Menu."""
def __init__(self, menu):
"""Attach the context menu to to the parent with the defined items."""
wx.Menu.__init__(self)
self._callbacks = {}
for i in menu:
menuid = wx.NewId()
item = wx.MenuItem(self, menuid, i[0])
... | the_stack_v2_python_sparse | rummage/lib/gui/controls/custom_statusbar.py | facelessuser/Rummage | train | 70 |
4ac01e9db0266170690e0c450adeb2258ce5ce60 | [
"super(GeneratorNet, self).__init__()\nself.n_features = 100\nself.n_out = 784\nself.__model_fn()\nself.optimizer = optim.Adam(self.parameters(), lr=0.0002)",
"self.hidden0 = nn.Sequential(nn.Linear(self.n_features, 256), nn.LeakyReLU(0.2))\nself.hidden1 = nn.Sequential(nn.Linear(256, 512), nn.LeakyReLU(0.2))\nse... | <|body_start_0|>
super(GeneratorNet, self).__init__()
self.n_features = 100
self.n_out = 784
self.__model_fn()
self.optimizer = optim.Adam(self.parameters(), lr=0.0002)
<|end_body_0|>
<|body_start_1|>
self.hidden0 = nn.Sequential(nn.Linear(self.n_features, 256), nn.Leaky... | Class GeneratorNet. | GeneratorNet | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GeneratorNet:
"""Class GeneratorNet."""
def __init__(self):
"""Constructor."""
<|body_0|>
def __model_fn(self):
"""Specifies the network."""
<|body_1|>
def forward(self, X):
"""Performs a forward-pass on the data. :param X: network input"""
... | stack_v2_sparse_classes_36k_train_012981 | 11,950 | no_license | [
{
"docstring": "Constructor.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Specifies the network.",
"name": "__model_fn",
"signature": "def __model_fn(self)"
},
{
"docstring": "Performs a forward-pass on the data. :param X: network input",
"name":... | 3 | stack_v2_sparse_classes_30k_train_013518 | Implement the Python class `GeneratorNet` described below.
Class description:
Class GeneratorNet.
Method signatures and docstrings:
- def __init__(self): Constructor.
- def __model_fn(self): Specifies the network.
- def forward(self, X): Performs a forward-pass on the data. :param X: network input | Implement the Python class `GeneratorNet` described below.
Class description:
Class GeneratorNet.
Method signatures and docstrings:
- def __init__(self): Constructor.
- def __model_fn(self): Specifies the network.
- def forward(self, X): Performs a forward-pass on the data. :param X: network input
<|skeleton|>
class... | 98b71b76f664d5f6493bd7f90036531d8f6644a7 | <|skeleton|>
class GeneratorNet:
"""Class GeneratorNet."""
def __init__(self):
"""Constructor."""
<|body_0|>
def __model_fn(self):
"""Specifies the network."""
<|body_1|>
def forward(self, X):
"""Performs a forward-pass on the data. :param X: network input"""
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GeneratorNet:
"""Class GeneratorNet."""
def __init__(self):
"""Constructor."""
super(GeneratorNet, self).__init__()
self.n_features = 100
self.n_out = 784
self.__model_fn()
self.optimizer = optim.Adam(self.parameters(), lr=0.0002)
def __model_fn(self):... | the_stack_v2_python_sparse | 06_python/misc/gan.py | pfisterer/Applied_ML_Fundamentals | train | 0 |
66f4852fd4f4ffadd33f36f25760bfa23338c89c | [
"sketch = Sketch.query.get_with_acl(sketch_id)\nscenario = Scenario.query.get(scenario_id)\nif not sketch:\n abort(HTTP_STATUS_CODE_NOT_FOUND, 'No sketch found with this ID')\nif not sketch.has_permission(current_user, 'write'):\n abort(HTTP_STATUS_CODE_FORBIDDEN, 'User does not have write access controls on ... | <|body_start_0|>
sketch = Sketch.query.get_with_acl(sketch_id)
scenario = Scenario.query.get(scenario_id)
if not sketch:
abort(HTTP_STATUS_CODE_NOT_FOUND, 'No sketch found with this ID')
if not sketch.has_permission(current_user, 'write'):
abort(HTTP_STATUS_CODE_F... | Resource for investigative scenarios. | ScenarioResource | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ScenarioResource:
"""Resource for investigative scenarios."""
def get(self, sketch_id, scenario_id):
"""Handles GET request to the resource. Returns: A list of JSON representations of the scenarios."""
<|body_0|>
def post(self, sketch_id, scenario_id):
"""Handles... | stack_v2_sparse_classes_36k_train_012982 | 15,391 | permissive | [
{
"docstring": "Handles GET request to the resource. Returns: A list of JSON representations of the scenarios.",
"name": "get",
"signature": "def get(self, sketch_id, scenario_id)"
},
{
"docstring": "Handles POST request to the resource. This resource creates a new scenario for a sketch based on... | 2 | stack_v2_sparse_classes_30k_train_014919 | Implement the Python class `ScenarioResource` described below.
Class description:
Resource for investigative scenarios.
Method signatures and docstrings:
- def get(self, sketch_id, scenario_id): Handles GET request to the resource. Returns: A list of JSON representations of the scenarios.
- def post(self, sketch_id, ... | Implement the Python class `ScenarioResource` described below.
Class description:
Resource for investigative scenarios.
Method signatures and docstrings:
- def get(self, sketch_id, scenario_id): Handles GET request to the resource. Returns: A list of JSON representations of the scenarios.
- def post(self, sketch_id, ... | 24f471b58ca4a87cb053961b5f05c07a544ca7b8 | <|skeleton|>
class ScenarioResource:
"""Resource for investigative scenarios."""
def get(self, sketch_id, scenario_id):
"""Handles GET request to the resource. Returns: A list of JSON representations of the scenarios."""
<|body_0|>
def post(self, sketch_id, scenario_id):
"""Handles... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ScenarioResource:
"""Resource for investigative scenarios."""
def get(self, sketch_id, scenario_id):
"""Handles GET request to the resource. Returns: A list of JSON representations of the scenarios."""
sketch = Sketch.query.get_with_acl(sketch_id)
scenario = Scenario.query.get(sce... | the_stack_v2_python_sparse | timesketch/api/v1/resources/scenarios.py | google/timesketch | train | 2,263 |
e9c5f30f1bc8ea3b6321a8daf805d87181566bb1 | [
"graph = BELGraph()\nself.update(graph)\nreturn graph",
"if self.name:\n graph.name = self.name\nif self.version:\n graph.version = self.version\nif self.authors:\n graph.authors = self.authors\nif self.description:\n graph.description = self.description\nif self.contact:\n graph.contact = self.con... | <|body_start_0|>
graph = BELGraph()
self.update(graph)
return graph
<|end_body_0|>
<|body_start_1|>
if self.name:
graph.name = self.name
if self.version:
graph.version = self.version
if self.authors:
graph.authors = self.authors
... | A container for BEL document metadata. | BELMetadata | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class BELMetadata:
"""A container for BEL document metadata."""
def new(self) -> BELGraph:
"""Generate a new BEL graph with the given metadata."""
