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A simplified Python API for Atlas

Project description


A simplified Atlas API for Python

Getting Started

To get setup in a new project folder, run:

$ mkdir newproj && cd newproj
$ virtualenv venv --python=python3
$ source venv/bin/activate

NOTE: pyatlas will automatically install the dependencies it needs, including the Protocol Buffers Python runtime - protobuf-2.6.1. Therefore, it is highly recommended that you develop pyatlas based projects in a Python virtual environment - you may need to install virtualenv if you have not already. (If you want to create a pyatlas distribution that does not automatically pull in dependencies, see the next section.)

Now that you have your virtual environment set up, you can install pyatlas with:

(venv) $ pip install pyatlas

If pip is unable to find the pyatlas package, you may need to build it from source yourself. Check the next section for more info.

To test that everything went smoothly, create a file with the following code:

from pyatlas import pyatlas_globalfunc

Now run:

(venv) $ python

If you see:

Hello Atlas!

then you're good to go!

Building the pyatlas module

To build the pyatlas module from source, run:

$ git clone
$ cd atlas
$ ./gradlew cleanPyatlas buildPyatlas

This will generate a wheel file at pyatlas/dist. You can now install this with pip like

$ cd /path/to/project/that/uses/pyatlas
$ virtualenv venv --python=python2.7
$ source venv/bin/activate
$ pip install /path/to/atlas/pyatlas/dist/pyatlas-VERSION.whl

Again, it is recommended that you do this in the desired virtual environment.

If you want to build a pyatlas wheel file that does not automatically pull dependencies, open up and remove the lines that say


Then re-run the ./gradlew cleanPyatlas buildPyatlas command from above and reinstall using pip. Note that you will now need to manage the required dependencies manually.

Note on the formatter

pyatlas uses the yapf formatting library to check for code format issues when building. If you are running into issues after modifying pyatlas, try running

./gradlew applyFormatPyatlas

Now pyatlas should make it past the CHECK format step!

Note there is an issue that causes the formatter to goof if a source file does not end with a newline (\n) character. If the CHECK format step is consistently failing after repeated APPLY steps, and you are seeing a message like the following: found issue, reformatting...

with no formatter diff being displayed, check to make sure that the file has an ending newline.


pyatlas documentation is automatically generated using the pydoc tool and stored in the doc folder. To build the documentation, run the gradle build command:

$ ./gradlew cleanPyatlas buildPyatlas

This will generate HTML files detailing the functions and classes available in each module.

Some sample use cases

pyatlas is a highly capable subset of the API provided by the Java Atlas. Here are some examples to get you started. Note that all of these examples were ran using the test.atlas provided in the resources folder, and assume that you have an atlas variable defined like:

from pyatlas.atlas import Atlas
atlas = Atlas('/path/to/atlas/pyatlas/resources/test.atlas')

Getting features and metadata

You can get filtered iterables over an Atlas's features using the methods provided in the Atlas class.

# print all Nodes
for node in atlas.nodes():
    print node

# print all Edges that have 'key1' as a tag key
for edge in atlas.edges(predicate=lambda e: 'key1' in e.get_tags().keys()):
    print edge

You can also get a feature with a specific identifier like:

# print the Relation with Atlas ID 2
print atlas.relation(2)

Metadata about the Atlas is also available. For a quick sample, try something like:

metadata = atlas.metadata()
print metadata.number_of_points

Check out doc/atlas.html and doc/atlas_metadata.html for more information.

Operating on features

The Atlas features themselves support a set of operations defined in their respective classes.

Here is a quick example:

# print the tag dict for Point with Atlas ID 3
print atlas.point(3).get_tags()

# print all Relations of which the Node with Atlas ID 1 is a member
for relation in atlas.node(1).relations():
    print relation

# print all the members of Relation with Atlas ID 1
for member in atlas.relation(1).get_members():
    # print the RelationMember object
    print member
    # print the actual AtlasEntity contained in the RelationMember
    print member.get_entity()

Nodes and Edges, in particular, support traversal through their connectivity API. Here are just the basics of what you can do with the connectivity interface:

# print Edges connected to Node with ID 3
for edge in atlas.node(3).in_edges():
    print edge
for edge in atlas.node(3).out_edges():
    print edge
for edge in atlas.node(3).connected_edges():
    print edge

# print the start and end Nodes of Edge 1
print atlas.edge(1).start()
print atlas.edge(1).end()

Many more methods are provided. See the classes in doc/atlas_entities.html for more information.


pyatlas features some really simple geometry primitives for working with locations and shapes on the surface of the Earth. Here is a simple example that uses these primitives:

from pyatlas import geometry
from pyatlas.geometry import Location, PolyLine, Polygon, Rectangle

# Location constructor (lat/lon ordering) uses dm7 by default, see Location docs for info on dm7
loc1 = Location(385000000, -1160200000)
# create the same Location but with degree values instead (lat/lon ordering)
loc2 = geometry.location_with_degrees(38.5, -116.02)
print loc1.get_latitude_deg()
print loc2.get_latitude()

# create a new PolyLine with two shape points
polyline1 = PolyLine([Location(385000000, -1160200000), Location(395000000, -116300000)])
for loc in polyline1.locations():
    print loc
print polyline1.bounds()

# create a new Polygon with specified vertices
polygon1 = Polygon([geometry.location_with_degrees(0, 0),
                    geometry.location_with_degrees(10, 0),
                    geometry.location_with_degrees(5, 10)])
print polygon1
# print the vertices, will print the first again at the end to simulate closedness
for loc in polygon1.closed_loop():
    print loc
print polygon1.bounds()
# will print True, since the point lies inside the triangle
print polygon1.fully_geometrically_encloses_location(geometry.location_with_degrees(5, 5))

# create a new Rectangle with given lower left and upper right corners
rect = Rectangle(geometry.location_with_degrees(0, 0), geometry.location_with_degrees(20, 20))
print rect
# this Rectangle intersects (overlaps at any point) polygon1
print rect.intersects(polygon1)

See the classes in doc/geometry.html for more information.

Spatial queries

pyatlas supports some simple spatial queries over its feature space. The queries use the geometry primitives provided by the geometry module, but convert to Shapely primitives under the hood to make queries into a native libgeos-backed R-tree. Below are examples for a few of the spatial queries the Atlas supports:

from pyatlas import geometry
from pyatlas.geometry import Rectangle

# print all Points intersecting a given Polygon that also have "key1" as a tag key
lower_left = geometry.location_with_degrees(37, -118.02)
upper_right = geometry.location_with_degrees(39, -118)
for point in atlas.points_within(Rectangle(lower_left, upper_right),
                                 predicate=lambda e: 'key1' in e.get_tags().keys()):
    print point

# print all Relations with at least one member intersecting a given Polygon
lower_left = geometry.location_with_degrees(37.999, -118.001)
upper_right = geometry.location_with_degrees(38.001, -117.999)
for relation in atlas.relations_with_entities_intersecting(Rectangle(lower_left, upper_right)):
    print relation

# print all Edges that intersect a given Polygon
lower_left = geometry.location_with_degrees(38, -120)
upper_right = geometry.location_with_degrees(40, -117)
for edge in atlas.edges_intersecting(Rectangle(lower_left, upper_right)):
    print edge

See doc/atlas.html for more information on the available spatial queries.

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