text stringlengths 190 325k |
|---|
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('_TState')
```
Input Types: typing.RelativeTime, typing.ScheduledAction[v0], Optional[v0]
Output Type: abc.DisposableBase
Dependencies:
Function Name: v1
Function:
```python
def v1(self, v2: typing.RelativeTime, v3: typing.ScheduledAction[v0... |
Imports:
```python
import cv2
import numpy as np
from numpy import ndarray as NDArray
import torch
import typing
```
Type definitions:
```python
v0 = Tuple[int, int, int, int]
```
Input Types: Any, float
Output Type: Any
Dependencies:
```python
def v1(v2):
(v3, v4, v5, v6, v7) = v2
return (v3, v4, v5 - v3, v6 -... |
Imports:
```python
import json
import typing
```
Type definitions:
Input Types:
Output Type: Dict[str, Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Dict[str, Any]:
try:
return json.loads(self.extra)
except (TypeError, json.JSONDecodeError):
return {}
``` |
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:
v2 = re.compile('(where|and) \\(select volt_tt_[a-z0-9]+\\.fl[i|o]p as fl[i|o]p from volt_tt_[a-z0-9]+\\) = 1( and)?', re.MULTILINE | re.IG... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: Dict[str, list]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> Dict[str, list]:
v2: Dict[str, list] = {}
if v1.plot_fitness_density:
v2['fitnesses'] = []
if v1.plot_fitness_accuracy:
v2[... |
Imports:
```python
import torch
from torch.utils.data import DataLoader
import typing
```
Type definitions:
Input Types: Any
Output Type: torch.BoolTensor
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> torch.BoolTensor:
v2 = v1.get_json(force=True)
v3 = v2['mask']
v4 = torch.BoolTensor(... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: str, v2: str, v3: dict, v4: BaseGeometry, v5: List[float], v6: Optional[dt.datetime], v7: Optional[dt.datetime], v8: dict, v9: List[ProductFile], v10: List[ProductFile], v11: List[ProductFile], v12: List[ProductFile])... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = '\n from typing import Literal\n\n class MyCM:\n def __enter__(self) -> None:\n pass\n\n ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> None:
v2: int
v3: Transient
self.next_free = v1
v3 = self.root
if v1 == v3.id:
self.root = v3.next
self.size -= 1
... |
Imports:
```python
from selenium.common.exceptions import WebDriverException, TimeoutException, ElementNotInteractableException, ElementClickInterceptedException, NoSuchElementException
from selenium.webdriver import Chrome, ActionChains
from selenium.webdriver.common.by import By
from selenium.webdriver.common.keys im... |
Imports:
```python
from requests.exceptions import ConnectionError
import typing
```
Type definitions:
Input Types: float, str
Output Type: None
Dependencies:
```python
def v0(v1: str=LOCATION, v2: str=LOCATION_TYPE) -> dict:
v3 = [f'areaType={v2}', f'areaName={v1}']
v4 = {'areaName': 'areaName', 'areaCode': '... |
Imports:
```python
from itertools import permutations
from fractions import Fraction
import typing
```
Type definitions:
Input Types: Any
Output Type: list
Dependencies:
```python
def v0(v1, v2, v3, v4) -> str:
return str(v1) + OPERATOR[v2] + str(v3) + ' = ' + str(v4)
```
```python
def v5(v6, v7) -> tuple:
v8 ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Tuple[float, float, float]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> Tuple[float, float, float]:
v2 = self.__get_url('accounts/' + v1 + '/balance?instType=BROKERAGE&realTimeNAV=true')
v3 = s... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: Text, v2: Node, v3: int, v4: Optional[Node]=None, v5: Optional[int]=None) -> None:
"""Create an Edge.
