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def not_at_goal_set(trees): """convenience / readability function which returns the not terminated trees from a list :param trees: list of input trees :type trees: list :return: trees from the input list which are not terminated :rtype: list """ not_at_goal = [] for tree in trees: ...
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def permalink_to_full_link(link: str) -> str: """Turns permalinks returned by Praw 4.0+ into full links""" return "https://www.reddit.com" + link
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def extract_helm_from_json(input_json): """Extracts the HELM strings out of a JSON array. :param input_json: JSON array of Peptide objects :return: output_helm: string (extracted HELM strings separated by a newline) """ output_helm = "" for peptide in input_json: if len(output_helm) > 0...
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def category_name(value): """Maps category value to names""" return { 0: "idle", 1: "unassigned", 2: "work", 3: "private", 4: "break", }.get(value, "?")
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import inspect def private_method(func): """Decorator for making an instance method private.""" def func_wrapper(*args, **kwargs): """Decorator wrapper function.""" outer_frame = inspect.stack()[1][0] if 'self' not in outer_frame.f_locals or outer_frame.f_locals['self'] is not args[0]...
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def unify_pos(pos, size): """ Convert position into standard one. Example: Given size = 5, Point(-2, -7) -> Point(3, 3) """ return pos % size
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def exclude(func): """Return the opposite of ``func`` (i.e. ``False`` instead of ``True``)""" return lambda x: not func(x)
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import random def randInt32(rng=random.random): """returns a random integer in [-2147483648..2147483647]. rng must return float in [0..1] """ i = int(rng() * 0x7FFFFFFF) if rng() < .5: i *= -1 return i
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import typing def split_name(name: str) -> typing.Tuple[str, str]: """ Returns a likely `(first, last)` split given a full name. This uses very simple heuristics, and assumes Western usage. :param name: A full name (first and last name). :return: A split pair with the first names, and the last na...
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def create_grid_string(grid): """Return a crossword grid as a string.""" size = len(grid) separator = ' +' + ('-----+')*size column_number_line = ' ' column_number_line += ''.join(f' {j:2} ' for j in range(size)) result = f'{column_number_line}\n{separator}\n' for (i, row) in enumerate(...
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def superset_data_db_name() -> str: """The name (in Superset) of the database that Superset reads from""" return 'MyCompany DWH'
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def get_subsequences_matching_query(hit_obj): """Takes a SearchIO hit object, and returns a list with the first element being a string representing the coordinates of the query to which the subject sequence aligns, and the second being the corresponding subject subsequence(s). """ # ***Eventuall...
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def buoy_distance(pixel_width, focal_length, ACTUAL_WIDTH=0.4): """ Calculates the distance of the buoy from the boat. The algorithm uses the similar triangles in the following equation: (focal_len / pixel_width) = (actual_distance / actual_width) Keyword arguments: pixel_width -- The width of...
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def init_jsobject(cls, bridge, name, value, description=None): """Initialize a JS object that is a subclassed base type. Arguments: cls -- Class the object has to be created from bridge -- JSBridge instance to use name -- Name of the JS object value -- Value of the object wrapped as JS object ...
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def default_order(json_page_obj): """Return ordering based on metadata.""" return json_page_obj["meta_order"], json_page_obj["title"]
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def centered_average(nums): """ take out 1 value of the smallest and largst compute and return the mean of the rest int div --> truncate the floating part? ASSUME: +3 ints pos/neg unsorted dupes possible Intutition: - computing an average (sum / # of points) Approac...
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def x12_271_member_not_found_message() -> str: """A X12 271 message where the member is not found in the payer system and does not have insurance coverage""" return 'ISA*00* *00* *ZZ*890069730 *ZZ*154663145 *200929*1705*|*00501*000000001*0*T*:~GS*HS*890069730*154663145*20200929*1705*...
