"""Create PyTables files and the object tree. This module support importing generic HDF5 files, on top of which PyTables files are created, read or extended. If a file exists, an object tree mirroring their hierarchical structure is created in memory. File class offer methods to traverse the tree, as well as to create new nodes. """ from __future__ import annotations import os import atexit import weakref import datetime import warnings from typing import Any, Literal from pathlib import Path from collections import defaultdict from collections.abc import Callable, Generator, Iterator import numpy as np import numexpr as ne import numpy.typing as npt from . import ( hdf5extension, utilsextension, parameters, undoredo, linkextension, lrucacheextension, ) from .atom import Atom from .leaf import Leaf from .link import SoftLink, ExternalLink from .node import Node, NotLoggedMixin from .path import join_path, split_path from .array import Array from .group import Group, RootGroup, TransactionGroupG, TransactionG, MarkG from .table import Table from .utils import detect_number_of_cores from .carray import CArray from .earray import EArray from .flavor import flavor_of, array_as_internal from .filters import Filters from .vlarray import VLArray from .registry import get_class_by_name from .exceptions import ( ClosedFileError, FileModeError, NodeError, NoSuchNodeError, UnclosedFileWarning, UndoRedoError, ClosedNodeError, PerformanceWarning, ) from .description import ( Description, IsDescription, UInt8Col, StringCol, descr_from_dtype, dtype_from_descr, ) # format_version = "1.0" # Initial format # format_version = "1.1" # Changes in ucl compression # format_version = "1.2" # Support for enlargeable arrays and VLA's # # 1.2 was introduced in PyTables 0.8 # format_version = "1.3" # Support for indexes in Tables # # 1.3 was introduced in PyTables 0.9 # format_version = "1.4" # Support for multidimensional attributes # # 1.4 was introduced in PyTables 1.1 # format_version = "1.5" # Support for persistent defaults in tables # # 1.5 was introduced in PyTables 1.2 # format_version = "1.6" # Support for NumPy objects and new flavors for # # objects. # # 1.6 was introduced in pytables 1.3 # format_version = "2.0" # Pickles are not used anymore in system attrs # # 2.0 was introduced in PyTables 2.0 format_version = "2.1" # Numeric and numarray flavors are gone. compatible_formats = [] # Old format versions we can read # # Empty means that we support all the old formats class _FileRegistry: def __init__(self) -> None: self._name_mapping: dict[str, set[File]] = defaultdict(set) self._handlers: set[File] = set() @property def filenames(self) -> list[str]: return list(self._name_mapping) @property def handlers(self) -> set[File]: # return set(self._handlers) # return a copy return self._handlers def __len__(self) -> int: return len(self._handlers) def __contains__(self, filename: str) -> bool: return filename in self.filenames def add(self, handler: File) -> None: self._name_mapping[handler.filename].add(handler) self._handlers.add(handler) def remove(self, handler: File) -> None: filename = handler.filename self._name_mapping[filename].remove(handler) # remove enpty keys if not self._name_mapping[filename]: del self._name_mapping[filename] self._handlers.remove(handler) def get_handlers_by_name(self, filename: str) -> set[File]: # return set(self._name_mapping[filename]) # return a copy return self._name_mapping[filename] def close_all(self) -> None: handlers = list(self._handlers) # make a copy for fileh in handlers: msg = f"Closing remaining open file: {fileh.filename}" warnings.warn(UnclosedFileWarning(msg)) fileh.close() # Dict of opened files (keys are filenames and values filehandlers) _open_files = _FileRegistry() # Opcodes for do-undo actions _op_to_code = { "MARK": 0, "CREATE": 1, "REMOVE": 2, "MOVE": 3, "ADDATTR": 4, "DELATTR": 5, } _code_to_op = ["MARK", "CREATE", "REMOVE", "MOVE", "ADDATTR", "DELATTR"] # Paths and names for hidden nodes related with transactions. _trans_version = "1.0" _trans_group_parent = "/" _trans_group_name = "_p_transactions" _trans_group_path = join_path(_trans_group_parent, _trans_group_name) _action_log_parent = _trans_group_path _action_log_name = "actionlog" _action_log_path = join_path(_action_log_parent, _action_log_name) _trans_parent = _trans_group_path _trans_name = "t%d" # %d -> transaction number _trans_path = join_path(_trans_parent, _trans_name) _mark_parent = _trans_path _mark_name = "m%d" # %d -> mark number _mark_path = join_path(_mark_parent, _mark_name) _shadow_parent = _mark_path _shadow_name = "a%d" # %d -> action number _shadow_path = join_path(_shadow_parent, _shadow_name) def _checkfilters(filters: Filters) -> None: if not (filters is None or isinstance(filters, Filters)): raise TypeError( f"filter parameter has to be None or a Filter " f"instance and the passed type is: '{type(filters)}'" ) def copy_file( srcfilename: str, dstfilename: str, overwrite: bool = False, **kwargs ) -> None: """Copy the content of a PyTables file to another. This function allows you to copy an existing PyTables file named srcfilename to another file called dstfilename. The source file must exist and be readable. The destination file can be overwritten in place if existing by asserting the overwrite argument. This function is a shorthand for the :meth:`File.copy_file` method, which acts on an already opened file. kwargs takes keyword arguments used to customize the copying process. See the documentation of :meth:`File.copy_file` for a description of those arguments. """ # Open the source file. srcfileh = open_file(srcfilename, mode="r") try: # Copy it to the destination file. srcfileh.copy_file(dstfilename, overwrite=overwrite, **kwargs) finally: # Close the source file. srcfileh.close() hdf5_version_str = utilsextension.get_hdf5_version() hdf5_version_tup = tuple(map(int, hdf5_version_str.split("-")[0].split("."))) _FILE_OPEN_POLICY = "strict" if hdf5_version_tup < (1, 8, 7) else "default" def open_file( filename: str, mode: Literal["r", "w", "a", "r+"] = "r", title: str = "", root_uep: str = "/", filters: Filters | None = None, **kwargs, ) -> File: """Open a PyTables (or generic HDF5) file and return a File object. Parameters ---------- filename : str The name of the file (supports environment variable expansion). It is suggested that file names have any of the .h5, .hdf or .hdf5 extensions, although this is not mandatory. mode : str The mode to open the file. It can be one of the following: * *'r'*: Read-only; no data can be modified. * *'w'*: Write; a new file is created (an existing file with the same name would be deleted). * *'a'*: Append; an existing file is opened for reading and writing, and if the file does not exist it is created. * *'r+'*: It is similar to 'a', but the file must already exist. title : str If the file is to be created, a TITLE string attribute will be set on the root group with the given value. Otherwise, the title will be read from disk, and this will not have any effect. root_uep : str The root User Entry Point. This is a group in the HDF5 hierarchy which will be taken as the starting point to create the object tree. It can be whatever existing group in the file, named by its HDF5 path. If it does not exist, an HDF5ExtError is issued. Use this if you do not want to build the *entire* object tree, but rather only a *subtree* of it. .. versionchanged:: 3.0 The *rootUEP* parameter has been renamed into *root_uep*. filters : Filters An instance of the Filters (see :ref:`FiltersClassDescr`) class that provides information about the desired I/O filters applicable to the leaves that hang directly from the *root group*, unless other filter properties are specified for these leaves. Besides, if you do not specify filter properties for child groups, they will inherit these ones, which will in turn propagate to child nodes. Notes ----- In addition, it recognizes the (lowercase) names of parameters present in :file:`tables/parameters.py` as additional keyword arguments. See :ref:`parameter_files` for a detailed info on the supported parameters. .. note:: If you need to deal with a large number of nodes in an efficient way, please see :ref:`LRUOptim` for more info and advices about the integrated node cache engine. """ filename = os.fspath(filename) # XXX filename normalization ?? # Check already opened files if _FILE_OPEN_POLICY == "strict": # This policy does not allow to open the same file multiple times # even in read-only mode if filename in _open_files: raise ValueError( "The file '%s' is already opened. " "Please close it before reopening. " "HDF5 v.%s, FILE_OPEN_POLICY = '%s'" % ( filename, utilsextension.get_hdf5_version(), _FILE_OPEN_POLICY, ) ) else: for filehandle in _open_files.get_handlers_by_name(filename): omode = filehandle.mode # 'r' is incompatible with everything except 'r' itself if mode == "r" and omode != "r": raise ValueError( "The file '%s' is already opened, but " "not in read-only mode (as requested)." % filename ) # 'a' and 'r+' are compatible with everything except 'r' elif mode in ("a", "r+") and omode == "r": raise ValueError( "The file '%s' is already opened, but " "in read-only mode. Please close it before " "reopening in append mode." % filename ) # 'w' means that we want to destroy existing contents elif mode == "w": raise ValueError( "The file '%s' is already opened. Please " "close it before reopening in write mode." % filename ) # Finally, create the File instance, and return it return File(filename, mode, title, root_uep, filters, **kwargs) # A dumb class that doesn't keep anything at all class _NoCache: def __len__(self) -> int: return 0 def __contains__(self, key: Any) -> bool: return False def __iter__(self) -> Iterator: return iter([]) def __setitem__(self, key: Any, value: Any) -> None: pass __marker = object() def pop(self, key, d=__marker): if d is not self.__marker: return d raise KeyError(key) class _DictCache(dict): def __init__(self, nslots: int) -> None: if nslots < 1: raise ValueError("Invalid number of slots: %d" % nslots) self.nslots = nslots super().__init__() def __setitem__(self, key: Any, value: Any) -> None: # Check if we are running out of space if len(self) > self.nslots: warnings.warn( "the dictionary of node cache is exceeding the recommended " "maximum number (%d); be ready to see PyTables asking for " "*lots* of memory and possibly slow I/O." % (self.nslots), PerformanceWarning, ) super().__setitem__(key, value) class NodeManager: """Node manager.""" def __init__(self, nslots: int = 64, node_factory=None) -> None: super().