Args:
name: Name of the edge. Used primarily for debugging.
node1: One of the nodes edge c... |
Imports:
```python
from .trace import TraceElement, trace_append_element, trace_path, trace_path_get, trace_stack_cv, trace_stack_pop, trace_stack_push, trace_stack_top
import typing
```
Type definitions:
```python
v0 = Callable[[HomeAssistant, TemplateVarsType], bool]
```
Input Types: v0
Output Type: v0
Dependencies:
... |
Imports:
```python
import logging, os, pandas as pd
import typing
```
Type definitions:
Input Types: Any, Optional[str], bool
Output Type: Iterable[str]
Dependencies:
```python
def v0(v1):
if isinstance(v1, str):
return v1.replace('"', '\\"')
return str(v1)
```
```python
def v2(v3: dict, v4: str, v5: s... |
Imports:
```python
from itertools import chain, product
import typing
```
Type definitions:
```python
v0 = TypeVar('K')
```
```python
v1 = TypeVar('V')
```
Input Types: Mapping[v0, Union[v1, List[v1], Set[v1], Tuple[v1]]]
Output Type: Iterable[Dict[v0, v1]]
Dependencies:
Function Name: v2
Function:
```python
def v2(v3... |
Imports:
```python
import numpy as np
from tensorflow.keras import backend as K
from tensorflow.keras.layers import Layer
from tensorflow.keras.utils import get_custom_objects
import typing
```
Type definitions:
Input Types: Any, Any, int, int, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: sg.Window, subprocess.Popen
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: sg.Window, v2: subprocess.Popen):
v1.write_event_value('-THREAD-', (v2, '===THEAD STARTING==='))
v1.write_event_value('-THREAD-', (v2,... |
Imports:
```python
import decimal
import typing
```
Type definitions:
Input Types: str, str, Optional[str], Optional[Dict[str, Any]], Optional[Union[Dict[str, Any], Sequence[Any]]], bool
Output Type: Tuple[int, Optional[Union[Dict[str, Any], List[Any]]]]
Dependencies:
```python
def v0(v1, v2, v3, v4, v5):
v6 = ''
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.stream_id = None
self._delete_alerts_by_id(self.alert_widgets.keys())
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Tuple[int, list]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> Tuple[int, list]:
v2 = open(v1, 'r').read().splitlines()
return (int(v2[0]), v2[1].split(','))
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self._version = self._version.clear(post=True)
return
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if len(self.indent) < 4:
raise SyntaxError('Unexpected end of block.')
self.indent = self.indent[:-4]
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'Cyclist', int, int, bool
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'Cyclist', v2: int, v3: int, v4: bool=False) -> int:
v5 = self.sections[v3].min_speed
v2 = v2 if not v4 or v5 is None else max(v2,... |
Imports:
```python
import typing
```
Type definitions:
Input Types: list, int, int
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list, v2: int, v3: int) -> str:
v4 = ''
v5 = [(v2 - 1, v3 - 1), (v2 - 1, v3), (v2 - 1, v3 + 1), (v2, v3 - 1), (v2, v3), (v2, v3 + 1), (v2 + 1, v3 -... |
Imports:
```python
import typing
```
Type definitions:
Input Types: pd.DataFrame
Output Type: Tuple[np.ndarray, List[np.ndarray]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pd.DataFrame) -> Tuple[np.ndarray, List[np.ndarray]]:
v2 = v1.groupby('groups').mean()['log2_bootstrap_CS_mean'].values
... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str
Output Type: Tuple[List[str], Optional[str], Optional[str]]
Dependencies:
```python
def v0(v1):
if v1 is None or v1.strip() == '':
return DELIM
if v1[0] != DELIM:
v1 = DELIM + v1
if v1[-1] != DELIM:
v1... |
Imports:
```python
import os
import tempfile
import typing
```
Type definitions:
Input Types: str, str, str, float
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str, v3: str, v4: float):
with tempfile.NamedTemporaryFile(mode='w+t', dir='.') as v5:
v5.write(... |
Imports:
```python
from datetime import datetime
from datetime import timedelta
from datetime import timezone
import numpy as np
import typing
```
Type definitions:
Input Types: datetime, float, bool
Output Type: Tuple[np.ndarray, np.ndarray]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dateti... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[List[int]]
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[List[int]]) -> int:
v2 = sorted({x for (v3, v4) in v1})
