_id stringlengths 2 7 | title stringlengths 1 88 | partition stringclasses 3
values | text stringlengths 75 19.8k | language stringclasses 1
value | meta_information dict |
|---|---|---|---|---|---|
q260200 | events.drag | validation | def drag(self, node):
""" Drags given node to mouse location.
"""
dx = self.mouse.x - self.graph.x
dy = self.mouse.y - self.graph.y
# A dashed line indicates the drag vector.
s = self.graph.styles.default
self._ctx.nofill()
self._ctx.nostroke()
if s.stroke:
self._ctx.strokewidth(s.strokewidth)
self._ctx.stroke(
s.stroke.r,
s.stroke.g,
s.stroke.g,
0.75
)
p = self._ctx.line(node.x, node.y, dx, dy, draw=False)
try: p._nsBezierPath.setLineDash_count_phase_([2,4], 2, 50)
except:
pass
self._ctx.drawpath(p)
r = node.__class__(None).r * 0.75
self._ctx.oval(dx-r/2, dy-r/2, r, r)
node.vx = dx / self.graph.d
node.vy = dy / self.graph.d | python | {
"resource": ""
} |
q260201 | events.hover | validation | def hover(self, node):
""" Displays a popup when hovering over a node.
"""
if self.popup == False: return
if self.popup == True or self.popup.node != node:
if self.popup_text.has_key(node.id):
texts = self.popup_text[node.id]
else:
texts = None
self.popup = popup(self._ctx, node, texts)
self.popup.draw() | python | {
"resource": ""
} |
q260202 | popup.textpath | validation | def textpath(self, i):
""" Returns a cached textpath of the given text in queue.
"""
if len(self._textpaths) == i:
self._ctx.font(self.font, self.fontsize)
txt = self.q[i]
if len(self.q) > 1:
# Indicate current text (e.g. 5/13).
txt += " ("+str(i+1)+"/" + str(len(self.q))+")"
p = self._ctx.textpath(txt, 0, 0, width=self._w)
h = self._ctx.textheight(txt, width=self._w)
self._textpaths.append((p, h))
return self._textpaths[i] | python | {
"resource": ""
} |
q260203 | popup.update | validation | def update(self):
""" Rotates the queued texts and determines display time.
"""
if self.delay > 0:
# It takes a while for the popup to appear.
self.delay -= 1; return
if self.fi == 0:
# Only one text in queue, displayed infinitely.
if len(self.q) == 1:
self.fn = float("inf")
# Else, display time depends on text length.
else:
self.fn = len(self.q[self.i]) / self.speed
self.fn = max(self.fn, self.mf)
self.fi += 1
if self.fi > self.fn:
# Rotate to the next text in queue.
self.fi = 0
self.i = (self.i+1) % len(self.q) | python | {
"resource": ""
} |
q260204 | popup.draw | validation | def draw(self):
""" Draws a popup rectangle with a rotating text queue.
"""
if len(self.q) > 0:
self.update()
if self.delay == 0:
# Rounded rectangle in the given background color.
p, h = self.textpath(self.i)
f = self.fontsize
self._ctx.fill(self.background)
self._ctx.rect(
self.node.x + f*1.0,
self.node.y + f*0.5,
self._w + f,
h + f*1.5,
roundness=0.2
)
# Fade in/out the current text.
alpha = 1.0
if self.fi < 5:
alpha = 0.2 * self.fi
if self.fn-self.fi < 5:
alpha = 0.2 * (self.fn-self.fi)
self._ctx.fill(
self.text.r,
self.text.g,
self.text.b,
self.text.a * alpha
)
self._ctx.translate(self.node.x + f*2.0, self.node.y + f*2.5)
self._ctx.drawpath(p) | python | {
"resource": ""
} |
q260205 | write_main | validation | def write_main(argv):
"""
write FILENAME
Write a local copy of FILENAME using FILENAME_tweaks for local tweaks.
"""
if len(argv) != 1:
print("Please provide the name of a file to write.")
return 1
filename = argv[0]
resource_name = "files/" + filename
tweaks_name = amend_filename(filename, "_tweaks")
if not pkg_resources.resource_exists("edx_lint", resource_name):
print(u"Don't have file %r to write." % filename)
return 2
if os.path.exists(filename):
print(u"Checking existing copy of %s" % filename)
tef = TamperEvidentFile(filename)
if not tef.validate():
bak_name = amend_filename(filename, "_backup")
print(u"Your copy of %s seems to have been edited, renaming it to %s" % (filename, bak_name))
if os.path.exists(bak_name):
print(u"A previous %s exists, deleting it" % bak_name)
os.remove(bak_name)
os.rename(filename, bak_name)
print(u"Reading edx_lint/files/%s" % filename)
cfg = configparser.RawConfigParser()
resource_string = pkg_resources.resource_string("edx_lint", resource_name).decode("utf8")
# pkg_resources always reads binary data (in both python2 and python3).
# ConfigParser.read_string only exists in python3, so we have to wrap the string
# from pkg_resources in a cStringIO so that we can pass it into ConfigParser.readfp.
if six.PY2:
cfg.readfp(cStringIO(resource_string), resource_name)
else:
cfg.read_string(resource_string, resource_name) # pylint: disable=no-member
if os.path.exists(tweaks_name):
print(u"Applying local tweaks from %s" % tweaks_name)
cfg_tweaks = configparser.RawConfigParser()
cfg_tweaks.read([tweaks_name])
merge_configs(cfg, cfg_tweaks)
print(u"Writing %s" % filename)
output_text = cStringIO()
output_text.write(WARNING_HEADER.format(filename=filename, tweaks_name=tweaks_name))
cfg.write(output_text)
out_tef = TamperEvidentFile(filename)
if six.PY2:
output_bytes = output_text.getvalue()
else:
output_bytes = output_text.getvalue().encode("utf8")
out_tef.write(output_bytes)
return 0 | python | {
"resource": ""
} |
q260206 | amend_filename | validation | def amend_filename(filename, amend):
"""Amend a filename with a suffix.
amend_filename("foo.txt", "_tweak") --> "foo_tweak.txt"
"""
base, ext = os.path.splitext(filename)
amended_name = base + amend + ext
return amended_name | python | {
"resource": ""
} |
q260207 | check_main | validation | def check_main(argv):
"""
check FILENAME
Check that FILENAME has not been edited since writing.
"""
if len(argv) != 1:
print("Please provide the name of a file to check.")
return 1
filename = argv[0]
if os.path.exists(filename):
print(u"Checking existing copy of %s" % filename)
tef = TamperEvidentFile(filename)
if tef.validate():
print(u"Your copy of %s is good" % filename)
else:
print(u"Your copy of %s seems to have been edited" % filename)
else:
print(u"You don't have a copy of %s" % filename)
return 0 | python | {
"resource": ""
} |
q260208 | merge_configs | validation | def merge_configs(main, tweaks):
"""Merge tweaks into a main config file."""
for section in tweaks.sections():
for option in tweaks.options(section):
value = tweaks.get(section, option)
if option.endswith("+"):
option = option[:-1]
value = main.get(section, option) + value
main.set(section, option, value) | python | {
"resource": ""
} |
q260209 | TamperEvidentFile.write | validation | def write(self, text, hashline=b"# {}"):
u"""
Write `text` to the file.
Writes the text to the file, with a final line checksumming the
contents. The entire file must be written with one `.write()` call.
The last line is written with the `hashline` format string, which can
be changed to accommodate different file syntaxes.
Both arguments are UTF8 byte strings.
Arguments:
text (UTF8 byte string): the contents of the file to write.
hashline (UTF8 byte string): the format of the last line to append
to the file, with "{}" replaced with the hash.
"""
if not text.endswith(b"\n"):
text += b"\n"
actual_hash = hashlib.sha1(text).hexdigest()
with open(self.filename, "wb") as f:
f.write(text)
f.write(hashline.decode("utf8").format(actual_hash).encode("utf8"))
f.write(b"\n") | python | {
"resource": ""
} |
q260210 | TamperEvidentFile.validate | validation | def validate(self):
"""
Check if the file still has its original contents.
Returns True if the file is unchanged, False if it has been tampered
with.
"""
with open(self.filename, "rb") as f:
text = f.read()
start_last_line = text.rfind(b"\n", 0, -1)
if start_last_line == -1:
return False
original_text = text[:start_last_line+1]
last_line = text[start_last_line+1:]
expected_hash = hashlib.sha1(original_text).hexdigest().encode('utf8')
match = re.search(b"[0-9a-f]{40}", last_line)
if not match:
return False
actual_hash = match.group(0)
return actual_hash == expected_hash | python | {
"resource": ""
} |
q260211 | check_visitors | validation | def check_visitors(cls):
"""Check that a checker's visitors are correctly named.
A checker has methods named visit_NODETYPE, but it's easy to mis-name
a visit method, and it will never be called. This decorator checks
the class to see that all of its visitors are named after an existing
node class.
"""
for name in dir(cls):
if name.startswith("visit_"):
if name[6:] not in CLASS_NAMES:
raise Exception(u"Method {} doesn't correspond to a node class".format(name))
return cls | python | {
"resource": ""
} |
q260212 | usable_class_name | validation | def usable_class_name(node):
"""Make a reasonable class name for a class node."""
name = node.qname()
for prefix in ["__builtin__.", "builtins.", "."]:
if name.startswith(prefix):
name = name[len(prefix):]
return name | python | {
"resource": ""
} |
q260213 | parse_pylint_output | validation | def parse_pylint_output(pylint_output):
"""
Parse the pylint output-format=parseable lines into PylintError tuples.
