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import hmac import hashlib def _hmac_sha256(key, msg): """ Generates a sha256 digest using the given key and message. :param str key: starting key for the hash :param str msg: message to be hashed :returns: sha256 digest of msg as bytes, hashed using the given key """ return hmac.new(key, msg, hashli...
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from typing import Dict from typing import List def convert_spin_to_list(spins: Dict) -> List: """Convert the Spin dictionary from the ssoCard into a list. Add the spin index as parameter to the Spin entries. Parameters ---------- spin : dict The dictionary located at parameters.physical....
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def _get_scripts_resource(pe): """Return the PYTHONSCRIPT resource entry.""" res = None for entry in pe.DIRECTORY_ENTRY_RESOURCE.entries: if entry.name and entry.name.string == b"PYTHONSCRIPT": res = entry.directory.entries[0].directory.entries[0] break return res
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from typing import List from typing import Any from typing import Tuple def pad(x: List[List[Any]], pad: int) -> Tuple[List[List[int]], List[List[bool]]]: """Pad 2d list x based on max length. Also generate a mask to access valid values in the padded list. Args: x (List[List[A...
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def get_last_slackblocks_message_text(messages) -> str: """ Utility methods for retrieving the text content of the most recent message. Assumes that message was constructed using a single SlackBlocks SectionBlock with at least one attachment. :raises KeyError: likely because the last messages was no...
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from typing import Dict def config_get_policy(config: Dict[str, str]): """Return the effective SELinux policy Checks if SELinux is enabled and if so returns the policy; otherwise `None` is returned. """ enabled = config.get('SELINUX', 'disabled') if enabled not in ['enforcing', 'permissive']:...
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def ebitda(gross_profit, sg_a): """ Computes EBITDA(earnings before interest, tax, depreciation and amortizatin). Parameters ---------- gross_profit : int or float Gross profit for the period sg_a : int or float Selling, general and administrative cost Returns ------- ...
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def king(r, rc, rt, sigma_0, alpha=2): """ See http://iopscience.iop.org/1538-3881/139/6/2097/fulltext/ Parameters ---------- r: float radius rc: float core radius rt: float truncation radius sigma_0: float central density """ def z(x): r...
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from pathlib import Path import glob import re def increment_path(path, exist_ok=False): """ Automatically increment path, i.e. runs/exp --> runs/exp0, runs/exp1 etc. Args: path (str or pathlib.Path): f"{model_dir}/{args.name}". exist_ok (bool): whether increment path (increment if False). ...
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def mk_rule_key(rule): """ Convert a rule tuple to a hyphen-separated string. """ return '{}-{}-{}-{}'.format(rule.source_institution, rule.destination_institution, rule.subject_area, rule.group_number)
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import pickle def get_original_config(dirname: str) -> dict: """ Get original model config used with hydra Args: dirname (str): model directory Returns: dict: config dict """ config = pickle.load(open(f"{dirname}/tb/config.pkl", "rb")) return config
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import six def to_bytestring(data): """ Convert data to a (utf-8 encoded) byte-string if it isn't a byte-string already. """ if not isinstance(data, six.binary_type): data = six.text_type(data).encode('utf-8') return data
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def point_to_node(gfa_, node_id): """Check if the given node_id point to a node in the gfa graph. """ return gfa_.nodes(identifier = node_id) != None
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import copy def filter_dict(target_dict, keys_to_filter): """Filters key(s) from top level of a dict Args: target_dict (dict): the dictionary to filter keys_to_filter (list, tuple, str): set of keys to filter Returns: A filtered copy of target_dict """ assert isinstance(tar...
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def create_pinhole_camera(height, width): """ Creates a pinhole camera according to height and width, assuming the principal point is in the center of the image """ cx = (width - 1) / 2 cy = (height - 1) / 2 f = max(cx, cy) return f, cx, cy
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from typing import List def _replace_pw_references(alias_cmd: str, pw_args: List[str]) -> str: """Replace all occurrences of pw@ with the path to the pw script (argv[0]) plus all pw options""" replacement = " ".join(pw_args) + " " return alias_cmd.replace("pw@", replacement)
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def single_state_time_spent(state_dict, state): """ Given a ticket's state dictionary, returns how much time it spent in the given `state`. Assumes state_dict has the key `state` present. """ # Measurement 2: Average Time Spent in Scrum Team Backlog # For the PRs that need to be reviewed by...
