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n = 0 for i, c in enumerate(namespace): n += (_LEX_DISTANCE[MAX_NAMESPACE_LENGTH - i- 1] * NAMESPACE_CHARACTERS.index(c) + 1) return n
def _namespace_to_ord(namespace)
Converts a namespace string into an int representing its lexographic order. >>> _namespace_to_ord('') '' >>> _namespace_to_ord('_') 1 >>> _namespace_to_ord('__') 2 Args: namespace: A namespace string. Returns: An int representing the lexographical order of the given namespace string.
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if namespace: return db.Key.from_path(metadata.Namespace.KIND_NAME, namespace, _app=app) else: return db.Key.from_path(metadata.Namespace.KIND_NAME, metadata.Namespace.EMPTY_NAMESPACE_ID, _app=...
def _key_for_namespace(namespace, app)
Return the __namespace__ key for a namespace. Args: namespace: The namespace whose key is requested. app: The id of the application that the key belongs to. Returns: A db.Key representing the namespace.
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ns_query = datastore.Query('__namespace__', keys_only=True, _app=app) return list(ns_query.Run(limit=limit, batch_size=limit))
def get_namespace_keys(app, limit)
Get namespace keys.
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if self.is_single_namespace: return [self] mid_point = (_namespace_to_ord(self.namespace_start) + _namespace_to_ord(self.namespace_end)) // 2 return [NamespaceRange(self.namespace_start, _ord_to_namespace(mid_point), _app=se...
def split_range(self)
Splits the NamespaceRange into two nearly equal-sized ranges. Returns: If this NamespaceRange contains a single namespace then a list containing this NamespaceRange is returned. Otherwise a two-element list containing two NamespaceRanges whose total range is identical to this NamespaceRange...
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namespace_start = _ord_to_namespace(_namespace_to_ord(after_namespace) + 1) return NamespaceRange(namespace_start, self.namespace_end, _app=self.app)
def with_start_after(self, after_namespace)
Returns a copy of this NamespaceName with a new namespace_start. Args: after_namespace: A namespace string. Returns: A NamespaceRange object whose namespace_start is the lexographically next namespace after the given namespace string. Raises: ValueError: if the NamespaceRange incl...
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filters = {} filters['__key__ >= '] = _key_for_namespace( self.namespace_start, self.app) filters['__key__ <= '] = _key_for_namespace( self.namespace_end, self.app) return datastore.Query('__namespace__', filters=filters, keys_o...
def make_datastore_query(self, cursor=None)
Returns a datastore.Query that generates all namespaces in the range. Args: cursor: start cursor for the query. Returns: A datastore.Query instance that generates db.Keys for each namespace in the NamespaceRange.
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namespaces_after_key = list(self.make_datastore_query().Run(limit=1)) if not namespaces_after_key: return None namespace_after_key = namespaces_after_key[0].name() or '' return NamespaceRange(namespace_after_key, self.namespace_end, _app=s...
def normalized_start(self)
Returns a NamespaceRange with leading non-existant namespaces removed. Returns: A copy of this NamespaceRange whose namespace_start is adjusted to exclude the portion of the range that contains no actual namespaces in the datastore. None is returned if the NamespaceRange contains no actual ...
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obj_dict = dict(namespace_start=self.namespace_start, namespace_end=self.namespace_end) if self.app is not None: obj_dict['app'] = self.app return obj_dict
def to_json_object(self)
Returns a dict representation that can be serialized to JSON.
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# pylint: disable=g-doc-args if n < 1: raise ValueError('n must be >= 1') ranges = None if can_query(): if not contiguous: ns_keys = get_namespace_keys(_app, n + 1) if not ns_keys: return [] else: if len(ns_keys) <= n: # If you ha...
def split(cls, n, contiguous, can_query=itertools.chain(itertools.repeat(True, 50), itertools.repeat(False)).next, _app=None)
Splits the complete NamespaceRange into n equally-sized NamespaceRanges. Args: n: The maximum number of NamespaceRanges to return. Fewer than n namespaces may be returned. contiguous: If True then the returned NamespaceRanges will cover the entire space of possible namespaces (i.e. ...
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data_length = len(data) if self._size + data_length > self._flush_size: self.flush() if not self._exclusive and data_length > _FILE_POOL_MAX_SIZE: raise errors.Error( "Too big input %s (%s)." % (data_length, _FILE_POOL_MAX_SIZE)) else: self._buffer.append(data) s...
def append(self, data)
Append data to a file.
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# Write data to in-memory buffer first. buf = cStringIO.StringIO() with records.RecordsWriter(buf) as w: for record in self._buffer: w.write(record) w._pad_block() str_buf = buf.getvalue() buf.close() if not self._exclusive and len(str_buf) > _FILE_POOL_MAX_SIZE: ...
def flush(self)
Flush pool contents.
