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53
.github/actions/setup-venv/action.yml
vendored
Normal file
53
.github/actions/setup-venv/action.yml
vendored
Normal file
@@ -0,0 +1,53 @@
|
||||
name: Python virtualenv
|
||||
description: Set up a Python virtual environment with caching
|
||||
inputs:
|
||||
python-version:
|
||||
description: The Python version to use
|
||||
required: true
|
||||
cache-prefix:
|
||||
description: Update this to invalidate the cache
|
||||
required: true
|
||||
default: v0
|
||||
runs:
|
||||
using: composite
|
||||
steps:
|
||||
- name: Setup Python
|
||||
uses: actions/setup-python@v4
|
||||
with:
|
||||
python-version: ${{ inputs.python-version }}
|
||||
|
||||
- shell: bash
|
||||
run: |
|
||||
# Install prerequisites.
|
||||
pip install --upgrade pip setuptools wheel virtualenv
|
||||
|
||||
- shell: bash
|
||||
run: |
|
||||
# Get the exact Python version to use in the cache key.
|
||||
echo "PYTHON_VERSION=$(python --version)" >> $GITHUB_ENV
|
||||
|
||||
- uses: actions/cache@v2
|
||||
id: virtualenv-cache
|
||||
with:
|
||||
path: .venv
|
||||
key: ${{ inputs.cache-prefix }}-${{ runner.os }}-${{ env.PYTHON_VERSION }}-${{ hashFiles('Pipfile.lock') }}
|
||||
- if: steps.virtualenv-cache.outputs.cache-hit != 'true'
|
||||
shell: bash
|
||||
run: |
|
||||
# Set up virtual environment without cache hit.
|
||||
test -d .venv || virtualenv -p $(which python) --copies --reset-app-data .venv
|
||||
. .venv/bin/activate
|
||||
pip install -e .[dev]
|
||||
|
||||
- if: steps.virtualenv-cache.outputs.cache-hit == 'true'
|
||||
shell: bash
|
||||
run: |
|
||||
# Set up virtual environment from cache hit.
|
||||
. .venv/bin/activate
|
||||
pip install --no-deps -e .[dev]
|
||||
|
||||
- shell: bash
|
||||
run: |
|
||||
# Show environment info.
|
||||
. .venv/bin/activate
|
||||
echo "✓ Installed $(python --version) virtual environment to $(which python)"
|
||||
10
.github/workflows/lint.yml
vendored
10
.github/workflows/lint.yml
vendored
@@ -1,10 +0,0 @@
|
||||
name: Lint
|
||||
|
||||
on: [push]
|
||||
|
||||
jobs:
|
||||
black:
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
- uses: psf/black@stable
|
||||
119
.github/workflows/main.yml
vendored
Normal file
119
.github/workflows/main.yml
vendored
Normal file
@@ -0,0 +1,119 @@
|
||||
name: Main
|
||||
|
||||
concurrency:
|
||||
group: ${{ github.workflow }}-${{ github.ref }}
|
||||
cancel-in-progress: true
|
||||
|
||||
# on: [push]
|
||||
|
||||
on:
|
||||
pull_request:
|
||||
branches:
|
||||
- main
|
||||
push:
|
||||
branches:
|
||||
- main
|
||||
tags:
|
||||
- "v*.*.*"
|
||||
|
||||
env:
|
||||
# Change this to invalidate existing cache.
|
||||
CACHE_PREFIX: v0
|
||||
PYTHONPATH: ./
|
||||
|
||||
jobs:
|
||||
checks:
|
||||
name: Python ${{ matrix.python }} - ${{ matrix.task.name }}
|
||||
runs-on: [ubuntu-latest]
|
||||
timeout-minutes: 15
|
||||
strategy:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
include:
|
||||
- python: "3.10"
|
||||
task:
|
||||
name: "Build"
|
||||
run: |
|
||||
python setup.py check
|
||||
python setup.py bdist_wheel sdist
|
||||
- python: "3.10"
|
||||
task:
|
||||
name: "Lint"
|
||||
run: |
|
||||
black --check .
|
||||
- python: "3.10"
|
||||
task:
|
||||
name: "Test"
|
||||
run: pytest --exitfirst --failed-first --assert=plain
|
||||
- python: "3.8"
|
||||
task:
|
||||
name: "Test (3.8)"
|
||||
run: pytest --exitfirst --failed-first --assert=plain
|
||||
steps:
|
||||
- uses: actions/checkout@v3
|
||||
|
||||
- name: Setup Python environment
|
||||
uses: ./.github/actions/setup-venv
|
||||
with:
|
||||
python-version: ${{ matrix.python }}
|
||||
cache-prefix: ${{ env.CACHE_PREFIX }}
|
||||
|
||||
- name: ${{ matrix.task.name }}
|
||||
run: |
|
||||
. .venv/bin/activate
|
||||
${{ matrix.task.run }}
|
||||
|
||||
- name: Upload package distribution files
|
||||
if: matrix.task.name == 'Build'
|
||||
uses: actions/upload-artifact@v4
|
||||
with:
|
||||
name: package
|
||||
path: dist
|
||||
|
||||
- name: Clean up
|
||||
if: always()
|
||||
run: |
|
||||
. .venv/bin/activate
|
||||
pip uninstall -y geoclustering
|
||||
|
||||
release:
|
||||
name: Release
|
||||
runs-on: ubuntu-latest
|
||||
needs: [checks]
|
||||
if: startsWith(github.ref, 'refs/tags/')
|
||||
steps:
|
||||
- uses: actions/checkout@v1
|
||||
|
||||
- name: Setup Python
|
||||
uses: actions/setup-python@v4
|
||||
with:
|
||||
python-version: "3.10"
|
||||
|
||||
- name: Install requirements
|
||||
run: |
|
||||
pip install --upgrade pip setuptools wheel "twine>=1.11.0"
|
||||
|
||||
- name: Prepare environment
|
||||
run: |
|
||||
echo "RELEASE_VERSION=${GITHUB_REF#refs/tags/v}" >> $GITHUB_ENV
|
||||
echo "TAG=${GITHUB_REF#refs/tags/}" >> $GITHUB_ENV
|
||||
|
||||
- name: Download package distribution files
|
||||
uses: actions/download-artifact@v4
|
||||
with:
|
||||
name: package
|
||||
path: dist
|
||||
|
||||
- name: Publish package to PyPI
|
||||
run: |
|
||||
twine upload -u '${{ secrets.PYPI_USERNAME }}' -p '${{ secrets.PYPI_PASSWORD }}' dist/*
|
||||
|
||||
- name: Publish GitHub release
|
||||
uses: softprops/action-gh-release@v1
|
||||
env:
|
||||
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
|
||||
with:
|
||||
# body_path: ${{ github.workspace }}-RELEASE_NOTES.md
|
||||
prerelease: ${{ contains(env.TAG, 'rc') }}
|
||||
files: |
|
||||
