# `quads`
[](https://quads.readthedocs.io/en/latest/?badge=latest)
A pure Python Quadtree implementation.
[Quadtrees](https://en.wikipedia.org/wiki/Quadtree) are a useful data
structure for sparse datasets where the location/position of the data is
important. They're especially good for spatial indexing & image processing.
An actual visualization of a `quads.QuadTree`:
## Usage
Full documentation at https://quads.readthedocs.io/en/latest/
```python
>>> import quads
>>> tree = quads.QuadTree(
... (0, 0), # The center point
... 10, # The width
... 10, # The height
... )
# You can choose to simply represent points that exist.
>>> tree.insert((1, 2))
True
# ...or include extra data at those points.
>>> tree.insert(quads.Point(4, -3, data="Samus"))
True
# You can search for a given point. It returns the point if found...
>>> tree.find((1, 2))
Point(1, 2)
# Or `None` if there's no match.
>>> tree.find((4, -4))
None
# You can also find all the points within a given region.
>>> bb = quads.BoundingBox(min_x=-1, min_y=-2, max_x=2, max_y=2)
>>> tree.within_bb(bb)
[Point(1, 2)]
# You can also search to find the nearest neighbors of a point, even
# if that point doesn't have data within the quadtree.
>>> tree.nearest_neighbors((0, 1), count=2)
[
Point(1, 2),
Point(4, -4),
]
# And if you have `matplotlib` installed (not required!), you can visualize
# the tree.
>>> quads.visualize(tree)
```
## Installation
```
$ pip install quads
```
## Requirements
* Python 3.7+ (untested on older versions but may work)
## Running Tests
```
$ git clone https://github.com/toastdriven/quads.git
$ cd quads
$ poetry install
$ poetry shell
# Just the tests.
$ pytest .
# With coverage.
$ pytest -s --cov=quads .
# And with pretty reports.
$ pytest -s --cov=quads . && coverage html
```
## License
New BSD
Raw data
{
"_id": null,
"home_page": "https://github.com/toastdriven/quads",
"name": "quads",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.7,<4.0",
"maintainer_email": "",
"keywords": "",
"author": "Daniel Lindsley",
"author_email": "daniel@toastdriven.com",
"download_url": "https://files.pythonhosted.org/packages/74/c7/257b7c30a7483e7cc699d0faf1695a04d3251f955789339a8d8f50c74008/quads-1.1.0.tar.gz",
"platform": "",
"description": "# `quads`\n\n[](https://quads.readthedocs.io/en/latest/?badge=latest)\n\n\nA pure Python Quadtree implementation.\n\n[Quadtrees](https://en.wikipedia.org/wiki/Quadtree) are a useful data\nstructure for sparse datasets where the location/position of the data is\nimportant. They're especially good for spatial indexing & image processing.\n\nAn actual visualization of a `quads.QuadTree`:\n\n\n\n\n## Usage\n\nFull documentation at https://quads.readthedocs.io/en/latest/\n\n```python\n>>> import quads\n>>> tree = quads.QuadTree(\n... (0, 0), # The center point\n... 10, # The width\n... 10, # The height\n... )\n\n# You can choose to simply represent points that exist.\n>>> tree.insert((1, 2))\nTrue\n# ...or include extra data at those points.\n>>> tree.insert(quads.Point(4, -3, data=\"Samus\"))\nTrue\n\n# You can search for a given point. It returns the point if found...\n>>> tree.find((1, 2))\nPoint(1, 2)\n\n# Or `None` if there's no match.\n>>> tree.find((4, -4))\nNone\n\n# You can also find all the points within a given region.\n>>> bb = quads.BoundingBox(min_x=-1, min_y=-2, max_x=2, max_y=2)\n>>> tree.within_bb(bb)\n[Point(1, 2)]\n\n# You can also search to find the nearest neighbors of a point, even\n# if that point doesn't have data within the quadtree.\n>>> tree.nearest_neighbors((0, 1), count=2)\n[\n Point(1, 2),\n Point(4, -4),\n]\n\n# And if you have `matplotlib` installed (not required!), you can visualize\n# the tree.\n>>> quads.visualize(tree)\n```\n\n\n## Installation\n\n```\n$ pip install quads\n```\n\n\n## Requirements\n\n* Python 3.7+ (untested on older versions but may work)\n\n\n## Running Tests\n\n```\n$ git clone https://github.com/toastdriven/quads.git\n$ cd quads\n$ poetry install\n$ poetry shell\n\n# Just the tests.\n$ pytest .\n\n# With coverage.\n$ pytest -s --cov=quads .\n# And with pretty reports.\n$ pytest -s --cov=quads . && coverage html\n```\n\n\n## License\n\nNew BSD\n",
"bugtrack_url": null,
"license": "BSD-3-Clause",
"summary": "A pure Python Quadtree implementation.",
"version": "1.1.0",
"project_urls": {
"Homepage": "https://github.com/toastdriven/quads",
"Repository": "https://github.com/toastdriven/quads"
},
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "0a18053514fdacc17ac4439496e44ccc99547e1672afce1536a2a8e84aacf5c2",
"md5": "808d7c3c9d1c350fa04f2cf981b28a2a",
"sha256": "4f2a05381f07fdf6d61352b0893819b2c52ae2286211c74bd9639a28d6424540"
},
"downloads": -1,
"filename": "quads-1.1.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "808d7c3c9d1c350fa04f2cf981b28a2a",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.7,<4.0",
"size": 9413,
"upload_time": "2020-07-22T21:15:04",
"upload_time_iso_8601": "2020-07-22T21:15:04.962101Z",
"url": "https://files.pythonhosted.org/packages/0a/18/053514fdacc17ac4439496e44ccc99547e1672afce1536a2a8e84aacf5c2/quads-1.1.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "74c7257b7c30a7483e7cc699d0faf1695a04d3251f955789339a8d8f50c74008",
"md5": "a4b4379fadbddd3e8bcaae1688e79528",
"sha256": "59c1d86e551a734ea83c61c185c84873cf604b54bbacdfdbce831067715ecc7e"
},
"downloads": -1,
"filename": "quads-1.1.0.tar.gz",
"has_sig": false,
"md5_digest": "a4b4379fadbddd3e8bcaae1688e79528",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.7,<4.0",
"size": 9639,
"upload_time": "2020-07-22T21:15:06",
"upload_time_iso_8601": "2020-07-22T21:15:06.148963Z",
"url": "https://files.pythonhosted.org/packages/74/c7/257b7c30a7483e7cc699d0faf1695a04d3251f955789339a8d8f50c74008/quads-1.1.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2020-07-22 21:15:06",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "toastdriven",
"github_project": "quads",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "quads"
}
JSON
