text stringlengths 190 325k |
|---|
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str, str, int, str
Output Type: Dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str=None, v3: str=None, v4: int=DEFAULT_PAGE_SIZE, v5: str=None) -> Dict:
v6 = {'$orderby': v2} if v2 else {}
if v3:
... |
Imports:
```python
import numpy as np
from pandas._libs.tslibs import OutOfBoundsDatetime, Timestamp
from pandas.tseries.offsets import DateOffset, Tick, generate_range
import typing
```
Type definitions:
Input Types: Timestamp, Timestamp, int, DateOffset
Output Type: Tuple[np.ndarray, str]
Dependencies:
```python
def... |
Imports:
```python
import typing
```
Type definitions:
Input Types: json_rpc.JsonRPCRequest
Output Type: Union[json_rpc.JsonRPCResponse, json_rpc.JsonRPCError]
Dependencies:
Function Name: v0
Function:
```python
async def v0(self, v1: json_rpc.JsonRPCRequest) -> Union[json_rpc.JsonRPCResponse, json_rpc.JsonRPCError]:... |
Imports:
```python
import typing
```
Type definitions:
Input Types: classfile.MemberInfo
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: classfile.MemberInfo):
self.accessFlags = v1.AccessFlags
self.name = v1.Name
self.descriptor = v1.Descriptor
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: list, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list, v2: str):
for v3 in range(len(self.syllabus_dict_list)):
v4 = self.syllabus_dict_list[v3]
if v4['kougi'] == v1['kougi'] and v4['... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: float):
v1 = float(v1)
self.__balance += v1
print(f'Erfolgreich {v1} eingezahlt!')
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: bytes
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bytes) -> int:
if self.debug:
print('-> ' + str(v1))
return self.connection.write(v1)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: pd.DataFrame, float, float, int, int
Output Type: pd.DataFrame
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: pd.DataFrame, v2: float=0.5, v3: float=0.5, v4: int=50, v5: int=200) -> pd.DataFrame:
v6 = v1['price'].rolling(v4).mean(... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Dict:
v1 = {}
if hasattr(self, 'session_id') and self.session_id is not None:
v1['session_id'] = self.session_id
return v1
``` |
Imports:
```python
import pandas as pd
import geopandas as gpd
from scipy.interpolate import interp1d
from scipy.spatial import distance_matrix
import typing
```
Type definitions:
Input Types: list, str, list, Any, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: list=None, v2... |
Imports:
```python
import typing
```
Type definitions:
```python
@dataclass
class v0:
v1: str
v2: str
v3: str
v4: UUID = uuid4()
v5: Dict = field(default_factory=dict)
v6: Union[List, Dict] = field(default_factory=dict)
v7: Dict = field(default_factory=dict)
v8: Dict = field(default_fact... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: dict
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> dict:
v1 = self.lwc_source.categorize_bits.quality_bits
return {key: v1[key] for v2 in ('radar', 'lidar')}
``` |
Imports:
```python
import numpy
import typing
```
Type definitions:
Input Types: numpy.ndarray, Optional[int], bool, Optional[int]
Output Type: numpy.ndarray
Dependencies:
```python
@njit('float32[:,:,:], float32[:,:,:], uint32[:,:], uint32', nogil=True)
def v0(v1: numpy.ndarray, v2: numpy.ndarray, v3: numpy.ndarray, ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[int]
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[int]) -> int:
v2 = {v1[0]: False}
for v3 in range(1, len(v1)):
if v1[v3] in v2:
v2[v1[v3]] = True
else:
... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: int, v2: StructuredStatement, v3: Optional[str]=None):
self.statement = v0.sanitize_goal_statement(v2, v3)
self.goal_id = v1
self.claim_label = v3
def v4(self) -> v0:
return v0(sel... |
Imports:
```python
import typing
```
Type definitions:
Input Types: bool
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: bool=True):
v2 = []
for v3 in self.image_dir.rglob('**/*'):
if v3.suffix.lower() in ('.png', '.jpg', '.jpeg'):
v2.append(v3)
v4... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: List[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> List[str]:
self._maybe_refresh()
if self._tickers is None:
self._fetch_info()
assert self._tickers is not None
return list(self._ticke... |
Imports:
```python
from PIL import Image, ImageDraw
import typing
```
Type definitions:
Input Types: Image.Image, int, int
Output Type: Image.Image
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Image.Image, v2: int, v3: int) -> Image.Image:
v4 = ImageDraw.Draw(v1)
(v5, v6) = v1.size
v4.li... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray) -> np.ndarray:
v2 = len(self.priority_queue)
self.beta = self.compute_beta(self.n_get_sample_called)
v3... |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: dict) -> None:
super().set_state(v1)
self.random_search.set_state(v1['random_search'])
self.lineages = v1['lineages']
self._queue = v1['queue'... |
Imports:
```python
import typing
```
Type definitions:
Input Types: float
Output Type: Tuple[int, float]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: float) -> Tuple[int, float]:
self.update_layers()
for (v2, v3) in enumerate(self[:-1]):
if v3.depth <= v1 < v3.depth_base:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: tuple[str, bool]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> tuple[str, bool]:
self._log.debug('Video cache: %s', self._video_file_cache)
try:
return (self._video_file_cache[v1], True)... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Dict[str, Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Dict[str, Any]:
v1 = []
for v2 in self.buckets:
v3 = v2.to_dict()
v1.append(v3)
v4 = self.name
v5: Dict[str, Any] = {}
... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, int, bool, bool
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray, v2: int=1, v3: bool=True, v4: bool=True) -> np.ndarray:
if v4 and v2 >= np.unique(v1).size:
... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray):
(v2, v3) = v1.shape
self.input = v1
if self.kernel_size > v2 or self.kernel_size > v3:
raise Arithmet... |
Imports:
```python
from pandas._libs import algos, hashtable, lib
from pandas._libs.hashtable import unique_label_indices
from pandas._typing import IndexKeyFunc, Shape, npt
from pandas.core.dtypes.common import ensure_int64, ensure_platform_int, is_extension_array_dtype
from pandas.core.dtypes.generic import ABCMultiI... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Tuple[int, ...]
Output Type: 'FockBasis'
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Tuple[int, ...]) -> 'FockBasis':
v2 = [0] * self.d
for v3 in v1:
v2[v3] = 1
return self + v2
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Tuple[float, int]
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Tuple[float, int]=None) -> bool:
if v1 is None:
v1 = self.state
return v1[0] <= self.MIN_ENERGY or v1[1] >= self.MAX_SETS
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str) -> str:
v2 = {'A': 'A', 'C': 'C', 'G': 'G', 'T': 'U'}
return ''.join((v2[t] for v3 in v1.upper()))
``` |
Imports:
```python
import itertools as it
from collections import defaultdict
import typing
```
Type definitions:
```python
v0 = Dict[str, int]
```
```python
v1 = Tuple[List[str], List[str]]
```
Input Types: IO, bool
Output Type: Any
Dependencies:
```python
def v2(v3: List[str], v4: Dict[str, str]) -> Optional[Dict[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:
v2 = self.ac.q1(v1)
v3 = self.ac.q2(v1)
return (v2, v3)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: AsyncGenerator[bytes, None]
Dependencies:
Function Name: v0
Function:
```python
async def v0() -> AsyncGenerator[bytes, None]:
for v1 in range(1024):
yield (b'123456789abcdef\n' * 64)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: dict
Output Type: list
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: dict) -> list:
v2 = tuple(v1['Functional'].keys())
v3 = ['_'.join((v1['Summary']['Subject ID'], 'ses-' + b.split('session ')[1].split(',')[0], 'task-' + b.s... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: Tuple[None, List[Tuple[int]]]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2) -> Tuple[None, List[Tuple[int]]]:
if len(v1) > 0:
raise ValueError(f'{self.__class__.__name__} does not accept co... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(Enum):
v1 = 'r'
v2 = 'rb'
v3 = 'r'
v4 = 'rb'
v5 = 'a'
v6 = 'a'
v7 = 'w'
v8 = 'wb'
v9 = 'w'
v10 = 'wb'
v11 = 'r+'
v12 = 'rb+'
