176 行
4.4 KiB
Cython
176 行
4.4 KiB
Cython
cimport cython
|
|
import numpy as np
|
|
|
|
from cpython cimport (
|
|
PyBytes_GET_SIZE,
|
|
PyUnicode_GET_LENGTH,
|
|
)
|
|
from numpy cimport (
|
|
ndarray,
|
|
uint8_t,
|
|
)
|
|
|
|
ctypedef fused pandas_string:
|
|
str
|
|
bytes
|
|
|
|
|
|
@cython.boundscheck(False)
|
|
@cython.wraparound(False)
|
|
def write_csv_rows(
|
|
list data,
|
|
ndarray data_index,
|
|
Py_ssize_t nlevels,
|
|
ndarray cols,
|
|
object writer
|
|
) -> None:
|
|
"""
|
|
Write the given data to the writer object, pre-allocating where possible
|
|
for performance improvements.
|
|
|
|
Parameters
|
|
----------
|
|
data : list[ArrayLike]
|
|
data_index : ndarray
|
|
nlevels : int
|
|
cols : ndarray
|
|
writer : _csv.writer
|
|
"""
|
|
# In crude testing, N>100 yields little marginal improvement
|
|
cdef:
|
|
Py_ssize_t i, j = 0, k = len(data_index), N = 100, ncols = len(cols)
|
|
list rows
|
|
|
|
# pre-allocate rows
|
|
rows = [[None] * (nlevels + ncols) for _ in range(N)]
|
|
|
|
if nlevels == 1:
|
|
for j in range(k):
|
|
row = rows[j % N]
|
|
row[0] = data_index[j]
|
|
for i in range(ncols):
|
|
row[1 + i] = data[i][j]
|
|
|
|
if j >= N - 1 and j % N == N - 1:
|
|
writer.writerows(rows)
|
|
elif nlevels > 1:
|
|
for j in range(k):
|
|
row = rows[j % N]
|
|
row[:nlevels] = list(data_index[j])
|
|
for i in range(ncols):
|
|
row[nlevels + i] = data[i][j]
|
|
|
|
if j >= N - 1 and j % N == N - 1:
|
|
writer.writerows(rows)
|
|
else:
|
|
for j in range(k):
|
|
row = rows[j % N]
|
|
for i in range(ncols):
|
|
row[i] = data[i][j]
|
|
|
|
if j >= N - 1 and j % N == N - 1:
|
|
writer.writerows(rows)
|
|
|
|
if j >= 0 and (j < N - 1 or (j % N) != N - 1):
|
|
writer.writerows(rows[:((j + 1) % N)])
|
|
|
|
|
|
@cython.boundscheck(False)
|
|
@cython.wraparound(False)
|
|
def convert_json_to_lines(arr: str) -> str:
|
|
"""
|
|
replace comma separated json with line feeds, paying special attention
|
|
to quotes & brackets
|
|
"""
|
|
cdef:
|
|
Py_ssize_t i = 0, num_open_brackets_seen = 0, length
|
|
bint in_quotes = False, is_escaping = False
|
|
ndarray[uint8_t, ndim=1] narr
|
|
unsigned char val, newline, comma, left_bracket, right_bracket, quote
|
|
unsigned char backslash
|
|
|
|
newline = ord('\n')
|
|
comma = ord(',')
|
|
left_bracket = ord('{')
|
|
right_bracket = ord('}')
|
|
quote = ord('"')
|
|
backslash = ord('\\')
|
|
|
|
narr = np.frombuffer(arr.encode('utf-8'), dtype='u1').copy()
|
|
length = narr.shape[0]
|
|
for i in range(length):
|
|
val = narr[i]
|
|
if val == quote and i > 0 and not is_escaping:
|
|
in_quotes = ~in_quotes
|
|
if val == backslash or is_escaping:
|
|
is_escaping = ~is_escaping
|
|
if val == comma: # commas that should be \n
|
|
if num_open_brackets_seen == 0 and not in_quotes:
|
|
narr[i] = newline
|
|
elif val == left_bracket:
|
|
if not in_quotes:
|
|
num_open_brackets_seen += 1
|
|
elif val == right_bracket:
|
|
if not in_quotes:
|
|
num_open_brackets_seen -= 1
|
|
|
|
return narr.tobytes().decode('utf-8') + '\n' # GH:36888
|
|
|
|
|
|
# stata, pytables
|
|
@cython.boundscheck(False)
|
|
@cython.wraparound(False)
|
|
def max_len_string_array(pandas_string[:] arr) -> Py_ssize_t:
|
|
"""
|
|
Return the maximum size of elements in a 1-dim string array.
|
|
"""
|
|
cdef:
|
|
Py_ssize_t i, m = 0, wlen = 0, length = arr.shape[0]
|
|
pandas_string val
|
|
|
|
for i in range(length):
|
|
val = arr[i]
|
|
wlen = word_len(val)
|
|
|
|
if wlen > m:
|
|
m = wlen
|
|
|
|
return m
|
|
|
|
|
|
cpdef inline Py_ssize_t word_len(object val):
|
|
"""
|
|
Return the maximum length of a string or bytes value.
|
|
"""
|
|
cdef:
|
|
Py_ssize_t wlen = 0
|
|
|
|
if isinstance(val, str):
|
|
wlen = PyUnicode_GET_LENGTH(val)
|
|
elif isinstance(val, bytes):
|
|
wlen = PyBytes_GET_SIZE(val)
|
|
|
|
return wlen
|
|
|
|
# ------------------------------------------------------------------
|
|
# PyTables Helpers
|
|
|
|
|
|
@cython.boundscheck(False)
|
|
@cython.wraparound(False)
|
|
def string_array_replace_from_nan_rep(
|
|
ndarray[object, ndim=1] arr,
|
|
object nan_rep,
|
|
object replace=np.nan
|
|
) -> None:
|
|
"""
|
|
Replace the values in the array with 'replacement' if
|
|
they are 'nan_rep'. Return the same array.
|
|
"""
|
|
cdef:
|
|
Py_ssize_t length = len(arr), i = 0
|
|
|
|
for i in range(length):
|
|
if arr[i] == nan_rep:
|
|
arr[i] = replace
|