__init__() self.registry = weakref.WeakValueDictionary() if nslots > 0: cache = lrucacheextension.NodeCache(nslots) elif nslots == 0: cache = _NoCache() else: # nslots < 0 cache = _DictCache(-nslots) self.cache = cache # node_factory(node_path) self.node_factory = node_factory def register_node(self, node: Node, key: str | None) -> None: """Register a node.""" if key is None: key = node._v_pathname if key in self.registry: if not self.registry[key]._v_isopen: del self.registry[key] self.registry[key] = node elif self.registry[key] is not node: raise RuntimeError( "trying to register a node with an " "existing key: ``%s``" % key ) else: self.registry[key] = node def cache_node(self, node: Node, key: str | None = None) -> None: """Create a node.""" if key is None: key = node._v_pathname self.register_node(node, key) if key in self.cache: oldnode = self.cache.pop(key) if oldnode is not node and oldnode._v_isopen: raise RuntimeError( "trying to cache a node with an " "existing key: ``%s``" % key ) self.cache[key] = node def get_node(self, key: str) -> Node: """Return a node matching the input key.""" node = self.cache.pop(key, None) if node is not None: if node._v_isopen: self.cache_node(node, key) return node else: # this should not happen warnings.warn("a closed node found in the cache: ``%s``" % key) if key in self.registry: node = self.registry[key] if node is None: # this should not happen since WeakValueDictionary drops all # dead weakrefs warnings.warn( "None is stored in the registry for key: " "``%s``" % key ) elif node._v_isopen: self.cache_node(node, key) return node else: # this should not happen warnings.warn( "a closed node found in the registry: " "``%s``" % key ) del self.registry[key] node = None if self.node_factory: node = self.node_factory(key) self.cache_node(node, key) return node def rename_node(self, oldkey: str, newkey: str) -> None: """Rename a node.""" for cache in (self.cache, self.registry): if oldkey in cache: node = cache.pop(oldkey) cache[newkey] = node def drop_from_cache(self, nodepath: str) -> None: """Remove the node from cache.""" # Remove the node from the cache. self.cache.pop(nodepath, None) def drop_node(self, node: Node, check_unregistered: bool = True) -> None: """Drop the `node`. Remove the node from the cache and, if it has no more references, close it. """ # Remove all references to the node. nodepath = node._v_pathname self.drop_from_cache(nodepath) if nodepath in self.registry: if not node._v_isopen: del self.registry[nodepath] elif check_unregistered: # If the node is not in the registry (this should never happen) # we close it forcibly since it is not ensured that the __del__ # method is called for object that are still alive when the # interpreter is shut down if node._v_isopen: warnings.warn( "dropping a node that is not in the registry: " "``%s``" % nodepath ) node._g_pre_kill_hook() node._f_close() def flush_nodes(self) -> None: """Flush all nodes.""" # Only iter on the nodes in the registry since nodes in the cache # should always have an entry in the registry closed_keys = [] for path, node in list(self.registry.items()): if not node._v_isopen: closed_keys.append(path) elif "/_i_" not in path: # Indexes are not necessary to be flushed if isinstance(node, Leaf): node.flush() for path in closed_keys: # self.cache.pop(path, None) if path in self.cache: warnings.warn("closed node the cache: ``%s``" % path) self.cache.pop(path, None) self.registry.pop(path) @staticmethod def _close_nodes( nodepaths: list[str], get_node: Callable[[str], Group | Node] ) -> None: for nodepath in nodepaths: try: node = get_node(nodepath) except KeyError: pass else: if not node._v_isopen or node._v__deleting: continue try: # Avoid descendent nodes to also iterate over # their descendents, which are already to be # closed by this loop. if hasattr(node, "_f_get_child"): node._g_close() else: node._f_close() del node except ClosedNodeError: # import traceback # type_, value, tb = sys.exc_info() # exception_dump = ''.join( # traceback.format_exception(type_, value, tb)) # warnings.warn( # "A '%s' exception occurred trying to close a node " # "that was supposed to be open.\n" # "%s" % (type_.__name__, exception_dump)) pass def close_subtree(self, prefix: str = "/") -> None: """Close a sub-tree of nodes.""" if not prefix.endswith("/"): prefix = prefix + "/" cache = self.cache registry = self.registry # Ensure tables are closed before their indices paths = [ path for path in cache if path.startswith(prefix) and "/_i_" not in path ] self._close_nodes(paths, cache.pop) # Close everything else (i.e. indices) paths = [path for path in cache if path.startswith(prefix)] self._close_nodes(paths, cache.pop) # Ensure tables are closed before their indices paths = [ path for path in registry if path.startswith(prefix) and "/_i_" not in path ] self._close_nodes(paths, registry.pop) # Close everything else (i.e. indices) paths = [path for path in registry if path.startswith(prefix)] self._close_nodes(paths, registry.pop) def shutdown(self) -> None: """Shutdown the node manager.""" registry = self.registry cache = self.cache # self.close_subtree('/') keys = list(cache) # copy for key in keys: node = cache.pop(key) if node._v_isopen: registry.pop(node._v_pathname, None) node._f_close() while registry: key, node = registry.popitem() if node._v_isopen: node._f_close() class File(hdf5extension.File): """The in-memory representation of a PyTables file. An instance of this class is returned when a PyTables file is opened with the :func:`tables.open_file` function. It offers methods to manipulate (create, rename, delete...) nodes and handle their attributes, as well as methods to traverse the object tree. The *user entry point* to the object tree attached to the HDF5 file is represented in the root_uep attribute. Other attributes are available. File objects support an *Undo/Redo mechanism* which can be enabled with the :meth:`File.enable_undo` method. Once the Undo/Redo mechanism is enabled, explicit *marks* (with an optional unique name) can be set on the state of the database using the :meth:`File.mark` method. There are two implicit marks which are always available: the initial mark (0) and the final mark (-1). Both the identifier of a mark and its name can be used in *undo* and *redo* operations. Hierarchy manipulation operations (node creation, movement and removal) and attribute handling operations (setting and deleting) made after a mark can be undone by using the :meth:`File.undo` method, which returns the database to the state of a past mark. If undo() is not followed by operations that modify the hierarchy or attributes, the :meth:`File.redo` method can be used to return the database to the state of a future mark. Else, future states of the database are forgotten. Note that data handling operations can not be undone nor redone by now. Also, hierarchy manipulation operations on nodes that do not support the Undo/Redo mechanism issue an UndoRedoWarning *before* changing the database. The Undo/Redo mechanism is persistent between sessions and can only be disabled by calling the :meth:`File.disable_undo` method. File objects can also act as context managers when using the with statement introduced in Python 2.5. When exiting a context, the file is automatically closed. Parameters ---------- filename : str The name of the file (supports environment variable expansion). It is suggested that file names have any of the .h5, .hdf or .hdf5 extensions, although this is not mandatory. mode : str The mode to open the file. It can be one of the following: * *'r'*: Read-only; no data can be modified. * *'w'*: Write; a new file is created (an existing file with the same name would be deleted). * *'a'*: Append; an existing file is opened for reading and writing, and if the file does not exist it is created. * *'r+'*: It is similar to 'a', but the file must already exist. title : str If the file is to be created, a TITLE string attribute will be set on the root group with the given value. Otherwise, the title will be read from disk, and this will not have any effect. root_uep : str The root User Entry Point. This is a group in the HDF5 hierarchy which will be taken as the starting point to create the object tree. It can be whatever existing group in the file, named by its HDF5 path. If it does not exist, an HDF5ExtError is issued. Use this if you do not want to build the *entire* object tree, but rather only a *subtree* of it. .. versionchanged:: 3.0 The *rootUEP* parameter has been renamed into *root_uep*. filters : Filters An instance of the Filters (see :ref:`FiltersClassDescr`) class that provides information about the desired I/O filters applicable to the leaves that hang directly from the *root group*, unless other filter properties are specified for these leaves. Besides, if you do not specify filter properties for child groups, they will inherit these ones, which will in turn propagate to child nodes. Notes ----- In addition, it recognizes the (lowercase) names of parameters present in :file:`tables/parameters.py` as additional keyword arguments. See :ref:`parameter_files` for a detailed info on the supported parameters. .. rubric:: File attributes .. attribute:: filename The name of the opened file. .. attribute:: format_version The PyTables version number of this file. .. attribute:: isopen True if the underlying file is open, false otherwise. .. attribute:: mode The mode in which the file was opened. .. attribute:: root The *root* of the object tree hierarchy (a Group instance). .. attribute:: root_uep The UEP (user entry point) group name in the file (see the :func:`open_file` function). .. versionchanged:: 3.0 The *rootUEP* attribute has been renamed into *root_uep*. """ # The top level kinds. Group must go first! _node_kinds = ("Group", "Leaf", "Link", "Unknown") @property def title(self) -> str: """Title of the root group in the file.""" return self.root._v_title @title.setter def title(self, title: str) -> None: self.root._v_title = title @title.deleter def title(self) -> None: del self.root._v_title @property def filters(self) -> Filters: """Filter properties for the root group. See :ref:`FiltersClassDescr`). """ return self.root._v_filters @filters.setter def filters(self, filters: Filters) -> None: self.root._v_filters = filters @filters.deleter def filters(self) -> None: del self.root._v_filters def __init__( self, filename: str, mode: Literal["r", "w", "a", "r+"] = "r", title: str = "", root_uep: str = "/", filters: Filters | None = None, **kwargs, ) -> None: self.filename = os.fspath(filename) """The name of the opened file.""" self.mode = mode """The mode in which the file was opened.""" if mode not in ("r", "r+", "a", "w"): raise ValueError( "invalid mode string ``%s``. Allowed modes are: " "'r', 'r+', 'a' and 'w'" % mode ) # Get all the parameters in parameter file(s) params = { k: v for k, v in parameters.