anchor stringlengths 16 95 | positive stringlengths 87 6.25k | negative stringlengths 87 6.4k |
|---|---|---|
generate maps between entities in python | def _generate_key_map(entity_list, key, entity_class):
""" Helper method to generate map from key to entity object for given list of dicts.
Args:
entity_list: List consisting of dict.
key: Key in each dict which will be key in the map.
entity_class: Class representing the entity.
Returns... | def _merge_maps(m1, m2):
"""merge two Mapping objects, keeping the type of the first mapping"""
return type(m1)(chain(m1.items(), m2.items())) |
generate maps between entities in python | def _generate_key_map(entity_list, key, entity_class):
""" Helper method to generate map from key to entity object for given list of dicts.
Args:
entity_list: List consisting of dict.
key: Key in each dict which will be key in the map.
entity_class: Class representing the entity.
Returns... | def get_edge_relations(graph: BELGraph) -> Mapping[Tuple[BaseEntity, BaseEntity], Set[str]]:
"""Build a dictionary of {node pair: set of edge types}."""
return group_dict_set(
((u, v), d[RELATION])
for u, v, d in graph.edges(data=True)
) |
generate maps between entities in python | def _generate_key_map(entity_list, key, entity_class):
""" Helper method to generate map from key to entity object for given list of dicts.
Args:
entity_list: List consisting of dict.
key: Key in each dict which will be key in the map.
entity_class: Class representing the entity.
Returns... | def map_with_obj(f, dct):
"""
Implementation of Ramda's mapObjIndexed without the final argument.
This returns the original key with the mapped value. Use map_key_values to modify the keys too
:param f: Called with a key and value
:param dct:
:return {dict}: Keyed by the original key, va... |
generate maps between entities in python | def _generate_key_map(entity_list, key, entity_class):
""" Helper method to generate map from key to entity object for given list of dicts.
Args:
entity_list: List consisting of dict.
key: Key in each dict which will be key in the map.
entity_class: Class representing the entity.
Returns... | def __add_method(m: lmap.Map, key: T, method: Method) -> lmap.Map:
"""Swap the methods atom to include method with key."""
return m.assoc(key, method) |
generate maps between entities in python | def _generate_key_map(entity_list, key, entity_class):
""" Helper method to generate map from key to entity object for given list of dicts.
Args:
entity_list: List consisting of dict.
key: Key in each dict which will be key in the map.
entity_class: Class representing the entity.
Returns... | def map_parameters(cls, params):
"""Maps parameters to form field names"""
d = {}
for k, v in six.iteritems(params):
d[cls.FIELD_MAP.get(k.lower(), k)] = v
return d |
python how to get dict intersection | def intersect(d1, d2):
"""Intersect dictionaries d1 and d2 by key *and* value."""
return dict((k, d1[k]) for k in d1 if k in d2 and d1[k] == d2[k]) | def compare_dict(da, db):
"""
Compare differencs from two dicts
"""
sa = set(da.items())
sb = set(db.items())
diff = sa & sb
return dict(sa - diff), dict(sb - diff) |
python how to get dict intersection | def intersect(d1, d2):
"""Intersect dictionaries d1 and d2 by key *and* value."""
return dict((k, d1[k]) for k in d1 if k in d2 and d1[k] == d2[k]) | def compare(dicts):
"""Compare by iteration"""
common_members = {}
common_keys = reduce(lambda x, y: x & y, map(dict.keys, dicts))
for k in common_keys:
common_members[k] = list(
reduce(lambda x, y: x & y, [set(d[k]) for d in dicts]))
return common_members |
python how to get dict intersection | def intersect(d1, d2):
"""Intersect dictionaries d1 and d2 by key *and* value."""
return dict((k, d1[k]) for k in d1 if k in d2 and d1[k] == d2[k]) | def _calc_overlap_count(
markers1: dict,
markers2: dict,
):
"""Calculate overlap count between the values of two dictionaries
Note: dict values must be sets
"""
overlaps=np.zeros((len(markers1), len(markers2)))
j=0
for marker_group in markers1:
tmp = [len(markers2[i].intersecti... |
python how to get dict intersection | def intersect(d1, d2):
"""Intersect dictionaries d1 and d2 by key *and* value."""
return dict((k, d1[k]) for k in d1 if k in d2 and d1[k] == d2[k]) | def is_same_dict(d1, d2):
"""Test two dictionary is equal on values. (ignore order)
"""
for k, v in d1.items():
if isinstance(v, dict):
is_same_dict(v, d2[k])
else:
assert d1[k] == d2[k]
for k, v in d2.items():
if isinstance(v, dict):
is_same_... |
python how to get dict intersection | def intersect(d1, d2):
"""Intersect dictionaries d1 and d2 by key *and* value."""
return dict((k, d1[k]) for k in d1 if k in d2 and d1[k] == d2[k]) | def flattened_nested_key_indices(nested_dict):
"""
Combine the outer and inner keys of nested dictionaries into a single
ordering.
"""
outer_keys, inner_keys = collect_nested_keys(nested_dict)
combined_keys = list(sorted(set(outer_keys + inner_keys)))
return {k: i for (i, k) in enumerate(com... |
python how to get the index of a rank | def rank(idx, dim):
"""Calculate the index rank according to Bertran's notation."""
idxm = multi_index(idx, dim)
out = 0
while idxm[-1:] == (0,):
out += 1
idxm = idxm[:-1]
return out | def zrank(self, name, value):
"""
Returns the rank of the element.
:param name: str the name of the redis key
:param value: the element in the sorted set
"""
with self.pipe as pipe:
value = self.valueparse.encode(value)
return pipe.zrank(self.... |
python how to get the index of a rank | def rank(idx, dim):
"""Calculate the index rank according to Bertran's notation."""
idxm = multi_index(idx, dim)
out = 0
while idxm[-1:] == (0,):
out += 1
idxm = idxm[:-1]
return out | def get_index_nested(x, i):
"""
Description:
Returns the first index of the array (vector) x containing the value i.