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def is_file_supported(suffix: str) -> bool: """ Check a path to be supported by safitty (only YAML or JSON) Args: suffix (str): path extension Returns: bool: File is YAML or JSON """ return suffix in [".json", ".yml", ".yaml"]
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def spacing(area, shape): """ Returns the spacing between grid nodes Parameters: * area ``(x1, x2, y1, y2)``: Borders of the grid * shape Shape of the regular grid, ie ``(nx, ny)``. Returns: * ``[dx, dy]`` Spacing the y and x directions Examples: >>> pri...
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def look_through_rows(board, column, player): """ Given a matrix, a column of the matrix, and a key, This function will look through the column bottom to top, and find the first empty slot indicated by a 0 and place a piece there (1 or 2) >>> look_through_rows(numpy.matrix('0,0,0,0,0; 0,0,0,0,0; 0,0...
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def get_available_resources(threshold, usage, total): """Get a map of the available resource capacity. :param threshold: A threshold on the maximum allowed resource usage. :param usage: A map of hosts to the resource usage. :param total: A map of hosts to the total resource capacity. :return: A map...
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from typing import List from typing import Dict def find_it(seq: List[int]) -> int: """ Given an array, find the int that appears an odd number of times. :param seq: :return: """ pares: Dict[int, int] = dict() result: int = 0 for n in seq: if n not in pares: pa...
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def AND(*args) -> str: """ Creates an AND Statement >>> AND(1, 2, 3) 'AND(1, 2, 3)' """ return "AND({})".format(",".join(args))
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def scaled_grad(g, inv_d): """Computes the scaled gradient.""" return inv_d * g
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def invariants(tensor): """ Calculates the first, second, and dimensionless invariants of the gradient tensor. .. note:: The coordinate system used is x->North, y->East, z->Down Parameters: * tensor : list A list of arrays with the 6 components of the gradient tensor measured ...
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def first_of(iterable, function): """ Return the first matching element of an iterable This function is useful if you already know there is at most one matching element. """ for item in iterable: if function(item): return item return None
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def find_features(extent, df): """ given an extent and a dataframe, return a new dataframe containing only features that fall within the extent Parameters ---------- extent: list -- geographic extent in lon (deg E)/lat (deg N) df: the geopandas dataframe to slice """ xleft, xrigh...
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def sum_even_integers(sequence): """ What comes in: -- A sequence What goes out: Returns the sum of the items in the sequence that: -- are integers AND -- are even. Side effects: None. Examples: sum_even_integers([3, 10, 6, 5, 5, 10]) returns 10 + 6 + 10, ...
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import random def balance_dataset(data, ratio): """ Subsamples dataset according to ratio. @param data: List of samples. @param ratio: Ratio of samples to be returned. @return: Subsampled dataset. """ sampled_data = random.sample(data, int(ratio * len(data))) return sampled_data
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def linear(y_0, y_1, x_0, x_1, k): """Returns the particular integral and its derivative for linear load. y_0, y_1 the ordinates @ the extremes of the loading, x_0, x_1 the abscissae @ the extremes of the loading, k the stiffness of the oscillator. The returned functions are defined in te...
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from datetime import datetime def _datetime_now() -> datetime: """Wrap ``datetime.now`` to easily mock it for testing. Returns ------- datetime Current datetime. """ return datetime.now()
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def _get_available_memory(mem_feat, constraints=None): """Get available memory If constraints are given, parse constraint string into array of constraints and compare them to active features. Currently only handles comma-separated strings and not the more advanced constructs described in the slurm ...