"""
for line in pylint_output:
if not line.strip():
continue
if line[0:5] in ("-"*5, "*"*5):
continue
parsed = PYLINT_PARSEABLE_REGEX.search(line)
if parsed is None:
LOG.warning(
u"Unable to parse %r. If this is a lint failure, please re-run pylint with the "
u"--output-format=parseable option, otherwise, you can ignore this message.",
line
)
continue
parsed_dict = parsed.groupdict()
parsed_dict['linenum'] = int(parsed_dict['linenum'])
yield PylintError(**parsed_dict) | python | {
"resource": ""
} |
q260214 | main | validation | def main(argv=None):
"""The edx_lint command entry point."""
if argv is None:
argv = sys.argv[1:]
if not argv or argv[0] == "help":
show_help()
return 0
elif argv[0] == "check":
return check_main(argv[1:])
elif argv[0] == "list":
return list_main(argv[1:])
elif argv[0] == "write":
return write_main(argv[1:])
else:
print(u"Don't understand {!r}".format(" ".join(argv)))
show_help()
return 1 | python | {
"resource": ""
} |
q260215 | show_help | validation | def show_help():
"""Print the help string for the edx_lint command."""
print("""\
Manage local config files from masters in edx_lint.
Commands:
""")
for cmd in [write_main, check_main, list_main]:
print(cmd.__doc__.lstrip("\n")) | python | {
"resource": ""
} |
q260216 | trans_new | validation | def trans_new(name, transform, inverse, breaks=None,
minor_breaks=None, _format=None,
domain=(-np.inf, np.inf), doc='', **kwargs):
"""
Create a transformation class object
Parameters
----------
name : str
Name of the transformation
transform : callable ``f(x)``
A function (preferably a `ufunc`) that computes
the transformation.
inverse : callable ``f(x)``
A function (preferably a `ufunc`) that computes
the inverse of the transformation.
breaks : callable ``f(limits)``
Function to compute the breaks for this transform.
If None, then a default good enough for a linear
domain is used.
minor_breaks : callable ``f(major, limits)``
Function to compute the minor breaks for this
transform. If None, then a default good enough for
a linear domain is used.
_format : callable ``f(breaks)``
Function to format the generated breaks.
domain : array_like
Domain over which the transformation is valid.
It should be of length 2.
doc : str
Docstring for the class.
**kwargs : dict
Attributes of the transform, e.g if base is passed
in kwargs, then `t.base` would be a valied attribute.
Returns
-------
out : trans
Transform class
"""
def _get(func):
if isinstance(func, (classmethod, staticmethod, MethodType)):
return func
else:
return staticmethod(func)
klass_name = '{}_trans'.format(name)
d = {'transform': _get(transform),
'inverse': _get(inverse),
'domain': domain,
'__doc__': doc,
**kwargs}
if breaks:
d['breaks_'] = _get(breaks)
if minor_breaks:
d['minor_breaks'] = _get(minor_breaks)
if _format:
d['format'] = _get(_format)
return type(klass_name, (trans,), d) | python | {
"resource": ""
} |
q260217 | gettrans | validation | def gettrans(t):
"""
Return a trans object
Parameters
----------
t : str | callable | type | trans
name of transformation function
Returns
-------
out : trans
"""
obj = t
# Make sure trans object is instantiated
if isinstance(obj, str):
name = '{}_trans'.format(obj)
obj = globals()[name]()
if callable(obj):
obj = obj()
if isinstance(obj, type):
obj = obj()
if not isinstance(obj, trans):
raise ValueError("Could not get transform object.")
return obj | python | {
"resource": ""
} |
q260218 | trans.breaks | validation | def breaks(self, limits):
"""
Calculate breaks in data space and return them
in transformed space.
Expects limits to be in *transform space*, this
is the same space as that where the domain is
specified.
This method wraps around :meth:`breaks_` to ensure
that the calculated breaks are within the domain
the transform. This is helpful in cases where an
aesthetic requests breaks with limits expanded for
some padding, yet the expansion goes beyond the
domain of the transform. e.g for a probability
transform the breaks will be in the domain
``[0, 1]`` despite any outward limits.
Parameters
----------
limits : tuple
The scale limits. Size 2.
Returns
-------
out : array_like
Major breaks
"""
# clip the breaks to the domain,
# e.g. probabilities will be in [0, 1] domain
vmin = np.max([self.domain[0], limits[0]])
vmax = np.min([self.domain[1], limits[1]])
breaks = np.asarray(self.breaks_([vmin, vmax]))
# Some methods(mpl_breaks, extended_breaks) that
# calculate breaks take the limits as guide posts and
# not hard limits.
breaks = breaks.compress((breaks >= self.domain[0]) &
(breaks <= self.domain[1]))
return breaks | python | {
"resource": ""
} |
q260219 | datetime_trans.transform | validation | def transform(x):
"""
Transform from date to a numerical format
"""
try:
x = date2num(x)
except AttributeError:
# numpy datetime64
# This is not ideal because the operations do not
# preserve the np.datetime64 type. May be need
# a datetime64_trans
x = [pd.Timestamp(item) for item in x]
x = date2num(x)
return x | python | {
"resource": ""
} |
q260220 | rescale | validation | def rescale(x, to=(0, 1), _from=None):
"""
Rescale numeric vector to have specified minimum and maximum.
Parameters
----------
x : array_like | numeric
1D vector of values to manipulate.
to : tuple
output range (numeric vector of length two)
_from : tuple
input range (numeric vector of length two).
If not given, is calculated from the range of x
Returns
-------
out : array_like
Rescaled values
Examples
--------
>>> x = [0, 2, 4, 6, 8, 10]
>>> rescale(x)
array([0. , 0.2, 0.4, 0.6, 0.8, 1. ])
>>> rescale(x, to=(0, 2))
array([0. , 0.4, 0.8, 1.2, 1.6, 2. ])
>>> rescale(x, to=(0, 2), _from=(0, 20))
array([0. , 0.2, 0.4, 0.6, 0.8, 1. ])
"""
if _from is None:
_from = np.min(x), np.max(x)
return np.interp(x, _from, to) | python | {
"resource": ""
} |
q260221 | rescale_mid | validation | def rescale_mid(x, to=(0, 1), _from=None, mid=0):
"""
Rescale numeric vector to have specified minimum, midpoint,
and maximum.
Parameters
----------
x : array_like | numeric
1D vector of values to manipulate.
to : tuple
output range (numeric vector of length two)
_from : tuple
input range (numeric vector of length two).
If not given, is calculated from the range of x
mid : numeric
mid-point of input range
Returns
-------
out : array_like
Rescaled values
Examples
--------
>>> rescale_mid([1, 2, 3], mid=1)
array([0.5 , 0.75, 1. ])
>>> rescale_mid([1, 2, 3], mid=2)
array([0. , 0.5, 1. ])
"""
array_like = True
try:
len(x)
except TypeError:
array_like = False
x = [x]
if not hasattr(x, 'dtype'):
x = np.asarray(x)
if _from is None:
_from = np.array([np.min(x), np.max(x)])
else:
_from = np.asarray(_from)
if (zero_range(_from) or zero_range(to)):
out = np.repeat(np.mean(to), len(x))
else:
extent = 2 * np.max(np.abs(_from - mid))
out = (x - mid) / extent * np.diff(to) + np.mean(to)
if not array_like:
out = out[0]
return out | python | {
"resource": ""
} |
q260222 | rescale_max | validation | def rescale_max(x, to=(0, 1), _from=None):
"""
Rescale numeric vector to have specified maximum.
Parameters
----------
x : array_like | numeric
1D vector of values to manipulate.
to : tuple
output range (numeric vector of length two)
_from : tuple
input range (numeric vector of length two).
If not given, is calculated from the range of x.
Only the 2nd (max) element is essential to the
output.
Returns
-------
out : array_like
Rescaled values
Examples
--------
>>> x = [0, 2, 4, 6, 8, 10]
>>> rescale_max(x, (0, 3))
array([0. , 0.6, 1.2, 1.8, 2.4, 3. ])
Only the 2nd (max) element of the parameters ``to``
and ``_from`` are essential to the output.
>>> rescale_max(x, (1, 3))
array([0. , 0.6, 1.2, 1.8, 2.4, 3. ])
>>> rescale_max(x, (0, 20))
array([ 0., 4., 8., 12., 16., 20.])
If :python:`max(x) < _from[1]` then values will be
scaled beyond the requested (:python:`to[1]`) maximum.
>>> rescale_max(x, to=(1, 3), _from=(-1, 6))
array([0., 1., 2., 3., 4., 5.])
"""
array_like = True
try:
len(x)
except TypeError:
array_like = False
x = [x]
if not hasattr(x, 'dtype'):
x = np.asarray(x)
if _from is None:
_from = np.array([np.min(x), np.max(x)])
out = x/_from[1] * to[1]
if not array_like:
out = out[0]
return out | python | {
"resource": ""
} |
q260223 | squish_infinite | validation | def squish_infinite(x, range=(0, 1)):
"""
Truncate infinite values to a range.
Parameters
----------
x : array_like
Values that should have infinities squished.
range : tuple
The range onto which to squish the infinites.
Must be of size 2.
Returns
-------
out : array_like
Values with infinites squished.
Examples
--------
>>> squish_infinite([0, .5, .25, np.inf, .44])
[0.0, 0.5, 0.25, 1.0, 0.44]
>>> squish_infinite([0, -np.inf, .5, .25, np.inf], (-10, 9))
[0.0, -10.0, 0.5, 0.25, 9.0]
"""
xtype = type(x)
if not hasattr(x, 'dtype'):
x = np.asarray(x)
x[x == -np.inf] = range[0]
x[x == np.inf] = range[1]
if not isinstance(x, xtype):
x = xtype(x)
return x | python | {
"resource": ""
} |
q260224 | squish | validation | def squish(x, range=(0, 1), only_finite=True):
"""
Squish values into range.
Parameters
----------
x : array_like
Values that should have out of range values squished.
range : tuple
The range onto which to squish the values.
only_finite: boolean
When true, only squishes finite values.
Returns
-------
out : array_like
Values with out of range values squished.
Examples
--------
>>> squish([-1.5, 0.2, 0.5, 0.8, 1.0, 1.2])
[0.0, 0.2, 0.5, 0.8, 1.0, 1.0]
>>> squish([-np.inf, -1.5, 0.2, 0.5, 0.8, 1.0, np.inf], only_finite=False)
[0.0, 0.0, 0.2, 0.5, 0.8, 1.0, 1.0]
"""
xtype = type(x)
if not hasattr(x, 'dtype'):
x = np.asarray(x)
finite = np.isfinite(x) if only_finite else True
x[np.logical_and(x < range[0], finite)] = range[0]
x[np.logical_and(x > range[1], finite)] = range[1]
if not isinstance(x, xtype):
x = xtype(x)
return x | python | {
"resource": ""
} |
q260225 | _censor_with | validation | def _censor_with(x, range, value=None):
"""
Censor any values outside of range with ``None``
"""
return [val if range[0] <= val <= range[1] else value
for val in x] | python | {
"resource": ""
} |
q260226 | zero_range | validation | def zero_range(x, tol=np.finfo(float).eps * 100):
"""
Determine if range of vector is close to zero.
