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payload = { "device-context": self._build_payload(device_id, obj_slot_id) } return self._post(self.url_prefix, payload)
def switch(self, device_id, obj_slot_id)
Switching of device-context
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payload = { "rib": self._build_payload(destination, mask, next_hops) } return self._post(self.url_prefix, payload)
def create(self, destination, mask, next_hops=[])
Create route to {destination} {mask} using {next_hops} expressed as (gateway, distance)
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for f in ["INCAR", "POSCAR", "POTCAR", "KPOINTS"]: if not os.path.exists(os.path.join(dir_name, f)) and \ not os.path.exists(os.path.join(dir_name, f + ".orig")): return False return True
def contains_vasp_input(dir_name)
Checks if a directory contains valid VASP input. Args: dir_name: Directory name to check. Returns: True if directory contains all four VASP input files (INCAR, POSCAR, KPOINTS and POTCAR).
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structure = Structure.from_dict(d["output"]["crystal"]) f = VoronoiNN() cn = [] for i, s in enumerate(structure.sites): try: n = f.get_cn(structure, i) number = int(round(n)) cn.append({"site": s.as_dict(), "coordination": number}) except Exceptio...
def get_coordination_numbers(d)
Helper method to get the coordination number of all sites in the final structure from a run. Args: d: Run dict generated by VaspToDbTaskDrone. Returns: Coordination numbers as a list of dict of [{"site": site_dict, "coordination": number}, ...].
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fullpath = os.path.abspath(dir_name) try: hostname = socket.gethostbyaddr(socket.gethostname())[0] except: hostname = socket.gethostname() return "{}:{}".format(hostname, fullpath)
def get_uri(dir_name)
Returns the URI path for a directory. This allows files hosted on different file servers to have distinct locations. Args: dir_name: A directory name. Returns: Full URI path, e.g., fileserver.host.com:/full/path/of/dir_name.
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try: d = self.get_task_doc(path) if self.mapi_key is not None and d["state"] == "successful": self.calculate_stability(d) tid = self._insert_doc(d) return tid except Exception as ex: import traceback logger....
def assimilate(self, path)
Parses vasp runs. Then insert the result into the db. and return the task_id or doc of the insertion. Returns: If in simulate_mode, the entire doc is returned for debugging purposes. Else, only the task_id of the inserted doc is returned.
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logger.info("Getting task doc for base dir :{}".format(path)) files = os.listdir(path) vasprun_files = OrderedDict() if "STOPCAR" in files: #Stopped runs. Try to parse as much as possible. logger.info(path + " contains stopped run") for r in self....
def get_task_doc(self, path)
Get the entire task doc for a path, including any post-processing.
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logger.info("Post-processing dir:{}".format(dir_name)) fullpath = os.path.abspath(dir_name) # VASP input generated by pymatgen's alchemy has a # transformations.json file that keeps track of the origin of a # particular structure. This is extremely useful for tracing b...
def post_process(self, dir_name, d)
Simple post-processing for various files other than the vasprun.xml. Called by generate_task_doc. Modify this if your runs have other kinds of processing requirements. Args: dir_name: The dir_name. d: Current doc generated.
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fullpath = os.path.abspath(dir_name) logger.info("Processing Killed run " + fullpath) d = {"dir_name": fullpath, "state": "killed", "oszicar": {}} for f in os.listdir(dir_name): filename = os.path.join(dir_name, f) if fnmatch(f, "INCAR*"): ...
def process_killed_run(self, dir_name)
Process a killed vasp run.
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vasprun_file = os.path.join(dir_name, filename) if self.parse_projected_eigen and (self.parse_projected_eigen != 'final' or \ taskname == self.runs[-1]): parse_projected_eigen = True else: parse_projected_eigen = False r = Vas...
def process_vasprun(self, dir_name, taskname, filename)
Process a vasprun.xml file.
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try: fullpath = os.path.abspath(dir_name) # Defensively copy the additional fields first. This is a MUST. # Otherwise, parallel updates will see the same object and inserts # will be overridden!! d = {k: v for k, v in self.additional_fields.i...
def generate_doc(self, dir_name, vasprun_files)
Process aflow style runs, where each run is actually a combination of two vasp runs.
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(parent, subdirs, files) = path if set(self.runs).intersection(subdirs): return [parent] if not any([parent.endswith(os.sep + r) for r in self.runs]) and \ len(glob.glob(os.path.join(parent, "vasprun.xml*"))) > 0: return [parent] return []
def get_valid_paths(self, path)
There are some restrictions on the valid directory structures: 1. There can be only one vasp run in each directory. Nested directories are fine. 2. Directories designated "relax1", "relax2" are considered to be 2 parts of an aflow style run. 3. Directories containing vasp ...
