def literal_eval(s):
"""
Wrapper around ``ast.literal_eval`` that returns its return value,
if possible, but returns the original string in cases where
``ast.literal_eval`` raises an exception.
"""
try:
return ast_literal_eval(s)
except (ValueError, SyntaxError):
return s
def clean_compression_algos(self):
""" Convert SelectMultiple selected choices
into a TextField with space separator """
compression_algos = self.cleaned_data.get('compression_algos')
if not compression_algos:
return ""
try:
""" Transform text formatted list into list"""
algos_list = ast_literal_eval(compression_algos)
except Exception:
raise ValidationError("Invalid field.")
else:
""" And return select choices with space separator """
return ' '.join(algos_list)
def load(self, filename=None, text=None):
f = None
if text is None:
f = open(filename, "r")
else:
f = io.StringIO(text)
exclusive = f.readline().strip() == "True"
inp = int(f.readline().strip())
hid = list(map(int, f.readline().strip().split(" ")))
out = int(f.readline().strip())
weights = []
for i in range(0, len(hid) + 1):
weights.append(np.matrix(ast_literal_eval(f.readline().strip())))
f.close()
self.initialize(inp, hid, out, weights, exclusive)
def intervals(self, value):
if not isinstance(value, (tuple, list)):
msg = "intervals attribute must be a tuple or list, not {0!r}"
raise ValueError(msg.format(value.__class__.__name__))
# Parse the intervals
values = []
for interval in value:
if isinstance(interval, str):
i = interval.split()
try:
x = ast_literal_eval(i.pop(0))
except Exception:
raise ValueError(
"Unparseable interval: {0!r}".format(interval))
if interval:
units = ' '.join(i)
else:
units = None
try:
d = Data(x, units)
except Exception:
raise ValueError(
"Unparseable interval: {0!r}".format(interval))
else:
try:
d = Data.asdata(interval, copy=True)
except Exception:
raise ValueError(
"Unparseable interval: {0!r}".format(interval))
# --- End: if
if d.size != 1:
raise ValueError(
"Unparseable interval: {0!r}".format(interval))
if d.ndim > 1:
d.squeeze(inplace=True)
values.append(d)
# --- End: for
self.set_qualifier('interval', tuple(values))
def intervals(self, value):
if not isinstance(value, (tuple, list)):
raise ValueError(
"intervals attribute must be a tuple or list, not "
f"{value.__class__.__name__!r}")
# Parse the intervals
values = []
for interval in value:
if isinstance(interval, str):
i = interval.split()
try:
x = ast_literal_eval(i.pop(0))
except Exception:
raise ValueError(f"Unparseable interval: {interval!r}")
if interval:
units = " ".join(i)
else:
units = None
try:
d = Data(x, units)
except Exception:
raise ValueError(f"Unparseable interval: {interval!r}")
else:
try:
d = Data.asdata(interval, copy=True)
except Exception:
raise ValueError(f"Unparseable interval: {interval!r}")
if d.size != 1:
raise ValueError(f"Unparseable interval: {interval!r}")
if d.ndim > 1:
d.squeeze(inplace=True)
values.append(d)
self.set_qualifier("interval", tuple(values))
def create(cls, cell_methods_string=None):
'''Parse a CF-like cell_methods string.
:Parameters:
cell_methods_string: `str`
A CF cell_methods string.
:Returns:
`list`
**Examples:**
>>> c = CellMethod.create('lat: mean (interval: 1 hour)')
'''
incorrect_interval = 'Cell method interval is incorrectly formatted'
out = []
if not cell_methods_string:
return out
# ------------------------------------------------------------
# Split the cell_methods string into a list of strings ready
# for parsing. For example:
#
# 'lat: mean (interval: 1 hour)'
#
# would be split up into:
#
# ['lat:', 'mean', '(', 'interval:', '1', 'hour', ')']
# ------------------------------------------------------------
cell_methods = re.sub('\((?=[^\s])', '( ', cell_methods_string)
cell_methods = re.sub('(?<=[^\s])\)', ' )', cell_methods).split()
while cell_methods:
cm = cls()
axes = []
while cell_methods:
if not cell_methods[0].endswith(':'):
break
# TODO Check that "name" ends with colon? How? ('lat: mean
# (area-weighted) or lat: mean (interval: 1 degree_north comment:
# area-weighted)')
axis = cell_methods.pop(0)[:-1]
axes.append(axis)
# --- End: while
cm.set_axes(axes)
if not cell_methods:
out.append(cm)
break
# Method
cm.set_method(cell_methods.pop(0))
if not cell_methods:
out.append(cm)
break