Parameters:
x: one-dimensional array
i: search value
"""
for ind in range(len(x)):
if i == x[ind]:
return ind
return -1 |
python how to get the index of a rank | def rank(idx, dim):
"""Calculate the index rank according to Bertran's notation."""
idxm = multi_index(idx, dim)
out = 0
while idxm[-1:] == (0,):
out += 1
idxm = idxm[:-1]
return out | def sorted_index(values, x):
"""
For list, values, returns the index location of element x. If x does not exist will raise an error.
:param values: list
:param x: item
:return: integer index
"""
i = bisect_left(values, x)
j = bisect_right(values, x)
return values[i:j].index(x) + i |
python how to get the index of a rank | def rank(idx, dim):
"""Calculate the index rank according to Bertran's notation."""
idxm = multi_index(idx, dim)
out = 0
while idxm[-1:] == (0,):
out += 1
idxm = idxm[:-1]
return out | def kindex(matrix, k):
""" Returns indices to select the kth nearest neighbour"""
ix = (np.arange(len(matrix)), matrix.argsort(axis=0)[k])
return ix |
python how to get the index of a rank | def rank(idx, dim):
"""Calculate the index rank according to Bertran's notation."""
idxm = multi_index(idx, dim)
out = 0
while idxm[-1:] == (0,):
out += 1
idxm = idxm[:-1]
return out | def get_list_index(lst, index_or_name):
"""
Return the index of an element in the list.
Args:
lst (list): The list.
index_or_name (int or str): The value of the reference element, or directly its numeric index.
Returns:
(int) The index of the element in the list.
"""
if... |
generate string from array python | def bitsToString(arr):
"""Returns a string representing a numpy array of 0's and 1's"""
s = array('c','.'*len(arr))
for i in xrange(len(arr)):
if arr[i] == 1:
s[i]='*'
return s | def toStringArray(name, a, width = 0):
"""
Returns an array (any sequence of floats, really) as a string.
"""
string = name + ": "
cnt = 0
for i in a:
string += "%4.2f " % i
if width > 0 and (cnt + 1) % width == 0:
string += '\n'
cnt += 1
return string |
generate string from array python | def bitsToString(arr):
"""Returns a string representing a numpy array of 0's and 1's"""
s = array('c','.'*len(arr))
for i in xrange(len(arr)):
if arr[i] == 1:
s[i]='*'
return s | def string_list_to_array(l):
"""
Turns a Python unicode string list into a Java String array.
:param l: the string list
:type: list
:rtype: java string array
:return: JB_Object
"""
result = javabridge.get_env().make_object_array(len(l), javabridge.get_env().find_class("java/lang/String"... |
generate string from array python | def bitsToString(arr):
"""Returns a string representing a numpy array of 0's and 1's"""
s = array('c','.'*len(arr))
for i in xrange(len(arr)):
if arr[i] == 1:
s[i]='*'
return s | def generate_random_string(chars=7):
"""
:param chars:
:return:
"""
return u"".join(random.sample(string.ascii_letters * 2 + string.digits, chars)) |
generate string from array python | def bitsToString(arr):
"""Returns a string representing a numpy array of 0's and 1's"""
s = array('c','.'*len(arr))
for i in xrange(len(arr)):
if arr[i] == 1:
s[i]='*'
return s | def bytes_to_c_array(data):
"""
Make a C array using the given string.
"""
chars = [
"'{}'".format(encode_escape(i))
for i in decode_escape(data)
]
return ', '.join(chars) + ', 0' |
generate string from array python | def bitsToString(arr):
"""Returns a string representing a numpy array of 0's and 1's"""
s = array('c','.'*len(arr))
for i in xrange(len(arr)):
if arr[i] == 1:
s[i]='*'
return s | def gen_random_string(str_len):
""" generate random string with specified length
"""
return ''.join(
random.choice(string.ascii_letters + string.digits) for _ in range(str_len)) |
python how to get the index of minimum value in an array | def find_nearest_index(arr, value):
"""For a given value, the function finds the nearest value
in the array and returns its index."""
arr = np.array(arr)
index = (abs(arr-value)).argmin()
return index | def last_location_of_minimum(x):
"""
Returns the last location of the minimal value of x.
The position is calculated relatively to the length of x.
:param x: the time series to calculate the feature of
:type x: numpy.ndarray
:return: the value of this feature
:return type: float
"""
... |
python how to get the index of minimum value in an array | def find_nearest_index(arr, value):
"""For a given value, the function finds the nearest value
in the array and returns its index."""
arr = np.array(arr)
index = (abs(arr-value)).argmin()
return index | def fn_min(self, a, axis=None):
"""
Return the minimum of an array, ignoring any NaNs.
:param a: The array.
:return: The minimum value of the array.
"""
return numpy.nanmin(self._to_ndarray(a), axis=axis) |
python how to get the index of minimum value in an array | def find_nearest_index(arr, value):
"""For a given value, the function finds the nearest value
in the array and returns its index."""
arr = np.array(arr)
index = (abs(arr-value)).argmin()
return index | def index_nearest(value, array):
"""
expects a _n.array
returns the global minimum of (value-array)^2
"""
a = (array-value)**2
return index(a.min(), a) |
python how to get the index of minimum value in an array | def find_nearest_index(arr, value):
"""For a given value, the function finds the nearest value
in the array and returns its index."""
arr = np.array(arr)
index = (abs(arr-value)).argmin()
return index | def min_values(args):
""" Return possible range for min function. """
return Interval(min(x.low for x in args), min(x.high for x in args)) |
python how to get the index of minimum value in an array | def find_nearest_index(arr, value):
"""For a given value, the function finds the nearest value
in the array and returns its index."""
arr = np.array(arr)
index = (abs(arr-value)).argmin()
return index | def min(self):
"""
:returns the minimum of the column
"""
res = self._qexec("min(%s)" % self._name)
if len(res) > 0:
self._min = res[0][0]
return self._min |
get array with longest length python | def longest_run(da, dim='time'):
"""Return the length of the longest consecutive run of True values.