v13 = 'r+'
v14 = 'rb+'
v15 = 'auto'
```
Input Types: str, v0,... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray, v2: np.ndarray) -> bool:
v3 = v1[:, 0:1]
v4 = v2[0:1, :]
return np.nanmax(np.abs(v1 - v3)) == 0 and np.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, List[str]
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: List[str]) -> str:
for v3 in v2:
v4 = v3[0]
if v4 == 'x':
(v5, v6) = [int(x) for v7 in v3[1:].split('/')]
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: List[int]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> List[int]:
if len(self.actions) == 0:
return []
v1 = self.get_selected_actions()
if len(v1) == 0:
return []
v2 = min((a.min_fr... |
Imports:
```python
import logging
import sys
import typing
```
Type definitions:
Input Types: Optional[bool], Optional[PathLike], Union[int, str]
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Optional[bool]=True, v2: Optional[PathLike]=None, v3: Union[int, str]='INFO') -> None:
... |
Imports:
```python
import contextlib
import typing
```
Type definitions:
Input Types: asyncio.subprocess.Process
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
async def v0(v1: asyncio.subprocess.Process) -> None:
with contextlib.suppress(ProcessLookupError):
v1.kill()
await v1.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Dict[str, Any]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Dict[str, Any]):
self._on_execution = None
self._result = dict()
v1 = self._get_parameters_data(v1)
if self.task_descriptor.type_task... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, List[nodes.Argument]
Output Type: List[nodes.Argument]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: List[nodes.Argument]) -> List[nodes.Argument]:
if v1 in ('__init_subclass__', '__class_getitem__'):
if v2[... |
Imports:
```python
import numpy as np
from numpy.linalg import solve
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: car.CarParams):
"""
Args:
CP: Car Parameters
"""
self.m = v1.mass
self.j = v1.rotationalInertia
self.l = v1.wheelbase
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
async def v0(v1: str):
v2: aio_pika.Queue = await self.channel.get_queue(v1, ensure=True)
async with v2.iterator() as v3:
async for v4 in v3:
yield v... |
Imports:
```python
import pandas as pd
from pandas import DataFrame
import typing
```
Type definitions:
Input Types: Any, Any
Output Type: DataFrame
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1='value', v2='1min') -> DataFrame:
if self.strategies:
v3 = []
for v4 in self.stra... |
Imports:
```python
import asyncio
import typing
```
Type definitions:
Input Types: int, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
async def v0(v1: int, v2: int):
print(f'function started')
await asyncio.sleep(5)
print(f'function finished')
return v1 + v2
``` |
Imports:
```python
import torch
import typing
```
Type definitions:
Input Types: torch.Tensor, torch.Tensor
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: torch.Tensor=None, v2: torch.Tensor=None) -> None:
if isinstance(v1, float):
v1 = v1 * torch.randn(self.size, d... |
Imports:
```python
import typing
```
Type definitions:
Input Types: aiohttp.ClientSession, str, str
Output Type: bytes
Dependencies:
Function Name: v0
Function:
```python
async def v0(v1: aiohttp.ClientSession, v2: str, v3: str) -> bytes:
v4 = f'{v2}/{v3}/{v3}.gif'.lower()
async with v1.get(v4) as v5:
... |
Imports:
```python
import ctypes
import ctypes.util
import typing
```
Type definitions:
Input Types: str, object, int
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: object, v3: int):
if v1 == 'mkl':
v2.mkl_set_num_threads(ctypes.byref(ctypes.c_int(v3)))
elif v... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
v1 = None
v2 = ''
v3 = ''
v4 = ''
v5 = 0
v6 = 0
v7 = ''
v8 = ''
v9 = False
v10 = False
def __init__(self, v11: List[Tuple[str, int]], v12: str, v13: str, v14: str, v15: int, v16: int, v17: str, v18: s... |
Imports:
```python
import argparse
import os
import typing
```
Type definitions:
Input Types: Any
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> str:
if os.path.isdir(v1):
return v1
else:
raise argparse.ArgumentTypeError(f'readable_dir:{v1} is not a valid pa... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: Tuple[int, int]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> Tuple[int, int]:
if self._warmup_param in self.state:
(v1, v2) = self.state[self._warmup_param]['warmup'].tolist()
else:
v1 = 0
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str, str
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str) -> int:
v3 = v1.split(' ')
v4 = 0
v5 = frozenset(v2)
for v6 in v3:
if v6 and len(set(v6) & v5) < 1:
v4 +=... |
Imports:
```python
import re
import warnings
from multiprocessing import cpu_count
import spacy
from nltk.stem import WordNetLemmatizer
from spacy.lang.en import English
from tqdm import tqdm
import typing
```
Type definitions:
Input Types: List[str], str, Union[str, List[str]], bool
Output Type: List[str]
Dependencie... |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[Tensor], int, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[Tensor], v2: int, v3: str):
(v4, v5) = v1
(v6, v7, v8) = self._calculate_edl_factors(v4)
v9 = self.loss_function(v6, v5)
... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: str, List[str]
Output Type: str
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: str, v2: List[str]=None) -> str:
if not v1:
return ''
v3: bool = v1[0] == '_'
v4: bool = v1[-1] == '_'
if v1.isupper():
... |
Imports:
```python
import json
from rdkit import Chem
import typing
```
Type definitions:
Input Types: List[Chem.rdchem.Mol], str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: List[Chem.rdchem.Mol], v2: str='geometries.json') -> None:
v3 = [Chem.MolToPDBBlock(mol) for v4 in v1]
... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: Dict[str, int]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, **v2) -> Dict[str, int]:
v3 = self._execute_callable_magic('estimate', v1, **v2)
return {operation_name: int(count) for (v4, v5) in v3.items(... |
Imports:
```python
import typing
```
Type definitions:
Input Types: rclpy.task.Future
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: rclpy.task.Future):
self.result_message = v1.result()
self.result_status = v1.result().status
self.result_status_string = self.status_... |
Imports:
```python
import json
import typing
```
Type definitions:
```python
v0 = Dict[str, str]
```
Input Types:
Output Type: Optional[v0]
Dependencies:
Function Name: v1
Function:
```python
def v1(self) -> Optional[v0]:
v2: Optional[v0] = None
v3 = self.get_binaries_file_path()
if v3.exists():
w... |
Imports:
```python
import torch
import torch.nn.functional as F
from torch.autograd import Function
import typing
```
Type definitions:
Input Types: torch.Tensor
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: torch.Tensor) -> torch.Tensor:
if not isinstance(v1, torch.Tens... |
Imports:
```python
import requests
import typing
```
Type definitions:
Input Types: List, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List, v2: str='RandomRoom'):
v3 = requests.post(f'{self.URL}/room/create', json={'users': ','.join(v1), 'roomName': v2, 'key': self.us... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: str):
self.text = v1
self.pos = 0
@property
def v2(self):
if self.pos == len(self.text):
return None
return self.text[self.pos]
def v3(self):
self.pos ... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: bool
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> bool:
v1 = self.pongRequired
self.pongRequired = False
return v1
``` |
Imports:
```python
from torch import Tensor
from torch.utils.data import DataLoader, IterableDataset, Dataset
import typing
```
Type definitions:
Input Types: Dataset, int
Output Type: DataLoader
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Dataset, v2: int=64) -> DataLoader:
v3 = DataLoader(v1,... |
Imports:
```python
from datetime import datetime, timezone
import typing
```
Type definitions:
Input Types:
Output Type: Optional[datetime]
Dependencies:
```python
def v0(v1: str):
v2 = v1[:-1]
return datetime.strptime(v2, _SQLITE_TS_FORMAT)
```
Function Name: v3
Function:
```python
def v3(self) -> Optional[d... |
Imports:
```python
import typing
```
Type definitions:
Input Types: BaseException, Any
Output Type: str
Dependencies:
```python
def v0(v1: BaseException, v2: Any) -> Dict[str, Any]:
v3 = hash_stacks.current.hash_reason
v4 = hash_stacks.current.hash_source
v5 = type_util.get_fqn_type(v2)