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def split(attr): """ Split <key>=<val> into tuple (<key>,<val>), if only string is passed, return ('id', <val>)""" if '=' in attr: ret = attr.split('=') return ret[0], ret[1] else: return 'id', attr
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def zero_diag(Q): """ Copy of Q altered such that diagonal entries are all 0. """ Q_nodiag = Q.copy() for ii in range(Q.shape[0]): Q_nodiag[ii, ii] = 0 return Q_nodiag
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def get_extremas_from_positions(positions): """ returns the minimum and maximum value for each dimension in the positions given """ return zip(*[(min(values), max(values)) for values in zip(*positions)])
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def degree(G,nbunch=None,weight=None): """Return degree of single node or of nbunch of nodes. If nbunch is ommitted, then return degrees of *all* nodes. """ return G.degree(nbunch,weight)
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def calc_angle(per, line): """ Calculate angle between two vector. Take into consideration a quarter circle :param per: first vector :type per: DB.XYZ :param line: second vector :type line: DB.XYZ :return: Angle between [-pi, pi] :rtype: float """ return (1 if per.Y >= 0 els...
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def generate_target_states_list(sweep, initial_state_labels): """Based on a bare state label (i1, i2, ...) with i1 being the excitation level of subsystem 1, i2 the excitation level of subsystem 2 etc., generate a list of new bare state labels. These bare state labels correspond to target states reached fr...
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def linked_embeddings_name(channel_id): """Returns the name of the linked embedding matrix for some channel ID.""" return 'linked_embedding_matrix_%d' % channel_id
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from typing import Callable from typing import List from typing import OrderedDict def order_json(data, sort_fn: Callable[[List[str]], List[str]] = sorted): """Sort json to a consistent order. When you hash json that has the some content but is different orders you get different fingerprints. .. cod...
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import torch def compute_argmax(ten): """Compute argmax for 2D grid for tensors of shape (batch_size, size_y, size_x) Args: ten (torch.[cuda].FloatTensor): (batch_size, size_y, size_x) Returns: indices (torch.[cuda].LongTensor): (batch_size, 2) index order: (y, x) """ batch_size ...
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def get_util_shape(row): """Get utility term shape based on ROI. Parameters ---------- row : pandas.core.series.Series Row of func_df DataFrame. Returns ------- str If 'chest' or 'rib in row['Roi'], then return 'linear'. Otherwise, return 'linear_quadratic'. ""...
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def isprefix(path1, path2): """Return true is path1 is a prefix of path2. :param path1: An FS path :param path2: An FS path >>> isprefix("foo/bar", "foo/bar/spam.txt") True >>> isprefix("foo/bar/", "foo/bar") True >>> isprefix("foo/barry", "foo/baz/bar") False >>> ispre...
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from typing import Tuple def sat_idx_to_in_orbit_idx(sat_idx: int, num_sat_per_orbit: int) -> Tuple[int, int]: """ Compute the satellite index in orbit and orbit index. Starting from the satellite index in the constellation. Args: sat_idx: Index of the satellite in the constellation. n...
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def non_gaussian(onset, frame): """ Calculate the Non-Gaussian parameter : ..math: \alpha_2 (t) = \frac{3}{5}\frac{\langle r_i^4(t)\rangle}{\langle r_i^2(t)\rangle^2} - 1 """ r_2 = ((frame - onset)**2).sum(axis=-1) return 3 / 5 * (r_2**2).mean() / r_2.mean()**2 - 1
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def get_rain_svg(risk_of_rain: float) -> str: """ Get SVG path to risk of rain icon :param risk_of_rain: Risk of rain between 0 and 1 :return: path to SVG resource """ if risk_of_rain < 0.33: return 'Icons/Shades.svg' return 'Icons/Umbrella.svg'
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import importlib def get_extractor_implementation(cls, pkg=None): """ Get the implementation of an Extractor. :param cls: class name (str) :param pkg: package where implementation is found (str) :return: class implementation """ # known extractors # others must be fully specified throu...
