Other sections of this documentation have explained how Rasterio can access data stored in existing files on disk written by other programs or write files to be used by other GIS programs. Filenames have been the typical inputs and files on disk have been the typical outputs.
with rasterio.open('example.tif') as dataset: data_array = dataset.read()
There are different options for Python programs that have streams of bytes, e.g., from a network socket, as their input or output instead of filenames. One is the use of a temporary file on disk.
import tempfile with tempfile.NamedTemporaryFile() as tmpfile: tmpfile.write(data) with rasterio.open(tmpfile.name) as dataset: data_array = dataset.read()
Another is Rasterio’s
MemoryFile, an abstraction for objects in GDAL’s
MemoryFile: BytesIO meets NamedTemporaryFile
MemoryFile class behaves a bit like
NamedTemporaryFile(). A GeoTIFF file in a sequence of
data bytes can be
opened in memory as shown below.
from rasterio.io import MemoryFile with MemoryFile(data) as memfile: with memfile.open() as dataset: data_array = dataset.read()
This code can be several times faster than the code using
NamedTemporaryFile() at roughly double the price in memory.
Incremental writes to an empty
MemoryFile are also possible.
with MemoryFile() as memfile: while True: data = f.read(8192) # ``f`` is an input stream. if not data: break memfile.write(data) with memfile.open() as dataset: data_array = dataset.read()
These two modes are incompatible: a
MemoryFile initialized with a sequence
of bytes cannot be extended.
MemoryFile can also be written to using dataset API methods.
with MemoryFile() as memfile: with memfile.open(driver='GTiff', count=3, ...) as dataset: dataset.write(data_array)
MemoryFile implements the Python file protocol and
methods. Instances are thus suitable as arguments for methods like
with MemoryFile() as memfile: with memfile.open(driver='GTiff', count=3, ...) as dataset: dataset.write(data_array) requests.post('https://example.com/upload', data=memfile)