This library supports reading and writing ESRI Shapefiles in pure Julia, as well as .zip files that contain shapefiles.
Basic example of reading a shapefile from test cases:
using Shapefile
path = joinpath(dirname(pathof(Shapefile)),"..","test","shapelib_testcases","test.shp")
table = Shapefile.Table(path)
# if you only want the geometries and not the metadata in the DBF file
geoms = Shapefile.shapes(table)
# whole columns can be retrieved by their name
table.Descriptio # => Union{String, Missing}["Square with triangle missing", "Smaller triangle", missing]
# example function that iterates over the rows and gathers shapes that meet specific criteria
function selectshapes(table)
geoms = empty(Shapefile.shapes(table))
for row in table
if !ismissing(row.TestDouble) && row.TestDouble < 2000.0
push!(geoms, Shapefile.shape(row))
end
end
return geoms
end
# the metadata can be converted to other Tables such as DataFrame
using DataFrames
df = DataFrame(table)Shapefiles can contain multiple parts for each shape entity.
Use GeoInterface.coordinates to fully decompose the shape data into parts.
# Example of converting the 1st shape of the file into parts (array of coordinates)
julia> GeoInterface.coordinates(Shapefile.shape(first(table)))
2-element Vector{Vector{Vector{Vector{Float64}}}}:
[[[20.0, 20.0], [20.0, 30.0], [30.0, 30.0], [20.0, 20.0]]]
[[[0.0, 0.0], [100.0, 0.0], [100.0, 100.0], [0.0, 100.0], [0.0, 0.0]]]Shapefiles that are compressed into a .zip file can be read by Shapefile.Table if you load the ZipFile library first.
If you want another lightweight pure Julia package for reading feature files, consider also GeoJSON.jl.
For more fully featured support for reading and writing geospatial data, at the cost of a larger binary dependency, look at ArchGDAL.jl or GeoDataFrames.jl.