How to resolve the error, “module umap has no attribute UMAP”.. I tried installing & reinstalling umap but didn’t work to me

To use UMAP you need to install umap-learn not umap. So, in case you installed umap run the following commands to uninstall umap and install upam-learn instead: pip uninstall umap pip install umap-learn And then in your python code make sure you are importing the module using: import umap.umap_ as umap Instead of import umap

Python 3: Catching warnings during multiprocessing

you can try to override the Process.run method to use warnings.catch_warnings. >>> from multiprocessing import Process >>> >>> def yell(text): … import warnings … print ‘about to yell %s’ % text … warnings.warn(text) … >>> class CustomProcess(Process): … def run(self, *args, **kwargs): … import warnings … with warnings.catch_warnings(): … warnings.simplefilter(“ignore”) … return Process.run(self, *args, **kwargs) …

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Why does Python threading.Condition() notify() require a lock?

This is not a definitive answer, but it’s supposed to cover the relevant details I’ve managed to gather about this problem. First, Python’s threading implementation is based on Java’s. Java’s Condition.signal() documentation reads: An implementation may (and typically does) require that the current thread hold the lock associated with this Condition when this method is …

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How to use pytest to assert NO Warning is raised

For pytest >= 7.0 The doc now explicitely mentions this case should be solved this way (without pytest): with warnings.catch_warnings(): warnings.simplefilter(“error”) … though this may not completely solve some cases (dynamic checks: see this post). The solution suggested for pytest < 7.0, below, now raises a DeprecationWarning. Thanks to @Warren-Weckesser for signaling this in comment! …

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PEP 0492 – Python 3.5 async keyword

No, co-routines do not involve any kind of threads. Co-routines allow for cooperative multi-tasking in that each co-routine yields control voluntarily. Threads on the other hand switch between units at arbitrary points. Up to Python 3.4, it was possible to write co-routines using generators; by using yield or yield from expressions in a function body …

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