[fix] Removing YAML inheritance as it doesn't merge nested dictionaries

This commit is contained in:
Al
2016-04-27 15:10:08 -04:00
parent 169f1db3bd
commit dff4a5e76e
2 changed files with 1147 additions and 1149 deletions

View File

@@ -10,13 +10,12 @@
# country overrides section. Each country can create its own copy of the entire top-level
# structure and it will be recursively merged with the defaults.
default: &default
# Number
# ======
# Number, No., #, etc. can be used in both floor and apartment numbers,
# so we'll define it separately
# Number
# ======
# Number, No., #, etc. can be used in both floor and apartment numbers,
# so we'll define it separately
numbers:
numbers:
default: &number
canonical: number # canonical word in libpostal dictionary
abbreviated: "no" # most common abbreviated form ("no" is a boolean in YAML, needs to be quoted)
@@ -37,11 +36,11 @@ default: &default
numeric_probability: 0.4 # With this probability, use the standard numeric
numeric_affix_probability: 0.6 # With this probability, use e.g. #3 instead of No. 3
# And
# ===
# The word for "and". Used both in intersections and phrases like "Units 1 & 2", etc.
# And
# ===
# The word for "and". Used both in intersections and phrases like "Units 1 & 2", etc.
and:
and:
default: &and
canonical: and
abbreviated: "&"
@@ -51,26 +50,26 @@ default: &default
sample_probability: 0.05
# Floor/level
# ===========
# OSM doesn't usually concern itself with the address beyond the front door
# yet many real-world addresses will have qualifying strings like "6th floor"
# and we'd like the parser to handle those.
#
# When we do get floor numbers in OSM addresses, it's usually in the form of the
# addr:floor or level tag, where the value is typically an integer or a half-floor
# (to indicate mezzanines). Those tags are relatively scarce in OSM, but many OSM
# addresses do have a building:levels tag. If we know there are 20 floors in the
# building, we can randomly sample numbers <= the # of floors and come up with plausible
# sounding addresses (i.e. a Floor 20 address is not as likely outside major cities).
#
# We're not done yet, because the integer value by itself isn't what people use when
# writing addresses. This part of the config helps us rewrite the raw integer floor
# numers as the sort of natural language text used in addresses like "Fl #1". The config
# is designed to be cross-lingual, so we can use the same structure with different words
# and do this for addresses in pretty much any language.
# Floor/level
# ===========
# OSM doesn't usually concern itself with the address beyond the front door
# yet many real-world addresses will have qualifying strings like "6th floor"
# and we'd like the parser to handle those.
#
# When we do get floor numbers in OSM addresses, it's usually in the form of the
# addr:floor or level tag, where the value is typically an integer or a half-floor
# (to indicate mezzanines). Those tags are relatively scarce in OSM, but many OSM
# addresses do have a building:levels tag. If we know there are 20 floors in the
# building, we can randomly sample numbers <= the # of floors and come up with plausible
# sounding addresses (i.e. a Floor 20 address is not as likely outside major cities).
#
# We're not done yet, because the integer value by itself isn't what people use when
# writing addresses. This part of the config helps us rewrite the raw integer floor
# numers as the sort of natural language text used in addresses like "Fl #1". The config
# is designed to be cross-lingual, so we can use the same structure with different words
# and do this for addresses in pretty much any language.
levels:
levels:
# Numbered floors
floor: &floor
canonical: floor
@@ -449,15 +448,15 @@ default: &default
probability: 0.25
# Intersections
# =============
# For constructing intersections like 5th Avenue & Broadway
# In OSM, a node that's part of two ways is an intersection.
#
# These simple rules make it possible to create training examples
# like: 26th/road Street/road and/intersection 6th/road Avenue/road
# Intersections
# =============
# For constructing intersections like 5th Avenue & Broadway
# In OSM, a node that's part of two ways is an intersection.
#
# These simple rules make it possible to create training examples
# like: 26th/road Street/road and/intersection 6th/road Avenue/road
cross_streets:
cross_streets:
# 26th & 6th Avenue
and: *and
# 26th @ Broadway
@@ -488,20 +487,20 @@ default: &default
sample: true
parentheses_probability: 0.5 # Probability of using parentheses e.g. (between 5th and 6th)