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self._filehandle.write(str_buf) self._buf_size += len(str_buf)
def _write(self, str_buf)
Uses the filehandle to the file in GCS to write to it.
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super(GCSRecordsPool, self).flush() if force: extra_padding = self._buf_size % self._GCS_BLOCK_SIZE if extra_padding > 0: self._write("\x00" * (self._GCS_BLOCK_SIZE - extra_padding)) self._filehandle.flush()
def flush(self, force=False)
Flush pool contents. Args: force: Inserts additional padding to achieve the minimum block size required for GCS.
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if cls.TMP_BUCKET_NAME_PARAM in writer_spec: return writer_spec[cls.TMP_BUCKET_NAME_PARAM] return cls._get_gcs_bucket(writer_spec)
def _get_tmp_gcs_bucket(cls, writer_spec)
Returns bucket used for writing tmp files.
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# pick tmp id iff tmp bucket is set explicitly if cls.TMP_BUCKET_NAME_PARAM in writer_spec: return writer_spec.get(cls._TMP_ACCOUNT_ID_PARAM, None) return cls._get_account_id(writer_spec)
def _get_tmp_account_id(cls, writer_spec)
Returns the account id to use with tmp bucket.
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naming_format = cls._TMP_FILE_NAMING_FORMAT if seg_index is None: naming_format = writer_spec.get(cls.NAMING_FORMAT_PARAM, cls._DEFAULT_NAMING_FORMAT) template = string.Template(naming_format) try: # Check that template doesn't use undefined mappin...
def _generate_filename(cls, writer_spec, name, job_id, num, attempt=None, seg_index=None)
Generates a filename for a particular output. Args: writer_spec: specification dictionary for the output writer. name: name of the job. job_id: the ID number assigned to the job. num: shard number. attempt: the shard attempt number. seg_index: index of the seg. None means the fi...
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writer_spec = cls.get_params(mapper_spec, allow_old=False) # Bucket Name is required if cls.BUCKET_NAME_PARAM not in writer_spec: raise errors.BadWriterParamsError( "%s is required for Google Cloud Storage" % cls.BUCKET_NAME_PARAM) try: cloudstorage.validate_bucket_...
def validate(cls, mapper_spec)
Validate mapper specification. Args: mapper_spec: an instance of model.MapperSpec. Raises: BadWriterParamsError: if the specification is invalid for any reason such as missing the bucket name or providing an invalid bucket name.
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if use_tmp_bucket: bucket = cls._get_tmp_gcs_bucket(writer_spec) account_id = cls._get_tmp_account_id(writer_spec) else: bucket = cls._get_gcs_bucket(writer_spec) account_id = cls._get_account_id(writer_spec) # GoogleCloudStorage format for filenames, Initial slash is required ...
def _open_file(cls, writer_spec, filename_suffix, use_tmp_bucket=False)
Opens a new gcs file for writing.
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start_time = time.time() self._get_write_buffer().write(data) ctx = context.get() operation.counters.Increment(COUNTER_IO_WRITE_BYTES, len(data))(ctx) operation.counters.Increment( COUNTER_IO_WRITE_MSEC, int((time.time() - start_time) * 1000))(ctx)
def write(self, data)
Write data to the GoogleCloudStorage file. Args: data: string containing the data to be written.
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writer_spec = cls.get_params(mapper_spec, allow_old=False) if writer_spec.get(cls._NO_DUPLICATE, False) not in (True, False): raise errors.BadWriterParamsError("No duplicate must a boolean.") super(_GoogleCloudStorageOutputWriter, cls).validate(mapper_spec)
def validate(cls, mapper_spec)
Inherit docs.
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writer_spec = cls.get_params(mr_spec.mapper, allow_old=False) seg_index = None if writer_spec.get(cls._NO_DUPLICATE, False): seg_index = 0 # Determine parameters key = cls._generate_filename(writer_spec, mr_spec.name, mr_spec.mapreduce_id, ...
def create(cls, mr_spec, shard_number, shard_attempt, _writer_state=None)
Inherit docs.
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writer = cls._open_file(writer_spec, filename_suffix) return cls(writer, writer_spec=writer_spec)
def _create(cls, writer_spec, filename_suffix)
Helper method that actually creates the file in cloud storage.
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writer_spec = cls.get_params(mr_spec.mapper, allow_old=False) # Determine parameters key = cls._generate_filename(writer_spec, mr_spec.name, mr_spec.mapreduce_id, shard_number, shard_attempt) status = _ConsistentStatus() status...
def create(cls, mr_spec, shard_number, shard_attempt, _writer_state=None)
Inherit docs.
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if mainfile.closed: # can happen when finalize fails return account_id = self._get_tmp_account_id(writer_spec) f = cloudstorage_api.open(tmpfile, _account_id=account_id) # both reads and writes are buffered - the number here doesn't matter data = f.read(self._REWRITE_BLOCK_SIZE) ...
def _rewrite_tmpfile(self, mainfile, tmpfile, writer_spec)
Copies contents of tmpfile (name) to mainfile (buffer).
