def read_vsimem(path, band_number=1):
"""
Read a single band into memory from a raster. This method
does not support all raster formats, only those that are
supported by /vsimem
Parameters
----------
path: string
Path to the raster file. Can be either local or s3/gs.
band_number: int
The band number to use
Returns
-------
RasterBand
"""
filename = str(uuid4())
with fileutils.open(path) as inf:
gdal.FileFromMemBuffer("/vsimem/%s" % filename,
inf.read())
ds = gdal.Open("/vsimem/%s" % filename)
gdal.Unlink("/vsimem/%s" % filename)
return RasterBand(ds, band_number=band_number)
def read_vsimem(path, band_number=1):
"""
Read a single band into memory from a raster. This method
does not support all raster formats, only those that are
supported by /vsimem
Parameters
----------
path: string
Path to the raster file. Can be either local or s3/gs.
band_number: int
The band number to use
Returns
-------
RasterBand
"""
filename = str(uuid4())
with fileutils.open(path) as inf:
gdal.FileFromMemBuffer("/vsimem/%s" % filename, inf.read())
ds = gdal.Open("/vsimem/%s" % filename)
gdal.Unlink("/vsimem/%s" % filename)
return RasterBand(ds, band_number=band_number)
def to_json(self, path=None, df=None, precision=6):
"""Return the layer as a GeoJSON. If a path is provided,
it will save to the path. Otherwise, will return a string.
Parameters
----------
path: str, (default=None)
The path to save the geojson data.
df: pandas.DataFrame (default=None)
The dataframe to supply the properties of the features.
The index of df must match the ids of the VectorLayer.
precision: int
Number of decimal places to keep for floats
Returns
-------
geojson string
"""
res = self.to_dict(df=df)
s = pd.io.json.dumps(res, double_precision=precision)
if path is None:
return s
else:
with fileutils.open(path, 'wb') as outf:
outf.write(s)
def to_json(self, path=None, df=None, precision=6):
"""Return the layer as a GeoJSON. If a path is provided,
it will save to the path. Otherwise, will return a string.
Parameters
----------
path: str, (default=None)
The path to save the geojson data.
df: pandas.DataFrame (default=None)
The dataframe to supply the properties of the features.
The index of df must match the ids of the VectorLayer.
precision: int
Number of decimal places to keep for floats
Returns
-------
geojson string
"""
res = self.to_dict(df=df)
s = pd.io.json.dumps(res, double_precision=precision)
if path is None:
return s
else:
with fileutils.open(path, 'wb') as outf:
outf.write(s)
def fetch_geojson(path):
url = urlparse(path)
if "http" in url.scheme:
geojson = requests.get(path).text
elif "s3" in url.scheme or url.scheme == "" or url.scheme == "file" or url.scheme == "gs":
with fileutils.open(path) as inf:
geojson = inf.read()
else:
return path
return geojson
def fetch_geojson(path):
url = urlparse(path)
if "http" in url.scheme:
geojson = requests.get(path).text
elif "s3" in url.scheme or url.scheme == "" or url.scheme == "file" or url.scheme == "gs":
with fileutils.open(path) as inf:
geojson = inf.read()
else:
return path
return geojson
def test_raster_io_gs():
filepath = 'data/raster/prism.tif'
gs_path = 'gs://%s/%s' % (gs_bucket_name, filepath)
# write a raster file to gs
outf = fileutils.open(gs_path, "wb")
with open(os.path.join(base, filepath)) as inf:
outf.write(inf.read())
outf.close()
# read the raster file from gs
rd = rst.read_raster(gs_path)
assert isinstance(rd, rst.RasterDataset)
# clean up
delete_gs_key(filepath)
def upload(local_filename, remote_path, remove_local=False):
"""Upload a local file to a remote location. Currently,
only s3/gs is suppported"""
uri = fileutils.parse_uri(remote_path)
if remote_path.endswith("/"):
fname = os.path.basename(local_filename)
if uri.scheme == "file":
uri.uri_path += fname
elif uri.scheme in ["s3", "gs"]:
uri.key_id += fname
else:
raise ValueError("%s must be local or s3/gs" % remote_path)
outf = fileutils.open(remote_path, "wb")
with open(local_filename) as inf:
for p in read_in_chunks(inf):
outf.write(p)
outf.close()
if remove_local:
os.remove(local_filename)
return str(uri)
def upload(local_filename, remote_path, remove_local=False):
"""Upload a local file to a remote location. Currently,
only s3 is suppported"""
uri = fileutils.parse_uri(remote_path)
if remote_path.endswith("/"):
fname = os.path.basename(local_filename)
if uri.scheme == "file":
uri.uri_path += fname
elif uri.scheme == "s3":
uri.key_id += fname
else:
raise ValueError("%s must be local or s3" % remote_path)
outf = fileutils.open(remote_path, "wb")
with open(local_filename) as inf:
for p in read_in_chunks(inf):
outf.write(p)
outf.close()
if remove_local:
os.remove(local_filename)
return str(uri)
def save(self, path):
"""Save the html to a file. Can be local or s3. If s3, assumes that
a .boto file exists"""
with fileutils.open(path, 'wb') as outf:
self._render()
outf.write(self.html)
def save(self, path):
"""Save the html to a file. Can be local or s3. If s3, assumes that
a .boto file exists"""
with fileutils.open(path, 'wb') as outf:
self._render()
outf.write(self.html)