<|body_0|>
def update(self, graph: BELGraph) -> None:
"""Update the BEL graph's metadata."""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_36k_train_012983 | 18,905 | permissive | [
{
"docstring": "Generate a new BEL graph with the given metadata.",
"name": "new",
"signature": "def new(self) -> BELGraph"
},
{
"docstring": "Update the BEL graph's metadata.",
"name": "update",
"signature": "def update(self, graph: BELGraph) -> None"
}
] | 2 | null | Implement the Python class `BELMetadata` described below.
Class description:
A container for BEL document metadata.
Method signatures and docstrings:
- def new(self) -> BELGraph: Generate a new BEL graph with the given metadata.
- def update(self, graph: BELGraph) -> None: Update the BEL graph's metadata. | Implement the Python class `BELMetadata` described below.
Class description:
A container for BEL document metadata.
Method signatures and docstrings:
- def new(self) -> BELGraph: Generate a new BEL graph with the given metadata.
- def update(self, graph: BELGraph) -> None: Update the BEL graph's metadata.
<|skeleton... | ed66f013a77f9cbc513892b0dad1025b8f68bb46 | <|skeleton|>
class BELMetadata:
"""A container for BEL document metadata."""
def new(self) -> BELGraph:
"""Generate a new BEL graph with the given metadata."""
<|body_0|>
def update(self, graph: BELGraph) -> None:
"""Update the BEL graph's metadata."""
<|body_1|>
<|end_ske... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class BELMetadata:
"""A container for BEL document metadata."""
def new(self) -> BELGraph:
"""Generate a new BEL graph with the given metadata."""
graph = BELGraph()
self.update(graph)
return graph
def update(self, graph: BELGraph) -> None:
"""Update the BEL graph's... | the_stack_v2_python_sparse | src/pybel/repository.py | pybel/pybel | train | 133 |
66b0d04f9ff8ff6a25a73968d0081278f7593e60 | [
"if form_class is None:\n form_class = self.get_form_class()\nreturn form_class(token=self.request.session.get('token', False), aiid=self.kwargs['aiid'], **self.get_form_kwargs())",
"initial = super(SkillsView, self).get_initial()\nai = get_ai(self.request.session.get('token', False), self.kwargs['aiid'])\nini... | <|body_start_0|>
if form_class is None:
form_class = self.get_form_class()
return form_class(token=self.request.session.get('token', False), aiid=self.kwargs['aiid'], **self.get_form_kwargs())
<|end_body_0|>
<|body_start_1|>
initial = super(SkillsView, self).get_initial()
ai... | SkillsView | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class SkillsView:
def get_form(self, form_class=None):
"""Return an instance of the form to be used in this view."""
<|body_0|>
def get_initial(self):
"""Returns the initial data to use for forms on this view."""
<|body_1|>
def form_valid(self, form):
... | stack_v2_sparse_classes_36k_train_012984 | 39,842 | permissive | [
{
"docstring": "Return an instance of the form to be used in this view.",
"name": "get_form",
"signature": "def get_form(self, form_class=None)"
},
{
"docstring": "Returns the initial data to use for forms on this view.",
"name": "get_initial",
"signature": "def get_initial(self)"
},
... | 3 | stack_v2_sparse_classes_30k_train_014337 | Implement the Python class `SkillsView` described below.
Class description:
Implement the SkillsView class.
Method signatures and docstrings:
- def get_form(self, form_class=None): Return an instance of the form to be used in this view.
- def get_initial(self): Returns the initial data to use for forms on this view.
... | Implement the Python class `SkillsView` described below.
Class description:
Implement the SkillsView class.
Method signatures and docstrings:
- def get_form(self, form_class=None): Return an instance of the form to be used in this view.
- def get_initial(self): Returns the initial data to use for forms on this view.
... | d632d00f9a22a7a826bba4896a7102b2ac8690ff | <|skeleton|>
class SkillsView:
def get_form(self, form_class=None):
"""Return an instance of the form to be used in this view."""
<|body_0|>
def get_initial(self):
"""Returns the initial data to use for forms on this view."""
<|body_1|>
def form_valid(self, form):
... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class SkillsView:
def get_form(self, form_class=None):
"""Return an instance of the form to be used in this view."""
if form_class is None:
form_class = self.get_form_class()
return form_class(token=self.request.session.get('token', False), aiid=self.kwargs['aiid'], **self.get_fo... | the_stack_v2_python_sparse | src/studio/views.py | hutomadotAI/web-console | train | 6 | |
2f6587ebab7cdefe199aa9036e8992aa4c02047e | [
"if 'not' in data:\n new_data = {'not': True}\n for key, value in data.get('not').items():\n new_data[key] = value\n data = new_data\nif 'enum' in data:\n if not isinstance(data.get('enum'), list):\n raise ValidationError('enum is not specified as a list')\nreturn data",
"if data.pop('no... | <|body_start_0|>
if 'not' in data:
new_data = {'not': True}
for key, value in data.get('not').items():
new_data[key] = value
data = new_data
if 'enum' in data:
if not isinstance(data.get('enum'), list):
raise ValidationError... | Single Filter Schema. | FilterSchema | [
"LicenseRef-scancode-dco-1.1",
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class FilterSchema:
"""Single Filter Schema."""
def extract_info(self, data, **kwargs):
"""Enum validation and not filter logic."""
<|body_0|>
def serialize_reformat(self, data, **kwargs):
"""Support serialization of not filter according to DIF spec."""
<|body_... | stack_v2_sparse_classes_36k_train_012985 | 27,273 | permissive | [
{
"docstring": "Enum validation and not filter logic.",
"name": "extract_info",
"signature": "def extract_info(self, data, **kwargs)"
},
{
"docstring": "Support serialization of not filter according to DIF spec.",
"name": "serialize_reformat",
"signature": "def serialize_reformat(self, d... | 2 | null | Implement the Python class `FilterSchema` described below.
Class description:
Single Filter Schema.
Method signatures and docstrings:
- def extract_info(self, data, **kwargs): Enum validation and not filter logic.
- def serialize_reformat(self, data, **kwargs): Support serialization of not filter according to DIF spe... | Implement the Python class `FilterSchema` described below.
Class description:
Single Filter Schema.
Method signatures and docstrings:
- def extract_info(self, data, **kwargs): Enum validation and not filter logic.
- def serialize_reformat(self, data, **kwargs): Support serialization of not filter according to DIF spe... | 39cac36d8937ce84a9307ce100aaefb8bc05ec04 | <|skeleton|>
class FilterSchema:
"""Single Filter Schema."""
def extract_info(self, data, **kwargs):
"""Enum validation and not filter logic."""