dist/*
|
||||
10
.pre-commit-config.yaml
Normal file
10
.pre-commit-config.yaml
Normal file
@@ -0,0 +1,10 @@
|
||||
repos:
|
||||
- repo: https://github.com/psf/black
|
||||
rev: 22.3.0
|
||||
hooks:
|
||||
- id: black
|
||||
# It is recommended to specify the latest version of Python
|
||||
# supported by your project here, or alternatively use
|
||||
# pre-commit's default_language_version, see
|
||||
# https://pre-commit.com/#top_level-default_language_version
|
||||
language_version: python3.9
|
||||
2
LICENSE
2
LICENSE
@@ -1,6 +1,6 @@
|
||||
MIT License
|
||||
|
||||
Copyright (c) 2022, Felix Spöttel
|
||||
Copyright (c) 2022, Stichting Bellingcat
|
||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining a copy
|
||||
of this software and associated documentation files (the "Software"), to deal
|
||||
|
||||
22
Pipfile
Normal file
22
Pipfile
Normal file
@@ -0,0 +1,22 @@
|
||||
[[source]]
|
||||
url = "https://pypi.org/simple"
|
||||
verify_ssl = true
|
||||
name = "pypi"
|
||||
|
||||
[packages]
|
||||
click = "*"
|
||||
geojson = "*"
|
||||
keplergl = "*"
|
||||
numpy = "*"
|
||||
pandas = "*"
|
||||
scikit-learn = "*"
|
||||
|
||||
[dev-packages]
|
||||
black = "*"
|
||||
pre-commit = "*"
|
||||
pytest = "*"
|
||||
wheel = "*"
|
||||
geoclustering = {editable = true, path = "."}
|
||||
|
||||
[requires]
|
||||
python_version = "3.9"
|
||||
2344
Pipfile.lock
generated
Normal file
2344
Pipfile.lock
generated
Normal file
File diff suppressed because it is too large
Load Diff
70
README.md
70
README.md
@@ -1,4 +1,4 @@
|
||||
# geocluster
|
||||
# geoclustering
|
||||
|
||||
> 📍 command-line tool for clustering geolocations.
|
||||
|
||||
@@ -10,34 +10,38 @@
|
||||
|
||||
### Clustering Method
|
||||
|
||||
A cluster is created when a certain number of points (=> `--size`) each are within a given distance (=> `--distance`) of at least one other point in the cluster.
|
||||
A cluster is created when a certain number of points (defined with `--size`) each are within a given distance (defined with `--distance`) of at least one other point in the cluster.
|
||||
|
||||
|
||||
## Install
|
||||
|
||||
Clone the repository:
|
||||
Install with pip:
|
||||
|
||||
```sh
|
||||
git clone https://github.com/fspoettel/geocluster
|
||||
cd geocluster
|
||||
# with kepler.gl visualization support
|
||||
pip install geoclustering[full]
|
||||
|
||||
# only text-based output
|
||||
pip install geoclustering
|
||||
```
|
||||
|
||||
Install keplergl build dependencies:
|
||||
If the `full` install fails, you might need to install kepler.gl build dependencies:
|
||||
|
||||
```sh
|
||||
# macos
|
||||
brew install proj gdal
|
||||
```
|
||||
|
||||
Install project with pip:
|
||||
```sh
|
||||
pip install .
|
||||
```
|
||||
|
||||
## Usage
|
||||
|
||||
```
|
||||
Usage: geocluster [OPTIONS] FILENAME
|
||||
Usage: geoclustering [OPTIONS] FILENAME
|
||||
|
||||
Tool to cluster geolocations. A cluster is created when a certain number of
|
||||
points (defined with --size) each are within a given distance (defined with
|
||||
--distance) of at least one other point in the cluster. Input is supplied as
|
||||
a csv file. At a minimum, each row needs to have a 'lat' and a 'lon' column.
|
||||
Other rows are reflected to the output.
|
||||
|
||||
Options:
|
||||
-d, --distance FLOAT (in km) Max. distance between two points in
|
||||
@@ -50,12 +54,15 @@ Options:
|
||||
Clustering algorithm to be used. `optics`
|
||||
produces tighter clusters but is slower.
|
||||
Default: dbscan
|
||||
--open Open the generated visualization in the
|
||||
default browser automatically.
|
||||
--debug Print debug output.
|
||||
--help Show this message and exit.
|
||||
```
|
||||
|
||||
## Input
|
||||
|
||||
Inputs are supplied as a `.csv` file. The only required fields are `lat` and `lon`, all other fields are reflected to the output.
|
||||
Inputs are supplied as a `.csv` file. At a minimum, each row needs to have a `lat` and a `lon`` column. Other rows are reflected to the output.
|
||||
|
||||
```csv
|
||||
id,name,lat,lon
|
||||
@@ -65,7 +72,7 @@ id,name,lat,lon
|
||||
|
||||
## Output
|
||||
|
||||
If at least one cluster was found, the tool outputs a folder with `json`, `geojson`, `text` and a kepler.gl `html` files.
|
||||
If at least one cluster was found, the tool outputs a folder with output as `json`, `geojson`, `txt`, `csv` files. A kepler.gl `html` file is generated as well.
|
||||
|
||||
### JSON
|
||||
|
||||
@@ -114,7 +121,7 @@ Encodes a single `FeatureCollection`, containing all points as `Feature` objects
|
||||
}
|
||||
```
|
||||
|
||||
### txt
|
||||
### Text
|
||||
|
||||
Encodes cluster as blocks separated by a newline, where each line in a cluster block contains one point.
|
||||
|
||||
@@ -125,6 +132,39 @@ id 9, name Rosanna Foggo, lat -6.2074293, lon 106.8915948
|
||||
// ...
|
||||
```
|
||||
|
||||
### CSV
|
||||
|
||||
Encodes each event in one line with `cluster_id` information associated.
|
||||
|
||||
```csv
|
||||
cluster_id,name,lat,lon
|
||||
9,Rosanna Foggo,-6.2074293,106.8915948
|
||||
...
|
||||
```
|
||||
|
||||
### kepler.gl
|
||||
|
||||

|
||||
|
||||
## Develop
|
||||
|
||||
It is assumed that you are using **Python3.9+**. It is encouraged to [setup a virtualenv](https://wiki.archlinux.org/title/Python/Virtual_environment#venv>) for development.
