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def __get_hosts_filename(): return __salt__['config.option']('hosts.file')
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return the path to the appropriate hosts file .
train
false
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def collect_bears(bear_dirs, bear_globs, kinds, log_printer, warn_if_unused_glob=True): bears_found = tuple(([] for i in range(len(kinds)))) bear_globs_with_bears = set() for (bear, glob) in icollect_bears(bear_dirs, bear_globs, kinds, log_printer): index = kinds.index(_get_kind(bear)) bears_found[index].append(bear) bear_globs_with_bears.add(glob) if warn_if_unused_glob: _warn_if_unused_glob(log_printer, bear_globs, bear_globs_with_bears, "No bears matching '{}' were found. Make sure you have coala-bears installed or you have typed the name correctly.") return bears_found
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collect all bears from bear directories that have a matching kind matching the given globs .
train
false
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def _prep_stats_dict(values): stats = [] d = values.get('stats', {}) for (k, v) in d.iteritems(): stat = models.ComputeNodeStat() stat['key'] = k stat['value'] = v stats.append(stat) values['stats'] = stats
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make list of computenodestats .
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def arcball_nearest_axis(point, axes): point = numpy.array(point, dtype=numpy.float64, copy=False) nearest = None mx = (-1.0) for axis in axes: t = numpy.dot(arcball_constrain_to_axis(point, axis), point) if (t > mx): nearest = axis mx = t return nearest
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return axis .
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def contains_nan(arr, node=None, var=None): if isinstance(arr, theano.gof.type._cdata_type): return False elif isinstance(arr, np.random.mtrand.RandomState): return False elif (var and getattr(var.tag, 'is_rng', False)): return False elif isinstance(arr, slice): return False elif (arr.size == 0): return False elif (cuda.cuda_available and isinstance(arr, cuda.CudaNdarray)): if (node and hasattr(theano.sandbox, 'rng_mrg') and isinstance(node.op, theano.sandbox.rng_mrg.GPU_mrg_uniform)): return False else: compile_gpu_func(True, False, False) return np.isnan(f_gpumin(arr.reshape(arr.size))) elif (pygpu_available and isinstance(arr, GpuArray)): return np.isnan(f_gpua_min(arr.reshape(arr.size))) return np.isnan(np.min(arr))
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test whether a numpy .
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def wait_for_free_port(host, port, timeout=None): if (not host): raise ValueError("Host values of '' or None are not allowed.") if (timeout is None): timeout = free_port_timeout for trial in range(50): try: check_port(host, port, timeout=timeout) except IOError: time.sleep(timeout) else: return raise IOError(('Port %r not free on %r' % (port, host)))
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wait for the specified port to become free .
train
false
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def offset_spines(offset=10, fig=None, ax=None): warn_msg = '`offset_spines` is deprecated and will be removed in v0.5' warnings.warn(warn_msg, UserWarning) if ((fig is None) and (ax is None)): axes = plt.gcf().axes elif (fig is not None): axes = fig.axes elif (ax is not None): axes = [ax] for ax_i in axes: for spine in ax_i.spines.values(): _set_spine_position(spine, ('outward', offset))
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simple function to offset spines away from axes .
train
false
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@verbose def spatio_temporal_dist_connectivity(src, n_times, dist, verbose=None): if (src[0]['dist'] is None): raise RuntimeError('src must have distances included, consider using\nmne_add_patch_info with --dist argument') edges = sparse_block_diag([s['dist'][s['vertno'], :][:, s['vertno']] for s in src]) edges.data[:] = np.less_equal(edges.data, dist) edges = edges.tocsr() edges.eliminate_zeros() edges = edges.tocoo() return _get_connectivity_from_edges(edges, n_times)
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compute connectivity from distances in a source space and time instants .
train
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def security_group_rule_get_by_instance(context, instance_uuid): return IMPL.security_group_rule_get_by_instance(context, instance_uuid)
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get all rules for a given instance .