<|body_0|>
def serialize_reformat(self, data, **kwargs):
"""Support serialization of not filter according to DIF spec."""
<|body_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class FilterSchema:
"""Single Filter Schema."""
def extract_info(self, data, **kwargs):
"""Enum validation and not filter logic."""
if 'not' in data:
new_data = {'not': True}
for key, value in data.get('not').items():
new_data[key] = value
dat... | the_stack_v2_python_sparse | aries_cloudagent/protocols/present_proof/dif/pres_exch.py | hyperledger/aries-cloudagent-python | train | 370 |
0ccd90e3cc0e4ba33dc54abaec43caa0ab161433 | [
"def f(txn: LoggingTransaction) -> None:\n txn.execute('SELECT 1 FROM erased_users WHERE user_id = ?', (user_id,))\n if txn.fetchone():\n return\n txn.execute('INSERT INTO erased_users (user_id) VALUES (?)', (user_id,))\n self._invalidate_cache_and_stream(txn, self.is_user_erased, (user_id,))\naw... | <|body_start_0|>
def f(txn: LoggingTransaction) -> None:
txn.execute('SELECT 1 FROM erased_users WHERE user_id = ?', (user_id,))
if txn.fetchone():
return
txn.execute('INSERT INTO erased_users (user_id) VALUES (?)', (user_id,))
self._invalidate_cac... | UserErasureStore | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class UserErasureStore:
async def mark_user_erased(self, user_id: str) -> None:
"""Indicate that user_id wishes their message history to be erased. Args: user_id: full user_id to be erased"""
<|body_0|>
async def mark_user_not_erased(self, user_id: str) -> None:
"""Indicat... | stack_v2_sparse_classes_36k_train_012986 | 3,689 | permissive | [
{
"docstring": "Indicate that user_id wishes their message history to be erased. Args: user_id: full user_id to be erased",
"name": "mark_user_erased",
"signature": "async def mark_user_erased(self, user_id: str) -> None"
},
{
"docstring": "Indicate that user_id is no longer erased. Args: user_i... | 2 | stack_v2_sparse_classes_30k_train_011104 | Implement the Python class `UserErasureStore` described below.
Class description:
Implement the UserErasureStore class.
Method signatures and docstrings:
- async def mark_user_erased(self, user_id: str) -> None: Indicate that user_id wishes their message history to be erased. Args: user_id: full user_id to be erased
... | Implement the Python class `UserErasureStore` described below.
Class description:
Implement the UserErasureStore class.
Method signatures and docstrings:
- async def mark_user_erased(self, user_id: str) -> None: Indicate that user_id wishes their message history to be erased. Args: user_id: full user_id to be erased
... | d35bed8369514fe727b4fe1afb68f48cc8b2655a | <|skeleton|>
class UserErasureStore:
async def mark_user_erased(self, user_id: str) -> None:
"""Indicate that user_id wishes their message history to be erased. Args: user_id: full user_id to be erased"""
<|body_0|>
async def mark_user_not_erased(self, user_id: str) -> None:
"""Indicat... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class UserErasureStore:
async def mark_user_erased(self, user_id: str) -> None:
"""Indicate that user_id wishes their message history to be erased. Args: user_id: full user_id to be erased"""
def f(txn: LoggingTransaction) -> None:
txn.execute('SELECT 1 FROM erased_users WHERE user_id = ... | the_stack_v2_python_sparse | synapse/storage/databases/main/user_erasure_store.py | matrix-org/synapse | train | 12,215 | |
1c74a998242901b44bb6fc055b65dfe6dd56c877 | [
"parser.add_argument('review_request_ids', metavar='REVIEW_REQUEST_ID', nargs='*', help='Specific review request IDs to reset.')\nparser.add_argument('-a', '--all', action='store_true', default=False, dest='all', help='Reset issue counts for all review requests.')\nparser.add_argument('--recalculate', action='store... | <|body_start_0|>
parser.add_argument('review_request_ids', metavar='REVIEW_REQUEST_ID', nargs='*', help='Specific review request IDs to reset.')
parser.add_argument('-a', '--all', action='store_true', default=False, dest='all', help='Reset issue counts for all review requests.')
parser.add_argum... | Management command to reset issue counters. | Command | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Command:
"""Management command to reset issue counters."""
def add_arguments(self, parser):
"""Add arguments to the command. Args: parser (argparse.ArgumentParser): The argument parser for the command."""
<|body_0|>
def handle(self, *args, **options):
"""Handle t... | stack_v2_sparse_classes_36k_train_012987 | 3,134 | permissive | [
{
"docstring": "Add arguments to the command. Args: parser (argparse.ArgumentParser): The argument parser for the command.",
"name": "add_arguments",
"signature": "def add_arguments(self, parser)"
},
{
"docstring": "Handle the command. Args: *args (tuple): Specific review request IDs to reset. *... | 2 | null | Implement the Python class `Command` described below.
Class description:
Management command to reset issue counters.
Method signatures and docstrings:
- def add_arguments(self, parser): Add arguments to the command. Args: parser (argparse.ArgumentParser): The argument parser for the command.
- def handle(self, *args,... | Implement the Python class `Command` described below.
Class description:
Management command to reset issue counters.
Method signatures and docstrings:
- def add_arguments(self, parser): Add arguments to the command. Args: parser (argparse.ArgumentParser): The argument parser for the command.
- def handle(self, *args,... | c3a991f1e9d7682239a1ab0e8661cee6da01d537 | <|skeleton|>
class Command:
"""Management command to reset issue counters."""
def add_arguments(self, parser):
"""Add arguments to the command. Args: parser (argparse.ArgumentParser): The argument parser for the command."""
<|body_0|>
def handle(self, *args, **options):
"""Handle t... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Command:
"""Management command to reset issue counters."""
def add_arguments(self, parser):
"""Add arguments to the command. Args: parser (argparse.ArgumentParser): The argument parser for the command."""
parser.add_argument('review_request_ids', metavar='REVIEW_REQUEST_ID', nargs='*', he... | the_stack_v2_python_sparse | reviewboard/reviews/management/commands/reset-issue-counts.py | reviewboard/reviewboard | train | 1,141 |
5aaa1f03a61c1e57da76276798c80ad98353eb91 | [
"logger = logger or setup_logger('LocalCommandRunner')\nself.logger = logger\nself.host = host",
"if isinstance(command, list):\n popen_args = command\nelse:\n popen_args = _shlex_split(command)\nself.logger.debug('[{0}] run: {1}'.format(self.host, popen_args))\nstdout = subprocess.PIPE if stdout_pipe else ... | <|body_start_0|>
logger = logger or setup_logger('LocalCommandRunner')
self.logger = logger
self.host = host
<|end_body_0|>
<|body_start_1|>
if isinstance(command, list):
popen_args = command
else:
popen_args = _shlex_split(command)
self.logger.de... | LocalCommandRunner | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class LocalCommandRunner:
def __init__(self, logger=None, host='localhost'):
""":param logger: This logger will be used for printing the output and the command."""
