I am trying to create a new environment with Python 3.7 using Conda like:
conda create -n qnn python=3.7
I got following errors:
Collecting package metadata (current_repodata.json): done
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed
PackagesNotFoundError: The following packages are not available from current channels:
- python==3.7
Current channels:
- https://conda.anaconda.org/conda-forge/osx-arm64
- https://conda.anaconda.org/conda-forge/noarch
To search for alternate channels that may provide the conda package you're
looking for, navigate to
https://anaconda.org
and use the search bar at the top of the page.
Why is Python 3.7 apparently unavailable?
System Details
This is on an Apple Silicon (osx-arm64) machine running macOS.
No native builds available
Since Python 3.8 had been released for about a year when Apple Silicon hit the market, Python 3.7 builds for osx-arm64 were never part of the regular build matrix for Conda Forge.
Workaround: Emulate
Immediate alternatives for using 3.7 on Apple Silicon systems would be to emulate x86_64 with Rosetta or use a container system, e.g., Docker.
Creating osx-64 environments
Similar to what one does for running win-32 environments on x86_64 machines, one can create osx-64 environments like
## create empty environment
conda create -n py37
## activate
conda activate py37
## use x86_64 architecture channel(s)
conda config --env --set subdir osx-64
## install python, numpy, etc. (add more packages here...)
conda install python=3.7 numpy
⚠️ Important Note: Be sure to always activate this environment before installing packages. Otherwise, the default CONDA_SUBDIR value (osx-arm64) may be active and could result in mixing architectures in the same environment.
Note that MacOS will automatically recognize the architecture and run through Rosetta - one need not do anything special.
Requesting native build
Longer term, you could try requesting that the python-feedstock include a 3.7 build for osx-arm64. However, 3.7.12 (Sept. 2021) was technically the final feature release, and it has now entered the maintenance-only phase (see PEP 537). Also, other packages that build Python-version-specific variants would not be built for osx-arm64, so even if one had python=3.7, the packages wouldn't be there (at least not through Conda). Basically, I wouldn't bet on anyone taking this up.
Not sure if this is the best strategy, but running
CONDA_SUBDIR=osx-64 conda
worked for my use case.
Related
I am taking a beginner course in Python so I downloaded and installed Anaconda on a
Windows 10 OS. It is possible to install the last version of Python, say 3.9.x or 3.10 to be run on VSCode. How do I manage to avoid conflicts between them. Can anyone tell how should I do because I have to use that text editor. Thanks in advance.
Yes, but Anaconda includes an environment management tool, Conda, and so it would be more idiomatic to use that to create a new environment, rather than installing a native, system- or user-level Python interpreter. If you are using Anaconda, then from Anaconda Command Prompt try
conda create -n py39 python=3.9
or
conda create -n py310 python=3.10
Note the argument used in the -n (or --name) is arbitrary - feel free to name environments as you'd like.
Idea is to build the distroless docker image and available python3 google distorless image version is 3.7 - gcr.io/distroless/python3. Our code is already compiled and running with python3.5 version and required to upgrade the version into 3.7 so that we can get rid of the library, compactability issues and can make use of the distroless image with verison 3.7. Some questions are,
Will version upgrade cause any issues to the existing code compilation?
Do we need to change all the requirements.txt versions according to the 3.7?
If yes, will there is an impact of the application?
the Python language does not provide backward compatibility. My recommendation for you is to run your code on a virtual env with the new version of Python and test your code. If you do not want to use virtual env you could create a new docker image with the Python version and test your app. Regarding the requirements.txt, without seeing the libraries or packages there, it is impossible to say if you should change the file.
Background
I've just got a new M1 mac mini dev machine, and migrated from my old x86 mac using apple's migration assistant.
Doing that also copied over all my conda environments to the new machine (they were all in my home directory)
I installed the latest version of anaconda and anaconda plus all my python code and environments seem to work fine (this includes a bunch of wheel modules, notably numpy/scipy).
I did a bunch of googling for my questions below, but couldn't find any good answers anywhere - so I thought I'd ask SO as this seems like a quite common situation others will run into
Questions
Does anyone know the status of M1 native versions of python/numpy/scipy etc provided by conda forge?
I presume that all the binaries in my environments for python/numpy etc all still the old x86 versions, as they were all in environments in my home directory, and running via emulation. So, how do you go about changing/updating those to a M1 arm native
version if/when available?
A quick update as of July 2021.
TLDR
The conda-forge group have a M1 native conda installer here.
Installation is simple - run the installer, and you have conda up and running.
This will install an M1 native conda, and that conda's default environment will by default install M1 native python versions and M1 native versions of modules (if available).
There seem to be native osx M1 native wheels for most common modules now available on the conda-forge channel.