train
false
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def get_font(section='main', option='font', font_size_delta=0): font = FONT_CACHE.get((section, option)) if (font is None): families = CONF.get(section, (option + '/family'), None) if (families is None): return QFont() family = get_family(families) weight = QFont.Normal italic = CONF.get(section, (option + '/italic'), False) if CONF.get(section, (option + '/bold'), False): weight = QFont.Bold size = (CONF.get(section, (option + '/size'), 9) + font_size_delta) font = QFont(family, size, weight) font.setItalic(italic) FONT_CACHE[(section, option)] = font size = (CONF.get(section, (option + '/size'), 9) + font_size_delta) font.setPointSize(size) return font
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get console font properties depending on os and user options .
train
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def flexible_boolean(boolean): if (boolean in ('1', 'true', 'True')): return True else: return False
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returns true for any of "1" .
train
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def get_all_remote_methods(resolver=None, ns_prefix=u''): if (not resolver): resolver = get_resolver(get_urlconf()) result = {} for name in resolver.reverse_dict.keys(): if (not isinstance(name, six.string_types)): continue try: url = reverse((ns_prefix + name)) resmgr = resolve(url) ViewClass = import_string(u'{0}.{1}'.format(resmgr.func.__module__, resmgr.func.__name__)) if (isclass(ViewClass) and issubclass(ViewClass, JSONResponseMixin)): result[name] = _get_remote_methods_for(ViewClass, url) except (NoReverseMatch, ImproperlyConfigured): pass for (namespace, ns_pattern) in resolver.namespace_dict.items(): sub_res = get_all_remote_methods(ns_pattern[1], ((ns_prefix + namespace) + u':')) if sub_res: result[namespace] = sub_res return result
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returns a dictionary to be used for calling djangocall .
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def print_and_modify(obj, mods, dels): obj.update(mods) for field in dels: try: del obj[field] except KeyError: pass return ui.show_model_changes(obj)
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print the modifications to an item and return a bool indicating whether any changes were made .
train
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def backup_destroy(context, backup_id): return IMPL.backup_destroy(context, backup_id)
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destroy the backup or raise if it does not exist .
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def __determine_resource_obj(service, resource): path = resource.split('.') node = service for elem in path: try: node = getattr(node, elem)() except AttributeError: raise AttributeError('"{0}" has no attribute "{1}"'.format('.'.join(path[0:path.index(elem)]), elem)) return node
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find the desired resource object method container from the service .
train
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def _get_hold(line, pattern=__HOLD_PATTERN, full=True): if full: if (_yum() == 'dnf'): lock_re = '({0}-\\S+)'.format(pattern) else: lock_re = '(\\d+:{0}-\\S+)'.format(pattern) elif (_yum() == 'dnf'): lock_re = '({0}-\\S+)'.format(pattern) else: lock_re = '\\d+:({0}-\\S+)'.format(pattern) match = re.search(lock_re, line) if match: if (not full): woarch = match.group(1).rsplit('.', 1)[0] worel = woarch.rsplit('-', 1)[0] return worel.rsplit('-', 1)[0] else: return match.group(1) return None
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resolve a package name from a line containing the hold expression .
train
true
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@login_required def delete_favorite(req, id): try: favorite = models.Favorite.objects.get(user=req.user, pk=id) favorite.delete() except ObjectDoesNotExist: pass response = {'has_favorite': 'false'} return HttpResponse(json.dumps(response), content_type='application/json', status=200)
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delete favorite and put favorite_info object in response .
train
false
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def set_task_user(f): @functools.wraps(f) def wrapper(*args, **kw): old_user = get_user() set_user(get_task_user()) try: result = f(*args, **kw) finally: set_user(old_user) return result return wrapper
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sets the user to be the task user .
train
false
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def parseString(string, namespaces=True): if namespaces: builder = ExpatBuilderNS() else: builder = ExpatBuilder() return builder.parseString(string)
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parse a document from a string .
train
false
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def getblock(lines): blockfinder = BlockFinder() try: tokenize.tokenize(iter(lines).next, blockfinder.tokeneater) except (EndOfBlock, IndentationError): pass return lines[:blockfinder.last]
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extract the block of code at the top of the given list of lines .
train
false
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def tolist(val): if (val is None): return None try: val.extend([]) return val except AttributeError: pass try: return re.split('\\s*,\\s*', val) except TypeError: return list(val)
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convert a value that may be a list or a string into a list .
train
true
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def worker_destroy(context, **filters): query = _worker_query(context, **filters) return query.delete()
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delete a worker .
