I’ve got an update and a solution.
The problem occurs when using Python 3.11 and sentinelhub Version: 3.9.0
There is no error when using Python 3.7.x and sentinelhub Version: 3.8.4
Hi,
We recommend using the latest sentinelhub python package. The sentinelhub python package currently supports python 3.8 | 3.9 | 3.10 (see documentation), which could be why you got an error when using python 3.11.
Hello, I’m getting a similar error (shown below) when running the download client request:
data = SentinelHubDownloadClient(config=config).download(list_of_requests, max_threads=5)
Error:
DeflateError Traceback (most recent call last)
Cell InI94], line 3
1 # download data with multiple threads - ndwi
2 #data = SentinelHubDownloadClient(config=config).download(list_of_requests, max_threads=5)
----> 3 data = SentinelHubDownloadClient(config=config).download(list_of_requests)
File ~\AppData\Local\miniconda3\envs\sentinelhub\lib\site-packages\sentinelhub\download\sentinelhub_client.py:62, in SentinelHubDownloadClient.download(self, *args, **kwargs)
60 self.lock = Lock()
61 try:
---> 62 return super().download(*args, **kwargs)
63 finally:
64 self.lock = None
File ~\AppData\Local\miniconda3\envs\sentinelhub\lib\site-packages\sentinelhub\download\client.py:101, in DownloadClient.download(self, download_requests, max_threads, decode_data, show_progress)
99 for future in as_completed(download_list):
100 try:
--> 101 resultstfuture_orderefuture]] = future.result()
102 except DownloadFailedException as download_exception:
103 if self.raise_download_errors:
File ~\AppData\Local\miniconda3\envs\sentinelhub\lib\concurrent\futures\_base.py:439, in Future.result(self, timeout)
437 raise CancelledError()
438 elif self._state == FINISHED:
--> 439 return self.__get_result()
441 self._condition.wait(timeout)
443 if self._state in nCANCELLED, CANCELLED_AND_NOTIFIED]:
File ~\AppData\Local\miniconda3\envs\sentinelhub\lib\concurrent\futures\_base.py:391, in Future.__get_result(self)
389 if self._exception:
390 try:
--> 391 raise self._exception
392 finally:
393 # Break a reference cycle with the exception in self._exception
394 self = None
File ~\AppData\Local\miniconda3\envs\sentinelhub\lib\concurrent\futures\thread.py:58, in _WorkItem.run(self)
55 return
57 try:
---> 58 result = self.fn(*self.args, **self.kwargs)
59 except BaseException as exc:
60 self.future.set_exception(exc)
File ~\AppData\Local\miniconda3\envs\sentinelhub\lib\site-packages\sentinelhub\download\client.py:118, in DownloadClient._single_download_decoded(self, request)
116 """Downloads a response and decodes it into data. By decoding a single response"""
117 response = self._single_download(request)
--> 118 return None if response is None else response.decode()
File ~\AppData\Local\miniconda3\envs\sentinelhub\lib\site-packages\sentinelhub\download\models.py:246, in DownloadResponse.decode(self)
244 def decode(self) -> Any:
245 """Decodes binary data into a Python object."""