Current status
It seems Anaconda still do not have a native M1 version, nor does Miniconda. ...I can't figure out why it's taken so long and neither still seem to have native M1 support, but that's a separate issue.
Alternative
However, as steff above mentioned, conda-forge (as in the group responsible for maintaining the conda-forge channel) do have a installer for their version of conda that is itself both native M1, and also sets up your environment to pull M1 native wheels where available. This they call Miniforge.
Their github is here.
Various installers for their Miniforge (via direct download, curl or homebrew) can be found on their github page (above) - the direct link to the ARM native miniforge installer is here.
A quick search on conda-forge show's almost all common modules do now have native M1 wheels available. (look for supporting platform 'osx-arm64` eg numpy)
Caveats
I've not tested this too extensively yet, and I'm not sure exactly what happens if a non-M1 wheel is available (I believe it will default to downloading a no-arch version).
I'm also not sure/haven't tested whether you can mix and match M1 wheels with x86 mac wheels. (I'm guessing this would work, but haven't tried).
I also have only done minimal testing using the conda's pip, and how well it recognizes/tries to download/resolves M1 vs x86 pip packages.
The answer here is going to evolve over time, so here is the most up-to-date knowledge I have as of 27 Jan 2021.
Installing conda in emulation mode works completely fine. All you need to do is to install it in a Terminal run in emulation mode, or else install it using a Terminal emulator that has not been ported over yet.
Once your conda environments are up and running, everything else looks and feels like it did on x86 Macs.
If you'd like a bit more detail, I blogged about my experience. Hopefully it helps you here.
I got my M1 about 2 weeks ago and managed to install absolutely everything I need natively from conda-forge and pip. The installer you can download here.
As of 5Feb Homebrew is also officially supported on osx-arm64.
2022/03/02 answers
Native M1 installations are pretty simple now. Here are a few options for Miniforge and Miniconda.
(1) Using Apple's instructions for Tensorflow with Miniforge
This uses the same Miniforge solution mentioned above but includes an M1-optimized Tensorflow install, meaning TF has access to the M1 GPU cores.
Look for the "arm64: Apple Silicon" section at:
https://developer.apple.com/metal/tensorflow-plugin/
(2) Running native M1 with Miniforge and Rosetta with Miniconda side-by-side (Jeff Heaton's tutorial from 2021/11)
Jeff basically uses Apple's solution above for the native Miniforge install.
https://www.youtube.com/watch?v=w2qlou7n7MA
(3) Using native M1 Miniconda
There was a native M1 Miniconda installer published in 2021/11: Miniconda3 macOS Apple M1 64-bit bash (Py38 conda 4.10.1 2021-11-08)
https://docs.conda.io/en/latest/miniconda.html
My Experiences
I successfully ran the side-by-side installation from Jeff's tutorial with a few changes. It was very easy and I verified that in the native M1 Miniforge environment that Numpy is using the optimized BLAS/LAPACK linear algebra libraries and that Tensorflow has GPU access. I will update here after I run the Miniconda native M1 installer.
I installed the native version of python3 through miniforge (Apple version) and Spyder (Intel version) through homebrew and everything is working just fine for me with one exception, I've observed one strange behaviour when setting the "graphics backend" option to "automatic" instead of "inline".
Spyder >>> Prefernces >>> IPython Console >>> Graphics >>> Graphics Backend >>> inline, or automatic
When I start Spyder with the "inline" option and switch to "automatic", the opened kernels function just as expected. However, if I open new consoles they don't work at all. The issue also persists after restarting Spyder. The only way I manage to plot graphics in a separate window is to start Spyder with IPython console "graphics backend" set to "inline" and then change it to "automatic".
If I run python3 through terminal, plotting graphics works just fine as well.
My installation commands were:
brew install --cask miniforge
conda init zsh
conda activate
brew install --cask spyder
brew install PyQt#5
pip3 install matplotlib
You can check out this anouncement by Anaconda. You can now use Anaconda on your M1 MAC direclty.
"The 2022.05 release of Anaconda Distribution features native compiling for Apple M1’s ARM64 architecture (boasting 20% faster compute), Anaconda Navigator 2.1.4, conda 4.12.0, as well as several new and updated packages. 2022.05 is also the last release that will support win32."
I have two virtual environments. One has python 3.7.9. the other had 3.8.5. I have downloaded torch 1.6.0 in the 1st virtual env. But when trying to install the same torch version in the second virtual env, it downloads the entire package again instead of installing from cache.
Is there any way to force download from cache as I want the same torch==1.6.0 in both the environments and its frustrating to download it everytime.
Have a look at the listed files...
https://pypi.org/project/torch/#files
There are different wheels for different Python versions.
This makes sense, as eg the syntax changes between Python versions.
