text stringlengths 190 325k |
|---|
Imports:
```python
import os
import shutil
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
def v0(v1, v2, v3=1):
for v4 in range(1, v2 + 1):
if not os.path.exists(v1):
return
try:
shutil.rmtree(v1)
break
except:... |
Imports:
```python
from ast import literal_eval
import os
import typing
```
Type definitions:
Input Types: dict, bool
Output Type: tuple
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict, v2: bool=False) -> tuple:
v3 = ['taskRoleArn', 'executionRoleArn', 'volumes', 'placementConstraints', ... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray, v2: np.ndarray):
print('Error rate / Misclassification Error:', np.mean(v1 != v2))
print('Accuracy:', np.mea... |
Imports:
```python
import typing
```
Type definitions:
```python
@dataclasses.dataclass(frozen=True)
class v0:
v1: float
v2: int
v3: Dict[str, float]
def v4(self, v5: v0) -> Optional[v0]:
"""
Subtracts "resources required" for a job from self, which is interpreted as
"resources ... |
Imports:
```python
import csv
import io
import typing
```
Type definitions:
Input Types: bytes
Output Type: List[Dict[str, Any]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: bytes) -> List[Dict[str, Any]]:
v2 = io.StringIO(v1.decode())
v3 = csv.DictReader(v2)
return [row for v4 in v3]
``... |
Imports:
```python
import pandas as pd
import typing
```
Type definitions:
Input Types: Doc
Output Type: pd.DataFrame
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Doc) -> pd.DataFrame:
v2 = ['matched_term', 'POS', 'tag', 'scispacy_object_category', 'object_id', 'object_category', 'object_label',... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: List[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> List[str]:
v1 = self._source or ''
v2 = self._collection or ''
v3 = self._description or ''
v4 = [self._id, v1, v2, self._name, ','.join(sorte... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str, str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: str, v3: str) -> str:
if '.' in v1:
v1 = v1.replace('.', '')
v4 = 6 - len(v1)
v1 = '0' * v4 + v1
else:
v4 =... |
Imports:
```python
import os
import os.path as op
import subprocess
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1):
self.revit_year = v1['<revit_year>']
self.model_path = v1['<model_path>']
self.ghdoc_path = v1['<ghdoc_path>']
self.add_rps = v1['--rps... |
Imports:
```python
import typing
```
Type definitions:
Input Types: etree.Element
Output Type: Tuple[str, str]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: etree.Element) -> Tuple[str, str]:
v2 = v1.nsmap
v3 = v1.find('article-meta', v2)
v4 = v3.find('fpage', v2)
v5 = v3.find('lpage'... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, bool, bool
Output Type: pd.DataFrame
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2: bool, v3: bool) -> pd.DataFrame:
if v2:
v1 = v1.resample('1S').mean()
if v3:
v1 = v1.interpolate(method='linear')
... |
Imports:
```python
import collections
import typing
```
Type definitions:
Input Types: int, int, int, int
Output Type: float
Dependencies:
```python
def v0(v1, v2):
if v1 < 0 or v1 > N - 1 or v2 < 0 or (v2 > N - 1):
return False
return True
```
Function Name: v3
Function:
```python
def v3(self, v4: int... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: int
Output Type: np.ndarray
Dependencies:
```python
def v0(v1: int) -> np.ndarray:
v2 = np.random.randn(v1, v1)
(v3, v4) = np.linalg.qr(v2)
v5 = np.diag(v4)
return v3 * (v5 / abs(v5))
```
Function Name: v6
Function:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: torch.Tensor
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor) -> None:
v2 = self.layer1(v1)
v2 = self.drop(v2)
v2 = self.layer2(v2)
v2 = v2.view(v2.size(0), -1)
v2 = self.drop(v2... |
Imports:
```python
import typing
```
Type definitions:
Input Types: pd.DataFrame, str, Any
Output Type: Any
Dependencies:
```python
def v0(v1, v2=20, v3=2, v4=2):
v5 = compute_sma(v1, window=v2)
v6 = v1.rolling(window=v2, center=False).std()
v7 = v5 + v3 * v6
v8 = v5 - v4 * v6
return (v5, v7, v8)
`... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool=None, *v2):