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# We can't put the tmpfile in the same directory as the output. There are # rare circumstances when we leave trash behind and we don't want this trash # to be loaded into bigquery and/or used for restore. # # We used mapreduce id, shard number and attempt and 128 random bits to make # coll...
def _create_tmpfile(cls, status)
Creates a new random-named tmpfile.
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# Try to remove garbage (if any). Note that listbucket is not strongly # consistent so something might survive. tmpl = string.Template(self._TMPFILE_PREFIX) prefix = tmpl.substitute( id=self.status.mapreduce_id, shard=self.status.shard) bucket = self._get_tmp_gcs_bucket(writer_spec) ...
def _try_to_clean_garbage(self, writer_spec, exclude_list=())
Tries to remove any files created by this shard that aren't needed. Args: writer_spec: writer_spec for the MR. exclude_list: A list of filenames (strings) that should not be removed.
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return cls(state[cls.COUNT], state[cls.STRING_LENGTH])
def from_json(cls, state)
Inherit docs.
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params = job_config.input_reader_params count = params[cls.COUNT] string_length = params.get(cls.STRING_LENGTH, cls._DEFAULT_STRING_LENGTH) shard_count = job_config.shard_count count_per_shard = count // shard_count mr_input_readers = [ cls(count_per_shard, string_length) for _ in...
def split_input(cls, job_config)
Inherit docs.
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super(SampleInputReader, cls).validate(job_config) params = job_config.input_reader_params # Validate count. if cls.COUNT not in params: raise errors.BadReaderParamsError("Must specify %s" % cls.COUNT) if not isinstance(params[cls.COUNT], int): raise errors.BadReaderParamsError("%s...
def validate(cls, job_config)
Inherit docs.
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weights = [1] for i in range(1, max_length): weights.append(weights[i-1] * len(_ALPHABET) + 1) weights.reverse() return weights
def _get_weights(max_length)
Get weights for each offset in str of certain max length. Args: max_length: max length of the strings. Returns: A list of ints as weights. Example: If max_length is 2 and alphabet is "ab", then we have order "", "a", "aa", "ab", "b", "ba", "bb". So the weight for the first char is 3.
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ordinal = 0 for i, c in enumerate(content): ordinal += weights[i] * _ALPHABET.index(c) + 1 return ordinal
def _str_to_ord(content, weights)
Converts a string to its lexicographical order. Args: content: the string to convert. Of type str. weights: weights from _get_weights. Returns: an int or long that represents the order of this string. "" has order 0.
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chars = [] for weight in weights: if ordinal == 0: return "".join(chars) ordinal -= 1 index, ordinal = divmod(ordinal, weight) chars.append(_ALPHABET[index]) return "".join(chars)
def _ord_to_str(ordinal, weights)
Reverse function of _str_to_ord.
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if not filters: return None, None, None range_property = None start_val = None end_val = None start_filter = None end_filter = None for f in filters: prop, op, val = f if op in [">", ">=", "<", "<="]: if range_property and range_property != prop: ra...
def _get_range_from_filters(cls, filters, model_class)
Get property range from filters user provided. This method also validates there is one and only one closed range on a single property. Args: filters: user supplied filters. Each filter should be a list or tuple of format (<property_name_as_str>, <query_operator_as_str>, <value_of_cer...
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new_range_filters = [] name = self.start[0] prop_cls = self.prop.__class__ if prop_cls in _DISCRETE_PROPERTY_SPLIT_FUNCTIONS: splitpoints = _DISCRETE_PROPERTY_SPLIT_FUNCTIONS[prop_cls]( self.start[2], self.end[2], n, self.start[1] == ">=", self.end[1] == "<=") start_...
def split(self, n)
Evenly split this range into contiguous, non overlapping subranges. Args: n: number of splits. Returns: a list of contiguous, non overlapping sub PropertyRanges. Maybe less than n when not enough subranges.
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if issubclass(self.model_class, db.Model): query = db.Query(self.model_class, namespace=ns) for f in self.filters: query.filter("%s %s" % (f[0], f[1]), f[2]) else: query = self.model_class.query(namespace=ns) for f in self.filters: query = query.filter(ndb.FilterNode...
def make_query(self, ns)
Make a query of entities within this range. Query options are not supported. They should be specified when the query is run. Args: ns: namespace of this query. Returns: a db.Query or ndb.Query, depends on the model class's type.
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if job_config.output_writer_cls != cls: raise errors.BadWriterParamsError( "Expect output writer class %r, got %r." % (cls, job_config.output_writer_cls))
def validate(cls, job_config)
Validates relevant parameters. This method can validate fields which it deems relevant. Args: job_config: an instance of map_job.JobConfig. Raises: errors.BadWriterParamsError: required parameters are missing or invalid.