|
||||
|
||||
```sh
|
||||
# install dependencies & dev-dependencies
|
||||
# PIP
|
||||
pip install -e .[dev,full]
|
||||
# PIPENV
|
||||
pipenv install --dev -e .
|
||||
|
||||
# install a git hook that runs the code formatter before each commit.
|
||||
pre-commit install
|
||||
```
|
||||
|
||||
We use [Black](https://github.com/psf/black) as our code formatter. If you don't want to use the `pre-commit` hook, you can run the formatter manually or via an editor plugin.
|
||||
|
||||
## Release
|
||||
|
||||
1. Update [version.py](geoclustering/version.py)
|
||||
2. Run `scripts/release.sh`
|
||||
3. Confirm GH action completed successfully
|
||||
@@ -1,64 +0,0 @@
|
||||
import click
|
||||
import webbrowser
|
||||
|
||||
import geocluster.clustering as clustering
|
||||
import geocluster.encoding as encoding
|
||||
import geocluster.io as io
|
||||
|
||||
|
||||
@click.command()
|
||||
@click.option(
|
||||
"--distance",
|
||||
"-d",
|
||||
type=click.FLOAT,
|
||||
required=True,
|
||||
help="(in km) Max. distance between two points in a cluster.",
|
||||
)
|
||||
@click.option(
|
||||
"--size",
|
||||
"-s",
|
||||
type=click.INT,
|
||||
required=True,
|
||||
help="Min. number of points in a cluster.",
|
||||
)
|
||||
@click.option(
|
||||
"--output",
|
||||
"-o",
|
||||
type=click.Path(exists=False),
|
||||
default="output",
|
||||
help="Output directory for results. Default: ./output",
|
||||
)
|
||||
@click.option(
|
||||
"--algorithm",
|
||||
"-a",
|
||||
type=click.Choice(
|
||||
["dbscan", "optics"],
|
||||
case_sensitive=False,
|
||||
),
|
||||
default="dbscan",
|
||||
help="Clustering algorithm to be used. `optics` produces tighter clusters but is slower. Default: dbscan",
|
||||
)
|
||||
@click.argument("filename", type=click.Path(exists=True))
|
||||
def main(distance, size, output, filename, algorithm):
|
||||
df = io.read_csv_file(filename)
|
||||
|
||||
clusters = clustering.cluster_locations(
|
||||
df=df, algorithm=algorithm, radius_km=distance, min_cluster_size=size
|
||||
)
|
||||
|
||||
if not bool(clusters):
|
||||
click.echo("Did not find clusters matching input parameters.")
|
||||
return
|
||||
|
||||
encoded = encoding.encode_clusters(clusters)
|
||||
|
||||
io.write_output_file(output, "result.txt", encoded["string"])
|
||||
io.write_output_file(output, "result.json", encoded["json"])
|
||||
io.write_output_file(output, "result.geojson", encoded["geojson"])
|
||||
vis = io.write_visualization(output, "result.html", encoded["geojson"])
|
||||
|
||||
webbrowser.open_new_tab("file://" + str(vis.absolute()))
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -1,78 +0,0 @@
|
||||
from keplergl import KeplerGl
|
||||
from pathlib import Path
|
||||
from pkg_resources import resource_filename
|
||||
import json
|
||||
import json
|
||||
import pandas as pd
|
||||
import numpy as np
|
||||
|
||||
|
||||
def is_valid_lat(val: str) -> bool:
|
||||
"""Given a string, check if it corresponds to a valid decimal latitude value"""
|
||||
try:
|
||||
val = float(val)
|
||||
return val >= -90 and val <= 90
|
||||
except:
|
||||
return False
|
||||
|
||||
|
||||
def is_valid_lon(val: str) -> bool:
|
||||
"""Given a string, check if it corresponds to a valid decimal longitude value"""
|
||||
try:
|
||||
val = float(val)
|
||||
return val >= -180 and val <= 180
|
||||
except:
|
||||
return False
|
||||
|
||||
|
||||
def read_csv_file(filename):
|
||||
"""Read input csv file, dropping rows that don't have valid location data."""
|
||||
df = pd.read_csv(filename)
|
||||
initial_rows = len(df)
|
||||
|
||||
df = df.dropna(subset=["lat", "lon"])
|
||||
df = df.replace(
|
||||
{np.nan: None}
|
||||
) # replace for other fields not to break kepler parsing
|
||||
print(f"Ignored {initial_rows - len(df)} coordinates with NaN")
|
||||
|
||||
valid_index = df.lat.astype(str).apply(is_valid_lat) & df.lon.astype(str).apply(
|
||||
is_valid_lon
|
||||
)
|
||||
if len(df_invalid := df[~valid_index]):
|
||||
print(f"Found {len(df_invalid)} invalid coordinate pairs, ignoring:")
|
||||
print(df_invalid[["lat", "lon"]].to_string())
|
||||
return df[valid_index]
|
||||
|
||||
|
||||
def ensure_file_path(dirname, filename):
|
||||
"""Ensure a parent directory exists for a file."""
|
||||
path = Path(dirname)
|
||||
path.mkdir(parents=True, exist_ok=True)
|
||||
return path / filename
|
||||
|
||||
|
||||
def write_output_file(dirname, filename, data):
|
||||
"""Write a file, ensuring parent directories."""
|
||||
filepath = ensure_file_path(dirname, filename)
|
||||
|
||||
with open(filepath, "w") as f:
|
||||
f.write(data)
|
||||
|
||||
return filepath
|
||||
|
||||
|
||||
def write_visualization(dirname, filename, data):
|
||||
"""Write a visualization, ensuring parent directories."""
|
||||
map = KeplerGl()
|
||||
map.add_data(data=data, name="clusters")
|
||||
|
||||
# config configures a default color scheme for our clusters layer.
|
||||
config_file = resource_filename("geocluster", "kepler_config.json")
|
||||
with open(config_file) as f:
|
||||
map.config = json.loads(f.read())
|
||||
|
||||
filepath = ensure_file_path(dirname, filename)
|
||||
map.save_to_html(file_name=str(filepath), center_map=True)
|
||||
|
||||
return filepath
|
||||
96
geoclustering/__main__.py
Normal file
96
geoclustering/__main__.py
Normal file
@@ -0,0 +1,96 @@
|
||||
from pathlib import Path
|
||||
import click
|
||||
import webbrowser
|
||||
|
||||
import geoclustering.clustering as clustering
|
||||
import geoclustering.encoding as encoding
|
||||
import geoclustering.io as io
|
||||
|
||||
|
||||
@click.command(
|
||||
help="Tool to cluster geolocations. A cluster is created when a certain number of points (defined with --size) each are within a given distance (defined with --distance) of at least one other point in the cluster. Input is supplied as a csv file. At a minimum, each row needs to have a 'lat' and a 'lon' column. Other rows are reflected to the output."