Parameters
----------
arr : N-dimensional array (boolean)
Input array
dim : Xarray dimension (default = 'time')
Dimension along which to calculate consecutive run... | def longest_run_1d(arr):
"""Return the length of the longest consecutive run of identical values.
Parameters
----------
arr : bool array
Input array
Returns
-------
int
Length of longest run.
"""
v, rl = rle_1d(arr)[:2]
return np.where(v, rl, 0).max() |
get array with longest length python | def longest_run(da, dim='time'):
"""Return the length of the longest consecutive run of True values.
Parameters
----------
arr : N-dimensional array (boolean)
Input array
dim : Xarray dimension (default = 'time')
Dimension along which to calculate consecutive run... | def _prm_get_longest_stringsize(string_list):
""" Returns the longest string size for a string entry across data."""
maxlength = 1
for stringar in string_list:
if isinstance(stringar, np.ndarray):
if stringar.ndim > 0:
for string in stringar.ravel... |
get array with longest length python | def longest_run(da, dim='time'):
"""Return the length of the longest consecutive run of True values.
Parameters
----------
arr : N-dimensional array (boolean)
Input array
dim : Xarray dimension (default = 'time')
Dimension along which to calculate consecutive run... | def find_largest_contig(contig_lengths_dict):
"""
Determine the largest contig for each strain
:param contig_lengths_dict: dictionary of strain name: reverse-sorted list of all contig lengths
:return: longest_contig_dict: dictionary of strain name: longest contig
"""
# Initialise the dictionary
... |
get array with longest length python | def longest_run(da, dim='time'):
"""Return the length of the longest consecutive run of True values.
Parameters
----------
arr : N-dimensional array (boolean)
Input array
dim : Xarray dimension (default = 'time')
Dimension along which to calculate consecutive run... | def get_longest_orf(orfs):
"""Find longest ORF from the given list of ORFs."""
sorted_orf = sorted(orfs, key=lambda x: len(x['sequence']), reverse=True)[0]
return sorted_orf |
get array with longest length python | def longest_run(da, dim='time'):
"""Return the length of the longest consecutive run of True values.
Parameters
----------
arr : N-dimensional array (boolean)
Input array
dim : Xarray dimension (default = 'time')
Dimension along which to calculate consecutive run... | def get_dimension_array(array):
"""
Get dimension of an array getting the number of rows and the max num of
columns.
"""
if all(isinstance(el, list) for el in array):
result = [len(array), len(max([x for x in array], key=len,))]
# elif array and isinstance(array, list):
else:
... |
python how to make an iterable variable | def force_iterable(f):
"""Will make any functions return an iterable objects by wrapping its result in a list."""
def wrapper(*args, **kwargs):
r = f(*args, **kwargs)
if hasattr(r, '__iter__'):
return r
else:
return [r]
return wrapper | def __init__(self, iterable):
"""Initialize the cycle with some iterable."""
self._values = []
self._iterable = iterable
self._initialized = False
self._depleted = False
self._offset = 0 |
python how to make an iterable variable | def force_iterable(f):
"""Will make any functions return an iterable objects by wrapping its result in a list."""
def wrapper(*args, **kwargs):
r = f(*args, **kwargs)
if hasattr(r, '__iter__'):
return r
else:
return [r]
return wrapper | def fromiterable(cls, itr):
"""Initialize from iterable"""
x, y, z = itr
return cls(x, y, z) |
python how to make an iterable variable | def force_iterable(f):
"""Will make any functions return an iterable objects by wrapping its result in a list."""
def wrapper(*args, **kwargs):
r = f(*args, **kwargs)
if hasattr(r, '__iter__'):
return r
else:
return [r]
return wrapper | def ensure_iterable(inst):
"""
Wraps scalars or string types as a list, or returns the iterable instance.
"""
if isinstance(inst, string_types):
return [inst]
elif not isinstance(inst, collections.Iterable):
return [inst]
else:
return inst |
python how to make an iterable variable | def force_iterable(f):
"""Will make any functions return an iterable objects by wrapping its result in a list."""
def wrapper(*args, **kwargs):
r = f(*args, **kwargs)
if hasattr(r, '__iter__'):
return r
else:
return [r]
return wrapper | def concat(cls, iterables):
"""
Similar to #itertools.chain.from_iterable().
"""
def generator():
for it in iterables:
for element in it:
yield element
return cls(generator()) |
python how to make an iterable variable | def force_iterable(f):
"""Will make any functions return an iterable objects by wrapping its result in a list."""
def wrapper(*args, **kwargs):
r = f(*args, **kwargs)
if hasattr(r, '__iter__'):
return r
else:
return [r]
return wrapper | def _varargs_to_iterable_method(func):
"""decorator to convert a *args method to one taking a iterable"""
def wrapped(self, iterable, **kwargs):
return func(self, *iterable, **kwargs)
return wrapped |
get distinct items in list python | def unique(input_list):
"""
Return a list of unique items (similar to set functionality).
Parameters
----------
input_list : list
A list containg some items that can occur more than once.
Returns
-------
list
A list with only unique occurances of an item.
"""
o... | def distinct(xs):
"""Get the list of distinct values with preserving order."""
# don't use collections.OrderedDict because we do support Python 2.6
seen = set()
return [x for x in xs if x not in seen and not seen.add(x)] |
get distinct items in list python | def unique(input_list):
"""
Return a list of unique items (similar to set functionality).
Parameters
----------
input_list : list
A list containg some items that can occur more than once.
Returns
-------
list
A list with only unique occurances of an item.
"""
o... | def uniqued(iterable):
"""Return unique list of ``iterable`` items preserving order.