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# How to make different types of objects iterable dict_handler = lambda d: chain.from_iterable(d.items()) all_handlers = {tuple: iter, list: iter, deque: iter, dict: dict_handler, set: iter, frozenset: i...
def total_size(o, handlers={}, verbose=False, count=False)
Returns the approximate memory footprint an object and all of its contents. Automatically finds the contents of the following builtin containers and their subclasses: tuple, list, deque, dict, set and frozenset. To search other containers, add handlers to iterate over their contents: handlers = {...
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if s is None: return {} d = {} for item in [e.strip() for e in s.split(",")]: try: key, value = item.split("=", 1) except ValueError: msg = "argument item '{}' not in form key=value".format(item) if _argparse_is_dumb: _alog.war...
def args_kvp_nodup(s)
Parse argument string as key=value pairs separated by commas. :param s: Argument string :return: Parsed value :rtype: dict :raises: ValueError for format violations or a duplicated key.
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if isinstance(o, dict): d = o if self._dx is None else self._dx(o) return {k: self.walk(v) for k, v in d.items()} elif isinstance(o, list): return [self.walk(v) for v in o] else: return o if self._vx is None else self._vx(o)
def walk(self, o)
Walk a dict & transform.
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r = {} for k, v in o.items(): if isinstance(k, str): k = k.replace('$', '_') if "." in k: sub_r, keys = r, k.split('.') # create sub-dicts until last part of key for k2 in keys[:-1]: sub_...
def dict_expand(o)
Expand keys in a dict with '.' in them into sub-dictionaries, e.g. {'a.b.c': 'foo'} ==> {'a': {'b': {'c': 'foo'}}}
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self._collection_name = value self._mongo_coll = self.db[value] self.collection = TrackedCollection(self._mongo_coll, operation=self._t_op, field=self._t_field)
def collection_name(self, value)
Switch to another collection. Note that you may have to set the aliases and default properties if the schema of the new collection differs from the current collection.
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_log.info("tracked_find.begin") # if tracking is off, just call find (ie do nothing) if self._tracking_off: _log.info("tracked_find.end, tracking=off") return self._coll_find(*args, **kwargs) # otherwise do somethin' real # fish 'filter' out of ar...
def tracked_find(self, *args, **kwargs)
Replacement for regular ``find()``.
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rec = self._c.find_one({}, {self._fld: 1}, sort=[(self._fld, -1)], limit=1) if rec is None: self._pos = self._empty_pos() elif not self._fld in rec: _log.error("Tracking field not found. field={} collection={}" .format(self._fld, self._c.na...
def update(self)
Update the position of the mark in the collection. :return: this object, for chaining :rtype: Mark
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return {self.FLD_OP: self._op.name, self.FLD_MARK: self._pos, self.FLD_FLD: self._fld}
def as_dict(self)
Representation as a dict for JSON serialization.
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return Mark(collection=coll, operation=Operation[d[cls.FLD_OP]], pos=d[cls.FLD_MARK], field=d[cls.FLD_FLD])
def from_dict(cls, coll, d)
Construct from dict :param coll: Collection for the mark :param d: Input :type d: dict :return: new instance :rtype: Mark
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q = {} for field, value in self._pos.items(): if value is None: q.update({field: {'$exists': True}}) else: q.update({field: {'$gt': value}}) return q
def query(self)
A mongdb query expression to find all records with higher values for this mark's fields in the collection. :rtype: dict
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if self._track is None: self._track = self.db[self.tracking_collection_name]
def create(self)
Create tracking collection. Does nothing if tracking collection already exists.
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self._check_exists() obj = mark.as_dict() try: # Make a 'filter' to find/update existing record, which uses # the field name and operation (but not the position). filt = {k: obj[k] for k in (mark.FLD_FLD, mark.FLD_OP)} _log.debug("save: up...
def save(self, mark)
Save a position in this collection. :param mark: The position to save :type mark: Mark :raises: DBError, NoTrackingCollection
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obj = self._get(operation, field) if obj is None: # empty Mark instance return Mark(collection=self.collection, operation=operation, field=field) return Mark.from_dict(self.collection, obj)
def retrieve(self, operation, field=None)
Retrieve a position in this collection. :param operation: Name of an operation :type operation: :class:`Operation` :param field: Name of field for sort order :type field: str :return: The position for this operation :rtype: Mark :raises: NoTrackingCollection
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self._check_exists() query = {Mark.FLD_OP: operation.name, Mark.FLD_MARK + "." + field: {"$exists": True}} return self._track.find_one(query)
def _get(self, operation, field)
Get tracked position for a given operation and field.