|
||||
)
|
||||
@click.option(
|
||||
"--distance",
|
||||
"-d",
|
||||
type=click.FLOAT,
|
||||
required=True,
|
||||
help="(in km) Max. distance between two points in a cluster.",
|
||||
)
|
||||
@click.option(
|
||||
"--size",
|
||||
"-s",
|
||||
type=click.INT,
|
||||
required=True,
|
||||
help="Min. number of points in a cluster.",
|
||||
)
|
||||
@click.option(
|
||||
"--output",
|
||||
"-o",
|
||||
type=click.Path(exists=False),
|
||||
default="output",
|
||||
help="Output directory for results. Default: ./output",
|
||||
)
|
||||
@click.option(
|
||||
"--algorithm",
|
||||
"-a",
|
||||
type=click.Choice(
|
||||
["dbscan", "optics"],
|
||||
case_sensitive=False,
|
||||
),
|
||||
default="dbscan",
|
||||
help="Clustering algorithm to be used. `optics` produces tighter clusters but is slower. Default: dbscan",
|
||||
)
|
||||
@click.option(
|
||||
"--open",
|
||||
"_open",
|
||||
is_flag=True,
|
||||
help="Open the generated visualization in the default browser automatically.",
|
||||
)
|
||||
@click.option("--debug", is_flag=True, help="Print debug output.")
|
||||
@click.argument("filename", type=click.Path(exists=True))
|
||||
def main(distance, size, output, filename, algorithm, _open, debug):
|
||||
def print_debug(s):
|
||||
if debug:
|
||||
click.secho(s, fg="bright_black")
|
||||
|
||||
df = io.read_csv_file(filename)
|
||||
print_debug(f"Read {len(df)} valid coordinates from {Path(filename).absolute()}")
|
||||
|
||||
clusters = clustering.cluster_locations(
|
||||
df=df, algorithm=algorithm, radius_km=distance, min_cluster_size=size
|
||||
)
|
||||
|
||||
if not bool(clusters):
|
||||
click.secho("Did not find clusters matching input parameters.", fg="yellow")
|
||||
return
|
||||
|
||||
print_debug(f"Found {len(clusters)} valid clusters using {algorithm}")
|
||||
|
||||
encoded = encoding.encode_clusters(clusters)
|
||||
io.write_output_file(output, "result.txt", encoded["string"])
|
||||
io.write_output_file(output, "result.json", encoded["json"])
|
||||
io.write_output_file(output, "result.geojson", encoded["geojson"])
|
||||
io.write_output_file(output, "result.csv", encoded["csv"])
|
||||
|
||||
vis = io.write_visualization(output, "result.html", encoded["geojson"])
|
||||
if vis is None:
|
||||
print_debug("Skipped generating visualization: kepler is not installed.")
|
||||
|
||||
click.echo(f"Output files saved to {Path(output).absolute()}")
|
||||
|
||||
if _open:
|
||||
if vis:
|
||||
webbrowser.open_new_tab("file://" + str(vis.absolute()))
|
||||
print_debug("Opened visualization in default browser.")
|
||||
else:
|
||||
click.secho(
|
||||
"Can't open kepler.gl: package not installed. Please re-install geoclustering with `pip install geoclustering[full]`.",
|
||||
fg="yellow",
|
||||
)
|
||||
|
||||
click.secho("Clustering completed.", fg="green")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
@@ -14,8 +14,6 @@ def to_cluster_dict(df, clustering):
|
||||
"""
|
||||
clusters_by_id = {}
|
||||
|
||||
print(clustering.labels_)
|
||||
|
||||
for idx, cluster_id in enumerate(clustering.labels_):
|
||||
# ignore "noise" locations that don't belong to any cluster.
|
||||
if cluster_id > -1:
|
||||
@@ -1,6 +1,8 @@
|
||||
import json
|
||||
import numpy as np
|
||||
import geojson
|
||||
import csv
|
||||
import io # not io.py
|
||||
|
||||
|
||||
class NpEncoder(json.JSONEncoder):
|
||||
@@ -47,7 +49,7 @@ class JSONEncoder:
|
||||
|
||||
for record in cluster:
|
||||
cluster_data["points"].append(record)
|
||||
self.state.append(cluster_data)
|
||||
self.state.append(cluster_data)
|
||||
|
||||
def get(self):
|
||||
return json.dumps(self.state, cls=NpEncoder)
|
||||
@@ -74,13 +76,37 @@ class GeoJSONEncoder:
|
||||
return json.dumps(geojson.FeatureCollection(self.state), cls=NpEncoder)
|
||||
|
||||
|
||||
class CSVEncoder:
|
||||
"""Encodes clustering result as a CSV"""
|
||||
|
||||
def __init__(self):
|
||||
self.state = io.StringIO()
|
||||
self.writer = False
|
||||
|
||||
def visitor(self, cluster_id, cluster):
|
||||
if not self.writer:
|
||||
self.writer = csv.DictWriter(
|
||||
self.state,
|
||||
fieldnames=["cluster_id"] + list(cluster[0].keys()),
|
||||
quoting=csv.QUOTE_NONNUMERIC,
|
||||
lineterminator="\n",
|
||||
)
|
||||
self.writer.writeheader()
|
||||
|
||||
for record in cluster:
|
||||
self.writer.writerow({**record, "cluster_id": cluster_id})
|
||||
|
||||
def get(self):
|
||||
return self.state.getvalue()
|
||||
|
||||
|
||||
def encode_clusters(clusters):
|
||||
json_encoder = JSONEncoder()
|
||||
geojson_encoder = GeoJSONEncoder()
|
||||
string_encoder = StringEncoder()
|
||||
csv_encoder = CSVEncoder()
|
||||
|
||||
encoders = [json_encoder, geojson_encoder, string_encoder]
|
||||
|
||||
encoders = [json_encoder, geojson_encoder, string_encoder, csv_encoder]
|
||||
for cluster_id, cluster in clusters.items():
|
||||
for encoder in encoders:
|
||||
encoder.visitor(cluster_id, cluster)
|
||||
@@ -89,4 +115,5 @@ def encode_clusters(clusters):
|
||||
"json": json_encoder.get(),
|
||||
"geojson": geojson_encoder.get(),
|
||||
"string": string_encoder.get(),
|
||||
"csv": csv_encoder.get(),
|
||||
}
|
||||
120
geoclustering/io.py
Normal file
120
geoclustering/io.py
Normal file
@@ -0,0 +1,120 @@
|
||||
from pathlib import Path
|
||||
from pkg_resources import resource_filename
|
||||
import json
|
||||
import pandas as pd
|
||||
import numpy as np
|
||||
import os
|
||||
import sys
|
||||
|
||||
# kepler is optional, check if installed.
|
||||
try:
|
||||
from keplergl import KeplerGl
|
||||
except:
|
||||
has_kepler = False
|
||||
else:
|
||||
has_kepler = True
|
||||
|
||||
|
||||
class HiddenPrints:
|
||||
"""Disables stdout prints for a block of code."""