train
false
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def create_chunks(sequence, size): return (sequence[p:(p + size)] for p in range(0, len(sequence), size))
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generate chunks from a sequence .
train
false
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def dont_import_local_tempest_into_lib(logical_line, filename): if ('tempest/lib/' not in filename): return if (not (('from tempest' in logical_line) or ('import tempest' in logical_line))): return if (('from tempest.lib' in logical_line) or ('import tempest.lib' in logical_line)): return msg = 'T112: tempest.lib should not import local tempest code to avoid circular dependency' (yield (0, msg))
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check that tempest .
train
false
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def task_upgrade_kernel(distribution): if is_centos_or_rhel(distribution): return sequence([yum_install(['kernel-devel', 'kernel']), run_from_args(['sync'])]) elif is_ubuntu(distribution): return sequence([]) else: raise DistributionNotSupported(distribution=distribution)
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upgrade kernel .
train
false
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@app.route('/delay/<delay>') def delay_response(delay): delay = min(float(delay), 10) time.sleep(delay) return jsonify(get_dict('url', 'args', 'form', 'data', 'origin', 'headers', 'files'))
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returns a delayed response .
train
true
53,781
def is_larger(unit_1, unit_2): unit_1 = functions.value_for_key(INFORMATION_UNITS, unit_1) unit_2 = functions.value_for_key(INFORMATION_UNITS, unit_2) return (ureg.parse_expression(unit_1) > ureg.parse_expression(unit_2))
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returns a boolean indicating whether unit_1 is larger than unit_2 .
train
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def requirement_available(requirement): try: util.activate(requirement) except errors.DependencyError: return False return True
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checks if requirement can be imported .
train
false
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def detachAcceptMsOriginating(): a = TpPd(pd=3) b = MessageType(mesType=6) c = ForceToStandbyAndSpareHalfOctets() packet = ((a / b) / c) return packet
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detach accept section 9 .
train
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def parse_http_load(full_load, http_methods): try: (headers, body) = full_load.split('\r\n\r\n', 1) except ValueError: headers = full_load body = '' header_lines = headers.split('\r\n') http_line = get_http_line(header_lines, http_methods) if (not http_line): headers = '' body = full_load header_lines = [line for line in header_lines if (line != http_line)] return (http_line, header_lines, body)
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split the raw load into list of headers and body string .
train
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def long_to_bson_ts(val): seconds = (val >> 32) increment = (val & 4294967295) return Timestamp(seconds, increment)
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convert integer into bson timestamp .
train
false
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@core_helper def resource_preview(resource, package): if (not resource['url']): return False datapreview.res_format(resource) directly = False data_dict = {'resource': resource, 'package': package} if datapreview.get_preview_plugin(data_dict, return_first=True): url = url_for(controller='package', action='resource_datapreview', resource_id=resource['id'], id=package['id'], qualified=True) else: return False return snippet('dataviewer/snippets/data_preview.html', embed=directly, resource_url=url, raw_resource_url=resource.get('url'))
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returns a rendered snippet for a embedded resource preview .
train
false
53,788
def keybinding(attr): ks = getattr(QKeySequence, attr) return from_qvariant(QKeySequence.keyBindings(ks)[0], str)
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return keybinding .
train
true
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def get_current_timezone(): return getattr(_active, 'value', get_default_timezone())
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returns the currently active time zone as a tzinfo instance .
train
false
53,790
def _get_lights(): return _query(None, None)
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get all available lighting devices .
train
false
53,792
def _ssh_slave_addresses(ssh_bin, master_address, ec2_key_pair_file): if ((not ec2_key_pair_file) or (not os.path.exists(ec2_key_pair_file))): return [] cmd = "hadoop dfsadmin -report | grep ^Name | cut -f2 -d: | cut -f2 -d' '" args = [('bash -c "%s"' % cmd)] ips = to_string(_check_output(*_ssh_run(ssh_bin, master_address, ec2_key_pair_file, args))) return [ip for ip in ips.split('\n') if ip]
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get the ip addresses of the slave nodes .
train
false
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def get_user_api_key(): return os.environ.get('GALAXY_TEST_USER_API_KEY', DEFAULT_GALAXY_USER_API_KEY)
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test user api key to use for functional tests .