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self._collection_name = value self.collection = self.db[value]
def collection_name(self, value)
Switch to another collection. Note that you may have to set the aliases and default properties if the schema of the new collection differs from the current collection.
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if aliases_config is None: with open(os.path.join(os.path.dirname(__file__), "aliases.json")) as f: d = json.load(f) self.aliases = d.get("aliases", {}) self.default_criteria = d.get("defaults", {}) e...
def set_aliases_and_defaults(self, aliases_config=None, default_properties=None)
Set the alias config and defaults to use. Typically used when switching to a collection with a different schema. Args: aliases_config: An alias dict to use. Defaults to None, which means the default aliases defined in "aliases.json" is used. See constructor ...
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chemsys_list = [] for i in range(len(elements)): for combi in itertools.combinations(elements, i + 1): chemsys = "-".join(sorted(combi)) chemsys_list.append(chemsys) crit = {"chemsys": {"$in": chemsys_list}} if additional_criteria is n...
def get_entries_in_system(self, elements, inc_structure=False, optional_data=None, additional_criteria=None)
Gets all entries in a chemical system, e.g. Li-Fe-O will return all Li-O, Fe-O, Li-Fe, Li-Fe-O compounds. .. note:: The get_entries_in_system and get_entries methods should be used with care. In essence, all entries, GGA, GGA+U or otherwise, are returned. The data...
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all_entries = list() optional_data = [] if not optional_data else list(optional_data) optional_data.append("oxide_type") fields = [k for k in optional_data] fields.extend(["task_id", "unit_cell_formula", "energy", "is_hubbard", "hubbards", "pseudo_...
def get_entries(self, criteria, inc_structure=False, optional_data=None)
Get ComputedEntries satisfying a particular criteria. .. note:: The get_entries_in_system and get_entries methods should be used with care. In essence, all entries, GGA, GGA+U or otherwise, are returned. The dataset is very heterogeneous and not directly compa...
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if criteria is None: return dict() parsed_crit = dict() for k, v in self.default_criteria.items(): if k not in criteria: parsed_crit[self.aliases.get(k, k)] = v for key, crit in list(criteria.items()): if key in ["normalized_f...
def _parse_criteria(self, criteria)
Internal method to perform mapping of criteria to proper mongo queries using aliases, as well as some useful sanitization. For example, string formulas such as "Fe2O3" are auto-converted to proper mongo queries of {"Fe":2, "O":3}. If 'criteria' is None, returns an empty dict. Putting th...
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return self.collection.ensure_index(key, unique=unique)
def ensure_index(self, key, unique=False)
Wrapper for pymongo.Collection.ensure_index
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if properties is not None: props, prop_dict = self._parse_properties(properties) else: props, prop_dict = None, None crit = self._parse_criteria(criteria) if self.query_post: for func in self.query_post: func(crit, props) ...
def query(self, properties=None, criteria=None, distinct_key=None, **kwargs)
Convenience method for database access. All properties and criteria can be specified using simplified names defined in Aliases. You can use the supported_properties property to get the list of supported properties. Results are returned as an iterator of dicts to ensure memory and cpu ...
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props = {} # TODO: clean up prop_dict? prop_dict = OrderedDict() # We use a dict instead of list to provide for a richer syntax for p in properties: if p in self.aliases: if isinstance(properties, dict): props[self.aliases[...
def _parse_properties(self, properties)
Make list of properties into 2 things: (1) dictionary of { 'aliased-field': 1, ... } for a mongodb query eg. {''} (2) dictionary, keyed by aliased field, for display
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for r in self.query(*args, **kwargs): return r return None
def query_one(self, *args, **kwargs)
Return first document from :meth:`query`, with same parameters.
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args = {'task_id': task_id} field = 'output.crystal' if final_structure else 'input.crystal' results = tuple(self.query([field], args)) if len(results) > 1: raise QueryError("More than one result found for task_id {}!".format(task_id)) elif len(results) == 0...
def get_structure_from_id(self, task_id, final_structure=True)
Returns a structure from the database given the task id. Args: task_id: The task_id to query for. final_structure: Whether to obtain the final or initial structure. Defaults to True.
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with open(config_file) as f: d = json.load(f) user = d["admin_user"] if use_admin else d["readonly_user"] password = d["admin_password"] if use_admin \ else d["readonly_password"] return QueryEngine( host=d["host"], port=d[...
def from_config(config_file, use_admin=False)
Initialize a QueryEngine from a JSON config file generated using mgdb init. Args: config_file: Filename of config file. use_admin: If True, the admin user and password in the config file is used. Otherwise, the readonly_user and pa...