if v1 is None:
return
self._autosave.set(v1)
if not self._autosave.is_set():
self._save_img.set(False)
sel... |
Imports:
```python
import nltk
import re
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.text = nltk.tokenize.word_tokenize(self.text)
self.text = [re.sub('[^A-Za-z]', '', token.lower()) for v1 in self.text]
... |
Imports:
```python
from urllib.parse import urlparse
import typing
```
Type definitions:
Input Types: str
Output Type: Tuple[str, str]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> Tuple[str, str]:
v2 = urlparse(v1)
if not v2.scheme == 'gs':
raise NameError('gcs_path must be a... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types:
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> float:
v1 = self.sigma ** 2
v2 = self.nu
return np.log(1 - self.theta * v2 - 0.5 * v1 * v2) / v2
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
v2 = []
v3 = 0
for v4 in range(len(v1)):
if v1[v4] == '-':
v5 = v1[v3:v4]
v3 = v4 + 1
v2.append(int(v5))... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list, list
Output Type: list
Dependencies:
```python
def v0(v1: Any) -> dict:
v2 = type(v1)
v3 = {}
if v2 == Calendar:
for v4 in KEYS_FOR_CALENDAR:
v3[v4] = v0(v1[v4])
elif v2 == Event:
for v4 in KEYS_FOR_EV... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[int], int
Output Type: List[int]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[int], v2: int) -> List[int]:
v3 = self._binary_search(v1, v2, True)
if v3 == len(v1) or v1[v3] != v2:
return [-1, -1]
... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str, str, str
Output Type: List[dict]
Dependencies:
```python
@config.retry
def v0(v1: str, v2: str) -> List[dict]:
v3 = sdk_cmd.cluster_request('GET', '/slave/{}/files/browse?path={}'.format(v1, v2), retry=False, raise_on_error=False, l... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: (int, int)
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2=ceil) -> (int, int):
if self.skipXY is not None:
assert len(self.skipXY) == 2
return self.skipXY
v3 = self.ratio
(v4,... |
Imports:
```python
import typing
```
Type definitions:
Input Types: s.While
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: s.While):
self._resolve(v1.condition)
self._resolve(v1.body)
return None
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: Tuple[np.ndarray, np.ndarray], Tuple[int, int], float, float
Output Type: np.ndarray
Dependencies:
```python
def v0(v1: np.ndarray, v2: int, v3: float, v4: float) -> np.ndarray:
v5 = np.floor((v1[v2] + v3 / 2.0) / v4).astype(int... |
Imports:
```python
from contextlib import redirect_stdout
import io
from textwrap import dedent
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
def v0(v1: str) -> str:
v2 = io.StringIO()
with redirect_stdout(v2):
Interpreter().run(v1)
return v2.getvalue()... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('TSerializable', bound='BaseSerializable')
```
Input Types: bytes
Output Type: v0
Dependencies:
Function Name: v1
Function:
```python
def v1(cls: Type[v0], v2: bytes) -> v0:
v3 = cls._meta.container_sedes.deserialize(v2)
return cls(*... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, **v1) -> dict:
v2 = 'tech_input_maint_total_costs_usd'
self.create_new_question(keyword=v2, translation={'label': {'en': 'Total costs for maintenance of the T... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int
Output Type: None
Dependencies:
```python
def v0():
self.i3.command(f'[id="{self.workspaces.window(index).id}"] focus')
self.i3.command(f'move container to workspace {workspace_to + 1}')
```
Function Name: v1
Function:
```python
def v... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str):
v2 = v1.split('/')
v3 = v2[0]
if len(v2) == 1:
return v3
v4 = v2[1]
if v4.__contains__('VGG'):
v4 = 'VGG'
elif v4.__cont... |
Imports:
```python
import numbers
import logging
import numpy as np
import typing
```
Type definitions:
Input Types: Dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Dict):
for (v2, v3) in v1.items():
if v2 in self.is_numeric:
if self.is_numeric[v2] !=... |
Imports:
```python