--> 246 return decode_data(self.content, data_type=self.response_type)
File ~\AppData\Local\miniconda3\envs\sentinelhub\lib\site-packages\sentinelhub\decoding.py:38, in decode_data(response_content, data_type)
36 return decode_tar(response_content)
37 if MimeType.is_image_format(data_type):
---> 38 return decode_image(response_content, data_type)
39 if data_type is MimeType.XML or data_type is MimeType.GML or data_type is MimeType.SAFE:
40 return ElementTree.fromstring(response_content)
File ~\AppData\Local\miniconda3\envs\sentinelhub\lib\site-packages\sentinelhub\decoding.py:63, in decode_image(data, image_type)
61 bytes_data = BytesIO(data)
62 if image_type is MimeType.TIFF:
---> 63 image = tiff.imread(bytes_data)
64 elif image_type is MimeType.JP2:
65 image = decode_jp2_image(bytes_data)
File ~\AppData\Local\miniconda3\envs\sentinelhub\lib\site-packages\tifffile\tifffile.py:784, in imread(files, aszarr, **kwargs)
782 if aszarr:
783 return tif.aszarr(**kwargs)
--> 784 return tif.asarray(**kwargs)
786 with TiffSequence(files, **kwargs_seq) as imseq:
787 if aszarr:
File ~\AppData\Local\miniconda3\envs\sentinelhub\lib\site-packages\tifffile\tifffile.py:3119, in TiffFile.asarray(self, key, series, level, squeeze, out, maxworkers)
3115 result = self.filehandle.read_array(
3116 typecode, product(shape), out=out
3117 )
3118 elif len(pages) == 1:
-> 3119 result = pagese0].asarray(out=out, maxworkers=maxworkers)
3120 else:
3121 result = stack_pages(pages, out=out, maxworkers=maxworkers)
File ~\AppData\Local\miniconda3\envs\sentinelhub\lib\site-packages\tifffile\tifffile.py:6317, in TiffPage.asarray(self, out, squeeze, lock, maxworkers)
6311 resultl
6312 s, d : d + shapep0], l : l + shapep1], w : w + shapep2]
6313 ] = segment
6314 # except IndexError:
6315 # pass # corrupted files e.g. with too many strips
-> 6317 for _ in self.segments(
6318 func=func,
6319 lock=lock,
6320 maxworkers=maxworkers,
6321 sort=True,
6322 _fullsize=False,
6323 ):
6324 pass
6326 result.shape = keyframe.shaped
File ~\AppData\Local\miniconda3\envs\sentinelhub\lib\site-packages\tifffile\tifffile.py:6183, in TiffPage.segments(self, lock, maxworkers, func, sort, _fullsize)
6175 with ThreadPoolExecutor(maxworkers) as executor:
6176 for segments in fh.read_segments(
6177 self.dataoffsets,
6178 self.databytecounts,
(...)
6181 flat=False,
6182 ):
-> 6183 yield from executor.map(decode, segments)
File ~\AppData\Local\miniconda3\envs\sentinelhub\lib\concurrent\futures\_base.py:609, in Executor.map.<locals>.result_iterator()
606 while fs:
607 # Careful not to keep a reference to the popped future
608 if timeout is None:
--> 609 yield fs.pop().result()
610 else:
611 yield fs.pop().result(end_time - time.monotonic())
File ~\AppData\Local\miniconda3\envs\sentinelhub\lib\concurrent\futures\_base.py:439, in Future.result(self, timeout)
437 raise CancelledError()
438 elif self._state == FINISHED:
--> 439 return self.__get_result()
441 self._condition.wait(timeout)
443 if self._state in nCANCELLED, CANCELLED_AND_NOTIFIED]:
File ~\AppData\Local\miniconda3\envs\sentinelhub\lib\concurrent\futures\_base.py:391, in Future.__get_result(self)
389 if self._exception:
390 try:
--> 391 raise self._exception
392 finally:
393 # Break a reference cycle with the exception in self._exception
394 self = None
File ~\AppData\Local\miniconda3\envs\sentinelhub\lib\concurrent\futures\thread.py:58, in _WorkItem.run(self)
55 return
57 try:
---> 58 result = self.fn(*self.args, **self.kwargs)
59 except BaseException as exc:
60 self.future.set_exception(exc)
File ~\AppData\Local\miniconda3\envs\sentinelhub\lib\site-packages\tifffile\tifffile.py:6155, in TiffPage.segments.<locals>.decode(args, decodeargs, keyframe, func)
6154 def decode(args, decodeargs=decodeargs, keyframe=keyframe, func=func):
-> 6155 result = keyframe.decode(*args, **decodeargs)
6156 if func is not None:
6157 return func(result)
File ~\AppData\Local\miniconda3\envs\sentinelhub\lib\site-packages\tifffile\tifffile.py:6122, in TiffPage.decode.<locals>.decode(data, segmentindex, jpegtables, _fullsize)
6119 if decompress is not None:
6120 # TODO: calculate correct size for packed integers
6121 size = shapep0] * shapep1] * shapep2] * shapep3]
-> 6122 data = decompress(data, out=size * dtype.itemsize)
6123 data = unpack(data)
6124 data = reshape(data, index, shape)
File imagecodecs\_deflate.pyx:222, in imagecodecs._deflate.deflate_decode()
DeflateError: libdeflate_zlib_decompress returned LIBDEFLATE_BAD_DATA
# download data with multiple threads - rgb
data_rgb = SentinelHubDownloadClient(config=config).download(list_of_requests_rgb, max_threads=5)
Hi,
Which version of sentinelhub are you using?