train
false
53,794
def overwrite_from_dates(asof, dense_dates, sparse_dates, asset_idx, value): if (asof is pd.NaT): return first_row = dense_dates.searchsorted(asof) next_idx = sparse_dates.searchsorted(asof.asm8, 'right') if (next_idx == len(sparse_dates)): last_row = (len(dense_dates) - 1) else: last_row = (dense_dates.searchsorted(sparse_dates[next_idx]) - 1) if (first_row > last_row): return (first, last) = asset_idx (yield Float64Overwrite(first_row, last_row, first, last, value))
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construct a float64overwrite with the correct start and end date based on the asof date of the delta .
train
false
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def item_create(item, item_id, item_type, create='create', extra_args=None, cibfile=None): cmd = ['pcs'] if isinstance(cibfile, six.string_types): cmd += ['-f', cibfile] if isinstance(item, six.string_types): cmd += [item] elif isinstance(item, (list, tuple)): cmd += item if (item in ['constraint']): if isinstance(item_type, six.string_types): cmd += [item_type] if isinstance(create, six.string_types): cmd += [create] elif isinstance(create, (list, tuple)): cmd += create if (item not in ['constraint']): cmd += [item_id] if isinstance(item_type, six.string_types): cmd += [item_type] if isinstance(extra_args, (list, tuple)): if (item in ['constraint']): extra_args = (extra_args + ['id={0}'.format(item_id)]) cmd += extra_args return __salt__['cmd.run_all'](cmd, output_loglevel='trace', python_shell=False)
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create an item via pcs command item config .
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def _connect_user(request, facebook, overwrite=True): if (not request.user.is_authenticated()): raise ValueError('Connect user can only be used on authenticated users') if (not facebook.is_authenticated()): raise ValueError('Facebook needs to be authenticated for connect flows') data = facebook.facebook_profile_data() facebook_id = data['id'] old_connections = _get_old_connections(facebook_id, request.user.id)[:20] if (old_connections and (not (request.POST.get('confirm_connect') or request.GET.get('confirm_connect')))): raise facebook_exceptions.AlreadyConnectedError(list(old_connections)) user = _update_user(request.user, facebook, overwrite=overwrite) return user
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update the fields on the user model and connects it to the facebook account .
train
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def path_separator(): return PATH_SEPARATOR[_os.name]
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get the path separator for the current operating system .
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def _string_from_json(value, _): return value
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noop string -> string coercion .
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def is_coroutine(function): return ((function.__code__.co_flags & 128) or getattr(function, '_is_coroutine', False))
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returns true if the passed in function is a coroutine .
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def nextLine(): caller = currentframe(1) return (getsourcefile(sys.modules[caller.f_globals['__name__']]), (caller.f_lineno + 1))
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retrive the file name and line number immediately after where this function is called .
train
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def _ConvertToCygpath(path): if (sys.platform == 'cygwin'): p = subprocess.Popen(['cygpath', path], stdout=subprocess.PIPE) path = p.communicate()[0].strip() return path
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convert to cygwin path if we are using cygwin .
train
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def load_werkzeug(path): sys.path[0] = path wz.__dict__.clear() for key in sys.modules.keys(): if (key.startswith('werkzeug.') or (key == 'werkzeug')): sys.modules.pop(key, None) import werkzeug for key in werkzeug.__all__: setattr(wz, key, getattr(werkzeug, key)) hg_tag = find_hg_tag(path) try: f = open(os.path.join(path, 'setup.py')) except IOError: pass else: try: for line in f: line = line.strip() if line.startswith('version='): return (line[8:].strip(' DCTB ,')[1:(-1)], hg_tag) finally: f.close() print >>sys.stderr, 'Unknown werkzeug version loaded' sys.exit(2)
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load werkzeug .