<|body_0|>
def run(self, command, exit_on_failure=True, stdout_pipe=True, stderr_pipe=True, cwd=None, execution_env=N... | stack_v2_sparse_classes_36k_train_012988 | 37,803 | permissive | [
{
"docstring": ":param logger: This logger will be used for printing the output and the command.",
"name": "__init__",
"signature": "def __init__(self, logger=None, host='localhost')"
},
{
"docstring": "Runs local commands. :param command: The command to execute. :param exit_on_failure: False to... | 2 | stack_v2_sparse_classes_30k_train_020655 | Implement the Python class `LocalCommandRunner` described below.
Class description:
Implement the LocalCommandRunner class.
Method signatures and docstrings:
- def __init__(self, logger=None, host='localhost'): :param logger: This logger will be used for printing the output and the command.
- def run(self, command, e... | Implement the Python class `LocalCommandRunner` described below.
Class description:
Implement the LocalCommandRunner class.
Method signatures and docstrings:
- def __init__(self, logger=None, host='localhost'): :param logger: This logger will be used for printing the output and the command.
- def run(self, command, e... | 246550c150e33e3e8cf815e1ecff244d82293832 | <|skeleton|>
class LocalCommandRunner:
def __init__(self, logger=None, host='localhost'):
""":param logger: This logger will be used for printing the output and the command."""
<|body_0|>
def run(self, command, exit_on_failure=True, stdout_pipe=True, stderr_pipe=True, cwd=None, execution_env=N... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class LocalCommandRunner:
def __init__(self, logger=None, host='localhost'):
""":param logger: This logger will be used for printing the output and the command."""
logger = logger or setup_logger('LocalCommandRunner')
self.logger = logger
self.host = host
def run(self, command, ... | the_stack_v2_python_sparse | cloudify/utils.py | cloudify-cosmo/cloudify-common | train | 8 | |
99df6a52d5abc0e40549369e2bff49581d55c2ef | [
"a, b = (0, 1)\nif n == 0:\n return 0\nwhile n > 1:\n n -= 1\n a, b = (b, a + b)\nreturn b % 1000000007",
"a, b = (1, 2)\nwhile n > 1:\n n -= 1\n a, b = (b, a + b)\nreturn a % 1000000007"
] | <|body_start_0|>
a, b = (0, 1)
if n == 0:
return 0
while n > 1:
n -= 1
a, b = (b, a + b)
return b % 1000000007
<|end_body_0|>
<|body_start_1|>
a, b = (1, 2)
while n > 1:
n -= 1
a, b = (b, a + b)
return a... | Solution | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Solution:
def fib(self, n: int) -> int:
"""offer 10-1斐波那契数列"""
<|body_0|>
def numWays(self, n: int) -> int:
"""offer 10-2青蛙跳台阶"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
a, b = (0, 1)
if n == 0:
return 0
while n > 1:... | stack_v2_sparse_classes_36k_train_012989 | 1,573 | no_license | [
{
"docstring": "offer 10-1斐波那契数列",
"name": "fib",
"signature": "def fib(self, n: int) -> int"
},
{
"docstring": "offer 10-2青蛙跳台阶",
"name": "numWays",
"signature": "def numWays(self, n: int) -> int"
}
] | 2 | null | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fib(self, n: int) -> int: offer 10-1斐波那契数列
- def numWays(self, n: int) -> int: offer 10-2青蛙跳台阶 | Implement the Python class `Solution` described below.
Class description:
Implement the Solution class.
Method signatures and docstrings:
- def fib(self, n: int) -> int: offer 10-1斐波那契数列
- def numWays(self, n: int) -> int: offer 10-2青蛙跳台阶
<|skeleton|>
class Solution:
def fib(self, n: int) -> int:
"""off... | 3fd69b85f52af861ff7e2c74d8aacc515b192615 | <|skeleton|>
class Solution:
def fib(self, n: int) -> int:
"""offer 10-1斐波那契数列"""
<|body_0|>
def numWays(self, n: int) -> int:
"""offer 10-2青蛙跳台阶"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Solution:
def fib(self, n: int) -> int:
"""offer 10-1斐波那契数列"""
a, b = (0, 1)
if n == 0:
return 0
while n > 1:
n -= 1
a, b = (b, a + b)
return b % 1000000007
def numWays(self, n: int) -> int:
"""offer 10-2青蛙跳台阶"""
... | the_stack_v2_python_sparse | Offer/09_CQueue.py | helloprogram6/leetcode_Cookbook_python | train | 0 | |
4ffe9820be16705c6336831481c97cf2bbc8094f | [
"if hasattr(self, '_cy'):\n return\nself._cy = Int(0)",
"from apysc.type import value_util\nself._initialize_cy_if_not_initialized()\nreturn value_util.get_copy(value=self._cy)",
"from apysc.validation import number_validation\nnumber_validation.validate_integer(integer=value)\nif not isinstance(value, Int):... | <|body_start_0|>
if hasattr(self, '_cy'):
return
self._cy = Int(0)
<|end_body_0|>
<|body_start_1|>
from apysc.type import value_util
self._initialize_cy_if_not_initialized()
return value_util.get_copy(value=self._cy)
<|end_body_1|>
<|body_start_2|>
from apys... | CyInterface | [
"MIT",
"CC-BY-4.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class CyInterface:
def _initialize_cy_if_not_initialized(self) -> None:
"""Initialize _cy attribute if it is not initialized yet."""
<|body_0|>
def y(self) -> Int:
"""Get a center y-coordinate. Returns ------- y : Int Center y-coordinate."""
<|body_1|>
def y(s... | stack_v2_sparse_classes_36k_train_012990 | 2,926 | permissive | [
{
"docstring": "Initialize _cy attribute if it is not initialized yet.",
"name": "_initialize_cy_if_not_initialized",
"signature": "def _initialize_cy_if_not_initialized(self) -> None"
},
{
"docstring": "Get a center y-coordinate. Returns ------- y : Int Center y-coordinate.",
"name": "y",
... | 6 | null | Implement the Python class `CyInterface` described below.
Class description:
Implement the CyInterface class.
Method signatures and docstrings:
- def _initialize_cy_if_not_initialized(self) -> None: Initialize _cy attribute if it is not initialized yet.
- def y(self) -> Int: Get a center y-coordinate. Returns -------... | Implement the Python class `CyInterface` described below.
Class description:
Implement the CyInterface class.
Method signatures and docstrings:
- def _initialize_cy_if_not_initialized(self) -> None: Initialize _cy attribute if it is not initialized yet.
