Bug#880245: statsmodels: FTBFS: RuntimeError: Kernel died before replying to kernel_info

Lucas Nussbaum lucas at debian.org
Mon Oct 30 19:32:11 UTC 2017


Source: statsmodels
Version: 0.8.0-6
Severity: serious
Tags: buster sid
User: debian-qa at lists.debian.org
Usertags: qa-ftbfs-20171030 qa-ftbfs
Justification: FTBFS on amd64

Hi,

During a rebuild of all packages in sid, your package failed to build on
amd64.

Relevant part (hopefully):
> make[2]: Entering directory '/<<PKGBUILDDIR>>/docs'
> Make static directory for images
> mkdir -p build/html/_static
> # generate the examples rst files
> Generating reST from examples folder
> #../tools/examples_rst.py
> Generating datasets from installed statsmodels.datasets
> python3 ../tools/dataset_rst.py
> /<<PKGBUILDDIR>>/.pybuild/pythonX.Y_3.6/build/statsmodels/compat/pandas.py:56: FutureWarning: The pandas.core.datetools module is deprecated and will be removed in a future version. Please use the pandas.tseries module instead.
>   from pandas.core import datetools
> Generating notebooks from examples/notebooks folder
> python3 ../tools/nbgenerate.py --execute=True --allow_errors=True
> Traceback (most recent call last):
>   File "/usr/lib/python3.6/runpy.py", line 193, in _run_module_as_main
>     "__main__", mod_spec)
>   File "/usr/lib/python3.6/runpy.py", line 85, in _run_code
>     exec(code, run_globals)
>   File "/usr/lib/python3/dist-packages/ipykernel_launcher.py", line 16, in <module>
>     app.launch_new_instance()
>   File "/usr/lib/python3/dist-packages/traitlets/config/application.py", line 657, in launch_instance
>     app.initialize(argv)
>   File "<decorator-gen-121>", line 2, in initialize
>   File "/usr/lib/python3/dist-packages/traitlets/config/application.py", line 87, in catch_config_error
>     return method(app, *args, **kwargs)
>   File "/usr/lib/python3/dist-packages/ipykernel/kernelapp.py", line 448, in initialize
>     self.init_sockets()
>   File "/usr/lib/python3/dist-packages/ipykernel/kernelapp.py", line 251, in init_sockets
>     self.init_iopub(context)
>   File "/usr/lib/python3/dist-packages/ipykernel/kernelapp.py", line 256, in init_iopub
>     self.iopub_port = self._bind_socket(self.iopub_socket, self.iopub_port)
>   File "/usr/lib/python3/dist-packages/ipykernel/kernelapp.py", line 180, in _bind_socket
>     s.bind("tcp://%s:%i" % (self.ip, port))
>   File "zmq/backend/cython/socket.pyx", line 495, in zmq.backend.cython.socket.Socket.bind (zmq/backend/cython/socket.c:5662)
>   File "zmq/backend/cython/checkrc.pxd", line 25, in zmq.backend.cython.checkrc._check_rc (zmq/backend/cython/socket.c:8400)
> zmq.error.ZMQError: Address already in use
> RUNNING THE L-BFGS-B CODE
> 
>            * * *
> 
> Machine precision = 2.220D-16
>  N =            3     M =           12
>  This problem is unconstrained.
> 
> At X0         0 variables are exactly at the bounds
> 
> At iterate    0    f=  4.23082D+00    |proj g|=  8.41904D-04
> 
> At iterate    5    f=  4.23082D+00    |proj g|=  2.53753D-04
> 
> At iterate   10    f=  4.23080D+00    |proj g|=  3.50830D-04
> 
> At iterate   15    f=  4.23080D+00    |proj g|=  0.00000D+00
> 
>            * * *
> 
> Tit   = total number of iterations
> Tnf   = total number of function evaluations
> Tnint = total number of segments explored during Cauchy searches
> Skip  = number of BFGS updates skipped
> Nact  = number of active bounds at final generalized Cauchy point
> Projg = norm of the final projected gradient
> F     = final function value
> 
>            * * *
> 
>    N    Tit     Tnf  Tnint  Skip  Nact     Projg        F
>     3     15     18      1     0     0   0.000D+00   4.231D+00
>   F =   4.2308031360255534     
> 
> CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL            
> 
>  Cauchy                time 0.000E+00 seconds.
>  Subspace minimization time 0.000E+00 seconds.
>  Line search           time 0.000E+00 seconds.
> 
>  Total User time 0.000E+00 seconds.
> 
> RUNNING THE L-BFGS-B CODE
> 
>            * * *
> 
> Machine precision = 2.220D-16
>  N =            4     M =           10
>  This problem is unconstrained.
> 
> At X0         0 variables are exactly at the bounds
> 
> At iterate    0    f=  4.23082D+00    |proj g|=  4.24640D-03
> 
> At iterate    5    f=  4.23081D+00    |proj g|=  4.05725D-04
> RUNNING THE L-BFGS-B CODE
> 
>            * * *
> 
> Machine precision = 2.220D-16
>  N =            4     M =           12
>  This problem is unconstrained.
> 
> At X0         0 variables are exactly at the bounds
> 
> At iterate    0    f=  4.22237D+00    |proj g|=  1.77733D-03
> 
> At iterate   10    f=  4.23081D+00    |proj g|=  1.30108D-04
> 
> At iterate    5    f=  4.22236D+00    |proj g|=  1.28697D-04
> 
> At iterate   15    f=  4.23080D+00    |proj g|=  1.31690D-03
> 
> At iterate   10    f=  4.22234D+00    |proj g|=  9.63318D-04
> 
>            * * *
> 
> Tit   = total number of iterations
> Tnf   = total number of function evaluations
> Tnint = total number of segments explored during Cauchy searches
> Skip  = number of BFGS updates skipped
> Nact  = number of active bounds at final generalized Cauchy point
> Projg = norm of the final projected gradient
> F     = final function value
> 
>            * * *
> 
>    N    Tit     Tnf  Tnint  Skip  Nact     Projg        F
>     4     19     23      1     0     0   3.347D-06   4.231D+00
>   F =   4.2308031361514580     
> 
> CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL            
> 
>  Cauchy                time 0.000E+00 seconds.
>  Subspace minimization time 0.000E+00 seconds.
>  Line search           time 0.000E+00 seconds.
> 
>  Total User time 0.000E+00 seconds.
> 
> 
> At iterate   15    f=  4.22234D+00    |proj g|=  1.24345D-06
> 
>            * * *
> 
> Tit   = total number of iterations
> Tnf   = total number of function evaluations
> Tnint = total number of segments explored during Cauchy searches
> Skip  = number of BFGS updates skipped
> Nact  = number of active bounds at final generalized Cauchy point
> Projg = norm of the final projected gradient
> F     = final function value
> 
>            * * *
> 
>    N    Tit     Tnf  Tnint  Skip  Nact     Projg        F
>     4     18     44      1     0     0   2.665D-07   4.222D+00
>   F =   4.2223359687691975     
> 
> CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH             
> 
>  Warning:  more than 10 function and gradient
>    evaluations in the last line search.  Termination
>    may possibly be caused by a bad search direction.
> 
>  Cauchy                time 0.000E+00 seconds.
>  Subspace minimization time 0.000E+00 seconds.
>  Line search           time 0.000E+00 seconds.
> 
>  Total User time 0.000E+00 seconds.
> 
> RUNNING THE L-BFGS-B CODE
> 
>            * * *
> 
> Machine precision = 2.220D-16
>  N =            5     M =           10
>  This problem is unconstrained.
> 
> At X0         0 variables are exactly at the bounds
> 
> At iterate    0    f=  4.22237D+00    |proj g|=  5.01920D-03
> 
> At iterate    5    f=  4.22236D+00    |proj g|=  2.92746D-04
> 
> At iterate   10    f=  4.22235D+00    |proj g|=  2.35957D-04
> 
> At iterate   15    f=  4.22234D+00    |proj g|=  1.81117D-03
> 
> At iterate   20    f=  4.22234D+00    |proj g|=  4.49940D-05
> 
>            * * *
> 
> Tit   = total number of iterations
> Tnf   = total number of function evaluations
> Tnint = total number of segments explored during Cauchy searches
> Skip  = number of BFGS updates skipped
> Nact  = number of active bounds at final generalized Cauchy point
> Projg = norm of the final projected gradient
> F     = final function value
> 
>            * * *
> 
>    N    Tit     Tnf  Tnint  Skip  Nact     Projg        F
>     5     20     23      1     0     0   4.499D-05   4.222D+00
>   F =   4.2223359703285395     
> 
> CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH             
> 
>  Cauchy                time 0.000E+00 seconds.
>  Subspace minimization time 0.000E+00 seconds.
>  Line search           time 0.000E+00 seconds.
> 
>  Total User time 0.000E+00 seconds.
> 
> RUNNING THE L-BFGS-B CODE
> 
>            * * *
> 
> Machine precision = 2.220D-16
>  N =            3     M =           12
>  This problem is unconstrained.
> 
> At X0         0 variables are exactly at the bounds
> 
> At iterate    0    f=  2.46776D+00    |proj g|=  8.52896D-03
> 
> At iterate    5    f=  2.46684D+00    |proj g|=  7.00551D-04
> 
> At iterate   10    f=  2.46684D+00    |proj g|=  0.00000D+00
> 
>            * * *
> 
> Tit   = total number of iterations
> Tnf   = total number of function evaluations
> Tnint = total number of segments explored during Cauchy searches
> Skip  = number of BFGS updates skipped
> Nact  = number of active bounds at final generalized Cauchy point
> Projg = norm of the final projected gradient
> F     = final function value
> 
>            * * *
> 
>    N    Tit     Tnf  Tnint  Skip  Nact     Projg        F
>     3     10     12      1     0     0   0.000D+00   2.467D+00
