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def parse_access(register, name, write, value, byte_order, silent): (modbus_type, address, pack_type, presenter) = re.match(REGISTER_RE, register).groups() if (not address): logging.warn('%r is not a known named register nor a valid register definition. Skipping it.', register) return None if (not modbus_type): modbus_type = 'h' else: modbus_type = modbus_type[:(- 1)] if (not pack_type): if (modbus_type in 'cCd'): pack_type = 'B' else: pack_type = 'H' else: pack_type = pack_type[1:] address = int(address) if (pack_type[0] not in '=<>!'): if (byte_order in ('le', 'mixed')): pack_type = ('<' + pack_type) elif (byte_order == 'be'): pack_type = ('!' + pack_type) if (modbus_type not in 'cCdhHi'): raise ValueError("Invalid Modbus type '{}'. Valid ones are 'cCdhHi'".format(modbus_type)) if (write and (modbus_type not in 'cChH')): raise ValueError("Invalid Modbus type '{}'. Only coils and holding registers are writable".format(modbus_type)) return Access(modbus_type, [address], [pack_type], [value], names=[name], presenters=[presenter], byte_order=byte_order, silent=silent)
def graphs_no_ep_in_address(): x = vars('x', 6) y = vars('y', 6) z = vars('z', 6, aliased=True) c = const(10) in_n0 = BasicBlock(0, [_assign(x[0], x[2]), _assign(z[0], x[0]), _assign(y[0], _addr(z[0])), _assign(x[1], c[0]), _assign(z[1], x[1]), _assign(y[1], _add(_addr(z[1]), x[0])), _assign(y[2], _add(_addr(c[2]), z[1]))]) in_cfg = ControlFlowGraph() in_cfg.add_node(in_n0) out_n0 = BasicBlock(0, [_assign(x[0], x[2]), _assign(z[0], x[2]), _assign(y[0], _addr(z[0])), _assign(x[1], c[0]), _assign(z[1], c[0]), _assign(y[1], _add(_addr(z[1]), x[2])), _assign(y[2], _add(_addr(c[2]), z[1]))]) out_cfg = ControlFlowGraph() out_cfg.add_node(out_n0) return (in_cfg, out_cfg)
class TriggerReqBody(BaseModel): messages: str = Field(..., description='User input messages') command: Optional[str] = Field(default='fix', description='Command name') model: Optional[str] = Field(default='gpt-3.5-turbo', description='Model name') stream: Optional[bool] = Field(default=False, description='Whether return stream') language: Optional[str] = Field(default='hive', description='Language') target_language: Optional[str] = Field(default='hive', description='Target language, use in translate') context: Optional[ReqContext] = Field(default=None, description='The context of the model request.')
_custom_acc_mapper_fn(op_and_target=('call_method', 'repeat_interleave'), arg_replacement_tuples=[('input', 'input'), ('repeats', 'repeats'), ('dim', 'dim', this_arg_is_optional), ('output_size', 'output_size', this_arg_is_optional)], skip_normalization_if_none=True) _custom_acc_mapper_fn(op_and_target=('call_function', torch.repeat_interleave), arg_replacement_tuples=[('input', 'input'), ('repeats', 'repeats'), ('dim', 'dim', this_arg_is_optional), ('output_size', 'output_size', this_arg_is_optional)], skip_normalization_if_none=True) def repeat_interleave_mapper(node: torch.fx.Node, _: nn.Module): input_node = node.kwargs['input'] repeats = cast(int, node.kwargs['repeats']) dim = node.kwargs['dim'] if (not (type(repeats) is int)): logger.info('Not mapping repeat_interleave to an acc op. We currently only support `repeat_interleave` with int repeats') return assert (type(repeats) is int), 'We currently only support `repeat_interleave` with int repeats' rank = node.meta['tensor_rank'] if (dim is None): repeat_dim = (rank - 1) else: assert (type(dim) is int), 'dim should be an int' repeat_dim = dim tile_dims = ([1] * (rank + 1)) tile_dims[(repeat_dim + 1)] = repeats with node.graph.inserting_before(node): unsqueeze_node = node.graph.create_node('call_function', unsqueeze, kwargs={'input': input_node, 'dim': (repeat_dim + 1)}, name=f'{node.name}_unsqueeze') tile_node = node.graph.create_node('call_function', tile, kwargs={'input': unsqueeze_node, 'dims': tuple(tile_dims)}, name=f'{node.name}_repeat_interleave_map_tile') new_shape = [] if (dim is not None): if (dim < 0): repeat_dim = (dim + rank) else: repeat_dim = dim size_node = node.graph.create_node('call_function', size, kwargs={'input': input_node}, name=f'{node.name}_size') size_node.meta['type'] = torch.Size for i in range(rank): shape_i = node.graph.create_node('call_function', getitem, kwargs={'input': size_node, 'idx': i}, name=f'{node.name}_size_{i}') if (i == repeat_dim): new_shape.append((- 1)) else: new_shape.append(shape_i) else: new_shape.append((- 1)) reshaped_node = node.graph.create_node('call_function', reshape, kwargs={'input': tile_node, 'acc_out_ty': acc_utils.build_raw_tensor_meta(shape=new_shape)}, name=f'{node.name}_reshape') reshaped_node.meta = node.meta.copy() return reshaped_node
def extractTracantranslationBlogspotCom(item): (vol, chp, frag, postfix) = extractVolChapterFragmentPostfix(item['title']) if ((not (chp or vol)) or ('preview' in item['title'].lower())): return None tagmap = [('PRC', 'PRC', 'translated'), ('Loiterous', 'Loiterous', 'oel')] for (tagname, name, tl_type) in tagmap: if (tagname in item['tags']): return buildReleaseMessageWithType(item, name, vol, chp, frag=frag, postfix=postfix, tl_type=tl_type) return False
def setup_to_pass(): shutil.copy('/etc/pam.d/system-auth', '/etc/pam.d/system-auth.bak') shutil.copy('/etc/pam.d/password-auth', '/etc/pam.d/password-auth.bak') shellexec("sed -i '/password\\s*sufficient\\s*pam_unix.so/ s/sha512/sha512 remember=5/' /etc/pam.d/system-auth") shellexec("sed -i '/password\\s*sufficient\\s*pam_unix.so/ s/sha512/sha512 remember=5/' /etc/pam.d/password-auth") (yield None) shutil.move('/etc/pam.d/system-auth.bak', '/etc/pam.d/system-auth') shutil.move('/etc/pam.d/password-auth.bak', '/etc/pam.d/password-auth')
.param_file((FIXTURE_PATH / 'mock_include.md')) def test_render(file_params, tmp_path, monkeypatch): monkeypatch.chdir(tmp_path) tmp_path.joinpath('other.md').write_text('a\nb\nc') tmp_path.joinpath('fmatter.md').write_text('---\na: 1\n---\nb') doctree = publish_doctree(file_params.content, parser=Parser(), settings_overrides={'myst_highlight_code_blocks': False}) doctree['source'] = 'tmpdir/test.md' output = doctree.pformat().replace((str(tmp_path) + os.sep), 'tmpdir/').rstrip() file_params.assert_expected(output, rstrip=True)
def xls_for_macs2(macs_xls, row_limit=None, cell_char_limit=None): if macs_xls.macs_version.startswith('1.'): raise Exception('Only handles output from MACS 2.0*') macs_xls.sort_on('fold_enrichment', reverse=True) if (row_limit is None): row_limit = Limits.MAX_NUMBER_ROWS_PER_WORKSHEET if (len(macs_xls.data) > row_limit): logging.warning('Data will be split over multiple worksheets on output') if (cell_char_limit is None): cell_char_limit = Limits.MAX_LEN_WORKSHEET_CELL_VALUE sheet_title_limit = Limits.MAX_LEN_WORKSHEET_TITLE legends_text = {'order': 'Sorting order FE', 'chr': 'Chromosome location of binding region', 'start': 'Start coordinate of binding region', 'end': 'Start coordinate of binding region', 'summit+100': 'Summit + 100bp', 'summit-1': 'Summit of binding region - 1', 'summit': 'Summit of binding region', 'abs_summit+100': 'Summit + 100bp', 'abs_summit-100': 'Summit of binding region - 100bp', 'abs_summit': 'Summit of binding region', 'length': 'Length of binding region', 'abs_summit': 'Coordinate of region summit', 'pileup': 'Number of non-degenerate and position corrected reads at summit', '-log10(pvalue)': 'Transformed Pvalue -log10(Pvalue) for the binding region (e.g. if Pvalue=1e-10, then this value should be 10)', 'fold_enrichment': 'Fold enrichment for this region against random Poisson distribution with local lambda', '-log10(qvalue)': 'Transformed Qvalue -log10(Pvalue) for the binding region (e.g. if Qvalue=0.05, then this value should be 1.3)', 'name': 'Name'} xls = XLSWorkBook() boldstyle = XLSStyle(bold=True) data_sheets = [] sheet_number = 1 data = xls.add_work_sheet('data', macs_xls.name) for line in macs_xls.data: if (data.last_row == row_limit): sheet_number += 1 name = ('data%d' % sheet_number) title = ('%s(%d)' % (macs_xls.name[:(sheet_title_limit - 4)], sheet_number)) print(("Making additional data sheet '%s'" % title)) data = xls.add_work_sheet(name, title) if (data.next_row == 1): data.write_row(1, data=macs_xls.columns_as_xls_header) data_sheets.append(data) data.append_row(line) for data in data_sheets: if (not macs_xls.with_broad_option): data.insert_column('E', text='chr') data.write_column('E', fill='=B?', from_row=2) data.insert_column('F', text='abs_summit-100') data.write_column('F', fill='=L?-100', from_row=2) data.insert_column('G', text='abs_summit+100') data.write_column('G', fill='=L?+100', from_row=2) data.insert_column('H', text='chr') data.write_column('H', fill='=B?', from_row=2) data.insert_column('I', text='summit-1') data.write_column('I', fill='=L?-1', from_row=2) data.insert_column('J', text='summit') data.write_column('J', fill='=L?', from_row=2) else: data.insert_column('E', text='chr') data.write_column('E', fill='=B?', from_row=2) notes = xls.add_work_sheet('notes', 'Notes') notes.write_row(1, text='MACS RUN NOTES:', style=boldstyle) notes.write_column('A', macs_xls.header, from_row=notes.next_row) notes.append_row(text='ADDITIONAL NOTES:', style=boldstyle) notes.append_row(text='By default regions are sorted by fold enrichment (in descending order)') for row in range(1, (notes.last_row + 1)): if notes['A'][row].startswith('# Command line:'): command_line = notes['A'][row] if (len(command_line) > cell_char_limit): logging.warning('Splitting command line over multiple cells') row_data = chunk(command_line, cell_char_limit, delimiter=' ') notes.write_row(row, data=row_data) data = data_sheets[0] legends = xls.add_work_sheet('legends', 'Legends') for col in ColumnRange(data.last_column): name = data[col][1].lstrip('#') try: legends.append_row(data=(name, legends_text[name])) except KeyError: logging.warning(("No legend description found for column '%s'" % name)) legends.append_row(data=(name, name.title())) for data in data_sheets: data.freeze_panes = 'A2' return xls
def train(model, train_loader, val_loader, optimizer, init_lr=0.002, checkpoint_dir=None, checkpoint_interval=None, nepochs=None, clip_thresh=1.0): if use_cuda: model = model.cuda() criterion = nn.CrossEntropyLoss() criterion_reconstruction = DiscretizedMixturelogisticLoss() global global_step, global_epoch if (hparams.exponential_moving_average is not None): ema = ExponentialMovingAverage(hparams.ema_decay) for (name, param) in model.named_parameters(): if param.requires_grad: ema.register(name, param.data) else: ema = None while (global_epoch < nepochs): model.train() h = open(logfile_name, 'a') running_loss = 0.0 running_loss_vq = 0.0 running_loss_encoder = 0.0 running_entropy = 0.0 running_loss_lid = 0.0 running_loss_reconstruction = 0.0 for (step, (mfcc, mfcc_lengths, mel, mol, lid, fnames)) in tqdm(enumerate(train_loader)): current_lr = learning_rate_decay(init_lr, global_step) for param_group in optimizer.param_groups: param_group['lr'] = current_lr optimizer.zero_grad() (sorted_lengths, indices) = torch.sort(mfcc_lengths.view((- 1)), dim=0, descending=True) sorted_lengths = sorted_lengths.long().numpy() mfcc = mfcc[indices] mel = mel[indices] mol = mol[indices] lid = lid[indices] (mfcc, mel, mol, lid) = (Variable(mfcc), Variable(mel), Variable(mol), Variable(lid)) if use_cuda: (mfcc, mel, mol, lid) = (mfcc.cuda(), mel.cuda(), mol.cuda(), lid.cuda().long()) logits = model(mfcc, mfcc_lengths=sorted_lengths) lid_loss = criterion(logits, lid) loss = lid_loss loss.backward(retain_graph=False) grad_norm = torch.nn.utils.clip_grad_norm_(model.parameters(), clip_thresh) optimizer.step() model.quantizer.after_update() if (ema is not None): for (name, param) in model.named_parameters(): if (name in ema.shadow): ema.update(name, param.data) if ((global_step % checkpoint_interval) == 0): save_checkpoint(model, optimizer, global_step, checkpoint_dir, global_epoch, ema=ema) log_value('Training Loss', float(loss.item()), global_step) log_value('gradient norm', grad_norm, global_step) log_value('learning rate', current_lr, global_step) log_value('VQ Penalty', vq_penalty, global_step) log_value('Encoder Penalty', encoder_penalty, global_step) log_value('Entropy', entropy, global_step) global_step += 1 running_loss += loss.item() averaged_loss = (running_loss / len(train_loader)) log_value('loss (per epoch)', averaged_loss, global_epoch) h.write((((('Loss after epoch ' + str(global_epoch)) + ': ') + format((running_loss / len(train_loader)))) + '\n')) h.close() (recall, model) = validate_model(model, val_loader) log_value('Unweighted Recall per epoch', recall, global_epoch) global_epoch += 1 return (model, ema)
def string_to_script_template(text: str) -> ScriptTemplate: if text.startswith(PREFIX_BIP276_SCRIPT): (prefix, version, network, data) = bip276_decode(text, Net.BIP276_VERSION) assert (network == Net.BIP276_VERSION), 'incompatible network' return classify_output_script(Script(data), Net.COIN) return Address.from_string(text, Net.COIN)