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def get_ip_version(network): if (netaddr.IPNetwork(network).version == 6): return 'IPv6' elif (netaddr.IPNetwork(network).version == 4): return 'IPv4'
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returns the ip version of a network .
train
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def make_secret_key(project_directory): local_setting = os.path.join(project_directory, 'config/settings/local.py') set_secret_key(local_setting) env_file = os.path.join(project_directory, 'env.example') set_secret_key(env_file)
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generates and saves random secret key .
train
false
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def samplesize_confint_proportion(proportion, half_length, alpha=0.05, method='normal'): q_ = proportion if (method == 'normal'): n = ((q_ * (1 - q_)) / ((half_length / stats.norm.isf((alpha / 2.0))) ** 2)) else: raise NotImplementedError('only "normal" is available') return n
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find sample size to get desired confidence interval length parameters proportion : float in proportion or quantile half_length : float in desired half length of the confidence interval alpha : float in significance level .
train
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def get_pointer(ctypes_func): return ctypes.cast(ctypes_func, ctypes.c_void_p).value
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get a pointer to the underlying function for a ctypes function as an integer .
train
false
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def _generate_meta(): d = {'root_url': request.url_root} return d
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generate meta information for export .
train
false
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def test_system_numerics_complex(): print 'TODO'
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URL this should be tested minimally here .
train
false
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def next_redirect(data, default, default_view, **get_kwargs): next = data.get('next', default) if (next is None): next = urlresolvers.reverse(default_view) if get_kwargs: if ('#' in next): tmp = next.rsplit('#', 1) next = tmp[0] anchor = ('#' + tmp[1]) else: anchor = '' joiner = ((('?' in next) and '&') or '?') next += ((joiner + urllib.urlencode(get_kwargs)) + anchor) return HttpResponseRedirect(next)
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handle the "where should i go next?" part of comment views .
train
false
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def quote_unix(value): value = six.moves.shlex_quote(value) return value
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return a quoted version of the value which can be used as one token in a shell command line .
train
false
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@LocalContext def unpack_many(data, word_size=None): word_size = (word_size or context.word_size) endianness = context.endianness sign = context.sign if (word_size == 'all'): return [unpack(data, word_size)] if ((word_size % 8) != 0): raise ValueError('unpack_many(): word_size must be a multiple of 8') out = [] n = (word_size // 8) for i in range(0, len(data), n): out.append(unpack(data[i:(i + n)], word_size)) return list(map(int, out))
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unpack -> int list splits data into groups of word_size//8 bytes and calls :func:unpack on each group .
train
false
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@_FFI.callback(u'Value(ExternContext*, uint8_t*, uint64_t)') def extern_create_exception(context_handle, msg_ptr, msg_len): c = _FFI.from_handle(context_handle) msg = bytes(_FFI.buffer(msg_ptr, msg_len)).decode(u'utf-8') return c.to_value(Exception(msg))
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given a utf8 message string .
train
false
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def stub_out(test, funcs): for (module, func) in funcs.items(): test.stub_out(module, func)
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set the stubs in mapping in the db api .
train
false
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def decode_barcode_8(nt_barcode): if (len(nt_barcode) != 8): raise ValueError('barcode must be 8 nt long.') if set(list(nt_barcode)).difference(CUR_ENC_FO.keys()): raise ValueError('Only A,T,C,G valid chars.') decoded = nt_to_cw(CUR_ENC_FO, nt_barcode) (num_errors, sym) = calc_syndrome(decoded, 16) if (num_errors == 1): nt_barcode = unpack_bitstr(CUR_REV_ENC_SI, ''.join(map(str, decoded))) elif (num_errors > 1): nt_barcode = None return (nt_barcode, (num_errors / 2.0))
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decode length 8 barcode .
train
false
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def global_subsystem_instance(subsystem_type, options=None): init_subsystem(subsystem_type, options) return subsystem_type.global_instance()
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returns the global instance of a subsystem .
train
false
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def _check_surfaces(surfs): for surf in surfs: _assert_complete_surface(surf) for (surf_1, surf_2) in zip(surfs[:(-1)], surfs[1:]): logger.info(('Checking that %s surface is inside %s surface...' % (_surf_name[surf_2['id']], _surf_name[surf_1['id']]))) _assert_inside(surf_2, surf_1)
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check that the surfaces are complete and non-intersecting .
train
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def is_pidfile_stale(pidfile): result = False pidfile_pid = pidfile.read_pid() if (pidfile_pid is not None): try: os.kill(pidfile_pid, signal.SIG_DFL) except OSError as exc: if (exc.errno == errno.ESRCH): result = True return result
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determine whether a pid file is stale .
train
false
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def trimHistory(): failed_db_con = db.DBConnection('failed.db') failed_db_con.action(('DELETE FROM history WHERE date < ' + str((datetime.datetime.today() - datetime.timedelta(days=30)).strftime(History.date_format))))
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trims history table to 1 month of history from today .