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args = {'task_id': task_id} fields = ['calculations'] structure = self.get_structure_from_id(task_id) dosid = None for r in self.query(fields, args): dosid = r['calculations'][-1]['dos_fs_id'] if dosid is not None: self._fs = gridfs.GridFS...
def get_dos_from_id(self, task_id)
Overrides the get_dos_from_id for the MIT gridfs format.
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def wrapped(*args, **kwargs): ret_val = func(*args, **kwargs) if isinstance(ret_val, pymongo.cursor.Cursor): ret_val = self.from_cursor(ret_val) return ret_val return wrapped
def _wrapper(self, func)
This function wraps all callable objects returned by self.__getattr__. If the result is a cursor, wrap it into a QueryResults object so that you can invoke postprocess functions in self._pproc
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# Apply result_post funcs for pulling out sandbox properties for func in self._pproc: func(r) # If we haven't asked for specific properties, just return object if not self._prop_dict: result = r else: result = dict() # Map ...
def _mapped_result(self, r)
Transform/map a result.
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if not os.path.exists(path): raise SchemaPathError() filepat = "*." + ext if ext else "*" for f in glob.glob(os.path.join(path, filepat)): with open(f, 'r') as fp: try: schema = json.load(fp) except ValueError: raise SchemaParseErr...
def add_schemas(path, ext="json")
Add schemas from files in 'path'. :param path: Path with schema files. Schemas are named by their file, with the extension stripped. e.g., if path is "/tmp/foo", then the schema in "/tmp/foo/bar.json" will be named "bar". :type path: str :param ext: File extension that ide...
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fp = open(file_or_fp, 'r') if isinstance(file_or_fp, str) else file_or_fp obj = json.load(fp) schema = Schema(obj) return schema
def load_schema(file_or_fp)
Load schema from file. :param file_or_fp: File name or file object :type file_or_fp: str, file :raise: IOError if file cannot be opened or read, ValueError if file is not valid JSON or JSON is not a valid schema.
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self._json_schema_keys = add_keys if self._json_schema is None: self._json_schema = self._build_schema(self._schema) return self._json_schema
def json_schema(self, **add_keys)
Convert our compact schema representation to the standard, but more verbose, JSON Schema standard. Example JSON schema: http://json-schema.org/examples.html Core standard: http://json-schema.org/latest/json-schema-core.html :param add_keys: Key, default value pairs to add in, ...
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w = self._whatis(s) if w == self.IS_LIST: w0 = self._whatis(s[0]) js = {"type": "array", "items": {"type": self._jstype(w0, s[0])}} elif w == self.IS_DICT: js = {"type": "object", "properties": {key: self._build_sch...
def _build_schema(self, s)
Recursive schema builder, called by `json_schema`.
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if stype == self.IS_LIST: return "array" if stype == self.IS_DICT: return "object" if isinstance(sval, Scalar): return sval.jstype # it is a Schema, so return type of contents v = sval._schema return self._jstype(self._whatis(v...
def _jstype(self, stype, sval)
Get JavaScript name for given data type, called by `_build_schema`.
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v = str(db_version) return os.path.join(_top_dir, '..', 'schemata', 'versions', v)
def get_schema_dir(db_version=1)
Get path to directory with schemata. :param db_version: Version of the database :type db_version: int :return: Path :rtype: str
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d = get_schema_dir(db_version=db_version) schemafile = "{}.{}.json".format(db, collection) f = open(os.path.join(d, schemafile), "r") return f
def get_schema_file(db_version=1, db="mg_core", collection="materials")
Get file with appropriate schema. :param db_version: Version of the database :type db_version: int :param db: Name of database, e.g. 'mg_core' :type db: str :param collection: Name of collection, e.g. 'materials' :type collection: str :return: File with schema :rtype: file :raise: I...
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settings = yaml.load(_as_file(infile)) if not hasattr(settings, 'keys'): raise ValueError("Settings not found in {}".format(infile)) # Processing of namespaced parameters in .pmgrc.yaml. processed_settings = {} for k, v in settings.items(): if k.startswith("PMG_DB_"): ...
def get_settings(infile)
Read settings from input file. :param infile: Input file for JSON settings. :type infile: file or str path :return: Settings parsed from file :rtype: dict
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for alias, real in ((USER_KEY, "readonly_user"), (PASS_KEY, "readonly_password")): if alias in d: d[real] = d[alias] del d[alias]
def auth_aliases(d)
Interpret user/password aliases.
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U, P = USER_KEY, PASS_KEY # If user/password, un-prefixed, exists, do nothing. if U in settings and P in settings: return True # Set prefixes prefixes = [] if readonly_first: if readonly: prefixes.append("readonly_") if admin: prefixes.append...
def normalize_auth(settings, admin=True, readonly=True, readonly_first=False)
Transform the readonly/admin user and password to simple user/password, as expected by QueryEngine. If return value is true, then admin or readonly password will be in keys "user" and "password". :param settings: Connection settings :type settings: dict :param admin: Check for admin password :p...