def create_diagram(cnarr, segarr, threshold, min_probes, outfname, show_range=None, title=None, show_labels=True): if (cnarr and segarr): do_both = True cnarr_is_seg = False else: if cnarr: cnarr_is_seg = False elif segarr: cnarr = segarr cnarr_is_seg = True else: raise ValueError('Must provide argument cnarr or segarr, or both. ') do_both = False if show_range: (chrom, start, end) = unpack_range(show_range) if (not ((start is None) and (end is None))): raise ValueError("Must provide chromosome only (genomic-range not allowed for 'diagram').") if cnarr: cnarr = cnarr.in_range(chrom=chrom, start=None, end=None) if segarr: segarr = segarr.in_range(chrom=chrom, start=None, end=None) gene_labels = _get_gene_labels(cnarr, segarr, cnarr_is_seg, threshold, min_probes) seen_genes = set() features = collections.defaultdict(list) strand = (1 if do_both else None) chrom_sizes = plots.chromosome_sizes(cnarr) if (not cnarr_is_seg): cnarr = cnarr.squash_genes() for row in cnarr: if (((row.start - 1) >= 0) and (row.end <= chrom_sizes[row.chromosome])): if (show_labels and (row.gene in gene_labels) and (row.gene not in seen_genes)): seen_genes.add(row.gene) feat_name = row.gene if (',' in feat_name): feat_name = feat_name.replace(',', ', ') else: feat_name = None features[row.chromosome].append(((row.start - 1), row.end, strand, feat_name, colors.Color(*plots.cvg2rgb(row.log2, (not cnarr_is_seg))))) if do_both: for (chrom, segrows) in segarr.by_chromosome(): for srow in segrows: if (((srow.start - 1) >= 0) and (srow.end <= chrom_sizes[chrom])): features[chrom].append(((srow.start - 1), srow.end, (- 1), None, colors.Color(*plots.cvg2rgb(srow.log2, False)))) if (not outfname): outfname = (cnarr.sample_id + '-diagram.pdf') drawing = build_chrom_diagram(features, chrom_sizes, cnarr.sample_id, title) cvs = canvas.Canvas(outfname, pagesize=PAGE_SIZE) renderPDF.draw(drawing, cvs, 0, 0) cvs.showPage() cvs.save() return outfname
def _create_model_start_listener(system_app: SystemApp): from dbgpt.datasource.manages.connection_manager import ConnectManager cfg = Config() def startup_event(wh): print('begin run _add_app_startup_event') conn_manage = ConnectManager(system_app) cfg.LOCAL_DB_MANAGE = conn_manage async_db_summary(system_app) return startup_event
.django_db def test_limit_values(client, create_idv_test_data): _test_post(client, {'award_id': 2, 'limit': 1}, (400002, 1, 1, False, 14)) _test_post(client, {'award_id': 2, 'limit': 5}, (400002, 5, 1, False, 14, 13, 12, 11, 10)) _test_post(client, {'award_id': 2, 'limit': 0}, expected_status_code=status.HTTP_422_UNPROCESSABLE_ENTITY) _test_post(client, {'award_id': 2, 'limit': }, expected_status_code=status.HTTP_422_UNPROCESSABLE_ENTITY) _test_post(client, {'award_id': 2, 'limit': {'BOGUS': 'LIMIT'}}, expected_status_code=status.HTTP_400_BAD_REQUEST)
class OptionSeriesBubbleSonification(Options): def contextTracks(self) -> 'OptionSeriesBubbleSonificationContexttracks': return self._config_sub_data('contextTracks', OptionSeriesBubbleSonificationContexttracks) def defaultInstrumentOptions(self) -> 'OptionSeriesBubbleSonificationDefaultinstrumentoptions': return self._config_sub_data('defaultInstrumentOptions', OptionSeriesBubbleSonificationDefaultinstrumentoptions) def defaultSpeechOptions(self) -> 'OptionSeriesBubbleSonificationDefaultspeechoptions': return self._config_sub_data('defaultSpeechOptions', OptionSeriesBubbleSonificationDefaultspeechoptions) def enabled(self): return self._config_get(True) def enabled(self, flag: bool): self._config(flag, js_type=False) def pointGrouping(self) -> 'OptionSeriesBubbleSonificationPointgrouping': return self._config_sub_data('pointGrouping', OptionSeriesBubbleSonificationPointgrouping) def tracks(self) -> 'OptionSeriesBubbleSonificationTracks': return self._config_sub_data('tracks', OptionSeriesBubbleSonificationTracks)
def get_erpnext_item_code(integration: str, integration_item_code: str, variant_id: Optional[str]=None, has_variants: Optional[int]=0) -> Optional[str]: filters = {'integration': integration, 'integration_item_code': integration_item_code} if variant_id: filters.update({'variant_id': variant_id}) elif has_variants: filters.update({'has_variants': 1}) return frappe.db.get_value('Ecommerce Item', filters, fieldname='erpnext_item_code')
def test_router_add_websocket_route(client): with client.websocket_connect('/ws') as session: text = session.receive_text() assert (text == 'Hello, world!') with client.websocket_connect('/ws/test') as session: text = session.receive_text() assert (text == 'Hello, test!')
(scope='function') def experience_config_tcf_overlay(db: Session) -> Generator: config = PrivacyExperienceConfig.create(db=db, data={'accept_button_label': 'Accept all', 'acknowledge_button_label': 'Confirm', 'banner_enabled': 'enabled_where_required', 'component': 'tcf_overlay', 'description': 'On this page you can opt in and out of these data uses cases', 'disabled': False, 'privacy_preferences_link_label': 'Manage preferences', 'privacy_policy_link_label': 'View our company&#x27;s privacy policy', 'privacy_policy_url': ' 'reject_button_label': 'Reject all', 'save_button_label': 'Save', 'title': 'Manage your consent'}) (yield config) for history in config.histories: history.delete(db) config.delete(db)
def run_trace(filename, out): with open(filename) as trace_file: sequence = parse_trace(trace_file, None) with open(out, 'w') as trace_file: for (command, out) in sequence: trace_file.write('$ {}\n'.format(command)) (status, stdout, stderr) = run_command(command) if ((status != 0) and (stdout == '')): print('[Error from command]') print(command) trace_file.write(stderr) else: trace_file.write(stdout)
def extractZetrotranslationWordpressCom(item): (vol, chp, frag, postfix) = extractVolChapterFragmentPostfix(item['title']) if ((not (chp or vol)) or ('preview' in item['title'].lower())): return None tagmap = [('PRC', 'PRC', 'translated'), ('Loiterous', 'Loiterous', 'oel')] for (tagname, name, tl_type) in tagmap: if (tagname in item['tags']): return buildReleaseMessageWithType(item, name, vol, chp, frag=frag, postfix=postfix, tl_type=tl_type) return False
def bm25(rawMatchInfo): match_info = _parseMatchInfo(rawMatchInfo) K = 0.5 B = 0.75 score = 0.0 (P_O, C_O, N_O, A_O) = range(4) term_count = match_info[P_O] col_count = match_info[C_O] total_docs = match_info[N_O] L_O = (A_O + col_count) X_O = (L_O + col_count) weights = ([1] * col_count) for i in range(term_count): for j in range(col_count): weight = weights[j] if (weight == 0): continue avg_length = float(match_info[(A_O + j)]) doc_length = float(match_info[(L_O + j)]) if (avg_length == 0): D = 0 else: D = ((1 - B) + (B * (doc_length / avg_length))) x = (X_O + ((3 * j) * (i + 1))) term_frequency = float(match_info[x]) docs_with_term = float(match_info[(x + 2)]) idf = max(math.log((((total_docs - docs_with_term) + 0.5) / (docs_with_term + 0.5))), 0) denom = (term_frequency + (K * D)) if (denom == 0): rhs = 0 else: rhs = ((term_frequency * (K + 1)) / denom) score += ((idf * rhs) * weight) return score
class _InnerEnv(BaseEnv, _EnvInterfaceInner): action_space = None observation_space = None reward_range = None metadata = None def seed(self, seed: int) -> None: pass def close(self) -> None: pass def reset(self) -> Any: pass def step(self, action): pass def method_inner(self) -> int: return 41
class _BaseVenvFactory(): venvs_directory: Path def venv(self, project: str, setup_commands: list[str]) -> Generator[(VirtualEnvironment, None, None)]: venv_path = (self.venvs_directory / project) old_cwd = Path.cwd() virtual_env = VirtualEnvironment(venv_path, project) virtual_env.setup(setup_commands, old_cwd) os.chdir((venv_path / 'project')) try: (yield virtual_env) finally: os.chdir(old_cwd)
.parametrize('host_in,port_in,expected_host_out,expected_port_out', ((None, None, 'localhost', 5432), (None, 5432, 'localhost', 5432), ('localhost', '5432', 'localhost', 5432), ('foo.bar', '5432', 'foo.bar', 5432), ('localhost,foo.bar', '5432,1234', 'localhost', 5432))) def test_get_destination(host_in, port_in, expected_host_out, expected_port_out): (host, port) = get_destination_info(host_in, port_in) assert (host == expected_host_out) assert (port == expected_port_out)
_converter(acc_ops.tile) def acc_ops_tile(target: Target, args: Tuple[(Argument, ...)], kwargs: Dict[(str, Argument)], name: str) -> ConverterOutput: input_val = kwargs['input'] if (not isinstance(input_val, AITTensor)): raise RuntimeError(f'Unexpected input for {name}: {input_val}') shape_dims = list(kwargs['dims']) input_dim_len = len(input_val.shape()) result = input_val if (len(shape_dims) < input_dim_len): for _ in range((input_dim_len - len(shape_dims))): shape_dims.insert(0, 1) if (input_dim_len < len(shape_dims)): new_shape = list(input_val.shape()) for _ in range((len(shape_dims) - input_dim_len)): new_shape.insert(0, IntImm(1)) result = reshape()(input_val, new_shape) for (i, shape) in enumerate(shape_dims): if (result.shape()[i]._attrs['name'] is not None): continue cat_groups = ([result] * shape) result = concatenate()(cat_groups, dim=i) return result
class DataFile(AbstractLayout): layout = 'text' opened_queue = [] max_queue_entries = 31 def __init__(self, textFile, textParser, variationModules): self._record_index = RecordIndex(textFile, textParser) self._text_parser = textParser self._text_file = textFile self._variation_modules = variationModules def index_text(self, forceIndexBuild=False, validateData=False): self._record_index.create(forceIndexBuild, validateData) return self def close(self): self._record_index.close() def get_handles(self): if (not self._record_index.is_open()): if (len(DataFile.opened_queue) > self.max_queue_entries): log.info(('Closing %s' % self)) DataFile.opened_queue[0].close() del DataFile.opened_queue[0] DataFile.opened_queue.append(self) log.info(('Opening %s' % self)) return self._record_index.get_handles() def process_var_binds(self, var_binds, **context): rsp_var_binds = [] if context.get('nextFlag'): error_status = exval.endOfMib else: error_status = exval.noSuchInstance try: (text, db) = self.get_handles() except SnmpsimError as exc: log.error(('Problem with data file or its index: %s' % exc)) ReportingManager.update_metrics(data_file=self._text_file, datafile_failure_count=1, transport_call_count=1, **context) return [(vb[0], error_status) for vb in var_binds] vars_remaining = vars_total = len(var_binds) err_total = 0 log.info(('Request var-binds: %s, flags: %s, %s' % (', '.join([('%s=<%s>' % (vb[0], vb[1].prettyPrint())) for vb in var_binds]), ((context.get('nextFlag') and 'NEXT') or 'EXACT'), ((context.get('setFlag') and 'SET') or 'GET')))) for (oid, val) in var_binds: text_oid = str(univ.OctetString('.'.join([('%s' % x) for x in oid]))) try: line = self._record_index.lookup(str(univ.OctetString('.'.join([('%s' % x) for x in oid])))) except KeyError: offset = search_record_by_oid(oid, text, self._text_parser) subtree_flag = exact_match = False else: (offset, subtree_flag, prev_offset) = line.split(str2octs(','), 2) (subtree_flag, exact_match) = (int(subtree_flag), True) offset = int(offset) text.seek(offset) vars_remaining -= 1 (line, _, _) = get_record(text) while True: if exact_match: if (context.get('nextFlag') and (not subtree_flag)): (_next_line, _, _) = get_record(text) if _next_line: (_next_oid, _) = self._text_parser.evaluate(_next_line, oidOnly=True) try: (_, subtree_flag, _) = self._record_index.lookup(str(_next_oid)).split(str2octs(','), 2) except KeyError: log.error(('data error for %s at %s, index broken?' % (self, _next_oid))) line = '' else: subtree_flag = int(subtree_flag) line = _next_line else: line = _next_line else: if line: (_oid, _) = self._text_parser.evaluate(line, oidOnly=True) else: _oid = 'last' try: (_, _, _prev_offset) = self._record_index.lookup(str(_oid)).split(str2octs(','), 2) except KeyError: log.error(('data error for %s at %s, index broken?' % (self, _oid))) line = '' else: _prev_offset = int(_prev_offset) if (_prev_offset >= 0): text.seek(_prev_offset) (_prev_line, _, _) = get_record(text) (_prev_oid, _) = self._text_parser.evaluate(_prev_line, oidOnly=True) if _prev_oid.isPrefixOf(oid): line = _prev_line subtree_flag = True if (not line): _oid = oid _val = error_status break call_context = context.copy() call_context.update((), origOid=oid, origValue=val, dataFile=self._text_file, subtreeFlag=subtree_flag, exactMatch=exact_match, errorStatus=error_status, varsTotal=vars_total, varsRemaining=vars_remaining, variationModules=self._variation_modules) try: (_oid, _val) = self._text_parser.evaluate(line, **call_context) if (_val is exval.endOfMib): exact_match = True subtree_flag = False continue except NoDataNotification: raise except MibOperationError: raise except Exception as exc: _oid = oid _val = error_status err_total += 1 log.error(('data error at %s for %s: %s' % (self, text_oid, exc))) break rsp_var_binds.append((_oid, _val)) log.info(('Response var-binds: %s' % ', '.join([('%s=<%s>' % (vb[0], vb[1].prettyPrint())) for vb in rsp_var_binds]))) ReportingManager.update_metrics(data_file=self._text_file, varbind_count=vars_total, datafile_call_count=1, datafile_failure_count=err_total, transport_call_count=1, **context) return rsp_var_binds def __str__(self): return ('%s controller' % self._text_file)
class OptionPlotoptionsDependencywheelSonificationTracksMappingTime(Options): def mapFunction(self): return self._config_get(None) def mapFunction(self, value: Any): self._config(value, js_type=False) def mapTo(self): return self._config_get(None) def mapTo(self, text: str): self._config(text, js_type=False) def max(self): return self._config_get(None) def max(self, num: float): self._config(num, js_type=False) def min(self): return self._config_get(None) def min(self, num: float): self._config(num, js_type=False) def within(self): return self._config_get(None) def within(self, value: Any): self._config(value, js_type=False)
class OptionPlotoptionsCylinderSonificationTracksMappingLowpassFrequency(Options): def mapFunction(self): return self._config_get(None) def mapFunction(self, value: Any): self._config(value, js_type=False) def mapTo(self): return self._config_get(None) def mapTo(self, text: str): self._config(text, js_type=False) def max(self): return self._config_get(None) def max(self, num: float): self._config(num, js_type=False) def min(self): return self._config_get(None) def min(self, num: float): self._config(num, js_type=False) def within(self): return self._config_get(None) def within(self, value: Any): self._config(value, js_type=False)
class ViolationAttributes(BaseModel): data_categories: List[str] = Field(description='A list of data categories which led to an evaluation violation.') data_subjects: List[str] = Field(description='A list of data subjects which led to an evaluation violation.') data_uses: List[str] = Field(description='A list of data uses which led to an evaluation violation.')
