flang | Fortran language front-end | Compiler library

down to the very bottom of the stack error:

As others have stated, Python 3.10 is not currently compatible with Matplotlib. You need to install and use Python 3.9 until it is supported. Until then you have a few options:

You can use the Python Launcher for Windows (py.exe) script to choose which Python version to run like so:

py.exe script help: py -h

List all installed versions py -0

Use a specified version py -3.9

e.g. 1 Create a virtual environment using python 3.9 py -3.9 venv .venv

e.g. 2 install matplotlib with pip using python 3.9 py -3.9 -m pip install matplotlib

On Linux you can run whatever Python version you like like so:

python3.9

You can set up a local (your working directory and all sub-directories) virtual environment that will use your specified version like so:

python3.9 -m venv .venv

Which will set the version of python used to 3.9 while in the local directory, and allow you to type python instead of python3.9 each time you need it.

Another relevant and helpful post by Rotareti here.

Please note that I have not described how to activate and use Python Virtual Environments here in detail, for more information on using them read the python docs.

Reference this answer if you're interested in installing a matplotlib release candidate.

In scipy's PyPI page, it looks like scipy doesn't support 3.10 as the meta says

Not totally sure, but I ran into the same issue. After some digging and testing I think I've found out that Matplotlib, and pylab aren't compatible with python3.10 yet. For the time being I've kept python3.9 along with 3.10 so whenever I use matplotlib, numpy, or pylab, I just use version 3.9.

Try to upgrade your pip

You can use pandas.merge to pull Quantite requise in from RecetteDF whenever you have a match. The merge should be done using left, so that we preserve rows of InventaireDF even when there is no match. Here is some code that should work:

This is a classic use case for threading.Semaphore

Inside each function that can't be run concurrently, Instantiate it globally (in the main thread) using Semaphore(1). Use acquire() and release() methods accordingly to serialize access to your "shared resource" (inside the main monitir_folder function or the process_csv functions, depends on where you're getting the error - in this case, CSV processing internal state

As the number of permits is 1, an RLock will also make a good fit, but A Semaphore better express what you are trying to achieve.

Example:

There are 3 slightly different versions of the solution here, for various versions of MySQL and MariaDB.

MariaDB 10.5 is compatible with all 3 solutions. MySQL 8.0 is compatible with 2, and MySQL 5.7 is compatible with just one of the following.

The pairs derived table or WITH clause term provides the pairs of patterns ('25TH', '25'), etc.

Once we have that, it's just a matter of joining with that list in your original SELECT query expression, used to generate the rows to be inserted.

What happens is that some libraries that require compiling, such as numpy, included the pre-compiled binaries inside the installer (wheel) file. But they won't include binaries for non-stable releases (or niche architectures) - instead, the same file has the source code and some of the resources needed to build the binaries on the client (computer that is installing the library) side.

The error indicates that: the binaries are not included, and building them on your computer failed, probably likely to the lack of a build environment. Under Linux it is more or less simple to install everything needed to build numpy (and other libraries). Setting up such an environment on Windows computer can be somewhat complicated.

You'd be better looking for an unofficial build wheel with the package pre-compiled for Python 3.10 - if numpy is already working with 3.10, which might not be the case: while for most end-user code no changes are needed changing from Python 3.9 to 3.10, projects like numpy depend heavily on internal details of the language.

One of the mirrors which keep pre-compiled binaries for various Python package seems to have a numpy for Python 3.10 on windows: https://www.lfd.uci.edu/~gohlke/pythonlibs/#numpy (please note that while looking alright, there is no mechanism to verify these packages are not adulterated from the source code, as happens with all binary installs (binary installs from official sources usually will have hashes or other verifying mechanisms + the certificate chain to the domain/brand names) , so, while I personally would use packages from lfd.uci.edu, this is not risk free)