jageocoder 1.1.3

A Python implementation of Japanese-address geocoder.

jageocoder - A Python Japanese geocoder

日本語版は README_ja.md をお読みください。

This is a Python port of the Japanese-address geocoder used in CSIS at the University of Tokyo's "Address Matching Service" and GSI Maps.

Getting Started

This package provides address-geocoding functionality for Python programs. The basic usage is to specify a dictionary with init() then call search() to get geocoding results.

python
>>> import jageocoder
>>> jageocoder.init()
>>> jageocoder.search('新宿区西新宿2-8-1')
{'matched': '新宿区西新宿2-8-', 'candidates': [{'id': 5961406, 'name': '8番', 'x': 139.691778, 'y': 35.689627, 'level': 7, 'note': None, 'fullname': ['東京都', '新宿区', '西新宿', '二丁目', '8番']}]}

How to install

Prerequisites

Requires Python 3.6.x or later.

The following packages will be installed automatically.

• marisa-trie for building and retrieving TRIE index
• SQLAlchemy for abstracting access to the RDBMS

Install instructions

• Install the package with pip install jageocoder
• Install the dictionary with install-dictionary command

pip install jageocoder
python -m jageocoder install-dictionary

The dictionary database will be created under {sys.prefix}/jageocoder/db/, or if the user doesn't have write permission there {site.USER_DATA}/jageocoder/db/ by default.

If you need to know the location of the directory containing the dictionary database, perform get-db-dir command as follows, or call jageocoder.get_db_dir() in your script.

python -m jageocoder get-db-dir

If you prefer to create it in another location, set the environment variable JAGEOCODER_DB_DIR before executing install_dictionary() to specify the directory.

export JAGEOCODER_DB_DIR='/usr/local/share/jageocoder/db'
python -m jageocoder install-dictionary

Migrate dictinary

The install-dictionary command will download and install a version of the address dictionary file that is compatible with the currently installed jageocoder package.

If you upgrade the jageocoder package after installing the address dictionary file, it may no longer be compatible with the installed address dictionary file. In which case you will need to reinstall or migrate the dictionary.

To migrate the dictionary, run the migrate-dictionary command. This process may take a long time.

python -m jageocoder migrate-dictionary

Uninstall instructions

Remove the directory containing the database, or perform uninstall-dictionary command as follows.

python -m jageocoder uninstall-dictionary

Then, uninstall the package with pip command.

pip uninstall jageocoder

How to use

Use from the command line

We assume that jageocoder will be embedded in applications as a library and used by calling the API, but for testing purposes, you can check the geocoding results with the following command.

python -m jageocoder search 新宿区西新宿２－８－１

If you want to look up an address from longitude and latitude, specify reverse instead of search.

python -m jageocoder reverse 139.6917 35.6896

You can check the list of available commands with --help.

python -m jageocoder --help

Using API

First, import jageocoder and initialize it with init().

>>> import jageocoder
>>> jageocoder.init()

Search for latitude and longitude by address

Use search() to search for the address you want to check the longitude and latitude of.

The search() function returns a dict with matched as the matched string and candidates as the list of search results. (The results are formatted for better viewing)

Each element of candidates contains the information of an address node (AddressNode).

>>> jageocoder.search('新宿区西新宿２－８－１')
{
  'matched': '新宿区西新宿２－８－',
  'candidates': [{
    'id': 12299846, 'name': '8番',
    'x': 139.691778, 'y': 35.689627, 'level': 7, 'note': None,
    'fullname': ['東京都', '新宿区', '西新宿', '二丁目', '8番']
  }]
}

The meaning of the items is as follows

• id: ID in the database
• name: Address notation
• x: longitude
• y: latitude
• level: Address level (1:Prefecture, 2:County, 3:City and 23 district, 4:Ward, 5:Oaza, 6:Aza and Chome, 7:Block, 8:Building)
• note: Notes such as city codes
• fullname: List of address notations from the prefecture level to this node

Search for addresses by longitude and latitude

Use reverse() to find addresses by longitude and latitude (so called 'reverse geocoding').

The reverse() function returns the three addresses surrounding the specified longitude and latitude. (The results are formatted for better viewing)

The candidate of each element contains information about the address node (AddressNode), and the dist contains the distance (geodesic distance, in meters) from the specified point to the representative point of the address.

>>> jageocoder.reverse(139.6917, 35.6896)
[
  {
    'candidate': {
      'id': 12299330, 'name': '二丁目',
      'x': 139.691774, 'y': 35.68945, 'level': 6,
      'note': 'postcode:1600023',
      'fullname': ['東京都', '新宿区', '西新宿', '二丁目']
    },
    'dist': 17.940303970792183
  }, {
    'candidate': {
      'id': 12300198, 'name': '六丁目',
      'x': 139.690969, 'y': 35.693426, 'level': 6,
      'note': 'postcode:1600023',
      'fullname': ['東京都', '新宿区', '西新宿', '六丁目']
    },
    'dist': 429.6327545403412
  }, {
    'candidate': {
      'id': 12300498, 'name': '四丁目',
      'x': 139.68762, 'y': 35.68754, 'level': 6,
      'note': 'postcode:1600023',
      'fullname': ['東京都', '新宿区', '西新宿', '四丁目']
    },
    'dist': 434.31591285255234
  }
]

If the level optional parameter is specified, it will return a more detailed address. However, it takes time to calculate.