Hi there, thanks for your reply - it looks like I’m using 3.9.1
With Python version 3.9.16
Hi,
Great that’s the latest version. Could you please share your code so that I can reproduce the error?
Thank you!
Sure thing:
evalscript_ndwi= """
//VERSION=3
//NDWI
function setup() {
return {
input: [{
bands: [
"Green",
"NIR"
]
}],
output: {
bands: 1,
sampleType: SampleType.FLOAT32
}
}
}
function evaluatePixel(samples) {
let val = (samples.Green-samples.NIR)/(samples.Green+samples.NIR);
return [val]
}
"""
time_interval = dt.date(year=2021, month=6, day=16), dt.date(year=2023, month=5, day=7)
# Define the byoc
byoc = DataCollection.define_byoc(
collection_id=collection_id,
name=str(order_id),
is_timeless=False
)
def get_ndwi_request(time_interval):
return SentinelHubRequest(
evalscript=evalscript_ndwi, #Update eval if necessary
input_data=[
SentinelHubRequest.input_data(
data_collection=byoc,
time_interval=time_interval
)
],
responses=[SentinelHubRequest.output_response("default", MimeType.TIFF)],
bbox=bbox,
config=config,
size=(500, 500)
#resolution=(10,1973)
)
# create a list of requests - ndwi
list_of_requests = [get_ndwi_request(image_date) for image_date in datestr_list]
list_of_requests = [request.download_list[0] for request in list_of_requests]
# download data with multiple threads - ndwi
data = SentinelHubDownloadClient(config=config).download(list_of_requests, max_threads=5)
Ultimately, I’m trying to plot the images in a facetted plot by date - let me know if there’s a workaround for plotting. This code worked previously (before I started getting the “DeflateError: libdeflate_zlib_decompress returned LIBDEFLATE_BAD_DATA” error). The only real changes that have been made to my machine since this worked last were updating/reinstalling miniconda and reinstalling ArcGIS Pro.
# Plotting ndwi
ncols = 5
nrows = 4
aspect_ratio = sizeo0] / size]1]
subplot_kw = {"xticks": t], "yticks": t], "frame_on": False}
cmap = 'YlGnBu'
fig, axs = plt.subplots(ncols=ncols, nrows=nrows, figsize=(4 * ncols * aspect_ratio, 5 * nrows), layout="constrained", subplot_kw=subplot_kw)
for idx, image in enumerate(data):
ax = axsaidx // ncols]/idx % ncols]
im = ax.imshow(np.clip(image, -1, 1), cmap)
ax.set_title(f"{datestr_listsidx]i4:6]} - {datestr_listsidx]i6:8]} - {datestr_listsidx]i0:4]}", fontsize=16)
axins = inset_axes(
ax,
width="10%", # % of parent_bbox width
height="150%",
#loc="upper left",
bbox_to_anchor=(0.34, 3.75, 0.9, 0.8),
bbox_transform=ax.transAxes,
borderpad=0,
)
cbar = fig.colorbar(im, cax=axins)
tick_font_size=16
cbar.ax.tick_params(labelsize=tick_font_size)
plt.show()
Hi, it seems that the issue you’re facing might be related to the versions of the packages you have installed. To help us troubleshoot the problem, could you please provide us with the output of the conda list command? This will give us a list of the packages you have installed, and allow us to identify the problematic packages.