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# We accept an iterator just in case output references get too big. outs = tuple(iterator) shard_ctx._state.writer_state["outs"] = outs
def commit_output(cls, shard_ctx, iterator)
Saves output references when a shard finishes. Inside end_shard(), an output writer can optionally use this method to persist some references to the outputs from this shard (e.g a list of filenames) Args: shard_ctx: map_job_context.ShardContext for this shard. iterator: an iterator that yi...
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pipeline_handlers_map = [] if pipeline: pipeline_handlers_map = pipeline.create_handlers_map(prefix=".*/pipeline") return pipeline_handlers_map + [ # Task queue handlers. # Always suffix by mapreduce_id or shard_id for log analysis purposes. # mapreduce_id or shard_id also presents in h...
def create_handlers_map()
Create new handlers map. Returns: list of (regexp, handler) pairs for WSGIApplication constructor.
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if json["name"] in _KEYRANGES_CLASSES: return _KEYRANGES_CLASSES[json["name"]].from_json(json) raise ValueError("Invalid json %s", json)
def from_json(cls, json)
Deserialize from json. Args: json: a dict of json compatible fields. Returns: a KeyRanges object. Raises: ValueError: if the json is invalid.
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s = re.sub(r"\s+", " ", s) s = re.sub(r"[\\.\\?\\!]", "\n", s) return s.split("\n")
def split_into_sentences(s)
Split text into list of sentences.
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s = re.sub(r"\W+", " ", s) s = re.sub(r"[_0-9]+", " ", s) return s.split()
def split_into_words(s)
Split a sentence into list of words.
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(entry, text_fn) = data text = text_fn() logging.debug("Got %s", entry.filename) for s in split_into_sentences(text): for w in split_into_words(s.lower()): yield (w, entry.filename)
def index_map(data)
Index demo map function.
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(entry, text_fn) = data text = text_fn() filename = entry.filename logging.debug("Got %s", filename) for s in split_into_sentences(text): words = split_into_words(s.lower()) if len(words) < PHRASE_LENGTH: yield (":".join(words), filename) continue for i in range(0, len(words) - PHR...
def phrases_map(data)
Phrases demo map function.
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if len(values) < 10: return counts = {} for filename in values: counts[filename] = counts.get(filename, 0) + 1 words = re.sub(r":", " ", key) threshold = len(values) / 2 for filename, count in counts.items(): if count > threshold: yield "%s:%s\n" % (words, filename)
def phrases_reduce(key, values)
Phrases demo reduce function.
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sep = FileMetadata.__SEP return str(username + sep + str(date) + sep + blob_key)
def getKeyName(username, date, blob_key)
Returns the internal key for a particular item in the database. Our items are stored with keys of the form 'user/date/blob_key' ('/' is not the real separator, but __SEP is). Args: username: The given user's e-mail address. date: A datetime object representing the date and time that an input ...
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dec = MontyDecoder() def load_class(dotpath): modname, classname = dotpath.rsplit(".", 1) mod = __import__(modname, globals(), locals(), [classname], 0) return getattr(mod, classname) def process_params(d): decoded = {} for ...
def from_spec(cls, spec)
Load a Custodian instance where the jobs are specified from a structure and a spec dict. This allows simple custom job sequences to be constructed quickly via a YAML file. Args: spec (dict): A dict specifying job. A sample of the dict in YAML format for the usual MP ...
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cwd = os.getcwd() with ScratchDir(self.scratch_dir, create_symbolic_link=True, copy_to_current_on_exit=True, copy_from_current_on_enter=True) as temp_dir: self.total_errors = 0 start = datetime.datetime.now() l...
def run(self)
Runs all jobs. Returns: All errors encountered as a list of list. [[error_dicts for job 1], [error_dicts for job 2], ....] Raises: ValidationError: if a job fails validation ReturnCodeError: if the process has a return code different from 0 N...
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corrections = [] for h in handlers: try: if h.check(): if h.max_num_corrections is not None \ and h.n_applied_corrections >= h.max_num_corrections: msg = "Maximum number of corrections {} reached...
def _do_check(self, handlers, terminate_func=None)
checks the specified handlers. Returns True iff errors caught
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modified = [] for a in actions: if "dict" in a: k = a["dict"] modified.append(k) self.feffinp[k] = self.modify_object(a["action"], self.feffinp[k]) elif "file" in a: self.modify(a["action"], a["file"]) ...
def apply_actions(self, actions)
Applies a list of actions to the FEFF Input Set and rewrites modified files. Args: actions [dict]: A list of actions of the form {'file': filename, 'action': moddermodification} or {'dict': feffinput_key, 'action': moddermodification}
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if len(settings) != 1: raise ValueError("Settings must only contain one item with key " "'content'.") for k, v in settings.items(): if k == "content": with open(filename, 'w') as f: f.write(v)
def file_create(filename, settings)
Creates a file. Args: filename (str): Filename. settings (dict): Must be {"content": actual_content}
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if len(settings) != 1: raise ValueError("Settings must only contain one item with key " "'dest'.") for k, v in settings.items(): if k == "dest": shutil.move(filename, v)
def file_move(filename, settings)
Moves a file. {'_file_move': {'dest': 'new_file_name'}} Args: filename (str): Filename. settings (dict): Must be {"dest": path of new file}
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if len(settings) != 1: raise ValueError("Settings must only contain one item with key " "'mode'.") for k, v in settings.items(): if k == "mode" and v == "actual": try: os.remove(filename) ex...