return max((v2[i] - v2[i - 1] for v5 in range(1, len(v2))))
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if 'bin' in self.__ls_unformatted():
self.rmdir('bin')
self.mkdir('bin')
``` |
Imports:
```python
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.cluster import KMeans
import torch as th
import typing
```
Type definitions:
Input Types: int, bool, bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int=0, v2: bool=True, ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict, str, int
Output Type: list
Dependencies:
```python
def v0(v1: dict) -> tuple:
v2 = sorted([(float(mass), float(intensity)) for (v3, v4) in v1.items() if v3 not in NON_MASS_KEYS], key=lambda x: x[1])
return (float(v1['retention_time']),) ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2) -> bool:
if v2.name in ['MissileTurret', 'SporeCrawler', 'SpineCrawler', 'PhotonCannon', 'Bunker']:
return True
v3 = self.towardsDirec... |
Imports:
```python
import torch
import typing
```
Type definitions:
Input Types: torch.Tensor
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: torch.Tensor):
v2 = torch.ones_like(v1, dtype=torch.int)
v2[v1 <= 1 / 3] = 0
v2[v1 >= 5 / 3] = 2
return v2
``` |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1):
self.val = v1
self.left = None
self.right = None
```
Input Types: v0, int
Output Type: int
Dependencies:
```python
def v2(v3: v0, v4):
if v3:
v2(v3.right, v4)
v4.append(v3.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Tensor, Tensor, bool
Output Type: Union[Tuple, Tensor]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Tensor, v2: Tensor=None, v3: bool=False) -> Union[Tuple, Tensor]:
(v4, v5, v6) = self._network(v1)
if v3:
retu... |
Imports:
```python
from .dataclasses import Station, TidalEvent, TidalHeight
import typing
```
Type definitions:
Input Types: str
Output Type: Station
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: str) -> Station:
v2 = self._base_url + '/' + v1
v3 = await self._async_get_data(v2)
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if self._change_set_arn is None:
return
v1 = self._session.client('cloudformation')
if self.change_type == 'CREATE':
v1.delete_st... |
Imports:
```python
from random import choice, random, shuffle
import typing
```
Type definitions:
```python
class v0(object):
v1: List[str] = ['unconnected', 'fs_neat_nohidden', 'fs_neat', 'fs_neat_hidden', 'full_nodirect', 'full', 'full_direct', 'partial_nodirect', 'partial', 'partial_direct']
def __init__(se... |
Imports:
```python
import numpy
import logging
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bool:
v1 = numpy.sum(self.board == numpy.array(None))
logging.debug(f'{v1} / {self.boardlen ** 2} board positions empty')
r... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(namedtuple('Location', ['direction', 'degrees', 'minutes', 'seconds'])):
def v1(self):
return '%d°%d"%d\'%s' % (self.degrees, self.minutes, self.seconds, self.direction)
```
Input Types: datetime, Any, Any
Output Type: Any
Dependenci... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bytes, dict, int, int, str, str
Output Type: dict
Dependencies:
```python
def v0(v1: bytes, v2: int, v3: int):
v4 = 0
v5 = (1 << 8 - v2) - 1
v6 = 255 ^ v5
v7 = []
while v4 < (v3 - 1) // 8 + 1:
v8 = (v1[v4] & v5) << v2
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: Tuple[Optional[str], Optional[str]]
Dependencies:
```python
def v0(v1: dict, v2: str) -> Optional[Union[str, List[str]]]:
for (v3, v4) in v1.items():
if isinstance(v4, dict):
v5 = v0(v4, v2)
if v5 ... |
Imports:
```python
import json
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str=DEFAULT_MSG_ENCODE_TYPE):
v2 = self.socket.recv(4096)
if v2 is None:
return None
v3 = json.loads(v2.decode(v1))
return v... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self._row_idx += 1
if self._row_idx == len(self._plate_type.rows()):
self._row_idx = 0
self._col_idx += 1
if self._col_idx ==... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int, int
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int, v2: int) -> int:
if v1 == 0:
return 0
v3 = self.gf_mult(v1, v1, v2)
v3 = self.gf_mult(v1, v3, v2)
v3 = self.gf_mult(v3, v3, v2... |
Imports:
```python
import torch
from torch.utils.data import DataLoader
from torch.utils.data.sampler import BatchSampler