>>> uniqued('spameggs')
['s', 'p', 'a', 'm', 'e', 'g']
"""
seen = set()
return [item for item in iterable if item not in seen and not seen.add(item)] |
get distinct items in list python | def unique(input_list):
"""
Return a list of unique items (similar to set functionality).
Parameters
----------
input_list : list
A list containg some items that can occur more than once.
Returns
-------
list
A list with only unique occurances of an item.
"""
o... | def uniqued(iterable):
"""Return unique list of items preserving order.
>>> uniqued([3, 2, 1, 3, 2, 1, 0])
[3, 2, 1, 0]
"""
seen = set()
add = seen.add
return [i for i in iterable if i not in seen and not add(i)] |
get distinct items in list python | def unique(input_list):
"""
Return a list of unique items (similar to set functionality).
Parameters
----------
input_list : list
A list containg some items that can occur more than once.
Returns
-------
list
A list with only unique occurances of an item.
"""
o... | def unique_items(seq):
"""Return the unique items from iterable *seq* (in order)."""
seen = set()
return [x for x in seq if not (x in seen or seen.add(x))] |
get distinct items in list python | def unique(input_list):
"""
Return a list of unique items (similar to set functionality).
Parameters
----------
input_list : list
A list containg some items that can occur more than once.
Returns
-------
list
A list with only unique occurances of an item.
"""
o... | def unique_element(ll):
""" returns unique elements from a list preserving the original order """
seen = {}
result = []
for item in ll:
if item in seen:
continue
seen[item] = 1
result.append(item)
return result |
get factors of a number python | def _factor_generator(n):
"""
From a given natural integer, returns the prime factors and their multiplicity
:param n: Natural integer
:return:
"""
p = prime_factors(n)
factors = {}
for p1 in p:
try:
factors[p1] += 1
except KeyError:
factors[p1] = ... | def computeFactorial(n):
"""
computes factorial of n
"""
sleep_walk(10)
ret = 1
for i in range(n):
ret = ret * (i + 1)
return ret |
get factors of a number python | def _factor_generator(n):
"""
From a given natural integer, returns the prime factors and their multiplicity
:param n: Natural integer
:return:
"""
p = prime_factors(n)
factors = {}
for p1 in p:
try:
factors[p1] += 1
except KeyError:
factors[p1] = ... | def factorial(n, mod=None):
"""Calculates factorial iteratively.
If mod is not None, then return (n! % mod)
Time Complexity - O(n)"""
if not (isinstance(n, int) and n >= 0):
raise ValueError("'n' must be a non-negative integer.")
if mod is not None and not (isinstance(mod, int) and mod > 0):... |
get factors of a number python | def _factor_generator(n):
"""
From a given natural integer, returns the prime factors and their multiplicity
:param n: Natural integer
:return:
"""
p = prime_factors(n)
factors = {}
for p1 in p:
try:
factors[p1] += 1
except KeyError:
factors[p1] = ... | def factors(n):
"""
Computes all the integer factors of the number `n`
Example:
>>> # ENABLE_DOCTEST
>>> from utool.util_alg import * # NOQA
>>> import utool as ut
>>> result = sorted(ut.factors(10))
>>> print(result)
[1, 2, 5, 10]
References:
h... |
get factors of a number python | def _factor_generator(n):
"""
From a given natural integer, returns the prime factors and their multiplicity
:param n: Natural integer
:return:
"""
p = prime_factors(n)
factors = {}
for p1 in p:
try:
factors[p1] += 1
except KeyError:
factors[p1] = ... | def getPrimeFactors(n):
"""
Get all the prime factor of given integer
@param n integer
@return list [1, ..., n]
"""
lo = [1]
n2 = n // 2
k = 2
for k in range(2, n2 + 1):
if (n // k)*k == n:
lo.append(k)
return lo + [n, ] |
get factors of a number python | def _factor_generator(n):
"""
From a given natural integer, returns the prime factors and their multiplicity
:param n: Natural integer
:return:
"""
p = prime_factors(n)
factors = {}
for p1 in p:
try:
factors[p1] += 1
except KeyError:
factors[p1] = ... | def is_power_of_2(num):
"""Return whether `num` is a power of two"""
log = math.log2(num)
return int(log) == float(log) |
python how to remove elements from an iterated list | def unique(seq):
"""Return the unique elements of a collection even if those elements are
unhashable and unsortable, like dicts and sets"""
cleaned = []
for each in seq:
if each not in cleaned:
cleaned.append(each)
return cleaned | def remove_elements(target, indices):
"""Remove multiple elements from a list and return result.
This implementation is faster than the alternative below.
Also note the creation of a new list to avoid altering the
original. We don't have any current use for the original
intact list, but may in the f... |
python how to remove elements from an iterated list | def unique(seq):
"""Return the unique elements of a collection even if those elements are
unhashable and unsortable, like dicts and sets"""
cleaned = []
for each in seq:
if each not in cleaned:
cleaned.append(each)
return cleaned | def without(seq1, seq2):
r"""Return a list with all elements in `seq2` removed from `seq1`, order
preserved.
Examples:
>>> without([1,2,3,1,2], [1])
[2, 3, 2]
"""
if isSet(seq2): d2 = seq2
else: d2 = set(seq2)
return [elt for elt in seq1 if elt not in d2] |
python how to remove elements from an iterated list | def unique(seq):
"""Return the unique elements of a collection even if those elements are
unhashable and unsortable, like dicts and sets"""
cleaned = []
for each in seq:
if each not in cleaned:
cleaned.append(each)
return cleaned | def dedup(seq):
"""Remove duplicates from a list while keeping order."""
seen = set()
for item in seq:
if item not in seen:
seen.add(item)
yield item |
python how to remove elements from an iterated list | def unique(seq):
"""Return the unique elements of a collection even if those elements are
unhashable and unsortable, like dicts and sets"""
cleaned = []
for each in seq:
if each not in cleaned:
cleaned.append(each)
return cleaned | def dedup_list(l):
"""Given a list (l) will removing duplicates from the list,
preserving the original order of the list. Assumes that
the list entrie are hashable."""
dedup = set()
return [ x for x in l if not (x in dedup or dedup.add(x))] |
python how to remove elements from an iterated list | def unique(seq):
"""Return the unique elements of a collection even if those elements are
unhashable and unsortable, like dicts and sets"""
cleaned = []
for each in seq:
if each not in cleaned:
cleaned.append(each)
return cleaned | def rm_empty_indices(*args):
"""
Remove unwanted list indices. First argument is the list
of indices to remove. Other elements are the lists
to trim.