def test_periodic_interval_div_free(): m = PeriodicUnitIntervalMesh(50) mesh = ExtrudedMesh(m, 50) V = VectorFunctionSpace(mesh, 'CG', 3) (x, y) = SpatialCoordinate(mesh) u = Function(V) u.interpolate(as_vector([sin(((2 * np.pi) * x)), ((((- 2) * np.pi) * y) * cos(((2 * np.pi) * x)))])) assert np.allclose(assemble((div(u) * dx)), 0) L2 = FunctionSpace(mesh, 'DG', 2) v = TestFunction(L2) f = assemble((inner(div(u), v) * dx)) assert np.allclose(f.dat.data, 0)
def test_sampling_array_dims(): raw = [1, 2, 3, 4, 5, 6] dimensions = [3] samples = sampling(raw, dimensions) assert np.array_equal(samples[0], np.array(raw[0:3])) assert np.array_equal(samples[1], np.array(raw[3:6])) dimensions = [6] samples = sampling(raw, dimensions) assert np.array_equal(samples[0], np.array(raw)) dimensions = [2, 3] samples = sampling(raw, dimensions) assert np.array_equal(samples[0][0], np.array(raw[0:3])) assert np.array_equal(samples[0][1], np.array(raw[3:6])) dimensions = [3, 2] samples = sampling(raw, dimensions) assert np.array_equal(samples[0][0], np.array(raw[0:2])) assert np.array_equal(samples[0][1], np.array(raw[2:4])) assert np.array_equal(samples[0][2], np.array(raw[4:6]))
def cfrp(agent: Agent, state: ShortDeckPokerState, i: int, t: int, c: int, locks: Dict[(str, mp.synchronize.Lock)]={}): ph = state.player_i player_not_in_hand = (not state.players[i].is_active) if (state.is_terminal or player_not_in_hand): return state.payout[i] elif (ph == i): this_info_sets_regret = agent.regret.get(state.info_set, state.initial_regret) sigma = calculate_strategy(this_info_sets_regret) vo = 0.0 voa: Dict[(str, float)] = dict() explored: Dict[(str, bool)] = {action: False for action in state.legal_actions} this_info_sets_regret = agent.regret.get(state.info_set, state.initial_regret) for action in state.legal_actions: if (this_info_sets_regret[action] > c): new_state: ShortDeckPokerState = state.apply_action(action) voa[action] = cfrp(agent, new_state, i, t, c, locks) explored[action] = True vo += (sigma[action] * voa[action]) if locks: locks['regret'].acquire() this_info_sets_regret = agent.regret.get(state.info_set, state.initial_regret) for action in state.legal_actions: if explored[action]: this_info_sets_regret[action] += (voa[action] - vo) agent.regret[state.info_set] = this_info_sets_regret if locks: locks['regret'].release() return vo else: this_info_sets_regret = agent.regret.get(state.info_set, state.initial_regret) sigma = calculate_strategy(this_info_sets_regret) available_actions: List[str] = list(sigma.keys()) action_probabilities: List[float] = list(sigma.values()) action: str = np.random.choice(available_actions, p=action_probabilities) new_state: ShortDeckPokerState = state.apply_action(action) return cfrp(agent, new_state, i, t, c, locks)
def test_adding_a_extra_init_container_as_yaml(): config = "\nextraInitContainers:\n - name: do-something\n image: busybox\n command: ['do', 'something']\n" r = helm_template(config) extraInitContainer = r['statefulset'][uname]['spec']['template']['spec']['initContainers'] assert ({'name': 'do-something', 'image': 'busybox', 'command': ['do', 'something']} in extraInitContainer)
class OptionSeriesPyramidDataDragdropGuideboxDefault(Options): def className(self): return self._config_get('highcharts-drag-box-default') def className(self, text: str): self._config(text, js_type=False) def color(self): return self._config_get('rgba(0, 0, 0, 0.1)') def color(self, text: str): self._config(text, js_type=False) def cursor(self): return self._config_get('move') def cursor(self, text: str): self._config(text, js_type=False) def lineColor(self): return self._config_get('#888') def lineColor(self, text: str): self._config(text, js_type=False) def lineWidth(self): return self._config_get(1) def lineWidth(self, num: float): self._config(num, js_type=False) def zIndex(self): return self._config_get(900) def zIndex(self, num: float): self._config(num, js_type=False)
def sequential_graph_fixer(fixers: List[GraphFixer]) -> GraphFixer: def sequential(bmg: BMGraphBuilder) -> GraphFixerResult: made_progress = False errors = ErrorReport() current = bmg for fixer in fixers: (current, fixer_made_progress, errors) = fixer(current) made_progress |= fixer_made_progress if errors.any(): break return (current, made_progress, errors) return sequential
def Fstiffness_k(k: int, kappa0: float, kappa1: float, innerimagelist: np.ndarray, outerimagelist: np.ndarray, Eholo_vertical: np.ndarray): v0inner = (innerimagelist[k] - innerimagelist[(k + 1)]) tdelta0inner = np.linalg.norm(v0inner) v0outer = (outerimagelist[k] - outerimagelist[(k + 1)]) tdelta0outer = np.linalg.norm(v0outer) tdeltadelta = (tdelta0inner - tdelta0outer) Vvert = ((((- Eholo_vertical[k]) * tdeltadelta) * kappa0) * 0.5) v1inner = (innerimagelist[k] - innerimagelist[(k - 1)]) tdelta1inner = np.linalg.norm(v1inner) v1outer = (outerimagelist[k] - outerimagelist[(k - 1)]) tdelta1outer = np.linalg.norm(v1outer) tdeltadelta = (tdelta1inner - tdelta1outer) Vvert -= (((Eholo_vertical[k] * tdeltadelta) * kappa1) * 0.5) return Vvert
class TestBasicLazy(AllTypes): def arg_builder(monkeypatch): with monkeypatch.context() as m: m.setattr(sys, 'argv', ['', '--config', './tests/conf/yaml/test.yaml']) config = ConfigArgBuilder(TypeConfig, TypeOptConfig, lazy=True) return config.generate()
def on_window_new(layouts: Layouts, state: State): def _on_window_new(i3l: Connection, e: WindowEvent): logger.debug(f'[ipc] window new event - container:{e.container.id}:{e.container.window}') context = state.sync_context(i3l) if ((not layouts.exists_for(context.workspace.name)) or (context.workspace_sequence is None)): logger.debug(' [ipc] window new event - no workspace layout') return if (not is_layout_container(e.container)): logger.debug(' [ipc] window new event - not a layout container') return if (len(context.containers) == 0): logger.debug(' [ipc] window new event - no container to handle') return context.workspace_sequence.set_order(e.container) logger.debug(' [ipc] window new event - update layout') layout = layouts.get(context.workspace.name) layout.update(context, e.container) state.handle_rebuild(context, e.container) return _on_window_new
class TaskStatusCondition(Condition): def __init__(self, workflow_name: str, task_name: str, namespace: str, expect_status: TaskStatus): key = TaskStatusChangedEvent.generate_task_status_changed_event_key(namespace, workflow_name, task_name) super().__init__([key]) self.expect_status = expect_status def is_met(self, event: Event, context: Context) -> bool: context_dict = json.loads(event.context) task_status = context_dict[EventContextConstant.TASK_STATUS] if (self.expect_status == task_status): return True else: return False
def upgrade(): op.execute('delete from users_events_roles where event_id is null or role_id is null or user_id is null') op.alter_column('users_events_roles', 'event_id', existing_type=sa.INTEGER(), nullable=False) op.alter_column('users_events_roles', 'role_id', existing_type=sa.INTEGER(), nullable=False) op.alter_column('users_events_roles', 'user_id', existing_type=sa.INTEGER(), nullable=False)
class EvaluatorStaticTest(unittest.TestCase, EvaluatorTestCases): grammar_scopes = AttributeGrammar.from_modules(scopes, rule_extractor=Parser()) grammar_arithmetic = AttributeGrammar.from_modules(arithmetic, rule_extractor=Parser()) evaluator_scopes = StaticEvaluator(grammar_scopes) evaluator_arithmetic = StaticEvaluator(grammar_arithmetic) def test_arithmetic(self): for (e, r, t, d) in self.expressions: ast = arithmetic.parse_rpn(e) ast.depth = 0 ast.index = None ast = self.evaluator_arithmetic.for_tree(ast).content self.assertEqual(ast.value, r) self.assertEqual(ast.type, t) self.assertEqual(ast.subtree_depth, d) def test_scopes(self): for e in self.ok: ast = scopes_parser.parse(e) ast.same = [] ast.env = {} self.assertTrue(self.evaluator_scopes.for_tree(ast).ok) for e in self.not_ok: ast = scopes_parser.parse(e) ast.same = [] ast.env = {} self.assertFalse(self.evaluator_scopes.for_tree(ast).ok, e)
class Deployer(object): def __init__(self, cloud='heroku', config_json=None, credentials_json=None): self.cloud = cloud self.dep = None if (cloud == 'local'): self.dep = Local(config_json=config_json, credentials_json=credentials_json) if (cloud == 'heroku'): self.dep = Heroku(config_json=config_json, credentials_json=credentials_json) if (cloud == 'aws'): self.dep = Aws(config_json=config_json, credentials_json=credentials_json) if (cloud == 'googlecloud'): self.dep = GoogleCloud(config_json=config_json, credentials_json=credentials_json) if (cloud == 'azure'): self.dep = Azure(config_json=config_json, credentials_json=credentials_json) def deploy(self, model_id): self.dep.deploy(model_id)
class OptionPlotoptionsPyramidSonificationDefaultinstrumentoptionsMappingVolume(Options): def mapFunction(self): return self._config_get(None) def mapFunction(self, value: Any): self._config(value, js_type=False) def mapTo(self): return self._config_get(None) def mapTo(self, text: str): self._config(text, js_type=False) def max(self): return self._config_get(None) def max(self, num: float): self._config(num, js_type=False) def min(self): return self._config_get(None) def min(self, num: float): self._config(num, js_type=False) def within(self): return self._config_get(None) def within(self, value: Any): self._config(value, js_type=False)
def test_get_experiment(poly_example_tmp_dir, dark_storage_client): resp: Response = dark_storage_client.get('/experiments') answer_json = resp.json() assert (len(answer_json) == 1) assert ('ensemble_ids' in answer_json[0]) assert (len(answer_json[0]['ensemble_ids']) == 2) assert ('name' in answer_json[0]) assert (answer_json[0]['name'] == 'default')
def rotate_alphabet(text, key): result = '' for letter in text: if letter.isalpha(): if letter.isupper(): result += AlPHABET[((AlPHABET.index(letter.lower()) + key) % 26)].upper() else: result += AlPHABET[((AlPHABET.index(letter) + key) % 26)] else: result += letter return result
def test_write_long(la: LogicAnalyzer, slave: I2CSlave): la.capture(2, block=False) slave.write_long(WRITE_DATA, REGISTER_ADDRESS) la.stop() (scl, sda) = la.fetch_data() assert (len(scl) == ((SCL_START + (SCL_WRITE * 6)) + SCL_STOP)) assert (len(sda) == ((((SDA_START + SDA_DEVICE_ADDRESS) + SDA_REGISTER_ADDRESS) + (SDA_WRITE * 4)) + SDA_ACK))
(scope='function') def exit_manager(manager_nospawn, monkeypatch, temp_output): def no_op(self, *args, **kwargs): def _(): self.is_counting = False return _ def new_config(self, qtile, bar): QuickExit._configure(self, qtile, bar) self.qtile.stop = no_op(self) monkeypatch.setattr('qtile_extras.widget.ScriptExit._configure', new_config) class ExitConfig(libqtile.confreader.Config): auto_fullscreen = True keys = [] mouse = [] groups = [libqtile.config.Group('a')] layouts = [libqtile.layout.Max()] floating_layout = libqtile.resources.default_config.floating_layout screens = [libqtile.config.Screen(top=libqtile.bar.Bar([qtile_extras.widget.ScriptExit(timer_interval=0.05, exit_script=temp_output)], 50))] manager_nospawn.start(ExitConfig) (yield manager_nospawn)
def test_data_integrity_test_all_unique_values() -> None: test_dataset = pd.DataFrame({'feature1': [1, 1, 2, 3], 'feature2': [1, 2, np.nan, 4], 'target': ['1', '2', '3', '']}) suite = TestSuite(tests=[TestColumnAllUniqueValues(column_name='not_exists_feature')]) suite.run(current_data=test_dataset, reference_data=None, column_mapping=ColumnMapping()) assert (not suite) suite = TestSuite(tests=[TestColumnAllUniqueValues(column_name='feature2')]) suite.run(current_data=test_dataset, reference_data=None, column_mapping=ColumnMapping()) suite._inner_suite.raise_for_error() assert suite assert suite.show() assert suite.json()
def test_object_many_objects_nameonly(tmpdir_factory, merge_files_manyLR): fpath = str(tmpdir_factory.mktemp('lf').join('same-id.dlis')) content = ['data/chap4-7/eflr/envelope.dlis.part', 'data/chap4-7/eflr/file-header.dlis.part', 'data/chap4-7/eflr/match/T.CHANNEL-I.MATCH1-O.16-C.0.dlis.part', 'data/chap4-7/eflr/match/T.CHANNEL-I.MATCH1-O.127-C.0.dlis.part'] merge_files_manyLR(fpath, content) with dlis.load(fpath) as (f, *_): with pytest.raises(ValueError) as exc: _ = f.object('CHANNEL', 'MATCH1') assert ('Candidates are' in str(exc.value)) assert ('origin=16, copy=0' in str(exc.value)) assert ('origin=127, copy=0' in str(exc.value))
class OptionPlotoptionsErrorbarSonificationContexttracksMappingTime(Options): def mapFunction(self): return self._config_get(None) def mapFunction(self, value: Any): self._config(value, js_type=False) def mapTo(self): return self._config_get(None) def mapTo(self, text: str): self._config(text, js_type=False) def max(self): return self._config_get(None) def max(self, num: float): self._config(num, js_type=False) def min(self): return self._config_get(None) def min(self, num: float): self._config(num, js_type=False) def within(self): return self._config_get(None) def within(self, value: Any): self._config(value, js_type=False)