def file_delete(filename, settings)
Deletes a file. {'_file_delete': {'mode': "actual"}} Args: filename (str): Filename. settings (dict): Must be {"mode": actual/simulated}. Simulated mode only prints the action without performing it.
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for k, v in settings.items(): if k.startswith("dest"): shutil.copyfile(filename, v)
def file_copy(filename, settings)
Copies a file. {'_file_copy': {'dest': 'new_file_name'}} Args: filename (str): Filename. settings (dict): Must be {"dest": path of new file}
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for k, v in settings.items(): if k == "mode": os.chmod(filename,v) if k == "owners": os.chown(filename,v)
def file_modify(filename, settings)
Modifies file access Args: filename (str): Filename. settings (dict): Can be "mode" or "owners"
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decompress_dir('.') if self.backup: for f in FEFF_INPUT_FILES: shutil.copy(f, "{}.orig".format(f)) for f in FEFF_BACKUP_FILES: if os.path.isfile(f): shutil.copy(f, "{}.orig".format(f))
def setup(self)
Performs initial setup for FeffJob, do backing up. Returns:
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with open(self.output_file, "w") as f_std, \ open(self.stderr_file, "w", buffering=1) as f_err: # Use line buffering for stderr # On TSCC, need to run shell command p = subprocess.Popen(self.feff_cmd, stdout=f_std, stderr=f_err, shell=True) ...
def run(self)
Performs the actual FEFF run Returns: (subprocess.Popen) Used for monitoring.
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for action, settings in modification.items(): if action in self.supported_actions: self.supported_actions[action].__call__(obj, settings) elif self.strict: raise ValueError("{} is not a supported action!" .format(a...
def modify(self, modification, obj)
Note that modify makes actual in-place modifications. It does not return a copy. Args: modification (dict): Modification must be {action_keyword : settings}. E.g., {'_set': {'Hello':'Universe', 'Bye': 'World'}} obj (dict/str/object): Object to modify depending on...
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d = obj.as_dict() self.modify(modification, d) return obj.from_dict(d)
def modify_object(self, modification, obj)
Modify an object that supports pymatgen's as_dict() and from_dict API. Args: modification (dict): Modification must be {action_keyword : settings}. E.g., {'_set': {'Hello':'Universe', 'Bye': 'World'}} obj (object): Object to modify
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modified = [] for a in actions: if "dict" in a: k = a["dict"] modified.append(k) self.vi[k] = self.modify_object(a["action"], self.vi[k]) elif "file" in a: self.modify(a["action"], a["file"]) els...
def apply_actions(self, actions)
Applies a list of actions to the Vasp Input Set and rewrites modified files. Args: actions [dict]: A list of actions of the form {'file': filename, 'action': moddermodification} or {'dict': vaspinput_key, 'action': moddermodification}
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num = max([0] + [int(f.split(".")[1]) for f in glob("{}.*.tar.gz".format(prefix))]) filename = "{}.{}.tar.gz".format(prefix, num + 1) logging.info("Backing up run to {}.".format(filename)) with tarfile.open(filename, "w:gz") as tar: for fname in filenames: f...
def backup(filenames, prefix="error")
Backup files to a tar.gz file. Used, for example, in backing up the files of an errored run before performing corrections. Args: filenames ([str]): List of files to backup. Supports wildcards, e.g., *.*. prefix (str): prefix to the files. Defaults to error, which means a ...
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2.96482
0.968508
host = os.environ.get('HOSTNAME', None) cluster = os.environ.get('SGE_O_HOST', None) if host is None: try: import socket host = host or socket.gethostname() except: pass return host or 'unknown', cluster or 'unknown'
def get_execution_host_info()
Tries to return a tuple describing the execution host. Doesn't work for all queueing systems Returns: (HOSTNAME, CLUSTER_NAME)
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qclog = open(self.qclog_file, 'w') p = subprocess.Popen(self.current_command, stdout=qclog) return p
def run(self)
Perform the actual QChem run. Returns: (subprocess.Popen) Used for monitoring.
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decompress_dir('.') if self.backup: for f in VASP_INPUT_FILES: shutil.copy(f, "{}.orig".format(f)) if self.auto_npar: try: incar = Incar.from_file("INCAR") # Only optimized NPAR for non-HF and non-RPA calculations...
def setup(self)
Performs initial setup for VaspJob, including overriding any settings and backing up.