train
false
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def buttap(N): if (abs(int(N)) != N): raise ValueError('Filter order must be a nonnegative integer') z = numpy.array([]) m = numpy.arange(((- N) + 1), N, 2) p = (- numpy.exp((((1j * pi) * m) / (2 * N)))) k = 1 return (z, p, k)
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return for analog prototype of nth-order butterworth filter .
train
false
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def create_version_h(svn_version): if ('-' in svn_version): while (svn_version.count('.') < 2): svn_version = svn_version.replace('-', '.0-') else: while (svn_version.count('.') < 2): svn_version += '.0' version_h = open(os.path.join(get_base_dir(), 'src', 'lxml', 'includes', 'lxml-version.h'), 'w') version_h.write(('#ifndef LXML_VERSION_STRING\n#define LXML_VERSION_STRING "%s"\n#endif\n' % svn_version)) version_h.close()
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create lxml-version .
train
false
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@authenticated_json_view @has_request_variables def json_subscription_property(request, user_profile, subscription_data=REQ(validator=check_list(check_dict([('stream', check_string), ('property', check_string), ('value', check_variable_type([check_string, check_bool]))])))): if (request.method != 'POST'): return json_error(_('Invalid verb')) property_converters = {'color': check_string, 'in_home_view': check_bool, 'desktop_notifications': check_bool, 'audible_notifications': check_bool, 'pin_to_top': check_bool} response_data = [] for change in subscription_data: stream_name = change['stream'] property = change['property'] value = change['value'] if (property not in property_converters): return json_error((_('Unknown subscription property: %s') % (property,))) sub = get_subscription_or_die(stream_name, user_profile)[0] property_conversion = property_converters[property](property, value) if property_conversion: return json_error(property_conversion) do_change_subscription_property(user_profile, sub, stream_name, property, value) response_data.append({'stream': stream_name, 'property': property, 'value': value}) return json_success({'subscription_data': response_data})
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this is the entry point to changing subscription properties .
train
false
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def project_time_week(row): try: thisdate = row['project_time.date'] except AttributeError: return current.messages['NONE'] if (not thisdate): return current.messages['NONE'] day = thisdate.date() monday = (day - datetime.timedelta(days=day.weekday())) return monday
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virtual field for project_time - returns the date of the monday of this entry .
train
false
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def start_time(pid): if ((not isinstance(pid, int)) or (pid < 0)): return None if stem.util.proc.is_available(): try: return float(stem.util.proc.stats(pid, stem.util.proc.Stat.START_TIME)[0]) except IOError: pass try: ps_results = call(('ps -p %s -o etime' % pid), []) if (len(ps_results) >= 2): etime = ps_results[1].strip() return (time.time() - stem.util.str_tools.parse_short_time_label(etime)) except: pass return None
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provides the unix timestamp when the given process started .
train
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def init(mpstate): return SerialModule(mpstate)
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initialise module .
train
false
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def _get_search_rank(collection_id): rights = rights_manager.get_collection_rights(collection_id) rank = (_DEFAULT_RANK + (_STATUS_PUBLICIZED_BONUS if (rights.status == rights_manager.ACTIVITY_STATUS_PUBLICIZED) else 0)) return max(rank, 0)
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gets the search rank of a given collection .
train
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def append_slash_redirect(environ, code=301): new_path = (environ['PATH_INFO'].strip('/') + '/') query_string = environ.get('QUERY_STRING') if query_string: new_path += ('?' + query_string) return redirect(new_path, code)
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redirect to the same url but with a slash appended .
train
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def group_list_of_dict(array): result = defaultdict(list) for item in array: for (key, value) in item.items(): result[key] += (value if isinstance(value, list) else [value]) return result
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helper method to group list of dict to dict with all possible values .
train
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def bind_expression_to_resources(expr, resources): if (resources is None): resources = {} return expr._subs({k: bz.data(v, dshape=k.dshape) for (k, v) in iteritems(resources)})
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bind a blaze expression to resources .
train
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@release.command() def changelog(): print changelog_as_markdown()
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get the most recent versions changelog as markdown .