>   F =   2.4668361847171627     
> 
> CONVERGENCE: NORM_OF_PROJECTED_GRADIENT_<=_PGTOL            
> 
>  Cauchy                time 0.000E+00 seconds.
>  Subspace minimization time 0.000E+00 seconds.
>  Line search           time 0.000E+00 seconds.
> 
>  Total User time 0.000E+00 seconds.
> 
> RUNNING THE L-BFGS-B CODE
> 
>            * * *
> 
> Machine precision = 2.220D-16
>  N =            6     M =           12
>  This problem is unconstrained.
> 
> At X0         0 variables are exactly at the bounds
> 
> At iterate    0    f=  2.31550D+00    |proj g|=  1.76959D-02
> 
> At iterate    5    f=  2.31296D+00    |proj g|=  5.40932D-03
> 
> At iterate   10    f=  2.31191D+00    |proj g|=  4.70379D-04
> 
> At iterate   15    f=  2.31191D+00    |proj g|=  1.77636D-07
> 
>            * * *
> 
> Tit   = total number of iterations
> Tnf   = total number of function evaluations
> Tnint = total number of segments explored during Cauchy searches
> Skip  = number of BFGS updates skipped
> Nact  = number of active bounds at final generalized Cauchy point
> Projg = norm of the final projected gradient
> F     = final function value
> 
>            * * *
> 
>    N    Tit     Tnf  Tnint  Skip  Nact     Projg        F
>     6     16     18      1     0     0   4.441D-08   2.312D+00
>   F =   2.3119057684973705     
> 
> CONVERGENCE: REL_REDUCTION_OF_F_<=_FACTR*EPSMCH             
> 
>  Cauchy                time 0.000E+00 seconds.
>  Subspace minimization time 0.000E+00 seconds.
>  Line search           time 0.000E+00 seconds.
> 
>  Total User time 0.000E+00 seconds.
> 
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/kernel_density.ipynb to /<<PKGBUILDDIR>>/examples/executed/kernel_density.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/kernel_density.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/kernel_density.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/statespace_dfm_coincident.ipynb to /<<PKGBUILDDIR>>/examples/executed/statespace_dfm_coincident.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/statespace_dfm_coincident.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/statespace_dfm_coincident.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/statespace_sarimax_internet.ipynb to /<<PKGBUILDDIR>>/examples/executed/statespace_sarimax_internet.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/statespace_sarimax_internet.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/statespace_sarimax_internet.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/statespace_sarimax_stata.ipynb to /<<PKGBUILDDIR>>/examples/executed/statespace_sarimax_stata.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/statespace_sarimax_stata.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/statespace_sarimax_stata.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/regression_diagnostics.ipynb to /<<PKGBUILDDIR>>/examples/executed/regression_diagnostics.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/regression_diagnostics.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/regression_diagnostics.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/quantile_regression.ipynb to /<<PKGBUILDDIR>>/examples/executed/quantile_regression.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/quantile_regression.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/quantile_regression.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/tsa_filters.ipynb to /<<PKGBUILDDIR>>/examples/executed/tsa_filters.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/tsa_filters.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/tsa_filters.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/regression_plots.ipynb to /<<PKGBUILDDIR>>/examples/executed/regression_plots.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/regression_plots.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/regression_plots.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/statespace_cycles.ipynb to /<<PKGBUILDDIR>>/examples/executed/statespace_cycles.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/statespace_cycles.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/statespace_cycles.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/categorical_interaction_plot.ipynb to /<<PKGBUILDDIR>>/examples/executed/categorical_interaction_plot.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/categorical_interaction_plot.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/categorical_interaction_plot.