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I'm trying to install eth-brownie using 'pipx install eth-brownie' but I get an error saying

I want to install packages from poetry.lock file; using poetry install.

However, the majority of packages throw the exact same error, indicating a shared fundamental problem.

What is causing this? What is the standard fix?

Specification:

• Windows 10,
• Visual Studio Code,
• Python 3.8.10 & Poetry 1.1.11,
• Ubuntu Bash.

Terminal:

• rm poetry.lock
• poetry update
• poetry install

Is it possible to set YAML line width, when dumping to file with ruyaml?

When dumping a YAML object to file with pyyaml and its content is fairly long 82+(or something similar) characters, there is a row break inserted. This can be circumvented by giving the parameter "width" to the dump function, where you can either give a specific length or as in the example below "inf".

That possibility seems to be missing in ruyaml.

I have pretrained model for object detection (Google Colab + TensorFlow) inside Google Colab and I run it two-three times per week for new images I have and everything was fine for the last year till this week. Now when I try to run model I have this message:

I have tried the similar problems' solutions on here but none seem to work. It seems that I get a memory error when installing tensorflow from requirements.txt. Does anyone know of a workaround? I believe that installing with --no-cache-dir would fix it but I can't figure out how to get EB to do that. Thank you.

Logs:

I have a local python project called jive that I would like to use in an another project. My current method of using jive in other projects is to activate the conda env for the project, then move to my jive directory and use python setup.py install. This works fine, and when I use conda list, I see everything installed in the env including jive, with a note that jive was installed using pip.

But what I really want is to do this with full conda. When I want to use jive in another project, I want to just put jive in that projects environment.yml.

So I did the following:

1. write a simple meta.yaml so I could use conda-build to build jive locally
2. build jive with conda build .
3. I looked at the tarball that was produced and it does indeed contain the jive source as expected
4. In my other project, add jive to the dependencies in environment.yml, and add 'local' to the list of channels.
5. create a conda env using that environment.yml.

When I activate the environment and use conda list, it lists all the dependencies including jive, as desired. But when I open python interpreter, I cannot import jive, it says there is no such package. (If use python setup.py install, I can import it.) How can I fix the build/install so that this works?

Here is the meta.yaml, which lives in the jive project top level directory:

I am trying to run the training of stylegan2-pytorch on a remote system. The remote system has gcc (9.3.0) installed on it. I'm using conda env that has the following installed (cudatoolkit=10.2, torch=1.5.0+, and ninja=1.8.2, gcc_linux-64=7.5.0). I encounter the following error:

I'm having trouble installing the following packages in a new python 3.9.7 virtual environment on Arch Linux.

My requirements.txt file:

I am trying to install the Tensorflow Object Detection API on a Google Colab and the part that installs the API, shown below, takes a very long time to execute (in excess of one hour) and eventually fails to install.