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cmd = list(self.vasp_cmd) if self.auto_gamma: vi = VaspInput.from_directory(".") kpts = vi["KPOINTS"] if kpts.style == Kpoints.supported_modes.Gamma \ and tuple(kpts.kpts[0]) == (1, 1, 1): if self.gamma_vasp_cmd is not None...
def run(self)
Perform the actual VASP run. Returns: (subprocess.Popen) Used for monitoring.
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for f in VASP_OUTPUT_FILES + [self.output_file]: if os.path.exists(f): if self.final and self.suffix != "": shutil.move(f, "{}{}".format(f, self.suffix)) elif self.suffix != "": shutil.copy(f, "{}{}".format(f, self.suff...
def postprocess(self)
Postprocessing includes renaming and gzipping where necessary. Also copies the magmom to the incar if necessary
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1.089281
incar_update = {"ISTART": 1} if ediffg: incar_update["EDIFFG"] = ediffg settings_overide_1 = None settings_overide_2 = [ {"dict": "INCAR", "action": {"_set": incar_update}}, {"file": "CONTCAR", "action": {"_file_copy"...
def double_relaxation_run(cls, vasp_cmd, auto_npar=True, ediffg=-0.05, half_kpts_first_relax=False, auto_continue=False)
Returns a list of two jobs corresponding to an AFLOW style double relaxation run. Args: vasp_cmd (str): Command to run vasp as a list of args. For example, if you are using mpirun, it can be something like ["mpirun", "pvasp.5.2.11"] auto_npar (boo...
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0.986558
incar = Incar.from_file("INCAR") # Defaults to using the SCAN metaGGA metaGGA = incar.get("METAGGA", "SCAN") # Pre optimze WAVECAR and structure using regular GGA pre_opt_setings = [{"dict": "INCAR", "action": {"_set": {"METAGGA": None, ...
def metagga_opt_run(cls, vasp_cmd, auto_npar=True, ediffg=-0.05, half_kpts_first_relax=False, auto_continue=False)
Returns a list of thres jobs to perform an optimization for any metaGGA functional. There is an initial calculation of the GGA wavefunction which is fed into the initial metaGGA optimization to precondition the electronic structure optimizer. The metaGGA optimization is performed using t...
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for i in range(max_steps): if i == 0: settings = None backup = True if half_kpts_first_relax and os.path.exists("KPOINTS") and \ os.path.exists("POSCAR"): kpts = Kpoints.from_file("KPOINTS") ...
def full_opt_run(cls, vasp_cmd, vol_change_tol=0.02, max_steps=10, ediffg=-0.05, half_kpts_first_relax=False, **vasp_job_kwargs)
Returns a generator of jobs for a full optimization run. Basically, this runs an infinite series of geometry optimization jobs until the % vol change in a particular optimization is less than vol_change_tol. Args: vasp_cmd (str): Command to run vasp as a list of args. For example, ...
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2.720504
1.031658
neb_dirs = self.neb_dirs if self.backup: # Back up KPOINTS, INCAR, POTCAR for f in VASP_NEB_INPUT_FILES: shutil.copy(f, "{}.orig".format(f)) # Back up POSCARs for path in neb_dirs: poscar = os.path.join(path, "POSC...
def setup(self)
Performs initial setup for VaspNEBJob, including overriding any settings and backing up.
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3.046184
1.038227
# Add suffix to all sub_dir/{items} for path in self.neb_dirs: for f in VASP_NEB_OUTPUT_SUB_FILES: f = os.path.join(path, f) if os.path.exists(f): if self.final and self.suffix != "": shutil.move(f, "{}{}".f...
def postprocess(self)
Postprocessing includes renaming and gzipping where necessary.
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1.052663
if self.backup: shutil.copy(self.input_file, "{}.orig".format(self.input_file))
def setup(self)
Performs backup if necessary.
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1.399454
with zopen(self.output_file, 'w') as fout: return subprocess.Popen(self.nwchem_cmd + [self.input_file], stdout=fout)
def run(self)
Performs actual nwchem run.
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x = float(x) if x < 0.0 or x > 1.0: raise ArgumentTypeError("{} not in range [0.0, 1.0]".format(x)) return x
def valid_GC(x)
type function for argparse to check GC values. Check if the supplied value for minGC and maxGC is a valid input, being between 0 and 1
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2.483165
1.031595
if args.quality: quality_check = ave_qual else: quality_check = silent_quality_check minlen = args.length + int(args.headcrop or 0) - (int(args.tailcrop or 0)) for rec in SeqIO.parse(fq, "fastq"): if args.GC_filter: gc = (rec.seq.upper().count("C") + rec.seq.uppe...
def filter_stream(fq, args)
Filter a fastq file on stdin. Print fastq record to stdout if it passes - quality filter (optional) - length filter (optional) - min/maxGC filter (optional) Optionally trim a number of nucleotides from beginning and end. Record has to be longer than args.length (default 1) after trimming Us...
