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Simple maps from the command line.
https://expediagroup.github.io/map-maker/
Installation is simple: install with pip
(or pip3
depending on your setup)
pip install map_maker
To test, run the following command (in the cloned repository):
map_maker data/bigfoot_sightings.csv data/texas_cities.csv
After it runs, a browser opens with a map of Bigfoot sightings in Texas, along with some polygons and lines around major metropolitan areas.
By default map maker uses Bokeh as a backend. To see the same map with Folium / Leaflet, run this command:
map_maker data/bigfoot_sightings.csv data/texas_cities.csv --backend folium
In the project directory you'll see a file map.html
- this is the map file.
As of right now, the data must be in csv format with the following fields:
name | type | description |
---|---|---|
shape | string | A shape encoded as WKT or GeoJSON in EPSG:4326 lon/lat coordinates. |
color | string | The color for the shape. For polygons this is fill and line color. Optional - default black. |
alpha | float | The alpha value of the shape. For polygons this is the fill alpha. Set to zero for a transparent polygon. Optional - default light blue. |
size | float | For points, the size of the point. For polygons and lines it's the width of the line. Default: 2.0 |
other | anything | Other columns are turned into tooltips on the map. Tooltip behavior is controlled with --tooltip . |
Other fields are permitted, but the above are required.
This is the only required argument to run map maker. Map maker supports multiple csv files, which can be useful if you need different tooltip fields for different datasets (i.e. polygons get one kind of tooltip, points get another). Options are:
Usage: map_maker [OPTIONS] [MAP_DATA_FILES]...
Creates a map from the input files
Arguments:
MAP_DATA_FILES - The csv input file(s), requires the following columns:
shape - The shape in WKT format, in EPSG:4326 lat/lon coordinates.
color [optional] - The color as a string.
alpha [optional] - The alpha as a float.
size [optional] - For points, the size of the point. For linestrings
and polygons, the width of the lines.
others [optional] - Other fields turn into tooltips.
Supports multiple files, which can be useful if the tooltip columns are
different.
Options:
-h, --plot-height INTEGER The height of the plot. Default: 800
-w, --plot-width INTEGER The width of the plot. Default: 800
-s, --point-size FLOAT The size of the points. Default: 2.0.
-l, --polygon-line-width FLOAT Line width of the polygon outline. Default
2.0. Set to 0 to disable polygon outlines.
-L, --linestring-width FLOAT Width of the linestrings. Default 2.0.
-o, --output-file TEXT The name of the output file for the map.
Default: map.html.
-t, --tooltip [points|linestrings|polygons]
Whether to display tooltips for the points,
linestrings, or polygons. Stackable.
Default: points.
-b, --backend [bokeh|folium] The backend to draw the map with. Current
choices are folium, bokeh. Default: bokeh
--help Show this message and exit.
As a library, map_maker
exposes one function: make_map_plot
.
make_map_plot
is imported from one of two backends: Bokeh or Folium.
Bokeh draws the map using custom Javascript, while Folium is powered by Leaflet, a popular Javascript mapping library.
The function can be imported as follows:
from map_maker.bokeh import make_map_plot
from map_maker.folium import make_map_plot
Both return a map as their respective plot objects, but they take the same data structure.
The tiles
keyword argument is different for both.
Consult the documentation for Bokeh and Folium if you want to change the tiles.
make_map_plot
returns a populated map, built from a list of dictionaries with the same schema as the CSV file command line input.
# If shape1 and shape2 are Shapely objects in EPSG:4326,
map_data = [
{
"shape": shape1,
"color": "red",
"alpha": 0.1,
"size": 1.0,
"number": 5 # <- becomes a tooltip
},
{
"shape": shape2,
"color": "blue" # alpha, color and size are optional, just like CSV.
"number": 1 # <- becomes a tooltip
}
]
map_plot = make_map_plot(map_data)
show(map_plot)
shape1
and shape2
can be Shapely shapes, WKT strings, GeoJSON strings or dictionaries.
It has the following signature:
def make_map_plot(
map_data,
plot_height=800,
plot_width=800,
tiles="cartodbpositron",
# The size fields are defaults. They're overridden by entries in map_data.
point_size=2,
polygon_line_width=2,
linestring_width=2,
tooltips={"points"}, # Can also be linestrings and polygons.
)
For development we've created a conda environment with the development dependencies. Miniconda is the simplest but regular Anaconda installations will work too.
To get started developing, clone the repo and build the development conda environment
# Create the environment.
conda env create -f environment.yaml
# Activate it.
conda activate map-maker
Then install the package as editable
# pip or pip3 depending on your setup.
pip install -e .
Note conda isn't required - you can use a virtualenv if you like and install the following packages yourself:
Once those are installed you then need to run pip install -e .
inside the virtualenv to install a local copy of the package for editing and testing.
Once the environment and package is installed, you can run the make targets for testing, linting, and building the docs.
# Runs pytest with pytest-cov for code coverage.
make test
# Runs flake8 on the `map_maker` and `tests` directories.
make lint
# Builds the sphinx docs.
make documentation
Makefile
- for development. Testing, linting and doc targets.
README.md
- Documentation.
map_maker/
- Source code.
environment.yaml
- Contains the runtime dependencies for development.
data
- Sample csvs and screen shots of outputs.
setup.py
- Defines python packaging.
sphinx-docs
- Documentation.
MANIFEST.in / setup.cfg / versioneer.py
- For versioneer.
This project is available under the Apache 2.0 License.
Copyright 2020 Expedia, Inc.
FAQs
Unknown package
We found that map-maker demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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