- def y(self) -> Int: Get a center y-coordinate. Returns -------... | 5c6a4674e2e9684cb2cb1325dc9b070879d4d355 | <|skeleton|>
class CyInterface:
def _initialize_cy_if_not_initialized(self) -> None:
"""Initialize _cy attribute if it is not initialized yet."""
<|body_0|>
def y(self) -> Int:
"""Get a center y-coordinate. Returns ------- y : Int Center y-coordinate."""
<|body_1|>
def y(s... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class CyInterface:
def _initialize_cy_if_not_initialized(self) -> None:
"""Initialize _cy attribute if it is not initialized yet."""
if hasattr(self, '_cy'):
return
self._cy = Int(0)
def y(self) -> Int:
"""Get a center y-coordinate. Returns ------- y : Int Center y-c... | the_stack_v2_python_sparse | apysc/display/cy_interface.py | TrendingTechnology/apysc | train | 0 | |
0d8beca4a6422279aac2463ce9e04c32cc8c6435 | [
"result = urlparse(base_url)\nresult = ParseResult(result.scheme, result.netloc, result.path, result.params, urlencode(query_parameters), result.fragment)\nreturn result.geturl()",
"try:\n url_parsed = urlparse(url)\nexcept AttributeError:\n return False\nurl_match_in_list = False\nfor allowed_domain in dom... | <|body_start_0|>
result = urlparse(base_url)
result = ParseResult(result.scheme, result.netloc, result.path, result.params, urlencode(query_parameters), result.fragment)
return result.geturl()
<|end_body_0|>
<|body_start_1|>
try:
url_parsed = urlparse(url)
except Att... | Contains different helper methods simplifying URL construction. | URLUtility | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class URLUtility:
"""Contains different helper methods simplifying URL construction."""
def build_url(base_url, query_parameters):
"""Construct a URL with specified query parameters. :param base_url: Base URL :type base_url: str :param query_parameters: Dictionary containing query paramete... | stack_v2_sparse_classes_36k_train_012991 | 3,107 | permissive | [
{
"docstring": "Construct a URL with specified query parameters. :param base_url: Base URL :type base_url: str :param query_parameters: Dictionary containing query parameters :type query_parameters: Dict :return: Constructed URL :rtype: str",
"name": "build_url",
"signature": "def build_url(base_url, qu... | 2 | null | Implement the Python class `URLUtility` described below.
Class description:
Contains different helper methods simplifying URL construction.
Method signatures and docstrings:
- def build_url(base_url, query_parameters): Construct a URL with specified query parameters. :param base_url: Base URL :type base_url: str :par... | Implement the Python class `URLUtility` described below.
Class description:
Contains different helper methods simplifying URL construction.
Method signatures and docstrings:
- def build_url(base_url, query_parameters): Construct a URL with specified query parameters. :param base_url: Base URL :type base_url: str :par... | 662cc7e0721d0153857c8c17a37e2a6df86f8ce6 | <|skeleton|>
class URLUtility:
"""Contains different helper methods simplifying URL construction."""
def build_url(base_url, query_parameters):
"""Construct a URL with specified query parameters. :param base_url: Base URL :type base_url: str :param query_parameters: Dictionary containing query paramete... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class URLUtility:
"""Contains different helper methods simplifying URL construction."""
def build_url(base_url, query_parameters):
"""Construct a URL with specified query parameters. :param base_url: Base URL :type base_url: str :param query_parameters: Dictionary containing query parameters :type quer... | the_stack_v2_python_sparse | api/util/url.py | NYPL-Simplified/circulation | train | 20 |
1b516fd1f764b25e83edf869f06c39e327824270 | [
"self.model = MultinomialNB\nself.active_model = None\nself.param_grid = {'alpha': [0, 0.25, 0.5, 0.75, 1], 'fit_prior': [True, False]}",
"classifier = GridSearchCV(self.model(), self.param_grid)\nclassifier.fit(training_data, training_labels)\nself.active_model = self.model(**classifier.best_params_)\nself.activ... | <|body_start_0|>
self.model = MultinomialNB
self.active_model = None
self.param_grid = {'alpha': [0, 0.25, 0.5, 0.75, 1], 'fit_prior': [True, False]}
<|end_body_0|>
<|body_start_1|>
classifier = GridSearchCV(self.model(), self.param_grid)
classifier.fit(training_data, training_l... | Basic implementation of a grid-search optimized Logistic Regression. | NaiveMultinomialBayes | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class NaiveMultinomialBayes:
"""Basic implementation of a grid-search optimized Logistic Regression."""
def __init__(self):
"""Initialize internal classifier."""
<|body_0|>
def train(self, training_data, training_labels):
"""Run grid search to optimize hyper-parameters... | stack_v2_sparse_classes_36k_train_012992 | 3,287 | no_license | [
{
"docstring": "Initialize internal classifier.",
"name": "__init__",
"signature": "def __init__(self)"
},
{
"docstring": "Run grid search to optimize hyper-parameters, then trains the final model.",
"name": "train",
"signature": "def train(self, training_data, training_labels)"
},
{... | 3 | stack_v2_sparse_classes_30k_test_000860 | Implement the Python class `NaiveMultinomialBayes` described below.
Class description:
Basic implementation of a grid-search optimized Logistic Regression.
Method signatures and docstrings:
- def __init__(self): Initialize internal classifier.
- def train(self, training_data, training_labels): Run grid search to opti... | Implement the Python class `NaiveMultinomialBayes` described below.
Class description:
Basic implementation of a grid-search optimized Logistic Regression.
Method signatures and docstrings:
- def __init__(self): Initialize internal classifier.
- def train(self, training_data, training_labels): Run grid search to opti... | edffa89740e5cef810344a7bbf8a157241f46d02 | <|skeleton|>
class NaiveMultinomialBayes:
"""Basic implementation of a grid-search optimized Logistic Regression."""
def __init__(self):
"""Initialize internal classifier."""