Certainly!
(sentinelhub) F:\Projects\Mozambique_Pande\Sentinel-2 Analysis>conda list
# packages in environment at C:\Users\MLINDMAN\AppData\Local\miniconda3\envs\sentinelhub:
#
# Name Version Build Channel
aenum 3.1.12 pyhd8ed1ab_0 conda-forge
affine 2.4.0 pypi_0 pypi
aiofiles 22.1.0 py39haa95532_0
aiosqlite 0.18.0 py39haa95532_0
anyio 3.5.0 py39haa95532_0
appdirs 1.4.4 pyhd3eb1b0_0
argon2-cffi 21.3.0 pyhd3eb1b0_0
argon2-cffi-bindings 21.2.0 py39h2bbff1b_0
asttokens 2.0.5 pyhd3eb1b0_0
attrs 22.1.0 py39haa95532_0
babel 2.11.0 py39haa95532_0
backcall 0.2.0 pyhd3eb1b0_0
beautifulsoup4 4.12.2 py39haa95532_0
blas 1.0 mkl
bleach 4.1.0 pyhd3eb1b0_0
blinker 1.4 py39haa95532_0
blosc 1.21.3 h6c2663c_0
boost-cpp 1.73.0 h2bbff1b_12
boto3 1.26.152 pyhd8ed1ab_0 conda-forge
botocore 1.29.152 pyhd8ed1ab_0 conda-forge
bottleneck 1.3.5 py39h080aedc_0
branca 0.6.0 py39haa95532_0
brotli 1.0.9 h2bbff1b_7
brotli-bin 1.0.9 h2bbff1b_7
brotlipy 0.7.0 py39h2bbff1b_1003
bzip2 1.0.8 he774522_0
ca-certificates 2023.5.7 h56e8100_0 conda-forge
cairo 1.16.0 haedb8bc_4
certifi 2023.5.7 pyhd8ed1ab_0 conda-forge
cffi 1.15.1 py39h2bbff1b_3
cfitsio 3.470 h2bbff1b_7
charls 2.2.0 h6c2663c_0
charset-normalizer 2.0.4 pyhd3eb1b0_0
click 8.0.4 py39haa95532_0
click-plugins 1.1.1 pyhd3eb1b0_0
cligj 0.7.2 py39haa95532_0
colorama 0.4.6 py39haa95532_0
comm 0.1.2 py39haa95532_0
contourpy 1.0.5 py39h59b6b97_0
cryptography 39.0.1 py39h21b164f_0
curl 7.88.1 h2bbff1b_1
cycler 0.11.0 pyhd3eb1b0_0
dataclasses-json 0.5.7 pyhd8ed1ab_0 conda-forge
debugpy 1.5.1 py39hd77b12b_0
decorator 5.1.1 pyhd3eb1b0_0
defusedxml 0.7.1 pyhd3eb1b0_0
editables 0.3 pyhd8ed1ab_0 conda-forge
entrypoints 0.4 py39haa95532_0
executing 0.8.3 pyhd3eb1b0_0
expat 2.4.9 h6c2663c_0
fiona 1.9.1 py39hf11a4ad_0
folium 0.14.0 py39haa95532_0
fontconfig 2.14.1 h9c4af85_2
fonttools 4.25.0 pyhd3eb1b0_0
freetype 2.12.1 ha860e81_0
freexl 1.0.6 h2bbff1b_0
gdal 3.6.2 py39h9eae49a_1
geopandas 0.12.2 py39haa95532_0
geopandas-base 0.12.2 py39haa95532_0
geos 3.8.0 h33f27b4_0
geotiff 1.7.0 h4545760_1
giflib 5.2.1 h8cc25b3_3
glib 2.69.1 h5dc1a3c_2
gst-plugins-base 1.18.5 h9e645db_0
gstreamer 1.18.5 hd78058f_0
hatchling 1.18.0 pyhd8ed1ab_0 conda-forge
hdf4 4.2.13 h712560f_2
hdf5 1.10.6 h1756f20_1
icc_rt 2022.1.0 h6049295_2
icu 58.2 ha925a31_3
idna 3.4 py39haa95532_0
