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A tool to more easily develop queries of OpenStreetMap

Project description

A Python to OverpassQL transpiler, now on both GitHub and GitLab

OverpassQL is the language used to query features on OpenStreetMap. Unfortunately, it’s not very readable.

The goal here is to enable people to write in a more developer-friendly language, and still have it work on the existing infrastructure. As of now, overpassify can take a snippet like:

from overpassify import overpassify

@overpassify
def query():
    search = Area(3600134503)
    ways = Way(search, highway=...)
    odd_keys_demo = Way(search, **{Regex('maxspeed(?::.+)?'): Regex('.+ mph')})
    nodes = Node(search)
    out(ways, geom=True, count=True)
    out(nodes, geom=True, count=True)
    noop()

And from that generate:

(area(3600134503);) -> .search;
(way["highway"](area.search);) -> .ways;
(way[~"maxspeed(?::.+)?"~".+ mph"](area.search);) -> .odd_keys_demo;
(node(area.search);) -> .nodes;
.ways out count;
.ways out geom;
.nodes out count;
.nodes out geom;

That last noop() is because of issue #2. And as a note, this library assumes you never use a variable name of the form tmp*. That format will probably be changed to something even less likely in the future, but some translations (for instance, a full ternary) require the use of temporary variables.

Overview

I’ll say this from the outset: overpassify will support a subset of Python. Some things are just too difficult (and maybe impossible) to automatically translate. Functions are an example of that.

On the other hand, it will try to support a superset of easily-usable OverpassQL. Some of those extra features won’t be as efficient as their Python counterparts, but they will be available.

Currently overpassify supports 41/56 of the features listed in the OverpassQL guide, and additionally supports ternary statements, if blocks, break, and continue.

Classes

This library provides wrappers for five types. Set(), Node(), Way(), Area(), and Relation(). Those last four are all considered subclasses of Set().

This library also provides support for strings and numbers. In the future it will provide support for regex and other things in specific places.

(Note: Currently nested constructors have some problems in implementation)

Assignment

This works about the way you’d expect it to. There are a couple caveats though.

  1. You cannot assign a non-Set() to a variable. This means only those five classes listed above.
  2. You cannot assign multiple variables in one line. No a, b = b, a, and the like. This could potentially be changed later.

Number and Set Arithmetic

Another supported feature is the ability to manipulate these sets and numbers.

Adding sets will produce the union of those sets. Adding numbers will produce their sum.

Subtracting two sets will produce their difference. Subtracting numbers will do the same.

Set Filtering

You are also allowed to filter a Set()’s contents by type. For instance, Way.filter(<some set>) would yield all the ways within <some set>.

Set intersections

A similar process will allow you to take the intersection of arbitrary numbers of named sets. So Set.intersect(a, b) will yield all elements common between a and b. You cannot, at the moment, use an expression inside this function. It must be predefined.

You can also use this in tandem with Set Filtering. So Area.intersect(a, b) would yield only the areas common between a and b.

Searching for Sets

This library also supports most of the ways OverpassQL can search for information. This currently includes:

  1. Checking within an area (or set of areas)
  2. Fetching by ID
  3. Tag matching
  4. Conditional filters (see next section)

The first two are just given as arguments to the constructor. If you put in Way(12345), that will find the Way with ID 12345. If you put in Way(<some area>), it will return all ways within that area.

You can also define areas using the Around() function. This has two useful overloads. The first takes the form Around(<some set>, <radius in meters>). The second takes the form Around(<radius in meters>, <latitude>, <longitude>).

Tag matching can be done with keyword arguments. So if you look for Node(highway="stop"), that will find you all stop signs. It also supports existence checking (Way(highway=...)), and non-existence checking (Area(landuse=None)), and regex matching (Way(highway=Regex("path|cycleway|sidewalk"))).

For keys which are not usable as a keyword, you can use a “splatted” dictionary. For instance Node(**{'maxspeed:advisory': Regex('.+ mph')}). The same follows for regex key matching, though regex key matching must be with a regex value.

You can also search by both an area and a filter. For instance: Way(<your hometown>, maxspeed=None).

Ternary Expressions and Conditional Filters

You can also filter using the familiar a if b else c. This would mean that if b is truthy, a should become b, and otherwise become c.

Unfortunately, since this is not a native feature to OverpassQL, it ends up evaluating both sides of that statement.

If you want c to be an empty set, however, we can optimize that. So foo = a if b else <type>() is the syntax to use there.

Additional performance is lost because OverpassQL does not support a conditional being the only filter. This means that we need to provide some other filter, and one in current use is to divide it by type and reconstruct. Because of this, filtering down to the appropriate set type yields significantly batter performance.