"""
rm_inds = args[0]
if not rm_inds:
return args[1:]
keep_inds = [i for i in range(len(args[1])) if i not in rm_inds]
retu... |
python how to remove spaces and add hashtag | def _add_hash(source):
"""Add a leading hash '#' at the beginning of every line in the source."""
source = '\n'.join('# ' + line.rstrip()
for line in source.splitlines())
return source | def do_striptags(value):
"""Strip SGML/XML tags and replace adjacent whitespace by one space.
"""
if hasattr(value, '__html__'):
value = value.__html__()
return Markup(unicode(value)).striptags() |
python how to remove spaces and add hashtag | def _add_hash(source):
"""Add a leading hash '#' at the beginning of every line in the source."""
source = '\n'.join('# ' + line.rstrip()
for line in source.splitlines())
return source | def slugify(string):
"""
Removes non-alpha characters, and converts spaces to hyphens. Useful for making file names.
Source: http://stackoverflow.com/questions/5574042/string-slugification-in-python
"""
string = re.sub('[^\w .-]', '', string)
string = string.replace(" ", "-")
return string |
python how to remove spaces and add hashtag | def _add_hash(source):
"""Add a leading hash '#' at the beginning of every line in the source."""
source = '\n'.join('# ' + line.rstrip()
for line in source.splitlines())
return source | def strip_tweet(text, remove_url=True):
"""Strip tweet message.
This method removes mentions strings and urls(optional).
:param text: tweet message
:type text: :class:`str`
:param remove_url: Remove urls. default :const:`True`.
:type remove_url: :class:`boolean`
:returns: Striped tweet m... |
python how to remove spaces and add hashtag | def _add_hash(source):
"""Add a leading hash '#' at the beginning of every line in the source."""
source = '\n'.join('# ' + line.rstrip()
for line in source.splitlines())
return source | def sanitize_word(s):
"""Remove non-alphanumerical characters from metric word.
And trim excessive underscores.
"""
s = re.sub('[^\w-]+', '_', s)
s = re.sub('__+', '_', s)
return s.strip('_') |
python how to remove spaces and add hashtag | def _add_hash(source):
"""Add a leading hash '#' at the beginning of every line in the source."""
source = '\n'.join('# ' + line.rstrip()
for line in source.splitlines())
return source | def urlize_twitter(text):
"""
Replace #hashtag and @username references in a tweet with HTML text.
"""
html = TwitterText(text).autolink.auto_link()
return mark_safe(html.replace(
'twitter.com/search?q=', 'twitter.com/search/realtime/')) |
python how to start a thread in bottle | def start():
"""Starts the web server."""
global app
bottle.run(app, host=conf.WebHost, port=conf.WebPort,
debug=conf.WebAutoReload, reloader=conf.WebAutoReload,
quiet=conf.WebQuiet) | def start(self):
"""Create a background thread for httpd and serve 'forever'"""
self._process = threading.Thread(target=self._background_runner)
self._process.start() |
python how to start a thread in bottle | def start():
"""Starts the web server."""
global app
bottle.run(app, host=conf.WebHost, port=conf.WebPort,
debug=conf.WebAutoReload, reloader=conf.WebAutoReload,
quiet=conf.WebQuiet) | def run(self, forever=True):
"""start the bot"""
loop = self.create_connection()
self.add_signal_handlers()
if forever:
loop.run_forever() |
python how to start a thread in bottle | def start():
"""Starts the web server."""
global app
bottle.run(app, host=conf.WebHost, port=conf.WebPort,
debug=conf.WebAutoReload, reloader=conf.WebAutoReload,
quiet=conf.WebQuiet) | def start(self):
"""Start the receiver.
"""
if not self._is_running:
self._do_run = True
self._thread.start()
return self |
python how to start a thread in bottle | def start():
"""Starts the web server."""
global app
bottle.run(app, host=conf.WebHost, port=conf.WebPort,
debug=conf.WebAutoReload, reloader=conf.WebAutoReload,
quiet=conf.WebQuiet) | def create_task(coro, loop):
# pragma: no cover
"""Compatibility wrapper for the loop.create_task() call introduced in
3.4.2."""
if hasattr(loop, 'create_task'):
return loop.create_task(coro)
return asyncio.Task(coro, loop=loop) |
python how to start a thread in bottle | def start():
"""Starts the web server."""
global app
bottle.run(app, host=conf.WebHost, port=conf.WebPort,
debug=conf.WebAutoReload, reloader=conf.WebAutoReload,
quiet=conf.WebQuiet) | def start(args):
"""Run server with provided command line arguments.
"""
application = tornado.web.Application([(r"/run", run.get_handler(args)),
(r"/status", run.StatusHandler)])
application.runmonitor = RunMonitor()
application.listen(args.port)
torna... |
get network details from device logs appium python | async def sysinfo(dev: Device):
"""Print out system information (version, MAC addrs)."""
click.echo(await dev.get_system_info())
click.echo(await dev.get_interface_information()) | def _get_device_id(self, bus):
"""
Find the device id
"""
_dbus = bus.get(SERVICE_BUS, PATH)
devices = _dbus.devices()
if self.device is None and self.device_id is None and len(devices) == 1:
return devices[0]
for id in devices:
self._dev... |
get network details from device logs appium python | async def sysinfo(dev: Device):
"""Print out system information (version, MAC addrs)."""
click.echo(await dev.get_system_info())
click.echo(await dev.get_interface_information()) | def autoscan():
"""autoscan will check all of the serial ports to see if they have
a matching VID:PID for a MicroPython board.