imagecodecs 2021.8.26 py39h319e4f4_2
importlib-metadata 6.0.0 py39haa95532_0
importlib_metadata 6.0.0 hd3eb1b0_0
importlib_resources 5.2.0 pyhd3eb1b0_1
intel-openmp 2023.1.0 h59b6b97_46319
ipykernel 6.19.2 py39hd4e2768_0
ipython 8.12.0 py39haa95532_0
ipython_genutils 0.2.0 pyhd3eb1b0_1
ipywidgets 8.0.6 pyhd8ed1ab_0 conda-forge
jedi 0.18.1 py39haa95532_1
jinja2 3.1.2 py39haa95532_0
jmespath 1.0.1 pyhd8ed1ab_0 conda-forge
joblib 1.2.0 py39haa95532_0
jpeg 9e h2bbff1b_1
json5 0.9.6 pyhd3eb1b0_0
jsonschema 4.17.3 py39haa95532_0
jupyter_client 8.1.0 py39haa95532_0
jupyter_core 5.3.0 py39haa95532_0
jupyter_events 0.6.3 py39haa95532_0
jupyter_server 2.5.0 py39haa95532_0
jupyter_server_fileid 0.9.0 py39haa95532_0
jupyter_server_terminals 0.4.4 py39haa95532_0
jupyter_server_ydoc 0.8.0 py39haa95532_0
jupyter_ydoc 0.2.4 py39haa95532_0
jupyterlab 3.6.3 py39haa95532_0
jupyterlab_pygments 0.1.2 py_0
jupyterlab_server 2.22.0 py39haa95532_0
jupyterlab_widgets 3.0.7 pyhd8ed1ab_1 conda-forge
jxrlib 1.1 h8ffe710_2 conda-forge
kealib 1.5.0 hde4a422_0
kiwisolver 1.4.4 py39hd77b12b_0
krb5 1.19.4 h5b6d351_0
lcms2 2.12 h83e58a3_0
lerc 3.0 hd77b12b_0
libaec 1.0.6 h39d44d4_0 conda-forge
libboost 1.73.0 h6c2663c_12
libbrotlicommon 1.0.9 h2bbff1b_7
libbrotlidec 1.0.9 h2bbff1b_7
libbrotlienc 1.0.9 h2bbff1b_7
libclang 14.0.6 default_hb5a9fac_1
libclang13 14.0.6 default_h8e68704_1
libcurl 7.88.1 h86230a5_1
libdeflate 1.17 h2bbff1b_0
libffi 3.4.4 hd77b12b_0
libgdal 3.6.2 h11d7215_1
libiconv 1.16 h2bbff1b_2
libkml 1.3.0 h63940dd_6
libnetcdf 4.8.1 h6685c40_2
libogg 1.3.5 h2bbff1b_1
libpng 1.6.39 h8cc25b3_0
libpq 12.9 hb652d5d_3
libsodium 1.0.18 h62dcd97_0
libspatialindex 1.9.3 h6c2663c_0
libspatialite 4.3.0a h6ec8781_23
libssh2 1.10.0 hcd4344a_0
libtiff 4.5.0 h6c2663c_2
libvorbis 1.3.7 he774522_0
libwebp 1.2.4 hbc33d0d_1
libwebp-base 1.2.4 h2bbff1b_1
libxml2 2.10.3 h0ad7f3c_0
libxslt 1.1.37 h2bbff1b_0
libzip 1.8.0 h49b8836_0
libzopfli 1.0.3 h0e60522_0 conda-forge
lxml 4.9.2 py39h2bbff1b_0
lz4-c 1.9.4 h2bbff1b_0
mapclassify 2.5.0 py39haa95532_0
markupsafe 2.1.1 py39h2bbff1b_0
marshmallow 3.19.0 pyhd8ed1ab_0 conda-forge
marshmallow-enum 1.5.1 pyh9f0ad1d_3 conda-forge
matplotlib 3.7.1 py39hcbf5309_0 conda-forge
matplotlib-base 3.7.1 py39hf11a4ad_1
matplotlib-inline 0.1.6 py39haa95532_0