train
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def cscore(v1, v2): v1_b = v1.astype(bool) v2_b = v2.astype(bool) sij = (v1_b * v2_b).sum() return ((v1_b.sum() - sij) * (v2_b.sum() - sij))
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calculate c-score between v1 and v2 according to stone and roberts 1990 .
train
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def compute_grad(J, f): if isinstance(J, LinearOperator): return J.rmatvec(f) else: return J.T.dot(f)
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compute gradient of the least-squares cost function .
train
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def require_module(module): def check_require_module(f): try: __import__(module) return f except ImportError: def new_f(self, *args, **kwargs): self.skipTest(('%s can not be imported.' % module)) new_f.__name__ = f.__name__ return new_f return check_require_module
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check if the given module is loaded .
train
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def bayesian_info_criterion_lsq(ssr, n_params, n_samples): return bayesian_info_criterion((((-0.5) * n_samples) * np.log((ssr / n_samples))), n_params, n_samples)
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computes the bayesian information criterion assuming that the observations come from a gaussian distribution .
train
false
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def with_inline_css(html_without_css): css_filepath = settings.NOTIFICATION_EMAIL_CSS if (not css_filepath.startswith('/')): css_filepath = file_path_finder(settings.NOTIFICATION_EMAIL_CSS) if css_filepath: with open(css_filepath, 'r') as _file: css_content = _file.read() html_with_inline_css = pynliner.fromString(((('<style>' + css_content) + '</style>') + html_without_css)) return html_with_inline_css return html_without_css
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returns html with inline css if the css file path exists else returns html with out the inline css .
train
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@testing.requires_testing_data def test_preload_modify(): tempdir = _TempDir() rng = np.random.RandomState(0) for preload in [False, True, 'memmap.dat']: raw = read_raw_fif(fif_fname, preload=preload) nsamp = ((raw.last_samp - raw.first_samp) + 1) picks = pick_types(raw.info, meg='grad', exclude='bads') data = rng.randn(len(picks), (nsamp // 2)) try: raw[picks, :(nsamp // 2)] = data except RuntimeError as err: if (not preload): continue else: raise err tmp_fname = op.join(tempdir, 'raw.fif') raw.save(tmp_fname, overwrite=True) raw_new = read_raw_fif(tmp_fname) (data_new, _) = raw_new[picks, :(nsamp / 2)] assert_allclose(data, data_new)
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test preloading and modifying data .
train
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def sample_content(name): with open(('tests/components/media_player/yamaha_samples/%s' % name), encoding='utf-8') as content: return content.read()
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read content into a string from a file .
train
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def write_trace(expt_dir, best_val, best_job, n_candidates, n_pending, n_complete): trace_fh = open(os.path.join(expt_dir, 'trace.csv'), 'a') trace_fh.write(('%d,%f,%d,%d,%d,%d\n' % (time.time(), best_val, best_job, n_candidates, n_pending, n_complete))) trace_fh.close()
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append current experiment state to trace file .
train
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def squared_loss(y_true, y_pred): return (((y_true - y_pred) ** 2).mean() / 2)
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compute the squared loss for regression .
train
false
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def code_name(code, number=0): hash_digest = hashlib.md5(code.encode('utf-8')).hexdigest() return '<ipython-input-{0}-{1}>'.format(number, hash_digest[:12])
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compute a unique name for code for caching .
train
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def pack_bitstring(bits): ret = '' i = packed = 0 for bit in bits: if bit: packed += 128 i += 1 if (i == 8): ret += chr(packed) i = packed = 0 else: packed >>= 1 if ((i > 0) and (i < 8)): packed >>= (7 - i) ret += chr(packed) return ret
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creates a string out of an array of bits .
train
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def generate_fused_type(codes): cytypes = map((lambda x: CY_TYPES[x]), codes) name = (codes + '_number_t') declaration = [(('ctypedef fused ' + name) + ':')] for cytype in cytypes: declaration.append((' ' + cytype)) declaration = '\n'.join(declaration) return (name, declaration)
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generate name of and cython code for a fused type .
train
false
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@timefunc(1) def conesearch_timer(*args, **kwargs): return conesearch(*args, **kwargs)
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time a single cone search using astropy .
train
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def is_valid_connection_id(entry): return is_valid_circuit_id(entry)
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checks if a string is a valid format for being a connection identifier .