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from typing import Union def clamp(value: Union[float, int], lower: Union[float, int], upper: Union[float, int]) -> Union[float, int]: """ Clamp a number Same as min(max((value, lower), higher) Args: value (Union[float, int]): Value to clamp lower (Union[float, int]): min value ...
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import json def file_open_json(file): """Reads json file from the location input :param file: path of the json file :type file: String :return: contents of json :rtype: dictionary(dict) :raise Exception: Throws exception if unable to load file """ try: with open(file) as f: ...
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def read_block(fi): """Read and returns one block of non-empty lines from an input stream (stripped lines are returned in a list)""" block = [] for line in fi: line = line.strip() if not line and len(block): break block.append(line) return block
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import sympy def handle_gcd_lcm(f, args): """ Return the result of gcd() or lcm(), as UnevaluatedExpr f: str - name of function ("gcd" or "lcm") args: List[Expr] - list of function arguments """ args = tuple(map(sympy.nsimplify, args)) # gcd() and lcm() don't support evaluate=False ...
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def get_author_name_and_id(soup): """ Get author name and id. Examples -------- >>> a_tag = '<a class="topic__author-link" href="/author_id">author_name</a>' >>> soup = make_soup(a_tag) >>> get_author_name_and_id(soup) ('author_name', 'author_id') """ author = soup.select('a.to...
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import re def _find_sgRNA(guide_sequence, target_sequence, strand): """ Find start, stop position of a sgRNA in a target sequence. Parameters: ----------- guide_sequence target_sequence Returns: -------- start, stop """ guide_span = re.search(guide_sequence, target_seq...
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import struct def getheader(filename, gtype): """Read header data from Gadget data file 'filename' with Gadget file type 'gtype'. Returns a dictionary with loaded values and filename.""" DESC = '=I4sII' # struct formatting string HEAD = '=I6I6dddii6iiiddddii6ii60xI' ...
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def gradient_add(grad_1, grad_2, param, verbose=0): """ Sum two gradients :param grad_1: (TensorFlow Tensor) The first gradient :param grad_2: (TensorFlow Tensor) The second gradient :param param: (TensorFlow parameters) The trainable parameters :param verbose: (int) verbosity level :return...
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def _remove_model_weights(model: dict, to_delete=None) -> dict: """ Removes certain weights of a given model. The weights to remove are given by the to_delete argument. If there is also a bias term, that is deleted as well. Args: model: Loaded detectron2 model to_delete (list): Names of ...
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def overlaps(df, idx): """ Check if the note at the given index in the given dataframe overlaps any other notes in the dataframe. Parameters ---------- df : pd.DataFrame The DataFrame to check for overlaps. idx : int The index of the note within df that might overlap. ...
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from typing import List from typing import Tuple def remove_pads(y_true: List[str], y_pred: List[str]) -> Tuple[List[str], List[str]]: """ Takes as input two lists of strings corresponding to the predicted and actual tags and returns the same lists except that any <pad> tags in y_true are removed and the ...
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def corr(result, result2, result3): """ Computes the correlation between the three regression methods by taking squared differences from averages in each category and then averaging those results. Interpret this as a smaller # meaning a better score / agreement. Parameters ---------- result:...
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from typing import Union import builtins import importlib def _load_exception_class(import_specifier: str) -> Union[Exception, None]: """Load an exception class to be used for filtering Sentry events. This function takes a string representation of an exception class to be filtered out of sending to Sentr...