class TreeNode(): def __init__(self, klass): self.klass = klass self.name = klass.__name__ self.children = [] self.parents = [] self.level = None def add_parent(self, parent): assert isinstance(parent, TreeNode) if (parent not in self.parents): self.parents.append(parent) def add_child(self, child): assert isinstance(child, TreeNode) if (child not in self.children): self.children.append(child) def get_level(self): if (not self.level): if self.parents: self.level = (max([x.get_level() for x in self.parents]) + 1) else: self.level = 0 return self.level def get_ancestors(self): def _get_ancestors(node, ancestors): ancestors.extend(node.parents) for p in node.parents: _get_ancestors(p, ancestors) ancestors = [] _get_ancestors(self, ancestors) return ancestors
def output_excel_footer(worksheet, row, no_file_comments, qn, elapsed_time): if (not no_file_comments): worksheet.write(row, 0, f'## {qn} queries scanned') worksheet.write((row + 1), 0, f'## Total time (seconds): {elapsed_time}') worksheet.write((row + 2), 0, f'## Rate: {(float(qn) / elapsed_time):.2f} q/s') return
class RoleDetail(ResourceDetail): def before_get_object(self, view_kwargs): if (view_kwargs.get('role_invite_id') is not None): role_invite = safe_query_kwargs(RoleInvite, view_kwargs, 'role_invite_id') view_kwargs['id'] = role_invite.role_id if (view_kwargs.get('users_events_roles_id') is not None): users_events_role = safe_query_kwargs(UsersEventsRoles, view_kwargs, 'users_events_roles_id') view_kwargs['id'] = users_events_role.role_id if (view_kwargs.get('users_groups_roles_id') is not None): users_groups_role = safe_query_kwargs(UsersGroupsRoles, view_kwargs, 'users_groups_roles_id') view_kwargs['id'] = users_groups_role.role_id def before_update_object(self, role, data, view_kwargs): if data.get('name'): if (data['name'] in ['owner', 'organizer', 'coorganizer', 'registrar', 'moderator', 'attendee', 'track_organizer']): raise UnprocessableEntityError({'data': 'name'}, 'The given name cannot be updated') def before_delete_object(self, obj, kwargs): if (obj.name in ['owner', 'organizer', 'coorganizer', 'registrar', 'moderator', 'attendee', 'track_organizer']): raise UnprocessableEntityError({'data': 'name'}, 'The resource with given name cannot be deleted') decorators = (api.has_permission('is_admin', methods='PATCH,DELETE'),) schema = RoleSchema data_layer = {'session': db.session, 'model': Role, 'methods': {'before_get_object': before_get_object, 'before_delete_object': before_delete_object}}
def get_prices(games: Iterable['Game'], country: str) -> Iterator[Tuple[(str, Price)]]: prices = {} chunk = [] for game in games: chunk.append(game) if (len(chunk) == 50): fetched = {nsuid: price for (nsuid, price) in fetch_prices(country=country, nsuids=[game.nsuid for game in chunk])} prices.update(fetched) chunk = [] if chunk: fetched = {nsuid: price for (nsuid, price) in fetch_prices(country=country, nsuids=[game.nsuid for game in chunk])} prices.update(fetched) (yield from prices.items())
.gui() .parametrize(('show_on_startup', 'expected_return_code'), [(False, introduction.Choice.SHOW), (True, introduction.Choice.DONT_SHOW)]) def test_introduction_toggle_checkbox_changes_return_code(qtbot, show_on_startup, expected_return_code): dialog = introduction.IntroductionDialog(show_on_startup=show_on_startup) qtbot.addWidget(dialog) def close_dialog(): while (not dialog.isVisible()): ... dialog.show_on_startup_checkbox.click() dialog.ok_button.click() QtCore.QTimer.singleShot(0, close_dialog) return_code = dialog.exec() assert (return_code == expected_return_code)
.skipif((('raspberrypi' != os.uname()[1]) and ('raspizero' != os.uname()[1])), reason='RPi only (ePhat) test') class TestE2eRPiEphatEgress(): def get_ping_status(self, fledge_url): conn = conn.request('GET', '/fledge/ping') r = conn.getresponse() assert (200 == r.status) r = r.read().decode() jdoc = json.loads(r) return jdoc def get_statistics_map(self, fledge_url): conn = conn.request('GET', '/fledge/statistics') r = conn.getresponse() assert (200 == r.status) r = r.read().decode() jdoc = json.loads(r) return utils.serialize_stats_map(jdoc) def start_south_north(self, reset_and_start_fledge, add_south, south_branch, disable_schedule, remove_data_file, skip_verify_north_interface, remove_directories, enable_schedule, fledge_url, start_north_pi_server_c, pi_host, pi_port, pi_token, wait_time): add_south(SOUTH_PLUGIN, south_branch, fledge_url, service_name=SVC_NAME) if (not skip_verify_north_interface): start_north_pi_server_c(fledge_url, pi_host, pi_port, pi_token, taskname=TASK_NAME, start_task=False) time.sleep(wait_time) disable_schedule(fledge_url, SVC_NAME) if (not skip_verify_north_interface): enable_schedule(fledge_url, TASK_NAME) (yield self.start_south_north) remove_directories('/tmp/fledge-south-{}'.format(SOUTH_PLUGIN)) def test_end_to_end(self, start_south_north, read_data_from_pi, fledge_url, pi_host, pi_admin, pi_passwd, pi_db, wait_time, retries, skip_verify_north_interface): time.sleep((wait_time * 2)) self._verify_ping_and_statistics(fledge_url, skip_verify_north_interface) self._verify_ingest(fledge_url) if (not skip_verify_north_interface): self._verify_egress(read_data_from_pi, pi_host, pi_admin, pi_passwd, pi_db, wait_time, retries) def _verify_ping_and_statistics(self, fledge_url, skip_verify_north_interface): ping_response = self.get_ping_status(fledge_url) assert ping_response['dataRead'] if (not skip_verify_north_interface): assert ping_response['dataSent'] actual_stats_map = self.get_statistics_map(fledge_url) assert actual_stats_map['{}{}'.format(ASSET_PREFIX.upper(), ASSET_NAME_W.upper())] assert actual_stats_map['{}{}'.format(ASSET_PREFIX.upper(), ASSET_NAME_M.upper())] assert actual_stats_map['{}{}'.format(ASSET_PREFIX.upper(), ASSET_NAME_A.upper())] assert actual_stats_map['{}{}'.format(ASSET_PREFIX.upper(), ASSET_NAME_C.upper())] assert actual_stats_map['READINGS'] if (not skip_verify_north_interface): assert actual_stats_map[TASK_NAME] assert actual_stats_map['Readings Sent'] def _verify_ingest(self, fledge_url): asset_name_with_prefix_w = '{}{}'.format(ASSET_PREFIX, ASSET_NAME_W) asset_name_with_prefix_m = '{}{}'.format(ASSET_PREFIX, ASSET_NAME_M) asset_name_with_prefix_a = '{}{}'.format(ASSET_PREFIX, ASSET_NAME_A) asset_name_with_prefix_c = '{}{}'.format(ASSET_PREFIX, ASSET_NAME_C) conn = conn.request('GET', '/fledge/asset') r = conn.getresponse() assert (200 == r.status) r = r.read().decode() jdoc = json.loads(r) assert len(jdoc), 'No asset found' actual_assets = [i['assetCode'] for i in jdoc] assert (asset_name_with_prefix_w in actual_assets) assert (asset_name_with_prefix_m in actual_assets) assert (asset_name_with_prefix_a in actual_assets) assert (asset_name_with_prefix_c in actual_assets) assert jdoc[0]['count'] expected_assets = Counter([asset_name_with_prefix_w, asset_name_with_prefix_m, asset_name_with_prefix_a, asset_name_with_prefix_c]) assert (Counter(actual_assets) == expected_assets) conn.request('GET', '/fledge/asset/{}'.format(quote(asset_name_with_prefix_w, safe=''))) r = conn.getresponse() assert (200 == r.status) r = r.read().decode() jdoc_asset = json.loads(r) for _sensor in SENSOR_READ_KEY_W: assert len(jdoc_asset), "No data found for asset '{}'".format(asset_name_with_prefix_w) assert (jdoc_asset[0]['reading'][_sensor] is not None) conn.request('GET', '/fledge/asset/{}/{}'.format(quote(asset_name_with_prefix_w, safe=''), _sensor)) r = conn.getresponse() assert (200 == r.status) r = r.read().decode() jdoc = json.loads(r) assert len(jdoc), "No data found for asset '{}' and datapoint '{}'".format(asset_name_with_prefix_w, _sensor) conn.request('GET', '/fledge/asset/{}'.format(quote(asset_name_with_prefix_m, safe=''))) r = conn.getresponse() assert (200 == r.status) r = r.read().decode() jdoc_asset = json.loads(r) for _sensor in SENSOR_READ_KEY_M: assert len(jdoc_asset), "No data found for asset '{}'".format(asset_name_with_prefix_m) assert (jdoc_asset[0]['reading'][_sensor] is not None) conn.request('GET', '/fledge/asset/{}/{}'.format(quote(asset_name_with_prefix_m, safe=''), _sensor)) r = conn.getresponse() assert (200 == r.status) r = r.read().decode() jdoc = json.loads(r) assert len(jdoc), "No data found for asset '{}' and datapoint '{}'".format(asset_name_with_prefix_m, _sensor) conn.request('GET', '/fledge/asset/{}'.format(quote(asset_name_with_prefix_a, safe=''))) r = conn.getresponse() assert (200 == r.status) r = r.read().decode() jdoc_asset = json.loads(r) for _sensor in SENSOR_READ_KEY_A: assert len(jdoc_asset), "No data found for asset '{}'".format(asset_name_with_prefix_a) assert (jdoc_asset[0]['reading'][_sensor] is not None) conn.request('GET', '/fledge/asset/{}/{}'.format(quote(asset_name_with_prefix_a, safe=''), _sensor)) r = conn.getresponse() assert (200 == r.status) r = r.read().decode() jdoc = json.loads(r) assert len(jdoc), "No data found for asset '{}' and datapoint '{}'".format(asset_name_with_prefix_a, _sensor) conn.request('GET', '/fledge/asset/{}'.format(quote(asset_name_with_prefix_c, safe=''))) r = conn.getresponse() assert (200 == r.status) r = r.read().decode() jdoc_asset = json.loads(r) for _sensor in SENSOR_READ_KEY_C: assert len(jdoc_asset), "No data found for asset '{}'".format(asset_name_with_prefix_c) assert (jdoc_asset[0]['reading'][_sensor] is not None) conn.request('GET', '/fledge/asset/{}/{}'.format(quote(asset_name_with_prefix_c, safe=''), _sensor)) r = conn.getresponse() assert (200 == r.status) r = r.read().decode() jdoc = json.loads(r) assert len(jdoc), "No data found for asset '{}' and datapoint '{}'".format(asset_name_with_prefix_c, _sensor) def _verify_egress(self, read_data_from_pi, pi_host, pi_admin, pi_passwd, pi_db, wait_time, retries): retry_count = 0 data_from_pi_w = None data_from_pi_m = None data_from_pi_a = None data_from_pi_c = None asset_name_with_prefix_w = '{}{}'.format(ASSET_PREFIX, ASSET_NAME_W) asset_name_with_prefix_a = '{}{}'.format(ASSET_PREFIX, ASSET_NAME_A) asset_name_with_prefix_m = '{}{}'.format(ASSET_PREFIX, ASSET_NAME_M) asset_name_with_prefix_c = '{}{}'.format(ASSET_PREFIX, ASSET_NAME_C) while (((data_from_pi_w is None) or (data_from_pi_w == [])) and (retry_count < retries)): data_from_pi_w = read_data_from_pi(pi_host, pi_admin, pi_passwd, pi_db, asset_name_with_prefix_w, SENSOR_READ_KEY_W) data_from_pi_m = read_data_from_pi(pi_host, pi_admin, pi_passwd, pi_db, asset_name_with_prefix_m, SENSOR_READ_KEY_M) data_from_pi_a = read_data_from_pi(pi_host, pi_admin, pi_passwd, pi_db, asset_name_with_prefix_a, SENSOR_READ_KEY_A) data_from_pi_c = read_data_from_pi(pi_host, pi_admin, pi_passwd, pi_db, asset_name_with_prefix_c, SENSOR_READ_KEY_C) retry_count += 1 time.sleep((wait_time * 2)) if ((data_from_pi_w is None) or (data_from_pi_m is None) or (data_from_pi_a is None) or (data_from_pi_c is None) or (retry_count == retries)): assert False, 'Failed to read data from PI' print('Data read from PI System:\nWeather={}\nMagnetometer={}\nAccelerometer={}\nrgbColor={}\n'.format(data_from_pi_w, data_from_pi_m, data_from_pi_a, data_from_pi_c)) for w in SENSOR_READ_KEY_W: assert (w in data_from_pi_w) abs_sum_w = sum([abs(n) for n in data_from_pi_w[w]]) print('Weather (sum of {} absolute values), Sensor={}'.format(len(data_from_pi_w[w]), w), abs_sum_w) assert abs_sum_w, 'Sum of weather sensor absolute values is 0' for a in SENSOR_READ_KEY_A: assert (a in data_from_pi_a) abs_sum_a = sum([abs(n) for n in data_from_pi_a[a]]) print('Accelerometer (sum of {} absolute values, Sensor={}'.format(len(data_from_pi_a[a]), a), abs_sum_a) assert abs_sum_a, 'Sum of accelerometer sensor absolute values is 0' for m in SENSOR_READ_KEY_M: assert (m in data_from_pi_m) abs_sum_m = sum([abs(n) for n in data_from_pi_m[m]]) print('Magnetometer (sum of {} absolute values), Sensor={}'.format(len(data_from_pi_m[m]), m), abs_sum_m) assert abs_sum_m, 'Sum of magnetometer sensor absolute values is 0' for c in SENSOR_READ_KEY_C: assert (c in data_from_pi_c) abs_sum_c = sum([abs(n) for n in data_from_pi_c[c]]) print('RGB colors (sum of {} absolute values), Sensor={}'.format(len(data_from_pi_c[c]), c), abs_sum_c) assert abs_sum_c, 'Sum of rgb sensors absolute values is 0'
def construct_article_list(modules_and_symbols): articles = {} symbol_to_article = {} for (mod_name, (module, symbols)) in modules_and_symbols.items(): if len(symbols): article_name = mod_name.lower() if (article_name in articles): suffix = 1 while ((article_name + str(suffix)) in articles): suffix += 1 article_name = (article_name + str(suffix)) articles[article_name] = (mod_name, module) symbol_to_article[mod_name] = article_name suffix = 0 for (symbol_name, symbol) in symbols: full_name = ((mod_name + '.') + symbol_name) article_name = full_name.lower() if (article_name in articles): suffix += 1 while ((article_name + str(suffix)) in articles): suffix += 1 article_name = (article_name + str(suffix)) articles[article_name] = (full_name, symbol) symbol_to_article[full_name] = article_name return (articles, symbol_to_article)