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/statespace_structural_harvey_jaeger.ipynb to /<<PKGBUILDDIR>>/examples/executed/statespace_structural_harvey_jaeger.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/statespace_structural_harvey_jaeger.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/statespace_structural_harvey_jaeger.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/tsa_arma_1.ipynb to /<<PKGBUILDDIR>>/examples/executed/tsa_arma_1.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/tsa_arma_1.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/tsa_arma_1.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/chi2_fitting.ipynb to /<<PKGBUILDDIR>>/examples/executed/chi2_fitting.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/chi2_fitting.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/chi2_fitting.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/glm_formula.ipynb to /<<PKGBUILDDIR>>/examples/executed/glm_formula.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/glm_formula.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/glm_formula.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/interactions_anova.ipynb to /<<PKGBUILDDIR>>/examples/executed/interactions_anova.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/interactions_anova.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/interactions_anova.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/ols.ipynb to /<<PKGBUILDDIR>>/examples/executed/ols.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/ols.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/ols.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/generic_mle.ipynb to /<<PKGBUILDDIR>>/examples/executed/generic_mle.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/generic_mle.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/generic_mle.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/pca_fertility_factors.ipynb to /<<PKGBUILDDIR>>/examples/executed/pca_fertility_factors.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/pca_fertility_factors.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/pca_fertility_factors.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/statespace_arma_0.ipynb to /<<PKGBUILDDIR>>/examples/executed/statespace_arma_0.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/statespace_arma_0.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/statespace_arma_0.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/formulas.ipynb to /<<PKGBUILDDIR>>/examples/executed/formulas.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/formulas.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/formulas.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/discrete_choice_example.ipynb to /<<PKGBUILDDIR>>/examples/executed/discrete_choice_example.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/discrete_choice_example.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/discrete_choice_example.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/statespace_varmax.ipynb to /<<PKGBUILDDIR>>/examples/executed/statespace_varmax.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/statespace_varmax.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/statespace_varmax.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/statespace_local_linear_trend.ipynb to /<<PKGBUILDDIR>>/examples/executed/statespace_local_linear_trend.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/statespace_local_linear_trend.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/statespace_local_linear_trend.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/wls.ipynb to /<<PKGBUILDDIR>>/examples/executed/wls.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/wls.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/wls.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/glm.ipynb to /<<PKGBUILDDIR>>/examples/executed/glm.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/glm.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/glm.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/contrasts.ipynb to /<<PKGBUILDDIR>>/examples/executed/contrasts.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/contrasts.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/contrasts.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/discrete_choice_overview.ipynb to /<<PKGBUILDDIR>>/examples/executed/discrete_choice_overview.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/discrete_choice_overview.