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def yaml_time_serializer(dumper, data): """ This function is required to serialize datetime.time as string objects when working with YAML as output format. """ return dumper.represent_scalar('tag:yaml.org,2002:str', str(data))
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def year_range(y_start, y_end): """Format a year range.""" year = y_start or '' if y_end: year += '–' + y_end return year
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def same_keys(a, b): """Determine if the dicts a and b have the same keys in them""" for ak in a.keys(): if ak not in b: return False for bk in b.keys(): if bk not in a: return False return True
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from pathlib import Path def pyyaml_path_constructor(loader, node): """Helper method to load Path tag in PyYAML.""" value = loader.construct_scalar(node) return Path(value)
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def filter_state(hdf_file_content, link_id, state='State0'): """Get the time series of a state for a link Parameters ---------- hdf_file_content : np.array data in the h5 file as a numpy array link_id : int link_id to be filtered state : str , ex. State0(default), Stat...
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def _get_metric_prefix(power: int, default: str = "") -> str: """Return the metric prefix for the power. Args: power (int): The power whose metric prefix will be returned. default (str): The default value to return if an exact match is not found. Returns: str: The metri...
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def get_average_att_network(networks, select='accuracy'): """Get the average accuracy for a group of networks. Args: networks (list): List of networks Returns: float: The average accuracy of a population of networks. """ total = 0 for network in networks: if select == 'ac...
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def parse_size(size): """ Converts a size specified as '800x600-fit' to a list like [800, 600] and a string 'fit'. The strings in the error messages are really for the developer so they don't need to be translated. """ first_split = size.split('-') if len(first_split) != 2: raise Att...
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def split_writable_text(encoder, text, encoding): """Splits off as many characters from the begnning of text as are writable with "encoding". Returns a 2-tuple (writable, rest). """ if not encoding: return None, text for idx, char in enumerate(text): if encoder.can_encode(encoding, ...
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from typing import OrderedDict def backwards_state_dict(state_dict): """ Modify the state dict of older models for backwards compatibility Parameters ---------- state_dict : dict Model state dict with pretrained weights Returns ------- state_dict : dict Updated model ...
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def are_attributes_valid(attributes): """ Determine if attributes provided are dict or not. Args: attributes: User attributes which need to be validated. Returns: Boolean depending upon whether attributes are in valid format or not. """ return type(attributes) is dict
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import shutil def desk_per_Win(path): """ path: the disk that you want to check, example: path = 'C:' return: the percentage of the free space on that disk """ # Get the disk usage statistics # about the given path stat = shutil.disk_usage(path) # Print disk usage statistics ...
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def create_query_token_func(session, model_class): """Create an ``query_token`` function that can be used in resource protector. :param session: SQLAlchemy session :param model_class: TokenCredential class """ def query_token(client_id, oauth_token): q = session.query(model_class) ...
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def check_parsed_args_compatible(imp, modules, contact, cc, parser): """ Check that the combination of arguments are compatible. Args: imp(str): CSV import specifier modules(str): Modules argument contact(str): Contact argument cc(str): CC argument parser(:class:`arg...
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def mod(p): """ Compute modulus of 3D vector p: array Cartesian coordinates """ return (p[0]**2 + p[1]**2 + p[2]**2)**0.5
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def get_weight_of(level: int) -> int: """Return the weight of a given `level`. The ratio is 1:3:5 for modules of L4:L5:L6 respectively.""" levels = {4: 1, 5: 3, 6: 5} return levels[level] if isinstance(level, int) and level in levels else 0
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def formatter(ms): """ formats the ms into seconds and ms :param ms: the number of ms :return: a string representing the same amount, but now represented in seconds and ms. """ sec = int(ms) // 1000 ms = int(ms) % 1000 if sec == 0: return '{0}ms'.format(ms) return '{0}.{1}s'....