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.state.seed = int(torch.randint(0, int(1000000... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[str, Any], List[Tuple[str, ...]], Optional[str]
Output Type: List[Tuple[str, ...]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Dict[str, Any], v2: List[Tuple[str, ...]], v3: Optional[str]=None) -> List[Tuple[str, ...]]:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: pd.DataFrame
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pd.DataFrame):
v2 = v1.fillna(v1.mean())
return v2
``` |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: str, str
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str) -> bool:
if v1 not in self.vdict or v2 not in self.vdict:
return False
v3 = self.graph.shortest_paths(sel... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str):
self.execute(v1)
self.commit()
self.populate_tables_dict()
``` |
Imports:
```python
import logging
import typing
```
Type definitions:
Input Types: 'tasks.ClassyTask'
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'tasks.ClassyTask') -> None:
if len(v1.config.MODEL.TEMP_FROZEN_PARAMS_ITER_MAP) == 0:
return
v2 = {}
for v3 ... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(object):
def __init__(self, v1=None, v2=None):
self.item = v1
self.next = v2
def v3(self, v4):
if v4 == None:
return False
return self.item == v4.item
```
Input Types: v0, int, v0
Output Type:... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Exception
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Exception):
self.stop(exc=v1)
self.exceptions.append(v1)
``` |
Imports:
```python
import inspect
import typing
```
Type definitions:
Input Types: Any, Any, Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1, v2, v3) -> None:
v4 = inspect.signature(v1)
v5 = list(v4.parameters.keys())[v2 - 1]
v6 = v4.parameters[v5]
if v6.annotation ... |
Imports:
```python
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, OutOfBoundsDatetime, Timestamp
from pandas._libs.tslibs.timezones import tz_compare
... |
Imports:
```python
import math
import typing
```
Type definitions:
Input Types: float, float, float
Output Type: float
Dependencies:
```python
def v0(v1: float, v2: float) -> float:
if v2 < 0:
raise ValueError('Partial pressure of water vapor in moist air cannot be negative')
v3 = v2 / GetSatVapPres(v1... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
if self.shuffle_type == 'per_mini_epoch' or (self.shuffle_type == 'per_epoch' and self.state_i == 0):
if self.data_len >= self... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[int], int
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[int], v2: int) -> None:
(v3, v2) = (len(v1), v2 % len(v1))
v4 = v5 = 0
while v5 < v3:
(v6, v7) = (v4, v1[v4])
while... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, [dict]
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: [dict]) -> dict:
v3 = v1[:-5]
for v4 in v2:
if v3 in v4.get('timestamp'):
return v4
return None
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Mapping[str, str]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Mapping[str, str]):
assert v1 == {'service_name': 'my-service'}
return v1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[str]
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[str]) -> str:
if not v1:
return ''
if len(v1) == 1:
return v1[0]
v2 = []
v3 = len(v1)
for v4 in zip(*v1):
print... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'Flow', bool
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'Flow', v2: bool=None) -> None:
for v3 in v1.tasks:
if v3 not in self.tasks:
self.add_task(v3)
for v4 in v1.edges:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bool:
if self.num_cols != self.num_rows:
return False
else:
v1 = True
for v2 in range(self.num_rows):
for v3 in range(s... |
Imports:
```python
import typing
```
Type definitions:
Input Types: 'Dihedron'
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: 'Dihedron'):
v2 = 1.53363
if hasattr(self, 'scale'):
v2 *= self.scale
(v3, v4, v5, v6) = (self.rak('N'), self.rak('CA'), self.rak('C'... |
Imports:
```python
import os
import json
import typing
```
Type definitions:
Input Types: Optional[str]
Output Type: dict
Dependencies:
```python
def v0(v1: Optional[str]=None) -> str:
v2 = os.path.dirname(__file__)
if v1:
v2 = v1
return os.path.join(v2, 'version.json')
```
Function Name: v3
Functi... |
Imports:
```python
import os
import glob