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main_fmt, sub_fmt = fmt.split('/') if sub_fmt.lower() == "text": msg = MIMEText(text, "plain") elif sub_fmt.lower() == "html": msg = MIMEText(text, "html") else: raise ValueError("Unknown message format: {}".format(fmt)) msg['Subject']...
def send(self, text, fmt)
Send the email message. :param text: The text to send :type text: str :param fmt: The name of the format of the text :type fmt: str :return: Number of recipients it was sent to :rtype: int
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keyset, maxwid = set(), {} for r in rs: key = tuple(sorted(r.keys())) keyset.add(key) if key not in maxwid: maxwid[key] = [len(k) for k in key] for i, k in enumerate(key): strlen = len("{}".format(r[k])) ...
def result_subsets(self, rs)
Break a result set into subsets with the same keys. :param rs: Result set, rows of a result as a list of dicts :type rs: list of dict :return: A set with distinct keys (tuples), and a dict, by these tuples, of max. widths for each column
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columns = list(columns) # might be a tuple fixed_cols = [self.key] if section.lower() == "different": fixed_cols.extend([Differ.CHANGED_MATCH_KEY, Differ.CHANGED_OLD, Differ.CHANGED_NEW]) map(columns.remove, fixed_cols) columns.sort() return fixed_co...
def ordered_cols(self, columns, section)
Return ordered list of columns, from given columns and the name of the section
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#print("@@ SORT ROWS:\n{}".format(rows)) # Section-specific determination of sort key if section.lower() == Differ.CHANGED.lower(): sort_key = Differ.CHANGED_DELTA else: sort_key = None if sort_key is not None: rows.sort(key=itemgetter...
def sort_rows(self, rows, section)
Sort the rows, as appropriate for the section. :param rows: List of tuples (all same length, same values in each position) :param section: Name of section, should match const in Differ class :return: None; rows are sorted in-place
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self._add_meta(result) walker = JsonWalker(JsonWalker.value_json, JsonWalker.dict_expand) r = walker.walk(result) return r
def document(self, result)
Build dict for MongoDB, expanding result keys as we go.
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css = "\n".join(self.css) content = "{}{}".format(self._header(), self._body(result)) if self._email: text = .format(css=css, content=content, sty=self.styles["content"]["_"]) else: text = .format(css=css, content=content) return text
def format(self, result)
Generate HTML report. :return: Report body :rtype: str
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m = self.meta lines = ['-' * len(self.TITLE), self.TITLE, '-' * len(self.TITLE), "Compared: {db1} <-> {db2}".format(**m), "Filter: {filter}".format(**m), "Run time: {start_time} -- {end_time} ({elapsed:.1f} sec...
def format(self, result)
Generate plain text report. :return: Report body :rtype: str
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try: qe = clazz(**config.settings) except Exception as err: raise CreateQueryEngineError(clazz, config.settings, err) return qe
def create_query_engine(config, clazz)
Create and return new query engine object from the given `DBConfig` object. :param config: Database configuration :type config: dbconfig.DBConfig :param clazz: Class to use for creating query engine. Should act like query_engine.QueryEngine. :type clazz: class :return: New que...
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if os.path.isdir(path): configs = glob.glob(_opj(path, pattern)) else: configs = [path] for config in configs: cfg = dbconfig.DBConfig(config_file=config) cs = cfg.settings if dbconfig.DB_KEY not in cs: ...
def add_path(self, path, pattern="*.json")
Add configuration file(s) in `path`. The path can be a single file or a directory. If path is a directory, then `pattern` (Unix glob-style) will be used to get a list of all config files in the directory. The name given to each file is the database name and collection na...
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self._d[name] = cfg if expand: self.expand(name) return self
def add(self, name, cfg, expand=False)
Add a configuration object. :param name: Name for later retrieval :param cfg: Configuration object :param expand: Flag for adding sub-configs for each sub-collection. See discussion in method doc. :return: self, for chaining :raises: CreateQueryEngineError...
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if self._is_pattern(name): expr = re.compile(self._pattern_to_regex(name)) for cfg_name in self._d.keys(): if expr.match(cfg_name): self._expand(cfg_name) else: self._expand(name)
def expand(self, name)
Expand config for `name` by adding a sub-configuration for every dot-separated collection "below" the given one (or all, if none given). For example, for a database 'mydb' with collections ['spiderman.amazing', 'spiderman.spectacular', 'spiderman2'] and a configuration {...