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/discrete_choice_overview.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/recursive_ls.ipynb to /<<PKGBUILDDIR>>/examples/executed/recursive_ls.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/recursive_ls.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/recursive_ls.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/markov_autoregression.ipynb to /<<PKGBUILDDIR>>/examples/executed/markov_autoregression.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/markov_autoregression.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/markov_autoregression.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/tsa_arma_0.ipynb to /<<PKGBUILDDIR>>/examples/executed/tsa_arma_0.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/tsa_arma_0.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/tsa_arma_0.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/robust_models_1.ipynb to /<<PKGBUILDDIR>>/examples/executed/robust_models_1.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/robust_models_1.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/robust_models_1.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/tsa_dates.ipynb to /<<PKGBUILDDIR>>/examples/executed/tsa_dates.ipynb
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/gls.ipynb to /<<PKGBUILDDIR>>/examples/executed/gls.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/gls.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/gls.html
> Executeing /<<PKGBUILDDIR>>/examples/notebooks/mixed_lm_example.ipynb to /<<PKGBUILDDIR>>/examples/executed/mixed_lm_example.ipynb
> Converting /<<PKGBUILDDIR>>/examples/executed/mixed_lm_example.ipynb to /<<PKGBUILDDIR>>/docs/source/examples/notebooks/generated/mixed_lm_example.html
> concurrent.futures.process._RemoteTraceback: 
> """
> Traceback (most recent call last):
>   File "/usr/lib/python3.6/concurrent/futures/process.py", line 175, in _process_worker
>     r = call_item.fn(*call_item.args, **call_item.kwargs)
>   File "/usr/lib/python3.6/concurrent/futures/process.py", line 153, in _process_chunk
>     return [fn(*args) for args in chunk]
>   File "/usr/lib/python3.6/concurrent/futures/process.py", line 153, in <listcomp>
>     return [fn(*args) for args in chunk]
>   File "../tools/nbgenerate.py", line 97, in do_one
>     kernel_name=kernel_name)
>   File "../tools/nbgenerate.py", line 55, in execute_nb
>     ep.preprocess(nb, {'metadta': {'path': 'notebooks/'}})
>   File "/usr/lib/python3/dist-packages/nbconvert/preprocessors/execute.py", line 257, in preprocess
>     cwd=path)
>   File "/usr/lib/python3/dist-packages/nbconvert/preprocessors/execute.py", line 241, in start_new_kernel
>     kc.wait_for_ready(timeout=startup_timeout)
>   File "/usr/lib/python3/dist-packages/jupyter_client/blocking/client.py", line 120, in wait_for_ready
>     raise RuntimeError('Kernel died before replying to kernel_info')
> RuntimeError: Kernel died before replying to kernel_info
> """
> 
> The above exception was the direct cause of the following exception:
> 
> Traceback (most recent call last):
>   File "../tools/nbgenerate.py", line 165, in <module>
>     main()
>   File "../tools/nbgenerate.py", line 162, in main
>     kernel_name=args.kernel_name)
>   File "../tools/nbgenerate.py", line 123, in do
>     for dst in pool.map(func, nbs):
>   File "/usr/lib/python3.6/concurrent/futures/process.py", line 366, in _chain_from_iterable_of_lists
>     for element in iterable:
>   File "/usr/lib/python3.6/concurrent/futures/_base.py", line 586, in result_iterator
>     yield fs.pop().result()
>   File "/usr/lib/python3.6/concurrent/futures/_base.py", line 432, in result
>     return self.__get_result()
>   File "/usr/lib/python3.6/concurrent/futures/_base.py", line 384, in __get_result
>     raise self._exception
> RuntimeError: Kernel died before replying to kernel_info
> Makefile:62: recipe for target 'html' failed
> make[2]: *** [html] Error 1

The full build log is available from:
   http://aws-logs.debian.net/2017/10/30/statsmodels_0.8.0-6_unstable.log

A list of current common problems and possible solutions is available at
http://wiki.debian.org/qa.debian.org/FTBFS . You're welcome to contribute!

About the archive rebuild: The rebuild was done on EC2 VM instances from
Amazon Web Services, using a clean, minimal and up-to-date chroot. Every
failed build was retried once to eliminate random failures.



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