Parameters
----------
x : array_like | numeric
Value(s) to check. If it is an array_like, it
should be of length 2.
tol : float
Tolerance. Default tolerance is the `machine epsilon`_
times :math:`10^2`.
Returns
-------
out : bool
Whether ``x`` has zero range.
Examples
--------
>>> zero_range([1, 1])
True
>>> zero_range([1, 2])
False
>>> zero_range([1, 2], tol=2)
True
.. _machine epsilon: https://en.wikipedia.org/wiki/Machine_epsilon
"""
try:
if len(x) == 1:
return True
except TypeError:
return True
if len(x) != 2:
raise ValueError('x must be length 1 or 2')
# Deals with array_likes that have non-standard indices
x = tuple(x)
# datetime - pandas, cpython
if isinstance(x[0], (pd.Timestamp, datetime.datetime)):
# date2num include timezone info, .toordinal() does not
x = date2num(x)
# datetime - numpy
elif isinstance(x[0], np.datetime64):
return x[0] == x[1]
# timedelta - pandas, cpython
elif isinstance(x[0], (pd.Timedelta, datetime.timedelta)):
x = x[0].total_seconds(), x[1].total_seconds()
# timedelta - numpy
elif isinstance(x[0], np.timedelta64):
return x[0] == x[1]
elif not isinstance(x[0], (float, int, np.number)):
raise TypeError(
"zero_range objects cannot work with objects "
"of type '{}'".format(type(x[0])))
if any(np.isnan(x)):
return np.nan
if x[0] == x[1]:
return True
if all(np.isinf(x)):
return False
m = np.abs(x).min()
if m == 0:
return False
return np.abs((x[0] - x[1]) / m) < tol | python | {
"resource": ""
} |
q260227 | expand_range | validation | def expand_range(range, mul=0, add=0, zero_width=1):
"""
Expand a range with a multiplicative or additive constant
Parameters
----------
range : tuple
Range of data. Size 2.
mul : int | float
Multiplicative constant
add : int | float | timedelta
Additive constant
zero_width : int | float | timedelta
Distance to use if range has zero width
Returns
-------
out : tuple
Expanded range
Examples
--------
>>> expand_range((3, 8))
(3, 8)
>>> expand_range((0, 10), mul=0.1)
(-1.0, 11.0)
>>> expand_range((0, 10), add=2)
(-2, 12)
>>> expand_range((0, 10), mul=.1, add=2)
(-3.0, 13.0)
>>> expand_range((0, 1))
(0, 1)
When the range has zero width
>>> expand_range((5, 5))
(4.5, 5.5)
Notes
-----
If expanding *datetime* or *timedelta* types, **add** and
**zero_width** must be suitable *timedeltas* i.e. You should
not mix types between **Numpy**, **Pandas** and the
:mod:`datetime` module.
In Python 2, you cannot multiplicative constant **mul** cannot be
a :class:`float`.
"""
x = range
# Enforce tuple
try:
x[0]
except TypeError:
x = (x, x)
# The expansion cases
if zero_range(x):
new = x[0]-zero_width/2, x[0]+zero_width/2
else:
dx = (x[1] - x[0]) * mul + add
new = x[0]-dx, x[1]+dx
return new | python | {
"resource": ""
} |
q260228 | expand_range_distinct | validation | def expand_range_distinct(range, expand=(0, 0, 0, 0), zero_width=1):
"""
Expand a range with a multiplicative or additive constants
Similar to :func:`expand_range` but both sides of the range
expanded using different constants
Parameters
----------
range : tuple
Range of data. Size 2
expand : tuple
Length 2 or 4. If length is 2, then the same constants
are used for both sides. If length is 4 then the first
two are are the Multiplicative (*mul*) and Additive (*add*)
constants for the lower limit, and the second two are
the constants for the upper limit.
zero_width : int | float | timedelta
Distance to use if range has zero width
Returns
-------
out : tuple
Expanded range
Examples
--------
>>> expand_range_distinct((3, 8))
(3, 8)
>>> expand_range_distinct((0, 10), (0.1, 0))
(-1.0, 11.0)
>>> expand_range_distinct((0, 10), (0.1, 0, 0.1, 0))
(-1.0, 11.0)
>>> expand_range_distinct((0, 10), (0.1, 0, 0, 0))
(-1.0, 10)
>>> expand_range_distinct((0, 10), (0, 2))
(-2, 12)
>>> expand_range_distinct((0, 10), (0, 2, 0, 2))
(-2, 12)
>>> expand_range_distinct((0, 10), (0, 0, 0, 2))
(0, 12)
>>> expand_range_distinct((0, 10), (.1, 2))
(-3.0, 13.0)
>>> expand_range_distinct((0, 10), (.1, 2, .1, 2))
(-3.0, 13.0)
>>> expand_range_distinct((0, 10), (0, 0, .1, 2))
(0, 13.0)
"""
if len(expand) == 2:
expand = tuple(expand) * 2
lower = expand_range(range, expand[0], expand[1], zero_width)[0]
upper = expand_range(range, expand[2], expand[3], zero_width)[1]
return (lower, upper) | python | {
"resource": ""
} |
q260229 | trans_minor_breaks._extend_breaks | validation | def _extend_breaks(self, major):
"""
Append 2 extra breaks at either end of major
If breaks of transform space are non-equidistant,
:func:`minor_breaks` add minor breaks beyond the first
and last major breaks. The solutions is to extend those
breaks (in transformed space) before the minor break call
is made. How the breaks depends on the type of transform.
"""
trans = self.trans
trans = trans if isinstance(trans, type) else trans.__class__
# so far we are only certain about this extending stuff
# making sense for log transform
is_log = trans.__name__.startswith('log')
diff = np.diff(major)
step = diff[0]
if is_log and all(diff == step):
major = np.hstack([major[0]-step, major, major[-1]+step])
return major | python | {
"resource": ""
} |
q260230 | timedelta_helper.best_units | validation | def best_units(self, sequence):
"""
Determine good units for representing a sequence of timedeltas
"""
# Read
# [(0.9, 's'),
# (9, 'm)]
# as, break ranges between 0.9 seconds (inclusive)
# and 9 minutes are represented in seconds. And so on.
ts_range = self.value(max(sequence)) - self.value(min(sequence))
package = self.determine_package(sequence[0])
if package == 'pandas':
cuts = [
(0.9, 'us'),
(0.9, 'ms'),
(0.9, 's'),
(9, 'm'),
(6, 'h'),
(4, 'd'),
(4, 'w'),
(4, 'M'),
(3, 'y')]
denomination = NANOSECONDS
base_units = 'ns'
else:
cuts = [
(0.9, 's'),
(9, 'm'),
(6, 'h'),
(4, 'd'),
(4, 'w'),
(4, 'M'),
(3, 'y')]
denomination = SECONDS
base_units = 'ms'
for size, units in reversed(cuts):
if ts_range >= size*denomination[units]:
return units
return base_units | python | {
"resource": ""
} |
q260231 | timedelta_helper.scaled_limits | validation | def scaled_limits(self):
"""
Minimum and Maximum to use for computing breaks
"""
_min = self.limits[0]/self.factor
_max = self.limits[1]/self.factor
return _min, _max | python | {
"resource": ""
} |
q260232 | timedelta_helper.numeric_to_timedelta | validation | def numeric_to_timedelta(self, numerics):
"""
Convert sequence of numerics to timedelta
"""
if self.package == 'pandas':
return [self.type(int(x*self.factor), units='ns')
for x in numerics]
else:
return [self.type(seconds=x*self.factor)
for x in numerics] | python | {
"resource": ""
} |
q260233 | timedelta_helper.to_numeric | validation | def to_numeric(self, td):
"""
Convert timedelta to a number corresponding to the
appropriate units. The appropriate units are those
determined with the object is initialised.
"""
if self.package == 'pandas':
return td.value/NANOSECONDS[self.units]
else:
return td.total_seconds()/SECONDS[self.units] | python | {
"resource": ""
} |
q260234 | round_any | validation | def round_any(x, accuracy, f=np.round):
"""
Round to multiple of any number.
"""
if not hasattr(x, 'dtype'):
x = np.asarray(x)
return f(x / accuracy) * accuracy | python | {
"resource": ""
} |
q260235 | min_max | validation | def min_max(x, na_rm=False, finite=True):
"""
Return the minimum and maximum of x
Parameters
----------
x : array_like
Sequence
na_rm : bool
Whether to remove ``nan`` values.
finite : bool
Whether to consider only finite values.
Returns
-------
out : tuple
(minimum, maximum) of x
"""
if not hasattr(x, 'dtype'):
x = np.asarray(x)
if na_rm and finite:
x = x[np.isfinite(x)]
elif not na_rm and np.any(np.isnan(x)):
return np.nan, np.nan
elif na_rm:
x = x[~np.isnan(x)]
elif finite:
x = x[~np.isinf(x)]
if (len(x)):
return np.min(x), np.max(x)
else:
return float('-inf'), float('inf') | python | {
"resource": ""
} |
q260236 | precision | validation | def precision(x):
"""
Return the precision of x
Parameters
----------
x : array_like | numeric
Value(s) whose for which to compute the precision.
Returns
-------
out : numeric
The precision of ``x`` or that the values in ``x``.
Notes
-----
The precision is computed in base 10.
Examples
--------
>>> precision(0.08)
0.01
>>> precision(9)
1
>>> precision(16)
10
"""
from .bounds import zero_range
rng = min_max(x, na_rm=True)
if zero_range(rng):
span = np.abs(rng[0])
else:
span = np.diff(rng)[0]
if span == 0:
return 1
else:
return 10 ** int(np.floor(np.log10(span))) | python | {
"resource": ""
} |
q260237 | multitype_sort | validation | def multitype_sort(a):
"""
Sort elements of multiple types
x is assumed to contain elements of different types, such that
plain sort would raise a `TypeError`.