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cfg = self._d[name] if cfg.collection is None: base_coll = '' else: base_coll = cfg.collection + self.SEP qe = self._get_qe(name, cfg) coll, db = qe.collection, qe.db cur_coll = coll.name for coll_name in db.collection_names(): ...
def _expand(self, name)
Perform real work of `expand()` function.
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delme = [] if self._is_pattern(name): expr = re.compile(self._pattern_to_regex(name)) for key, obj in self._cached.items(): if expr.match(key): delme.append(key) else: if name in self._cached: delme....
def uncache(self, name)
Remove all created query engines that match `name` from the cache (this disconnects from MongoDB, which is the point). :param name: Name used for :meth:`add`, or pattern :return: None
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if prefix is None: self._pfx = None else: self._pfx = prefix + self.SEP
def set_prefix(self, prefix=None)
Set prefix to use as a namespace for item lookup. A dot (.) will be automatically added to the given string. :param prefix: Prefix, or None to unset :return: None
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if key in self._cached: return self._cached[key] qe = create_query_engine(obj, self._class) self._cached[key] = qe return qe
def _get_qe(self, key, obj)
Instantiate a query engine, or retrieve a cached one.
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if not pattern.endswith("$"): pattern += "$" expr = re.compile(pattern) return list(filter(expr.match, self.keys()))
def re_keys(self, pattern)
Find keys matching `pattern`. :param pattern: Regular expression :return: Matching keys or empty list :rtype: list
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return {k: self[k] for k in self.re_keys(pattern)}
def re_get(self, pattern)
Return values whose key matches `pattern` :param pattern: Regular expression :return: Found values, as a dict.
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self._target_coll = target.collection if not crit: # reduce any False-y crit value to None crit = None cur = source.query(criteria=crit) _log.info("source.collection={} crit={} source_records={:d}" .format(source.collection, crit, len(cur))) ...
def get_items(self, source=None, target=None, crit=None)
Copy records from source to target collection. :param source: Input collection :type source: QueryEngine :param target: Output collection :type target: QueryEngine :param crit: Filter criteria, e.g. "{ 'flag': True }". :type crit: dict
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doc = fn.__doc__ params, return_ = {}, {} param_order = [] for line in doc.split("\n"): line = line.strip() if line.startswith(":param"): _, name, desc = line.split(":", 2) name = name[6:].strip() # skip 'param ' params[name] = {'desc': desc.stri...
def parse_fn_docstring(fn)
Get parameter and return types from function's docstring. Docstrings must use this format:: :param foo: What is foo :type foo: int :return: What is returned :rtype: double :return: A map of names, each with keys 'type' and 'desc'. :rtype: tuple(dict)
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merged = copy.copy(sandbox_collections) # create/clear target collection target = merged.database[new_tasks] if wipe: _log.debug("merge_tasks.wipe.begin") target.remove() merged.database['counter'].remove() _log.debug("merge_tasks.wipe.end") # perform the merge ...
def merge_tasks(core_collections, sandbox_collections, id_prefix, new_tasks, batch_size=100, wipe=False)
Merge core and sandbox collections into a temporary collection in the sandbox. :param core_collections: Core collection info :type core_collections: Collections :param sandbox_collections: Sandbox collection info :type sandbox_collections: Collections
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sep = '\n' + ' ' * depth * indent return ''.join( ("{}: {}{}".format( k, alphadump(d[k], depth=depth+1) if isinstance(d[k], dict) else str(d[k]), sep) for k in sorted(d.keys())) )
def alphadump(d, indent=2, depth=0)
Dump a dict to a str, with keys in alphabetical order.
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for collection, doc in self.examples(): _log.debug("validating example in collection {}".format(collection)) sch = schema.get_schema(collection) # with more err. checking result = sch.validate(doc) _log.debug("validation result: {}".format("OK" if result...
def validate_examples(self, fail_fn)
Check the examples against the schema. :param fail_fn: Pass failure messages to this function :type fail_fn: function(str)
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user_kw = {} if user_kw is None else user_kw build_kw = {} if build_kw is None else build_kw n = self._build(self.get_items(**user_kw), **build_kw) finalized = self.finalize(self._status.has_failures()) if not finalized: _log.error("Finalization failed") ...
def run(self, user_kw=None, build_kw=None)
Run the builder. :param user_kw: keywords from user :type user_kw: dict :param build_kw: internal settings :type build_kw: dict :return: Number of items processed :rtype: int
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if isinstance(config, str): conn = dbutil.get_database(config_file=config) elif isinstance(config, dict): conn = dbutil.get_database(settings=config) else: raise ValueError("Configuration, '{}', must be a path to " "a con...
def connect(self, config)
Connect to database with given configuration, which may be a dict or a path to a pymatgen-db configuration.