class SnowflakeAdapterTeleport(TeleportAdapter): def __init__(self, db_adapter: BaseAdapter, teleport_credentials: TeleportCredentials): from dbt.adapters.fal_experimental.adapter_support import new_connection self._db_adapter = db_adapter self._credentials = teleport_credentials url = f's3://{teleport_credentials.s3_bucket}/teleport' with new_connection(self._db_adapter, 'fal-snowflake:setup-teleport') as conn: cur = conn.handle.cursor() create_stage_query = f'''CREATE OR REPLACE STAGE falstage URL = '{url}' CREDENTIALS = ( aws_key_id='{self._credentials.s3_access_key_id}', aws_secret_key='{self._credentials.s3_access_key}');''' create_format_query = "CREATE OR REPLACE FILE FORMAT falparquet type = 'PARQUET';" cur.execute(create_stage_query) cur.execute(create_format_query) def storage_formats(cls): return ['parquet'] def teleport_from_external_storage(self, relation: BaseRelation, relation_path: str, teleport_info: TeleportInfo) -> None: assert (teleport_info.format == 'parquet'), 'snowflake only supports parquet format for Teleport' location = f'/{relation_path}' with self._db_adapter.connection_named('teleport:copy_from'): create_macro = self._db_adapter.execute_macro('snowflake__create_table_from_parquet', kwargs={'relation': relation, 'location': location}) self._db_adapter.execute(create_macro) copy_macro = self._db_adapter.execute_macro('snowflake__copy_from_parquet', kwargs={'relation': relation, 'location': location}) self._db_adapter.execute(copy_macro) def teleport_to_external_storage(self, relation: BaseRelation, teleport_info: TeleportInfo) -> str: assert (teleport_info.format == 'parquet'), 'snowflake only supports parquet format for Teleport' relation_path = teleport_info.build_relation_path(relation) location = f'/{relation_path}' rendered_macro = self._db_adapter.execute_macro('snowflake__copy_to_parquet', kwargs={'relation': relation, 'location': location}) with self._db_adapter.connection_named('teleport:copy_to'): self._db_adapter.execute(rendered_macro) return relation_path
def largest_optimized(min_factor, max_factor): if (min_factor > max_factor): raise ValueError('min must be <= max') result = 0 answer = [] for number_a in range(max_factor, (min_factor - 1), (- 1)): was_bigger = False for number_b in range(max_factor, (number_a - 1), (- 1)): if ((number_a * number_b) >= result): was_bigger = True test_value = str((number_a * number_b)) if (test_value == test_value[::(- 1)]): if ((number_a * number_b) > result): answer = [] result = int(test_value) answer.append([number_a, number_b]) if (not was_bigger): break if (result == 0): result = None return (result, answer)
class TestRefreshingToken(): def test_repr(self): low_token = make_token_obj('token', False) cred = MagicMock() auto_token = RefreshingToken(low_token, cred) assert repr(auto_token).startswith('RefreshingToken(') def test_fresh_token_returned(self): low_token = make_token_obj('token', False) cred = MagicMock() auto_token = RefreshingToken(low_token, cred) assert (auto_token.access_token == 'token') def test_expiring_token_refreshed(self): expiring = make_token_obj('expiring', True) refreshed = make_token_obj('refreshed', False) cred = MagicMock() cred.refresh.return_value = refreshed auto_token = RefreshingToken(expiring, cred) assert (auto_token.access_token == 'refreshed') def test_refreshing_token_has_same_attributes_as_regular(self): token_info = MagicMock() token = Token(token_info, uses_pkce=False) token._expires_at = 3000 auto_token = RefreshingToken(token, MagicMock()) token_attributes = [a for a in dir(token) if (not a.startswith('_'))] auto_attributes = [a for a in dir(auto_token) if (not a.startswith('_'))] for attribute in token_attributes: auto_token.__getattribute__(attribute) assert (attribute in auto_attributes) def test_refreshing_token_expiration_attributes(self): token_info = MagicMock() token = Token(token_info, uses_pkce=False) token._expires_at = 0 auto_token = RefreshingToken(token, MagicMock()) assert (auto_token.is_expiring is False) assert (auto_token.expires_in is None) assert (auto_token.expires_at is None)
class PKManyToManyTests(TestCase): def setUp(self): for idx in range(1, 4): target = ManyToManyTarget(name=('target-%d' % idx)) target.save() source = ManyToManySource(name=('source-%d' % idx)) source.save() for target in ManyToManyTarget.objects.all(): source.targets.add(target) def test_many_to_many_retrieve(self): queryset = ManyToManySource.objects.all() serializer = ManyToManySourceSerializer(queryset, many=True) expected = [{'id': 1, 'name': 'source-1', 'targets': [1]}, {'id': 2, 'name': 'source-2', 'targets': [1, 2]}, {'id': 3, 'name': 'source-3', 'targets': [1, 2, 3]}] with self.assertNumQueries(4): assert (serializer.data == expected) def test_many_to_many_retrieve_prefetch_related(self): queryset = ManyToManySource.objects.all().prefetch_related('targets') serializer = ManyToManySourceSerializer(queryset, many=True) with self.assertNumQueries(2): serializer.data def test_reverse_many_to_many_retrieve(self): queryset = ManyToManyTarget.objects.all() serializer = ManyToManyTargetSerializer(queryset, many=True) expected = [{'id': 1, 'name': 'target-1', 'sources': [1, 2, 3]}, {'id': 2, 'name': 'target-2', 'sources': [2, 3]}, {'id': 3, 'name': 'target-3', 'sources': [3]}] with self.assertNumQueries(4): assert (serializer.data == expected) def test_many_to_many_update(self): data = {'id': 1, 'name': 'source-1', 'targets': [1, 2, 3]} instance = ManyToManySource.objects.get(pk=1) serializer = ManyToManySourceSerializer(instance, data=data) assert serializer.is_valid() serializer.save() assert (serializer.data == data) queryset = ManyToManySource.objects.all() serializer = ManyToManySourceSerializer(queryset, many=True) expected = [{'id': 1, 'name': 'source-1', 'targets': [1, 2, 3]}, {'id': 2, 'name': 'source-2', 'targets': [1, 2]}, {'id': 3, 'name': 'source-3', 'targets': [1, 2, 3]}] assert (serializer.data == expected) def test_reverse_many_to_many_update(self): data = {'id': 1, 'name': 'target-1', 'sources': [1]} instance = ManyToManyTarget.objects.get(pk=1) serializer = ManyToManyTargetSerializer(instance, data=data) assert serializer.is_valid() serializer.save() assert (serializer.data == data) queryset = ManyToManyTarget.objects.all() serializer = ManyToManyTargetSerializer(queryset, many=True) expected = [{'id': 1, 'name': 'target-1', 'sources': [1]}, {'id': 2, 'name': 'target-2', 'sources': [2, 3]}, {'id': 3, 'name': 'target-3', 'sources': [3]}] assert (serializer.data == expected) def test_many_to_many_create(self): data = {'id': 4, 'name': 'source-4', 'targets': [1, 3]} serializer = ManyToManySourceSerializer(data=data) assert serializer.is_valid() obj = serializer.save() assert (serializer.data == data) assert (obj.name == 'source-4') queryset = ManyToManySource.objects.all() serializer = ManyToManySourceSerializer(queryset, many=True) expected = [{'id': 1, 'name': 'source-1', 'targets': [1]}, {'id': 2, 'name': 'source-2', 'targets': [1, 2]}, {'id': 3, 'name': 'source-3', 'targets': [1, 2, 3]}, {'id': 4, 'name': 'source-4', 'targets': [1, 3]}] assert (serializer.data == expected) def test_many_to_many_unsaved(self): source = ManyToManySource(name='source-unsaved') serializer = ManyToManySourceSerializer(source) expected = {'id': None, 'name': 'source-unsaved', 'targets': []} with self.assertNumQueries(0): assert (serializer.data == expected) def test_reverse_many_to_many_create(self): data = {'id': 4, 'name': 'target-4', 'sources': [1, 3]} serializer = ManyToManyTargetSerializer(data=data) assert serializer.is_valid() obj = serializer.save() assert (serializer.data == data) assert (obj.name == 'target-4') queryset = ManyToManyTarget.objects.all() serializer = ManyToManyTargetSerializer(queryset, many=True) expected = [{'id': 1, 'name': 'target-1', 'sources': [1, 2, 3]}, {'id': 2, 'name': 'target-2', 'sources': [2, 3]}, {'id': 3, 'name': 'target-3', 'sources': [3]}, {'id': 4, 'name': 'target-4', 'sources': [1, 3]}] assert (serializer.data == expected)
class OptionPlotoptionsLineSonificationTracksMappingLowpass(Options): def frequency(self) -> 'OptionPlotoptionsLineSonificationTracksMappingLowpassFrequency': return self._config_sub_data('frequency', OptionPlotoptionsLineSonificationTracksMappingLowpassFrequency) def resonance(self) -> 'OptionPlotoptionsLineSonificationTracksMappingLowpassResonance': return self._config_sub_data('resonance', OptionPlotoptionsLineSonificationTracksMappingLowpassResonance)
class TestCu2QuPen(unittest.TestCase, _TestPenMixin): def __init__(self, *args, **kwargs): super(TestCu2QuPen, self).__init__(*args, **kwargs) self.Glyph = DummyGlyph self.Pen = DummyPen self.Cu2QuPen = Cu2QuPen self.pen_getter_name = 'getPen' self.draw_method_name = 'draw' def test_qCurveTo_1_point(self): pen = DummyPen() quadpen = Cu2QuPen(pen, MAX_ERR) quadpen.moveTo((0, 0)) quadpen.qCurveTo((1, 1)) self.assertEqual(str(pen).splitlines(), ['pen.moveTo((0, 0))', 'pen.qCurveTo((1, 1))']) def test_qCurveTo_more_than_1_point(self): pen = DummyPen() quadpen = Cu2QuPen(pen, MAX_ERR) quadpen.moveTo((0, 0)) quadpen.qCurveTo((1, 1), (2, 2)) self.assertEqual(str(pen).splitlines(), ['pen.moveTo((0, 0))', 'pen.qCurveTo((1, 1), (2, 2))']) def test_curveTo_1_point(self): pen = DummyPen() quadpen = Cu2QuPen(pen, MAX_ERR) quadpen.moveTo((0, 0)) quadpen.curveTo((1, 1)) self.assertEqual(str(pen).splitlines(), ['pen.moveTo((0, 0))', 'pen.qCurveTo((1, 1))']) def test_curveTo_2_points(self): pen = DummyPen() quadpen = Cu2QuPen(pen, MAX_ERR) quadpen.moveTo((0, 0)) quadpen.curveTo((1, 1), (2, 2)) self.assertEqual(str(pen).splitlines(), ['pen.moveTo((0, 0))', 'pen.qCurveTo((1, 1), (2, 2))']) def test_curveTo_3_points(self): pen = DummyPen() quadpen = Cu2QuPen(pen, MAX_ERR) quadpen.moveTo((0, 0)) quadpen.curveTo((1, 1), (2, 2), (3, 3)) self.assertEqual(str(pen).splitlines(), ['pen.moveTo((0, 0))', 'pen.qCurveTo((0.75, 0.75), (2.25, 2.25), (3, 3))']) def test_curveTo_more_than_3_points(self): pen = DummyPen() quadpen = Cu2QuPen(pen, MAX_ERR) quadpen.moveTo((0, 0)) quadpen.curveTo((1, 1), (2, 2), (3, 3), (4, 4)) self.assertEqual(str(pen).splitlines(), ['pen.moveTo((0, 0))', 'pen.qCurveTo((0.75, 0.75), (1.625, 1.625), (2, 2))', 'pen.qCurveTo((2.375, 2.375), (3.25, 3.25), (4, 4))'])
(IStatusBarManager) class StatusBarManager(HasTraits): message = Property messages = List(Str) status_bar = Any() def create_status_bar(self, parent): if (self.status_bar is None): self.status_bar = wx.StatusBar(parent) self.status_bar._pyface_control = self if (len(self.messages) > 1): self.status_bar.SetFieldsCount(len(self.messages)) for i in range(len(self.messages)): self.status_bar.SetStatusText(self.messages[i], i) else: self.status_bar.SetStatusText(self.message) return self.status_bar def destroy(self): if (self.status_bar is not None): self.status_bar.Destroy() self.status_bar._pyface_control = None self.status_bar = None def _get_message(self): if (len(self.messages) > 0): message = self.messages[0] else: message = '' return message def _set_message(self, value): if (len(self.messages) > 0): old = self.messages[0] self.messages[0] = value else: old = '' self.messages.append(value) self.trait_property_changed('message', old, value) return def _messages_changed(self): if (self.status_bar is not None): for i in range(len(self.messages)): self.status_bar.SetStatusText(self.messages[i], i) def _messages_items_changed(self): if (self.status_bar is not None): for i in range(len(self.messages)): self.status_bar.SetStatusText(self.messages[i], i) return
class GreetingWorkflowImpl(GreetingWorkflow): async def get_greeting(self): global version_found_in_step_1_0, version_found_in_step_1_1 global version_found_in_step_2_0, version_found_in_step_2_1 version_found_in_step_1_0 = Workflow.get_version('first-item', DEFAULT_VERSION, 2) version_found_in_step_1_1 = Workflow.get_version('first-item', DEFAULT_VERSION, 2) (await Workflow.sleep(60)) version_found_in_step_2_0 = Workflow.get_version('first-item', DEFAULT_VERSION, 2) version_found_in_step_2_1 = Workflow.get_version('first-item', DEFAULT_VERSION, 2)
def setup_logging(verbosity: int, color_logging: bool=False, apprise_notifiers: List[str]=[]) -> None: add_logging_level('EXTRA_DEBUG', (logging.DEBUG - 1)) add_logging_level('WEBSOCKET_DATA', (logging.DEBUG - 2)) format = '{asctime} [{levelname:^11s}] {name:<42} : {message}' sh = create_logging_handler(format, color_logging) logger = logging.getLogger('unifi_protect_backup') logger.addHandler(sh) logger.propagate = False if (verbosity == 0): logging.basicConfig(level=logging.WARN, handlers=[sh]) logger.setLevel(logging.INFO) elif (verbosity == 1): logging.basicConfig(level=logging.WARN, handlers=[sh]) logger.setLevel(logging.DEBUG) elif (verbosity == 2): logging.basicConfig(level=logging.WARN, handlers=[sh]) logger.setLevel(logging.EXTRA_DEBUG) elif (verbosity == 3): logging.basicConfig(level=logging.INFO, handlers=[sh]) logger.setLevel(logging.EXTRA_DEBUG) elif (verbosity == 4): logging.basicConfig(level=logging.INFO, handlers=[sh]) logger.setLevel(logging.WEBSOCKET_DATA) elif (verbosity >= 5): logging.basicConfig(level=logging.DEBUG, handlers=[sh]) logger.setLevel(logging.WEBSOCKET_DATA)
