I just started using Python 3 on Jupyter so I'm not really confortable with it. When I open a file with some commands, if I try to run it, the screen will give me back errors saying that the variables are not defined.
If I try to run directly filename.find("2019") it gives an error back. So when I open a file should, as first step, run all the cells?
Yes, generally speaking, when you open an existing notebook and want to add some code to it at the end, you should first run all the existing cells. You can do this from the menu: Cell -> Run All. Otherwise you would have no proper way of testing your additional code, since it may depend on changes to the namespace in the preceding code.
If the notebook wasn't active so far in that Jupyter session, there is no need to restart the kernel. Jupyter starts a separate kernel instance for every notebook you open.
Related
So I have a project that has multiple files regular python, and I'm using a jupyter lab python file as the 'main' file that imports and runs all the rest of the code. But if I make changes to those python files, the jupyter lab file does not automatically respond to updates in those files, and it takes a long time before the code runs properly with the updates.
The main problem is that I have a text file that I constantly update, and the jupyter lab file reads from that, but it takes forever before the changes in the text file are actually noticed and the code runs off that. Is this just a known issue with jupyter lab or?
There is no code so is difficult to know what is happening here. But how the Jupyter environ "notice" these changes? You must to re run de code again and must to consider than Jupyter maintain the vars in memory until the kernel is restarted (because the garbage collector of Python).
I've tried to erase the variables with del but always Jupyter maintain a reference to the old value (I don't know why) for that reason I try to use my code inside of function's scope in this way the variable dies when the function is done. This is the only way I found to deal with this problem.
I always try work with functions because is hard to debug a code in Jupyter with old variables values.
As the title says, is there a way to run a Jupyter Notebook cell in the background (in Python)?
For example, is there a hypothetical magic command %%run_in_background that allows me to kick off a cell to execute in the background without blocking other cells from executing.
Technically you can’t do that, each kernel is like an instance of python, you can only run a script at a time.
You could run the cell, then refresh the browser and run the notebook fresh. The previous command will continue running but there is no way of accessing it in the notebook anymore. You won’t get the result you want, the output from the previous run won’t appear in this new instance.
Your best bet is to use 2 different notebooks, or 2 python scripts or use multiprocessing modules.
Lately, I've been running some Jupyter notebooks in VS Code, and I've been encountering a strange issue: whenever I open such a file, I am bombarded with pop-ups that look like this:
Sometimes a few will pop up; other times it can be upwards of 10 pop-ups. What's bizarre about this is that I already have my VS Code set up properly, and I can run my Jupyter notebooks just fine. I've tried selecting the 'Modify' option and going with the default selections just to make it go away, but no dice. How do I prevent these annoying pop-ups?
Per your new comments, can you check your default settings to see which application is targeted to open .ipynb files? Perhaps .ipynb files are linked to open (strangely) via the Setup exe.
I can't import statsmodels.api in Jupyter Notebook anymore. I thought that it requires updating statsmodels.api. Then I typed "Conda update statsmodels.api". Then, the message comes up below.
PackageNotInstalledError: Package is not installed in prefix.
prefix: XXX
package name: statsmodels.api
Note: you may need to restart the kernel to use updated packages.
In order to update statsmodels.api, it seems that it would require restarting the kernel. But when trying to restart kernel, the warning came up as below.
"Do you want to restart the current kernel? All variables will be lost."
What does "all variable will be lost" mean? Will I lose all the things saved at Jupyter notebook? If so, how can I restart the Kernel safely without losing all the things I keep in my Jupyter notebook?
Restarting your kernel will reset your Jupyter notebook and remove all variables or methods you have defined.
You will not lose the code written by you. Just that, you have to run all the code cell again to set the variables and methods.
OR,
You can do "Restart & Run All"
It will show the message--
Are you sure you want to restart the current kernel and re-execute the whole notebook? All variables and outputs will be lost.
However, after selecting the above option, all the variables and methods will be set again. You don't have to manually execute all the code cells.
Jupyter lab has this feature where I can have a ipython console for every notebook I have opened. Whenever I run a cell inside this notebook, the console will have all the variables defined and modules imported corresponding to notebook. In addition, we can run extra commands and helps in debugging at times. Is there a similar feature in VS code? I really like it and would like to move completely to vs code. Python interactive command line in vscode is the closest to this that I found. However, it is not attached to the notebook and I have to run all the code inside the notebook which is a bit tedious.
I believe this would work Connecting a terminal to an existing kernel
However, you're likely looking for a way to do this within VS code. You might be able to do this by running %connect_info in a cell, starting a terminal, and then running the appropriate jupyter command.
Something like so:
jupyter console --existing kernel-2c0993da-95c7-435a-9140-118c10d33e1a.json
If you're refering to .py files you can do that the same way you would in pycharm.
First, you need to put a breakpoint in the code:
Them you run the code with the debugger:
Then, when the code reaches the breakpoint, you will be able to play with the variables, like the Jupyter terminal:
I also like to have a JupyterLab-style console open that is connected to a notebook. This is my workaround in order to achieve this in Visual Studio Code (at least it works when my kernel is a remote Jupyter session).
Suppose your notebook is called hello.ipynb.
Create a dummy file called hello.py.
Open hello.py, right-click in the code window and choose Run Current File in Interactive Window. This opens the JupyterLab-style console.
Change the kernel for the interactive window to the same kernel that the notebook hello.ipynb is using.
(Optional) Close the hello.py tab since it is not needed.
Now I have an interactive window sharing everything with the notebook.