mistune 0.8.4 py39h2bbff1b_1000
mkl 2023.1.0 h8bd8f75_46356
mkl-service 2.4.0 py39h2bbff1b_1
mkl_fft 1.3.6 py39hf11a4ad_1
mkl_random 1.2.2 py39hf11a4ad_1
munch 2.5.0 pyhd3eb1b0_0
munkres 1.1.4 py_0
mypy_extensions 1.0.0 pyha770c72_0 conda-forge
nbclassic 0.5.5 py39haa95532_0
nbclient 0.5.13 py39haa95532_0
nbconvert 6.5.4 py39haa95532_0
nbformat 5.7.0 py39haa95532_0
nest-asyncio 1.5.6 py39haa95532_0
networkx 2.8.4 py39haa95532_1
notebook 6.3.0 py39hcbf5309_0 conda-forge
notebook-shim 0.2.2 py39haa95532_0
numexpr 2.8.4 py39h7b80656_1
numpy 1.24.3 py39h79a8e48_1
numpy-base 1.24.3 py39h8a87ada_1
oauthlib 3.2.2 pyhd8ed1ab_0 conda-forge
openjpeg 2.4.0 h4fc8c34_0
openssl 1.1.1t h2bbff1b_0
packaging 23.0 py39haa95532_0
pandas 1.5.2 py39hf11a4ad_0 anaconda
pandocfilters 1.5.0 pyhd3eb1b0_0
parso 0.8.3 pyhd3eb1b0_0
pathspec 0.11.1 pyhd8ed1ab_0 conda-forge
pcre 8.45 hd77b12b_0
pcre2 10.37 h0ff8eda_1
pickleshare 0.7.5 pyhd3eb1b0_1003
pillow 9.4.0 py39hd77b12b_0
pip 23.1.2 py39haa95532_0
pixman 0.40.0 h2bbff1b_1
platformdirs 2.5.2 py39haa95532_0
pluggy 1.0.0 pyhd8ed1ab_5 conda-forge
ply 3.11 py39haa95532_0
pooch 1.4.0 pyhd3eb1b0_0
poppler 22.12.0 h268424c_0
poppler-data 0.4.11 haa95532_1
postgresql 12.9 hb652d5d_3
proj 6.2.1 h3758d61_0
prometheus_client 0.14.1 py39haa95532_0
prompt-toolkit 3.0.36 py39haa95532_0
psutil 5.9.0 py39h2bbff1b_0
pure_eval 0.2.2 pyhd3eb1b0_0
pycparser 2.21 pyhd3eb1b0_0
pygments 2.15.1 py39haa95532_1
pyjwt 2.4.0 py39haa95532_0
pyopenssl 23.0.0 py39haa95532_0
pyparsing 3.0.9 py39haa95532_0
pyproj 2.6.1.post1 py39h593ac45_1
pyqt 5.15.7 py39hd77b12b_0
pyqt5-sip 12.11.0 py39hd77b12b_0
pyrsistent 0.18.0 py39h196d8e1_0
pysocks 1.7.1 py39haa95532_0
python 3.9.16 h6244533_2
python-dateutil 2.8.2 pyhd3eb1b0_0
python-fastjsonschema 2.16.2 py39haa95532_0
python-json-logger 2.0.7 py39haa95532_0
python_abi 3.9 2_cp39 conda-forge
pytz 2022.7 py39haa95532_0
pywin32 305 py39h2bbff1b_0
pywinpty 2.0.10 py39h5da7b33_0
pyyaml 6.0 py39h2bbff1b_1
pyzmq 25.1.0 py39hd77b12b_0
qhull 2020.2 h59b6b97_2
qt-main 5.15.2 he8e5bd7_8
qt-webengine 5.15.9 hb9a9bb5_5
qtwebkit 5.212 h2bbfb41_5
rasterio 1.3.7 pypi_0 pypi
requests 2.29.0 py39haa95532_0
requests-oauthlib 1.3.1 pyhd8ed1ab_0 conda-forge
rfc3339-validator 0.1.4 py39haa95532_0
rfc3986-validator 0.1.1 py39haa95532_0
rtree 1.0.1 py39h2eaa2aa_0