if v4 is None o... |
Imports:
```python
import difflib
import typing
```
Type definitions:
Input Types: str, str, str
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str, v3: str) -> None:
self.source_config = v1
self.candidate_config = v2
self.device_diff = v3
v4 = difflib.... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Iterable[int], Dict[int, Dict[int, int]], bool
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Iterable[int], v2: Dict[int, Dict[int, int]], v3: bool) -> int:
v4 = 0
v5 = 0
v6 = list(v1)
while v6:
... |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0() -> None:
import budget.load.balances
import budget.load.transactions
import budget.analyze
assert True
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any, Any, connection.Connection, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1, v2, v3: connection.Connection, v4):
v5 = list()
for v6 in range(v4):
(v7, v8) = self._work(v1, v2)
v5.a... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1) -> None:
for v2 in v1.statements:
self.gen_stmt(v2)
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[Callable]
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: List[Callable]):
self._middlewares += v1
self._build_middlewares_chain()
``` |
Imports:
```python
import curses
import curses.ascii
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
curses.nocbreak()
self.stdscr.keypad(False)
curses.echo()
curses.endwin()
self.loop.stop()
``` |
Imports:
```python
import multiprocessing as mp
import typing
```
Type definitions:
Input Types: int, int
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int, v2: int) -> None:
del signum, frame
global interrupted
v3 = True
v4 = mp.current_process().name
if v4 is n... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: deque[HanoiTowerDisk]=deque()) -> None:
self.__disks: deque[HanoiTowerDisk] = v1
assert self.__check_order(), 'disks order error'
self.__hash: int = 0
self.__calc_hash()
return
... |
Imports:
```python
import numpy as np
from numpy.linalg import norm
import typing
```
Type definitions:
Input Types: np.ndarray, np.ndarray, np.ndarray, np.ndarray, float
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: np.ndarray, v2: np.ndarray, v3: np.ndarray, v4: np.ndarray, ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: cir.FieldConversion, t.Optional[t.Dict[str, t.Any]]
Output Type: t.Dict[str, t.Any]
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: cir.FieldConversion, v2: t.Optional[t.Dict[str, t.Any]]=None) -> t.Dict[str, t.Any]:
v3 = {'t... |
Imports:
```python
import torch
from torch import Tensor
import typing
```
Type definitions:
Input Types: torch.Tensor, Any, Any, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: torch.Tensor, v2=None, v3=None, v4=True):
v5: Optional[Tensor] = None
if v3 is None:
v5 ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: Tuple[int, int, int]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> Tuple[int, int, int]:
v2 = max(v1)
v3 = min(v1)
return (v3, v2, v2 - v3)
``` |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str, str
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str, v2: str=_SGE.STD_TOPOL):
with open(os.path.join(v1, v2), 'r') as v3:
self.top_lines = v3.readlines()
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: List[float], float
Output Type: Optional[float]
Dependencies:
```python
def v0(v1):
return 0 if not v1 else sum(v1) / len(v1)
```
Function Name: v2
Function:
```python
def v2(v3: List[float], v4: float=1) -> Optional[float]:
if not v3:
... |
Imports:
```python
import re
import typing
```
Type definitions:
Input Types: dict
Output Type: Any
Dependencies:
```python
def v0(v1: str):
return re.match('^[a-z]-', v1, re.I)
```
```python
def v2(v3: str):
return re.match('^[a-z]', v3, re.I)
```
```python
def v4(v5: list, v6: callable):
for v7 in v5:
... |
Imports:
```python
import random
import numpy as np
import typing
```
Type definitions:
```python
class v0:
def __init__(self, v1: Union[List[float], List[int]], v2: Union[List[int], List[float]], v3: Union[List[int], List[float]], v4: float, v5: int, v6: float=0, v7: float=0):
assert len(v1) == len(v2), '... |
Imports:
```python
import typing
```
Type definitions:
Input Types: sqlite3.Cursor, str, Optional[tuple[Any, ...]]