Parameters
----------
a : array-like
Array of items to be sorted
Returns
-------
out : list
Items sorted within their type groups.
"""
types = defaultdict(list)
numbers = {int, float, complex}
for x in a:
t = type(x)
if t in numbers:
types['number'].append(x)
else:
types[t].append(x)
for t in types:
types[t] = np.sort(types[t])
return list(chain(*(types[t] for t in types))) | python | {
"resource": ""
} |
q260238 | nearest_int | validation | def nearest_int(x):
"""
Return nearest long integer to x
"""
if x == 0:
return np.int64(0)
elif x > 0:
return np.int64(x + 0.5)
else:
return np.int64(x - 0.5) | python | {
"resource": ""
} |
q260239 | is_close_to_int | validation | def is_close_to_int(x):
"""
Check if value is close to an integer
Parameters
----------
x : float
Numeric value to check
Returns
-------
out : bool
"""
if not np.isfinite(x):
return False
return abs(x - nearest_int(x)) < 1e-10 | python | {
"resource": ""
} |
q260240 | same_log10_order_of_magnitude | validation | def same_log10_order_of_magnitude(x, delta=0.1):
"""
Return true if range is approximately in same order of magnitude
For example these sequences are in the same order of magnitude:
- [1, 8, 5] # [1, 10)
- [35, 20, 80] # [10 100)
- [232, 730] # [100, 1000)
Parameters
----------
x : array-like
Values in base 10. Must be size 2 and
``rng[0] <= rng[1]``.
delta : float
Fuzz factor for approximation. It is multiplicative.
"""
dmin = np.log10(np.min(x)*(1-delta))
dmax = np.log10(np.max(x)*(1+delta))
return np.floor(dmin) == np.floor(dmax) | python | {
"resource": ""
} |
q260241 | _format | validation | def _format(formatter, x):
"""
Helper to format and tidy up
"""
# For MPL to play nice
formatter.create_dummy_axis()
# For sensible decimal places
formatter.set_locs([val for val in x if ~np.isnan(val)])
try:
oom = int(formatter.orderOfMagnitude)
except AttributeError:
oom = 0
labels = [formatter(tick) for tick in x]
# Remove unnecessary decimals
pattern = re.compile(r'\.0+$')
for i, label in enumerate(labels):
match = pattern.search(label)
if match:
labels[i] = pattern.sub('', label)
# MPL does not add the exponential component
if oom:
labels = ['{}e{}'.format(s, oom) if s != '0' else s
for s in labels]
return labels | python | {
"resource": ""
} |
q260242 | log_format._tidyup_labels | validation | def _tidyup_labels(self, labels):
"""
Make all labels uniform in format and remove redundant zeros
for labels in exponential format.
Parameters
----------
labels : list-like
Labels to be tidied.
Returns
-------
out : list-like
Labels
"""
def remove_zeroes(s):
"""
Remove unnecessary zeros for float string s
"""
tup = s.split('e')
if len(tup) == 2:
mantissa = tup[0].rstrip('0').rstrip('.')
exponent = int(tup[1])
if exponent:
s = '%se%d' % (mantissa, exponent)
else:
s = mantissa
return s
def as_exp(s):
"""
Float string s as in exponential format
"""
return s if 'e' in s else '{:1.0e}'.format(float(s))
# If any are in exponential format, make all of
# them expontential
has_e = np.array(['e' in x for x in labels])
if not np.all(has_e) and not np.all(~has_e):
labels = [as_exp(x) for x in labels]
labels = [remove_zeroes(x) for x in labels]
return labels | python | {
"resource": ""
} |
q260243 | hls_palette | validation | def hls_palette(n_colors=6, h=.01, l=.6, s=.65):
"""
Get a set of evenly spaced colors in HLS hue space.
h, l, and s should be between 0 and 1
Parameters
----------
n_colors : int
number of colors in the palette
h : float
first hue
l : float
lightness
s : float
saturation
Returns
-------
palette : list
List of colors as RGB hex strings.
See Also
--------
husl_palette : Make a palette using evenly spaced circular
hues in the HUSL system.
Examples
--------
>>> len(hls_palette(2))
2
>>> len(hls_palette(9))
9
"""
hues = np.linspace(0, 1, n_colors + 1)[:-1]
hues += h
hues %= 1
hues -= hues.astype(int)
palette = [colorsys.hls_to_rgb(h_i, l, s) for h_i in hues]
return palette | python | {
"resource": ""
} |
q260244 | husl_palette | validation | def husl_palette(n_colors=6, h=.01, s=.9, l=.65):
"""
Get a set of evenly spaced colors in HUSL hue space.
h, s, and l should be between 0 and 1
Parameters
----------
n_colors : int
number of colors in the palette
h : float
first hue
s : float
saturation
l : float
lightness
Returns
-------
palette : list
List of colors as RGB hex strings.
See Also
--------
hls_palette : Make a palette using evenly spaced circular
hues in the HSL system.
Examples
--------
>>> len(husl_palette(3))
3
>>> len(husl_palette(11))
11
"""
hues = np.linspace(0, 1, n_colors + 1)[:-1]
hues += h
hues %= 1
hues *= 359
s *= 99
l *= 99
palette = [husl.husl_to_rgb(h_i, s, l) for h_i in hues]
return palette | python | {
"resource": ""
} |
q260245 | grey_pal | validation | def grey_pal(start=0.2, end=0.8):
"""
Utility for creating continuous grey scale palette
Parameters
----------
start : float
grey value at low end of palette
end : float
grey value at high end of palette
Returns
-------
out : function
Continuous color palette that takes a single
:class:`int` parameter ``n`` and returns ``n``
equally spaced colors.
Examples
--------
>>> palette = grey_pal()
>>> palette(5)
['#333333', '#737373', '#989898', '#b5b5b5', '#cccccc']
"""
gamma = 2.2
ends = ((0.0, start, start), (1.0, end, end))
cdict = {'red': ends, 'green': ends, 'blue': ends}
grey_cmap = mcolors.LinearSegmentedColormap('grey', cdict)
def continuous_grey_palette(n):
colors = []
# The grey scale points are linearly separated in
# gamma encoded space
for x in np.linspace(start**gamma, end**gamma, n):
# Map points onto the [0, 1] palette domain
x = (x ** (1./gamma) - start) / (end - start)
colors.append(mcolors.rgb2hex(grey_cmap(x)))
return colors
return continuous_grey_palette | python | {
"resource": ""
} |
q260246 | hue_pal | validation | def hue_pal(h=.01, l=.6, s=.65, color_space='hls'):
"""
Utility for making hue palettes for color schemes.
Parameters
----------
h : float
first hue. In the [0, 1] range
l : float
lightness. In the [0, 1] range
s : float
saturation. In the [0, 1] range
color_space : 'hls' | 'husl'
Color space to use for the palette
Returns
-------
out : function
A discrete color palette that takes a single
:class:`int` parameter ``n`` and returns ``n``
equally spaced colors. Though the palette
is continuous, since it is varies the hue it
is good for categorical data. However if ``n``
is large enough the colors show continuity.
Examples
--------
>>> hue_pal()(5)
['#db5f57', '#b9db57', '#57db94', '#5784db', '#c957db']
>>> hue_pal(color_space='husl')(5)
['#e0697e', '#9b9054', '#569d79', '#5b98ab', '#b675d7']
"""
if not all([0 <= val <= 1 for val in (h, l, s)]):
msg = ("hue_pal expects values to be between 0 and 1. "
" I got h={}, l={}, s={}".format(h, l, s))
raise ValueError(msg)
if color_space not in ('hls', 'husl'):
msg = "color_space should be one of ['hls', 'husl']"
raise ValueError(msg)
name = '{}_palette'.format(color_space)
palette = globals()[name]
def _hue_pal(n):
colors = palette(n, h=h, l=l, s=s)
return [mcolors.rgb2hex(c) for c in colors]
return _hue_pal | python | {
"resource": ""
} |
q260247 | brewer_pal | validation | def brewer_pal(type='seq', palette=1):
"""
Utility for making a brewer palette
Parameters
----------
type : 'sequential' | 'qualitative' | 'diverging'
Type of palette. Sequential, Qualitative or
Diverging. The following abbreviations may
be used, ``seq``, ``qual`` or ``div``.
palette : int | str
Which palette to choose from. If is an integer,
it must be in the range ``[0, m]``, where ``m``
depends on the number sequential, qualitative or
diverging palettes. If it is a string, then it
is the name of the palette.
Returns
-------
out : function
A color palette that takes a single
:class:`int` parameter ``n`` and returns ``n``
colors. The maximum value of ``n`` varies
depending on the parameters.