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import torch def disagreement(logits_1, logits_2): """Disagreement between the predictions of two classifiers.""" preds_1 = torch.argmax(logits_1, dim=-1).type(torch.int32) preds_2 = torch.argmax(logits_2, dim=-1).type(torch.int32) return torch.mean((preds_1 != preds_2).type(torch.float32))
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def getPropertyAsSingleValue( data, name, default ): """ Read a property from an LDAP data structure. Multi-valued properties are read as single-valued, with only the first value being used. """ try: return data[name][0] except (IndexError, KeyError): return default
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from typing import Tuple from typing import List from typing import Dict def selection(triple: Tuple[str, str, str], variables: List[str]) -> Dict[str, str]: """Apply a selection on a RDF triple, producing a set of solution mappings. Args: * triple: RDF triple on which the selection is applied. *...
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import json def dump_json(file, array): """Dumps a dict to a JSON file""" with open(file, 'w') as f: return json.dump(array, f)
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def models_of_same_type(*models): """ Checks whether all the provided `models` are of the same type. """ return len(set(m._meta.concrete_model for m in models)) == 1
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def get_layout_locations(version, base_path, dsid): """Return dataset-related path in a RIA store Parameters ---------- version : int Layout version of the store. base_path : Path Base path of the store. dsid : str Dataset ID Returns ------- Path, Path, Path ...
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def calCentroid(xmn, ymn, xmx, ymx): """ Function to calculate the centroid of a given image """ xmid = (xmx + xmn) / 2 ymid = (ymx + ymn) / 2 return xmid, ymid
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def eqrr(registers, opcodes): """eqrr (equal register/register) sets register C to 1 if register A is equal to register B. Otherwise, register C is set to 0. """ return int(registers[opcodes[1]] == registers[opcodes[2]])
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def get_normalisation_coefficient(sample_size): """ Returns a multiplicator for normalising entropy estimated on the sample based on the size of the sample. The coefficients were estimated empirically based on bootstrap resampling. """ if sample_size < 55: raise ValueError('No coeffi...
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import torch def focal_loss(bce_loss, targets, gamma, alpha): """Binary focal loss, mean. Per https://discuss.pytorch.org/t/is-this-a-correct-implementation-for-focal-loss-in-pytorch/43327/5 with improvements for alpha. :param bce_loss: Binary Cross Entropy loss, a torch tensor. :param targets: a...
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def response_id(req_data): """ Get the ID for the response from a JSON-RPC request Return None if ID is missing or invalid """ _id = None if isinstance(req_data, dict): _id = req_data.get('id') if type(_id) in (str, int): return _id else: return None
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import requests from bs4 import BeautifulSoup def get_data(url): """ Return BeautifulSoup html object. """ r = requests.get(url) data = BeautifulSoup(r.text, 'lxml') return data
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from typing import List import re def _find_matching_tags(tag: 'str', lst: 'List[str]'): """ Extract the full list of matches to the regex stored in tag. :param tag: A regex to search for :type tag: str :param lst: A set of tags to search :type lst: List[str] :return: The matching tags f...
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def serialize_tree(root): """ Given a tree root node (some object with a 'data' attribute and a 'children' attribute which is a list of child nodes), serialize it to a list, each element of which is either a pair (data, has_children_flag), or None (which signals an end of a sibling chain). """ l...
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from typing import List from typing import Dict def species_by_charge(state_ids: List[str], charges: List[int]) -> Dict[int, List[str]]: """Make a dict with charge as key, and lists of species as values. Parameters ---------- state_ids - identifiers for states charges - charges for states Re...
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def admin_pc_client(admin_pc): """Returns the client from the default admin's ProjectContext """ return admin_pc.client
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from pathlib import Path def filesize(fname): """ Simply returns the size of the file fname in bytes """ return (Path(fname).stat().st_size)
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def _format_optname(value): """Format the name of an option in the configuration file to a more readable option in the command-line.""" return value.replace('_', '-').replace(' ', '-')
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import zlib import pickle def blobdumps(py_obj, cPickle_protocol=2, compression_level=7): """ Pickle any Python object, and compress the pickled object. Returns a binary string. `compression_level`: Between 1 and 9 The higher the level is, the more compressed the object will be. """ ...