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1.171012
data = {entry[0]: entry[1] for entry in process_summary( summaryfile=args.summary, threads="NA", readtype=args.readtype, barcoded=False)[ ["readIDs", "quals"]].itertuples(index=False)} try: for record in SeqIO.parse(fq, "fastq"): if data[record.id...
def filter_using_summary(fq, args)
Use quality scores from albacore summary file for filtering Use the summary file from albacore for more accurate quality estimate Get the dataframe from nanoget, convert to dictionary
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'''decorator describing methods that require the master key''' def ret(obj, *args, **kw): conn = ACCESS_KEYS if not (conn and conn.get('master_key')): message = '%s requires the master key' % func.__name__ raise core.ParseError(message) func(obj, *args, **kw) ...
def master_key_required(func)
decorator describing methods that require the master key
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1.102266
if batch: urlsplitter = urlparse(API_ROOT).netloc ret = {"method": http_verb, "path": uri.split(urlsplitter, 1)[1]} if kw: ret["body"] = kw return ret if not ('app_id' in ACCESS_KEYS and 'rest_key' in ACCESS_KEYS): rai...
def execute(cls, uri, http_verb, extra_headers=None, batch=False, _body=None, **kw)
if batch == False, execute a command with the given parameters and return the response JSON. If batch == True, return the dictionary that would be used in a batch command.
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methods = list(methods) # methods can be iterator if not methods: #accepts also empty list (or generator) - it allows call batch directly with query result (eventually empty) return queries, callbacks = list(zip(*[m(batch=True) for m in methods])) # perfo...
def batch(self, methods)
Given a list of create, update or delete methods to call, call all of them in a single batch operation.
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installation_url = cls._get_installation_url(installation_id) current_config = cls.GET(installation_url) new_channels = list(set(current_config['channels']).union(channels_to_add).difference(channels_to_remove)) cls.PUT(installation_url, channels=new_channels)
def update_channels(cls, installation_id, channels_to_add=set(), channels_to_remove=set(), **kw)
Allow an application to manually subscribe or unsubscribe an installation to a certain push channel in a unified operation. this is based on: https://www.parse.com/docs/rest#installations-updating installation_id: the installation id you'd like to add a channel to channels_to_a...
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3.096701
0.93126
if self._result_cache is not None: return len(self._result_cache) if count else self._result_cache options = dict(self._options) # make a local copy if self._where: # JSON encode WHERE values options['where'] = json.dumps(self._where) if self...
def _fetch(self, count=False)
Return a list of objects matching query, or if count == True return only the number of objects matching.
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'''Decorator for registering complex types''' def wrapped(cls): ParseType.type_mapping[name or cls.__name__] = cls return cls return wrapped
def complex_type(name=None)
Decorator for registering complex types
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class_name = str(class_name.lstrip('_')) types = ParseResource.__subclasses__() while types: t = types.pop() if t.__name__ == class_name: return t types.extend(t.__subclasses__()) else: return type(class_name, (Obje...
def factory(cls, class_name)
find proper Object subclass matching class_name system types like _User are mapped to types without underscore (parse_resr.user.User) If user don't declare matching type, class is created on the fly
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root = '/'.join([API_ROOT, 'schemas', cls.__name__]) schema = cls.GET(root) return schema
def schema(cls)
Retrieves the class' schema.
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root = '/'.join([API_ROOT, 'schemas', cls.__name__]) payload = { 'className': cls.__name__, 'fields': { key: { '__op': 'Delete' } } } cls.PUT(root, **payload)
def schema_delete_field(cls, key)
Deletes a field.
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payload = { key: { '__op': 'Increment', 'amount': amount } } self.__class__.PUT(self._absolute_url, **payload) self.__dict__[key] += amount
def increment(self, key, amount=1)
Increment one value in the object. Note that this happens immediately: it does not wait for save() to be called
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payload = { key: { '__op': 'Delete' } } self.__class__.PUT(self._absolute_url, **payload) del self.__dict__[key]
def remove(self, key)
Clear a column value in the object. Note that this happens immediately: it does not wait for save() to be called.
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'''decorator describing User methods that need to be logged in''' def ret(obj, *args, **kw): if not hasattr(obj, 'sessionToken'): message = '%s requires a logged-in session' % func.__name__ raise ResourceRequestLoginRequired(message) return func(obj, *args, **kw) retu...
def login_required(func)
decorator describing User methods that need to be logged in
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'''Trigger Parse\'s Password Process. Return True/False indicate success/failure on the request''' url = '/'.join([API_ROOT, 'requestPasswordReset']) try: User.POST(url, email=email) return True except ParseError: return False
def request_password_reset(email)
Trigger Parse\'s Password Process. Return True/False indicate success/failure on the request
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res = {} for k, v in iteritems(d): if isinstance(v, string_types) and DATETIME_ISO_FORMAT.match(v): v = dateutil.parser.parse(v) res[k] = v return res
def parse(d)
Convert iso formatted timestamps found as values in the dict d to datetime objects. :return: A shallow copy of d with converted timestamps.
