prep.py Error #30

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1. isunli commented on Apr 5, 2018

   

   isunli

   on Apr 5, 2018

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   Same, any one can fix this problem?
2. mdtdev commented on Dec 4, 2018

   

   mdtdev

   on Dec 4, 2018

   Last edited by mdtdev

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   Clearly the data source is no longer supported. Does anyone know an alternate source to use for the data? Or equivalent data to download?
3. mrocklin commented on Dec 4, 2018

   

   mrocklin

   on Dec 4, 2018

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   I don't personally know of a good place to download this data, but I wouldn't be surprised if one exists.

   The dask repository now includes a dask.datasets.timeseries function that generates entirely fake data that might fit in, though would be less interesting. If someone wants to do this I suspect it would be welcome.
4. cdeil commented on Jan 23, 2019

   

   cdeil

   on Jan 23, 2019

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   I also wanted to try this tutorial, but couldn't get the data:

   (parallel) hfm-1804a:parallel-tutorial deil$ python prep.py
   Traceback (most recent call last):
     File "prep.py", line 21, in <module>
       dask.set_options(get=dask.multiprocessing.get)
     File "/Users/deil/software/anaconda3/envs/parallel/lib/python3.6/site-packages/dask/context.py", line 18, in set_options
       raise TypeError("The dask.set_options function has been deprecated.\n"
   TypeError: The dask.set_options function has been deprecated.
   Please use dask.config.set instead
   
     Before: with dask.set_options(foo='bar'):
                 ...
     After:  with dask.config.set(foo='bar'):
                 ...
   

   I don't personally know of a good place to download this data, but I wouldn't be surprised if one exists.

   How big is the data that was downloaded by prep.py. If it's less than 1 GB maybe you could just put a copy in this Github repo?

   Would be great to have this tutorial working....
5. mrocklin commented on Jan 23, 2019

   

   mrocklin

   on Jan 23, 2019

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   I agree that putting the data into the repository is possible. Unfortunately I no longer know how to obtain the data. My recommendation that someone rework the examples to use the dask.datasets.timeseries function is, I think, still the best approach I can think of personally. Alternate solutions would be welcome if people want to implement them.
6. cdeil commented on Jan 23, 2019

   

   cdeil

   on Jan 23, 2019

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   I agree that putting the data into the repository is possible. Unfortunately I no longer know how to obtain the data.

   @minrk - maybe you still have a copy of the files around?

   My recommendation that someone rework the examples to use the dask.datasets.timeseries function is, I think, still the best approach I can think of personally.

   I could try tomorrow. But to me, bundling example data in the tutorial repo seems like the better solution if it's small, to increase chances of it working in the future.
7. mrocklin commented on Jan 23, 2019

   

   mrocklin

   on Jan 23, 2019

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   dask.datasets.timeseries produces random data using the numpy.random module. It's definitely as robust as packaging data, and has the benefit of working over conference wifi.

   I think it's ok to have a few megabytes of data here, but we need to expect this tutorial to be run over very poor internet connections. Anything over a few tens of megabytes is unpleasant.
8. jjbankert commented on Mar 15, 2019

   

   jjbankert

   on Mar 15, 2019

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   In order to even get to the google error I've set dask=0.20.2 and pandas =0.22 in the environment.yml file. Dask ran into the same issue as @cdeil reported, and pandas reported the following exception:

   (parallel) [parallel-tutorial]$ python prep.py
   Traceback (most recent call last):
     File "prep.py", line 44, in <module>
       write_stock(symbol)
     File "prep.py", line 37, in write_stock
       data_source='google')
     File "/opt/anaconda3/envs/parallel/lib/python3.6/site-packages/dask/dataframe/io/demo.py", line 202, in daily_stock
       from pandas_datareader import data
     File "/opt/anaconda3/envs/parallel/lib/python3.6/site-packages/pandas_datareader/__init__.py", line 2, in <module>
       from .data import (DataReader, Options, get_components_yahoo,
     File "/opt/anaconda3/envs/parallel/lib/python3.6/site-packages/pandas_datareader/data.py", line 14, in <module>
       from pandas_datareader.fred import FredReader
     File "/opt/anaconda3/envs/parallel/lib/python3.6/site-packages/pandas_datareader/fred.py", line 1, in <module>
       from pandas.core.common import is_list_like
   ImportError: cannot import name 'is_list_like'