"""
for port in serial.tools.list_ports.comports():
if is_micropython_usb_device(port):
connect_serial(port[0]) |
get network details from device logs appium python | async def sysinfo(dev: Device):
"""Print out system information (version, MAC addrs)."""
click.echo(await dev.get_system_info())
click.echo(await dev.get_interface_information()) | def device_state(device_id):
""" Get device state via HTTP GET. """
if device_id not in devices:
return jsonify(success=False)
return jsonify(state=devices[device_id].state) |
get network details from device logs appium python | async def sysinfo(dev: Device):
"""Print out system information (version, MAC addrs)."""
click.echo(await dev.get_system_info())
click.echo(await dev.get_interface_information()) | def get_services():
"""
Retrieve a list of all system services.
@see: L{get_active_services},
L{start_service}, L{stop_service},
L{pause_service}, L{resume_service}
@rtype: list( L{win32.ServiceStatusProcessEntry} )
@return: List of service status descr... |
get network details from device logs appium python | async def sysinfo(dev: Device):
"""Print out system information (version, MAC addrs)."""
click.echo(await dev.get_system_info())
click.echo(await dev.get_interface_information()) | def desc(self):
"""Get a short description of the device."""
return '{0} (ID: {1}) - {2} - {3}'.format(
self.name, self.device_id, self.type, self.status) |
python how to use a string to access list index | def get_list_index(lst, index_or_name):
"""
Return the index of an element in the list.
Args:
lst (list): The list.
index_or_name (int or str): The value of the reference element, or directly its numeric index.
Returns:
(int) The index of the element in the list.
"""
if... | def _read_indexlist(self, name):
"""Read a list of indexes."""
setattr(self, '_' + name, [self._timeline[int(i)] for i in
self.db.lrange('site:{0}'.format(name), 0,
-1)]) |
python how to use a string to access list index | def get_list_index(lst, index_or_name):
"""
Return the index of an element in the list.
Args:
lst (list): The list.
index_or_name (int or str): The value of the reference element, or directly its numeric index.
Returns:
(int) The index of the element in the list.
"""
if... | def index(self, item):
""" Not recommended for use on large lists due to time
complexity, but it works
-> #int list index of @item
"""
for i, x in enumerate(self.iter()):
if x == item:
return i
return None |
python how to use a string to access list index | def get_list_index(lst, index_or_name):
"""
Return the index of an element in the list.
Args:
lst (list): The list.
index_or_name (int or str): The value of the reference element, or directly its numeric index.
Returns:
(int) The index of the element in the list.
"""
if... | def get_model_index_properties(instance, index):
"""Return the list of properties specified for a model in an index."""
mapping = get_index_mapping(index)
doc_type = instance._meta.model_name.lower()
return list(mapping["mappings"][doc_type]["properties"].keys()) |
python how to use a string to access list index | def get_list_index(lst, index_or_name):
"""
Return the index of an element in the list.
Args:
lst (list): The list.
index_or_name (int or str): The value of the reference element, or directly its numeric index.
Returns:
(int) The index of the element in the list.
"""
if... | def sorted_index(values, x):
"""
For list, values, returns the index location of element x. If x does not exist will raise an error.
:param values: list
:param x: item
:return: integer index
"""
i = bisect_left(values, x)
j = bisect_right(values, x)
return values[i:j].index(x) + i |
python how to use a string to access list index | def get_list_index(lst, index_or_name):
"""
Return the index of an element in the list.
Args:
lst (list): The list.
index_or_name (int or str): The value of the reference element, or directly its numeric index.
Returns:
(int) The index of the element in the list.
"""
if... | def get_index_nested(x, i):
"""
Description:
Returns the first index of the array (vector) x containing the value i.
Parameters:
x: one-dimensional array
i: search value
"""
for ind in range(len(x)):
if i == x[ind]:
return ind
return -1 |
get only letters from string python | def return_letters_from_string(text):
"""Get letters from string only."""
out = ""
for letter in text:
if letter.isalpha():
out += letter
return out | def chars(string: any) -> str:
"""Return all (and only) the chars in the given string."""
return ''.join([c if c.isalpha() else '' for c in str(string)]) |
get only letters from string python | def return_letters_from_string(text):
"""Get letters from string only."""
out = ""
for letter in text:
if letter.isalpha():
out += letter
return out | def strip_accents(string):
"""
Strip all the accents from the string
"""
return u''.join(
(character for character in unicodedata.normalize('NFD', string)
if unicodedata.category(character) != 'Mn')) |
get only letters from string python | def return_letters_from_string(text):
"""Get letters from string only."""
out = ""
for letter in text:
if letter.isalpha():
out += letter
return out | def lowercase_chars(string: any) -> str:
"""Return all (and only) the lowercase chars in the given string."""
return ''.join([c if c.islower() else '' for c in str(string)]) |
get only letters from string python | def return_letters_from_string(text):
"""Get letters from string only."""
out = ""
for letter in text:
if letter.isalpha():
out += letter
return out | def uppercase_chars(string: any) -> str:
"""Return all (and only) the uppercase chars in the given string."""
return ''.join([c if c.isupper() else '' for c in str(string)]) |
get only letters from string python | def return_letters_from_string(text):
"""Get letters from string only."""
out = ""
for letter in text:
if letter.isalpha():
out += letter
return out | def _to_lower_alpha_only(s):
"""Return a lowercased string with non alphabetic chars removed.