Examples
--------
>>> brewer_pal()(5)
['#EFF3FF', '#BDD7E7', '#6BAED6', '#3182BD', '#08519C']
>>> brewer_pal('qual')(5)
['#7FC97F', '#BEAED4', '#FDC086', '#FFFF99', '#386CB0']
>>> brewer_pal('qual', 2)(5)
['#1B9E77', '#D95F02', '#7570B3', '#E7298A', '#66A61E']
>>> brewer_pal('seq', 'PuBuGn')(5)
['#F6EFF7', '#BDC9E1', '#67A9CF', '#1C9099', '#016C59']
The available color names for each palette type can be
obtained using the following code::
import palettable.colorbrewer as brewer
print([k for k in brewer.COLOR_MAPS['Sequential'].keys()])
print([k for k in brewer.COLOR_MAPS['Qualitative'].keys()])
print([k for k in brewer.COLOR_MAPS['Diverging'].keys()])
"""
def full_type_name(text):
abbrevs = {
'seq': 'Sequential',
'qual': 'Qualitative',
'div': 'Diverging'
}
text = abbrevs.get(text, text)
return text.title()
def number_to_palette_name(ctype, n):
"""
Return palette name that corresponds to a given number
Uses alphabetical ordering
"""
n -= 1
palettes = sorted(colorbrewer.COLOR_MAPS[ctype].keys())
if n < len(palettes):
return palettes[n]
raise ValueError(
"There are only '{}' palettes of type {}. "
"You requested palette no. {}".format(len(palettes),
ctype, n+1))
def max_palette_colors(type, palette_name):
"""
Return the number of colors in the brewer palette
"""
if type == 'Sequential':
return 9
elif type == 'Diverging':
return 11
else:
# Qualitative palettes have different limits
qlimit = {'Accent': 8, 'Dark2': 8, 'Paired': 12,
'Pastel1': 9, 'Pastel2': 8, 'Set1': 9,
'Set2': 8, 'Set3': 12}
return qlimit[palette_name]
type = full_type_name(type)
if isinstance(palette, int):
palette_name = number_to_palette_name(type, palette)
else:
palette_name = palette
nmax = max_palette_colors(type, palette_name)
def _brewer_pal(n):
# Only draw the maximum allowable colors from the palette
# and fill any remaining spots with None
_n = n if n <= nmax else nmax
try:
bmap = colorbrewer.get_map(palette_name, type, _n)
except ValueError as err:
# Some palettes have a minimum no. of colors set at 3
# We get around that restriction.
if 0 <= _n < 3:
bmap = colorbrewer.get_map(palette_name, type, 3)
else:
raise err
hex_colors = bmap.hex_colors[:n]
if n > nmax:
msg = ("Warning message:"
"Brewer palette {} has a maximum of {} colors"
"Returning the palette you asked for with"
"that many colors".format(palette_name, nmax))
warnings.warn(msg)
hex_colors = hex_colors + [None] * (n - nmax)
return hex_colors
return _brewer_pal | python | {
"resource": ""
} |
q260248 | gradient_n_pal | validation | def gradient_n_pal(colors, values=None, name='gradientn'):
"""
Create a n color gradient palette
Parameters
----------
colors : list
list of colors
values : list, optional
list of points in the range [0, 1] at which to
place each color. Must be the same size as
`colors`. Default to evenly space the colors
name : str
Name to call the resultant MPL colormap
Returns
-------
out : function
Continuous color palette that takes a single
parameter either a :class:`float` or a sequence
of floats maps those value(s) onto the palette
and returns color(s). The float(s) must be
in the range [0, 1].
Examples
--------
>>> palette = gradient_n_pal(['red', 'blue'])
>>> palette([0, .25, .5, .75, 1])
['#ff0000', '#bf0040', '#7f0080', '#3f00c0', '#0000ff']
"""
# Note: For better results across devices and media types,
# it would be better to do the interpolation in
# Lab color space.
if values is None:
colormap = mcolors.LinearSegmentedColormap.from_list(
name, colors)
else:
colormap = mcolors.LinearSegmentedColormap.from_list(
name, list(zip(values, colors)))
def _gradient_n_pal(vals):
return ratios_to_colors(vals, colormap)
return _gradient_n_pal | python | {
"resource": ""
} |
q260249 | cmap_pal | validation | def cmap_pal(name=None, lut=None):
"""
Create a continuous palette using an MPL colormap
Parameters
----------
name : str
Name of colormap
lut : None | int
This is the number of entries desired in the lookup table.
Default is ``None``, leave it up Matplotlib.
Returns
-------
out : function
Continuous color palette that takes a single
parameter either a :class:`float` or a sequence
of floats maps those value(s) onto the palette
and returns color(s). The float(s) must be
in the range [0, 1].
Examples
--------
>>> palette = cmap_pal('viridis')
>>> palette([.1, .2, .3, .4, .5])
['#482475', '#414487', '#355f8d', '#2a788e', '#21918c']
"""
colormap = get_cmap(name, lut)
def _cmap_pal(vals):
return ratios_to_colors(vals, colormap)
return _cmap_pal | python | {
"resource": ""
} |
q260250 | cmap_d_pal | validation | def cmap_d_pal(name=None, lut=None):
"""
Create a discrete palette using an MPL Listed colormap
Parameters
----------
name : str
Name of colormap
lut : None | int
This is the number of entries desired in the lookup table.
Default is ``None``, leave it up Matplotlib.
Returns
-------
out : function
A discrete color palette that takes a single
:class:`int` parameter ``n`` and returns ``n``
colors. The maximum value of ``n`` varies
depending on the parameters.
Examples
--------
>>> palette = cmap_d_pal('viridis')
>>> palette(5)
['#440154', '#3b528b', '#21918c', '#5cc863', '#fde725']
"""
colormap = get_cmap(name, lut)
if not isinstance(colormap, mcolors.ListedColormap):
raise ValueError(
"For a discrete palette, cmap must be of type "
"matplotlib.colors.ListedColormap")
ncolors = len(colormap.colors)
def _cmap_d_pal(n):
if n > ncolors:
raise ValueError(
"cmap `{}` has {} colors you requested {} "
"colors.".format(name, ncolors, n))
if ncolors < 256:
return [mcolors.rgb2hex(c) for c in colormap.colors[:n]]
else:
# Assume these are continuous and get colors equally spaced
# intervals e.g. viridis is defined with 256 colors
idx = np.linspace(0, ncolors-1, n).round().astype(int)
return [mcolors.rgb2hex(colormap.colors[i]) for i in idx]
return _cmap_d_pal | python | {
"resource": ""
} |
q260251 | desaturate_pal | validation | def desaturate_pal(color, prop, reverse=False):
"""
Create a palette that desaturate a color by some proportion
Parameters
----------
color : matplotlib color
hex, rgb-tuple, or html color name
prop : float
saturation channel of color will be multiplied by
this value
reverse : bool
Whether to reverse the palette.
Returns
-------
out : function
Continuous color palette that takes a single
parameter either a :class:`float` or a sequence
of floats maps those value(s) onto the palette
and returns color(s). The float(s) must be
in the range [0, 1].
Examples
--------
>>> palette = desaturate_pal('red', .1)
>>> palette([0, .25, .5, .75, 1])
['#ff0000', '#e21d1d', '#c53a3a', '#a95656', '#8c7373']
"""
if not 0 <= prop <= 1:
raise ValueError("prop must be between 0 and 1")
# Get rgb tuple rep
# Convert to hls
# Desaturate the saturation channel
# Convert back to rgb
rgb = mcolors.colorConverter.to_rgb(color)
h, l, s = colorsys.rgb_to_hls(*rgb)
s *= prop
desaturated_color = colorsys.hls_to_rgb(h, l, s)
colors = [color, desaturated_color]
if reverse:
colors = colors[::-1]
return gradient_n_pal(colors, name='desaturated') | python | {
"resource": ""
} |
q260252 | manual_pal | validation | def manual_pal(values):
"""
Create a palette from a list of values
Parameters
----------
values : sequence
Values that will be returned by the palette function.
Returns
-------
out : function
A function palette that takes a single
:class:`int` parameter ``n`` and returns ``n`` values.
Examples
--------
>>> palette = manual_pal(['a', 'b', 'c', 'd', 'e'])
>>> palette(3)
['a', 'b', 'c']
"""
max_n = len(values)
def _manual_pal(n):
if n > max_n:
msg = ("Palette can return a maximum of {} values. "
"{} were requested from it.")
warnings.warn(msg.format(max_n, n))
return values[:n]
return _manual_pal | python | {
"resource": ""
} |
q260253 | cubehelix_pal | validation | def cubehelix_pal(start=0, rot=.4, gamma=1.0, hue=0.8,
light=.85, dark=.15, reverse=False):
"""
Utility for creating continuous palette from the cubehelix system.
This produces a colormap with linearly-decreasing (or increasing)
brightness. That means that information will be preserved if printed to
black and white or viewed by someone who is colorblind.
Parameters
----------
start : float (0 <= start <= 3)
The hue at the start of the helix.
rot : float
Rotations around the hue wheel over the range of the palette.
gamma : float (0 <= gamma)
Gamma factor to emphasize darker (gamma < 1) or lighter (gamma > 1)
colors.
hue : float (0 <= hue <= 1)
Saturation of the colors.
dark : float (0 <= dark <= 1)
Intensity of the darkest color in the palette.
light : float (0 <= light <= 1)
Intensity of the lightest color in the palette.
reverse : bool
If True, the palette will go from dark to light.
Returns
-------
out : function
Continuous color palette that takes a single
:class:`int` parameter ``n`` and returns ``n``
equally spaced colors.
References
----------
Green, D. A. (2011). "A colour scheme for the display of astronomical
intensity images". Bulletin of the Astromical Society of India, Vol. 39,
p. 289-295.
Examples
--------
>>> palette = cubehelix_pal()
>>> palette(5)
['#edd1cb', '#d499a7', '#aa688f', '#6e4071', '#2d1e3e']
"""
cdict = mpl._cm.cubehelix(gamma, start, rot, hue)
cubehelix_cmap = mpl.colors.LinearSegmentedColormap('cubehelix', cdict)
def cubehelix_palette(n):
values = np.linspace(light, dark, n)
return [mcolors.rgb2hex(cubehelix_cmap(x)) for x in values]
return cubehelix_palette | python | {
"resource": ""
} |
q260254 | scale_continuous.apply | validation | def apply(cls, x, palette, na_value=None, trans=None):
"""
Scale data continuously
Parameters
----------
x : array_like
Continuous values to scale
palette : callable ``f(x)``
Palette to use
na_value : object
Value to use for missing values.
trans : trans
How to transform the data before scaling. If
``None``, no transformation is done.
Returns
-------
out : array_like
Scaled values
"""
if trans is not None:
x = trans.transform(x)
limits = cls.train(x)
return cls.map(x, palette, limits, na_value) | python | {
"resource": ""
} |
q260255 | scale_continuous.map | validation | def map(cls, x, palette, limits, na_value=None, oob=censor):
"""
Map values to a continuous palette
Parameters
----------
x : array_like
Continuous values to scale
palette : callable ``f(x)``
palette to use
na_value : object
Value to use for missing values.
oob : callable ``f(x)``
Function to deal with values that are
beyond the limits
Returns
-------
out : array_like
Values mapped onto a palette
"""
x = oob(rescale(x, _from=limits))
pal = palette(x)
try:
pal[pd.isnull(x)] = na_value
except TypeError:
pal = [v if not pd.isnull(v) else na_value for v in pal]
return pal | python | {
"resource": ""
} |
q260256 | scale_discrete.map | validation | def map(cls, x, palette, limits, na_value=None):
"""
Map values to a discrete palette
Parameters
----------
palette : callable ``f(x)``
palette to use
x : array_like
Continuous values to scale
na_value : object
Value to use for missing values.
