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Cities and cities.py

A colleague pointed me to the GNU miscfiles cities database after I posted geolocation and path cross, suggesting that it would be a useful database to support. Being that it includes five hundred places around the globe, and I already have the database installed, I have to agree.

GNU miscfiles is a package of, well miscellaneous files. It contains, amongst other things a list of world currencies, languages and the file we're looking at today :file:`cities.dat`.

In v1.4.2, the version I have installed, :file:`cities.dat` contains 497 entries. The file is a simple flat Unicode database, with records separated by //, a format that would be as well suited to processing with awk as it would with Python.

You don't need to hand process the data though, I've added :mod:`~upoints.cities` to the upoints tarball that takes care of importing the data. When you import the entries with :meth:`~upoints.cities.Cities.import_locations` it returns a dictionary of :class:`~upoints.cities.City` objects that are children of the :class:`~upoints.trigpoints.Trigpoint` objects defined for Trigpointing and point.py

On my Gentoo desktop the cities database is installed as :file:`/usr/share/misc/cities.dat`, and can be imported as simply as:

>>> from upoints import cities
>>> Cities = cities.Cities(open("/usr/share/misc/cities.dat"))

And the imported database can be used in a variety of ways:

>>> print("%i cities" % len(Cities))
497 cities
>>> print("Cities larger with more than 8 million people")
Cities larger with more than 8 million people
>>> for city in Cities:
...     if city.population > 8000000:
...         print("  %s - %s" % (city.name, city.population))
   Bombay - 8243405
   Jakarta - 9200000
   Moskwa - 8769000
   Sao Paolo - 10063110
   Tokyo - 8354615
   Mexico - 8831079
>>> print("Mountains")
Mountains
>>> for city in Cities:
...     if city.ptype == "Mountain":
...         print("  %s" % city.name)
   Aconcagua
   Popocatepetl

You can recreate the database as a smoke test using the following:

>>> f = open("cities.dat", "w")
>>> f.write("\n//\n".join(map(str, Cities)))
>>> f.close()

unfortunately the files aren't simply comparable using :command:`diff` because of some unusual formatting in the original file, but visually scanning over the :command:`diff -w` output to ignore the whitespace changes shows that we have a correct export.

The :class:`~upoints.cities.City` class inherits :class:`~upoints.trigpoints.Trigpoint` which in turn inherits :class:`~upoints.point.Point`, and therefore has all the same methods they do. This allows you to calculate distances and bearings between the class:~upoints.cities.City objects or any other derivative object of the parent classes. For example, you could use the :func:`~upoints.utils.dump_xearth_markers` function:

>>> from upoints.utils import dump_xearth_markers
>>> scottish_markers = dict((x.identifier, x) for x in Cities
...                         if x.region == "Scotland")
>>> print("\n".join(dump_xearth_markers(scottish_markers, "name")))
57.150000 -2.083000 "Aberdeen" # 1
55.950000 -3.183000 "Edinburgh" # 83
55.867000 -4.267000 "Glasgow" # 92

Take a look at the Sphinx generated documentation that is included in the tarball to see what can be done.