class TestMlabNullEngineBase(unittest.TestCase): def setUp(self): e = Engine() e.start() self._non_null_engine = e mlab.set_engine(e) def tearDown(self): if (not (mlab.get_engine() is self._non_null_engine)): raise AssertionError('The NullEngine has overridden the default one') engine_manager.current_engine = None registry.unregister_engine(self._non_null_engine) for engine in list(registry.engines): registry.unregister_engine(engine)
class KiwoomOpenApiPlusServiceServer(Logging): def __init__(self, control, host=None, port=None, credentials=None, **kwargs): if (host is None): host = config.get_string('koapy.backend.kiwoom_open_api_plus.grpc.host', 'localhost') host = config.get_string('koapy.backend.kiwoom_open_api_plus.grpc.server.host', host) if (port is None): port = config.get_int('koapy.backend.kiwoom_open_api_plus.grpc.port', 0) port = config.get_int('koapy.backend.kiwoom_open_api_plus.grpc.server.port', port) if (port == 0): port = find_free_port_for_host(host) self.logger.info('Using one of the free ports, final address would be %s:%d', host, port) self._control = control self._host = host self._port = port self._credentials = credentials self._kwargs = dict(kwargs) self._servicer = KiwoomOpenApiPlusServiceServicer(self._control) self._address = ((self._host + ':') + str(self._port)) grpc_server_signature = inspect.signature(grpc.server) grpc_server_params = list(grpc_server_signature.parameters.keys()) grpc_server_kwargs = {k: v for (k, v) in self._kwargs.items() if (k in grpc_server_params)} grpc_server_bound_arguments = grpc_server_signature.bind_partial(**grpc_server_kwargs) if (grpc_server_bound_arguments.arguments.get('thread_pool') is None): thread_pool_signature = inspect.signature(ThreadPoolExecutor) thread_pool_params = list(thread_pool_signature.parameters.keys()) thread_pool_kwargs = {k: v for (k, v) in self._kwargs.items() if (k in thread_pool_params)} thread_pool_bound_arguments = thread_pool_signature.bind(**thread_pool_kwargs) if (thread_pool_bound_arguments.arguments.get('max_workers') is None): max_workers = config.get_int('koapy.backend.kiwoom_open_api_plus.grpc.server.max_workers', 8) thread_pool_bound_arguments.arguments['max_workers'] = max_workers thread_pool = ThreadPoolExecutor(*thread_pool_bound_arguments.args, **thread_pool_bound_arguments.kwargs) grpc_server_bound_arguments.arguments['thread_pool'] = thread_pool self._thread_pool = thread_pool else: self._thread_pool = grpc_server_bound_arguments.arguments['thread_pool'] self._grpc_server_bound_arguments = grpc_server_bound_arguments self._server = None self._server_started = False self._server_stopped = False self.reinitialize_server() def reinitialize_server(self): if (self._server is not None): self.stop() self.wait_for_termination() self._server = grpc.server(*self._grpc_server_bound_arguments.args, **self._grpc_server_bound_arguments.kwargs) self._server_started = False self._server_stopped = False KiwoomOpenApiPlusService_pb2_grpc.add_KiwoomOpenApiPlusServiceServicer_to_server(self._servicer, self._server) if (self._credentials is None): if (not is_in_private_network(self._host)): self.logger.warning('Adding insecure port %s to server, but the address is not private.', self._address) self._server.add_insecure_port(self._address) else: self._server.add_secure_port(self._address, self._credentials) def get_host(self): return self._host def get_port(self): return self._port def start(self): if (self._server_started and self._server_stopped): self.reinitialize_server() if (not self._server_started): self._server.start() self._server_started = True def wait_for_termination(self, timeout=None): return self._server.wait_for_termination(timeout) def is_running(self): return self.wait_for_termination(1) def stop(self, grace=None): event = self._server.stop(grace) self._server_stopped = True return event def __getattr__(self, name): return getattr(self._server, name) def __enter__(self): self.start() return self def __exit__(self, exc_type, exc_value, traceback): self.stop() self.wait_for_termination()
class Arm(BaseArch): bits = 32 gpr_registers = ['r0', 'r1', 'r2', 'r3', 'r4', 'r5', 'r6', 'r7', 'r8', 'r9', 'r10', 'r11', 'r12', 'sp', 'lr', 'pc'] gpr_key = 'general' flag_register = 'cpsr' flag_register_bit_masks = {'n': , 'z': , 'c': , 'v': , 'q': , 'j': , 'ge': 983040, 'e': 512, 'a': 256, 'i': 128, 'f': 64, 't': 32}
def get_curr_and_ref_df(data: InputData, min_rel_score: Optional[int]=None, no_feedback_users: bool=False, bin_data: bool=True): target_column = data.data_definition.get_target_column() prediction = data.data_definition.get_prediction_columns() if ((target_column is None) or (prediction is None)): raise ValueError('Target and prediction were not found in data.') (_, target_current, target_reference) = data.get_data(target_column.column_name) recommendations_type = (data.column_mapping.recom_type or RecomType.SCORE) if (prediction.prediction_probas is not None): pred_name = prediction.prediction_probas[0].column_name elif (prediction.predicted_values is not None): pred_name = prediction.predicted_values.column_name (_, prediction_current, prediction_reference) = data.get_data(pred_name) user_column = data.column_mapping.user_id if (user_column is None): raise ValueError('User_id was not found in data.') (_, user_current, user_reference) = data.get_data(user_column) curr = collect_dataset(user_current, target_current, prediction_current, recommendations_type, min_rel_score, no_feedback_users, bin_data) ref: Optional[pd.DataFrame] = None if ((user_reference is not None) and (target_reference is not None) and (prediction_reference is not None)): ref = collect_dataset(user_reference, target_reference, prediction_reference, recommendations_type, min_rel_score, no_feedback_users, bin_data) return (curr, ref)
class M12L16161A(SDRModule): nbanks = 2 nrows = 2048 ncols = 256 technology_timings = _TechnologyTimings(tREFI=(.0 / 4096), tWTR=(2, None), tCCD=(1, None), tRRD=(None, 10)) speedgrade_timings = {'default': _SpeedgradeTimings(tRP=15, tRCD=15, tWR=15, tRFC=(None, 55), tFAW=None, tRAS=40)}
def extractIdidmybesttranslationsWordpressCom(item): (vol, chp, frag, postfix) = extractVolChapterFragmentPostfix(item['title']) if ((not (chp or vol)) or ('preview' in item['title'].lower())): return None tagmap = [('PRC', 'PRC', 'translated'), ('Loiterous', 'Loiterous', 'oel')] for (tagname, name, tl_type) in tagmap: if (tagname in item['tags']): return buildReleaseMessageWithType(item, name, vol, chp, frag=frag, postfix=postfix, tl_type=tl_type) if (item['tags'] == ['Uncategorized']): titlemap = [('After Being Transported into a Book, I Adopted the Villain Chapter ', 'After Being Transported into a Book, I Adopted the Villain', 'translated'), ('After Being Transported into a Book, I Adopted the Villain Ch. ', 'After Being Transported into a Book, I Adopted the Villain', 'translated'), ('After Being Transported into a Book, I Adopted the Villain Ch.', 'After Being Transported into a Book, I Adopted the Villain', 'translated'), ('Tensei Shoujo no Rirekisho', 'Tensei Shoujo no Rirekisho', 'translated'), ('Master of Dungeon', 'Master of Dungeon', 'oel')] for (titlecomponent, name, tl_type) in titlemap: if (titlecomponent.lower() in item['title'].lower()): return buildReleaseMessageWithType(item, name, vol, chp, frag=frag, postfix=postfix, tl_type=tl_type) return False
class UserDeleteView(MenuItemMixin, FormView): form_class = UserDeletionForm template_name = 'registration/unregister.html' menu_parameters = 'account' _decorator(login_required) def dispatch(self, request, *args, **kwargs): return super(UserDeleteView, self).dispatch(request, *args, **kwargs) def get_form_kwargs(self): kwargs = super(UserDeleteView, self).get_form_kwargs() kwargs['user'] = self.request.user return kwargs def form_valid(self, form): user = self.request.user user.delete() logout(self.request) messages.success(self.request, _('Your account has been removed')) return HttpResponseRedirect(reverse('forum:index'))
.parametrize('ops', ALL_OPS) .parametrize('dtype', FLOAT_TYPES) def test_reduce_mean(ops, dtype): X = ops.asarray2f([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0], [1.0, 2.0], [3.0, 4.0]], dtype=dtype) lengths = ops.asarray1i([3, 2]) ops.xp.testing.assert_allclose(ops.reduce_mean(X, lengths), [[3.0, 4.0], [2.0, 3.0]]) lengths = ops.asarray1i([3, 0, 2]) ops.xp.testing.assert_allclose(ops.reduce_mean(X, lengths), [[3.0, 4.0], [0.0, 0.0], [2.0, 3.0]]) X = ops.asarray2f([[1.0, 2.0], [3.0, 4.0], [5.0, 6.0]], dtype=dtype) lengths = ops.asarray1i([3, 0]) ops.xp.testing.assert_allclose(ops.reduce_mean(X, lengths), [[3.0, 4.0], [0.0, 0.0]]) with pytest.raises(IndexError): ops.reduce_mean(X, ops.xp.array([3, 3], dtype='i')) with pytest.raises(ValueError): ops.reduce_mean(X, ops.xp.array([(- 1), 5], dtype='i'))
class OptionPlotoptionsAreasplineSonificationContexttracksMappingFrequency(Options): def mapFunction(self): return self._config_get(None) def mapFunction(self, value: Any): self._config(value, js_type=False) def mapTo(self): return self._config_get(None) def mapTo(self, text: str): self._config(text, js_type=False) def max(self): return self._config_get(None) def max(self, num: float): self._config(num, js_type=False) def min(self): return self._config_get(None) def min(self, num: float): self._config(num, js_type=False) def within(self): return self._config_get(None) def within(self, value: Any): self._config(value, js_type=False)
() ('--batch-size', type=int, default=0, help='Inference batch size') ('--seq-length', type=int, default=0, help='Inference sequence length') ('--activation', type=str, default='fast_gelu', help='Activation function applied on BERT, currently only support fast_gelu on Rocm. CUDA supports both gelu and fast_gelu. No effect if framework is pt.') ('--graph-mode', type=bool, default=True, help='Use CUDA graph or not. hipGraph is not supported yet. No effect if framework is pt.') ('--use-fp16-acc', type=bool, default=True, help='Use fp16 accumulation or not (TensorRT is using fp16_acc). No effect if framework is pt.') ('--use-pretrained-pt-model', type=bool, default=True, help='Whether or not to use the pretrained BERT model weights.') ('--encoders-only', type=bool, default=True, help='Whether or not to run the BERT benchmark with encoders only. If enabled, only the transformer blocks without BERT embeddings are benchmarked.') def compile_and_benchmark(batch_size: int, seq_length: int, activation: str, graph_mode: bool, use_fp16_acc: bool, use_pretrained_pt_model: bool, encoders_only: bool): if (detect_target().name() == 'rocm'): graph_mode = False assert (activation in 'fast_gelu'), f'Unsupported activation: {activation} on rocm' pt_model = BertPt(pretrained=use_pretrained_pt_model)._model pt_model.eval() hidden_size = pt_model.config.hidden_size if (batch_size < 1): batch_sizes = [1, 2, 4, 8, 16, 32, 64, 128, 256] else: batch_sizes = [batch_size] if (seq_length < 1): seq_lengths = ([64, 128, 384, 512, 1024, 4096] if encoders_only else [64, 128, 384, 512]) else: seq_lengths = [seq_length] for seq_length in seq_lengths: for bs in batch_sizes: mod = compile_module(bs, seq_length, hidden_size, activation, use_fp16_acc, encoders_only, pt_model) benchmark(bs, seq_length, hidden_size, mod, graph_mode, encoders_only)
def test_alias_argument_1(): f = alias_argument()(func_x) assert (f(1) == 1) assert (f(x=1) == 1) with pytest.raises(TypeError): assert (f(unk=1) == 1) f = alias_argument(x=['alias'])(func_x) assert (f(alias=1) == 1) assert (f(x=1) == 1) f = alias_argument(x='alias')(func_x) assert (f(alias=1) == 1) assert (f(x=1) == 1) with pytest.raises(ValueError): f = alias_argument(x={'alias': 'value'})(func_x) f = alias_argument(x=['alias', 'blias'])(func_x) assert (f(alias=1) == 1) with pytest.raises(TypeError): f = alias_argument(unk=['x'])(func_x) assert (f(x=1) == 1)
def request_counter(metrics_name: str) -> Callable: def wrap(f: Callable): (f) def wrapper_sync(self: MetricsGetter, *args, **kwargs): if self.has_metrics(): self.get_metrics().count(metrics_name, 1) return f(self, *args, **kwargs) (f) async def wrapper_async(self: MetricsGetter, *args, **kwargs): if self.has_metrics(): self.get_metrics().count(metrics_name, 1) return (await f(self, *args, **kwargs)) return (wrapper_async if asyncio.iscoroutinefunction(f) else wrapper_sync) return wrap
.xfail(raises=ImageComparisonFailure, reason='Matplotlib plots for reasons a different image size.') .skipif((MID_MEMORY > memory), reason='Travis has too less memory to run it.') def test_hicPlotMatrix_region_region2_log1p_clearMaskedBins_and_bigwig_vmin_vmax_vertical(): outfile = NamedTemporaryFile(suffix='.png', prefix='hicexplorer_test_h5_', delete=False) args = '--matrix {0}/Li_et_al_2015.h5 --region chrX:3000000-3500000 --region2 chrX:3100000-3600000 --outFileName {1} --log1p --clearMaskedBins --bigwig {2} --vMinBigwig {3} --vMaxBigwig {4} --bigwigAdditionalVerticalAxis'.format(ROOT, outfile.name, (ROOT + 'bigwig_chrx_2e6_5e6.bw'), 0, 1).split() test_image_path = ((ROOT + 'hicPlotMatrix') + '/Li_chrX30-35-chrX31-36_log1p_clearmaskedbins_vbigwigmin_vbigwigmax_vertical.png') compute(hicexplorer.hicPlotMatrix.main, args, 5) res = compare_images(test_image_path, outfile.name, tolerance) assert (res is None), res