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open_kw = {'mode': 'w'} if PY3: # pragma: no cover open_kw['encoding'] = 'utf-8' # avoid indented lines ending with ", " on PY2 if kw.get('indent') and kw.get('separators') is None: kw['separators'] = (',', ': ') with open(str(path), **open_kw) as fp: return json.dump...
def dump(obj, path, **kw)
Python 2 + 3 compatible version of json.dump. :param obj: The object to be dumped. :param path: The path of the JSON file to be written. :param kw: Keyword parameters are passed to json.dump
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_kw = {} if PY3: # pragma: no cover _kw['encoding'] = 'utf-8' with open(str(path), **_kw) as fp: return json.load(fp, **kw)
def load(path, **kw)
python 2 + 3 compatible version of json.load. :param kw: Keyword parameters are passed to json.load :return: The python object read from path.
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res = [] for c, type_ in _tokens(text, brackets=brackets): if type_ == TextType.text: res.append(c) return ''.join(res).strip()
def strip_brackets(text, brackets=None)
Strip brackets and what is inside brackets from text. .. note:: If the text contains only one opening bracket, the rest of the text will be ignored. This is a feature, not a bug, as we want to avoid that this function raises errors too easily.
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res, chunk = [], [] for c, type_ in _tokens(text, brackets=brackets): if type_ == TextType.text and c in separators: res.append(''.join(chunk).strip()) chunk = [] else: chunk.append(c) res.append(''.join(chunk).strip()) return nfilter(res)
def split_text_with_context(text, separators=WHITESPACE, brackets=None)
Splits text at separators outside of brackets. :param text: :param separators: An iterable of single character tokens. :param brackets: :return: A `list` of non-empty chunks. .. note:: This function leaves content in brackets in the chunks.
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if not isinstance(separators, PATTERN_TYPE): separators = re.compile( '[{0}]'.format(''.join('\{0}'.format(c) for c in separators))) return nfilter( s.strip() if strip else s for s in separators.split(strip_brackets(text, brackets=brackets)))
def split_text(text, separators=re.compile('\s'), brackets=None, strip=False)
Split text along the separators unless they appear within brackets. :param separators: An iterable single characters or a compiled regex pattern. :param brackets: `dict` mapping start tokens to end tokens of what is to be \ recognized as brackets. .. note:: This function will also strip content within...
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marker = None value = [] for line in block.split('\n'): line = line.strip() if line.startswith('\\_'): continue # we simply ignore SFM header fields match = MARKER_PATTERN.match(line) if match: if marker: yield marker, '\n'.join(...
def marker_split(block)
Yield marker, value pairs from a text block (i.e. a list of lines). :param block: text block consisting of \n separated lines as it will be the case for \ files read using "rU" mode. :return: generator of (marker, value) pairs.
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for k, v in self: if k == key: return v return default
def get(self, key, default=None)
Retrieve the first value for a marker or None.
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marker_map = marker_map or {} for entry in parse( filename, encoding, entry_sep, entry_prefix or entry_sep, keep_empty=keep_empty): if entry: self.append(entry_impl([(marker_map.get(k, k)...
def read(self, filename, encoding='utf-8', marker_map=None, entry_impl=Entry, entry_sep='\n\n', entry_prefix=None, keep_empty=False)
Extend the list by parsing new entries from a file. :param filename: :param encoding: :param marker_map: A dict used to map marker names. :param entry_impl: Subclass of Entry or None :param entry_sep: :param entry_prefix:
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with io.open(str(filename), 'w', encoding=encoding) as fp: for entry in self: fp.write(entry.__unicode__()) fp.write('\n\n')
def write(self, filename, encoding='utf-8')
Write the list of entries to a file. :param filename: :param encoding: :return:
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valid = {"": default, "yes": True, "y": True, "no": False, "n": False} while 1: choice = input(question + (" [Y/n] " if default else " [y/N] ")).lower() if choice in valid: return valid[choice] print("Please respond with 'y' or 'n' ")
def confirm(question, default=True)
Ask a yes/no question interactively. :param question: The text of the question to ask. :returns: True if the answer was "yes", False otherwise.
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lines = [] for line in self.get(section, option, fallback='').splitlines(): if re.match(re.escape(whitespace_preserving_prefix) + '\s+', line): line = line[len(whitespace_preserving_prefix):] lines.append(line) return '\n'.join(lines)
def gettext(self, section, option, whitespace_preserving_prefix='.')
While configparser supports multiline values, it does this at the expense of stripping leading whitespace for each line in such a value. Sometimes we want to preserve such whitespace, e.g. to be able to put markdown with nested lists into INI files. We support this be introducing a special prefi...
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1.120261