<|body_0|>
def train(self, training_data, training_labels):
"""Run grid search to optimize hyper-parameters... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class NaiveMultinomialBayes:
"""Basic implementation of a grid-search optimized Logistic Regression."""
def __init__(self):
"""Initialize internal classifier."""
self.model = MultinomialNB
self.active_model = None
self.param_grid = {'alpha': [0, 0.25, 0.5, 0.75, 1], 'fit_prior':... | the_stack_v2_python_sparse | enso/experiment/NB.py | RichGit101/Enso | train | 0 |
a836d8d69051acefa80329429809e02e940a1ba7 | [
"if not source:\n raise ValueError('badge 需要使用键值对的的形式传入, 否则会引发递归调用')\ntarget = get_subclasses_graph(source, relative, badge_name)\nif return_class:\n return target\ncls_name = target.__name__\ncaller = traceback.extract_stack()[-2]\nlogging.debug('{} in {} -> {} install subclass <{}> from <{}>.'.format(caller... | <|body_start_0|>
if not source:
raise ValueError('badge 需要使用键值对的的形式传入, 否则会引发递归调用')
target = get_subclasses_graph(source, relative, badge_name)
if return_class:
return target
cls_name = target.__name__
caller = traceback.extract_stack()[-2]
logging.... | 徽章是所有成员联络的基础 <img src=''/> Badges are the basis for all members to contact. | Badge | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class Badge:
"""徽章是所有成员联络的基础 <img src=''/> Badges are the basis for all members to contact."""
def __new__(cls, *args, source=None, singleton=False, relative=True, return_class=False, badge_name='', **kwargs):
"""通过获取组内最远亲的子类，获取其子类的单例返回, 需要通过此类获取实例化的对象，否则会创建一个新的实例。 只会获取最远亲的子类。当然这也会牺牲init方法... | stack_v2_sparse_classes_36k_train_012993 | 6,733 | permissive | [
{
"docstring": "通过获取组内最远亲的子类，获取其子类的单例返回, 需要通过此类获取实例化的对象，否则会创建一个新的实例。 只会获取最远亲的子类。当然这也会牺牲init方法初始化参数的问题，只能依托于重构方法时 手动创建。 To get the singleton return of its subclass, you need to get the instantiated object through this class, otherwise a new instance will be created. Only get the most distant relatives. :param so... | 2 | stack_v2_sparse_classes_30k_train_006495 | Implement the Python class `Badge` described below.
Class description:
徽章是所有成员联络的基础 <img src=''/> Badges are the basis for all members to contact.
Method signatures and docstrings:
- def __new__(cls, *args, source=None, singleton=False, relative=True, return_class=False, badge_name='', **kwargs): 通过获取组内最远亲的子类，获取其子类的单... | Implement the Python class `Badge` described below.
Class description:
徽章是所有成员联络的基础 <img src=''/> Badges are the basis for all members to contact.
Method signatures and docstrings:
- def __new__(cls, *args, source=None, singleton=False, relative=True, return_class=False, badge_name='', **kwargs): 通过获取组内最远亲的子类，获取其子类的单... | edaa6398260d5f8c7a90cdf2a9669f0a02ca5102 | <|skeleton|>
class Badge:
"""徽章是所有成员联络的基础 <img src=''/> Badges are the basis for all members to contact."""
def __new__(cls, *args, source=None, singleton=False, relative=True, return_class=False, badge_name='', **kwargs):
"""通过获取组内最远亲的子类，获取其子类的单例返回, 需要通过此类获取实例化的对象，否则会创建一个新的实例。 只会获取最远亲的子类。当然这也会牺牲init方法... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class Badge:
"""徽章是所有成员联络的基础 <img src=''/> Badges are the basis for all members to contact."""
def __new__(cls, *args, source=None, singleton=False, relative=True, return_class=False, badge_name='', **kwargs):
"""通过获取组内最远亲的子类，获取其子类的单例返回, 需要通过此类获取实例化的对象，否则会创建一个新的实例。 只会获取最远亲的子类。当然这也会牺牲init方法初始化参数的问题，只能依托... | the_stack_v2_python_sparse | sherry/core/badge.py | wumaoland/sherry | train | 0 |
1be7690b54b5cdd754c9e1a6455449796c7e406c | [
"super(ProbPacConv2d, self).__init__(in_channels, out_channels, kernel_size, stride=1, padding=padding, dilation=1, bias=bias, kernel_type=kernel_type, smooth_kernel_type='none', normalize_kernel=False, shared_filters=shared_filters, filler='uniform', native_impl=False)\nself.weight_normalization = torch.nn.paramet... | <|body_start_0|>
super(ProbPacConv2d, self).__init__(in_channels, out_channels, kernel_size, stride=1, padding=padding, dilation=1, bias=bias, kernel_type=kernel_type, smooth_kernel_type='none', normalize_kernel=False, shared_filters=shared_filters, filler='uniform', native_impl=False)
self.weight_norma... | Implements a probabilistic pixel-adaptive convolution. | ProbPacConv2d | [
"Apache-2.0"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ProbPacConv2d:
"""Implements a probabilistic pixel-adaptive convolution."""
def __init__(self, in_channels, out_channels, kernel_size, padding=0, bias=True, kernel_type='gaussian', shared_filters=False):
"""Initializes PPAC. Args: in_channels: Number of input channels. out_channels: ... | stack_v2_sparse_classes_36k_train_012994 | 7,401 | permissive | [
{
"docstring": "Initializes PPAC. Args: in_channels: Number of input channels. out_channels: Number of output channels. kernel_size: Filter size of used kernel. padding: Number of zero padding elements applied at all borders. bias: Usage of bias term. kernel_type: Type of kernel function K. See original PAC for... | 2 | stack_v2_sparse_classes_30k_train_021419 | Implement the Python class `ProbPacConv2d` described below.
Class description:
Implements a probabilistic pixel-adaptive convolution.
Method signatures and docstrings:
- def __init__(self, in_channels, out_channels, kernel_size, padding=0, bias=True, kernel_type='gaussian', shared_filters=False): Initializes PPAC. Ar... | Implement the Python class `ProbPacConv2d` described below.
Class description:
Implements a probabilistic pixel-adaptive convolution.
Method signatures and docstrings:
- def __init__(self, in_channels, out_channels, kernel_size, padding=0, bias=True, kernel_type='gaussian', shared_filters=False): Initializes PPAC. Ar... | 04a8676f5eb96c41ec6b1125c6bcad430218ef30 | <|skeleton|>
class ProbPacConv2d:
"""Implements a probabilistic pixel-adaptive convolution."""
def __init__(self, in_channels, out_channels, kernel_size, padding=0, bias=True, kernel_type='gaussian', shared_filters=False):
"""Initializes PPAC. Args: in_channels: Number of input channels. out_channels: ... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ProbPacConv2d:
"""Implements a probabilistic pixel-adaptive convolution."""
def __init__(self, in_channels, out_channels, kernel_size, padding=0, bias=True, kernel_type='gaussian', shared_filters=False):
"""Initializes PPAC. Args: in_channels: Number of input channels. out_channels: Number of out... | the_stack_v2_python_sparse | src/probabilistic_pac.py | visinf/ppac_refinement | train | 81 |
6cfee43b0338e9d172c4ca80bc8a6451963240fd | [
"super().__init__()\nself.conv1 = nn.Conv2d(features, features, kernel_size=3, stride=1, padding=1, bias=True)\nself.conv2 = nn.Conv2d(features, features, kernel_size=3, stride=1, padding=1, bias=True)\nself.relu = nn.ReLU(inplace=True)",
"out = self.relu(x)\nout = self.conv1(out)\nout = self.relu(out)\nout = sel... | <|body_start_0|>
super().__init__()
self.conv1 = nn.Conv2d(features, features, kernel_size=3, stride=1, padding=1, bias=True)
self.conv2 = nn.Conv2d(features, features, kernel_size=3, stride=1, padding=1, bias=True)
self.relu = nn.ReLU(inplace=True)
<|end_body_0|>
<|body_start_1|>
... | Residual convolution module. | ResidualConvUnit | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ResidualConvUnit:
"""Residual convolution module."""