__dict__.items() if k.isupper() and not k.startswith("_") } # Update them with possible keyword arguments if [k for k in kwargs if k.isupper()]: warnings.warn( "The use of uppercase keyword parameters is " "deprecated", DeprecationWarning, ) kwargs = {k.upper(): v for k, v in kwargs.items()} params.update(kwargs) # If MAX_ * _THREADS is not set yet, set it to the number of cores # on this machine. if params["MAX_NUMEXPR_THREADS"] is None: params["MAX_NUMEXPR_THREADS"] = detect_number_of_cores() if params["MAX_BLOSC_THREADS"] is None: params["MAX_BLOSC_THREADS"] = detect_number_of_cores() self.params = params # Now, it is time to initialize the File extension self._g_new(filename, mode, **params) # Check filters and set PyTables format version for new files. new = self._v_new if new: _checkfilters(filters) self.format_version = format_version """The PyTables version number of this file.""" # The node manager must be initialized before the root group # initialization but the node_factory attribute is set onl later # because it is a bound method of the root grop itself. node_cache_slots = params["NODE_CACHE_SLOTS"] self._node_manager = NodeManager(nslots=node_cache_slots) # For the moment Undo/Redo is not enabled. self._undoEnabled = False # Set the flag to indicate that the file has been opened. # It must be set before opening the root group # to allow some basic access to its attributes. self.isopen = 1 """True if the underlying file os open, False otherwise.""" # Append the name of the file to the global dict of files opened. _open_files.add(self) # Set the number of times this file has been opened to 1 self._open_count = 1 # Get the root group from this file self.root = root = self.__get_root_group(root_uep, title, filters) """The *root* of the object tree hierarchy (a Group instance).""" # Complete the creation of the root node # (see the explanation in ``RootGroup.__init__()``). root._g_post_init_hook() self._node_manager.node_factory = self.root._g_load_child # Save the PyTables format version for this file. if new: if params["PYTABLES_SYS_ATTRS"]: root._v_attrs._g__setattr( "PYTABLES_FORMAT_VERSION", format_version ) # If the file is old, and not opened in "read-only" mode, # check if it has a transaction log if not new and self.mode != "r" and _trans_group_path in self: # It does. Enable the undo. self.enable_undo() # Set the maximum number of threads for Numexpr ne.set_vml_num_threads(params["MAX_NUMEXPR_THREADS"]) def __get_root_group( self, root_uep: str | None, title: str, filters: Filters ) -> RootGroup: """Return a Group instance which can act as the root group in a tree. If file is opened in "r", "r+" or "a" mode, and the file already exists, this method dynamically builds a python object tree emulating the structure present on file. """ self._v_objectid = self._get_file_id() if root_uep in [None, ""]: root_uep = "/" # Save the User Entry Point in a variable class self.root_uep = root_uep new = self._v_new # Get format version *before* getting the object tree if not new: # Firstly, get the PyTables format version for this file self.format_version = utilsextension.read_f_attr( self._v_objectid, "PYTABLES_FORMAT_VERSION" ) if not self.format_version: # PYTABLES_FORMAT_VERSION attribute is not present self.format_version = "unknown" self._isPTFile = False elif not isinstance(self.format_version, str): # system attributes should always be str self.format_version = self.format_version.decode("utf-8") # Create new attributes for the root Group instance and # create the object tree return RootGroup(self, root_uep, title=title, new=new, filters=filters) def _get_or_create_path( self, path: Node | str, create: bool ) -> Group | Node | RootGroup: """Get the given `path` or create it if `create` is true. If `create` is true, `path` *must* be a string path and not a node, otherwise a `TypeError`will be raised. """ if create: path = path._v_pathname if hasattr(path, "_v_pathname") else path return self._create_path(path) else: return self.get_node(path) def _create_path(self, path: str) -> Group: """Create the groups needed for the `path` to exist. The group associated with the given `path` is returned. """ if not hasattr(path, "split"): raise TypeError("when creating parents, parent must be a path") if path == "/": return self.root parent, create_group = self.root, self.create_group for pcomp in path.split("/")[1:]: try: child = parent._f_get_child(pcomp) except NoSuchNodeError: child = create_group(parent, pcomp) parent = child return parent def create_group( self, where: Group | str, name: str, title: str = "", filters: Filters | None = None, createparents: bool = False, ) -> Group: """Create a new group. Parameters ---------- where : str or Group The parent group from which the new group will hang. It can be a path string (for example '/level1/leaf5'), or a Group instance (see :ref:`GroupClassDescr`). name : str The name of the new group. title : str, optional A description for this node (it sets the TITLE HDF5 attribute on disk). filters : Filters An instance of the Filters class (see :ref:`FiltersClassDescr`) that provides information about the desired I/O filters applicable to the leaves that hang directly from this new group (unless other filter properties are specified for these leaves). Besides, if you do not specify filter properties for its child groups, they will inherit these ones. createparents : bool Whether to create the needed groups for the parent path to exist (not done by default). See Also -------- Group : for more information on groups """ parentnode = self._get_or_create_path(where, createparents) _checkfilters(filters) return Group(parentnode, name, title=title, new=True, filters=filters) def create_table( self, where: Group | str, name: str, description: ( dict | type[IsDescription] | Description | npt.DTypeLike | None ) = None, title: str = "", filters: Filters | None = None, expectedrows: int = 10_000, chunkshape: int | tuple[int] | None = None, byteorder: str | None = None, createparents: bool = False, obj: np.ndarray | None = None, track_times: bool = True, ) -> Table: """Create a new table with the given name in where location. Parameters ---------- where : str or Group The parent group from which the new table will hang. It can be a path string (for example '/level1/leaf5'), or a Group instance (see :ref:`GroupClassDescr`). name : str The name of the new table. description : Description This is an object that describes the table, i.e. how many columns it has, their names, types, shapes, etc. It can be any of the following: * *A user-defined class*: This should inherit from the IsDescription class (see :ref:`IsDescriptionClassDescr`) where table fields are specified. * *A dictionary*: For example, when you do not know beforehand which structure your table will have). * *A Description instance*: You can use the description attribute of another table to create a new one with the same structure. * *A NumPy dtype*: A completely general structured NumPy dtype. * *A NumPy (structured) array instance*: The dtype of this structured array will be used as the description. Also, in case the array has actual data, it will be injected into the newly created table. .. versionchanged:: 3.0 The *description* parameter can be None (default) if *obj* is provided. In that case the structure of the table is deduced by *obj*. title : str A description for this node (it sets the TITLE HDF5 attribute on disk). filters : Filters An instance of the Filters class (see :ref:`FiltersClassDescr`) that provides information about the desired I/O filters to be applied during the life of this object. expectedrows : int A user estimate of the number of records that will be in the table. If not provided, the default value is EXPECTED_ROWS_TABLE (see :file:`tables/parameters.py`). If you plan to create a bigger table try providing a guess; this will optimize the HDF5 B-Tree creation and management process time and memory used. chunkshape The shape of the data chunk to be read or written in a single HDF5 I/O operation. Filters are applied to those chunks of data. The rank of the chunkshape for tables must be 1. If None, a sensible value is calculated based on the expectedrows parameter (which is recommended). byteorder : str The byteorder of data *on disk*, specified as 'little' or 'big'. If this is not specified, the byteorder is that of the platform, unless you passed an array as the description, in which case its byteorder will be used. createparents : bool Whether to create the needed groups for the parent path to exist (not done by default). obj : python object The recarray to be saved. Accepted types are NumPy record arrays. The *obj* parameter is optional and it can be provided in alternative to the *description* parameter. If both *obj* and *description* are provided they must be consistent with each other. .. versionadded:: 3.0 track_times Whether time data associated with the leaf are recorded (object access time, raw data modification time, metadata change time, object birth time); default True. Semantics of these times depend on their implementation in the HDF5 library: refer to documentation of the H5O_info_t data structure. As of HDF5 1.8.15, only ctime (metadata change time) is implemented. .. versionadded:: 3.4.3 See Also -------- Table : for more information on tables """ if obj is not None: if not isinstance(obj, np.ndarray): raise TypeError("invalid obj parameter %r" % obj) descr, _ = descr_from_dtype(obj.dtype, ptparams=self.params) if ( description is not None and dtype_from_descr(description, ptparams=self.params) != obj.dtype ): raise TypeError( "the desctiption parameter is not consistent " "with the data type of the obj parameter" ) elif description is None: description = descr parentnode = self._get_or_create_path(where, createparents) if description is None: raise ValueError("invalid table description: None") _checkfilters(filters) ptobj = Table( parentnode, name, description=description, title=title, filters=filters, expectedrows=expectedrows, chunkshape=chunkshape, byteorder=byteorder, track_times=track_times, ) if obj is not None: ptobj.append(obj) return ptobj def create_array( self, where: Group | str, name: str, obj: np.ndarray | None = None, title: str = "", byteorder: str | None = None, createparents: bool = False, atom: Atom | None = None, shape: tuple[int, ...] | None = None, track_times: bool = True, ) -> Array: """Create a new array. Parameters ---------- where : str or Group The parent group from which the new array will hang. It can be a path string (for example '/level1/leaf5'), or a Group instance (see :ref:`GroupClassDescr`). name : str The name of the new array obj : python object The array or scalar to be saved. Accepted types are NumPy arrays and scalars, as well as native Python sequences and scalars, provided that values are regular (i.e. they are not like ``[[1,2],2]``) and homogeneous (i.e. all the elements are of the same type). Also, objects that have some of their dimensions equal to 0 are not supported (use an EArray node (see :ref:`EArrayClassDescr`) if you want to store an array with one of its dimensions equal to 0). .. versionchanged:: 3.0 The *Object parameter has been renamed into *obj*.* title : str A description for this node (it sets the TITLE HDF5 attribute on disk). byteorder : str The byteorder of the data *on disk*, specified as 'little' or 'big'. If this is not specified, the byteorder is that of the given object. createparents : bool, optional Whether to create the needed groups for the parent path to exist (not done by default). atom : Atom An Atom (see :ref:`AtomClassDescr`) instance representing the *type* and *shape* of the atomic objects to be saved. .. versionadded:: 3.0 shape : tuple of ints The shape of the stored array. .. versionadded:: 3.0 track_times Whether time data associated with the leaf are recorded (object access time, raw data modification time, metadata change time, object birth time); default True. Semantics of these times depend on their implementation in the HDF5 library: refer to documentation of the H5O_info_t data structure. As of HDF5 1.8.15, only ctime (metadata change time) is implemented. .. versionadded:: 3.4.3 See Also -------- Array : for more information on arrays create_table : for more information on the rest of parameters """ if obj is None: if atom is None or shape is None: raise TypeError( "if the obj parameter is not specified " "(or None) then both the atom and shape " "parametes should be provided." ) else: # Making strides=(0,...) below is a trick to create the # array fast and without memory consumption dflt = np.zeros((), dtype=atom.dtype) obj = np.ndarray( shape, dtype=atom.dtype, buffer=dflt, strides=(0,) * len(shape), ) else: flavor = flavor_of(obj) # use a temporary object because converting obj at this stage # breaks some test. This is solution performs a double, # potentially expensive, conversion of the obj parameter. _obj = array_as_internal(obj, flavor) if shape is not None and shape != _obj.shape: raise TypeError("the shape parameter do not match obj.shape") if atom is not None and atom.dtype != _obj.dtype: raise TypeError( "the atom parameter is not consistent with " "the data type of the obj parameter" ) parentnode = self._get_or_create_path(where, createparents) return Array( parentnode, name, obj=obj, title=title, byteorder=byteorder, track_times=track_times, ) def create_carray( self, where: Group | str, name: str, atom: Atom | None = None, shape: tuple[int, ...] | None = None, title: str = "", filters: Filters | None = None, chunkshape: int | tuple[int, ...] | None = None, byteorder: str | None = None, createparents: bool = False, obj: np.ndarray | None = None, track_times: bool = True, ) -> CArray: """Create a new chunked array. Parameters ---------- where : str or Group The parent group from which the new array will hang. It can be a path string (for example '/level1/leaf5'), or a Group instance (see :ref:`GroupClassDescr`). name : str The name of the new array atom : Atom An Atom (see :ref:`AtomClassDescr`) instance representing the *type* and *shape* of the atomic objects to be saved. .. versionchanged:: 3.0 The *atom* parameter can be None (default) if *obj* is provided. shape : tuple The shape of the new array. .. versionchanged:: 3.0 The *shape* parameter can be None (default) if *obj* is provided. title : str, optional A description for this node (it sets the TITLE HDF5 attribute on disk). filters : Filters, optional An instance of the Filters class (see :ref:`FiltersClassDescr`) that provides information about the desired I/O filters to be applied during the life of this object. chunkshape : tuple or number or None, optional The shape of the data chunk to be read or written in a single HDF5 I/O operation. Filters are applied to those chunks of data. The dimensionality of chunkshape must be the same as that of shape. If None, a sensible value is calculated (which is recommended). byteorder : str, optional The byteorder of the data *on disk*, specified as 'little' or 'big'. If this is not specified, the byteorder is that of the given object. createparents : bool, optional Whether to create the needed groups for the parent path to exist (not done by default). obj : python object The array or scalar to be saved. Accepted types are NumPy arrays and scalars, as well as native Python sequences and scalars, provided that values are regular (i.e. they are not like ``[[1,2],2]``) and homogeneous (i.e. all the elements are of the same type). Also, objects that have some of their dimensions equal to 0 are not supported. Please use an EArray node (see :ref:`EArrayClassDescr`) if you want to store an array with one of its dimensions equal to 0. The *obj* parameter is optional and it can be provided in alternative to the *atom* and *shape* parameters. If both *obj* and *atom* and/or *shape* are provided they must be consistent with each other. .. versionadded:: 3.0 track_times Whether time data associated with the leaf are recorded (object access time, raw data modification time, metadata change time, object birth time); default True. Semantics of these times depend on their implementation in the HDF5 library: refer to documentation of the H5O_info_t data structure. As of HDF5 1.8.15, only ctime (metadata change time) is implemented. .. versionadded:: 3.4.3 See Also -------- CArray : for more information on chunked arrays """ if obj is not None: flavor = flavor_of(obj) obj = array_as_internal(obj, flavor) if shape is not None and shape != obj.shape: raise TypeError("the shape parameter do not match obj.shape") else: shape = obj.shape if atom is not None and atom.dtype != obj.dtype: raise TypeError( "the 'atom' parameter is not consistent with " "the data type of the 'obj' parameter" ) elif atom is None: atom = Atom.from_dtype(obj.dtype) else: if atom is None and shape is None: raise TypeError( "the 'atom' and 'shape' parameters or the 'obj' parameter " "must be provided" ) parentnode = self._get_or_create_path(where, createparents) _checkfilters(filters) ptobj = CArray( parentnode, name, atom=atom, shape=shape, title=title, filters=filters, chunkshape=chunkshape, byteorder=byteorder, track_times=track_times, ) if obj is not None: ptobj[...] = obj return ptobj def create_earray( self, where: Group | str, name: str, atom: Atom | None = None, shape: tuple[int, ...] | None = None, title: str = "", filters: Filters | None = None, expectedrows: int = 1000, chunkshape: int | tuple[int, ...] | None = None, byteorder: str | None = None, createparents: bool = False, obj: np.ndarray | None = None, track_times: bool = True, ) -> EArray: """Create a new enlargeable array. Parameters ---------- where : str or Group The parent group from which the new array will hang. It can be a path string (for example '/level1/leaf5'), or a Group instance (see :ref:`GroupClassDescr`). name : str The name of the new array atom : Atom An Atom (see :ref:`AtomClassDescr`) instance representing the *type* and *shape* of the atomic objects to be saved. .. versionchanged:: 3.0 The *atom* parameter can be None (default) if *obj* is provided. shape : tuple The shape of the new array. One (and only one) of the shape dimensions *must* be 0. The dimension being 0 means that the resulting EArray object can be extended along it. Multiple enlargeable dimensions are not supported right now. .. versionchanged:: 3.0 The *shape* parameter can be None (default) if *obj* is provided. title : str, optional A description for this node (it sets the TITLE HDF5 attribute on disk). filters : Filters, optional An instance of the Filters class (see :ref:`FiltersClassDescr`) that provides information about the desired I/O filters to be applied during the life of this object. expectedrows : int, optional A user estimate about the number of row elements that will be added to the growable dimension in the EArray node. If not provided, the default value is EXPECTED_ROWS_EARRAY (see tables/parameters.py). If you plan to create either a much smaller or a much bigger array try providing a guess; this will optimize the HDF5 B-Tree creation and management process time and the amount of memory used. chunkshape : tuple, numeric, or None, optional The shape of the data chunk to be read or written in a single HDF5 I/O operation. Filters are applied to those chunks of data. The dimensionality of chunkshape must be the same as that of shape (beware: no dimension should be 0 this time!). If None, a sensible value is calculated based on the expectedrows parameter (which is recommended). byteorder : str, optional The byteorder of the data *on disk*, specified as 'little' or 'big'. If this is not specified, the byteorder is that of the platform. createparents : bool, optional Whether to create the needed groups for the parent path to exist (not done by default). obj : python object The array or scalar to be saved. Accepted types are NumPy arrays and scalars, as well as native Python sequences and scalars, provided that values are regular (i.e. they are not like ``[[1,2],2]``) and homogeneous (i.e. all the elements are of the same type). The *obj* parameter is optional and it can be provided in alternative to the *atom* and *shape* parameters. If both *obj* and *atom* and/or *shape* are provided they must be consistent with each other. .. versionadded:: 3.0 track_times Whether time data associated with the leaf are recorded (object access time, raw data modification time, metadata change time, object birth time); default True. Semantics of these times depend on their implementation in the HDF5 library: refer to documentation of the H5O_info_t data structure. As of HDF5 1.8.15, only ctime (metadata change time) is implemented. .. versionadded:: 3.4.3 See Also -------- EArray : for more information on enlargeable arrays """ if obj is not None: flavor = flavor_of(obj) obj = array_as_internal(obj, flavor) earray_shape = (0,) + obj.shape[1:] if shape is not None and shape != earray_shape: raise TypeError( "the shape parameter is not compatible " "with obj.shape." ) else: shape = earray_shape if atom is not None and atom.dtype != obj.dtype: raise TypeError( "the atom parameter is not consistent with " "the data type of the obj parameter" ) elif atom is None: atom = Atom.from_dtype(obj.dtype) parentnode = self._get_or_create_path(where, createparents) _checkfilters(filters) ptobj = EArray( parentnode, name, atom=atom, shape=shape, title=title, filters=filters, expectedrows=expectedrows, chunkshape=chunkshape, byteorder=byteorder, track_times=track_times, ) if obj is not None: ptobj.append(obj) return ptobj def create_vlarray( self, where: Group | str, name: str, atom: Atom | None = None, title: str = "", filters: Filters | None = None, expectedrows: int | None = None, chunkshape: int | tuple[int, ...] | None = None, byteorder: str | None = None, createparents: bool = False, obj: np.ndarray | None = None, track_times: bool = True, ) -> VLArray: """Create a new variable-length array. Parameters ---------- where : str or Group The parent group from which the new array will hang. It can be a path string (for example '/level1/leaf5'), or a Group instance (see :ref:`GroupClassDescr`). name : str The name of the new array atom : Atom An Atom (see :ref:`AtomClassDescr`) instance representing the *type* and *shape* of the atomic objects to be saved. .. versionchanged:: 3.0 The *atom* parameter can be None (default) if *obj* is provided. title : str, optional A description for this node (it sets the TITLE HDF5 attribute on disk). filters : Filters An instance of the Filters class (see :ref:`FiltersClassDescr`) that provides information about the desired I/O filters to be applied during the life of this object. expectedrows : int, optional A user estimate about the number of row elements that will be added to the growable dimension in the `VLArray` node. If not provided, the default value is ``EXPECTED_ROWS_VLARRAY`` (see ``tables/parameters.py``). If you plan to create either a much smaller or a much bigger `VLArray` try providing a guess; this will optimize the HDF5 B-Tree creation and management process time and the amount of memory used. .. versionadded:: 3.0 chunkshape : int or tuple of int, optional The shape of the data chunk to be read or written in a single HDF5 I/O operation. Filters are applied to those chunks of data. The dimensionality of chunkshape must be 1. If None, a sensible value is calculated (which is recommended). byteorder : str, optional The byteorder of the data *on disk*, specified as 'little' or 'big'. If this is not specified, the byteorder is that of the platform. createparents : bool, optional Whether to create the needed groups for the parent path to exist (not done by default). obj : python object The array or scalar to be saved. Accepted types are NumPy arrays and scalars, as well as native Python sequences and scalars, provided that values are regular (i.e. they are not like ``[[1,2],2]``) and homogeneous (i.e. all the elements are of the same type). The *obj* parameter is optional and it can be provided in alternative to the *atom* parameter. If both *obj* and *atom* and are provided they must be consistent with each other. .. versionadded:: 3.0 track_times Whether time data associated with the leaf are recorded (object access time, raw data modification time, metadata change time, object birth time); default True. Semantics of these times depend on their implementation in the HDF5 library: refer to documentation of the H5O_info_t data structure. As of HDF5 1.8.15, only ctime (metadata change time) is implemented. .. versionadded:: 3.4.3 See Also -------- VLArray : for more informationon variable-length arrays .. versionchanged:: 3.0 The *expectedsizeinMB* parameter has been replaced by *expectedrows*. """ if obj is not None: flavor = flavor_of(obj) obj = array_as_internal(obj, flavor) if atom is not None and atom.dtype != obj.dtype: raise TypeError( "the atom parameter is not consistent with " "the data type of the obj parameter" ) if atom is None: atom = Atom.from_dtype(obj.dtype) elif atom is None: raise ValueError("atom parameter cannot be None") parentnode = self._get_or_create_path(where, createparents) _checkfilters(filters) ptobj = VLArray( parentnode, name, atom=atom, title=title, filters=filters, expectedrows=expectedrows, chunkshape=chunkshape, byteorder=byteorder, track_times=track_times, ) if obj is not None: ptobj.append(obj) return ptobj def create_hard_link( self, where: Node | str, name: str, target: Node | str, createparents: bool = False, ) -> Group | Leaf: """Create a hard link. Create a hard link to a `target` node with the given `name` in `where` location. `target` can be a node object or a path string. If `createparents` is true, the intermediate groups required for reaching `where` are created (the default is not doing so). The returned node is a regular `Group` or `Leaf` instance. """ targetnode = self.get_node(target) parentnode = self._get_or_create_path(where, createparents) linkextension._g_create_hard_link(parentnode, name, targetnode) # Refresh children names in link's parent node parentnode._g_add_children_names() # Return the target node return self.get_node(parentnode, name) def create_soft_link( self, where: Node | str, name: str, target: Node | str, createparents: bool = False, ) -> SoftLink: """Create a soft link (aka symbolic link) to a `target` node. Create a soft link (aka symbolic link) to a `target` nodewith the given `name` in `where` location. `target` can be a node object or a path string. If `createparents` is true, the intermediate groups required for reaching `where` are created. (the default is not doing so). The returned node is a SoftLink instance. See the SoftLink class (in :ref:`SoftLinkClassDescr`) for more information on soft links. """ if not isinstance(target, str): if hasattr(target, "_v_pathname"): # quacks like a Node target = target._v_pathname else: raise ValueError( "`target` has to be a string or a node object" ) parentnode = self._get_or_create_path(where, createparents) slink = SoftLink(parentnode, name, target) # Refresh children names in link's parent node parentnode._g_add_children_names() return slink def create_external_link( self, where: Node | str, name: str, target: Node | str, createparents: bool = False, ) -> ExternalLink: """Create an external link. Create an external link to a *target* node with the given *name* in *where* location. *target* can be a node object in another file or a path string in the form 'file:/path/to/node'. If *createparents* is true, the intermediate groups required for reaching *where* are created (the default is not doing so). The returned node is an :class:`ExternalLink` instance. """ if not isinstance(target, str): if hasattr(target, "_v_pathname"): # quacks like a Node target = target._v_file.filename + ":" + target._v_pathname else: raise ValueError( "`target` has to be a string or a node object" ) elif target.find(":/") == -1: raise ValueError("`target` must expressed as 'file:/path/to/node'") parentnode = self._get_or_create_path(where, createparents) elink = ExternalLink(parentnode, name, target) # Refresh children names in link's parent node parentnode._g_add_children_names() return elink def _get_node(self, nodepath: str) -> Node | RootGroup: # The root node is always at hand. if nodepath == "/": return self.root node = self._node_manager.get_node(nodepath) assert node is not None, "unable to instantiate node ``%s``" % nodepath return node def get_node( self, where: Node | str, name: str | None = None, classname: str | None = None, ) -> Node: """Get the node under where with the given name. Parameters ---------- where : str or Node This can be a path string leading to a node or a Node instance (see :ref:`NodeClassDescr`). If no name is specified, that node is returned. .. note:: If where is a Node instance from a different file than the one on which this function is called, the returned node will also be from that other file. name : str, optional If a name is specified, this must be a string with the name of a node under where. In this case the where argument can only lead to a Group (see :ref:`GroupClassDescr`) instance (else a TypeError is raised). The node called name under the group where is returned. classname : str, optional If the classname argument is specified, it must be the name of a class derived from Node (e.g. Table). If the node is found but it is not an instance of that class, a NoSuchNodeError is also raised. Notes ----- If the node to be returned does not exist, a NoSuchNodeError is raised. Please note that hidden nodes are also considered. """ self._check_open() if isinstance(where, Node): where._g_check_open() basepath = where._v_pathname nodepath = join_path(basepath, name or "") or "/" node = where._v_file._get_node(nodepath) elif isinstance(where, (str, np.str_)): if not where.startswith("/"): raise NameError("``where`` must start with a slash ('/')") basepath = where nodepath = join_path(basepath, name or "") or "/" node = self._get_node(nodepath) else: raise TypeError(f"``where`` must be a string or a node: {where!r}") # Finally, check whether the desired node is an instance # of the expected class. if classname: class_ = get_class_by_name(classname) if not isinstance(node, class_): npathname = node._v_pathname nclassname = node.__class__.__name__ # This error message is right since it can never be shown # for ``classname in [None, 'Node']``. raise NoSuchNodeError( "could not find a ``%s`` node at ``%s``; " "instead, a ``%s`` node has been found there" % (classname, npathname, nclassname) ) return node def is_visible_node(self, path: str) -> bool: """Return True if the node under `path` is visible. If the node does not exist, a NoSuchNodeError is raised. """ # ``util.isvisiblepath()`` is still recommended for internal use. return self.get_node(path)._f_isvisible() def rename_node( self, where: Node | str, newname: str, name: str | None = None, overwrite: bool = False, ) -> None: """Change the name of the node specified by where and name to newname. Parameters ---------- where, name These arguments work as in :meth:`File.get_node`, referencing the node to be acted upon. newname : str The new name to be assigned to the node (a string). overwrite : bool Whether to recursively remove a node with the same newname if it already exists (not done by default). """ obj = self.get_node(where, name=name) obj._f_rename(newname, overwrite) def move_node( self, where: Node | str, newparent: Group | str | None = None, newname: str | None = None, name: str | None = None, overwrite: bool = False, createparents: bool = False, ) -> None: """Move the node specified by where and name to newparent/newname. Parameters ---------- where, name : path These arguments work as in :meth:`File.get_node`, referencing the node to be acted upon. newparent The destination group the node will be moved into (a path name or a Group instance). If it is not specified or None, the current parent group is chosen as the new parent. newname The new name to be assigned to the node in its destination (a string). If it is not specified or None, the current name is chosen as the new name. overwrite : bool, optional Whether to allow moving over