Comments (9)
Eak, sorry about this, I really need to write some more tests so we can catch simple failures like this before pushing to master. Sorry, my bad! I'll look into this next week
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@JackKelly Will do! Thanks.
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It's possible that we can just remove engine='h5netcdf'
. Or see here for an alternative approach: pydata/xarray#1075 (comment)
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Getting a lot of these errors atm:
2020-05-29 17:49:47,688 - metoffice_ec2 - ERROR - No module named 'h5netcdf'
Traceback (most recent call last):
File "scripts/ec2.py", line 114, in loop
load_subset_and_save_data(mo_message, s3)
File "scripts/ec2.py", line 64, in load_subset_and_save_data
dataset = mo_message.load_netcdf()
File "/usr/src/app/metoffice_ec2/message.py", line 73, in load_netcdf
return xr.open_dataset(netcdf_bytes_io)
File "/opt/conda/envs/metoffice_ec2/lib/python3.8/site-packages/xarray/backends/api.py", line 533, in open_dataset
store = backends.H5NetCDFStore.open(
File "/opt/conda/envs/metoffice_ec2/lib/python3.8/site-packages/xarray/backends/h5netcdf_.py", line 123, in open
import h5netcdf
ModuleNotFoundError: No module named 'h5netcdf'
Reopening this issue, didn't seem to resolve it.
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Reverted this via #30 to fix deployment.
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No worries! Yes, we should probably add some tests haha
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I've recreated this issue locally.
I've tried changing the engine to all the options (other than h5netcdf
) and it always responds: ValueError: can only read bytes or file-like objects with engine='scipy' or 'h5netcdf'
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I've recreated this issue locally.
I've tried changing the engine to all the options (other than h5netcdf
) and it always responds: ValueError: can only read bytes or file-like objects with engine='scipy' or 'h5netcdf'
But I think I've got it working without h5netcdf
using the netCDF4
trick described here: pydata/xarray#1075 (comment)
@FWirtz no rush, but please could you try this new code on AWS?
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That worked!
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Related Issues (20)
- Use zstd instead of LZMA HOT 1
- Script uses increasingly large amounts of memory on EC2 HOT 5
- rename MetOfficeMessage.load_netcdf to open_netcdf
- More unit tests :) HOT 1
- Run creating output images for FE on AWS
- Investigate why script doesn't output files HOT 2
- Add Sentry Error Logging
- Predict PV yield using baseline NWP model
- Deal with increasing S3 cost HOT 3
- Look into running workload on Spot instead of Fargate HOT 2
- Autoscale Compute Fleet based on SQS HOT 1
- Automatically build docker images HOT 1
- Find out which irradiance field to use HOT 2
- load_subset_and_save_data() missing 1 required positional argument
- Use irradiance data for predictions HOT 1
- float() argument must be a string or a number, not 'list' HOT 5
- dimensions or multi-index levels ['height'] do not exist HOT 2
- Run inference on AWS
- Various NaN values in predictions HOT 1
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