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def format_imports(import_statements): """ ----- examples: @need from fastest.constants import TestBodies @end @let import_input = TestBodies.TEST_STACK_IMPORTS_INPUT output = TestBodies.TEST_STACK_IMPORTS_OUTPUT @end 1) format_imports(import_input) -> output ----- :...
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def CleanStrForFilenames(filename): """Sanitize a string to be used as a filename""" keepcharacters = (' ', '.', '_') FILEOUT = "".join(c for c in filename if c.isalnum() or c in keepcharacters).rstrip() return FILEOUT
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def lerp(a, b, x): """Linear interpolation between a and b using weight x.""" return a + x * (b - a)
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def make_key(x,y): """ function to combine two coordinates into a valid dict key """ return f'{x}, {y}'
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import re def extract_swagger_path(path): """ Extracts a swagger type path from the given flask style path. This /path/<parameter> turns into this /path/{parameter} And this /<string(length=2):lang_code>/<string:id>/<float:probability> to this: /{lang_code}/{id}/{probability} """ return re.sub('<(?:[^:]...
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def find_number_3_multiples(x): """Calculate the number of times that 3 goes into x.""" mult3=x//3 return mult3
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def is_triangle_possible(triangle): """Check if triangle is possible.""" return sum(sorted(triangle)[:2]) > max(triangle)
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def create_content_item_id_set(id_set_list: list) -> dict: """ Given an id_set.json content item list, creates a dictionary representation""" res = dict() for item in id_set_list: for key, val in item.items(): res[key] = val return res
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import ast def parse_imports(filepath): """Formulate a dictionary of imports within a python file for usage by ``apipkg``. Parameters ---------- filepath The python file containing the imports to be parsed. Returns ------- imports_for_apipkg A dictionary of imports in the...
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def aic_hmm(log_likelihood, dof): """ Function to compute the Aikaike's information criterion for an HMM given the log-likelihood of observations. :param log_likelihood: logarithmised likelihood of the model dof (int) - single numeric value representing the number of trainable parameter...
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def searchList(listOfTerms, query: str, filter='in'): """Search within a list""" matches = [] for item in listOfTerms: if filter == 'in' and query in item: matches.append(item) elif filter == 'start' and item.startswith(query): matches.append(item) elif filter...
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def get_extrap_col_and_ht(height, num, primary_height, sensor='Ane', var='WS'): """ Determine name of column and height to use for extrapolation purposes :param height: comparison height :param num: number/label of comparison height :param primary_height: Primary comparison height :param sensor:...
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def add_plugin_to_endpoints(endpoints, plugin): """ Add the endpoint key to each endpoint dictionary in the list :param endpoints: List of endpoint dictionaries :param plugin: String of the plugin name """ for endpoint in endpoints: endpoint.update({ 'plugin': plugin, ...
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def compose(*functions): """ Compose functions This is useful for combining decorators. """ def _composed(*args): for fn in functions: try: args = fn(*args) except TypeError: # args must be scalar so we don't try to expand it ...
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def getArrayDimensions(shape): """ Get the dimensions of the grid where the cell will be zoomed. The zoomed cell contains a `numpy` array and will be displayed in a table with the same shape than it. :Parameter shape: the cell shape :Returns: a tuple (rows, columns) """ # Numpy scala...
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def get_item_properties(item, columns): """Get specified in columns properties, with preserved order. Required for correct cli table generation :param item: dict :param columns: list with arbitrary keys """ properties = [] for key in columns: properties.append(item.get(key, '')) ...
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def get_original_keys(keys, keymap, strict=False): """ Get original keys from normalized keys. Args: keys: The collection of keys that identify a value in the dataset. keymap: The keymap returned from :meth:`load` or :meth:`loads`. strict: If true...