def __init__(self, features):
"""Init. Args: features (int): number of features"""
<|body_0|>
def forward(self, x):
"""Forward pass. Args: x (tensor): input Returns: tensor: output"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_36k_train_012995 | 17,410 | permissive | [
{
"docstring": "Init. Args: features (int): number of features",
"name": "__init__",
"signature": "def __init__(self, features)"
},
{
"docstring": "Forward pass. Args: x (tensor): input Returns: tensor: output",
"name": "forward",
"signature": "def forward(self, x)"
}
] | 2 | null | Implement the Python class `ResidualConvUnit` described below.
Class description:
Residual convolution module.
Method signatures and docstrings:
- def __init__(self, features): Init. Args: features (int): number of features
- def forward(self, x): Forward pass. Args: x (tensor): input Returns: tensor: output | Implement the Python class `ResidualConvUnit` described below.
Class description:
Residual convolution module.
Method signatures and docstrings:
- def __init__(self, features): Init. Args: features (int): number of features
- def forward(self, x): Forward pass. Args: x (tensor): input Returns: tensor: output
<|skele... | a00c3619bf4042e446e1919087f0b09fe9fa3a65 | <|skeleton|>
class ResidualConvUnit:
"""Residual convolution module."""
def __init__(self, features):
"""Init. Args: features (int): number of features"""
<|body_0|>
def forward(self, x):
"""Forward pass. Args: x (tensor): input Returns: tensor: output"""
<|body_1|>
<|end_... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ResidualConvUnit:
"""Residual convolution module."""
def __init__(self, features):
"""Init. Args: features (int): number of features"""
super().__init__()
self.conv1 = nn.Conv2d(features, features, kernel_size=3, stride=1, padding=1, bias=True)
self.conv2 = nn.Conv2d(featu... | the_stack_v2_python_sparse | nasws/cnn/search_space/monodepth/models/blocks.py | kcyu2014/nas-landmarkreg | train | 10 |
9d4cc8d14c0e4cf37d81584303445a28d2496bd4 | [
"Request.__init__(self, id_, environment)\nself.compression = 'true' if compression is True else 'false'\nself.software = 'bankws 1.01'\nself.key = key\nself.certificate = certificate",
"if start_date is None:\n startdate = str(date.today())\nelse:\n startdate = str(start_date)\nget_file = DOC(CUSTOMERID(se... | <|body_start_0|>
Request.__init__(self, id_, environment)
self.compression = 'true' if compression is True else 'false'
self.software = 'bankws 1.01'
self.key = key
self.certificate = certificate
<|end_body_0|>
<|body_start_1|>
if start_date is None:
startdat... | GetFile - class can be used to generate getfile messages for finnish banks web-services interfaces. @type compression: string @ivar compression: Is compression used in messages. (Default false) @type software: string @ivar software: Name of software @type key: string @ivar key: RSA-private key filename. @type certifica... | GetFile | [
"MIT"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class GetFile:
"""GetFile - class can be used to generate getfile messages for finnish banks web-services interfaces. @type compression: string @ivar compression: Is compression used in messages. (Default false) @type software: string @ivar software: Name of software @type key: string @ivar key: RSA-pr... | stack_v2_sparse_classes_36k_train_012996 | 3,693 | permissive | [
{
"docstring": "Initializes GetFile class. @type id_: number @param id_: User customerid to web services @type environment: string @param environment: TEST or PRODUCTION @type key: string @param key: RSA-key filename. @type certificate: string @param certificate: X509 certificate filename. @type compression: bo... | 2 | stack_v2_sparse_classes_30k_train_008050 | Implement the Python class `GetFile` described below.
Class description:
GetFile - class can be used to generate getfile messages for finnish banks web-services interfaces. @type compression: string @ivar compression: Is compression used in messages. (Default false) @type software: string @ivar software: Name of softw... | Implement the Python class `GetFile` described below.
Class description:
GetFile - class can be used to generate getfile messages for finnish banks web-services interfaces. @type compression: string @ivar compression: Is compression used in messages. (Default false) @type software: string @ivar software: Name of softw... | 70a500a1a3c85d86bf76a8b9010264ce941c2799 | <|skeleton|>
class GetFile:
"""GetFile - class can be used to generate getfile messages for finnish banks web-services interfaces. @type compression: string @ivar compression: Is compression used in messages. (Default false) @type software: string @ivar software: Name of software @type key: string @ivar key: RSA-pr... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class GetFile:
"""GetFile - class can be used to generate getfile messages for finnish banks web-services interfaces. @type compression: string @ivar compression: Is compression used in messages. (Default false) @type software: string @ivar software: Name of software @type key: string @ivar key: RSA-private key fil... | the_stack_v2_python_sparse | bankws/getfile.py | luojus/bankws | train | 3 |
57d6d5e4d9eb53340f3ab34c8790f97805938378 | [
"query = query.replace('(', ' ( ')\nnormalized = query.replace(')', ' ) ')\nreturn normalized",
"if query.count('(') != query.count(')'):\n raise QueryException('Parentheses dont match')\nif query[0] in ['AND', 'OR', ')']:\n raise QueryException('Invalid First Term')\ni = 1\nwhile i < len(query):\n if ty... | <|body_start_0|>
query = query.replace('(', ' ( ')
normalized = query.replace(')', ' ) ')
return normalized
<|end_body_0|>
<|body_start_1|>
if query.count('(') != query.count(')'):
raise QueryException('Parentheses dont match')
if query[0] in ['AND', 'OR', ')']:
... | Manages parsing boolean query strings, and converting them to a postfix list. | QueryParser | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class QueryParser:
"""Manages parsing boolean query strings, and converting them to a postfix list."""
def _normalize_query(self, query):
"""Normalizes the braces in the query to be padded with spaces. Allows easy splitting of the query."""
<|body_0|>
def _validate_query(self,... | stack_v2_sparse_classes_36k_train_012997 | 5,387 | no_license | [
{
"docstring": "Normalizes the braces in the query to be padded with spaces. Allows easy splitting of the query.",
"name": "_normalize_query",
"signature": "def _normalize_query(self, query)"
},
{
"docstring": "Validates the order and overall construction of the query :exception: QueryException ... | 5 | stack_v2_sparse_classes_30k_train_000231 | Implement the Python class `QueryParser` described below.