Returning Data

In OverpassQL, data can be returned in pieces throughout the function. It’s more equivalent to Python’s yield than return. The function we use for that here is out().

out() takes in one positional argument, and many possible keyword arguments. It yields data for the positional argument using all the types defined in the keywords.

For instance out(<set of nodes>, geom=True, body=True, qt=True) would return all the data that MapRoulette needs to draw those points on their map.

As a sidenote, the value given for these keywords is never actually checked. It could as easily be geom=False as geom=True, and overpassify will not care.

For-Each Loop

Here you can use the traditional Python for loop:

for way in ways:
    out(way, geom=True)

It does not yet support the else clause, and though it supports break and continue, please be aware that this will dramatically slow runtime in that loop.

If Statements

This is a feature that OverpassQL cannot do without some emulation. So what we do here is:

  1. Grab an individual item that will probably be stable over long periods of time; in this case, the Relation() representing Antarctica
  2. Use a conditional filter on that relation to get a one item or zero item Set()
  3. Iterate over that in a for loop
  4. If there is an else clause, use a conditional filter with the negation of the test given to get a one item or zero item Set()
  5. Iterate over the else clause in a for loop

Settings

We also provide a wrapper for the option headers. Note that this will raise an error if it’s not on the first line of your query.

The valid keywords for Settings() are as follows:

  • timeout: The maximum number of seconds you would like your query to run for
  • maxsize: The maximum number of bytes you would like your query to return
  • out: The format to return in. It defaults to XML, but you can set it to "json" or a variant on "csv", as described in the OverpassQL spec
  • bbox: The string describing a global bounding box. It is used to limit the area your query can encompass, and should take the form "<southern lat>,<western lon>,<northern lat>,<eastern lon>"
  • date: The string describing what date you would like to query for. This allows you to look at past database states. Note that it needs an extra set of quotes, so it would look like date='"2012-09-12T06:55:00Z"'
  • diff: Similar to the above, except it will return the difference between that query run at each time. If you give one time, it will assume you want to compare to now. It would look like diff='"2012-09-12T06:55:00Z","2014-12-24T13:33:00Z"'
  • adiff: Similar to the above, except that it tells you what happened to each absent element

Rough Translation Table

Feature OverpassQL Python
Assignment <expr> -> .name name = <expr>
Unions (<set>; ...; <set>) <set> + ... + <set>
Difference (<set> - <set>) <set> - <set>
Intersection .<set>.<set> Set.intersect(<set>, <set>)
Type-filtering way.<set> Way.filter(<set>)
Searching    
..By ID area(1) or way(7) Area(1) or Way(7)
..In an area way(area.<set>) Way(<set>)
..By tags way["tag"="value"] Way(tag=value)
..By tag existence way["tag"] Way(tag=...)
..By tag nonexistence way[!"tag"] Way(tag=None)
..By regex way["highway"~"a|b"](area.<set>) Way(<set>, highway=Regex("a|b"))
..By inverse regex way["highway"!~"a|b"](area.<set>) Way(<set>, highway=NotRegex("a|b"))
..In area + tag way["highway"](area.<set>) Way(<set>, highway=...)
Ternary very long <expr> if <condition> else <expr>
Conditional Filter <type>.<set>(if: <condition>) <expr> if <condition> else <type>()
For Loop foreach.<set>->.<each>(<body>) for <each> in <set>:\n    <body>
If Statement very long if <condition>:\n    <body>\nelse:\n    <body>
Recursing    
..Up .a < or .a < -> .b a.recurse_up() or b = a.recurse_up()
..Up (w/ relations) .a << or .a << -> .b a.recurse_up_relations()
..Down .a > or .a > -> .b a.recurse_down()
..Down (w/ relations) .a >> or .a >> -> .b a.recurse_down_relations()
is_in filers    
..On a set .a is_in -> .areas_with_part_of_a areas_containing_part_of_a = is_in(a)
..On a lat/lon pair is_in(0, 0) -> .areas_with_0_0 areas_containing_0_0 = is_in(0, 0)

Features Not Yet Implemented

  1. Filters
    1. Recursion Functions
    2. Filter By Bounding Box
    3. Filter By Polygon
    4. Filter By “newer”
    5. Filter By Date Of Change
    6. Filter By User
    7. Filter By Area Pivot
  2. ID Evaluators
    1. id() And type()
    2. is_tag() And Tag Fetching
    3. Property Count Functions
  3. Aggregators
    1. Union and Set
    2. Min and Max
    3. Sum
    4. Statistical Counts
  4. Number Normalizer
  5. Date Normalizer

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