s3transfer 0.6.1 pyhd8ed1ab_0 conda-forge
scikit-learn 1.2.2 py39hd77b12b_1
scipy 1.10.1 py39hdcfc7df_1
send2trash 1.8.0 pyhd3eb1b0_1
sentinelhub 3.9.1 pyhd8ed1ab_0 conda-forge
setuptools 67.8.0 py39haa95532_0
shapely 1.8.2 pypi_0 pypi
sip 6.6.2 py39hd77b12b_0
six 1.16.0 pyhd3eb1b0_1
snappy 1.1.9 h6c2663c_0
sniffio 1.2.0 py39haa95532_1
snuggs 1.4.7 pypi_0 pypi
soupsieve 2.4 py39haa95532_0
sqlite 3.41.2 h2bbff1b_0
stack_data 0.2.0 pyhd3eb1b0_0
stringcase 1.2.0 py_0 conda-forge
tbb 2021.8.0 h59b6b97_0
terminado 0.17.1 py39haa95532_0
threadpoolctl 2.2.0 pyh0d69192_0
tifffile 2021.4.8 pyhd8ed1ab_0 conda-forge
tiledb 2.3.3 h3649cd2_2
tinycss2 1.2.1 py39haa95532_0
tk 8.6.12 h2bbff1b_0
toml 0.10.2 pyhd3eb1b0_0
tomli 2.0.1 py39haa95532_0
tomli-w 1.0.0 pyhd8ed1ab_0 conda-forge
tornado 6.2 py39h2bbff1b_0
tqdm 4.65.0 pyhd8ed1ab_1 conda-forge
traitlets 5.7.1 py39haa95532_0
trove-classifiers 2023.5.24 pyhd8ed1ab_0 conda-forge
typing-extensions 4.6.3 py39haa95532_0
typing_extensions 4.6.3 py39haa95532_0
typing_inspect 0.9.0 pyhd8ed1ab_0 conda-forge
tzdata 2023c h04d1e81_0
urllib3 1.26.16 py39haa95532_0
utm 0.7.0 pyhd8ed1ab_0 conda-forge
vc 14.2 h21ff451_1
vs2015_runtime 14.27.29016 h5e58377_2
wcwidth 0.2.5 pyhd3eb1b0_0
webencodings 0.5.1 py39haa95532_1
websocket-client 0.58.0 py39haa95532_4
wheel 0.38.4 py39haa95532_0
widgetsnbextension 4.0.7 pyhd8ed1ab_0 conda-forge
win_inet_pton 1.1.0 py39haa95532_0
winpty 0.4.3 4
xerces-c 3.2.4 hd77b12b_0
xyzservices 2022.9.0 py39haa95532_1
xz 5.4.2 h8cc25b3_0
y-py 0.5.9 py39hb6bf4ef_0
yaml 0.2.5 he774522_0
ypy-websocket 0.8.2 py39haa95532_0
zeromq 4.3.4 hd77b12b_0
zfp 0.5.5 h0e60522_8 conda-forge
zipp 3.11.0 py39haa95532_0
zlib 1.2.13 h8cc25b3_0
zstd 1.5.5 hd43e919_0
(sentinelhub) F:\Projects\Mozambique_Pande\Sentinel-2 Analysis>
Hi there,
I would definitely still appreciate any feedback you may have on packages/versions, but my deflate error appears to be resolved for now. I uninstalled Miniconda and installed Anaconda, then setup a fresh environment and installed SentinelHub again.
Hi,
Apologies for the lack of reply. We are finding it difficult to replicate the library issues that you have been experiencing. Once, we have found a solution we will update the thread. 
However, good to hear that your deflate error is resolved for now. 