|
||||
|
||||
def __enter__(self):
|
||||
self._original_stdout = sys.stdout
|
||||
sys.stdout = open(os.devnull, "w")
|
||||
|
||||
def __exit__(self, exc_type, exc_val, exc_tb):
|
||||
sys.stdout.close()
|
||||
sys.stdout = self._original_stdout
|
||||
|
||||
|
||||
def is_valid_lat(val: str) -> bool:
|
||||
"""Given a string, check if it corresponds to a valid decimal latitude value"""
|
||||
try:
|
||||
val = float(val)
|
||||
return val >= -90 and val <= 90
|
||||
except:
|
||||
return False
|
||||
|
||||
|
||||
def is_valid_lon(val: str) -> bool:
|
||||
"""Given a string, check if it corresponds to a valid decimal longitude value"""
|
||||
try:
|
||||
val = float(val)
|
||||
return val >= -180 and val <= 180
|
||||
except:
|
||||
return False
|
||||
|
||||
|
||||
def is_not_none(val: any) -> bool:
|
||||
return val is not None
|
||||
|
||||
|
||||
def read_csv_file(filename):
|
||||
"""Read input csv file, dropping rows that don't have valid location data."""
|
||||
# replace NaN for all fields not to break kepler parsing.
|
||||
df = pd.read_csv(filename).replace({np.nan: None})
|
||||
|
||||
# construct an index of values with valid lat & lon.
|
||||
valid_index = df.lat.apply(is_valid_lat) & df.lon.apply(is_valid_lon)
|
||||
df_invalid = df[~valid_index]
|
||||
|
||||
count_invalid = len(df_invalid)
|
||||
if count_invalid:
|
||||
df_not_empty = df_invalid[
|
||||
(df_invalid.lat.apply(is_not_none) | df_invalid.lon.apply(is_not_none))
|
||||
]
|
||||
|
||||
count_not_empty = len(df_not_empty)
|
||||
count_empty = count_invalid - count_not_empty
|
||||
|
||||
if count_empty:
|
||||
print(f"Removed {count_empty} empty coordinate pairs.")
|
||||
|
||||
if count_not_empty:
|
||||
print(f"Removed {count_not_empty} invalid coordinate pairs:")
|
||||
print(df_not_empty[["lat", "lon"]].to_string())
|
||||
|
||||
return df[valid_index]
|
||||
|
||||
|
||||
def ensure_file_path(dirname, filename):
|
||||
"""Ensure a parent directory exists for a file."""
|
||||
path = Path(dirname)
|
||||
path.mkdir(parents=True, exist_ok=True)
|
||||
return path / filename
|
||||
|
||||
|
||||
def write_output_file(dirname, filename, data):
|
||||
"""Write a file, ensuring parent directories."""
|
||||
filepath = ensure_file_path(dirname, filename)
|
||||
|
||||
with open(filepath, "w") as f:
|
||||
f.write(data)
|
||||
|
||||
return filepath
|
||||
|
||||
|
||||
def write_visualization(dirname, filename, data):
|
||||
"""Write a visualization, ensuring parent directories."""
|
||||
|
||||
if not has_kepler:
|
||||
return None
|
||||
|
||||
# Hide kepler stdout output.
|
||||
with HiddenPrints():
|
||||
map = KeplerGl()
|
||||
|
||||
map.add_data(data=data, name="clusters")
|
||||
|
||||
# config configures a default color scheme for our clusters layer.
|
||||
config_file = resource_filename("geoclustering", "kepler_config.json")
|
||||
with open(config_file) as f:
|
||||
map.config = json.loads(f.read())
|
||||
|
||||
filepath = ensure_file_path(dirname, filename)
|
||||
|
||||
# Hide kepler stdout output.
|
||||
with HiddenPrints():
|
||||
map.save_to_html(file_name=str(filepath), center_map=True)
|
||||
|
||||
return filepath
|
||||
@@ -9,7 +9,7 @@
|
||||
"config": {
|
||||
"dataId": "clusters",
|
||||
"label": "clusters",
|
||||
"color": [179, 173, 158],
|
||||
"color": [248, 149, 112],
|
||||
"highlightColor": [252, 242, 26, 255],
|
||||
"columns": { "geojson": "_geojson" },
|
||||
"isVisible": true,
|
||||
@@ -19,16 +19,30 @@
|
||||
"thickness": 0.5,
|
||||
"strokeColor": null,
|
||||
"colorRange": {
|
||||
"name": "Global Warming",
|
||||
"type": "sequential",
|
||||
"name": "Uber Viz Qualitative 4",
|
||||
"type": "qualitative",
|
||||
"category": "Uber",
|
||||
"colors": [
|
||||
"#5A1846",
|
||||
"#900C3F",
|
||||
"#C70039",
|
||||
"#E3611C",
|
||||
"#F1920E",
|
||||
"#FFC300"
|
||||
"#12939A",
|
||||
"#DDB27C",
|
||||
"#88572C",
|
||||
"#FF991F",
|
||||
"#F15C17",
|
||||
"#223F9A",
|
||||
"#DA70BF",
|
||||
"#125C77",
|
||||
"#4DC19C",
|
||||
"#776E57",
|
||||
"#17B8BE",
|
||||
"#F6D18A",
|
||||
"#B7885E",
|
||||
"#FFCB99",
|
||||
"#F89570",
|
||||
"#829AE3",
|
||||
"#E79FD5",
|
||||
"#1E96BE",
|
||||
"#89DAC1",
|
||||
"#B3AD9E"
|
||||
]
|
||||
},
|
||||
"strokeColorRange": {
|
||||
11
geoclustering/version.py
Normal file
11
geoclustering/version.py
Normal file
@@ -0,0 +1,11 @@
|
||||
_MAJOR = "0"
|
||||
_MINOR = "4"
|
||||
# On main and in a nightly release the patch should be one ahead of the last
|
||||
# released build.
|
||||
_PATCH = "1"
