jupyter-notebook

问题 I am wondering if there's an easy way to build an iPyWidget with a datetime slider. Right now it is easy to slide over integer or floating point ranges (e.g. numbers 1-10, decimals 0.01, 0.02, ...). I imagine you could convert dates to floats or integers, build some sort of slider using these, and then convert back to dates for the display labels on the slider. However, this seems clunky. Does anyone have a smoother solution? 回答1: I had the same issue recently. I had to write my own class to

问题 I'm constantly running out of RAM with some Jupyter Notebooks and I seem to be unable to release memory that is no longer needed. Here is an example: import gc thing = Thing() result = thing.do_something(...) thing = None gc.collect() As you can presume, thing uses a lot of memory to do something and then I don't need it anymore. I should be able to release the memory it uses. Even though it doesn't write to any variables that I can access from my notebook, garbage collector isn't freeing up

问题 So I went through some questions being posted about the usage of %matplotlib inline function in Jupyter Notebook, I do understand that "%matplotlib inline sets the backend of matplotlib to the 'inline' backend" & "When using the 'inline' backend, your matplotlib graphs will be included in your notebook, next to the code". But, I don't see any difference in my plot results with or without the use of "%matplotlib inline". Can someone explain this to me if I am misunderstanding something? Here's

问题 So I went through some questions being posted about the usage of %matplotlib inline function in Jupyter Notebook, I do understand that "%matplotlib inline sets the backend of matplotlib to the 'inline' backend" & "When using the 'inline' backend, your matplotlib graphs will be included in your notebook, next to the code". But, I don't see any difference in my plot results with or without the use of "%matplotlib inline". Can someone explain this to me if I am misunderstanding something? Here's

问题 I'm running Jupyter 5.0.0 notebook with Python 3.5.3 on Windows 10. The following example code fails to run: from concurrent.futures import as_completed, ProcessPoolExecutor import time import numpy as np def do_work(idx1, idx2): time.sleep(0.2) return np.mean([idx1, idx2]) with ProcessPoolExecutor(max_workers=4) as executor: futures = set() for idx in range(32): future = winprocess.submit( executor, do_work, idx, idx * 2 ) futures.add(future) for future in as_completed(futures): print(future

问题 I'm running Jupyter 5.0.0 notebook with Python 3.5.3 on Windows 10. The following example code fails to run: from concurrent.futures import as_completed, ProcessPoolExecutor import time import numpy as np def do_work(idx1, idx2): time.sleep(0.2) return np.mean([idx1, idx2]) with ProcessPoolExecutor(max_workers=4) as executor: futures = set() for idx in range(32): future = winprocess.submit( executor, do_work, idx, idx * 2 ) futures.add(future) for future in as_completed(futures): print(future

问题 I'm running Jupyter 5.0.0 notebook with Python 3.5.3 on Windows 10. The following example code fails to run: from concurrent.futures import as_completed, ProcessPoolExecutor import time import numpy as np def do_work(idx1, idx2): time.sleep(0.2) return np.mean([idx1, idx2]) with ProcessPoolExecutor(max_workers=4) as executor: futures = set() for idx in range(32): future = winprocess.submit( executor, do_work, idx, idx * 2 ) futures.add(future) for future in as_completed(futures): print(future

问题 I am working with Keras and happens to me to leave the jupyter notebook running overnight and close the browser. When I reopen it, the notebook gets stuck in the (Starting) phase and while the kernel is still running I cannot see any update in the output cells. Leaving the browser open doesn't help because eventually the output freezes anyway.. I don't know the exact memory taken by the notebook, but it's a con with several layers so I bet quite heavy. I am working on Ubuntu with Firefox. Any

问题 I am trying to run a jupyter notebook created in Docker. Firstly I run a container: docker run -p 8888:8888 jupyter/tensorflow-notebook What I get is: [I 19:44:47.140 NotebookApp] Writing notebook server cookie secret to /home/jovyan/.local/share/jupyter/runtime/notebook_cookie_secret [I 19:44:51.731 NotebookApp] JupyterLab extension loaded from /opt/conda/lib/python3.7/site-packages/jupyterlab [I 19:44:51.732 NotebookApp] JupyterLab application directory is /opt/conda/share/jupyter/lab [I 19

问题 I am trying to run a jupyter notebook created in Docker. Firstly I run a container: docker run -p 8888:8888 jupyter/tensorflow-notebook What I get is: [I 19:44:47.140 NotebookApp] Writing notebook server cookie secret to /home/jovyan/.local/share/jupyter/runtime/notebook_cookie_secret [I 19:44:51.731 NotebookApp] JupyterLab extension loaded from /opt/conda/lib/python3.7/site-packages/jupyterlab [I 19:44:51.732 NotebookApp] JupyterLab application directory is /opt/conda/share/jupyter/lab [I 19