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_log.debug("_build, chunk_size={:d}".format(chunk_size)) n, i = 0, 0 for i, item in enumerate(items): if i == 0: _log.debug("_build, first item") if 0 == (i + 1) % chunk_size: if self._seq: self._run(0) ...
def _build(self, items, chunk_size=10000)
Build the output, in chunks. :return: Number of items processed :rtype: int
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_log.debug("run.parallel.multiprocess.start") processes = [] ProcRunner.instance = self for i in range(self._ncores): self._status.running(i) proc = multiprocessing.Process(target=ProcRunner.run, args=(i,)) proc.start() processes.a...
def _run_parallel_multiprocess(self)
Run processes from queue
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while 1: try: item = self._queue.get(timeout=2) self.process_item(item) except Queue.Empty: break except Exception as err: _log.error("In _run(): {}".format(err)) if _log.isEnabledFor(log...
def _run(self, index)
Run method for one thread or process Just pull an item off the queue and process it, until the queue is empty. :param index: Sequential index of this process or thread :type index: int
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def _keys(x, pre=''): for k in x: yield (pre + k) if isinstance(x[k], dict): for nested in _keys(x[k], pre + k + sep): yield nested return list(_keys(coll.find_one()))
def collection_keys(coll, sep='.')
Get a list of all (including nested) keys in a collection. Examines the first document in the collection. :param sep: Separator for nested keys :return: List of str
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if len(d) == 0: return "{}" return "{" + ', '.join(["'{}': {}".format(k, quotable(v)) for k, v in d.items()]) + "}"
def csv_dict(d)
Format dict to a string with comma-separated values.
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return ', '.join( ["{}={}".format(k, quotable(v)) for k, v in d.items()])
def kvp_dict(d)
Format dict to key=value pairs.
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self._groups = self.shared_dict() self._target_coll = target.collection self._src = source return source.query()
def get_items(self, source=None, target=None)
Get all records from source collection to add to target. :param source: Input collection :type source: QueryEngine :param target: Output collection :type target: QueryEngine
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group, value = item['group'], item['value'] if group in self._groups: cur_val = self._groups[group] self._groups[group] = max(cur_val, value) else: # New group. Could fetch old max. from target collection, # but for the sake of illustratio...
def process_item(self, item)
Calculate new maximum value for each group, for "new" items only.
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for group, value in self._groups.items(): doc = {'group': group, 'value': value} self._target_coll.update({'group': group}, doc, upsert=True) return True
def finalize(self, errs)
Update target collection with calculated maximum values.
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if not rec: return default if not isinstance(rec, collections.Mapping): raise ValueError('input record must act like a dict') if not '.' in key: return rec.get(key, default) for key_part in key.split('.'): if not isinstance(rec, collections.Mapping): retu...
def mongo_get(rec, key, default=None)
Get value from dict using MongoDB dot-separated path semantics. For example: >>> assert mongo_get({'a': {'b': 1}, 'x': 2}, 'a.b') == 1 >>> assert mongo_get({'a': {'b': 1}, 'x': 2}, 'x') == 2 >>> assert mongo_get({'a': {'b': 1}, 'x': 2}, 'a.b.c') is None :param rec: mongodb document :param key:...
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if field.has_subfield(): self._fields[field.full_name] = 1 else: self._fields[field.name] = 1 if op and op.is_size() and not op.is_variable(): # get minimal part of array with slicing, # but cannot use slice with variables self...
def add(self, field, op=None, val=None)
Update report fields to include new one, if it doesn't already. :param field: The field to include :type field: Field :param op: Operation :type op: ConstraintOperator :return: None
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d = copy.copy(self._fields) for k, v in self._slices.items(): d[k] = {'$slice': v} return d
def to_mongo(self)
Translate projection to MongoDB query form. :return: Dictionary to put into a MongoDB JSON query :rtype: dict
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rec = {} if record is None else record for v in violations: self._viol.append((v, rec))
def add_violations(self, violations, record=None)
Add constraint violations and associated record. :param violations: List of violations :type violations: list(ConstraintViolation) :param record: Associated record :type record: dict :rtype: None
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# extract filter and constraints try: fltr = item[self.FILTER_SECT] except KeyError: raise ValueError("configuration requires '{}'".format(self.FILTER_SECT)) sample = item.get(self.SAMPLE_SECT, None) constraints = item.get(self.CONSTRAINT_SECT, No...
def _add_complex_section(self, item)
Add a section that has a filter and set of constraints :raise: ValueError if filter or constraints is missing
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self._spec = constraint_spec self._progress.set_subject(subject) self._build(constraint_spec) for sect_parts in self._sections: cvg = self._validate_section(subject, coll, sect_parts) if cvg is not None: yield cvg
def validate(self, coll, constraint_spec, subject='collection')
Validation of a collection. This is a generator that yields ConstraintViolationGroups. :param coll: Mongo collection :type coll: pymongo.Collection :param constraint_spec: Constraint specification :type constraint_spec: ConstraintSpec :param subject: Name of the thing b...