# PO Box addresses
# ================
# For PO box addresses, there's almost no data in OSM, so we'll need to
# generate them somewhat randomly.
#
# The strategy is: for every amenity=post_office, generate a number of PO box
# addresses using random numbers (and some alpha-numerics so we capture patterns
# like PO Box 1Q, etc.) It doesn't matter if the post boxes themselves actually
# exist, as long as they cover the patterns of digits we expect in real addresses.
# The parser cares more about how many digits a number has and the surrounding
# words/phrases than the specific number i.e. numbers in the range 1000-9999
# can simply be normalized to DDDD.
# PO Box addresses
# ================
# For PO box addresses, there's almost no data in OSM, so we'll need to
# generate them somewhat randomly.
#
# The strategy is: for every amenity=post_office, generate a number of PO box
# addresses using random numbers (and some alpha-numerics so we capture patterns
# like PO Box 1Q, etc.) It doesn't matter if the post boxes themselves actually
# exist, as long as they cover the patterns of digits we expect in real addresses.
# The parser cares more about how many digits a number has and the surrounding
# words/phrases than the specific number i.e. numbers in the range 1000-9999
# can simply be normalized to DDDD.
po_boxes:
po_boxes:
po_box: &po_box
canonical: post office box
abbreviated: p.o. box
@@ -593,12 +592,12 @@ default: &default
- before: house
probability: 0.2
# Categories
# ==========
# Use the operators "in" and "near" for building category queries
# such as "restaurants in Hackney, London"
# Categories
# ==========
# Use the operators "in" and "near" for building category queries
# such as "restaurants in Hackney, London"
categories:
categories:
near:
default:
canonical: near
@@ -628,13 +627,13 @@ default: &default
near_me_probability: 0.1
in_probability: 0.35
# Directions
# ==========
# Unit types, stairways, etc. may have a direction associated
# with them whether it's right/left or a cardinal direction
# like "East Entrance".
# Directions
# ==========
# Unit types, stairways, etc. may have a direction associated
# with them whether it's right/left or a cardinal direction
# like "East Entrance".
directions:
directions:
right: &right
canonical: right
abbreviated: r
@@ -693,7 +692,7 @@ default: &default
- alternative: *rear
probability: 0.05
cardinal_directions:
cardinal_directions:
east: &east
canonical: east
abbreviated: e
@@ -761,11 +760,11 @@ default: &default
- alternative: *west
probability: 0.25
# Entrance
# ========
# For deriving strings like "North Entrance"
# Entrance
# ========
# For deriving strings like "North Entrance"
entrances:
entrances:
entrance: &entrance
canonical: entrance
abbreviated: ent
@@ -794,11 +793,11 @@ default: &default
- alternative:
canonical: freight
# Staircase
# =========
# For deriving strings like "Staircase A" in apartment buildings
# Staircase
# =========
# For deriving strings like "Staircase A" in apartment buildings
staircases:
staircases:
stair: &stair
canonical: stair
sample: true
@@ -843,13 +842,13 @@ default: &default
- alternative: *front
# Unit types
# ==========
# Unit information is common in residential addresses, offices, business parks, etc.
# Just like thoroughfare types (Street, Avenue, etc.), there are many common ways to
# refer to the
# Unit types
# ==========
# Unit information is common in residential addresses, offices, business parks, etc.
# Just like thoroughfare types (Street, Avenue, etc.), there are many common ways to
# refer to the
units:
units:
# Units are not part of the global address formats (and are not always standard)
# This is a list of places in the address where the unit line might go
order:
@@ -1176,7 +1175,6 @@ default: &default
countries:
# United States
us:
<<: *default
levels:
storey: &story
canonical: story
@@ -1263,7 +1261,6 @@ countries:
# Canada
# Specifically Canadian English. If the address is in French it will use fr.yaml
ca:
<<: *default
levels:
# Note: Canadian English uses "storey" keeping with the British convention, so no need to change that
@@ -1291,7 +1288,6 @@ countries:
combined_probability: 0.1
# Australia
au:
<<: *default
po_boxes: &australia_po_boxes
alphanumeric:
default: *po_box
@@ -1334,7 +1330,6 @@ countries:
# New Zealand - same rules as Australia
nz:
<<: *default
po_boxes: *australia_po_boxes
units: *australia_unit_types

View File

@@ -10,6 +10,7 @@ from geodata.address_expansions.address_dictionaries import address_phrase_dicti
from geodata.configs.utils import nested_get, DoesNotExist, recursive_merge
from geodata.math.sampling import cdf, check_probability_distribution
this_dir = os.path.realpath(os.path.dirname(__file__))
ADDRESS_CONFIG_DIR = os.path.join(this_dir, os.pardir, os.pardir, os.pardir,
@@ -29,14 +30,17 @@ class AddressConfig(object):
continue
config = yaml.load(open(os.path.join(ADDRESS_CONFIG_DIR, filename)))
default = config['default']
countries = config.pop('countries', {})
if countries:
default['countries'] = countries
for k in countries.keys():
country_config = countries[k]
config_copy = copy.deepcopy(config)
countries[k] = recursive_merge(config_copy, country_config)
config['countries'] = countries
lang = filename.strip('.yaml')
self.address_configs[lang] = default
self.address_configs[lang] = config
self.sample_phrases = {}
@@ -55,7 +59,6 @@ class AddressConfig(object):
if country_config:
config = country_config
value = nested_get(config, keys)
if value is not DoesNotExist:
return value