def _rstrip_inplace(array):
"""
Performs an in-place rstrip operation on string arrays. This is necessary
since the built-in `np.char.rstrip` in Numpy does not perform an in-place
calculation.
"""
# The following implementation convert the string to unsigned integers of
# the right length. Trailing spaces (which are represented as 32) are then
# converted to null characters (represented as zeros). To avoid creating
# large temporary mask arrays, we loop over chunks (attempting to do that
# on a 1-D version of the array; large memory may still be needed in the
# unlikely case that a string array has small first dimension and cannot
# be represented as a contiguous 1-D array in memory).
dt = array.dtype
if dt.kind not in 'SU':
raise TypeError("This function can only be used on string arrays")
# View the array as appropriate integers. The last dimension will
# equal the number of characters in each string.
bpc = 1 if dt.kind == 'S' else 4
dt_int = f"({dt.itemsize // bpc},){dt.byteorder}u{bpc}"
b = array.view(dt_int, np.ndarray)
# For optimal speed, work in chunks of the internal ufunc buffer size.
bufsize = np.getbufsize()
# Attempt to have the strings as a 1-D array to give the chunk known size.
# Note: the code will work if this fails; the chunks will just be larger.
if b.ndim > 2:
try:
b.shape = -1, b.shape[-1]
except AttributeError: # can occur for non-contiguous arrays
pass
for j in range(0, b.shape[0], bufsize):
c = b[j:j + bufsize]
# Mask which will tell whether we're in a sequence of trailing spaces.
mask = np.ones(c.shape[:-1], dtype=bool)
# Loop over the characters in the strings, in reverse order. We process
# the i-th character of all strings in the chunk at the same time. If
# the character is 32, this corresponds to a space, and we then change
# this to 0. We then construct a new mask to find rows where the
# i-th character is 0 (null) and the i-1-th is 32 (space) and repeat.
for i in range(-1, -c.shape[-1], -1):
mask &= c[..., i] == 32
c[..., i][mask] = 0
mask = c[..., i] == 0
return array
def _rstrip_inplace(array):
"""
Performs an in-place rstrip operation on string arrays. This is necessary
since the built-in `np.char.rstrip` in Numpy does not perform an in-place
calculation.
"""
# The following implementation convert the string to unsigned integers of
# the right length. Trailing spaces (which are represented as 32) are then
# converted to null characters (represented as zeros). To avoid creating
# large temporary mask arrays, we loop over chunks (attempting to do that
# on a 1-D version of the array; large memory may still be needed in the
# unlikely case that a string array has small first dimension and cannot
# be represented as a contiguous 1-D array in memory).
dt = array.dtype
if dt.kind not in 'SU':
raise TypeError("This function can only be used on string arrays")
# View the array as appropriate integers. The last dimension will
# equal the number of characters in each string.
bpc = 1 if dt.kind == 'S' else 4
dt_int = "{0}{1}u{2}".format(dt.itemsize // bpc, dt.byteorder, bpc)
b = array.view(dt_int, np.ndarray)
# For optimal speed, work in chunks of the internal ufunc buffer size.
bufsize = np.getbufsize()
# Attempt to have the strings as a 1-D array to give the chunk known size.
# Note: the code will work if this fails; the chunks will just be larger.
if b.ndim > 2:
try:
b.shape = -1, b.shape[-1]
except AttributeError: # can occur for non-contiguous arrays
pass
for j in range(0, b.shape[0], bufsize):
c = b[j:j + bufsize]
# Mask which will tell whether we're in a sequence of trailing spaces.
mask = np.ones(c.shape[:-1], dtype=bool)
# Loop over the characters in the strings, in reverse order. We process
# the i-th character of all strings in the chunk at the same time. If
# the character is 32, this corresponds to a space, and we then change
# this to 0. We then construct a new mask to find rows where the
# i-th character is 0 (null) and the i-1-th is 32 (space) and repeat.
for i in range(-1, -c.shape[-1], -1):
mask &= c[..., i] == 32
c[..., i][mask] = 0
mask = c[..., i] == 0
return array
import numpy numpy.getbufsize()
coded by: Roi Tzadok
version: 1.0
date:4.4.2017
a simple client that is able to communicate with the server
"""
import shutil
import os
import urllib2
import socket
import numpy
import platform
import webbrowser
import zipfile
MY_PLATFORM = platform.system()
BUFF_SIZE = numpy.getbufsize()
def unzip(file_path, file_dst):
"""
unzip a nupkg file
@param file_path: the zip file path
@param file_dst: where to unzip to
"""
zip_ref = zipfile.ZipFile(file_path)
zip_ref.extractall(file_dst)
zip_ref.close()
def try_to_download_from_choco(client_socket, file_name):
"""
def func1(a: str, b: int) -> None: ...
def func2(a: str, b: int, c: float = ...) -> None: ...
def func3(a: str, b: int) -> int: ...
class Write1:
def write(self, a: str) -> None: ...
class Write2:
def write(self, a: str, b: int = ...) -> None: ...
class Write3:
def write(self, a: str) -> int: ...
_err_default = np.geterr()
_bufsize_default = np.getbufsize()
_errcall_default = np.geterrcall()
try:
np.seterr(all=None)
np.seterr(divide="ignore")
np.seterr(over="warn")
np.seterr(under="call")
np.seterr(invalid="raise")
np.geterr()
np.setbufsize(4096)
np.getbufsize()
np.seterrcall(func1)
np.seterrcall(func2)
reveal_type(
np.seterr(all=None)) # E: TypedDict('numpy.core._ufunc_config._ErrDict'
reveal_type(np.seterr(
divide="ignore")) # E: TypedDict('numpy.core._ufunc_config._ErrDict'
reveal_type(
np.seterr(over="warn")) # E: TypedDict('numpy.core._ufunc_config._ErrDict'
reveal_type(np.seterr(
under="call")) # E: TypedDict('numpy.core._ufunc_config._ErrDict'
reveal_type(np.seterr(
invalid="raise")) # E: TypedDict('numpy.core._ufunc_config._ErrDict'
reveal_type(np.geterr()) # E: TypedDict('numpy.core._ufunc_config._ErrDict'
reveal_type(np.setbufsize(4096)) # E: int
reveal_type(np.getbufsize()) # E: int
reveal_type(
np.seterrcall(func)
) # E: Union[None, def (builtins.str, builtins.int) -> Any, numpy.core._ufunc_config._SupportsWrite]
reveal_type(
np.seterrcall(Write())
) # E: Union[None, def (builtins.str, builtins.int) -> Any, numpy.core._ufunc_config._SupportsWrite]
reveal_type(
np.geterrcall()
) # E: Union[None, def (builtins.str, builtins.int) -> Any, numpy.core._ufunc_config._SupportsWrite]
reveal_type(np.errstate(
call=func,
all="call")) # E: numpy.errstate[def (a: builtins.str, b: builtins.int)]
reveal_type(np.errstate(call=Write(), divide="log",
