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How to use path_matches_pattern method in localstack

Best Python code snippet using localstack_python

runner.py

Source:runner.py

...94        pattern = self.filename_pattern()95        matched_records = [96            record97            for record in records_for_source98            if path_matches_pattern(record["imported_file"], pattern)99        ]100        sorted_records = sorted(101            matched_records, key=lambda record: record["imported_at"]102        )103        return [record["imported_file"] for record in sorted_records]104    def input_paths(self):105        """Return list of of paths to input files for task."""106        paths = glob.glob("%s/*/*" % self.source.data_dir)107        return sorted(108            path109            for path in paths110            if path_matches_pattern(path, self.filename_pattern())111        )112    def set_last_imported_path(self, path):113        """Set the path of the most recently imported data for this source."""114        now = datetime.datetime.now().replace(microsecond=0).isoformat()115        records = load_import_records()116        records[self.source.name].append({"imported_file": path, "imported_at": now})117        dump_import_records(records)118    def unimported_paths(self):119        """Return list of of paths to input files for task that have not been120        imported."""121        imported_paths = [record for record in self.imported_paths()]122        return [path for path in self.input_paths() if path not in imported_paths]123class ManualFetchTask(Task):124    def run(self, year, month):125        print("Running manual fetch task {}".format(self.name))126        instructions = self.manual_fetch_instructions()127        print(instructions)128        paths_before = find_files(self.source.data_dir)129        input("Press return when done, or to skip this step")130        paths_after = find_files(self.source.data_dir)131        new_paths = [path for path in paths_after if path not in paths_before]132        if new_paths:133            print("The following files have been manually fetched:")134            for path in new_paths:135                print(" * {}".format(path))136        else:137            print("No new files were found at {}".format(self.source.data_dir))138        input(139            "Press return to confirm, or Ctrl+C to cancel " "and resolve any problems"140        )141    def manual_fetch_instructions(self):142        source = self.source143        expected_location = os.path.join(144            settings.PIPELINE_DATA_BASEDIR, source.name, "YYYY_MM"145        )146        output = []147        output.append("~" * 80)148        output.append(149            "You should now locate the latest data for %s, if "150            "available" % source.name151        )152        output.append("You should save it at:")153        output.append("    %s" % expected_location)154        if source.index_url:155            output.append("Where to look:")156            output.append("    %s" % source.index_url)157        if source.urls:158            output.append("Previous data has been found at:")159            for k, v in source.urls.items():160                output.append("    %s: %s" % (k, v))161        if source.publication_schedule:162            output.append("Publication frequency:")163            output.append("    %s" % source.publication_schedule)164        if source.notes:165            output.append("Notes:")166            for line in textwrap.wrap(source.notes):167                output.append("    %s" % line)168        output.append("The last imported data can be found at:")169        for task in source.tasks_that_use_raw_source_data():170            paths = task.imported_paths()171            if paths:172                path = paths[-1]173            else:174                path = "<never imported>"175            output.append("    %s" % path)176        return "\n".join(output)177class AutoFetchTask(Task):178    def run(self, year, month):179        print("Running auto fetch task {}".format(self.name))180        command = self.command.format(year=year, month=month)181        tokens = shlex.split(command)182        call_command(*tokens)183class ConvertTask(Task):184    def run(self, year, month):185        # For now, year and month are ignored186        print("Running convert task {}".format(self.name))187        unimported_paths = self.unimported_paths()188        for path in unimported_paths:189            command = self.command.replace(self.filename_pattern(), path)190            tokens = shlex.split(command)191            call_command(*tokens)192            self.set_last_imported_path(path)193class ImportTask(Task):194    def run(self, year, month):195        # For now, year and month are ignored196        print("Running import task {}".format(self.name))197        unimported_paths = self.unimported_paths()198        for path in unimported_paths:199            command = self.command.replace(self.filename_pattern(), path)200            tokens = shlex.split(command)201            call_command(*tokens)202            self.set_last_imported_path(path)203class PostProcessTask(Task):204    def run(self, year, month, last_imported):205        # For now, year and month are ignored206        command = self.command.format(last_imported=last_imported)207        tokens = shlex.split(command)208        call_command(*tokens)209class TaskCollection(object):210    task_type_to_cls = {211        "manual_fetch": ManualFetchTask,212        "manual_fetch_skip_for_now": ManualFetchTask,213        "auto_fetch": AutoFetchTask,214        "convert": ConvertTask,215        "import": ImportTask,216        "post_process": PostProcessTask,217    }218    def __init__(self, task_data=None, ordered=False, task_type=None):219        self._tasks = {}220        if isinstance(task_data, dict):221            for name, attrs in task_data.items():222                cls = self.task_type_to_cls[attrs["type"]]223                task = cls(name, attrs)224                self.add(task)225        elif isinstance(task_data, list):226            for task in task_data:227                self.add(task)228        self._ordered = ordered229        self._type = task_type230    def add(self, task):231        self._tasks[task.name] = task232    def __getitem__(self, name):233        return self._tasks[name]234    def __iter__(self):235        if self._ordered:236            graph = nx.DiGraph()237            for task in self._tasks.values():238                graph.add_node(task)239                for dependency in task.dependencies:240                    graph.add_node(dependency)241                    graph.add_edge(dependency, task)242            tasks = nx.topological_sort(graph)243        else:244            tasks = [task for _, task in sorted(self._tasks.items())]245        for task in tasks:246            if self._type is None:247                yield task248            else:249                if self._type == task.task_type:250                    yield task251    def __bool__(self):252        if self._type:253            return any(task for task in self if task.task_type == self._type)254        else:255            return bool(self._tasks)256    def by_type(self, task_type):257        return TaskCollection(list(self), ordered=self._ordered, task_type=task_type)258    def ordered(self):259        return TaskCollection(list(self), ordered=True, task_type=self._type)260def load_tasks():261    metadata_path = settings.PIPELINE_METADATA_DIR262    with open(os.path.join(metadata_path, "sources.json")) as f:263        source_data = json.load(f)264    sources = SourceCollection(source_data)265    with open(os.path.join(metadata_path, "tasks.json")) as f:266        task_data = json.load(f)267    tasks = TaskCollection(task_data)268    for task in tasks:269        if task.source_id is None:270            task.set_source(None)271        else:272            source = sources[task.source_id]273            task.set_source(source)274            source.add_task(task)275        task.resolve_dependencies(tasks)276    return tasks277def load_import_records():278    with open(settings.PIPELINE_IMPORT_LOG_PATH) as f:279        log_data = json.load(f)280    return defaultdict(list, log_data)281def dump_import_records(records):282    with open(settings.PIPELINE_IMPORT_LOG_PATH, "w") as f:283        json.dump(records, f, indent=2, separators=(",", ": "))284def upload_all_to_storage(tasks):285    for task in tasks.by_type("convert"):286        upload_task_input_files(task)287    for task in tasks.by_type("import"):288        upload_task_input_files(task)289def upload_task_input_files(task):290    storage_client = StorageClient()291    bucket = storage_client.get_bucket()292    for path in task.input_paths():293        assert path[0] == "/"294        assert settings.PIPELINE_DATA_BASEDIR[-1] == "/"295        name = "hscic" + path.replace(settings.PIPELINE_DATA_BASEDIR, "/")296        blob = bucket.blob(name)297        if blob.exists():298            print("Skipping %s, already uploaded" % name)299            continue300        print("Uploading %s to %s" % (path, name))301        with open(path, "rb") as f:302            blob.upload_from_file(f)303def path_matches_pattern(path, pattern):304    return fnmatch.fnmatch(os.path.basename(path), pattern)305def call_command(*args):306    print("call_command {}".format(args))307    return django_call_command(*args)308def run_task(task, year, month, **kwargs):309    if TaskLog.objects.filter(310        year=year, month=month, task_name=task.name, status=TaskLog.SUCCESSFUL311    ).exists():312        # This task has already been run successfully313        return314    task_log = TaskLog.objects.create(year=year, month=month, task_name=task.name)315    try:316        task.run(year, month, **kwargs)317        task_log.mark_succeeded()...