class OptionPlotoptionsTreemapSonificationContexttracks(Options): def activeWhen(self) -> 'OptionPlotoptionsTreemapSonificationContexttracksActivewhen': return self._config_sub_data('activeWhen', OptionPlotoptionsTreemapSonificationContexttracksActivewhen) def instrument(self): return self._config_get('piano') def instrument(self, text: str): self._config(text, js_type=False) def mapping(self) -> 'OptionPlotoptionsTreemapSonificationContexttracksMapping': return self._config_sub_data('mapping', OptionPlotoptionsTreemapSonificationContexttracksMapping) def midiName(self): return self._config_get(None) def midiName(self, text: str): self._config(text, js_type=False) def pointGrouping(self) -> 'OptionPlotoptionsTreemapSonificationContexttracksPointgrouping': return self._config_sub_data('pointGrouping', OptionPlotoptionsTreemapSonificationContexttracksPointgrouping) def roundToMusicalNotes(self): return self._config_get(True) def roundToMusicalNotes(self, flag: bool): self._config(flag, js_type=False) def showPlayMarker(self): return self._config_get(True) def showPlayMarker(self, flag: bool): self._config(flag, js_type=False) def timeInterval(self): return self._config_get(None) def timeInterval(self, num: float): self._config(num, js_type=False) def type(self): return self._config_get('instrument') def type(self, text: str): self._config(text, js_type=False) def valueInterval(self): return self._config_get(None) def valueInterval(self, num: float): self._config(num, js_type=False) def valueMapFunction(self): return self._config_get('linear') def valueMapFunction(self, value: Any): self._config(value, js_type=False) def valueProp(self): return self._config_get('"x"') def valueProp(self, text: str): self._config(text, js_type=False)
class TestLeakyReluConverter(AITTestCase): def test_leaky_relu(self): class TestModule(torch.nn.Module): def forward(self, x: torch.Tensor) -> torch.Tensor: return torch.nn.functional.leaky_relu(x, negative_slope=0.05) model = TestModule().cuda().half() inputs = [torch.randn(2, 3).half().cuda()] self.run_test(model, inputs, expected_ops={acc_ops.leaky_relu})
.scheduler def test_surface_init_fails_during_forward_model_callback(copy_case, monkeypatch, try_queue_and_scheduler): copy_case('snake_oil_field') rng = np.random.default_rng() Path('./surface').mkdir() nx = 5 ny = 10 surf = xtgeo.RegularSurface(ncol=nx, nrow=ny, xinc=1.0, yinc=1.0, values=rng.standard_normal(size=(nx, ny))) surf.to_file('surface/surf_init_0.irap', fformat='irap_ascii') config_file_name = 'snake_oil_surface.ert' parameter_name = 'TOP' with open(config_file_name, mode='r+', encoding='utf-8') as config_file_handler: content_lines = config_file_handler.read().splitlines() index_line_with_surface_top = [index for (index, line) in enumerate(content_lines) if line.startswith(f'SURFACE {parameter_name}')][0] line_with_surface_top = content_lines[index_line_with_surface_top] breaking_line_with_surface_top = line_with_surface_top content_lines[index_line_with_surface_top] = breaking_line_with_surface_top config_file_handler.seek(0) config_file_handler.write('\n'.join(content_lines)) try: run_ert_test_run(config_file_name) except ErtCliError as err: assert (f'Failed to initialize parameter {parameter_name!r}' in str(err))
class NotifierTest(ForsetiTestCase): def test_can_convert_created_at_datetime_to_timestamp_string(self): violations = [dict(created_at_datetime=datetime(1999, 12, 25, 1, 2, 3)), dict(created_at_datetime=datetime(2010, 6, 8, 4, 5, 6))] expected_timestamps = ['1999-12-25T01:02:03Z', '2010-06-08T04:05:06Z'] violations_with_converted_timestamp = notifier.convert_to_timestamp(violations) converted_timestamps = [] for i in violations_with_converted_timestamp: converted_timestamps.append(i['created_at_datetime']) self.assertEqual(expected_timestamps, converted_timestamps) ('google.cloud.forseti.notifier.notifier.find_notifiers', autospec=True) ('google.cloud.forseti.notifier.notifier.scanner_dao', autospec=True) def test_no_notifications_for_empty_violations(self, mock_dao, mock_find_notifiers): mock_dao.map_by_resource.return_value = dict() mock_service_cfg = mock.MagicMock() mock_service_cfg.get_global_config.return_value = fake_violations.GLOBAL_CONFIGS mock_service_cfg.get_notifier_config.return_value = fake_violations.NOTIFIER_CONFIGS notifier.run('iid-1-2-3', None, mock.MagicMock(), mock_service_cfg) self.assertFalse(mock_find_notifiers.called) ('google.cloud.forseti.notifier.notifiers.email_violations.EmailViolations', autospec=True) ('google.cloud.forseti.notifier.notifiers.gcs_violations.GcsViolations', autospec=True) ('google.cloud.forseti.notifier.notifier.find_notifiers', autospec=True) ('google.cloud.forseti.notifier.notifier.scanner_dao', autospec=True) def test_notifications_for_nonempty_violations(self, mock_dao, mock_find_notifiers, mock_gcs_violations_cls, mock_email_violations_cls): mock_dao.map_by_resource.return_value = fake_violations.VIOLATIONS mock_service_cfg = mock.MagicMock() mock_service_cfg.get_global_config.return_value = fake_violations.GLOBAL_CONFIGS mock_service_cfg.get_notifier_config.return_value = fake_violations.NOTIFIER_CONFIGS mock_email_violations = mock.MagicMock(spec=email_violations.EmailViolations) mock_email_violations_cls.return_value = mock_email_violations mock_email_violations = mock_email_violations_cls.return_value mock_gcs_violations = mock_gcs_violations_cls.return_value mock_find_notifiers.side_effect = [mock_email_violations_cls, mock_gcs_violations_cls] notifier.run('iid-1-2-3', None, mock.MagicMock(), mock_service_cfg) self.assertTrue(mock_find_notifiers.called) self.assertEqual(1, mock_email_violations_cls.call_count) self.assertEqual('iam_policy_violations', mock_email_violations_cls.call_args[0][0]) self.assertEqual(1, mock_email_violations.run.call_count) self.assertEqual(1, mock_gcs_violations_cls.call_count) self.assertEqual('iam_policy_violations', mock_gcs_violations_cls.call_args[0][0]) self.assertEqual(1, mock_gcs_violations.run.call_count) ('google.cloud.forseti.notifier.notifiers.email_violations.EmailViolations', autospec=True) ('google.cloud.forseti.notifier.notifiers.gcs_violations.GcsViolations', autospec=True) ('google.cloud.forseti.notifier.notifier.find_notifiers', autospec=True) ('google.cloud.forseti.notifier.notifier.scanner_dao', autospec=True) ('google.cloud.forseti.notifier.notifier.LOGGER', autospec=True) def test_notifications_are_not_sent_without_valid_scanner_index_id(self, mock_logger, mock_dao, mock_find_notifiers, mock_gcs_violations_cls, mock_email_violations_cls): mock_dao.get_latest_scanner_index_id.return_value = None mock_service_cfg = mock.MagicMock() mock_service_cfg.get_global_config.return_value = fake_violations.GLOBAL_CONFIGS mock_service_cfg.get_notifier_config.return_value = fake_violations.NOTIFIER_CONFIGS mock_email_violations = mock.MagicMock(spec=email_violations.EmailViolations) mock_email_violations_cls.return_value = mock_email_violations mock_email_violations = mock_email_violations_cls.return_value mock_gcs_violations = mock_gcs_violations_cls.return_value mock_find_notifiers.side_effect = [mock_email_violations_cls, mock_gcs_violations_cls] notifier.run('iid-1-2-3', None, mock.MagicMock(), mock_service_cfg) self.assertFalse(mock_find_notifiers.called) self.assertFalse(mock_dao.map_by_resource.called) self.assertTrue(mock_logger.error.called) ('google.cloud.forseti.notifier.notifier.InventorySummary', autospec=True) ('google.cloud.forseti.notifier.notifier.find_notifiers', autospec=True) ('google.cloud.forseti.notifier.notifier.scanner_dao', autospec=True) def test_inventory_summary_is_called(self, mock_dao, mock_find_notifiers, mock_inventor_summary): mock_dao.map_by_resource.return_value = dict() mock_service_cfg = mock.MagicMock() mock_service_cfg.get_global_config.return_value = fake_violations.GLOBAL_CONFIGS mock_service_cfg.get_notifier_config.return_value = fake_violations.NOTIFIER_CONFIGS notifier.run('iid-1-2-3', None, mock.MagicMock(), mock_service_cfg) self.assertFalse(mock_find_notifiers.called) self.assertTrue(mock_inventor_summary.called)
class LinkableContract(Contract): unlinked_references: Optional[Tuple[Dict[(str, Any)]]] = None linked_references: Optional[Tuple[Dict[(str, Any)]]] = None needs_bytecode_linking = None def __init__(self, address: bytes, **kwargs: Any) -> None: if self.needs_bytecode_linking: raise BytecodeLinkingError('Contract cannot be instantiated until its bytecode is linked.') validate_address(address) super().__init__(address=address, **kwargs) def factory(cls, w3: 'Web3', class_name: str=None, **kwargs: Any) -> Type[Self]: dep_link_refs = kwargs.get('unlinked_references') bytecode = kwargs.get('bytecode') needs_bytecode_linking = False if (dep_link_refs and bytecode): if (not is_prelinked_bytecode(to_bytes(hexstr=bytecode), dep_link_refs)): needs_bytecode_linking = True kwargs = assoc(kwargs, 'needs_bytecode_linking', needs_bytecode_linking) return super().factory(w3, class_name, **kwargs) def constructor(cls, *args: Any, **kwargs: Any) -> ContractConstructor: if cls.needs_bytecode_linking: raise BytecodeLinkingError('Contract cannot be deployed until its bytecode is linked.') return super().constructor(*args, **kwargs) def link_bytecode(cls, attr_dict: Dict[(str, str)]) -> Type['LinkableContract']: if ((not cls.unlinked_references) and (not cls.linked_references)): raise BytecodeLinkingError('Contract factory has no linkable bytecode.') if (not cls.needs_bytecode_linking): raise BytecodeLinkingError('Bytecode for this contract factory does not require bytecode linking.') cls.validate_attr_dict(attr_dict) bytecode = apply_all_link_refs(cls.bytecode, cls.unlinked_references, attr_dict) runtime = apply_all_link_refs(cls.bytecode_runtime, cls.linked_references, attr_dict) linked_class = cls.factory(cls.w3, bytecode_runtime=runtime, bytecode=bytecode) if linked_class.needs_bytecode_linking: raise BytecodeLinkingError('Expected class to be fully linked, but class still needs bytecode linking.') return linked_class def validate_attr_dict(self, attr_dict: Dict[(str, str)]) -> None: attr_dict_names = attr_dict.keys() if ((not self.unlinked_references) and (not self.linked_references)): raise BytecodeLinkingError('Unable to validate attr dict, this contract has no linked/unlinked references.') unlinked_refs = (self.unlinked_references or ({},)) linked_refs = (self.linked_references or ({},)) all_link_refs = (unlinked_refs + linked_refs) all_link_names = {ref['name'] for ref in all_link_refs if ref} if (attr_dict_names != all_link_names): raise BytecodeLinkingError('All link references must be defined when calling `link_bytecode` on a contract factory.') for address in attr_dict.values(): validate_address(address)
class MsgStub(object): def __init__(self, channel): self.VerifyInvariant = channel.unary_unary('/cosmos.crisis.v1beta1.Msg/VerifyInvariant', request_serializer=cosmos_dot_crisis_dot_v1beta1_dot_tx__pb2.MsgVerifyInvariant.SerializeToString, response_deserializer=cosmos_dot_crisis_dot_v1beta1_dot_tx__pb2.MsgVerifyInvariantResponse.FromString)
class DPSet(app_manager.RyuApp): def __init__(self, *args, **kwargs): super(DPSet, self).__init__(*args, **kwargs) self.name = 'dpset' self.dps = {} self.port_state = {} def _register(self, dp): LOG.debug('DPSET: register datapath %s', dp) assert (dp.id is not None) send_dp_reconnected = False if (dp.id in self.dps): self.logger.warning('DPSET: Multiple connections from %s', dpid_to_str(dp.id)) self.logger.debug('DPSET: Forgetting datapath %s', self.dps[dp.id]) self.dps[dp.id].close() self.logger.debug('DPSET: New datapath %s', dp) send_dp_reconnected = True self.dps[dp.id] = dp if (dp.id not in self.port_state): self.port_state[dp.id] = PortState() ev = EventDP(dp, True) with warnings.catch_warnings(): warnings.simplefilter('ignore') for port in dp.ports.values(): self._port_added(dp, port) ev.ports.append(port) self.send_event_to_observers(ev) if send_dp_reconnected: ev = EventDPReconnected(dp) ev.ports = self.port_state.get(dp.id, {}).values() self.send_event_to_observers(ev) def _unregister(self, dp): if (dp not in self.dps.values()): return LOG.debug('DPSET: unregister datapath %s', dp) assert (self.dps[dp.id] == dp) ev = EventDP(dp, False) for port in list(self.port_state.get(dp.id, {}).values()): self._port_deleted(dp, port) ev.ports.append(port) self.send_event_to_observers(ev) del self.dps[dp.id] del self.port_state[dp.id] def get(self, dp_id): return self.dps.get(dp_id) def get_all(self): return list(self.dps.items()) def _port_added(self, datapath, port): self.port_state[datapath.id].add(port.port_no, port) def _port_deleted(self, datapath, port): self.port_state[datapath.id].remove(port.port_no) _ev_cls(ofp_event.EventOFPStateChange, [handler.MAIN_DISPATCHER, handler.DEAD_DISPATCHER]) def dispatcher_change(self, ev): datapath = ev.datapath assert (datapath is not None) if (ev.state == handler.MAIN_DISPATCHER): self._register(datapath) elif (ev.state == handler.DEAD_DISPATCHER): self._unregister(datapath) _ev_cls(ofp_event.EventOFPSwitchFeatures, handler.CONFIG_DISPATCHER) def switch_features_handler(self, ev): msg = ev.msg datapath = msg.datapath if (datapath.ofproto.OFP_VERSION < 4): datapath.ports = msg.ports _ev_cls(ofp_event.EventOFPPortStatus, handler.MAIN_DISPATCHER) def port_status_handler(self, ev): msg = ev.msg reason = msg.reason datapath = msg.datapath port = msg.desc ofproto = datapath.ofproto if (reason == ofproto.OFPPR_ADD): LOG.debug(('DPSET: A port was added.' + '(datapath id = %s, port number = %s)'), dpid_to_str(datapath.id), port.port_no) self._port_added(datapath, port) self.send_event_to_observers(EventPortAdd(datapath, port)) elif (reason == ofproto.OFPPR_DELETE): LOG.debug(('DPSET: A port was deleted.' + '(datapath id = %s, port number = %s)'), dpid_to_str(datapath.id), port.port_no) self._port_deleted(datapath, port) self.send_event_to_observers(EventPortDelete(datapath, port)) else: assert (reason == ofproto.OFPPR_MODIFY) LOG.debug(('DPSET: A port was modified.' + '(datapath id = %s, port number = %s)'), dpid_to_str(datapath.id), port.port_no) self.port_state[datapath.id].modify(port.port_no, port) self.send_event_to_observers(EventPortModify(datapath, port)) def get_port(self, dpid, port_no): try: return self.port_state[dpid][port_no] except KeyError: raise ryu_exc.PortNotFound(dpid=dpid, port=port_no, network_id=None) def get_ports(self, dpid): return list(self.port_state[dpid].values())
