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Udacity_Nanodegree_Intermed…/Exploring_Near_Earth_Objects/database.py

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Python

"""A database encapsulating collections of near-Earth objects and their close approaches.
A `NEODatabase` holds an interconnected data set of NEOs and close approaches.
It provides methods to fetch an NEO by primary designation or by name, as well
as a method to query the set of close approaches that match a collection of
user-specified criteria.
Under normal circumstances, the main module creates one NEODatabase from the
data on NEOs and close approaches extracted by `extract.load_neos` and
`extract.load_approaches`.
You'll edit this file in Tasks 2 and 3.
"""
class NEODatabase:
"""A database of near-Earth objects and their close approaches.
A `NEODatabase` contains a collection of NEOs and a collection of close
approaches. It additionally maintains a few auxiliary data structures to
help fetch NEOs by primary designation or by name and to help speed up
querying for close approaches that match criteria.
"""
def __init__(self, neos, approaches):
"""Create a new `NEODatabase`.
As a precondition, this constructor assumes that the collections of NEOs
and close approaches haven't yet been linked - that is, the
`.approaches` attribute of each `NearEarthObject` resolves to an empty
collection, and the `.neo` attribute of each `CloseApproach` is None.
However, each `CloseApproach` has an attribute (`._designation`) that
matches the `.designation` attribute of the corresponding NEO. This
constructor modifies the supplied NEOs and close approaches to link them
together - after it's done, the `.approaches` attribute of each NEO has
a collection of that NEO's close approaches, and the `.neo` attribute of
each close approach references the appropriate NEO.
:param neos: A collection of `NearEarthObject`s.
:param approaches: A collection of `CloseApproach`es.
"""
self._neos = neos
self._approaches = approaches
self._neo_by_designation = {neo.designation: neo for neo in self._neos}
self._neo_by_name = {neo.name: neo for neo in self._neos}
for approach in self._approaches:
# Link approach.neo to the corresponding NearEarthObject, namely
# the one whose designation matches approach._designation.
approach.neo = self._neo_by_designation[approach._designation]
# Add this approach to the corresponding NearEarthObject's
# .approaches collection.
self._neo_by_designation[approach._designation].approaches.append(approach)
def get_neo_by_designation(self, designation):
"""Find and return an NEO by its primary designation.
If no match is found, return `None` instead.
Each NEO in the data set has a unique primary designation, as a string.
The matching is exact - check for spelling and capitalization if no
match is found.
:param designation: The primary designation of the NEO to search for.
:return: The `NearEarthObject` with the desired primary designation, or `None`.
"""
return self._neo_by_designation.get(designation, None)
def get_neo_by_name(self, name):
"""Find and return an NEO by its name.
If no match is found, return `None` instead.
Not every NEO in the data set has a name. No NEOs are associated with
the empty string nor with the `None` singleton.
The matching is exact - check for spelling and capitalization if no
match is found.
:param name: The name, as a string, of the NEO to search for.
:return: The `NearEarthObject` with the desired name, or `None`.
"""
return self._neo_by_name.get(name, None)
def query(self, filters=()):
"""Query close approaches to generate those that match a collection of filters.
This generates a stream of `CloseApproach` objects that match all of the
provided filters.
If no arguments are provided, generate all known close approaches.
The `CloseApproach` objects are generated in internal order, which isn't
guaranteed to be sorted meaningfully, although is often sorted by time.
:param filters: A collection of filters capturing user-specified criteria.
:return: A stream of matching `CloseApproach` objects.
"""
for approach in self._approaches:
cases = [filter_i(approach) for filter_i in filters]
if all(cases):
yield approach