import logging
import typing
```
Type definitions:
Input Types: Any, Any, bool, str, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2=logging.DEBUG, v3: bool=False, v4: str=None, v5=logging.WARNING):
if v1 in logging.Logger.manager.loggerDict.keys():
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> int:
v2 = sorted(v1)
return sum((v1[i] != v2[i] for v3 in range(len(v1))))
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.event.on_stop()
self.running = False
self.stream.disconnect()
self.thread.join()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> None:
global dialog
v2 = None
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: MutableMapping[str, Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> MutableMapping[str, Any]:
v1 = super().get_config()
v1['groups'] = self._groups
v1['batch_norm_layer'] = self.batch_norm_layer
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional[float]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Optional[float]=None) -> None:
if self.trainer.lr_scheduler._is_plateau:
self.trainer.lr_scheduler.epoch_update(v1)
else:
s... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: dict, str
Output Type: str
Dependencies:
```python
def v0(v1: dict) -> int:
v2 = 4
if 'indent_size' in v1:
v2 = v1['indent_size']
if v2 == 'tab':
v2 = get_tab_size(v1, no_recurse=True)
else:
... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1, v2, v3, v4):
assert v2 > v1 >= 0, 'Got invalid box with xmin: {0} and xmax {1}'.format(v1, v2)
assert v4 > v3 >= 0, 'Got invalid box with ymin: {0} and ymax {1}'.format(v3, v4)
self._xmin = v1
... |
Imports:
```python
import os
from pathlib import Path
import typing
```
Type definitions:
Input Types: Any, Any, Any
Output Type: None
Dependencies:
```python
def v0(v1, v2, v3) -> None:
try:
v4 = apply_annotations.apply_stub_annotations(v2, v3)
with open(v3, 'w') as v5:
v5.write(v4)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional[int]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Optional[int]=None):
if v1 is None:
v1 = 1
return self.fc1.weight.new(v1, self.hidden_dim).zero_()
``` |
Imports:
```python
import json
from datetime import datetime, timezone, tzinfo
from uuid import uuid4
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
```python
def v0() -> oscatalog.Catalog:
v1 = common.Metadata(**{'title': 'My simple catalog', 'last-modified': datetime.now().asti... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Union[Image.Image, np.ndarray, 'torch.Tensor', List[Image.Image], List[np.ndarray], List['torch.Tensor']], bool
Output Type: Dict[str, Dict]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Union[Image.Image, np.ndarray, 'torch.Te... |
Imports:
```python
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch import Tensor
import typing
```
Type definitions:
Input Types: Tensor
Output Type: Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Tensor) -> Tensor:
(v2, v3, v2, v2) = v1.size()
v4 = s... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: List['BaseTrainingParticipant'], float
Output Type: List['BaseTrainingParticipant']
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List['BaseTrainingParticipant'], v2: float) -> List['BaseTrainingParticipant']:
... |
Imports:
```python
import pickle
import typing
```
Type definitions:
Input Types: str, str
Output Type: Any
Dependencies:
```python
def v0(v1: str, v2: str):
v3 = open(v1 + v2 + '.pickle', 'rb')
v4 = pickle.load(v3)
v3.close()
return v4
```
Function Name: v5
Function:
```python
def v5(v6: str, v7: str)... |
Imports:
```python
import typing
```
Type definitions:
Input Types: torch.Tensor
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor) -> torch.Tensor:
v1 = self.features(v1)
v1 = self.avgpool(v1)
v1 = v1.view(v1.size(0), -1)
v1 = self.classifier(... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str='<desconhecido>', v2=0):
v3 = v1
v4 = v2
if len(v3.strip()) <= 0:
v3 = '<desconhecido>'
if len(v4.strip()) <= 0:
v4 = 0
r... |
Imports:
```python
from glob import glob
from pathlib import Path
import typing
```
Type definitions:
Input Types: Union[str, Path]