# Climatological statistics, and statistics which apply to
# portions of cells
while cell_methods[0] in ('within', 'where', 'over'):
attr = cell_methods.pop(0)
cm.set_qualifier(attr, cell_methods.pop(0))
if not cell_methods:
break
# --- End: while
if not cell_methods:
out.append(cm)
break
# interval and comment
intervals = []
if cell_methods[0].endswith('('):
cell_methods.pop(0)
if not (re.search('^(interval|comment):$', cell_methods[0])):
cell_methods.insert(0, 'comment:')
while not re.search('^\)$', cell_methods[0]):
term = cell_methods.pop(0)[:-1]
if term == 'interval':
interval = cell_methods.pop(0)
if cell_methods[0] != ')':
units = cell_methods.pop(0)
else:
units = None
try:
parsed_interval = ast_literal_eval(interval)
except (SyntaxError, ValueError):
raise ValueError("{}: {!r}".format(
incorrect_interval, interval))
try:
data = Data(array=parsed_interval,
units=units,
copy=False)
except Exception:
raise ValueError("{}: {!r}".format(
incorrect_interval, interval))
intervals.append(data)
continue
# --- End: if
if term == 'comment':
comment = []
while cell_methods:
if cell_methods[0].endswith(')'):
break
if cell_methods[0].endswith(':'):
break
comment.append(cell_methods.pop(0))
# --- End: while
cm.set_qualifier('comment', ' '.join(comment))
# --- End: while
if cell_methods[0].endswith(')'):
cell_methods.pop(0)
# --- End: if
n_intervals = len(intervals)
if n_intervals > 1 and n_intervals != len(axes):
raise ValueError("{} (doesn't match axes): {!r}".format(
incorrect_interval, interval))
if intervals:
cm.set_qualifier('interval', intervals)
out.append(cm)
# --- End: while
return out
from ast import literal_eval as ast_literal_eval
from re import compile as re_compile
from setuptools import find_packages, setup
PKG_NAME = 'list-cli'
PKG_DESCRIPTION = 'List Management Application (CLI)'
_version_re = re_compile(r'__version__\s+=\s+(.*)')
with open('list/cli.py'.format(PKG_NAME), 'rb') as f:
PKG_VERSION = str(
ast_literal_eval(
_version_re.search(f.read().decode('utf-8')).group(1)))
setup(
name=PKG_NAME,
version=PKG_VERSION,
url='https://github.com/jzaleski/list-cli',
license='MIT',
description=PKG_DESCRIPTION,
long_description=PKG_DESCRIPTION,
author='Jonathan W. Zaleski',
author_email='*****@*****.**',
packages=find_packages(),
install_requires=[],
entry_points={'console_scripts': ['list-cli=list.__main__:main']},
classifiers=[
'Development Status :: 3 - Alpha',
'Intended Audience :: Developers',
'License :: OSI Approved :: MIT License',
'Operating System :: POSIX :: Linux',
'Programming Language :: Python :: 3',
def _create_data(
self,
ncvar,
construct=None,
unpacked_dtype=False,
uncompress_override=None,
parent_ncvar=None,
):
"""TODO.
.. versionadded:: 3.0.0
:Parameters:
ncvar: `str`
The name of the netCDF variable that contains the data.
construct: optional
unpacked_dtype: `False` or `numpy.dtype`, optional
uncompress_override: `bool`, optional
:Returns:
`Data`
"""
g = self.read_vars
is_cfa_variable = (
g["cfa"]
and construct.get_property("cf_role", None) == "cfa_variable"
)
if not is_cfa_variable:
# --------------------------------------------------------
# Create data for a normal netCDF variable
# --------------------------------------------------------
return super()._create_data(
ncvar=ncvar,
construct=construct,
unpacked_dtype=unpacked_dtype,
uncompress_override=uncompress_override,
parent_ncvar=parent_ncvar,
)
# ------------------------------------------------------------
# Still here? Then create data for a CFA netCDF variable
# ------------------------------------------------------------
# print (' Creating data from CFA variable', repr(ncvar),
# repr(construct))
try:
cfa_data = json.loads(construct.get_property("cfa_array"))
except ValueError as error:
raise ValueError(
"Error during JSON-decoding of netCDF attribute 'cfa_array': "
"{}".format(error)
)
variable = g["variables"][ncvar]
cfa_data["file"] = g["filename"]
cfa_data["Units"] = construct.Units
cfa_data["fill_value"] = construct.fill_value()
cfa_data["_pmshape"] = cfa_data.pop("pmshape", ())
cfa_data["_pmaxes"] = cfa_data.pop("pmdimensions", ())
base = cfa_data.get("base", None)
if base is not None:
cfa_data["base"] = pathjoin(dirname(g["filename"]), base)
ncdimensions = construct.get_property("cfa_dimensions", "").split()
dtype = variable.dtype
if dtype is str:
# netCDF string types have a dtype of `str`, which needs
# to be reset as a numpy.dtype, but we don't know what
# without reading the data, so set it to None for now.
dtype = None
# UNICODE???? TODO
if self._is_char(ncvar) and dtype.kind in "SU" and ncdimensions:
strlen = g["nc"].dimensions[ncdimensions[-1]].size
if strlen > 1:
ncdimensions.pop()
dtype = numpy_dtype("S{0}".format(strlen))
# --- End: if
cfa_data["dtype"] = dtype
cfa_data["_axes"] = ncdimensions
cfa_data["shape"] = [
g["nc"].dimensions[ncdim].size for ncdim in ncdimensions
]
for attrs in cfa_data["Partitions"]:
# FORMAT
sformat = attrs.get("subarray", {}).pop("format", "netCDF")
if sformat is not None:
attrs["format"] = sformat
# DTYPE
dtype = attrs.get("subarray", {}).pop("dtype", None)
if dtype not in (None, "char"):
attrs["subarray"]["dtype"] = numpy_dtype(dtype)
# UNITS and CALENDAR
units = attrs.pop("punits", None)
calendar = attrs.pop("pcalendar", None)
if units is not None or calendar is not None:
attrs["Units"] = Units(units, calendar)
# AXES
pdimensions = attrs.pop("pdimensions", None)
if pdimensions is not None:
attrs["axes"] = pdimensions
# REVERSE
reverse = attrs.pop("reverse", None)
if reverse is not None:
attrs["reverse"] = reverse
# LOCATION: Change to python indexing (i.e. range does not
# include the final index)
for r in attrs["location"]:
r[1] += 1
# PART: Change to python indexing (i.e. slice range does
# not include the final index)
part = attrs.get("part", None)
if part:
p = []
for x in ast_literal_eval(part):
if isinstance(x, list):
if x[2] > 0:
p.append(slice(x[0], x[1] + 1, x[2]))
elif x[1] == 0:
p.append(slice(x[0], None, x[2]))
else:
p.append(slice(x[0], x[1] - 1, x[2]))
else:
p.append(list(x))
# --- End: for
attrs["part"] = p
# --- End: for
construct.del_property("cf_role")
construct.del_property("cfa_array")
construct.del_property("cfa_dimensions", None)
out = self._create_Data(loadd=cfa_data)
return out
def create(cls, cell_methods_string=None):
"""Parse a CF-like cell_methods string.
:Parameters:
cell_methods_string: `str`
A CF cell_methods string.
:Returns:
`list`
**Examples:**
>>> c = CellMethod.create('lat: mean (interval: 1 hour)')
"""
incorrect_interval = "Cell method interval is incorrectly formatted"
out = []
if not cell_methods_string:
return out
# ------------------------------------------------------------
# Split the cell_methods string into a list of strings ready
# for parsing. For example:
#
# 'lat: mean (interval: 1 hour)'
#
# would be split up into:
#
# ['lat:', 'mean', '(', 'interval:', '1', 'hour', ')']
# ------------------------------------------------------------
cell_methods = re.sub("\((?=[^\s])", "( ", cell_methods_string)
cell_methods = re.sub("(?<=[^\s])\)", " )", cell_methods).split()
while cell_methods:
cm = cls()
axes = []
while cell_methods:
if not cell_methods[0].endswith(":"):
break
# TODO Check that "name" ends with colon? How? ('lat: mean
# (area-weighted) or lat: mean (interval: 1 degree_north comment:
# area-weighted)')
axis = cell_methods.pop(0)[:-1]
axes.append(axis)
cm.set_axes(axes)
if not cell_methods:
out.append(cm)
break
# Method
cm.set_method(cell_methods.pop(0))
if not cell_methods:
out.append(cm)
break
# Climatological statistics, and statistics which apply to
# portions of cells
while cell_methods[0] in ("within", "where", "over"):
attr = cell_methods.pop(0)
cm.set_qualifier(attr, cell_methods.pop(0))
if not cell_methods:
break
if not cell_methods:
out.append(cm)
break
# interval and comment
intervals = []
if cell_methods[0].endswith("("):
cell_methods.pop(0)
if not (re.search("^(interval|comment):$", cell_methods[0])):
cell_methods.insert(0, "comment:")
while not re.search("^\)$", cell_methods[0]):
term = cell_methods.pop(0)[:-1]
if term == "interval":
interval = cell_methods.pop(0)
if cell_methods[0] != ")":
units = cell_methods.pop(0)
else:
units = None
try:
parsed_interval = ast_literal_eval(interval)
except (SyntaxError, ValueError):
raise ValueError(
f"{incorrect_interval}: {interval!r}")
try:
data = Data(array=parsed_interval,
units=units,
copy=False)
except Exception:
raise ValueError(
f"{incorrect_interval}: {interval!r}")
intervals.append(data)
continue
if term == "comment":
comment = []
while cell_methods:
if cell_methods[0].endswith(")"):
break
if cell_methods[0].endswith(":"):
break
comment.append(cell_methods.pop(0))
cm.set_qualifier("comment", " ".join(comment))
if cell_methods[0].endswith(")"):
cell_methods.pop(0)
n_intervals = len(intervals)
if n_intervals > 1 and n_intervals != len(axes):
raise ValueError(
f"{incorrect_interval} (doesn't match axes): {interval!r}")
if intervals:
cm.set_qualifier("interval", intervals)
out.append(cm)
return out