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def form_binary_patterns(k: int) -> list: """ Return a list of strings containing all binary numbers of length not exceeding 'k' (with leading zeroes) """ result = [] format_string = '{{:0{}b}}'.format(k) for n in range(2 ** k): result.append(format_string.format(n)) return result
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def containsZero(n): """ n: an int or a str output: True if n contains '0' """ numStr = str(n) for letter in numStr: if letter is '0': return True return False
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def produit(a,b): """ renvoie le résultat de la multiplication des nombres a et b""" return a*b
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def extract_hairpin_name_and_sequence(file,sampleName): """ Reads one MIRNA cluster file It returns the corresponding cluster name and hairpin sequence in a Python dictionary Dictionary keys: cluster names Dictionary values: cluster sequences """ with open(file,"r") as filin: lines =...
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def _max_len(choices): """Given a list of char field choices, return the field max length""" lengths = [len(choice) for choice, _ in choices] return max(lengths)
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def CommandLine(command, args): """Convert an executable path and a sequence of arguments into a command line that can be passed to CreateProcess""" cmd = "\"" + command.replace("\"", "\"\"") + "\"" for arg in args: cmd = cmd + " \"" + arg.replace("\"", "\"\"") + "\"" return cmd
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import torch def reflect(v: torch.Tensor, axis: torch.Tensor): """reflect vector a w.r.t. axis Args: `v`: tensor of shape `[...,3]`. `axis`: tensor with the same shape or dim as `a`. Returns: the reflected vector """ axis = torch.broadcast_to(axis, v.shape) h_vec = 2*ax...
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import random import string def get_random_string(length=10): """Get a string with random content""" return ''.join(random.choice(string.ascii_uppercase) for i in range(length))
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def _convert_line_to_tab_from_orifile(line): """ :param line: :return: >>> _convert_line_to_tab_from_orifile('''IMG_1468832894.185000000.jpg -75.622522 -40.654833 -172.350586 \ 657739.197431 6860690.284637 53.534337''') ['IMG_1468832894.185000000.jpg', '...
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import torch def get_ja(arr): """ calculates jaw aperture (euclidean distance between UL / J (LI)): pertinent indexes: Jx : 6, ULx: 10, Jy : 7, ULy : 11 """ return torch.sqrt((arr[:,6]-arr[:,10])**2+(arr[:,7]-arr[:,11])**2)
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def is_ranged_value(value, min_value=None, max_value=None, min_inclusive: bool=True, max_inclusive: bool=True) -> bool: """ Parameters ---------- value : float float : the value as a float min_value / max_value : float / None float : the constraint is active ...
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def get_dynamic_edgelist(data): """ Make an edge list for all of the sequential visits of one site to the next in a day per user. Each edge is directed. There is a dummy start node to indicate the transition from being home to the first site visited that day """ data['total_people'] = 1 ...
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def linear_segment(x0, x1, y0, y1, t): """Return the linear function interpolating the given points.""" return y0 + (t - x0) / (x1 - x0) * (y1 - y0)
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from datetime import datetime def now() -> str: """Return string timestamp for current time, to the second.""" return datetime.utcnow().isoformat(timespec='seconds')
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from typing import Any from typing import Union from typing import List from typing import Sequence def _list_convert(x: Any) -> Union[Any, List[Any]]: """Converts argument to list if not already a sequence.""" return [x] if not isinstance(x, Sequence) else x
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def title(value): """ Title cases a string, replacing hyphens with spaces """ return value.replace('-', ' ').title()
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from typing import Iterable from typing import List def make_error_col_names(qcols: Iterable) -> List: """helper func to make error column names of the form <col_name>_low ... <col_name>_high Args: qcols (iterable): an iterable of column names used for matching Returns: list: list of e...
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import copy def add_node_to_path(node, path): """ Adds the name of the node to the copy of the list of strings inside the safely copied version of the path. Leave the other two items in path unchanged (total distance traveled and total number of buildings). Parameters: path: li...
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def get_div(value, start): """Returns the maximum divider for `value` starting from `start` value""" div = 1 for d in range(start, 0, -1): if (value % d) == 0: div = d break return div
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def pack_str(var): """Convert a string to a list of bytes.""" return str(var).encode("utf-8")
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import operator def hamming_distance(s1, s2, equality_function=operator.eq): """ Returns the hamming distance between two strings. """ if not len(s1) == len(s2): raise ValueError("String lengths are not equal") # Number of non-matching characters: return sum(not equality_function(c1, ...