Returns
-------
out : array_like
Values mapped onto a palette
"""
n = len(limits)
pal = palette(n)[match(x, limits)]
try:
pal[pd.isnull(x)] = na_value
except TypeError:
pal = [v if not pd.isnull(v) else na_value for v in pal]
return pal | python | {
"resource": ""
} |
q260257 | EnvConfig.parse | validation | def parse(type: Type):
"""
Register a parser for a attribute type.
Parsers will be used to parse `str` type objects from either
the commandline arguments or environment variables.
Args:
type: the type the decorated function will be responsible
for parsing a environment variable to.
"""
def decorator(parser):
EnvVar.parsers[type] = parser
return parser
return decorator | python | {
"resource": ""
} |
q260258 | _patched_run_hook | validation | def _patched_run_hook(hook_name, project_dir, context):
"""Used to patch cookiecutter's ``run_hook`` function.
This patched version ensures that the temple.yaml file is created before
any cookiecutter hooks are executed
"""
if hook_name == 'post_gen_project':
with temple.utils.cd(project_dir):
temple.utils.write_temple_config(context['cookiecutter'],
context['template'],
context['version'])
return cc_hooks.run_hook(hook_name, project_dir, context) | python | {
"resource": ""
} |
q260259 | _generate_files | validation | def _generate_files(repo_dir, config, template, version):
"""Uses cookiecutter to generate files for the project.
Monkeypatches cookiecutter's "run_hook" to ensure that the temple.yaml file is
generated before any hooks run. This is important to ensure that hooks can also
perform any actions involving temple.yaml
"""
with unittest.mock.patch('cookiecutter.generate.run_hook', side_effect=_patched_run_hook):
cc_generate.generate_files(repo_dir=repo_dir,
context={'cookiecutter': config,
'template': template,
'version': version},
overwrite_if_exists=False,
output_dir='.') | python | {
"resource": ""
} |
q260260 | setup | validation | def setup(template, version=None):
"""Sets up a new project from a template
Note that the `temple.constants.TEMPLE_ENV_VAR` is set to 'setup' during the duration
of this function.
Args:
template (str): The git SSH path to a template
version (str, optional): The version of the template to use when updating. Defaults
to the latest version
"""
temple.check.is_git_ssh_path(template)
temple.check.not_in_git_repo()
repo_path = temple.utils.get_repo_path(template)
msg = (
'You will be prompted for the parameters of your new project.'
' Please read the docs at https://github.com/{} before entering parameters.'
).format(repo_path)
print(msg)
cc_repo_dir, config = temple.utils.get_cookiecutter_config(template, version=version)
if not version:
with temple.utils.cd(cc_repo_dir):
ret = temple.utils.shell('git rev-parse HEAD', stdout=subprocess.PIPE)
version = ret.stdout.decode('utf-8').strip()
_generate_files(repo_dir=cc_repo_dir, config=config, template=template, version=version) | python | {
"resource": ""
} |
q260261 | _parse_link_header | validation | def _parse_link_header(headers):
"""Parses Github's link header for pagination.
TODO eventually use a github client for this
"""
links = {}
if 'link' in headers:
link_headers = headers['link'].split(', ')
for link_header in link_headers:
(url, rel) = link_header.split('; ')
url = url[1:-1]
rel = rel[5:-1]
links[rel] = url
return links | python | {
"resource": ""
} |
q260262 | _code_search | validation | def _code_search(query, github_user=None):
"""Performs a Github API code search
Args:
query (str): The query sent to Github's code search
github_user (str, optional): The Github user being searched in the query string
Returns:
dict: A dictionary of repository information keyed on the git SSH url
Raises:
`InvalidGithubUserError`: When ``github_user`` is invalid
"""
github_client = temple.utils.GithubClient()
headers = {'Accept': 'application/vnd.github.v3.text-match+json'}
resp = github_client.get('/search/code',
params={'q': query, 'per_page': 100},
headers=headers)
if resp.status_code == requests.codes.unprocessable_entity and github_user:
raise temple.exceptions.InvalidGithubUserError(
'Invalid Github user or org - "{}"'.format(github_user))
resp.raise_for_status()
resp_data = resp.json()
repositories = collections.defaultdict(dict)
while True:
repositories.update({
'git@github.com:{}.git'.format(repo['repository']['full_name']): repo['repository']
for repo in resp_data['items']
})
next_url = _parse_link_header(resp.headers).get('next')
if next_url:
resp = requests.get(next_url, headers=headers)
resp.raise_for_status()
resp_data = resp.json()
else:
break
return repositories | python | {
"resource": ""
} |
q260263 | ls | validation | def ls(github_user, template=None):
"""Lists all temple templates and packages associated with those templates
If ``template`` is None, returns the available templates for the configured
Github org.
If ``template`` is a Github path to a template, returns all projects spun
up with that template.
``ls`` uses the github search API to find results.
Note that the `temple.constants.TEMPLE_ENV_VAR` is set to 'ls' for the duration of this
function.
Args:
github_user (str): The github user or org being searched.
template (str, optional): The template git repo path. If provided, lists
all projects that have been created with the provided template. Note
that the template path is the SSH path
(e.g. git@github.com:CloverHealth/temple.git)
Returns:
dict: A dictionary of repository information keyed on the SSH Github url
Raises:
`InvalidGithubUserError`: When ``github_user`` is invalid
"""
temple.check.has_env_vars(temple.constants.GITHUB_API_TOKEN_ENV_VAR)
if template:
temple.check.is_git_ssh_path(template)
search_q = 'user:{} filename:{} {}'.format(
github_user,
temple.constants.TEMPLE_CONFIG_FILE,
template)
else:
search_q = 'user:{} cookiecutter.json in:path'.format(github_user)
results = _code_search(search_q, github_user)
return collections.OrderedDict(sorted(results.items())) | python | {
"resource": ""
} |
q260264 | update | validation | def update(check, enter_parameters, version):
"""
Update package with latest template. Must be inside of the project
folder to run.
Using "-e" will prompt for re-entering the template parameters again
even if the project is up to date.
Use "-v" to update to a particular version of a template.
Using "-c" will perform a check that the project is up to date
with the latest version of the template (or the version specified by "-v").
No updating will happen when using this option.
"""
if check:
if temple.update.up_to_date(version=version):
print('Temple package is up to date')
else:
msg = (
'This temple package is out of date with the latest template.'
' Update your package by running "temple update" and commiting changes.'
)
raise temple.exceptions.NotUpToDateWithTemplateError(msg)
else:
temple.update.update(new_version=version, enter_parameters=enter_parameters) | python | {
"resource": ""
} |
q260265 | ls | validation | def ls(github_user, template, long_format):
"""
List packages created with temple. Enter a github user or
organization to list all templates under the user or org.
Using a template path as the second argument will list all projects
that have been started with that template.
Use "-l" to print the Github repository descriptions of templates
or projects.
"""
github_urls = temple.ls.ls(github_user, template=template)
for ssh_path, info in github_urls.items():
if long_format:
print(ssh_path, '-', info['description'] or '(no project description found)')
else:
print(ssh_path) | python | {
"resource": ""
} |
q260266 | switch | validation | def switch(template, version):
"""
Switch a project's template to a different template.
"""
temple.update.update(new_template=template, new_version=version) | python | {
"resource": ""
} |
q260267 | _in_git_repo | validation | def _in_git_repo():
"""Returns True if inside a git repo, False otherwise"""
ret = temple.utils.shell('git rev-parse', stderr=subprocess.DEVNULL, check=False)
return ret.returncode == 0 | python | {
"resource": ""
} |
q260268 | _has_branch | validation | def _has_branch(branch):
"""Return True if the target branch exists."""
ret = temple.utils.shell('git rev-parse --verify {}'.format(branch),
stderr=subprocess.DEVNULL,
stdout=subprocess.DEVNULL,
check=False)
return ret.returncode == 0 | python | {
"resource": ""
} |
q260269 | not_has_branch | validation | def not_has_branch(branch):
"""Raises `ExistingBranchError` if the specified branch exists."""
if _has_branch(branch):
msg = 'Cannot proceed while {} branch exists; remove and try again.'.format(branch)
raise temple.exceptions.ExistingBranchError(msg) | python | {
"resource": ""
} |
q260270 | has_env_vars | validation | def has_env_vars(*env_vars):
"""Raises `InvalidEnvironmentError` when one isnt set"""
for env_var in env_vars:
if not os.environ.get(env_var):
msg = (
'Must set {} environment variable. View docs for setting up environment at {}'
).format(env_var, temple.constants.TEMPLE_DOCS_URL)
raise temple.exceptions.InvalidEnvironmentError(msg) | python | {
"resource": ""
} |
q260271 | is_temple_project | validation | def is_temple_project():
"""Raises `InvalidTempleProjectError` if repository is not a temple project"""
if not os.path.exists(temple.constants.TEMPLE_CONFIG_FILE):
msg = 'No {} file found in repository.'.format(temple.constants.TEMPLE_CONFIG_FILE)
raise temple.exceptions.InvalidTempleProjectError(msg) | python | {
"resource": ""
} |
q260272 | _get_current_branch | validation | def _get_current_branch():
"""Determine the current git branch"""
result = temple.utils.shell('git rev-parse --abbrev-ref HEAD', stdout=subprocess.PIPE)
return result.stdout.decode('utf8').strip() | python | {
"resource": ""
} |
q260273 | clean | validation | def clean():
"""Cleans up temporary resources
Tries to clean up:
1. The temporary update branch used during ``temple update``
2. The primary update branch used during ``temple update``
"""
temple.check.in_git_repo()
current_branch = _get_current_branch()
update_branch = temple.constants.UPDATE_BRANCH_NAME
temp_update_branch = temple.constants.TEMP_UPDATE_BRANCH_NAME
if current_branch in (update_branch, temp_update_branch):
err_msg = (
'You must change from the "{}" branch since it will be deleted during cleanup'
).format(current_branch)
raise temple.exceptions.InvalidCurrentBranchError(err_msg)
if temple.check._has_branch(update_branch):
temple.utils.shell('git branch -D {}'.format(update_branch))
if temple.check._has_branch(temp_update_branch):
temple.utils.shell('git branch -D {}'.format(temp_update_branch)) | python | {
"resource": ""
} |
q260274 | _cookiecutter_configs_have_changed | validation | def _cookiecutter_configs_have_changed(template, old_version, new_version):
"""Given an old version and new version, check if the cookiecutter.json files have changed
When the cookiecutter.json files change, it means the user will need to be prompted for
new context
Args:
template (str): The git SSH path to the template
old_version (str): The git SHA of the old version
new_version (str): The git SHA of the new version
Returns:
bool: True if the cookiecutter.json files have been changed in the old and new versions
"""
temple.check.is_git_ssh_path(template)
repo_path = temple.utils.get_repo_path(template)
github_client = temple.utils.GithubClient()
api = '/repos/{}/contents/cookiecutter.json'.format(repo_path)
old_config_resp = github_client.get(api, params={'ref': old_version})
old_config_resp.raise_for_status()
new_config_resp = github_client.get(api, params={'ref': new_version})
new_config_resp.raise_for_status()
return old_config_resp.json()['content'] != new_config_resp.json()['content'] | python | {
"resource": ""
} |
q260275 | _apply_template | validation | def _apply_template(template, target, *, checkout, extra_context):
"""Apply a template to a temporary directory and then copy results to target."""