White spaces are not to be removed."""
s = re.sub(r'\n', ' ', s.lower())
return re.sub(r'[^a-z\s]', '', s) |
get rid of spaces in str python | def strip_spaces(x):
"""
Strips spaces
:param x:
:return:
"""
x = x.replace(b' ', b'')
x = x.replace(b'\t', b'')
return x | def strip_spaces(s):
""" Strip excess spaces from a string """
return u" ".join([c for c in s.split(u' ') if c]) |
get rid of spaces in str python | def strip_spaces(x):
"""
Strips spaces
:param x:
:return:
"""
x = x.replace(b' ', b'')
x = x.replace(b'\t', b'')
return x | def detokenize(s):
""" Detokenize a string by removing spaces before punctuation."""
print(s)
s = re.sub("\s+([;:,\.\?!])", "\\1", s)
s = re.sub("\s+(n't)", "\\1", s)
return s |
get rid of spaces in str python | def strip_spaces(x):
"""
Strips spaces
:param x:
:return:
"""
x = x.replace(b' ', b'')
x = x.replace(b'\t', b'')
return x | def strip_accents(text):
"""
Strip agents from a string.
"""
normalized_str = unicodedata.normalize('NFD', text)
return ''.join([
c for c in normalized_str if unicodedata.category(c) != 'Mn']) |
get rid of spaces in str python | def strip_spaces(x):
"""
Strips spaces
:param x:
:return:
"""
x = x.replace(b' ', b'')
x = x.replace(b'\t', b'')
return x | def _repr_strip(mystring):
"""
Returns the string without any initial or final quotes.
"""
r = repr(mystring)
if r.startswith("'") and r.endswith("'"):
return r[1:-1]
else:
return r |
get rid of spaces in str python | def strip_spaces(x):
"""
Strips spaces
:param x:
:return:
"""
x = x.replace(b' ', b'')
x = x.replace(b'\t', b'')
return x | def lowstrip(term):
"""Convert to lowercase and strip spaces"""
term = re.sub('\s+', ' ', term)
term = term.lower()
return term |
get sort index python numpy | def argsort_indices(a, axis=-1):
"""Like argsort, but returns an index suitable for sorting the
the original array even if that array is multidimensional
"""
a = np.asarray(a)
ind = list(np.ix_(*[np.arange(d) for d in a.shape]))
ind[axis] = a.argsort(axis)
return tuple(ind) | def sortlevel(self, level=None, ascending=True, sort_remaining=None):
"""
For internal compatibility with with the Index API.
Sort the Index. This is for compat with MultiIndex
Parameters
----------
ascending : boolean, default True
False to sort in descendi... |
get sort index python numpy | def argsort_indices(a, axis=-1):
"""Like argsort, but returns an index suitable for sorting the
the original array even if that array is multidimensional
"""
a = np.asarray(a)
ind = list(np.ix_(*[np.arange(d) for d in a.shape]))
ind[axis] = a.argsort(axis)
return tuple(ind) | def arglexsort(arrays):
"""
Returns the indices of the lexicographical sorting
order of the supplied arrays.
"""
dtypes = ','.join(array.dtype.str for array in arrays)
recarray = np.empty(len(arrays[0]), dtype=dtypes)
for i, array in enumerate(arrays):
recarray['f%s' % i] = array
... |
get sort index python numpy | def argsort_indices(a, axis=-1):
"""Like argsort, but returns an index suitable for sorting the
the original array even if that array is multidimensional
"""
a = np.asarray(a)
ind = list(np.ix_(*[np.arange(d) for d in a.shape]))
ind[axis] = a.argsort(axis)
return tuple(ind) | def sort_key(val):
"""Sort key for sorting keys in grevlex order."""
return numpy.sum((max(val)+1)**numpy.arange(len(val)-1, -1, -1)*val) |
get sort index python numpy | def argsort_indices(a, axis=-1):
"""Like argsort, but returns an index suitable for sorting the
the original array even if that array is multidimensional
"""
a = np.asarray(a)
ind = list(np.ix_(*[np.arange(d) for d in a.shape]))
ind[axis] = a.argsort(axis)
return tuple(ind) | def naturalsortkey(s):
"""Natural sort order"""
return [int(part) if part.isdigit() else part
for part in re.split('([0-9]+)', s)] |
get sort index python numpy | def argsort_indices(a, axis=-1):
"""Like argsort, but returns an index suitable for sorting the
the original array even if that array is multidimensional
"""
a = np.asarray(a)
ind = list(np.ix_(*[np.arange(d) for d in a.shape]))
ind[axis] = a.argsort(axis)
return tuple(ind) | def rank(self):
"""how high in sorted list each key is. inverse permutation of sorter, such that sorted[rank]==keys"""
r = np.empty(self.size, np.int)
r[self.sorter] = np.arange(self.size)
return r |
get te left most value of a column in python | def find_le(a, x):
"""Find rightmost value less than or equal to x."""
i = bs.bisect_right(a, x)
if i: return i - 1
raise ValueError | def _longest_val_in_column(self, col):
"""
get size of longest value in specific column
:param col: str, column name
:return int
"""
try:
# +2 is for implicit separator
return max([len(x[col]) for x in self.table if x[col]]) + 2
except Key... |
get te left most value of a column in python | def find_le(a, x):
"""Find rightmost value less than or equal to x."""
i = bs.bisect_right(a, x)
if i: return i - 1
raise ValueError | def get_last_filled_cell(self, table=None):
"""Returns key for the bottommost rightmost cell with content
Parameters
----------
table: Integer, defaults to None
\tLimit search to this table
"""
maxrow = 0
maxcol = 0
for row, col, tab in self.di... |
get te left most value of a column in python | def find_le(a, x):
"""Find rightmost value less than or equal to x."""
i = bs.bisect_right(a, x)
if i: return i - 1
raise ValueError | def min(self):
"""
:returns the minimum of the column
"""
res = self._qexec("min(%s)" % self._name)
if len(res) > 0:
self._min = res[0][0]
return self._min |
get te left most value of a column in python | def find_le(a, x):
"""Find rightmost value less than or equal to x."""
i = bs.bisect_right(a, x)
if i: return i - 1
raise ValueError | def index(self, value):
"""
Return the smallest index of the row(s) with this column
equal to value.