class OefSearchDialogue(Dialogue): INITIAL_PERFORMATIVES: FrozenSet[Message.Performative] = frozenset({OefSearchMessage.Performative.REGISTER_SERVICE, OefSearchMessage.Performative.UNREGISTER_SERVICE, OefSearchMessage.Performative.SEARCH_SERVICES}) TERMINAL_PERFORMATIVES: FrozenSet[Message.Performative] = frozenset({OefSearchMessage.Performative.OEF_ERROR, OefSearchMessage.Performative.SEARCH_RESULT, OefSearchMessage.Performative.SUCCESS}) VALID_REPLIES: Dict[(Message.Performative, FrozenSet[Message.Performative])] = {OefSearchMessage.Performative.OEF_ERROR: frozenset(), OefSearchMessage.Performative.REGISTER_SERVICE: frozenset({OefSearchMessage.Performative.SUCCESS, OefSearchMessage.Performative.OEF_ERROR}), OefSearchMessage.Performative.SEARCH_RESULT: frozenset(), OefSearchMessage.Performative.SEARCH_SERVICES: frozenset({OefSearchMessage.Performative.SEARCH_RESULT, OefSearchMessage.Performative.OEF_ERROR}), OefSearchMessage.Performative.SUCCESS: frozenset(), OefSearchMessage.Performative.UNREGISTER_SERVICE: frozenset({OefSearchMessage.Performative.SUCCESS, OefSearchMessage.Performative.OEF_ERROR})} class Role(Dialogue.Role): AGENT = 'agent' OEF_NODE = 'oef_node' class EndState(Dialogue.EndState): SUCCESSFUL = 0 FAILED = 1 def __init__(self, dialogue_label: DialogueLabel, self_address: Address, role: Dialogue.Role, message_class: Type[OefSearchMessage]=OefSearchMessage) -> None: Dialogue.__init__(self, dialogue_label=dialogue_label, message_class=message_class, self_address=self_address, role=role)
class TestDialogues(SimpleDataRequestTestCase): def setup(cls): super().setup() cls. = cast(HttpDialogues, cls._skill.skill_context. def test_ 'Test the HttpDialogues class.' (_, dialogue) = self. performative=HttpMessage.Performative.REQUEST, method='some_method', url='some_url', version='some_version', headers='some_headers', body=b'some_body') assert (dialogue.role == HttpDialogue.Role.CLIENT) assert (dialogue.self_address == str(self.skill.skill_context.skill_id))
class ESRolloutWorkerWrapper(Wrapper[Union[(StructuredEnv, LogStatsEnv)]]): def __init__(self, env: Union[(StructuredEnv, LogStatsEnv)], shared_noise: SharedNoiseTable, agent_instance_seed: int): super().__init__(env) self.shared_noise = shared_noise self.abort = False self.wrapper_rng = np.random.RandomState(agent_instance_seed) def set_abort(self): self.abort = True def clear_abort(self): self.abort = False T = TypeVar('T') def rollout(self, policy: Union[(Policy, TorchModel)]) -> None: observation = self.reset() start_time = time.time() for _ in itertools.count(): if self.abort: raise ESAbortException() with torch.no_grad(): action = policy.compute_action(observation=observation, actor_id=self.actor_id(), maze_state=(self.get_maze_state() if policy.needs_state() else None), env=(self if policy.needs_env() else None), deterministic=False) (observation, reward, done, _) = self.step(convert_to_numpy(action, cast=None, in_place=False)) if done: break self.reset() logger.debug(f'Rollout took {(time.time() - start_time):.1f} seconds') def generate_evaluation(self, policy: Union[(Policy, TorchModel)]) -> ESRolloutResult: self.rollout(policy) r = ESRolloutResult(is_eval=True) aggregator = self.get_stats(LogStatsLevel.EPISODE) r.episode_stats.append(aggregator.last_stats) return r def generate_training(self, policy: Union[(Policy, TorchModel)], noise_stddev: float) -> ESRolloutResult: r = ESRolloutResult(is_eval=False) noise_idx = self.shared_noise.sample_index(self.wrapper_rng) v = (noise_stddev * self.shared_noise.get(noise_idx, policy.num_params)) v = torch.from_numpy(v).to(policy._device) params = get_flat_parameters(policy) aggregator = self.get_stats(LogStatsLevel.EPISODE) r.noise_indices.append(noise_idx) self.seed(noise_idx) set_flat_parameters(policy, (params + v)) self.rollout(policy) r.episode_stats.append(aggregator.last_stats) self.seed(noise_idx) set_flat_parameters(policy, (params - v)) self.rollout(policy) r.episode_stats.append(aggregator.last_stats) set_flat_parameters(policy, params) return r
class Default(Plugin): def __init__(self, parser, cfg): super().__init__(parser, cfg) group = parser.add_argument_group('Azure authentication options') group.add_argument('--ad-authority', metavar='NAME', default=self.cfg('authority', type=Str, default='login.microsoftonline.com'), help='Azure AD authority host') def instantiate(self, args): return CredsViaAzureDefault(authority=args.ad_authority)
def test_vertical_alignment_enum(): r = ft.Row(vertical_alignment=ft.CrossAxisAlignment.STRETCH) assert isinstance(r.vertical_alignment, ft.CrossAxisAlignment) assert isinstance(r._get_attr('verticalAlignment'), str) cmd = r._build_add_commands() assert (cmd[0].attrs['verticalalignment'] == 'stretch')
def test_prepare_transaction_replacement_gas_price_defaulting_when_strategy_higher(w3): def higher_gas_price_strategy(w3, txn): return 20 w3.eth.set_gas_price_strategy(higher_gas_price_strategy) current_transaction = SIMPLE_CURRENT_TRANSACTION new_transaction = {'value': 2} replacement_transaction = prepare_replacement_transaction(w3, current_transaction, new_transaction) assert (replacement_transaction['gasPrice'] == 20)
class LightenerConfigFlow(config_entries.ConfigFlow, domain=DOMAIN): VERSION = 2 def __init__(self) -> None: self.lightener_flow = LightenerFlow(self, steps={'name': 'user'}) super().__init__() async def async_step_user(self, user_input: (dict[(str, Any)] | None)=None): return (await self.lightener_flow.async_step_name(user_input)) async def async_step_lights(self, user_input: (dict[(str, Any)] | None)=None) -> FlowResult: return (await self.lightener_flow.async_step_lights(user_input)) async def async_step_light_configuration(self, user_input: (dict[(str, Any)] | None)=None) -> FlowResult: return (await self.lightener_flow.async_step_light_configuration(user_input)) def async_get_options_flow(config_entry: config_entries.ConfigEntry) -> config_entries.OptionsFlow: return LightenerOptionsFlow(config_entry)
def test(): ind = GraphApi() item1 = (1, 'aaaa1') item2 = (2, 'aaaa2') item3 = (3, 'aaaa1') item4 = (4, 'aaaa2') item5 = (5, 'aaaa1') item6 = (6, 'aaaa2') item7 = (7, 'aaaa1') item8 = (8, 'aaaa2') ind.insert_link(item1, item2) ind.insert_link(item2, item3) ind.insert_link(item3, item4) ind.insert_link(item4, item5) ind.insert_link(item5, item6) ind.insert_link(item6, item7) ind.insert_link(item7, item8) ind.insert_link(item8, item1)
def create_data_format_readers(patch_reader, ffrom, to_size): dfpatch_size = unpack_size(patch_reader) if (dfpatch_size > 0): data_format = unpack_size(patch_reader) patch = patch_reader.decompress(dfpatch_size) (dfdiff, ffrom) = create_readers(data_format, ffrom, patch, to_size) ffrom.seek(0) else: dfdiff = None return (dfdiff, ffrom)
class ConfigLoader(): _config = {} _config_last_modified_time = None def _config_modified(): current_time = time.time() modified_time = os.path.getmtime(CONFIG_FILE) if (ConfigLoader._config_last_modified_time is None): ConfigLoader._config_last_modified_time = modified_time return True return (modified_time > ConfigLoader._config_last_modified_time) def load_config(): if ConfigLoader._config_modified(): with open(CONFIG_FILE, mode='r') as f: ConfigLoader._config = json.load(f) ConfigLoader._config_last_modified_time = os.path.getmtime(CONFIG_FILE) def get(*keys): ConfigLoader.load_config() try: result = reduce((lambda d, key: d[key]), keys, ConfigLoader._config) except KeyError: with open('config.json.template', 'r') as f: config_dict_template = json.load(f) result = reduce((lambda d, key: d[key]), keys, config_dict_template) return result
def optPortLongOnly(cov, mu=None): inv = np.linalg.inv(cov) ones = np.ones(shape=(inv.shape[0], 1)) if (mu is None): mu = ones w = np.dot(inv, mu) w /= np.dot(ones.T, w) w = w.flatten() threshold = (w < 0) wpluss = w.copy() wpluss[threshold] = 0 wpluss = (wpluss / np.sum(wpluss)) return wpluss
class Testing(Module): def timeTravel(self, timestamp: int) -> None: return self.w3.manager.request_blocking(RPC.testing_timeTravel, [timestamp]) def mine(self, num_blocks: int=1) -> None: return self.w3.manager.request_blocking(RPC.evm_mine, [num_blocks]) def snapshot(self) -> int: self.last_snapshot_idx = self.w3.manager.request_blocking(RPC.evm_snapshot, []) return self.last_snapshot_idx def reset(self) -> None: return self.w3.manager.request_blocking(RPC.evm_reset, []) def revert(self, snapshot_idx: Optional[int]=None) -> None: if (snapshot_idx is None): revert_target = self.last_snapshot_idx else: revert_target = snapshot_idx return self.w3.manager.request_blocking(RPC.evm_revert, [revert_target])
def envelope_from_bytes(bytes_: bytes, separator: bytes=SEPARATOR, logger: Logger=_default_logger) -> Optional[Envelope]: logger.debug('processing: {!r}'.format(bytes_)) envelope = None try: envelope = _decode(bytes_, separator=separator) except ValueError as e: logger.error('Bad formatted input: {!r}. {}'.format(bytes_, e)) except Exception as e: logger.exception('Error when processing a input. Message: {}'.format(str(e))) return envelope
def downgrade(): op.drop_index(op.f('ix_accessmanualwebhook_id'), table_name='accessmanualwebhook') op.drop_table('accessmanualwebhook') op.execute('alter type connectiontype rename to connectiontype_old') op.execute("create type connectiontype as enum('postgres', 'mongodb', 'mysql', ' 'snowflake', 'redshift', 'mssql', 'mariadb', 'bigquery', 'saas', 'manual', 'email')") op.execute('alter table connectionconfig alter column connection_type type connectiontype using connection_type::text::connectiontype') op.execute('drop type connectiontype_old') op.execute('alter type privacyrequeststatus rename to privacyrequeststatus_old') op.execute("create type privacyrequeststatus as enum('in_processing', 'complete', 'pending', 'error', 'paused', 'approved', 'denied', 'canceled', 'identity_unverified')") op.execute('alter table privacyrequest alter column status type privacyrequeststatus using status::text::privacyrequeststatus') op.execute('drop type privacyrequeststatus_old')
.django_db def test_program_activity_list_success(client, monkeypatch, agency_account_data, helpers): helpers.mock_current_fiscal_year(monkeypatch) resp = client.get(url.format(code='007', query_params='')) expected_result = {'fiscal_year': helpers.get_mocked_current_fiscal_year(), 'toptier_code': '007', 'messages': [], 'page_metadata': {'hasNext': False, 'hasPrevious': False, 'limit': 10, 'next': None, 'page': 1, 'previous': None, 'total': 4}, 'results': [{'gross_outlay_amount': 100000.0, 'name': 'NAME 3', 'obligated_amount': 100.0}, {'gross_outlay_amount': 1000000.0, 'name': 'NAME 2', 'obligated_amount': 10.0}, {'gross_outlay_amount': 1000000.0, 'name': 'NAME 5', 'obligated_amount': 10.0}, {'gross_outlay_amount': .0, 'name': 'NAME 1', 'obligated_amount': 1.0}]} assert (resp.status_code == status.HTTP_200_OK) assert (resp.json() == expected_result) query_params = '?fiscal_year=2017' resp = client.get(url.format(code='007', query_params=query_params)) expected_result = {'fiscal_year': 2017, 'toptier_code': '007', 'messages': [], 'page_metadata': {'hasNext': False, 'hasPrevious': False, 'limit': 10, 'next': None, 'page': 1, 'previous': None, 'total': 0}, 'results': []} assert (resp.status_code == status.HTTP_200_OK) assert (resp.json() == expected_result) query_params = '?fiscal_year=2016' resp = client.get(url.format(code='010', query_params=query_params)) expected_result = {'fiscal_year': 2016, 'toptier_code': '010', 'messages': ['Account data powering this endpoint were first collected in FY2017 Q2 under the DATA Act; as such, there are no data available for prior fiscal years.'], 'page_metadata': {'hasNext': False, 'hasPrevious': False, 'limit': 10, 'next': None, 'page': 1, 'previous': None, 'total': 0}, 'results': []} assert (resp.status_code == status.HTTP_200_OK) assert (resp.json() == expected_result)