|
||||
# This is mainly for nightly builds which have the suffix ".dev$DATE". See
|
||||
# https://semver.org/#is-v123-a-semantic-version for the semantics.
|
||||
_SUFFIX = ""
|
||||
|
||||
VERSION_SHORT = "{0}.{1}".format(_MAJOR, _MINOR)
|
||||
VERSION = "{0}.{1}.{2}{3}".format(_MAJOR, _MINOR, _PATCH, _SUFFIX)
|
||||
3
pytest.ini
Normal file
3
pytest.ini
Normal file
@@ -0,0 +1,3 @@
|
||||
[pytest]
|
||||
testpaths = tests/
|
||||
python_files = *.py
|
||||
18
scripts/release.sh
Executable file
18
scripts/release.sh
Executable file
@@ -0,0 +1,18 @@
|
||||
#!/bin/bash
|
||||
|
||||
set -e
|
||||
|
||||
TAG=$(python -c 'from geoclustering.version import VERSION; print("v" + VERSION)')
|
||||
|
||||
read -p "Creating new release for $TAG. Do you want to continue? [Y/n] " prompt
|
||||
|
||||
if [[ $prompt == "y" || $prompt == "Y" || $prompt == "yes" || $prompt == "Yes" ]]; then
|
||||
git add -A
|
||||
git commit -m "Bump version to $TAG for release" || true && git push
|
||||
echo "Creating new git tag $TAG"
|
||||
git tag "$TAG" -m "$TAG"
|
||||
git push --tags
|
||||
else
|
||||
echo "Cancelled"
|
||||
exit 1
|
||||
fi
|
||||
34
setup.py
34
setup.py
@@ -1,21 +1,41 @@
|
||||
from setuptools import setup
|
||||
|
||||
# version.py defines the VERSION and VERSION_SHORT variables.
|
||||
# We use exec here so we don't import cached_path whilst setting up.
|
||||
VERSION = {} # type: ignore
|
||||
with open("geoclustering/version.py", "r") as version_file:
|
||||
exec(version_file.read(), VERSION)
|
||||
|
||||
setup(
|
||||
name="geocluster",
|
||||
version="0.1",
|
||||
description="",
|
||||
name="geoclustering",
|
||||
version=VERSION["VERSION"],
|
||||
description="📍 command-line tool for clustering geolocations.",
|
||||
long_description=open("README.md").read(),
|
||||
long_description_content_type="text/markdown",
|
||||
classifiers=[
|
||||
"Intended Audience :: Developers",
|
||||
"Intended Audience :: Science/Research",
|
||||
"License :: OSI Approved :: MIT License",
|
||||
"Programming Language :: Python :: 3",
|
||||
],
|
||||
author="Bellingcat",
|
||||
packages=["geocluster"],
|
||||
entry_points={"console_scripts": ["geocluster = geocluster.__main__:main"]},
|
||||
author_email="tech@bellingcat.com",
|
||||
license="MIT",
|
||||
packages=["geoclustering"],
|
||||
package_data={"geoclustering": ["kepler_config.json"]},
|
||||
keywords=["cluster", "gis", "pattern-analysis"],
|
||||
entry_points={"console_scripts": ["geoclustering = geoclustering.__main__:main"]},
|
||||
install_requires=[
|
||||
"click",
|
||||
"geojson",
|
||||
"keplergl",
|
||||
"numpy",
|
||||
"pandas",
|
||||
"scikit-learn",
|
||||
],
|
||||
extras_require={"dev": ["black", "wheel"]},
|
||||
extras_require={
|
||||
"dev": ["black", "wheel", "pre-commit", "pytest"],
|
||||
"full": ["keplergl"],
|
||||
},
|
||||
include_package_data=True,
|
||||
zip_safe=False,
|
||||
)
|
||||
|
||||
0
tests/__init__.py
Normal file
0
tests/__init__.py
Normal file
41
tests/clustering.py
Normal file
41
tests/clustering.py
Normal file
@@ -0,0 +1,41 @@
|
||||
from geoclustering.clustering import cluster_locations
|
||||
from tests.helpers import read_fixture_csv
|
||||
|
||||
|
||||
df = read_fixture_csv("clustering.csv")
|
||||
|
||||
|
||||
def has_member(list, name):
|
||||
return any(x for x in list if x["name"] == name)
|
||||
|
||||
|
||||
def test_clustering_all():
|
||||
# there should be one cluster with all members but Erin.
|
||||
res = cluster_locations(
|
||||
df=df, algorithm="dbscan", radius_km=1.97, min_cluster_size=4
|
||||
)
|
||||
assert len(res.values()) == 1
|
||||
assert len(res[0]) == 4
|
||||
|
||||
|
||||
def test_clustering_split():
|
||||
res = cluster_locations(
|
||||
df=df, algorithm="dbscan", radius_km=0.5, min_cluster_size=2
|
||||
)
|
||||
# there should be two cluster: Alice & Bob and Carol & Dan
|
||||
assert len(res.values()) == 2
|
||||
cluster_one = res[0]
|
||||
cluster_two = res[1]
|
||||
assert len(cluster_one) == 2
|
||||
assert has_member(cluster_one, "Alice")
|
||||
assert has_member(cluster_one, "Bob")
|
||||
assert has_member(cluster_two, "Carol")
|
||||
assert has_member(cluster_two, "Dan")
|
||||
|
||||
|
||||
def test_clustering_none():