"""
for i in xrange(len(self.parentNode)):
if getattr(self.parentNode[i], self.Name) == value:
return i
raise ValueError(value) |
get te left most value of a column in python | def find_le(a, x):
"""Find rightmost value less than or equal to x."""
i = bs.bisect_right(a, x)
if i: return i - 1
raise ValueError | def argmax(self, rows: List[Row], column: ComparableColumn) -> List[Row]:
"""
Takes a list of rows and a column name and returns a list containing a single row (dict from
columns to cells) that has the maximum numerical value in the given column. We return a list
instead of a single dict... |
get the data type in python code | def datatype(dbtype, description, cursor):
"""Google AppEngine Helper to convert a data type into a string."""
dt = cursor.db.introspection.get_field_type(dbtype, description)
if type(dt) is tuple:
return dt[0]
else:
return dt | def _get_type(self, value):
"""Get the data type for *value*."""
if value is None:
return type(None)
elif type(value) in int_types:
return int
elif type(value) in float_types:
return float
elif isinstance(value, binary_type):
return... |
get the data type in python code | def datatype(dbtype, description, cursor):
"""Google AppEngine Helper to convert a data type into a string."""
dt = cursor.db.introspection.get_field_type(dbtype, description)
if type(dt) is tuple:
return dt[0]
else:
return dt | def _api_type(self, value):
"""
Returns the API type of the given value based on its python type.
"""
if isinstance(value, six.string_types):
return 'string'
elif isinstance(value, six.integer_types):
return 'integer'
elif type(value) is datetime.... |
get the data type in python code | def datatype(dbtype, description, cursor):
"""Google AppEngine Helper to convert a data type into a string."""
dt = cursor.db.introspection.get_field_type(dbtype, description)
if type(dt) is tuple:
return dt[0]
else:
return dt | def gtype(n):
"""
Return the a string with the data type of a value, for Graph data
"""
t = type(n).__name__
return str(t) if t != 'Literal' else 'Literal, {}'.format(n.language) |
get the data type in python code | def datatype(dbtype, description, cursor):
"""Google AppEngine Helper to convert a data type into a string."""
dt = cursor.db.introspection.get_field_type(dbtype, description)
if type(dt) is tuple:
return dt[0]
else:
return dt | def maybe_infer_dtype_type(element):
"""Try to infer an object's dtype, for use in arithmetic ops
Uses `element.dtype` if that's available.
Objects implementing the iterator protocol are cast to a NumPy array,
and from there the array's type is used.
Parameters
----------
element : object
... |
get the data type in python code | def datatype(dbtype, description, cursor):
"""Google AppEngine Helper to convert a data type into a string."""
dt = cursor.db.introspection.get_field_type(dbtype, description)
if type(dt) is tuple:
return dt[0]
else:
return dt | def validate_type(self, type_):
"""Take an str/unicode `type_` and raise a ValueError if it's not
a valid type for the object.
A valid type for a field is a value from the types_set attribute of
that field's class.
"""
if type_ is not None and type_ n... |
python image to buffer | def get_buffer(self, data_np, header, format, output=None):
"""Get image as a buffer in (format).
Format should be 'jpeg', 'png', etc.
"""
if not have_pil:
raise Exception("Install PIL to use this method")
image = PILimage.fromarray(data_np)
buf = output
... | def url_to_image(url, flag=cv2.IMREAD_COLOR):
""" download the image, convert it to a NumPy array, and then read
it into OpenCV format """
resp = urlopen(url)
image = np.asarray(bytearray(resp.read()), dtype="uint8")
image = cv2.imdecode(image, flag)
return image |
python image to buffer | def get_buffer(self, data_np, header, format, output=None):
"""Get image as a buffer in (format).
Format should be 'jpeg', 'png', etc.
"""
if not have_pil:
raise Exception("Install PIL to use this method")
image = PILimage.fromarray(data_np)
buf = output
... | def read_img(path):
""" Reads image specified by path into numpy.ndarray"""
img = cv2.resize(cv2.imread(path, 0), (80, 30)).astype(np.float32) / 255
img = np.expand_dims(img.transpose(1, 0), 0)
return img |
python image to buffer | def get_buffer(self, data_np, header, format, output=None):
"""Get image as a buffer in (format).
Format should be 'jpeg', 'png', etc.
"""
if not have_pil:
raise Exception("Install PIL to use this method")
image = PILimage.fromarray(data_np)
buf = output
... | def uint32_to_uint8(cls, img):
"""
Cast uint32 RGB image to 4 uint8 channels.
"""
return np.flipud(img.view(dtype=np.uint8).reshape(img.shape + (4,))) |
python image to buffer | def get_buffer(self, data_np, header, format, output=None):
"""Get image as a buffer in (format).
Format should be 'jpeg', 'png', etc.
"""
if not have_pil:
raise Exception("Install PIL to use this method")
image = PILimage.fromarray(data_np)
buf = output
... | def load_preprocess_images(image_paths: List[str], image_size: tuple) -> List[np.ndarray]:
"""
Load and pre-process the images specified with absolute paths.
:param image_paths: List of images specified with paths.
:param image_size: Tuple to resize the image to (Channels, Height, Width)
:return: A... |
python image to buffer | def get_buffer(self, data_np, header, format, output=None):
"""Get image as a buffer in (format).
Format should be 'jpeg', 'png', etc.
"""
if not have_pil:
raise Exception("Install PIL to use this method")
image = PILimage.fromarray(data_np)
buf = output
... | def read_image(filepath):
"""Returns an image tensor."""
im_bytes = tf.io.read_file(filepath)
im = tf.image.decode_image(im_bytes, channels=CHANNELS)
im = tf.image.convert_image_dtype(im, tf.float32)
return im |
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