import typing
```
Type definitions:
Input Types: str
Output Type: List[Dict[str, Union[str, List[Dict]]]]
Dependencies:
```python
def v0(v1) -> int:
for (v2, v3) in enumerate(sentences):
if v1[0] >= v3['span'][0] and v1[1] <= v3['span'][1]:
return (v2, v... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
self.check('x = y = z = 1 # type: int', 'x = y = z = 1 # type: int')
self.check('x, y, z = [], [], [] # type: (List[int], List[int], List[str])', 'x... |
Imports:
```python
import torch
from torch.nn import Module
import typing
```
Type definitions:
Input Types:
Output Type: Module
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Module:
self.__update_properties(dtype=torch.double)
return super().double()
``` |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1):
self.number = v1 + 1
self.index = v1
self.reporting = None
self.connection = None
self.address = None
self.queue = Queue(maxsize=2)
self.host = ''
self.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float, Any
Output Type: dict
Dependencies:
```python
def v0() -> dict:
return {'count': 0, 'mean': 0, 'M2': 0}
```
Function Name: v1
Function:
```python
def v1(v2: float, v3=10) -> dict:
assert 0 <= v2 <= 1
v4 = v0()
v4.update({'rho': ... |
Imports:
```python
from collections import defaultdict
import numpy as np
import typing
```
Type definitions:
Input Types:
Output Type: List[Tuple[int, int, int, int]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> List[Tuple[int, int, int, int]]:
self.log.info('start get_free_faces')
v1... |
Imports:
```python
import typing
```
Type definitions:
Input Types: int
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: int) -> int:
try:
if self.i[v1] == 're' and self.i[v1 - 1] == 're':
return 10
elif self.i[v1] == 're' and self.i[v1 - 1] == 'o':... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = List[Tuple[int, int]]
```
Input Types: List[str]
Output Type: v0
Dependencies:
Function Name: v1
Function:
```python
def v1(v2: List[str]) -> v0:
v3 = []
for v4 in v2:
v5 = v4[0]
v6 = int(v4[1:])
if v5 == 'R':
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float, float, float, float, Tuple[int, int]
Output Type: Tuple[int, int]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: float, v2: float, v3: float, v4: float, v5: Tuple[int, int]) -> Tuple[int, int]:
v6 = ((v4 - v3) / v5[0], (v4 ... |
Imports:
```python
import glob
import re
import os
import typing
```
Type definitions:
Input Types: List[str]
Output Type: List[Dict[str, str]]
Dependencies:
```python
def v0(v1: str):
if not v1:
return ''
v2 = re.sub('^.', v1[0].upper(), v1)
v2 = re.sub('([A-Z]+)([A-Z])([a-z0-9])', '\\1 \\2\\3', v... |
Imports:
```python
import numpy as np
from scipy.ndimage import gaussian_filter, convolve
import typing
```
Type definitions:
Input Types: np.ndarray, float, float, str, str, float
Output Type: [np.ndarray, np.ndarray, np.ndarray]
Dependencies:
```python
def v0(v1: np.ndarray, v2: str='gradient') -> [np.ndarray, np.nd... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[int, int], Callable[[], int], Callable[[int], None]
Output Type: None
Dependencies:
```python
def v0(v1: int, v2: int) -> int:
v3 = v1 // 10 ** (v2 + 1) % 10
if v3 == 0:
return prog[prog[pc + v2]]
elif v3 == 1:
return ... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray, float
Output Type: float
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray, v2: np.ndarray, v3: float) -> float:
v4 = 2.0 * np.pi * v3 * v1
return np.arctan2(np.sum(v2 *... |
Imports:
```python
import numpy as np
from sklearn.metrics import explained_variance_score, mean_squared_error
import typing
```
Type definitions:
Input Types: List[float], List[float]
Output Type: Dict
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[float], v2: List[float]) -> Dict:
v3 = dict... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(Model):
v1: str
v2: str
v3: List[ModelsRule]
v4: str
v5: int
v6: str
v7: str
def v8(self, v9: str) -> v0:
self.configuration_code = v9
return self
def v10(self, v11: str) -> v0:
self.d... |
Imports:
```python
import pandas as pd
import requests
import typing
```
Type definitions:
Input Types: str
Output Type: pd.DataFrame
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str='2019') -> pd.DataFrame:
v2 = 'http://fund.eastmoney.com/Company/home/HistoryScaleTable'
v3 = {'year': v1}
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Sequence[float], 'Lattice'
