pynacl | Python binding to the Networking and Cryptography | Cryptography library

Looking at the strace output for both root and greg, the problem seems clear.

For the root user, python 3.6 finds the libraries in /usr/lib64/python3.6.

However, for greg, it only looks under /usr/bin/python3 for subdirectories. That doesn't work because /usr/bin/python3 is a file.

I suspect that the user greg has PYTOHNHOME set erroneously to the location of the Python binary , and that is causing the issue.

Remove PYTOHNHOME from your environment, log out and log in again.

Note: the stuff below is probably barking up the wrong tree. I'll leave it for information.

The encodings module is an (undocumented) part of the python standard library. It is used by the locale module.

Based on the output I suspect that your Python installation has been damaged or corrupted. Try re-installing python.

EDIT:

If a forced re-install doesn't fix the problem, check that the directory encodings exist in your Python stdlib directory, and is accessible for all users.

To find out which directory that is:

This is mostly the same as the link you attached in your comment, but here is a more succinct example that may help

Your error says you don't have the make utility installed.

Install it by executing

Seems you need to upgrade pip, see this question.

But there can be multiple pips in a Dataproc cluster, you need to choose the right one.

1. For init actions, at cluster creation time, /opt/conda/default is a symbolic link to either /opt/conda/miniconda3 or /opt/conda/anaconda, depending on which Conda env you choose, the default is Miniconda3, but in your case it is Anaconda. So you can run either /opt/conda/default/bin/pip install --upgrade pip or /opt/conda/anaconda/bin/pip install --upgrade pip.

2. For custom images, at image creation time, you want to use the explicit full path, /opt/conda/anaconda/bin/pip install --upgrade pip for Anaconda, or /opt/conda/miniconda3/bin/pip install --upgrade pip for Miniconda3.

So, you can simply use /opt/conda/anaconda/bin/pip install --upgrade pip for both init actions and custom images.

Thanks for providing a concrete example on this, you're very close! The encoding is absolutely the issue here -- the pubkey is correctly encoded in Python as bytes. That first byte of \x90, encoded as two hex values, is 144 in JS, and you can check that in Python with: int('90', 16) = 144.

So to verify your key, you can instead use the base58 package https://github.com/keis/base58 and do:

Your application is a worker (Procfile declares types -> worker) so it does respond to HTTP requests.

Change to web and make sure you bind the PORT provided by Heroku.

BTW BOTs can run as workers (without dealing with incoming requests) if they poll the server for messages/updates. This is a viable option too (keep it as worker) but ensure the BOT logs what it does at startup.

Try to upgrade pip: python -m pip install --upgrade pip

Build tags in you environment.yml are quite strict requirements to satisfy and most often not needed. In your case, changing the yml file to

Looks like this is part of an actively tracked issue with Tkinter in PyCharm. You can find the reference on the Pycharm's developer's issue tracker. The issue is undiagnosed, but if looking at similar problems with Tk on StackOverflow, one can see that it's an issue with thread safety and/or multithreading.

All I can do is speculate as to the cause, which is not helpful, however, I can at least collate the suggested workarounds:

1. Switch to a different Matplotlib backend (See docs: What is a backend?). Such as Qt5, but you will need to make sure they are available in your environment.

   This approach is the most promising as other backends are better able to deal with not being the main thread or are explicitly safe for multi-threading. It's also the simplest unless you have a really specific reason for preferring TkAgg.

2. Do not use the debugger with interactive plots.

3. Set "Variables Loading Policy" to "Synchronously" in Debugger as suggested by a PyCharm dev in the linked issue.

4. Enable "Scientific mode" in Pycharm.

5. More esoteric workarounds such as closing your figures within the code before drawing the second one. Example, after plotting the first figure: