Source code for satpy.dependency_tree

#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright (c) 2020 Satpy developers
# This file is part of satpy.
# satpy is free software: you can redistribute it and/or modify it under the
# terms of the GNU General Public License as published by the Free Software
# Foundation, either version 3 of the License, or (at your option) any later
# version.
# satpy is distributed in the hope that it will be useful, but WITHOUT ANY
# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR
# A PARTICULAR PURPOSE.  See the GNU General Public License for more details.
# You should have received a copy of the GNU General Public License along with
# satpy.  If not, see <>.
"""Implementation of a dependency tree."""

import numpy as np

from satpy.dataset import create_filtered_query, ModifierTuple
from satpy.dataset.data_dict import TooManyResults, get_key
from satpy.node import CompositorNode, Node, EMPTY_LEAF_NAME, MissingDependencies, LOG, ReaderNode

[docs]class Tree: """A tree implementation.""" # simplify future logic by only having one "sentinel" empty node # making it a class attribute ensures it is the same across instances empty_node = Node(EMPTY_LEAF_NAME) def __init__(self): """Set up the tree.""" self._root = Node(None) # keep a flat dictionary of nodes contained in the tree for better # __contains__ self._all_nodes = _DataIDContainer()
[docs] def leaves(self, nodes=None, unique=True): """Get the leaves of the tree starting at the root. Args: nodes (iterable): limit leaves for these node names unique: only include individual leaf nodes once Returns: list of leaf nodes """ if nodes is None: return self._root.leaves(unique=unique) res = list() for child_id in nodes: for sub_child in self._all_nodes[child_id].leaves(unique=unique): if not unique or sub_child not in res: res.append(sub_child) return res
[docs] def trunk(self, nodes=None, unique=True): """Get the trunk nodes of the tree starting at this root. Args: nodes (iterable): limit trunk nodes to the names specified or the children of them that are also trunk nodes. unique: only include individual trunk nodes once Returns: list of trunk nodes """ if nodes is None: return self._root.trunk(unique=unique) res = list() for child_id in nodes: for sub_child in self._all_nodes[child_id].trunk(unique=unique): if not unique or sub_child not in res: res.append(sub_child) return res
[docs] def add_child(self, parent, child): """Add a child to the tree.""" Node.add_child(parent, child) # Sanity check: Node objects should be unique. They can be added # multiple times if more than one Node depends on them # but they should all map to the same Node object. if self.contains( assert self._all_nodes[] is child if child is self.empty_node: # No need to store "empty" nodes return self._all_nodes[] = child
[docs] def add_leaf(self, ds_id, parent=None): """Add a leaf to the tree.""" if parent is None: parent = self._root try: node = self[ds_id] except KeyError: node = Node(ds_id) self.add_child(parent, node) return node
def __contains__(self, item): """Check if a item is in the tree.""" return item in self._all_nodes def __getitem__(self, item): """Get an item of the tree.""" return self._all_nodes[item]
[docs] def contains(self, item): """Check contains when we know the *exact* DataID or DataQuery.""" return super(_DataIDContainer, self._all_nodes).__contains__(item)
[docs] def getitem(self, item): """Get Node when we know the *exact* DataID or DataQuery.""" return super(_DataIDContainer, self._all_nodes).__getitem__(item)
def __str__(self): """Render the dependency tree as a string.""" return self._root.display()
[docs]class DependencyTree(Tree): """Structure to discover and store `Dataset` dependencies. Used primarily by the `Scene` object to organize dependency finding. Dependencies are stored used a series of `Node` objects which this class is a subclass of. """ def __init__(self, readers, compositors, modifiers, available_only=False): """Collect Dataset generating information. Collect the objects that generate and have information about Datasets including objects that may depend on certain Datasets being generated. This includes readers, compositors, and modifiers. Composites and modifiers are defined per-sensor. If multiple sensors are available, compositors and modifiers are searched for in sensor alphabetical order. Args: readers (dict): Reader name -> Reader Object compositors (dict): Sensor name -> Composite ID -> Composite Object modifiers (dict): Sensor name -> Modifier name -> (Modifier Class, modifier options) available_only (bool): Whether only reader's available/loadable datasets should be used when searching for dependencies (True) or use all known/configured datasets regardless of whether the necessary files were provided to the reader (False). Note that when ``False`` loadable variations of a dataset will have priority over other known variations. Default is ``False``. """ super().__init__() self.readers = readers self.compositors = compositors self.modifiers = modifiers self._available_only = available_only
[docs] def copy(self): """Copy this node tree. Note all references to readers are removed. This is meant to avoid tree copies accessing readers that would return incompatible (Area) data. Theoretically it should be possible for tree copies to request compositor or modifier information as long as they don't depend on any datasets not already existing in the dependency tree. """ new_tree = DependencyTree({}, self.compositors, self.modifiers) for c in self._root.children: c = c.copy(node_cache=new_tree._all_nodes) new_tree.add_child(new_tree._root, c) return new_tree
[docs] def populate_with_keys(self, dataset_keys: set, query=None): """Populate the dependency tree. Args: dataset_keys (set): Strings, DataIDs, DataQuerys to find dependencies for query (DataQuery): Additional filter parameters. See `satpy.readers.get_key` for more details. Returns: (Node, set): Root node of the dependency tree and a set of unknown datasets """ unknown_datasets = list() known_nodes = list() for key in dataset_keys.copy(): try: dsq = create_filtered_query(key, query) node = self._create_subtree_for_key(dsq, query) except MissingDependencies as unknown: unknown_datasets.append(unknown.missing_dependencies) else: known_nodes.append(node) self.add_child(self._root, node) for key in dataset_keys.copy(): dataset_keys.discard(key) for node in known_nodes: dataset_keys.add( if unknown_datasets: raise MissingDependencies(unknown_datasets, "Unknown datasets:")
def _create_subtree_for_key(self, dataset_key, query=None): """Find the dependencies for *dataset_key*. Args: dataset_key (str, float, DataID, DataQuery): Dataset identifier to locate and find any additional dependencies for. query (DataQuery): Additional filter parameters. See `satpy.readers.get_key` for more details. """ # 0 check if the *exact* dataset is already loaded try: node = self._get_subtree_for_existing_key(dataset_key) except MissingDependencies: # exact dataset isn't loaded, let's load it below pass else: return node # 1 try to get *best* dataset from reader try: node = self._create_subtree_from_reader(dataset_key, query) except TooManyResults: LOG.warning("Too many possible datasets to load for {}".format(dataset_key)) raise MissingDependencies({dataset_key}) except MissingDependencies: pass else: return node # 2 try to find a composite by name (any version of it is good enough) try: node = self._get_subtree_for_existing_name(dataset_key) except MissingDependencies: pass else: return node # 3 try to find a composite that matches try: node = self._create_subtree_from_compositors(dataset_key, query) except MissingDependencies: raise else: return node def _get_subtree_for_existing_key(self, dsq): try: node = self.getitem(dsq) LOG.trace("Found exact dataset already loaded: {}".format( return node except KeyError: LOG.trace("Exact dataset {} isn't loaded, will try reader...".format(dsq)) raise MissingDependencies({dsq}) def _create_subtree_from_reader(self, dataset_key, query): try: node = self._find_reader_node(dataset_key, query) except MissingDependencies: LOG.trace("Could not find dataset in reader: {}".format(dataset_key)) raise else: LOG.trace("Found reader provided dataset:\n\tRequested: {}\n\tFound: {}".format(dataset_key, return node def _find_reader_node(self, dataset_key, query): """Attempt to find a `DataID` in the available readers. Args: dataset_key (str, float, DataID, DataQuery): Dataset name, wavelength, `DataID` or `DataQuery` to use in searching for the dataset from the available readers. """ matching_ids = self._find_matching_ids_in_readers(dataset_key) unique_id = self._get_unique_matching_id(matching_ids, dataset_key, query) for reader_name, ids in matching_ids.items(): if unique_id in ids: return self._get_unique_reader_node_from_id(unique_id, reader_name) raise RuntimeError("Data ID disappeared.") def _find_matching_ids_in_readers(self, dataset_key): matching_ids = {} for reader_name, reader_instance in self.readers.items(): matching_ids[reader_name] = [] try: ds_ids = reader_instance.get_dataset_key(dataset_key, available_only=self._available_only, num_results=0, best=False) except KeyError: LOG.trace("Can't find dataset %s in reader %s", str(dataset_key), reader_name) continue matching_ids[reader_name].extend(ds_ids) return matching_ids def _get_unique_matching_id(self, matching_ids, dataset_key, query): """Get unique matching id from `matching_ids`, for a given `dataset_key` and some optional `query`.""" all_ids = sum(matching_ids.values(), []) if len(all_ids) == 0: raise MissingDependencies({dataset_key}) elif len(all_ids) == 1: result = all_ids[0] else: sorted_ids, distances = dataset_key.sort_dataids_with_preference(all_ids, query) try: result = self._get_unique_id_from_sorted_ids(sorted_ids, distances) except TooManyResults: LOG.trace("Too many datasets matching key {} in readers {}".format(dataset_key, matching_ids.keys())) raise TooManyResults("Too many keys matching: {}".format(dataset_key)) except MissingDependencies: raise MissingDependencies({dataset_key}) return result @staticmethod def _get_unique_id_from_sorted_ids(sorted_ids, distances): if distances[0] != np.inf: if distances[0] != distances[1]: result = sorted_ids[0] else: raise TooManyResults else: raise MissingDependencies return result def _get_unique_reader_node_from_id(self, data_id, reader_name): try: # now that we know we have the exact DataID see if we have already created a Node for it return self.getitem(data_id) except KeyError: # we haven't created a node yet, create it now return ReaderNode(data_id, reader_name) def _get_subtree_for_existing_name(self, dsq): try: # assume that there is no such thing as a "better" composite # version so if we find any DataIDs already loaded then # we want to use them node = self[dsq] LOG.trace("Composite already loaded:\n\tRequested: {}\n\tFound: {}".format(dsq, return node except KeyError: # composite hasn't been loaded yet, let's load it below LOG.trace("Composite hasn't been loaded yet, will load: {}".format(dsq)) raise MissingDependencies({dsq}) def _create_subtree_from_compositors(self, dataset_key, query): try: node = self._find_compositor(dataset_key, query) LOG.trace("Found composite:\n\tRequested: {}\n\tFound: {}".format(dataset_key, node and except KeyError: LOG.trace("Composite not found: {}".format(dataset_key)) raise MissingDependencies({dataset_key}) return node def _find_compositor(self, dataset_key, query): """Find the compositor object for the given dataset_key.""" # NOTE: This function can not find a modifier that performs # one or more modifications if it has modifiers see if we can find # the unmodified version first if dataset_key.is_modified(): implicit_dependency_node = self._create_implicit_dependency_subtree(dataset_key, query) dataset_key = self._promote_query_to_modified_dataid(dataset_key, try: compositor = self.get_modifier(dataset_key) except KeyError: raise KeyError("Can't find anything called {}".format(str(dataset_key))) compositor.attrs['prerequisites'] = [implicit_dependency_node] + list(compositor.attrs['prerequisites']) else: try: compositor = self.get_compositor(dataset_key) except KeyError: raise KeyError("Can't find anything called {}".format(str(dataset_key))) root = CompositorNode(compositor) composite_id = prerequisite_filter = composite_id.create_filter_query_without_required_fields(dataset_key) # Get the prerequisites LOG.trace("Looking for composite prerequisites for: {}".format(dataset_key)) prereqs = [create_filtered_query(prereq, prerequisite_filter) if not isinstance(prereq, Node) else prereq for prereq in compositor.attrs['prerequisites']] prereqs = self._create_required_subtrees(root, prereqs, query=query) root.add_required_nodes(prereqs) # Get the optionals LOG.trace("Looking for optional prerequisites for: {}".format(dataset_key)) optionals = [create_filtered_query(prereq, prerequisite_filter) if not isinstance(prereq, Node) else prereq for prereq in compositor.attrs['optional_prerequisites']] optionals = self._create_optional_subtrees(root, optionals, query=query) root.add_optional_nodes(optionals) return root def _create_implicit_dependency_subtree(self, dataset_key, query): new_prereq = dataset_key.create_less_modified_query() src_node = self._create_subtree_for_key(new_prereq, query) return src_node def _promote_query_to_modified_dataid(self, query, dep_key): """Promote a query to an id based on the dataset it will modify (dep). Typical use case is requesting a modified dataset (query). This modified dataset most likely depends on a less-modified dataset (dep_key). The less-modified dataset must come from a reader (at least for now) or will eventually depend on a reader dataset. The original request key may be limited like (wavelength=0.67, modifiers=('a', 'b')) while the reader-based key should have all of its properties specified. This method updates the original request key so it is fully specified and should reduce the chance of Node's not being unique. """ orig_dict = query._asdict() dep_dict = dep_key._asdict() for key, dep_val in dep_dict.items(): # don't change the modifiers, just cast them to the right class if isinstance(dep_val, ModifierTuple): orig_dict[key] = dep_val.__class__(orig_dict[key]) else: orig_dict[key] = dep_val return dep_key.from_dict(orig_dict)
[docs] def get_compositor(self, key): """Get a compositor.""" for sensor_name in sorted(self.compositors): try: return self.compositors[sensor_name][key] except KeyError: continue raise KeyError("Could not find compositor '{}'".format(key))
[docs] def get_modifier(self, comp_id): """Get a modifer.""" # create a DataID for the compositor we are generating modifier = comp_id['modifiers'][-1] for sensor_name in sorted(self.modifiers): modifiers = self.modifiers[sensor_name] compositors = self.compositors[sensor_name] if modifier not in modifiers: continue mloader, moptions = modifiers[modifier] moptions = moptions.copy() moptions.update(comp_id.to_dict()) moptions['sensor'] = sensor_name compositors[comp_id] = mloader(_satpy_id=comp_id, **moptions) return compositors[comp_id] raise KeyError("Could not find modifier '{}'".format(modifier))
def _create_required_subtrees(self, parent, prereqs, query=None): """Determine required prerequisite Nodes for a composite. Args: parent (Node): Compositor node to add these prerequisites under prereqs (sequence): Strings (names), floats (wavelengths), DataQuerys or Nodes to analyze. """ prereq_nodes, unknown_datasets = self._create_prerequisite_subtrees(parent, prereqs, query) if unknown_datasets: raise MissingDependencies(unknown_datasets) return prereq_nodes def _create_optional_subtrees(self, parent, prereqs, query=None): """Determine optional prerequisite Nodes for a composite. Args: parent (Node): Compositor node to add these prerequisites under prereqs (sequence): Strings (names), floats (wavelengths), or DataQuerys to analyze. """ prereq_nodes, unknown_datasets = self._create_prerequisite_subtrees(parent, prereqs, query) for prereq, unknowns in unknown_datasets.items(): u_str = ", ".join([str(x) for x in unknowns]) LOG.debug('Skipping optional %s: Unknown dataset %s', str(prereq), u_str) return prereq_nodes def _create_prerequisite_subtrees(self, parent, prereqs, query=None): """Determine prerequisite Nodes for a composite. Args: parent (Node): Compositor node to add these prerequisites under prereqs (sequence): Strings (names), floats (wavelengths), DataQuerys or Nodes to analyze. """ prereq_nodes = [] unknown_datasets = dict() if not prereqs: # this composite has no required prerequisites prereq_nodes.append(self.empty_node) self.add_child(parent, self.empty_node) return prereq_nodes, unknown_datasets for prereq in prereqs: try: if isinstance(prereq, Node): node = prereq else: node = self._create_subtree_for_key(prereq, query=query) except MissingDependencies as unknown: unknown_datasets[prereq] = unknown.missing_dependencies else: prereq_nodes.append(node) self.add_child(parent, node) return prereq_nodes, unknown_datasets
class _DataIDContainer(dict): """Special dictionary object that can handle dict operations based on dataset name, wavelength, or DataID. Note: Internal dictionary keys are `DataID` objects. """ def keys(self): """Give currently contained keys.""" # sort keys so things are a little more deterministic (.keys() is not) return sorted(super(_DataIDContainer, self).keys()) def get_key(self, match_key): """Get multiple fully-specified keys that match the provided query. Args: match_key (DataID): DataID or DataQuery of query parameters to use for searching. Can also be a string representing the dataset name or a number representing the dataset wavelength. """ return get_key(match_key, self.keys()) def __getitem__(self, item): """Get item from container.""" try: # short circuit - try to get the object without more work return super(_DataIDContainer, self).__getitem__(item) except KeyError: key = self.get_key(item) return super(_DataIDContainer, self).__getitem__(key) def __contains__(self, item): """Check if item exists in container.""" try: key = self.get_key(item) except KeyError: return False return super(_DataIDContainer, self).__contains__(key)