another node, in which case that node is recursively removed before moving (not done by default). createparents : bool, optional If True, any necessary parents of newparent will be created. Defaults to False. Notes ----- The other arguments work as in :meth:`Node._f_move`. """ obj = self.get_node(where, name=name) obj._f_move(newparent, newname, overwrite, createparents) def copy_node( self, where: Node | str, newparent: Group | str | None = None, newname: str | None = None, name: str | None = None, overwrite: bool = False, recursive: bool = False, createparents: bool = False, **kwargs, ) -> Node: """Copy the node specified by where and name to newparent/newname. Parameters ---------- where : str These arguments work as in :meth:`File.get_node`, referencing the node to be acted upon. newparent : str or Group The destination group that the node will be copied into (a path name or a Group instance). If not specified or None, the current parent group is chosen as the new parent. newname : str The name to be assigned to the new copy in its destination (a string). If it is not specified or None, the current name is chosen as the new name. name : str These arguments work as in :meth:`File.get_node`, referencing the node to be acted upon. overwrite : bool, optional If True, the destination group will be overwritten if it already exists. Defaults to False. recursive : bool, optional If True, all descendant nodes of the node to be acted upon are recursively copied. Defaults to False. createparents : bool, optional If True, any necessary parents of newparent will be created. Defaults to False. kwargs Additional keyword arguments can be used to customize the copying process. See the documentation of :meth:`Group._f_copy` for a description of those arguments. Returns ------- node : Node The newly created copy of the source node (i.e. the destination node). See :meth:`.Node._f_copy` for further details on the semantics of copying nodes. """ obj = self.get_node(where, name=name) if obj._v_depth == 0 and newparent and not newname: npobj = self.get_node(newparent) if obj._v_file is not npobj._v_file: # Special case for copying file1:/ --> file2:/path self.root._f_copy_children( npobj, overwrite=overwrite, recursive=recursive, **kwargs ) return npobj else: raise OSError( "You cannot copy a root group over the same file" ) return obj._f_copy( newparent, newname, overwrite, recursive, createparents, **kwargs ) def remove_node( self, where: Node | str, name: str | None = None, recursive: bool = False, ) -> None: """Remove the object node *name* under *where* location. Parameters ---------- where, name These arguments work as in :meth:`File.get_node`, referencing the node to be acted upon. recursive : bool If not supplied or false, the node will be removed only if it has no children; if it does, a NodeError will be raised. If supplied with a true value, the node and all its descendants will be completely removed. """ obj = self.get_node(where, name=name) obj._f_remove(recursive) def get_node_attr( self, where: Node | str, attrname: str, name: str | None = None ) -> Any: """Get a PyTables attribute from the given node. Parameters ---------- where, name These arguments work as in :meth:`File.get_node`, referencing the node to be acted upon. attrname The name of the attribute to retrieve. If the named attribute does not exist, an AttributeError is raised. """ obj = self.get_node(where, name=name) return obj._f_getattr(attrname) def set_node_attr( self, where: Node | str, attrname: str, attrvalue: Any, name: str | None = None, ) -> None: """Set a PyTables attribute for the given node. Parameters ---------- where, name These arguments work as in :meth:`File.get_node`, referencing the node to be acted upon. attrname The name of the attribute to set. attrvalue The value of the attribute to set. Any kind of Python object (like strings, ints, floats, lists, tuples, dicts, small NumPy objects ...) can be stored as an attribute. However, if necessary, pickle is automatically used so as to serialize objects that you might want to save. See the :class:`AttributeSet` class for details. Notes ----- If the node already has a large number of attributes, a PerformanceWarning is issued. """ obj = self.get_node(where, name=name) obj._f_setattr(attrname, attrvalue) def del_node_attr( self, where: Node | str, attrname: str, name: str | None = None ) -> None: """Delete a PyTables attribute from the given node. Parameters ---------- where, name These arguments work as in :meth:`File.get_node`, referencing the node to be acted upon. attrname The name of the attribute to delete. If the named attribute does not exist, an AttributeError is raised. """ obj = self.get_node(where, name=name) obj._f_delattr(attrname) def copy_node_attrs( self, where: Node | str, dstnode: Node | str, name: str | None = None ) -> None: """Copy PyTables attributes from one node to another. Parameters ---------- where, name These arguments work as in :meth:`File.get_node`, referencing the node to be acted upon. dstnode The destination node where the attributes will be copied to. It can be a path string or a Node instance (see :ref:`NodeClassDescr`). """ srcobject = self.get_node(where, name=name) dstobject = self.get_node(dstnode) srcobject._v_attrs._f_copy(dstobject) def copy_children( self, srcgroup: str, dstgroup: str, overwrite: bool = False, recursive: bool = False, createparents: bool = False, **kwargs, ) -> None: """Copy the children of a group into another group. Parameters ---------- srcgroup : str The group to copy from. dstgroup : str The destination group. overwrite : bool, optional If True, the destination group will be overwritten if it already exists. Defaults to False. recursive : bool, optional If True, all descendant nodes of srcgroup are recursively copied. Defaults to False. createparents : bool, optional If True, any necessary parents of dstgroup will be created. Defaults to False. kwargs : dict Additional keyword arguments can be used to customize the copying process. See the documentation of :meth:`Group._f_copy_children` for a description of those arguments. """ srcgroup = self.get_node(srcgroup) # Does the source node exist? self._check_group(srcgroup) # Is it a group? srcgroup._f_copy_children( dstgroup, overwrite, recursive, createparents, **kwargs ) def copy_file( self, dstfilename: str, overwrite: bool = False, **kwargs ) -> None: """Copy the contents of this file to dstfilename. Parameters ---------- dstfilename : str A path string indicating the name of the destination file. If it already exists, the copy will fail with an IOError, unless the overwrite argument is true. overwrite : bool, optional If true, the destination file will be overwritten if it already exists. In this case, the destination file must be closed, or errors will occur. Defaults to False. kwargs Additional keyword arguments discussed below. Notes ----- Additional keyword arguments may be passed to customize the copying process. For instance, title and filters may be changed, user attributes may be or may not be copied, data may be sub-sampled, stats may be collected, etc. Arguments unknown to nodes are simply ignored. Check the documentation for copying operations of nodes to see which options they support. In addition, it recognizes the names of parameters present in :file:`tables/parameters.py` as additional keyword arguments. See :ref:`parameter_files` for a detailed info on the supported parameters. Copying a file usually has the beneficial side effect of creating a more compact and cleaner version of the original file. """ self._check_open() # Check that we are not treading our own shoes if Path(self.filename).resolve() == Path(dstfilename).resolve(): raise OSError("You cannot copy a file over itself") # Compute default arguments. # These are *not* passed on. filters = kwargs.pop("filters", None) if filters is None: # By checking the HDF5 attribute, we avoid setting filters # in the destination file if not explicitly set in the # source file. Just by assigning ``self.filters`` we would # not be able to tell. filters = getattr(self.root._v_attrs, "FILTERS", None) copyuserattrs = kwargs.get("copyuserattrs", True) title = kwargs.pop("title", self.title) if Path(dstfilename).is_file() and not overwrite: raise OSError( f"file ``{dstfilename}`` already exists; you may want to " f"use the ``overwrite`` argument" ) # Create destination file, overwriting it. dstfileh = open_file( dstfilename, mode="w", title=title, filters=filters, **kwargs ) try: # Maybe copy the user attributes of the root group. if copyuserattrs: self.root._v_attrs._f_copy(dstfileh.root) # Copy the rest of the hierarchy. self.root._f_copy_children(dstfileh.root, recursive=True, **kwargs) finally: dstfileh.close() def list_nodes( self, where: Node | str, classname: str | None = None ) -> list[Node]: """Return a *list* with children nodes hanging from where. This is a list-returning version of :meth:`File.iter_nodes`. """ group = self.get_node(where) # Does the parent exist? self._check_group(group) # Is it a group? return group._f_list_nodes(classname) def iter_nodes( self, where: Node | str, classname: str | None = None ) -> Generator[Node]: """Iterate over children nodes hanging from where. Parameters ---------- where This argument works as in :meth:`File.get_node`, referencing the node to be acted upon. classname If the name of a class derived from Node (see :ref:`NodeClassDescr`) is supplied, only instances of that class (or subclasses of it) will be returned. Notes ----- The returned nodes are alphanumerically sorted by their name. This is an iterator version of :meth:`File.list_nodes`. """ group = self.get_node(where) # Does the parent exist? self._check_group(group) # Is it a group? return group._f_iter_nodes(classname) def __contains__(self, path: str) -> bool: """Return True if there is a node with the specified path. Returns True if the file has a node with the given path (a string), False otherwise. """ try: self.get_node(path) except NoSuchNodeError: return False else: return True def __iter__(self) -> Generator[Node]: """Recursively iterate over the nodes in the tree. This is equivalent to calling :meth:`File.walk_nodes` with no arguments. Examples -------- :: # Recursively list all the nodes in the object tree. h5file = tables.open_file('vlarray1.h5') print("All nodes in the object tree:") for node in h5file: print(node) """ return self.walk_nodes("/") def walk_nodes( self, where: Group | str = "/", classname: str | None = None ) -> Generator[Node]: """Recursively iterate over nodes hanging from where. Parameters ---------- where : str or Group, optional If supplied, the iteration starts from (and includes) this group. It can be a path string or a Group instance (see :ref:`GroupClassDescr`). classname If the name of a class derived from Node (see :ref:`GroupClassDescr`) is supplied, only instances of that class (or subclasses of it) will be returned. Notes ----- This version iterates over the leaves in the same group in order to avoid having a list referencing to them and thus, preventing the LRU cache to remove them after their use. Examples -------- :: # Recursively print all the nodes hanging from '/detector'. print("Nodes hanging from group '/detector':") for node in h5file.walk_nodes('/detector', classname='EArray'): print(node) """ class_ = get_class_by_name(classname) if class_ is Group: # only groups yield from self.walk_groups(where) elif class_ is Node: # all nodes yield self.get_node(where) for group in self.walk_groups(where): yield from self.iter_nodes(group) else: # only nodes of the named type for group in self.walk_groups(where): yield from self.iter_nodes(group, classname) def walk_groups(self, where: Group | str = "/") -> Generator[Group]: """Recursively iterate over groups (not leaves) hanging from where. The where group itself is listed first (preorder), then each of its child groups (following an alphanumerical order) is also traversed, following the same procedure. If where is not supplied, the root group is used. The where argument can be a path string or a Group instance (see :ref:`GroupClassDescr`). """ group = self.get_node(where) # Does the parent exist? self._check_group(group) # Is it a group? return group._f_walk_groups() def _check_open(self) -> None: """Check the state of the file. If the file is closed, a `ClosedFileError` is raised. """ if not self.isopen: raise ClosedFileError("the file object is closed") def _iswritable(self) -> bool: """Return True if the file is writable.""" return self.mode in ("w", "a", "r+") def _check_writable(self) -> None: """Check whether the file is writable. If the file is not writable, a `FileModeError` is raised. """ if not self._iswritable(): raise FileModeError("the file is not writable") def _check_group(self, node: Group) -> None: # `node` must already be a node. if not isinstance(node, Group): raise TypeError(f"node ``{node._v_pathname}`` is not a group") def is_undo_enabled(self) -> bool: """Return True uf the Undo/Redo mechanism is enabled. Returns True if the Undo/Redo mechanism has been enabled for this file, False otherwise. Please note that this mechanism is persistent, so a newly opened PyTables file may already have Undo/Redo support enabled. """ self._check_open() return self._undoEnabled def _check_undo_enabled(self) -> None: if not self._undoEnabled: raise UndoRedoError("Undo/Redo feature is currently disabled!") def _create_transaction_group(self) -> TransactionGroupG: tgroup = TransactionGroupG( self.root, _trans_group_name, "Transaction information container", new=True, ) # The format of the transaction container. tgroup._v_attrs._g__setattr("FORMATVERSION", _trans_version) return tgroup def _create_transaction( self, troot: TransactionGroupG, tid: int ) -> TransactionG: return TransactionG( troot, _trans_name % tid, f"Transaction number {tid}", new=True ) def _create_mark(self, trans: TransactionG, mid: int) -> MarkG: return MarkG(trans, _mark_name % mid, "Mark number %d" % mid, new=True) def enable_undo(self, filters: Filters = Filters(complevel=1)) -> None: """Enable the Undo/Redo mechanism. This operation prepares the database for undoing and redoing modifications in the node hierarchy. This allows :meth:`File.mark`, :meth:`File.undo`, :meth:`File.redo` and other methods to be called. The filters argument, when specified, must be an instance of class Filters (see :ref:`FiltersClassDescr`) and is meant for setting the compression values for the action log. The default is having compression enabled, as the gains in terms of space can be considerable. You may want to disable compression if you want maximum speed for Undo/Redo operations. Calling this method when the Undo/Redo mechanism is already enabled raises an UndoRedoError. """ maxundo = self.params["MAX_UNDO_PATH_LENGTH"] class ActionLog(NotLoggedMixin, Table): pass class ActionLogDesc(IsDescription): opcode = UInt8Col(pos=0) arg1 = StringCol(maxundo, pos=1, dflt=b"") arg2 = StringCol(maxundo, pos=2, dflt=b"") self._check_open() # Enabling several times is not allowed to avoid the user having # the illusion that a new implicit mark has been created # when calling enable_undo for the second time. if self.is_undo_enabled(): raise UndoRedoError("Undo/Redo feature is already enabled!") self._markers: dict[str, int] = {} self._seqmarkers: list[int] = [] self._nmarks = 0 self._curtransaction = 0 self._curmark = -1 # No marks yet # Get the Group for keeping user actions try: tgroup = self.get_node(_trans_group_path) except NodeError: # The file is going to be changed. self._check_writable() # A transaction log group does not exist. Create it tgroup = self._create_transaction_group() # Create a transaction. self._trans = self._create_transaction( tgroup, self._curtransaction ) # Create an action log self._actionlog = ActionLog( tgroup, _action_log_name, ActionLogDesc, "Action log", filters=filters, ) # Create an implicit mark self._actionlog.append([(_op_to_code["MARK"], str(0), "")]) self._nmarks += 1 self._seqmarkers.append(0) # current action is 0 # Create a group for mark 0 self._create_mark(self._trans, 0) # Initialize the marker pointer self._curmark = int(self._nmarks - 1) # Initialize the action pointer self._curaction = self._actionlog.nrows - 1 else: # The group seems to exist already # Get the default transaction self._trans = tgroup._f_get_child( _trans_name % self._curtransaction ) # Open the action log and go to the end of it self._actionlog = tgroup.actionlog for row in self._actionlog: if row["opcode"] == _op_to_code["MARK"]: name = row["arg2"].decode("utf-8") self._markers[name] = self._nmarks self._seqmarkers.append(row.nrow) self._nmarks += 1 # Get the current mark and current action self._curmark = int(self._actionlog.attrs.CURMARK) self._curaction = self._actionlog.attrs.CURACTION # The Undo/Redo mechanism has been enabled. self._undoEnabled = True def disable_undo(self) -> None: """Disable the Undo/Redo mechanism. Disabling the Undo/Redo mechanism leaves the database in the current state and forgets past and future database states. This makes :meth:`File.mark`, :meth:`File.undo`, :meth:`File.redo` and other methods fail with an UndoRedoError. Calling this method when the Undo/Redo mechanism is already disabled raises an UndoRedoError. """ self._check_open() if not self.is_undo_enabled(): raise UndoRedoError("Undo/Redo feature is already disabled!") # The file is going to be changed. self._check_writable() del self._markers del self._seqmarkers del self._curmark del self._curaction del self._curtransaction del self._nmarks del self._actionlog # Recursively delete the transaction group tnode = self.get_node(_trans_group_path) tnode._g_remove(recursive=1) # The Undo/Redo mechanism has been disabled. self._undoEnabled = False def mark(self, name: str | None = None) -> int: """Mark the state of the database. Creates a mark for the current state of the database. A unique (and immutable) identifier for the mark is returned. An optional name (a string) can be assigned to the mark. Both the identifier of a mark and its name can be used in :meth:`File.undo` and :meth:`File.redo` operations. When the name has already been used for another mark, an UndoRedoError is raised. This method can only be called when the Undo/Redo mechanism has been enabled. Otherwise, an UndoRedoError is raised. """ self._check_open() self._check_undo_enabled() if name is None: name = "" else: if not isinstance(name, str): raise TypeError( "Only strings are allowed as mark names. " "You passed object: '%s'" % name ) if name in self._markers: raise UndoRedoError( "Name '%s' is already used as a marker " "name. Try another one." % name ) # The file is going to be changed. self._check_writable() self._markers[name] = self._curmark + 1 # Create an explicit mark # Insert the mark in the action log self._log("MARK", str(self._curmark + 1), name) self._curmark += 1 self._nmarks = self._curmark + 1 self._seqmarkers.append(self._curaction) # Create a group for the current mark self._create_mark(self._trans, self._curmark) return self._curmark def _log(self, action: str, *args) -> None: """Log an action. The `action` must be an all-uppercase string identifying it. Arguments must also be strings. This method should be called once the action has been completed. This method can only be called when the Undo/Redo mechanism has been enabled. Otherwise, an `UndoRedoError` is raised. """ assert self.is_undo_enabled() maxundo = self.params["MAX_UNDO_PATH_LENGTH"] # Check whether we are at the end of the action log or not if self._curaction != self._actionlog.nrows - 1: # We are not, so delete the trailing actions self._actionlog.remove_rows( self._curaction + 1, self._actionlog.nrows ) # Reset the current marker group mnode = self.get_node( _mark_path % (self._curtransaction, self._curmark) ) mnode._g_reset() # Delete the marker groups with backup objects for mark in range(self._curmark + 1, self._nmarks): mnode = self.get_node( _mark_path % (self._curtransaction, mark) ) mnode._g_remove(recursive=1) # Update the new number of marks self._nmarks = self._curmark + 1 self._seqmarkers = self._seqmarkers[: self._nmarks] if action not in _op_to_code: # INTERNAL raise UndoRedoError( "Action ``%s`` not in ``_op_to_code`` " "dictionary: %r" % (action, _op_to_code) ) arg1 = "" arg2 = "" if len(args) <= 1: arg1 = args[0] elif len(args) <= 2: arg1 = args[0] arg2 = args[1] else: # INTERNAL raise UndoRedoError( "Too many parameters for action log: " "%r" ).with_traceback(args) if len(arg1) > maxundo or len(arg2) > maxundo: # INTERNAL raise UndoRedoError( "Parameter arg1 or arg2 is too long: " "(%r, %r)" % (arg1, arg2) ) # print("Logging-->", (action, arg1, arg2)) self._actionlog.append( [(_op_to_code[action], arg1.encode("utf-8"), arg2.encode("utf-8"))] ) self._curaction += 1 def _get_mark_id(self, mark: int | str) -> int: """Get an integer markid from a mark sequence number or name.""" if isinstance(mark, int): markid = mark elif isinstance(mark, str): if mark not in self._markers: lmarkers = sorted(self._markers) raise UndoRedoError( "The mark that you have specified has not " "been found in the internal marker list: " "%r" % lmarkers ) markid = self._markers[mark] else: raise TypeError( "Parameter mark can only be an integer or a " "string, and you passed a type <%s>" % type(mark) ) # print("markid, self._nmarks:", markid, self._nmarks) return markid def _get_final_action(self, markid: int) -> int: """Get the action to go. It does not