>>> jageocoder.reverse(139.6917, 35.6896, level=7)
[
  {
    'candidate': {
      'id': 12299340, 'name': '8番',
      'x': 139.691778, 'y': 35.689627, 'level': 7,
      'note': None,
      'fullname': ['東京都', '新宿区', '西新宿', '二丁目', '8番']
    },
    'dist': 7.669497303543382
  }, {
    'candidate': {
      'id': 12299330, 'name': '二丁目',
      'x': 139.691774, 'y': 35.68945, 'level': 6,
      'note': 'postcode:1600023',
      'fullname': ['東京都', '新宿区', '西新宿', '二丁目']
    },
    'dist': 17.940303970792183
  }, {
    'candidate': {
      'id': 12300588, 'name': '15番',
      'x': 139.688172, 'y': 35.689264, 'level': 7,
      'note': None,
      'fullname': ['東京都', '新宿区', '西新宿', '四丁目', '15番']
    },
    'dist': 321.50874020809823
  }
]

Explore the attribute information of an address

Use searchNode() to retrieve information about an address.

This function returns a list of type jageocoder.result.Result . You can access the address node from node element of the Result object.

>>> results = jageocoder.searchNode('新宿区西新宿２－８－１')
>>> len(results)
1
>>> results[0].matched
'新宿区西新宿２－８－'
>>> type(results[0].node)
<class 'jageocoder.node.AddressNode'>
>>> node = results[0].node
>>> node.get_fullname()
['東京都', '新宿区', '西新宿', '二丁目', '8番']

Get GeoJSON representation

You can use the as_geojson() method of the Result and AddressNode objects to obtain the GeoJSON representation.

>>> results[0].as_geojson()
{'type': 'Feature', 'geometry': {'type': 'Point', 'coordinates': [139.691778, 35.689627]}, 'properties': {'id': 12299851, 'name': '8番', 'level': 7, 'note': None, 'fullname': ['東京都', '新宿区', '西新宿', '二丁目', '8番'], 'matched': '新宿区西新宿２－８－'}}
>>> results[0].node.as_geojson()
{'type': 'Feature', 'geometry': {'type': 'Point', 'coordinates': [139.691778, 35.689627]}, 'properties': {'id': 12299851, 'name': '8番', 'level': 7, 'note': None, 'fullname': ['東京都', '新宿区', '西新宿', '二丁目', '8番']}}

Get the local government codes

There are two types of local government codes: JISX0402 (5-digit) and Local Government Code (6-digit).

You can also obtain the prefecture code JISX0401 (2 digits).

>>> node.get_city_jiscode()  # 5-digit code
'13104'
>>> node.get_city_local_authority_code() # 6-digit code
'131041'
>>> node.get_pref_jiscode()  # prefecture code
'13'

Get link URLs to maps

Generate URLs to link to GSI and Google maps.

>>> node.get_gsimap_link()
'https://maps.gsi.go.jp/#16/35.689627/139.691778/'
>>> node.get_googlemap_link()
'https://maps.google.com/maps?q=35.689627,139.691778&z=16'

Traverse the parent node

A "parent node" is a node that represents a level above the address. Get the node by attribute parent.

Now the node points to '8番', so the parent node will be '二丁目'.

>>> parent = node.parent
>>> parent.get_fullname()
['東京都', '新宿区', '西新宿', '二丁目']
>>> parent.x, parent.y
(139.691774, 35.68945)

Traverse the child nodes

A "child node" is a node that represents a level below the address. Get the node by attribute children.

There is one parent node, but there are multiple child nodes. The actual return is a SQL query object, but it can be looped through with an iterator or cast to a list.

Now the parent points to '二丁目', so the child node will be the block number (○番) contained therein.

>>> parent.children
<sqlalchemy.orm.dynamic.AppenderQuery object at 0x7fbc08404b38>
>>> [child.name for child in parent.children]
['10番', '11番', '1番', '2番', '3番', '4番', '5番', '6番', '7番', '8番', '9番']

For developers

Running the unittests

python -m unittest

tests.test_search tests for some special address notations.

• Street address in Sapporo city such as '北3西1' for '北三条西一丁目'
• Toorina in Kyoto city such as '下立売通新町西入薮ノ内町' for '薮ノ内町'

Create your own dictionary

Please use the dictionary coverter jageocoder-converter.

Sample Web Application

A sample of a simple web app using Flask is available under flask-demo.

Perform the following steps. Then, access port 5000.

cd flask-demo
pip install flask flask-cors
bash run.sh

ToDos

• Supporting address changes

  The functionality to handle address changes due to municipal consolidation, etc. has already been implemented in the C++ version, but will be implemented in this package in the future.

Contributing

Address notation varies. So suggestions for logic improvements are welcome. Please submit an issue with examples of address notations in use and how they should be parsed.

Authors

• Takeshi SAGARA - Info-proto Co.,Ltd.

License

This project is licensed under the MIT License.

This is not the scope of the dictionary data license. Please follow the license of the respective dictionary data.

Acknowledgements

We would like to thank CSIS for allowing us to provide address matching services on their institutional website for over 20 years.

We would also like to thank Professor Asanobu Kitamoto of NII for providing us with a large sample of areas using the older address system and for his many help in confirming the results of our analysis.