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cvgroup = ConstraintViolationGroup() cvgroup.subject = subject # If the constraint is an 'import' of code, treat it differently here # if self._is_python(parts): # num_found = self._run_python(cvgroup, coll, parts) # return None if num_found == 0 else cvgr...
def _validate_section(self, subject, coll, parts)
Validate one section of a spec. :param subject: Name of subject :type subject: str :param coll: The collection to validate :type coll: pymongo.Collection :param parts: Section parts :type parts: Validator.SectionParts :return: Group of constraint violations, if a...
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# special case, when no constraints are given if len(query.all_clauses) == 0: return [NullConstraintViolation()] # normal case, check all the constraints reasons = [] for clause in query.all_clauses: var_name = None key = clause.constr...
def _get_violations(self, query, record)
Reverse-engineer the query to figure out why a record was selected. :param query: MongoDB query :type query: MongQuery :param record: Record in question :type record: dict :return: Reasons why bad :rtype: list(ConstraintViolation)
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self._sections = [] # For each condition in the spec for sval in constraint_spec: rpt_fld = self._base_report_fields.copy() #print("@@ CONDS = {}".format(sval.filters)) #print("@@ MAIN = {}".format(sval.constraints)) # Constraints ...
def _build(self, constraint_spec)
Generate queries to execute. Sets instance variables so that Mongo query strings, etc. can now be extracted from the object. :param constraint_spec: Constraint specification :type constraint_spec: ConstraintSpec
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# process expressions, grouping by field groups = {} for expr in expr_list: field, raw_op, val = parse_expr(expr) op = ConstraintOperator(raw_op) if field not in groups: groups[field] = ConstraintGroup(Field(field, self._aliases)) ...
def _process_constraint_expressions(self, expr_list, conflict_check=True, rev=True)
Create and return constraints from expressions in expr_list. :param expr_list: The expressions :conflict_check: If True, check for conflicting expressions within each field :return: Constraints grouped by field (the key is the field name) :rtype: dict
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if len(constraint_list) == 1 and \ PythonMethod.constraint_is_method(constraint_list[0]): return True if len(constraint_list) > 1 and \ any(filter(PythonMethod.constraint_is_method, constraint_list)): condensed_list = '/'.join(constraint_l...
def _is_python(self, constraint_list)
Check whether constraint is an import of Python code. :param constraint_list: List of raw constraints from YAML file :type constraint_list: list(str) :return: True if this refers to an import of code, False otherwise :raises: ValidatorSyntaxError
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"Set aliases and wrap errors in ValueError" try: self.aliases = new_value except Exception as err: raise ValueError("invalid value: {}".format(err))
def set_aliases(self, new_value)
Set aliases and wrap errors in ValueError
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count = cursor.count() # special case: empty collection if count == 0: self._empty = True raise ValueError("Empty collection") # special case: entire collection if self.p >= 1 and self.max_items <= 0: for item in cursor: ...
def sample(self, cursor)
Extract records randomly from the database. Continue until the target proportion of the items have been extracted, or until `min_items` if this is larger. If `max_items` is non-negative, do not extract more than these. This function is a generator, yielding items incrementally. ...
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print 'The following LiveSync agents are available:' for name, backend in current_plugin.backend_classes.iteritems(): print cformat(' - %{white!}{}%{reset}: {} ({})').format(name, backend.title, backend.description)
def available_backends()
Lists the currently available backend types
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print 'The following LiveSync agents are active:' agent_list = LiveSyncAgent.find().order_by(LiveSyncAgent.backend_name, db.func.lower(LiveSyncAgent.name)).all() table_data = [['ID', 'Name', 'Backend', 'Initial Export', 'Queue']] for agent in agent_list: initial = (cformat('%{green!}done%{r...
def agents()
Lists the currently active agents
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agent = LiveSyncAgent.find_first(id=agent_id) if agent is None: print 'No such agent' return if agent.backend is None: print cformat('Cannot run agent %{red!}{}%{reset} (backend not found)').format(agent.name) return print cformat('Selected agent: %{white!}{}%{reset}...
def initial_export(agent_id, force)
Performs the initial data export for an agent
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if agent_id is None: agent_list = LiveSyncAgent.find_all() else: agent = LiveSyncAgent.find_first(id=agent_id) if agent is None: print 'No such agent' return agent_list = [agent] for agent in agent_list: if agent.backend is None: ...
def run(agent_id, force=False)
Runs the livesync agent
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