train
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def join_list(delimeter): def join_string_lambda(value): return delimeter.join(value) return join_string_lambda
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join a list into a string using the delimeter .
train
false
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def get_elliptic_curves(): return _EllipticCurve._get_elliptic_curves(_lib)
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return a set of objects representing the elliptic curves supported in the openssl build in use .
train
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def reset(): _runtime.reset()
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reset the cuda subsystem for the current thread .
train
false
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def escape4xml(value): if isinstance(value, int): value = str(value) value = _re_amp.sub('&amp;', value) value = value.replace('"', '&quot;').replace("'", '&apos;') value = value.replace('<', '&lt;').replace('>', '&gt;') if isinstance(value, unicode): value = value.encode('ascii', 'xmlcharrefreplace') return value
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escape some chars that cant be present in a xml value .
train
false
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def owner(*paths): return __salt__['lowpkg.owner'](*paths)
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return the name of the package that owns the file .
train
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def set_default_etree(etree): from pyamf import xml return xml.set_default_interface(etree)
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sets the default interface that will called apon to both de/serialise xml entities .
train
false
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def find_it(): with RopeContext() as ctx: (_, offset) = env.get_offset_params() try: occurrences = findit.find_occurrences(ctx.project, ctx.resource, offset) except exceptions.BadIdentifierError: occurrences = [] lst = [] for oc in occurrences: lst.append(dict(filename=oc.resource.path, text=(env.lines[(oc.lineno - 1)] if (oc.resource.real_path == env.curbuf.name) else ''), lnum=oc.lineno)) env.let('loclist._loclist', lst)
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find occurrences .
train
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def inroot_notwritable(prefix): return (abspath(prefix).startswith(context.root_dir) and (not context.root_writable))
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return true if the prefix is under root and root is not writeable .
train
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def find_tables(clause, check_columns=False, include_aliases=False, include_joins=False, include_selects=False, include_crud=False): tables = [] _visitors = {} if include_selects: _visitors['select'] = _visitors['compound_select'] = tables.append if include_joins: _visitors['join'] = tables.append if include_aliases: _visitors['alias'] = tables.append if include_crud: _visitors['insert'] = _visitors['update'] = _visitors['delete'] = (lambda ent: tables.append(ent.table)) if check_columns: def visit_column(column): tables.append(column.table) _visitors['column'] = visit_column _visitors['table'] = tables.append visitors.traverse(clause, {'column_collections': False}, _visitors) return tables
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locate table objects within the given expression .
train
false
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def get_benchmark_returns(symbol, start_date, end_date): return pd.read_csv(format_yahoo_index_url(symbol, start_date, end_date), parse_dates=['Date'], index_col='Date', usecols=['Adj Close', 'Date'], squeeze=True).sort_index().tz_localize('UTC').pct_change(1).iloc[1:]
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get a series of benchmark returns from yahoo .
train
false
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def set_date(name, date): cmd = 'chage -d {0} {1}'.format(date, name) return (not __salt__['cmd.run'](cmd, python_shell=False))
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sets the value for the date the password was last changed to days since the epoch .
train
false
53,877
def get_os_vendor(): logging.warn('utils.get_os_vendor() is deprecated, please use autotest.client.shared.distro.detect() instead') vendor = 'Unknown' if os.path.isfile('/etc/SuSE-release'): return 'SUSE' issue = '/etc/issue' if (not os.path.isfile(issue)): return vendor if file_contains_pattern(issue, 'Red Hat'): vendor = 'Red Hat' if file_contains_pattern(issue, 'CentOS'): vendor = 'Red Hat' elif file_contains_pattern(issue, 'Fedora'): vendor = 'Fedora' elif file_contains_pattern(issue, 'SUSE'): vendor = 'SUSE' elif file_contains_pattern(issue, 'Ubuntu'): vendor = 'Ubuntu' elif file_contains_pattern(issue, 'Debian'): vendor = 'Debian' logging.debug('Detected OS vendor: %s', vendor) return vendor
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try to guess whats the os vendor .
train
false
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def path_to_local_track_uri(relpath): if isinstance(relpath, compat.text_type): relpath = relpath.encode(u'utf-8') return (u'local:track:%s' % urllib.quote(relpath))
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convert path relative to :confval:local/media_dir to local track uri .
train
false