Output Type: sqlite3.Cursor
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: sqlite3.Cursor, v2: str, v3: Optional[tuple[Any, ...]]=None) -> sqlite3.Cursor:
if v3 is None:
v4 = ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: int
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> int:
v1 = sorted(set([int(c) for v2 in v1 if v2.isdigit()]), reverse=True)
if v1 and len(v1) >= 2:
return v1[1]
return -1
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: Any
Dependencies:
```python
def v0(v1: str):
v2 = {}
for v3 in v1.split('&'):
v4 = str(v3).split('=', 1)
if len(v4) < 2:
continue
(v5, v6) = v4
v2[v5] = v6
return v2
```
Function... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: typing.Tuple[typing.Union[str, None]]
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> typing.Tuple[typing.Union[str, None]]:
v2 = v1.find_all('tr')[0]
v3 = v2.text.strip()
v4 = v3.split(' - ')
return... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: List
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1='') -> List:
v1 = v1 if v1 else self.turn
if self._pieces_remaining[v1] == 0:
return []
else:
return self._board.valid_moves(v1)
``` |
Imports:
```python
from datetime import datetime, timezone
import typing
```
Type definitions:
Input Types: datetime, Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: datetime, v2):
if v1.tzinfo is None:
v1 = v1.astimezone(timezone.utc)
return v1.astimezone(tim... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types:
Output Type: None
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> None:
v1 = os.path.join(self.checkpoint_dir, 'best_model.pth')
self.t_logger.info('Saving best model ...')
self._save_model(v1)
``` |
Imports:
```python
import pandas as pd
import numpy as np
import warnings
import typing
```
Type definitions:
Input Types: Any
Output Type: pd.DataFrame
Dependencies:
Function Name: v0
Function:
```python
def v0(v1) -> pd.DataFrame:
v2 = pd.DataFrame.from_dict({'x': [np.nan], 'y': [np.nan], 'z': [np.nan], 'origin... |
Imports:
```python
import typing
```
Type definitions:
Input Types: str
Output Type: np.ndarray
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str=None) -> np.ndarray:
if v1 is None:
raise ValueError('`column` must be specified when calling .to_numpy() on Arrow blocks.')
if v1 no... |
Imports:
```python
import torch
import typing
```
Type definitions:
Input Types: Union[int, float, Tuple[float, float]], Any
Output Type: torch.Tensor
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: Union[int, float, Tuple[float, float]], v2=torch.float32) -> torch.Tensor:
if isinstance(v1, tuple):... |
Imports:
```python
import os
import typing
```
Type definitions:
Input Types: str
Output Type: NoReturn
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: str) -> NoReturn:
if v1:
v2 = os.path.abspath(os.path.expanduser(v1))
if os.path.exists(v2):
self._extension_file... |
Imports:
```python
import typing
```
Type definitions:
Input Types: Any
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: Any):
v2 = id(v1)
if v2 in self.visited:
return False
self.visited.add(v2)
return True
``` |
Imports:
```python
import typing
```
Type definitions:
Input Types:
Output Type: List[str]
Dependencies:
Function Name: v0
Function:
```python
def v0(self) -> List[str]:
if 'ntags' not in self.columns:
raise ValueError("Tags column 'ntags' not present. Either use the notes table or merge it into your tab... |
Imports:
```python
import typing
```
Type definitions:
```python
class v0(object):
def __init__(self, v1: Text, v2: Optional[Text]=''):
"""Construct an instance of TfxArtifact.
Each instance of TfxArtifact wraps an Artifact and its type internally.
When first created, the artifact will have an emp... |
Imports:
```python
import numpy as np
import typing
```
Type definitions:
Input Types: int, int, []
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(v1: int, v2: int, v3: []):
if np.random.binomial(1, v1) == 1:
return np.random.choice(v2)
return np.random.choice(np.where(v3 ... |
Imports:
```python
import typing
```
Type definitions:
Input Types: np.ndarray
Output Type: Any
Dependencies:
Function Name: v0
Function:
```python
def v0(self, v1: np.ndarray):
assert self.graph.graph_index is not None, 'Environment need to be reset'
assert not self.is_done(), 'Environment has already been t... |
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