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Downgrading python within a conda enviorment

Hello I am trying to downgrade my python version within a conda environment. I was originally running 3.6 but I package I wanted required version 3.7. So I ran conda install python=3.7 adn built then installed apex, the package I needed. however I now needed to return to python 3.6 so that I could install numpy 1.13.3. I ran conda install --no-depspython=3.6 This gives me the a whole lot of package conflict errors .I then tried uninstalling python (to later reinstall) but this produces this error RemoveError: This operation will remove conda without replacing it with another version of conda.. So is there any possible way to downgrade my python version?

Tensorflow pip install on mac with python3

I know this has been asked many times, I saw them tried to solve my problem but I can't, nothing works for me.
I have a mac m1, My os version is BigSur 11.5.1
My python3 version is 3.8.10
I have a project folder, which I created my env in there as atai_env
I ran pip upgrade, my pip version is current which is 21.3.1
I activated my env and ran pip install tensorflow which gives this error;
ERROR: Could not find a version that satisfies the requirement tensorflow (from versions: none)
ERROR: No matching distribution found for tensorflow
I saw some command as pip install tensorflow-macos so I tried it, it seems to install but at the end it gives this Failed to build h5py which I tried to install but failed again
Then I tried to ran pip command given here for python 3.8 -> https://www.tensorflow.org/install/pip and it gives below error;
tensorflow-2.7.0-cp38-cp38-macosx_10_11_x86_64.whl is not a supported wheel on this platform.
I am so sick of this :/ I tried to install other versions of python but it always fails. Can someone explain what should I do, I can't believe I spent more than 2 hours on this.
On the tensorflow install page, it seems I should only be running pip install tensorflow but that doesn't work

Ok, Nothing that I found on google helped. I started over, and decided to try python versions starting from 3.9 with decreasing versions. Finally this command just worked -> pip install tensorflow with python 3.7.9 It is so frustrating, cost me a few hours. I wasn't expecting it would be unstable like this. Anyway, if you happen to face it just try to use one of the version 7 even tho tensorflow says it works for 3.7 - 3.9
PS: I am sorry but this is really stupid, it is almost 2022 and we are working on AI with this framework comon :/

I have MacOS BigSur 11.6.1 running and just created a virtualenv with Python 3.8.12. Installing tensorflow works without any problems:
pip install tensorflow
pip install tensorflow 1 err | 8s | voice_assistant py
Collecting tensorflow
Downloading tensorflow-2.7.0-cp38-cp38-macosx_10_11_x86_64.whl (207.1 MB)

I could successfully install and run TensorFlow from my M1 MacBook Pro. Monterey 12.4. Here's what I did:
1. Install Homebrew first
How typical.
2. Install Anaconda via Homebrew
brew install anaconda
Installing Python is a mess and I know most tutorials will suggest to use pyenv as the version management tools. I tried that, but didn't work. What worked for me is Anaconda.
3. Download PyCharm
It's a GUI-friendly way to switch between Python versions and environments.
4. Set the Python interpreter inside PyCharm
Note that I use Conda Environment. Note also that the conda executable is inside /opt/homebrew/anaconda3/bin/conda.
5. Install tensorflow-macos from the PyCharm terminal
After doing this, you can import tensorflow as tf inside your .py files.

You can try upgrading the version of pip.

Can't install tensorflow on pycharm?

I recently installed pycharm. I also use a different libraries when I code. I was able to install Numpy, Pandas, etc. But when I tried to install tensor flow, I got an error saying,
ERROR: Could not find a version that satisfies the requirement tensorflow (from versions: none)
ERROR: No matching distribution found for tensorflow
I have the latest pip(20.1.1) and latest pycharm version. I use python 3.8.1 which is not the latest. I don't know if it's the problem or not because it fits the requirements.