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from pathlib import Path def enterprise_1_12_artifact() -> Path: """ Return the path to a build artifact for DC/OS Enterprise 1.12. """ return Path('/tmp/dcos_generate_config_1_12.ee.sh')
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import json def create_label(name, color, repos, session, origin): """ Creates label :param name: name of the label :param color: color of the label :param repos: repository where label is created :param session: session for communication :param origin: repository where the label came fro...
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def indent(block): """Indent each row of the given string block with ``n*2`` spaces.""" indentation = " " * 2 return "\n".join([indentation + s for s in block.split('\n')])
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def version_greater_or_equal_to(version, min_version): """Compares two version strings and returns True if version > min_version >>> version_greater_or_equal_to('1.0', '0') True >>> version_greater_or_equal_to('1.0', '0.9.9.9') True >>> version_greater_or_equal_to('1.0', '2.0') False >>> version_greate...
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def to_red(string): """ Converts a string to bright red color (16bit) Returns: str: the string in bright red color """ return f"\u001b[31;1m{string}\u001b[0m"
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import re def get_function_name(line): """Get name of a function.""" func_name = re.split(r"\(", line)[0] func_name = re.split(r" ", func_name)[-1] func_name = re.sub(r"(\*|\+|\-)", r"", func_name) return func_name
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def linearize_dict(indict, sep='_', lower=False): """Linearize levels of an input dict, using separator Args: indict(`dict`): input dict with nested levels sep(str): separator lower(bool): lower all itens Returns: `dict`: output dict with just one level """ def li...
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def check_resource_existence(client, resource_group): """Create if resource group exists in Azure or not :param client: Azure object using ResourceManagementClient :param resource_group: string, name of Azure resource group :return: True if exists, otherwise False :rtype: boolean """ respon...
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import re def diff_replace_old_new(diff): """Return the (old, new) filenames from difference tuple `diff`.""" match = re.search(r"replaced '(.+)' with '(.+)'", diff[-1]) if match: return match.group(1), match.group(2) else: return None, None
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import hashlib def checksum_file(f, blocksize: int = 2 << 15) -> str: """ Checksum a file-like object. """ hasher = hashlib.sha256() for block in iter(lambda: f.read(blocksize), b""): hasher.update(block) f.seek(0) return hasher.hexdigest()
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def get_node_set_map(tuple_list): """ Function to get a mapping of random node names to values between 0 and number of nodes - 1, with a modified adjacency list. Args: tuple_list : adjacency list with weights and arbitrary node names Returns: tuples : canonicalized adjacency list ...
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import json def is_new_version_model_file(model_file_path: str) -> bool: """Check whether the model file belongs to the new version of HuggingFace Tokenizers, i.e., >= 0.8 Parameters ---------- model_file_path Path to the model file Returns ------- is_new_version Whet...
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import json def configure_connection (instance, name = 'database', credentials = None): """Configures IBM Streams for a certain connection. Creates or updates an application configuration object containing the required properties with connection information. Example for creating a configuration for a ...
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def has_tag(method, tag: str) -> bool: """ Checks if the given method has the given tag. :param method: The method to check. :param tag: The tag to check for. :return: True if the tag exists on the method, False if not. """ return hasattr(method, '__tags') an...
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def make_plant_indices(plant_ids, storage_candidates=None): """Make the indices for existing and hypothetical generators for input to Switch. :param iterable plant_ids: plant IDs. :param set storage_candidates: buses at which to enable storage expansion. :return: (*dict*) -- keys are {'existing', 'expa...
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def get_blurb(in_file): """Get the first paragraph of a Markdown file""" with open(in_file, "r") as f: f.readline() # Title f.readline() # Title underline f.readline() # Blank out = "" line = f.readline() while len(line) > 0 and line != "\n": out +...
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def pointInRect(p, rect): """Return True when point (x, y) is inside rect.""" (x, y) = p xMin, yMin, xMax, yMax = rect return (xMin <= x <= xMax) and (yMin <= y <= yMax)
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