|
||||
# there should be no clusters now.
|
||||
res = cluster_locations(
|
||||
df=df, algorithm="dbscan", radius_km=0.5, min_cluster_size=3
|
||||
)
|
||||
assert len(res.values()) == 0
|
||||
30
tests/encoding.py
Normal file
30
tests/encoding.py
Normal file
@@ -0,0 +1,30 @@
|
||||
from geoclustering.encoding import encode_clusters
|
||||
from tests.helpers import read_fixture_csv, read_fixture_content
|
||||
|
||||
|
||||
df = read_fixture_csv("clustering.csv")
|
||||
|
||||
|
||||
def test_encoders():
|
||||
clusters = {
|
||||
0: [
|
||||
{"id": 1, "name": "Alice", "lat": 52.523955, "lon": 13.442362},
|
||||
{"id": 2, "name": "Bob", "lat": 52.526659, "lon": 13.448097},
|
||||
],
|
||||
1: [
|
||||
{"id": 3, "name": "Carol", "lat": 52.525626, "lon": 13.419246},
|
||||
{
|
||||
"id": 4,
|
||||
"name": "Dan",
|
||||
"lat": 52.52443559865125,
|
||||
"lon": 13.41261723049818,
|
||||
},
|
||||
],
|
||||
}
|
||||
|
||||
res = encode_clusters(clusters)
|
||||
|
||||
assert res["string"] == read_fixture_content("snapshots/result.txt")
|
||||
assert res["json"] == read_fixture_content("snapshots/result.json")
|
||||
assert res["geojson"] == read_fixture_content("snapshots/result.geojson")
|
||||
assert res["csv"] == read_fixture_content("snapshots/result.csv")
|
||||
6
tests/fixtures/clustering.csv
vendored
Normal file
6
tests/fixtures/clustering.csv
vendored
Normal file
@@ -0,0 +1,6 @@
|
||||
id,name,lat,lon
|
||||
1,Alice,52.523955,13.442362
|
||||
2,Bob,52.526659,13.448097
|
||||
3,Carol,52.525626,13.419246
|
||||
4,Dan,52.52443559865125,13.41261723049818
|
||||
5,Erin,52.524838991760774,13.383188597040382
|
||||
|
9
tests/fixtures/io.csv
vendored
Normal file
9
tests/fixtures/io.csv
vendored
Normal file
@@ -0,0 +1,9 @@
|
||||
id,name,lat,lon
|
||||
1,Alice,,
|
||||
2,,52.523955,13.442362
|
||||
,,-90.12,132.23
|
||||
4,,78.234,-180.1212
|
||||
5,Bob,52.524838991760774,13.383188597040382
|
||||
6,Peter,91.234,
|
||||
7,Horst,,23.23
|
||||
7,Erin,foo,bar
|
||||
|
2002
tests/fixtures/mock1000.csv
vendored
2002
tests/fixtures/mock1000.csv
vendored
File diff suppressed because it is too large
Load Diff
102
tests/fixtures/mock50.csv
vendored
102
tests/fixtures/mock50.csv
vendored
@@ -1,51 +1,51 @@
|
||||
id,name,lat,lon
|
||||
1,Bonnibelle Mathwen,40.1324085,64.4911086
|
||||
2,Fayette Elt,49.6235379,6.2379992
|
||||
3,Jandy Cooch,-7.5874497,110.7420464
|
||||
4,Robb Gerbel,22.2455315,-80.3936994
|
||||
5,Silvie Clipson,40.3418956,21.5118754
|
||||
6,Kristina Izakoff,30.741991,121.341969
|
||||
7,Ricky Sweeting,11.2666664,122.5333328
|
||||
8,Quintin Hazart,35.119385,109.167435
|
||||
9,Sholom Kilmister,55.7393377,37.6642542
|
||||
10,Misty Dooher,49.9776657,20.9421091
|
||||
11,Knox Phython,-8.4985,123.5226
|
||||
12,Shay Davidy,14.4142191,120.9495257
|
||||
13,Dre Benoey,-31.4561755,-64.2111608
|
||||
14,Prudi Tomek,40.692169,117.163821
|
||||
15,Evey Ealam,31.123586,114.893666
|
||||
16,Norry Urch,45.8022541,17.497172
|
||||
17,Valerye Dumberell,50.4438122,48.1450932
|
||||
18,Freddy Furtado,58.3767785,11.6764538
|
||||
19,Catarina Samett,50.4034992,26.141892
|
||||
20,Lidia Muckian,-38.7359018,-72.5903739
|
||||
21,Stacey Dockrey,29.741986,106.273576
|
||||
22,Norri Bonhill,60.6184239,16.7769535
|
||||
23,Florence Pretsel,55.96667,25.15
|
||||
24,Marten Matantsev,50.9603536,14.3596743
|
||||
25,Claiborn Everall,43.884893,-0.5046003
|
||||
26,Randolf Hailey,49.4679131,18.2282007
|
||||
27,Meggi Kirkebye,57.6888453,11.9943311
|
||||
28,Denna Le Grove,16.7124054,98.5746649
|
||||
29,Randy Verheijden,40.4722617,-7.9751886
|
||||
30,Caterina Blancowe,35.422892,103.352654
|
||||
31,Joanne Adamovitch,55.9251242,39.4489055
|
||||
32,Orazio Coppins,,111.6556388
|
||||
33,Anastassia Bennedsen,45.212088,130.478187
|
||||
34,Linoel Ruggier,22.066171,107.781956
|
||||
35,Paulina Moralis,-11.806679,-77.1657716
|
||||
36,Ambur Outhwaite,59.4033695,17.9443213
|
||||
37,Laetitia Aspland,37.6086169,138.9089988
|
||||
38,Dew Moxstead,6.1317011,-75.6382657
|
||||
39,Berna Klaiser,40.1394691,-8.3092933
|
||||
40,Krystle Ingold,7.1518505,0.4738293
|
||||
41,Cassaundra Cuffin,56.6342788,36.885813
|
||||
42,Malanie Harpin,46.9,109.75
|
||||
43,Laurence Stothart,39.912765,116.18362
|
||||
44,Luz O'Siaghail,40.4476834,25.5917918
|
||||
45,Brittni Garrod,59.0836123,16.18741
|
||||
46,Karlie Semrad,-8.793392,121.9330894
|
||||
47,Leigh Allderidge,45.768045,15.947739
|
||||
48,Ashlin Gogerty,50.3250139,34.9100068
|
||||
49,Mozelle De Launde,53.31611,40.70806
|
||||
50,Ema le Keux,41.6315023,19.9310781
|
||||
id,name,lat,lon
|
||||
1,Bonnibelle Mathwen,40.1324085,64.4911086
|
||||
2,Fayette Elt,49.6235379,6.2379992
|
||||
3,Jandy Cooch,-7.5874497,110.7420464
|
||||
4,Robb Gerbel,22.2455315,-80.3936994
|
||||
5,Silvie Clipson,40.3418956,21.5118754
|
||||
6,Kristina Izakoff,30.741991,121.341969
|
||||
7,Ricky Sweeting,11.2666664,122.5333328
|
||||
8,Quintin Hazart,35.119385,109.167435
|
||||
9,Sholom Kilmister,55.7393377,37.6642542
|
||||
10,Misty Dooher,49.9776657,20.9421091
|
||||
11,Knox Phython,-8.4985,123.5226
|
||||
12,Shay Davidy,14.4142191,120.9495257
|
||||
13,Dre Benoey,-31.4561755,-64.2111608