Output Type: Optional[List[str]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Union[str, Path]) -> Optional[List[str]]:
v2 = Path(v1) / 'build' / 'contracts' / '*.j... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool, bool, float
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool=True, v2: bool=True, v3: float=None) -> bool:
if self.monofasc():
return True
if v1:
if self.fascicle_fascicle_inter... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, typing.Union[list, dict]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: typing.Union[list, dict], *v3):
if isinstance(v2, dict):
return super()._value_thru_fields(v1, v2, *v3)
v4 = ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[int]
Output Type: List[int]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[int]) -> List[int]:
v2 = []
for v3 in v1:
v4 = abs(v3) - 1
if v1[v4] > 0:
v1[v4] *= -1
else:
... |
Imports:
```python
import torch
from torch.utils.data.dataloader import DataLoader
from torch.utils.data.sampler import SequentialSampler, RandomSampler
import typing
```
Type definitions:
Input Types: Trainer, torch.nn.Module, Dict[str, Union[torch.Tensor, Any]]
Output Type: bool
Dependencies:
```python
def v0(v1: Tr... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int):
for v2 in self._traverse_overflow(v1):
self._mem.del_node(v2)
``` |
Imports:
```python
from io import BytesIO
from wave import Wave_write, Wave_read
import typing
```
Type definitions:
Input Types: bytes
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: bytes) -> dict:
v2 = Wave_read(BytesIO(v1))
v3 = v2.getparams()
if v3.comptype == 'NONE':... |
Imports:
```python
from datetime import datetime as dt
from datetime import timedelta, timezone
import typing
```
Type definitions:
Input Types:
Output Type: dt
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> dt:
try:
v1 = dt.now().replace(minute=0, second=0, microsecond=0).date()
... |
Imports:
```python
import os
import torch
import torch.utils.data
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1, v2, v3, v4, v5, v6, v7):
self.id = v1
self.locations = v3
self.base = float(v3[0])
self.window_size = v7.window_size
self.interval... |
Imports:
```python
import numpy as np
import pandas as pd
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: pd.DatetimeIndex
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2='%Y%m%d%H%M') -> pd.DatetimeIndex:
if not isinstance(v1, np.ndarray):
raise TypeError
v3 =... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
if self.last_fetched_indicator__modified is None:
self.last_fetched_indicator__modified = v1
else:
v2 = self.stix_time_to_datetime... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> str:
v1 = []
v2 = 0
for v3 in self.q_qubits:
v1.append(f'[q{v2}]|Οβͺ = {round(v3[0][0], 3)}|0βͺ + {round(v3[1][0], 3)}|1βͺ')
v2 += 1
v1... |
Imports:
```python
import datetime
import typing
```
Type definitions:
Input Types: bool
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool=False) -> dict:
if self.is_global:
self._session_info = self._global_session_info
self._session_start = self._global_... |
Imports:
```python
import numpy as np
from numpy.linalg import pinv
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray
Output Type: NoReturn
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray, v2: np.ndarray) -> NoReturn:
if self.include_intercept_:
v3 = n... |
Imports:
```python
import warnings
import typing
```
Type definitions:
Input Types: str, str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str=None) -> bool:
warnings.warn('`client.exists_table(name)` is deprecated, and will be removed in a future version of Ibis.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: float) -> str:
v2 = 1000 * round(v1 - int(v1), 3)
(v3, v4) = divmod(v1, 60)
(v5, v3) = divmod(v3, 60)
return '%02d:%02d:%02d.%03d' % (v5, v3, v4, v2... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[str], List[str], int, bool
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[str], v2: List[str], v3: int=32, v4: bool=False) -> int:
(v1, v2, v5) = self.remove_eq_sents(v1, v2)