with tempfile.TemporaryDirectory() as tempdir:
repo_dir = cc_main.cookiecutter(
template,
checkout=checkout,
no_input=True,
output_dir=tempdir,
extra_context=extra_context)
for item in os.listdir(repo_dir):
src = os.path.join(repo_dir, item)
dst = os.path.join(target, item)
if os.path.isdir(src):
if os.path.exists(dst):
shutil.rmtree(dst)
shutil.copytree(src, dst)
else:
if os.path.exists(dst):
os.remove(dst)
shutil.copy2(src, dst) | python | {
"resource": ""
} |
q260276 | up_to_date | validation | def up_to_date(version=None):
"""Checks if a temple project is up to date with the repo
Note that the `temple.constants.TEMPLE_ENV_VAR` is set to 'update' for the duration of this
function.
Args:
version (str, optional): Update against this git SHA or branch of the template
Returns:
boolean: True if up to date with ``version`` (or latest version), False otherwise
Raises:
`NotInGitRepoError`: When running outside of a git repo
`InvalidTempleProjectError`: When not inside a valid temple repository
"""
temple.check.in_git_repo()
temple.check.is_temple_project()
temple_config = temple.utils.read_temple_config()
old_template_version = temple_config['_version']
new_template_version = version or _get_latest_template_version(temple_config['_template'])
return new_template_version == old_template_version | python | {
"resource": ""
} |
q260277 | _needs_new_cc_config_for_update | validation | def _needs_new_cc_config_for_update(old_template, old_version, new_template, new_version):
"""
Given two templates and their respective versions, return True if a new cookiecutter
config needs to be obtained from the user
"""
if old_template != new_template:
return True
else:
return _cookiecutter_configs_have_changed(new_template,
old_version,
new_version) | python | {
"resource": ""
} |
q260278 | shell | validation | def shell(cmd, check=True, stdin=None, stdout=None, stderr=None):
"""Runs a subprocess shell with check=True by default"""
return subprocess.run(cmd, shell=True, check=check, stdin=stdin, stdout=stdout, stderr=stderr) | python | {
"resource": ""
} |
q260279 | read_temple_config | validation | def read_temple_config():
"""Reads the temple YAML configuration file in the repository"""
with open(temple.constants.TEMPLE_CONFIG_FILE) as temple_config_file:
return yaml.load(temple_config_file, Loader=yaml.SafeLoader) | python | {
"resource": ""
} |
q260280 | write_temple_config | validation | def write_temple_config(temple_config, template, version):
"""Writes the temple YAML configuration"""
with open(temple.constants.TEMPLE_CONFIG_FILE, 'w') as temple_config_file:
versioned_config = {
**temple_config,
**{'_version': version, '_template': template},
}
yaml.dump(versioned_config, temple_config_file, Dumper=yaml.SafeDumper) | python | {
"resource": ""
} |
q260281 | get_cookiecutter_config | validation | def get_cookiecutter_config(template, default_config=None, version=None):
"""Obtains the configuration used for cookiecutter templating
Args:
template: Path to the template
default_config (dict, optional): The default configuration
version (str, optional): The git SHA or branch to use when
checking out template. Defaults to latest version
Returns:
tuple: The cookiecutter repo directory and the config dict
"""
default_config = default_config or {}
config_dict = cc_config.get_user_config()
repo_dir, _ = cc_repository.determine_repo_dir(
template=template,
abbreviations=config_dict['abbreviations'],
clone_to_dir=config_dict['cookiecutters_dir'],
checkout=version,
no_input=True)
context_file = os.path.join(repo_dir, 'cookiecutter.json')
context = cc_generate.generate_context(
context_file=context_file,
default_context={**config_dict['default_context'], **default_config})
return repo_dir, cc_prompt.prompt_for_config(context) | python | {
"resource": ""
} |
q260282 | set_cmd_env_var | validation | def set_cmd_env_var(value):
"""Decorator that sets the temple command env var to value"""
def func_decorator(function):
@functools.wraps(function)
def wrapper(*args, **kwargs):
previous_cmd_env_var = os.getenv(temple.constants.TEMPLE_ENV_VAR)
os.environ[temple.constants.TEMPLE_ENV_VAR] = value
try:
ret_val = function(*args, **kwargs)
finally:
if previous_cmd_env_var is None:
del os.environ[temple.constants.TEMPLE_ENV_VAR]
else:
os.environ[temple.constants.TEMPLE_ENV_VAR] = previous_cmd_env_var
return ret_val
return wrapper
return func_decorator | python | {
"resource": ""
} |
q260283 | GithubClient._call_api | validation | def _call_api(self, verb, url, **request_kwargs):
"""Perform a github API call
Args:
verb (str): Can be "post", "put", or "get"
url (str): The base URL with a leading slash for Github API (v3)
auth (str or HTTPBasicAuth): A Github API token or a HTTPBasicAuth object
"""
api = 'https://api.github.com{}'.format(url)
auth_headers = {'Authorization': 'token {}'.format(self.api_token)}
headers = {**auth_headers, **request_kwargs.pop('headers', {})}
return getattr(requests, verb)(api, headers=headers, **request_kwargs) | python | {
"resource": ""
} |
q260284 | deploy | validation | def deploy(target):
"""Deploys the package and documentation.
Proceeds in the following steps:
1. Ensures proper environment variables are set and checks that we are on Circle CI
2. Tags the repository with the new version
3. Creates a standard distribution and a wheel
4. Updates version.py to have the proper version
5. Commits the ChangeLog, AUTHORS, and version.py file
6. Pushes to PyPI
7. Pushes the tags and newly committed files
Raises:
`EnvironmentError`:
- Not running on CircleCI
- `*_PYPI_USERNAME` and/or `*_PYPI_PASSWORD` environment variables
are missing
- Attempting to deploy to production from a branch that isn't master
"""
# Ensure proper environment
if not os.getenv(CIRCLECI_ENV_VAR): # pragma: no cover
raise EnvironmentError('Must be on CircleCI to run this script')
current_branch = os.getenv('CIRCLE_BRANCH')
if (target == 'PROD') and (current_branch != 'master'):
raise EnvironmentError((
'Refusing to deploy to production from branch {current_branch!r}. '
'Production deploys can only be made from master.'
).format(current_branch=current_branch))
if target in ('PROD', 'TEST'):
pypi_username = os.getenv('{target}_PYPI_USERNAME'.format(target=target))
pypi_password = os.getenv('{target}_PYPI_PASSWORD'.format(target=target))
else:
raise ValueError(
"Deploy target must be 'PROD' or 'TEST', got {target!r}.".format(target=target))
if not (pypi_username and pypi_password): # pragma: no cover
raise EnvironmentError((
"Missing '{target}_PYPI_USERNAME' and/or '{target}_PYPI_PASSWORD' "
"environment variables. These are required to push to PyPI."
).format(target=target))
# Twine requires these environment variables to be set. Subprocesses will
# inherit these when we invoke them, so no need to pass them on the command
# line. We want to avoid that in case something's logging each command run.
os.environ['TWINE_USERNAME'] = pypi_username
os.environ['TWINE_PASSWORD'] = pypi_password
# Set up git on circle to push to the current branch
_shell('git config --global user.email "oss@cloverhealth.com"')
_shell('git config --global user.name "Circle CI"')
_shell('git config push.default current')
# Obtain the version to deploy
ret = _shell('make version', stdout=subprocess.PIPE)
version = ret.stdout.decode('utf-8').strip()
print('Deploying version {version!r}...'.format(version=version))
# Tag the version
_shell('git tag -f -a {version} -m "Version {version}"'.format(version=version))
# Update the version
_shell(
'sed -i.bak "s/^__version__ = .*/__version__ = {version!r}/" */version.py'.format(
version=version))
# Create a standard distribution and a wheel
_shell('python setup.py sdist bdist_wheel')
# Add the updated ChangeLog and AUTHORS
_shell('git add ChangeLog AUTHORS */version.py')
# Start the commit message with "Merge" so that PBR will ignore it in the
# ChangeLog. Use [skip ci] to ensure CircleCI doesn't recursively deploy.
_shell('git commit --no-verify -m "Merge autogenerated files [skip ci]"')
# Push the distributions to PyPI.
_pypi_push('dist')
# Push the tag and AUTHORS / ChangeLog after successful PyPI deploy
_shell('git push --follow-tags')
print('Deployment complete. Latest version is {version}.'.format(version=version)) | python | {
"resource": ""
} |
q260285 | DSStoreChecker.run | validation | def run(self):
"""
Finds .DS_Store files into path
"""
filename = ".DS_Store"
command = "find {path} -type f -name \"{filename}\" ".format(path = self.path, filename = filename)
cmd = CommandHelper(command)
cmd.execute()
files = cmd.output.split("\n")
for f in files:
if not f.endswith(filename):
continue
# Ignore paths excluded
rel_path = f.replace(self.path, "")
if rel_path.startswith(tuple(self.CONFIG['exclude_paths'])):
continue
issue = Issue()
issue.name = "File .DS_Store detected"
issue.potential = False
issue.severity = Issue.SEVERITY_LOW
# Get only relative path
issue.file = rel_path
self.saveIssue(issue) | python | {
"resource": ""
} |
q260286 | HttpReport.run | validation | def run(self):
"""
Method executed dynamically by framework. This method will do a http request to
endpoint setted into config file with the issues and other data.