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import six def iterable(obj, strok=False): """ Checks if the input implements the iterator interface. An exception is made for strings, which return False unless `strok` is True Args: obj (object): a scalar or iterable input strok (bool): if True allow strings to be interpreted as it...
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def annotation2rgb(i,palette,arr): """Go from annotation of patch to color. Parameters ---------- i:int Annotation index. palette:palette Index to color mapping. arr:array Image array. Returns ------- array Resulting image. """ col = palette[i] for i in range(3): arr[...,i] = int(col[i]*255) r...
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def fig_path(path, *specs, suffix='.png'): """Get output path for figure.""" stem = '-'.join((path.stem,) + specs) return (path.parent / stem).with_suffix(suffix)
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from typing import Callable from typing import Optional from typing import Tuple def then_parser( first_parser: Callable[[str], Optional[Tuple[str, str]]], second_parser: Callable[[str], Optional[Tuple[str, str]]], text: str, ) -> Optional[Tuple[str, str]]: """ Uses one parser on the text, then uses the next pa...
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import pickle def load_investment_results(iteration): """Load investment results""" with open(f'output/investment_plan/investment-results_{iteration}.pickle', 'rb') as f: results = pickle.load(f) return results
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def _translate_backupjobrun_summary_view(context, backupjobrun): """Maps keys for backupjobruns summary view.""" d = {} d['id'] = backupjobrun['id'] d['created_at'] = backupjobrun['created_at'] d['status'] = backupjobrun['status'] return d
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def inbreeding_as_dispersion(inbreeding, unique_haplotypes): """Calculate dispersion parameter of a Dirichlet-multinomial distribution assuming equal population frequency of each haplotype. Parameters ---------- inbreeding : float Expected inbreeding coefficient of the sample. unique_ha...
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def _pitch2m(res): """Convert pitch string to meters. Something like -600- is assumed to mean "six-hundreths of an inch". >>> _pitch2m("-600-") 4.233333333333333e-05 >>> _pitch2m("-1200-") 2.1166666666666665e-05 """ res = int(res[1:-1]) return 0.0254 / res
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def tmp_bdb_root(mocker, tmp_path): """Set a temporary root directory for the BerkeleyDB minter hierarchy. By default, a BDB path resolved by the minter will reference a location in EZID's minter hierarchy, as configured in the EZID settings. Currently, `ezid/db/minters`. This fixture causes BDB paths ...
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def parse_csv(columns, line): """ Parse a CSV line that has ',' as a separator. Columns is a list of the column names, must match the number of comma-separated values in the input line. """ data = {} split = line.split(',') for idx, name in enumerate(columns): data[name] = split[...
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def armstrong(some_int: int) -> bool: """ Accepts an int Returns whether or not int is an armstrong number :param some_int: :return: """ string_rep = str(some_int) sum_val = 0 for digit in string_rep: sum_val += int(digit) ** 3 return some_int == sum_val
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def prepare_auth_params_json(bot, manifest): """Returns a dict to put into JSON file passed to task_runner. This JSON file contains various tokens and configuration parameters that allow task_runner to make HTTP calls authenticated by bot's own credentials. The file is managed by bot_main.py (main Swarming bo...
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import ast def get_input(arg, valid_keys): """Convert the input to a dict and perform basic validation""" json_string = arg.replace("\\n", "\n") try: input_dict = ast.literal_eval(json_string) if not all(k in input_dict for k in valid_keys): return None except Exception: ...
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import requests import json import logging def authenticate_with_ome(ip_address: str, user_name: str, password: str) -> tuple: """ Authenticates a session against an OME server Args: ip_address: IP address of the OME server user_name: Username for OME password: Password for the OM...
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def searchForInsert(sortedList:list, value:float)->int: """Search for where to insert the value for the list to remain sorted Args: sortedList (list): a sorted list value (float): the value to insert into the sorted list Returns: int: the index where to insert the value """ ...