helpers.py

Source:helpers.py

...185        # check if we have an exact match186        for match in matches:187            if match[0] == path:188                return match189            if path_matches_pattern(path, match[0]):190                return match191        raise Exception('Ambiguous API path %s - matches found: %s' % (path, matches))192    return matches[0]193def path_matches_pattern(path, api_path):194    api_paths = api_path.split('/')195    paths = path.split('/')196    reg_check = re.compile(r'\{(.*)\}')197    results = []198    if len(api_paths) != len(paths):199        return False200    for indx, part in enumerate(api_paths):201        if reg_check.match(part) is None and part:202            results.append(part == paths[indx])203    return len(results) > 0 and all(results)204def connect_api_gateway_to_sqs(gateway_name, stage_name, queue_arn, path, region_name=None):205    resources = {}206    template = APIGATEWAY_SQS_DATA_INBOUND_TEMPLATE207    resource_path = path.replace('/', '')...

tools.py

Source:tools.py

...157TRAILING_DOUBLE_STAR_RE = re.compile(r'\/\.\*\.\*$')158TRAILING_DOUBLE_STAR_REPL = r'/.+'159# no / matches basename160NO_SLASH_RE = r'(.*/)?'161def path_matches_pattern(path: str, pattern: str) -> bool:162    """Return True if path matches the LFS filter pattern.163    See gitignore and gitattributes documentation for more on this.164    """165    # gitignore documentation to the contrary notwithstanding, a pattern ending166    # with '/' matches nothing when used for gitattributes.167    if pattern.endswith('/'):  # directory pattern168        return False169    # Git documentation quoted here:170    #171    # Git treats the pattern as a shell glob suitable for consumption by172    # fnmatch(3) with the FNM_PATHNAME flag: wildcards in the pattern will not173    # match a / in the pathname.174    #175    # However, Python's fnmatch does not support FNM_PATHNAME, so use fnmatch to...

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