"""
options = {}
if bool(self.config['use_proxy']):
options['proxies'] = {"http": self.config['proxy'], "https": self.config['proxy']}
options["url"] = self.config['url']
options["data"] = {"issues": json.dumps(map(lambda x: x.__todict__(), self.issues))}
if 'get' == self.config['method'].lower():
requests.get(**options)
else:
requests.post(**options) | python | {
"resource": ""
} |
q260287 | GenericChecker.path | validation | def path(self, value):
"""
Setter for 'path' property
Args:
value (str): Absolute path to scan
"""
if not value.endswith('/'):
self._path = '{v}/'.format(v=value)
else:
self._path = value | python | {
"resource": ""
} |
q260288 | GenericChecker.parseConfig | validation | def parseConfig(cls, value):
"""
Parse the config values
Args:
value (dict): Dictionary which contains the checker config
Returns:
dict: The checker config with parsed values
"""
if 'enabled' in value:
value['enabled'] = bool(value['enabled'])
if 'exclude_paths' in value:
value['exclude_paths'] = [n.strip() for n in ast.literal_eval(value['exclude_paths'])]
return value | python | {
"resource": ""
} |
q260289 | CommandHelper.getOSName | validation | def getOSName(self):
"""
Get the OS name. If OS is linux, returns the Linux distribution name
Returns:
str: OS name
"""
_system = platform.system()
if _system in [self.__class__.OS_WINDOWS, self.__class__.OS_MAC, self.__class__.OS_LINUX]:
if _system == self.__class__.OS_LINUX:
_dist = platform.linux_distribution()[0]
if _dist.lower() == self.__class__.OS_UBUNTU.lower():
return self.__class__.OS_UBUNTU
elif _dist.lower() == self.__class__.OS_DEBIAN.lower():
return self.__class__.OS_DEBIAN
elif _dist.lower() == self.__class__.OS_CENTOS.lower():
return self.__class__.OS_CENTOS
elif _dist.lower() == self.__class__.OS_REDHAT.lower():
return self.__class__.OS_REDHAT
elif _dist.lower() == self.__class__.OS_KALI.lower():
return self.__class__.OS_KALI
return _system
else:
return None | python | {
"resource": ""
} |
q260290 | CommandHelper.execute | validation | def execute(self, shell = True):
"""
Executes the command setted into class
Args:
shell (boolean): Set True if command is a shell command. Default: True
"""
process = Popen(self.command, stdout=PIPE, stderr=PIPE, shell=shell)
self.output, self.errors = process.communicate() | python | {
"resource": ""
} |
q260291 | AtomShieldsScanner._debug | validation | def _debug(message, color=None, attrs=None):
"""
Print a message if the class attribute 'verbose' is enabled
Args:
message (str): Message to print
"""
if attrs is None:
attrs = []
if color is not None:
print colored(message, color, attrs=attrs)
else:
if len(attrs) > 0:
print colored(message, "white", attrs=attrs)
else:
print message | python | {
"resource": ""
} |
q260292 | AtomShieldsScanner.setup | validation | def setup():
"""
Creates required directories and copy checkers and reports.
"""
# # Check if dir is writable
# if not os.access(AtomShieldsScanner.HOME, os.W_OK):
# AtomShieldsScanner.HOME = os.path.expanduser("~/.atomshields")
# AtomShieldsScanner.CHECKERS_DIR = os.path.join(AtomShieldsScanner.HOME, "checkers")
# AtomShieldsScanner.REPORTS_DIR = os.path.join(AtomShieldsScanner.HOME, "reports")
if not os.path.isdir(AtomShieldsScanner.CHECKERS_DIR):
os.makedirs(AtomShieldsScanner.CHECKERS_DIR)
if not os.path.isdir(AtomShieldsScanner.REPORTS_DIR):
os.makedirs(AtomShieldsScanner.REPORTS_DIR)
# Copy all checkers
for f in AtomShieldsScanner._getFiles(os.path.join(os.path.dirname(os.path.realpath(__file__)), "checkers"), "*.py"):
AtomShieldsScanner.installChecker(f)
# Copy all reports
for f in AtomShieldsScanner._getFiles(os.path.join(os.path.dirname(os.path.realpath(__file__)), "reports"), "*.py"):
AtomShieldsScanner.installReport(f)
AtomShieldsScanner._executeMassiveMethod(path=AtomShieldsScanner.CHECKERS_DIR, method="install", args={})
config_dir = os.path.dirname(AtomShieldsScanner.CONFIG_PATH)
if not os.path.isdir(config_dir):
os.makedirs(config_dir) | python | {
"resource": ""
} |
q260293 | AtomShieldsScanner._addConfig | validation | def _addConfig(instance, config, parent_section):
"""
Writes a section for a plugin.
Args:
instance (object): Class instance for plugin
config (object): Object (ConfigParser) which the current config
parent_section (str): Parent section for plugin. Usually 'checkers' or 'reports'
"""
try:
section_name = "{p}/{n}".format(p = parent_section, n=instance.NAME.lower())
config.add_section(section_name)
for k in instance.CONFIG.keys():
config.set(section_name, k, instance.CONFIG[k])
except Exception as e:
print "[!] %s" % e | python | {
"resource": ""
} |
q260294 | AtomShieldsScanner.getConfig | validation | def getConfig(self, section = None):
"""
Returns a dictionary which contains the current config. If a section is setted,
only will returns the section config
Args:
section (str): (Optional) Section name.
Returns:
dict: Representation of current config
"""
data = {}
if section is None:
for s in self.config.sections():
if '/' in s:
# Subsection
parent, _s = s.split('/')
data[parent][_s] = dict(self.config.items(s))
else:
data[s] = dict(self.config.items(s))
else:
# Only one section will be returned
data = dict(self.config.items(section))
return data | python | {
"resource": ""
} |
q260295 | AtomShieldsScanner._getClassInstance | validation | def _getClassInstance(path, args=None):
"""
Returns a class instance from a .py file.
Args:
path (str): Absolute path to .py file
args (dict): Arguments passed via class constructor
Returns:
object: Class instance or None
"""
if not path.endswith(".py"):
return None
if args is None:
args = {}
classname = AtomShieldsScanner._getClassName(path)
basename = os.path.basename(path).replace(".py", "")
sys.path.append(os.path.dirname(path))
try:
mod = __import__(basename, globals(), locals(), [classname], -1)
class_ = getattr(mod, classname)
instance = class_(**args)
except Exception as e:
AtomShieldsScanner._debug("[!] %s" % e)
return None
finally:
sys.path.remove(os.path.dirname(path))
return instance | python | {
"resource": ""
} |
q260296 | AtomShieldsScanner._executeMassiveMethod | validation | def _executeMassiveMethod(path, method, args=None, classArgs = None):
"""
Execute an specific method for each class instance located in path
Args:
path (str): Absolute path which contains the .py files
method (str): Method to execute into class instance
Returns:
dict: Dictionary which contains the response for every class instance.
The dictionary keys are the value of 'NAME' class variable.
"""
response = {}
if args is None:
args = {}
if classArgs is None:
classArgs = {}
sys.path.append(path)
exclude = ["__init__.py", "base.py"]
for f in AtomShieldsScanner._getFiles(path, "*.py", exclude=exclude):
try:
instance = AtomShieldsScanner._getClassInstance(path = f, args = classArgs)
if instance is not None:
if callable(method):
args["instance"] = instance
output = method(**args)
response[instance.__class__.NAME] = output
else:
if hasattr(instance, method):
output = getattr(instance, method)(**args)
response[instance.__class__.NAME] = output
else:
continue
except Exception as e:
AtomShieldsScanner._debug("[!] %s" % e)
sys.path.remove(path)
return response | python | {
"resource": ""
} |
q260297 | AtomShieldsScanner.run | validation | def run(self):
"""
Run a scan in the path setted.
"""
self.checkProperties()
self.debug("[*] Iniciando escaneo de AtomShields con las siguientes propiedades. . . ")
self.showScanProperties()
self.loadConfig()
# Init time counter
init_ts = datetime.now()
# Execute plugins
cwd = os.getcwd()
os.chdir(self.path)
issues = self.executeCheckers()
os.chdir(cwd)
# Finish time counter
end_ts = datetime.now()
duration = '{}'.format(end_ts - init_ts)
# Process and set issues
for plugin in issues.keys():
value = issues[plugin]
if isinstance(value, list):
map(self.saveIssue, value)
else:
self.saveIssue(value)
# Execute reports
print ""
self.executeReports()
# Print summary output.
self.debug("")
self.debug("Duration: {t}".format(t=duration))
self.showSummary()
return self.issues | python | {
"resource": ""
} |
q260298 | RetireJSChecker.install | validation | def install():
"""
Install all the dependences
"""
cmd = CommandHelper()
cmd.install("npm")
cmd = CommandHelper()
cmd.install("nodejs-legacy")
# Install retre with npm
cmd = CommandHelper()
cmd.command = "npm install -g retire"
cmd.execute()
if cmd.errors:
from termcolor import colored
print colored(cmd.errors, "red")
else:
print cmd.output | python | {
"resource": ""
} |
q260299 | Issue.potential | validation | def potential(self, value):
"""
Setter for 'potential' property
Args:
value (bool): True if a potential is required. False else
"""
if value:
self._potential = True
else:
self._potential = False | python | {
"resource": ""
} |
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