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Sequence[float], v2: 'Lattice'):
for (v3, v4) in zip(self.free_parameters, v1):
for v5 in v2.search(v3.element):
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: ArgumentParser
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: ArgumentParser) -> None:
super().add_parser_arguments(v1)
v1.add_argument('--nested', help='Will report data in the newer nested format, rat... |
Imports:
```python
from urllib.parse import unquote_plus
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> Any:
v1 = unquote_plus(v1)
if v1 == 'true':
return True
if v1 == 'false':
return False
t... |
Imports:
```python
import typing
```
Type definitions:
```python
v0 = TypeVar('T', bound='SdkParser')
```
Input Types: str
Output Type: str
Dependencies:
Function Name: v1
Function:
```python
def v1(self: Type[v0], v2: str) -> str:
if v2 in self.value_tranlation_table:
return self.value_tranlation_table[v2... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str=DatabaseUtils.sqlitedb_dump) -> None:
with open(v1, 'w') as v2:
for v3 in self._connection.iterdump():
v3 = v3.encode('utf8')
... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, float, np.ndarray, float
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray, v2: float, v3: np.ndarray, v4: float) -> None:
v5 = self._calculate_sigma_points(v4)
v6... |
Imports:
```python
from collections import defaultdict
import numpy as np
import typing
```
Type definitions:
Input Types: list or np.ndarray
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: list or np.ndarray):
v1 = np.array(v1).flatten()
v2 = defaultdict(int)
v3 = list(np.... |
Imports:
```python
from selenium.common.exceptions import StaleElementReferenceException, ElementClickInterceptedException, TimeoutException, NoAlertPresentException, NoSuchElementException
from selenium.webdriver.chrome.webdriver import WebDriver
from selenium.webdriver.remote.webelement import WebElement
from seleniu... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[List[int]], List[int]
Output Type: List[List[int]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[List[int]], v2: List[int]) -> List[List[int]]:
if not v1:
return [v2]
v3 = False
v4 = []
for v5 ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[int]
Output Type: List[List[int]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[int]) -> List[List[int]]:
v2 = []
v1.sort()
v3 = len(v1)
for v4 in range(v3):
if v4 > 0 and v1[v4] == v1[v4 - 1]:... |
Imports:
```python
from datetime import datetime
import typing
```
Type definitions:
Input Types: trdb2py.trading2_pb2.PNLAssetData, Any, bool, str, Any
Output Type: dict
Dependencies:
```python
def v0(v1, v2: trdb2py.trading2_pb2.PNLAssetData, v3: bool=True) -> int:
if v3:
for v4 in range(0, len(v2.values... |
Imports:
```python
import numpy as np
from pandas._config import get_option
from pandas._libs import lib
import pandas._libs.missing as libmissing
from pandas._libs.tslibs import NaT, iNaT
from pandas._typing import ArrayLike, DtypeObj
from pandas.core.dtypes.common import DT64NS_DTYPE, TD64NS_DTYPE, ensure_object, is_... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Sequence['jina_pb2.Document']
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Sequence['jina_pb2.Document'], *v2, **v3):
for v4 in v1:
if getattr(v4, self.target) and (not self.override):
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, Any, Any, Any
Output Type: Any
Dependencies:
```python
def v0(v1=POSITION.FIRST, v2=None):
v3 = {}
if v1 == POSITION.AFTER_MEDIA:
v3 = {'position': v1, 'relativeMediaItemId': v2}
elif v1 == POSITION.AFTER_ENRICHMENT:
v... |
Imports:
```python
import cv2
import typing
```
Type definitions:
Input Types: str, int, int, int
Output Type: Any
Dependencies:
```python
def v0(v1) -> str:
v2 = ('⠀', '⠁', '⠂', '⠃', '⠄', '⠅', '⠆', '⠇', '⠈', '⠉', '⠊', '⠋', '⠌', '⠍', '⠎', '⠏', '⠐', '⠑', '⠒', '⠓', '⠔', '⠕', '⠖', '⠗', '⠘', '⠙', '⠚', '⠛', '⠜', '⠝', '... |
Imports:
```python
import tensorflow as tf
import typing
```
Type definitions:
Input Types: tf.Tensor, Dict[str, tf.io.FixedLenFeature]
Output Type: Dict[str, Tuple[tf.Tensor, ...]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: tf.Tensor, v2: Dict[str, tf.io.FixedLenFeature], **v3: Dict[str, List[int... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.