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def deep_to(batch, device, dtype): """ Static method to call :func:`to` on tensors or tuples. All items in tuple will have :func:`deep_to` called Args: batch (tuple / list / :class:`torch.Tensor`): The mini-batch which requires a :func:`to` call device (:class:`torch.device`): The desired devic...
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def sum_two_smallest_numbers(numbers): """Find two lowest positive integers and add them.""" return sorted(numbers)[0] + sorted(numbers)[1]
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import re def parse_log(line): """Parse logs with regex Function that parse raw logs and extracts request_time and url Args: line: Decoded line Returns: reqest_time_data: float number or None if log can't be parsed url_data: String or None if log can't be parsed """ ...
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def deregister_sub(topics_to_subs, sub): """Deregister a Subscription from a mapping topics->subscriptions. Args: topics_to_subs (dict): dictionnary topic -> list of subscriptions sub (Subscription): subscription to deregister """ key = str(sub.topics) if key in topics_to_subs: ...
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def server_status_field(log, server_status, field_name): """ Return (0, result) for a field of BarreleServerStatusCache """ # pylint: disable=unused-argument return server_status.bssc_field_result(log, field_name)
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import warnings def normalize_df( df, method, drop_degenerate_cols=True, replace_zero_denom=False): """For a given dataframe with columns including numerical values, it generates a function which can be applied to original data as well as any future data to normalize using ...
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def _check_handle(handle): """Checks if provided file handle is valid.""" return handle is not None and handle.fileno() >= 0
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def clear_data_for_origin(origin: str, storageTypes: str) -> dict: """Clears storage for origin. Parameters ---------- origin: str Security origin. storageTypes: str Comma separated list of StorageType to clear. """ return { "method": "Storage.clearDataForOri...
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def get_one_item(CURSOR, BARCODE): """ Returns the specified item from the database, determined by the primary key - in this case the barcode number. Args: CURSOR (object): BARCODE (str): the barcode number Returns: ITEM (list): the item in the database """ ITEM = CURSOR.execute(""" SEL...
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def linear_search(L, v): """ (list, object) -> int Return the index of the first occurrence of v in L, or return -1 if v is not in L. >>> linear_search([2, 3, 5, 3], 2) 0 >>> linear_search([2, 3, 5, 3], 5) 2 >>> linear_search([2, 3, 5, 3], 8) -1 """ i = 0 while i != l...
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def matrix_identity(n: int) -> list: """ Generate the n-sized identity matrix. """ if n == 0: return [0] identity: list = [] for col in range(n): column: list = [] for row in range(n): if col == row: column.append(1) else: ...
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def get_gcd(x, y): """Calculate the greatest common divisor of two numbers.""" if y > x: x, y = y, x r = x % y if r == 0: return y else: result = get_gcd(y, r) return result
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import math def repeat_data(preload, num_simulation_steps): """Repeats the transformer preload data until there are as many values as there are simulation steps. Args: preload: (list): Containing the data (floats) to be repeated. num_simulation_steps: (int): Number of simulation steps and...
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def get_node_and_attribute(attribute): """ Split a name between its node and its attribute. Args: attribute (str): attribute name, node.attribute. Returns: list: [node_name, attribute] """ split_attribute = attribute.split('.') if not split_att...
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def txn_data(df, txns): """Return dataframe with supplied transactions.""" return df[df.transaction_id.isin(txns)].copy()
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def _parse_nyquist_vel(nyquist_vel, radar, check_uniform): """ Parse the nyquist_vel parameter, extract from the radar if needed. """ if nyquist_vel is None: nyquist_vel = [radar.get_nyquist_vel(i, check_uniform) for i in range(radar.nsweeps)] else: # Nyquist velocity explic...
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def applyBandOffset(C, height, bandName, lines, inter=False): """Produce bands from a list of lines. Bands are defined relative to lines by means of offsets of the top and bottom heights of the lines. Bands may also be interlinear: defined between the bottom of one line and the top of the next lin...
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