Class description:
Manages parsing boolean query strings, and converting them to a postfix list.
Method signatures and docstrings:
- def _normalize_query(self, query): Normalizes the braces in the query to be padded with spaces. Allows easy splitting of the qu... | Implement the Python class `QueryParser` described below.
Class description:
Manages parsing boolean query strings, and converting them to a postfix list.
Method signatures and docstrings:
- def _normalize_query(self, query): Normalizes the braces in the query to be padded with spaces. Allows easy splitting of the qu... | 54481dfd88637572b92b8e17ba6ef6458fade9a4 | <|skeleton|>
class QueryParser:
"""Manages parsing boolean query strings, and converting them to a postfix list."""
def _normalize_query(self, query):
"""Normalizes the braces in the query to be padded with spaces. Allows easy splitting of the query."""
<|body_0|>
def _validate_query(self,... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class QueryParser:
"""Manages parsing boolean query strings, and converting them to a postfix list."""
def _normalize_query(self, query):
"""Normalizes the braces in the query to be padded with spaces. Allows easy splitting of the query."""
query = query.replace('(', ' ( ')
normalized =... | the_stack_v2_python_sparse | web/bfex/components/search_engine/parser.py | MandyMeindersma/BFEX | train | 0 |
02cb826392f772204ad1c4f3d43cd1a0472e2054 | [
"activity = self.get_object()\nif kwargs.get('order'):\n try:\n getattr(activity, 'to')(int(kwargs['order']))\n except AttributeError:\n log.exception('Unknown ordering method!')\n return HttpResponse(status=201)\nreturn super().get(request, *args, **kwargs)",
"activity = self.get_object()\... | <|body_start_0|>
activity = self.get_object()
if kwargs.get('order'):
try:
getattr(activity, 'to')(int(kwargs['order']))
except AttributeError:
log.exception('Unknown ordering method!')
return HttpResponse(status=201)
return sup... | ActivityUpdate | [
"BSD-3-Clause"
] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class ActivityUpdate:
def get(self, request, *args, **kwargs):
"""To Update activity by a GET request. Updating activities order and running update method in the superclass. The drag and drop feature uses this view."""
<|body_0|>
def post(self, request, *args, **kwargs):
"... | stack_v2_sparse_classes_36k_train_012998 | 36,805 | permissive | [
{
"docstring": "To Update activity by a GET request. Updating activities order and running update method in the superclass. The drag and drop feature uses this view.",
"name": "get",
"signature": "def get(self, request, *args, **kwargs)"
},
{
"docstring": "To Update activity by a POST request. U... | 2 | stack_v2_sparse_classes_30k_train_001616 | Implement the Python class `ActivityUpdate` described below.
Class description:
Implement the ActivityUpdate class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): To Update activity by a GET request. Updating activities order and running update method in the superclass. The drag and drop... | Implement the Python class `ActivityUpdate` described below.
Class description:
Implement the ActivityUpdate class.
Method signatures and docstrings:
- def get(self, request, *args, **kwargs): To Update activity by a GET request. Updating activities order and running update method in the superclass. The drag and drop... | 07c04dadaaaeefc840593e5582dacdb188fcf8f8 | <|skeleton|>
class ActivityUpdate:
def get(self, request, *args, **kwargs):
"""To Update activity by a GET request. Updating activities order and running update method in the superclass. The drag and drop feature uses this view."""
<|body_0|>
def post(self, request, *args, **kwargs):
"... | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class ActivityUpdate:
def get(self, request, *args, **kwargs):
"""To Update activity by a GET request. Updating activities order and running update method in the superclass. The drag and drop feature uses this view."""
activity = self.get_object()
if kwargs.get('order'):
try:
... | the_stack_v2_python_sparse | bridge_adaptivity/module/views.py | ahsaniqbal94/bridge-adaptivity | train | 0 | |
2ce0900a1f9d3913db3dbd2041d6ae3060a6fc69 | [
"assert len(self.buff_dict) == 10\nassert self.buff_dict.popitem() == (9, 9)\nassert len(self.buff_dict) == 9\nassert (9, 9) not in self.buff_dict.items()",
"try:\n assert self.buff_dict.get(i) == i\nexcept AssertionError:\n assert self.buff_dict.get(i) is None"
] | <|body_start_0|>
assert len(self.buff_dict) == 10
assert self.buff_dict.popitem() == (9, 9)
assert len(self.buff_dict) == 9
assert (9, 9) not in self.buff_dict.items()
<|end_body_0|>
<|body_start_1|>
try:
assert self.buff_dict.get(i) == i
except AssertionErro... | тесты для dict | TestDict2 | [] | stack_v2_sparse_python_classes_v1 | <|skeleton|>
class TestDict2:
"""тесты для dict"""
def test_dict_2_1(self):
"""тест метода popitem"""
<|body_0|>
def test_dict_2_2(self, i):
"""тест метода get"""
<|body_1|>
<|end_skeleton|>
<|body_start_0|>
assert len(self.buff_dict) == 10
assert self.buf... | stack_v2_sparse_classes_36k_train_012999 | 1,316 | no_license | [
{
"docstring": "тест метода popitem",
"name": "test_dict_2_1",
"signature": "def test_dict_2_1(self)"
},
{
"docstring": "тест метода get",
"name": "test_dict_2_2",
"signature": "def test_dict_2_2(self, i)"
}
] | 2 | stack_v2_sparse_classes_30k_train_000632 | Implement the Python class `TestDict2` described below.
Class description:
тесты для dict
Method signatures and docstrings:
- def test_dict_2_1(self): тест метода popitem
- def test_dict_2_2(self, i): тест метода get | Implement the Python class `TestDict2` described below.
Class description:
тесты для dict
Method signatures and docstrings:
- def test_dict_2_1(self): тест метода popitem
- def test_dict_2_2(self, i): тест метода get
<|skeleton|>
class TestDict2:
"""тесты для dict"""
def test_dict_2_1(self):
"""тест... | 9c468bc73dc4e326f423cb7932090f59b50a4371 | <|skeleton|>
class TestDict2:
"""тесты для dict"""
def test_dict_2_1(self):
"""тест метода popitem"""
<|body_0|>
def test_dict_2_2(self, i):
"""тест метода get"""
<|body_1|>
<|end_skeleton|> | stack_v2_sparse_classes_36k | data/stack_v2_sparse_classes_30k | class TestDict2:
"""тесты для dict"""
def test_dict_2_1(self):
"""тест метода popitem"""
assert len(self.buff_dict) == 10
assert self.buff_dict.popitem() == (9, 9)
assert len(self.buff_dict) == 9
assert (9, 9) not in self.buff_dict.items()
def test_dict_2_2(self, i)... | the_stack_v2_python_sparse | hw1/test_dict.py | ikramanop/2020-1-Atom-QA-Python-L-Marder | train | 1 |
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