touch the self private attributes """ if markid > self._nmarks - 1: # The required mark is beyond the end of the action log # The final action is the last row return self._actionlog.nrows elif markid <= 0: # The required mark is the first one # return the first row return 0 return self._seqmarkers[markid] def _doundo(self, finalaction: int, direction: int) -> None: """Undo/Redo actions up to final action in the specified direction.""" if direction < 0: actionlog = self._actionlog[finalaction + 1 : self._curaction + 1][ ::-1 ] else: actionlog = self._actionlog[self._curaction : finalaction] # Uncomment this for debugging # print("curaction, finalaction, direction", \ # self._curaction, finalaction, direction) for i in range(len(actionlog)): if actionlog["opcode"][i] != _op_to_code["MARK"]: # undo/redo the action if direction > 0: # Uncomment this for debugging # print("redo-->", \ # _code_to_op[actionlog['opcode'][i]],\ # actionlog['arg1'][i],\ # actionlog['arg2'][i]) undoredo.redo( self, # _code_to_op[actionlog['opcode'][i]], # The next is a workaround for python < 2.5 _code_to_op[int(actionlog["opcode"][i])], actionlog["arg1"][i].decode("utf8"), actionlog["arg2"][i].decode("utf8"), ) else: # Uncomment this for debugging # print("undo-->", \ # _code_to_op[actionlog['opcode'][i]],\ # actionlog['arg1'][i].decode('utf8'),\ # actionlog['arg2'][i].decode('utf8')) undoredo.undo( self, # _code_to_op[actionlog['opcode'][i]], # The next is a workaround for python < 2.5 _code_to_op[int(actionlog["opcode"][i])], actionlog["arg1"][i].decode("utf8"), actionlog["arg2"][i].decode("utf8"), ) else: if direction > 0: self._curmark = int(actionlog["arg1"][i]) else: self._curmark = int(actionlog["arg1"][i]) - 1 # Protection against negative marks if self._curmark < 0: self._curmark = 0 self._curaction += direction def undo(self, mark: int | str | None = None) -> None: """Go to a past state of the database. Returns the database to the state associated with the specified mark. Both the identifier of a mark and its name can be used. If the mark is omitted, the last created mark is used. If there are no past marks, or the specified mark is not older than the current one, an UndoRedoError is raised. This method can only be called when the Undo/Redo mechanism has been enabled. Otherwise, an UndoRedoError is raised. """ self._check_open() self._check_undo_enabled() # print("(pre)UNDO: (curaction, curmark) = (%s,%s)" % \ # (self._curaction, self._curmark)) if mark is None: markid = self._curmark # Correction if we are settled on top of a mark opcode = self._actionlog.cols.opcode if opcode[self._curaction] == _op_to_code["MARK"]: markid -= 1 else: # Get the mark ID number markid = self._get_mark_id(mark) # Get the final action ID to go finalaction = self._get_final_action(markid) if finalaction > self._curaction: raise UndoRedoError( "Mark ``%s`` is newer than the current mark. " "Use `redo()` or `goto()` instead." % (mark,) ) # The file is going to be changed. self._check_writable() # Try to reach this mark by unwinding actions in the log self._doundo(finalaction - 1, -1) if self._curaction < self._actionlog.nrows - 1: self._curaction += 1 self._curmark = int(self._actionlog.cols.arg1[self._curaction]) # print("(post)UNDO: (curaction, curmark) = (%s,%s)" % \ # (self._curaction, self._curmark)) def redo(self, mark: int | str | None = None) -> None: """Go to a future state of the database. Returns the database to the state associated with the specified mark. Both the identifier of a mark and its name can be used. If the `mark` is omitted, the next created mark is used. If there are no future marks, or the specified mark is not newer than the current one, an UndoRedoError is raised. This method can only be called when the Undo/Redo mechanism has been enabled. Otherwise, an UndoRedoError is raised. """ self._check_open() self._check_undo_enabled() # print("(pre)REDO: (curaction, curmark) = (%s, %s)" % \ # (self._curaction, self._curmark)) if self._curaction >= self._actionlog.nrows - 1: # We are at the end of log, so no action return if mark is None: mark = self._curmark + 1 elif mark == -1: mark = int(self._nmarks) # Go beyond the mark bounds up to the end # Get the mark ID number markid = self._get_mark_id(mark) finalaction = self._get_final_action(markid) if finalaction < self._curaction + 1: raise UndoRedoError( "Mark ``%s`` is older than the current mark. " "Use `redo()` or `goto()` instead." % (mark,) ) # The file is going to be changed. self._check_writable() # Get the final action ID to go self._curaction += 1 # Try to reach this mark by redoing the actions in the log self._doundo(finalaction, 1) # Increment the current mark only if we are not at the end of marks if self._curmark < self._nmarks - 1: self._curmark += 1 if self._curaction > self._actionlog.nrows - 1: self._curaction = self._actionlog.nrows - 1 # print("(post)REDO: (curaction, curmark) = (%s,%s)" % \ # (self._curaction, self._curmark)) def goto(self, mark: int | str) -> None: """Go to a specific mark of the database. Returns the database to the state associated with the specified mark. Both the identifier of a mark and its name can be used. This method can only be called when the Undo/Redo mechanism has been enabled. Otherwise, an UndoRedoError is raised. """ self._check_open() self._check_undo_enabled() if mark == -1: # Special case mark = self._nmarks # Go beyond the mark bounds up to the end # Get the mark ID number markid = self._get_mark_id(mark) finalaction = self._get_final_action(markid) if finalaction < self._curaction: self.undo(mark) else: self.redo(mark) def get_current_mark(self) -> int: """Get the identifier of the current mark. Returns the identifier of the current mark. This can be used to know the state of a database after an application crash, or to get the identifier of the initial implicit mark after a call to :meth:`File.enable_undo`. This method can only be called when the Undo/Redo mechanism has been enabled. Otherwise, an UndoRedoError is raised. """ self._check_open() self._check_undo_enabled() return self._curmark def _shadow_name(self) -> tuple[Node, str]: """Compute and return a shadow name. Computes the current shadow name according to the current transaction, mark and action. It returns a tuple with the shadow parent node and the name of the shadow in it. """ parent = self.get_node( _shadow_parent % (self._curtransaction, self._curmark) ) name = _shadow_name % (self._curaction,) return (parent, name) def flush(self) -> None: """Flush all the alive leaves in the object tree.""" self._check_open() # Flush the cache to disk self._node_manager.flush_nodes() self._flush_file(0) # 0 means local scope, 1 global (virtual) scope def close(self) -> None: """Flush all the alive leaves in object tree and close the file.""" # If the file is already closed, return immediately if not self.isopen: return # If this file has been opened more than once, decrease the # counter and return if self._open_count > 1: self._open_count -= 1 return filename = self.filename if self._undoEnabled and self._iswritable(): # Save the current mark and current action self._actionlog.attrs._g__setattr("CURMARK", self._curmark) self._actionlog.attrs._g__setattr("CURACTION", self._curaction) # Close all loaded nodes. self.root._f_close() self._node_manager.shutdown() # Post-conditions assert ( len(self._node_manager.cache) == 0 ), "cached nodes remain after closing: %s" % list( self._node_manager.cache ) # No other nodes should have been revived. assert ( len(self._node_manager.registry) == 0 ), "alive nodes remain after closing: %s" % list( self._node_manager.registry ) # Close the file self._close_file() # After the objects are disconnected, destroy the # object dictionary using the brute force ;-) # This should help to the garbage collector self.__dict__.clear() # Set the flag to indicate that the file is closed self.isopen = 0 # Restore the filename attribute that is used by _FileRegistry self.filename = filename # Delete the entry from the registry of opened files _open_files.remove(self) def __enter__(self) -> File: """Enter a context and return the same file.""" return self def __exit__(self, *exc_info) -> bool: """Exit a context and close the file.""" self.close() return False # do not hide exceptions def __str__(self) -> str: """Return a short string representation of the object tree. Examples -------- :: >>> import tables >>> f = tables.open_file('tables/tests/Tables_lzo2.h5') >>> print(f) tables/tests/Tables_lzo2.h5 (File) 'Table Benchmark' Last modif.: '...' Object Tree: / (RootGroup) 'Table Benchmark' /tuple0 (Table(100,)lzo(1)) 'This is the table title' /group0 (Group) '' /group0/tuple1 (Table(100,)lzo(1)) 'This is the table title' /group0/group1 (Group) '' /group0/group1/tuple2 (Table(100,)lzo(1)) 'This is the table title' /group0/group1/group2 (Group) '' >>> f.close() """ if not self.isopen: return "" # Print all the nodes (Group and Leaf objects) on object tree try: date = datetime.datetime.fromtimestamp( Path(self.filename).stat().st_mtime, datetime.UTC ).isoformat(timespec="seconds") except OSError: # in-memory file date = "" lines = [ f"{self.filename} (File) {self.title!r}", f"Last modif.: {date!r}", "Object Tree: ", ] for group in self.walk_groups("/"): lines.append(f"{group}") for kind in self._node_kinds[1:]: for node in self.list_nodes(group, kind): lines.append(f"{node}") return "\n".join(lines) + "\n" def __repr__(self) -> str: """Return a detailed string representation of the object tree.""" if not self.isopen: return "" # Print all the nodes (Group and Leaf objects) on object tree lines = [ f"File(filename={self.filename!s}, title={self.title!r}, " f"mode={self.mode!r}, root_uep={self.root_uep!r}, " f"filters={self.filters!r})" ] for group in self.walk_groups("/"): lines.append(f"{group}") for kind in self._node_kinds[1:]: for node in self.list_nodes(group, kind): lines.append(f"{node!r}") return "\n".join(lines) + "\n" def _update_node_locations(self, oldpath: str, newpath: str) -> None: """Update location information of nodes under `oldpath`. This only affects *already loaded* nodes. """ oldprefix = oldpath + "/" # root node can not be renamed, anyway oldprefix_len = len(oldprefix) # Update alive and dead descendents. for cache in [self._node_manager.cache, self._node_manager.registry]: for nodepath in list(cache): if nodepath.startswith(oldprefix) and nodepath != oldprefix: nodesuffix = nodepath[oldprefix_len:] newnodepath = join_path(newpath, nodesuffix) newnodeppath = split_path(newnodepath)[0] descendent_node = self._get_node(nodepath) descendent_node._g_update_location(newnodeppath) # If a user hits ^C during a run, it is wise to gracefully close the # opened files. atexit.register(_open_files.close_all)