|
||||
14,Prudi Tomek,40.692169,117.163821
|
||||
15,Evey Ealam,31.123586,114.893666
|
||||
16,Norry Urch,45.8022541,17.497172
|
||||
17,Valerye Dumberell,50.4438122,48.1450932
|
||||
18,Freddy Furtado,58.3767785,11.6764538
|
||||
19,Catarina Samett,50.4034992,26.141892
|
||||
20,Lidia Muckian,-38.7359018,-72.5903739
|
||||
21,Stacey Dockrey,29.741986,106.273576
|
||||
22,Norri Bonhill,60.6184239,16.7769535
|
||||
23,Florence Pretsel,55.96667,25.15
|
||||
24,Marten Matantsev,50.9603536,14.3596743
|
||||
25,Claiborn Everall,43.884893,-0.5046003
|
||||
26,Randolf Hailey,49.4679131,18.2282007
|
||||
27,Meggi Kirkebye,57.6888453,11.9943311
|
||||
28,Denna Le Grove,16.7124054,98.5746649
|
||||
29,Randy Verheijden,40.4722617,-7.9751886
|
||||
30,Caterina Blancowe,35.422892,103.352654
|
||||
31,Joanne Adamovitch,55.9251242,39.4489055
|
||||
32,Orazio Coppins,,111.6556388
|
||||
33,Anastassia Bennedsen,45.212088,130.478187
|
||||
34,Linoel Ruggier,22.066171,107.781956
|
||||
35,Paulina Moralis,-11.806679,-77.1657716
|
||||
36,Ambur Outhwaite,59.4033695,17.9443213
|
||||
37,Laetitia Aspland,37.6086169,138.9089988
|
||||
38,Dew Moxstead,6.1317011,-75.6382657
|
||||
39,Berna Klaiser,40.1394691,-8.3092933
|
||||
40,Krystle Ingold,7.1518505,0.4738293
|
||||
41,Cassaundra Cuffin,56.6342788,36.885813
|
||||
42,Malanie Harpin,46.9,109.75
|
||||
43,Laurence Stothart,39.912765,116.18362
|
||||
44,Luz O'Siaghail,40.4476834,25.5917918
|
||||
45,Brittni Garrod,59.0836123,16.18741
|
||||
46,Karlie Semrad,-8.793392,121.9330894
|
||||
47,Leigh Allderidge,45.768045,15.947739
|
||||
48,Ashlin Gogerty,50.3250139,34.9100068
|
||||
49,Mozelle De Launde,53.31611,40.70806
|
||||
50,Ema le Keux,41.6315023,19.9310781
|
||||
|
||||
|
5
tests/fixtures/snapshots/result.csv
vendored
Normal file
5
tests/fixtures/snapshots/result.csv
vendored
Normal file
@@ -0,0 +1,5 @@
|
||||
"cluster_id","id","name","lat","lon"
|
||||
0,1,"Alice",52.523955,13.442362
|
||||
0,2,"Bob",52.526659,13.448097
|
||||
1,3,"Carol",52.525626,13.419246
|
||||
1,4,"Dan",52.52443559865125,13.41261723049818
|
||||
|
1
tests/fixtures/snapshots/result.geojson
vendored
Normal file
1
tests/fixtures/snapshots/result.geojson
vendored
Normal file
@@ -0,0 +1 @@
|
||||
{"type": "FeatureCollection", "features": [{"type": "Feature", "geometry": {"type": "Point", "coordinates": [13.442362, 52.523955]}, "properties": {"id": 1, "name": "Alice", "cluster_id": 0}}, {"type": "Feature", "geometry": {"type": "Point", "coordinates": [13.448097, 52.526659]}, "properties": {"id": 2, "name": "Bob", "cluster_id": 0}}, {"type": "Feature", "geometry": {"type": "Point", "coordinates": [13.419246, 52.525626]}, "properties": {"id": 3, "name": "Carol", "cluster_id": 1}}, {"type": "Feature", "geometry": {"type": "Point", "coordinates": [13.412617, 52.524436]}, "properties": {"id": 4, "name": "Dan", "cluster_id": 1}}]}
|
||||
1
tests/fixtures/snapshots/result.json
vendored
Normal file
1
tests/fixtures/snapshots/result.json
vendored
Normal file
@@ -0,0 +1 @@
|
||||
[{"cluster_id": 0, "points": [{"id": 1, "name": "Alice", "lat": 52.523955, "lon": 13.442362}, {"id": 2, "name": "Bob", "lat": 52.526659, "lon": 13.448097}]}, {"cluster_id": 1, "points": [{"id": 3, "name": "Carol", "lat": 52.525626, "lon": 13.419246}, {"id": 4, "name": "Dan", "lat": 52.52443559865125, "lon": 13.41261723049818}]}]
|
||||
7
tests/fixtures/snapshots/result.txt
vendored
Normal file
7
tests/fixtures/snapshots/result.txt
vendored
Normal file
@@ -0,0 +1,7 @@
|
||||
Cluster 0
|
||||
id 1, name Alice, lat 52.523955, lon 13.442362
|
||||
id 2, name Bob, lat 52.526659, lon 13.448097
|
||||
|
||||
Cluster 1
|
||||
id 3, name Carol, lat 52.525626, lon 13.419246
|
||||
id 4, name Dan, lat 52.52443559865125, lon 13.41261723049818
|
||||
16
tests/helpers.py
Normal file
16
tests/helpers.py
Normal file
@@ -0,0 +1,16 @@
|
||||
import os
|
||||
from geoclustering.io import read_csv_file
|
||||
|
||||
|
||||
def get_fixture_path(filename):
|
||||
dir_path = os.path.dirname(os.path.realpath(__file__))
|
||||
return os.path.join(dir_path, "fixtures", filename)
|
||||
|
||||
|
||||
def read_fixture_csv(filename):
|
||||
return read_csv_file(get_fixture_path(filename))
|
||||
|
||||
|
||||
def read_fixture_content(filename):
|
||||
with open(get_fixture_path(filename)) as f:
|
||||
return f.read()
|
||||
25
tests/io.py
Normal file
25
tests/io.py
Normal file
@@ -0,0 +1,25 @@
|
||||
from pathlib import Path
|
||||
import shutil
|
||||
from geoclustering.io import write_output_file
|
||||
from tests.helpers import read_fixture_csv
|
||||
|
||||
|
||||
def test_csv_filters():
|
||||
df = read_fixture_csv("io.csv")
|
||||
# entries 2 & 5 in fixture are valid.
|
||||
assert len(df) == 2
|
||||
assert df.iloc[0]["name"] == None
|
||||
assert df.iloc[1]["name"] == "Bob"
|
||||
|
||||
|
||||
def test_write_output_file():
|
||||
p = "./this/dir/does/not/exist"
|
||||
f = "test.txt"
|
||||
write_output_file(p, f, "test")
|
||||
|
||||
path = Path(p) / f
|
||||
|
||||
with open(path) as f:
|
||||
assert f.read() == "test"
|
||||
|
||||
shutil.rmtree(Path("./this"))
|
||||
Reference in New Issue
Block a user