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