I'm trying to use bluetooth with python, and I came across a module - pybluez. Right then, I tried installing it by running pip install pybluez. The package was located and downloaded, but it raised an error when running python setup.py egg_info.
I then tried to download pyBluez from this link https://pypi.python.org/pypi/PyBluez
But, it said that the Python version installed on my PC is not 2.7 ( I have 2.7.10; do I need 2.7.0 for this?) Also, this download link is for a 32-bit system, and that might be the reason it does not run on mine.
So I ask:
1. How do I fix this error?
Error in the output when I try to install pybluez using pip:
2.Does download using https://pypi.python.org/pypi/PyBluez need python 2.7.0, and a 32-bit system? If so, can someone suggest a better way for a 64-bit system?
3.Any other bluetooth module that could work as a substitute?
I have successfully built pybluez for win10x64 with python3.6
Download and install windows 10 build tools: https://www.visualstudio.com/pl/thank-you-downloading-visual-studio/?sku=BuildTools&rel=15
Run 'Developer Command Prompt for VS' as administrator
Clone pybluez repo https://github.com/karulis/pybluez
cd to directory with repo
run python setup.py install
Happy bluetoothing
This is an "expanded solution" which supplements the other answers posted.
Bluetooth is readily supported on Linux in basically any context. Python 3 built-in socket objects work over bluetooth even. But for Windows, there are hoops to jump through. The standard solution for this is to use PyBluez. If you're really lucky, you might be able to install with just pip install PyBluez-win10. If that fails, however, the way to go is an installation via a pre-compiled "wheel".
A given wheel only works for your specific context, however, i.e. exact Python version. So, for the sake of future proofing, if you are going to need PyBluez, you should know how create a wheel from the source for yourself. It's a long, annoying process if you don't have the all the software required already and are not familiar with some parts of the process e.g. using Anaconda. So, if you are working in a team, I suggest having one person burn their time on this and then share the wheel with everyone (who are hopefully on the same version of Python!).
The following is a paraphrased version of what is posted here: https://github.com/pybluez/pybluez/issues/180 which includes the actual developer's comments and methodology.
Download and run the "Visual Studio Build Tools" installer:
For an official list of exact compilers and links to match against target Python versions, refer to: https://wiki.python.org/moin/WindowsCompilers
Here's the 2019 Build Tools link, which works with Py3.7:
https://visualstudio.microsoft.com/downloads/#build-tools-for-visual-studio-2019
During the install you MUST select BOTH "Visual C++ build tools" AND "Universal Windows Platform build tools". Leave the default options alone within those (e.g. including the Windows 10 SDK).
Note: this requires 15GB of disk space, and some patience!
Install "Miniconda":
https://docs.conda.io/en/latest/miniconda.html
Select the one which matches the bit set (32 vs 64) of the destination Python version
you wish to install PyBluez into.
Clone the PyBluez source repo to a temp location (e.g. your desktop). Then, launch the terminal and change into that directory:
git clone https://github.com/pybluez/pybluez
cd pybluez
If you did NOT put conda on the system path (as the installer recommends NOT doing so), you can add it for this local CMD session per this example command:
set CONDA_DIR=%USERPROFILE%\Miniconda3
set PATH=%CONDA_DIR%\condabin;%PATH%
Create a dedicated environment to build pybluez with the desired Python version. Then, launch that. The example below uses Python 3.7 but the same steps will also work for other versions (including Py 2.x etc)
conda create -y -n pybluez python==3.7
activate pybluez
Build a wheel file. Then, leave the dedicated environment.
python setup.py install
python setup.py bdist_wheel
deactivate
Copy the wheel to your desktop. From there, you can do with it as you wish. Then, delete the pybluez conda environment and the source repo, (as you no longer need either of them).
copy .\dist\*.whl "%USERPROFILE%\Desktop"
cd..
rd /s /q "%CONDA_DIR%\envs\pybluez"
rd /s /q pybluez
Finally, you can install the wheel to a target Python instance and/or store/share it:
The name of these files and the path will vary, so define those first for your use case
set PYBLUEZ_WHEEL=%USERPROFILE%\Desktop\PyBluez-0.22-cp37-cp37m-win_amd64.whl
set PYTHON_PATH=python
Install the wheel:
%PYTHON_PATH% -m pip install "%PYBLUEZ_WHEEL%"
Confirm installation:
%PYTHON_PATH% -c "import bluetooth; print(bluetooth.__version__)"
I downloaded a Python 3.6 wheel from here (wheels for python 2.7, 3.5, 3.6, 3.7 available too).
I installed it in my virtual environment via
pip install PyBluez-0.22-cp36-cp36m-win_amd64.whl
One command solution.
pip install git+https://github.com/pybluez/pybluez.git#egg=pybluez