v6 = self.ppl(v1, ... |
Imports:
```python
import numpy as np
from matplotlib import patches
import typing
```
Type definitions:
Input Types: Any, list, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2: list, v3: str='white'):
for v4 in v2:
v5 = patches.Polygon(np.array(v4).reshape(-1, 2), f... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: Sequence, str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Sequence, v2: str) -> None:
if not 8 < len(v1) < 65536:
raise ValueError('data must be between 8 and 65536 samples')
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int):
(v2, v3, v4, v5, v6, v7, v8) = self.data[v1]
v9 = []
if self.speed_perturb is None:
v9.append([v2, v5, v4, v6, v7, v8])
else:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> None:
with open(v1) as v2:
v3 = ['#']
while v3[0][0] == '#':
v3 = v2.readline().split()
v4 = 0
v5 = 0
... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1, v2, v3, v4):
self._session = v1
self._attributes = v2
self._obj_id = v3
self._relationships = v4
def v5(self, v6):
logging.debug('Attributes: {}'.format(self._attributes))
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> str:
if self.private._field_name is None:
return ''
return self.private._field_name
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: tuple[int | str, int | str]
Output Type: pycep_typing.GreaterThanOrEquals
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: tuple[int | str, int | str]) -> pycep_typing.GreaterThanOrEquals:
(v2, v3) = v1
return {'type': 'gr... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Optional[Dict]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self: Any, v1: Optional[Dict]=None) -> None:
v2: Any = {}
self._hgp = v2
self._hgps = {}
if v1:
pass
``` |
Imports:
```python
import numpy as np
import sklearn
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray, v2: np.ndarray) -> Any:
v2 = np.eye(30)[v2]
v3 = np.zeros((30,))
for v4 in range(30):
... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> str:
if not len(v1):
return ''
v2 = re.search('[a-zA-Z]', v1)
return v2.group() if v2 else ''
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str='access_token.txt') -> str:
with open(v1, mode='r') as v2:
v3 = v2.readline().replace('\n', '')
return v3
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int, int, int, int
Output Type: List[int]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int, v2: int, v3: int, v4: int, v5: int=1) -> List[int]:
assert v5 >= 1
assert v4 > 0
assert v1 > 0
assert v2 >= 0
asser... |
Imports:
```python
import typing
```
Type definitions:
Input Types: pygame.display
Output Type: Any
Dependencies:
```python
def v0(self, v1: int):
self.rotation += v1
```
Function Name: v2
Function:
```python
def v2(self, v3: pygame.display):
v4 = v0(self.image, self.rotation)
(self.sx, self.sy) = v4.get_s... |
Imports:
```python
from pandas._config import get_option
from pandas._libs import algos as libalgos, index as libindex, lib
import pandas._libs.join as libjoin
from pandas._libs.lib import is_datetime_array, no_default
from pandas._libs.tslibs import IncompatibleFrequency, NaTType, OutOfBoundsDatetime, Timestamp, tz_co... |
Imports:
```python
from urllib.parse import urlparse
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
```python
def v0(v1: str) -> bool:
try:
return bool(urlparse(v1).netloc)
except Exception:
return False
```
Function Name: v2
Function:
```python
def v2(v3: s... |
Imports:
```python
import typing
```
Type definitions:
Input Types: json
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: json):
v2 = 0
if 'retem_ir' in v1:
if v1['retem_ir'] == 'S':
v2 += v1['valor_ir']
if 'retem_cofins' in v1:
if v1['retem... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = t.TypeVar('KT')
```
```python
v1 = t.TypeVar('VT')
```
Input Types: v0, v1
Output Type: t.Dict[v0, v1]
Dependencies:
Function Name: v2
Function:
```python
def v2(self, v3: v0, v4: v1) -> t.Dict[v0, v1]:
if len(self._cache) >= self.max_size:
... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: dict
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict) -> None:
if not v1.get('displayName'):
v2 = os.path.basename(os.getcwd()).replace(self.app_prefix, '')
v2 = v2.replace('_'... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[str]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[str]) -> Any:
v2 = {}
for (v3, v4) in enumerate(v1):
for (v5, v6) in enumerate(v4):
v2[v5, v3] = int(v6)
v7 = len(v1)
v... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(Model):
v1: str
v2: str
v3: str
v4: bool
v5: str
v6: str
v7: str
v8: str
v9: str
v10: str
def v11(self, v12: str) -> v0:
self.acs_url = v12
return self
def v13(self, v14: str) -> v... |
Imports:
```python
import logging
import logging.handlers
import sys
import typing
```
Type definitions:
Input Types: T.Dict[T.Text, T.Any]
Output Type: logging.Logger
Dependencies:
```python
def v0(v1: logging.Formatter, v2: int) -> logging.Handler:
v3 = logging.StreamHandler(stream=sys.stdout)
v3.setFormatte... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> dict:
v2 = self._prep_settings()[v1]
v3 = {k: v for (v4, v5) in v2 if v4 in ['port', 'password']}
v3 += dict(username=v2['user'], hostname=... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> str:
v1 = ''
for (v2, v3) in sorted(self.zones_map.items()):
v1 += v2 + '\n'
return self.ZONES_FILE.format(invocation=self.invocation, tz_versio... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[int, models.Host], List[models.ProcessStatus]
Output Type: Dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Dict[int, models.Host], v2: List[models.ProcessStatus]) -> Dict:
v3 = None
v4 = None
for v5 in v2:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Callable, Callable, Callable
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Callable, v2: Callable, v3: Callable):
self.mc_button.config(command=v1)
self.type_button.config(command=v2)
self.select_gr... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int, v2: int) -> str:
if v2 == 16:
return hex(v1)[2:]
if v1 == 0:
return '0'
v3 = []
while v1:
v3.append(str(v1 % v2))
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: typing.Dict[int, str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> typing.Dict[int, str]:
v1 = {}
for v2 in self.__records:
v1[v2.groupID] = v2.groupName
return v1
``` |
Imports:
```python
from pathlib import Path
import typing
```
Type definitions:
Input Types: List[Text], Text
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[Text], v2: Text) -> None:
for v3 in v1:
v3 = v2 + '/' + str(v3)
if not Path(v3).exists():
... |
Imports:
```python
import asyncio
import typing
```
Type definitions:
Input Types: str
Output Type: Union[Any, None]
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: str, *v2) -> Union[Any, None]:
async with self.asyncio_lock:
self.invocation_event = asyncio.Event()
self.... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, *v1: str, **v2: Any) -> bool:
v3 = True
if not v1:
for v4 in self._async_handlers:
v3 = v4._async_join(**v2) and v3
else:
for ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[Union[str, int, float]], [str, int, float], int
Output Type: List[Union[str, int, float]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[Union[str, int, float]], v2: [str, int, float]=None, v3: int=5) -> List[Union[str, int,... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Union[GaussianMixture, KMeans]
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Union[GaussianMixture, KMeans]) -> np.ndarray:
if self.algorithm == 'gmm':
return v1.means_
return v1.cluster_... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types:
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> str:
if self.compiler_type:
return self.compiler_type
v1 = []
for v2 in ['clang', 'gcc']:
v3 = os.path.join(self.toolchain_roo... |
Imports:
```python
import datetime
import typing
```
Type definitions:
Input Types: dict
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: dict):
for v2 in tuple(v1.keys()):
if not v1[v2] or (v2 == 'footer' and 'text' not in v1[v2]) or (v2 == 'author' and 'name' not in v1[v2]... |
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