I had the same issue , it's because the latest version of Python matches with Tensorflow 2.x , and these versions are not supported by pip installation ( venv ) , you better install Anaconda and create a portable environnement that you can use on multiple projects , it'll be easier to install Tensorflow
conda install tensorflow
Or you can use the Anaconda Navigator for a gui interface packages installation

Try first using pip command. You will have more details of the fails.
pip install pandas
also check which python version are you using inside pycharm. I suggest you to configure a virtualenv.

Try this,
MacOS:
python -m pip install --upgrade https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-2.2.0-cp38-cp38-macosx_10_14_x86_64.whl
Windows:
python -m pip install --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.2.0-cp38-cp38-win_amd64.whl

I have python 3.7.4 installed but I am unable to install dolfin package

I have python 3.7.4 installed on my computer in windows platform. I can not install dolfin package
pip install dolfin
ERROR: Could not find a version that satisfies the requirement Dolfin (from versions: none)
ERROR: No matching distribution found for Dolfin

You cannot simply install dolfin package using pip.
Check this official doc for detailed guide.
After installation you need to install these python dependencies.
pybind11 (https://github.com/pybind/pybind11)
NumPy (http://www.numpy.org)
ply (https://github.com/dabeaz/ply)

As stated in the issue #515, pip install dolfin is not possible.
You may want to check general documentation or code documentation for the installation guide.

The other answers are correct. It's currently (still) not possible to install dolfin via pip (as of 11/2021).
I want to add to the other answers, that it is also possible to install dolfin conveniently via the conda package manager: https://anaconda.org/conda-forge/fenics-dolfin
If you don't have the conda command, install Anaconda or Miniconda. Miniconda is enough, since you only need the conda command and packages dependencies will be installed automatically by conda.
Note: After the installation, I needed to execute source ~/.profile to
activate the default virtualenv in which conda is accessible.
Execute conda install -c conda-forge fenics-dolfin to install dolfin.
I don't like to install conda system-wide for this, but this way it's possible to install dolfin without building anything from source yourself. (I assume you are looking for a quick and easy way to install dolfin, since you did not ask a specific question.)

How to downgrade tensorflow, multiple versions possible?

I have tensorflow 1.2.1 installed, and I need to downgrade it to version 1.1 to run a specific tutorial. What is the safe way to do it? I am using windows 10, python 3.5. Tensorflow was installed with pip3, but "pip3 show tensorflow" returns blank.
Is it possible to have multiple version of tensorflow on the same OS?

Pip allows to specify the version
pip install tensorflow==1.1

I discovered the joy of anaconda: https://www.continuum.io/downloads. It allows multiple virtual environments to host different versions of phyton and tensorflow. For example the following creates a virtual environment with pyton3.5 and tensorflow1.1
C:> conda create -n tensorflow1.1 python=3.5
C:> activate tensorflow1.1
(tensorflow1.1)
C:> pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-1.1.0-cp35-cp35m-win_amd64.whl
voila, a virtual environment is created.

Is it possible to have multiple version of tensorflow on the same OS?
Yes, you can use python virtual environments for this. From the docs:
A Virtual Environment is a tool to keep the dependencies required by different projects in separate places, by creating virtual Python environments for them. It solves the “Project X depends on version 1.x but, Project Y needs 4.x” dilemma, and keeps your global site-packages directory clean and manageable.
After you have install virtualenv (see the docs), you can create a virtual environment for the tutorial and install the tensorflow version you need in it:
PATH_TO_PYTHON=/usr/bin/python3.5
virtualenv -p $PATH_TO_PYTHON my_tutorial_env
source my_tutorial_env/bin/activate # this activates your new environment
pip install tensorflow==1.1
PATH_TO_PYTHON should point to where python is installed on your system.
When you want to use the other version of tensorflow execute:
deactivate my_tutorial_env
Now you can work again with the tensorflow version that was already installed on your system.

If you are using python3 on windows then you might do this as well
pip3 install tensorflow==1.4
you may select any version from "(from versions: 1.2.0rc2, 1.2.0, 1.2.1, 1.3.0rc0, 1.3.0rc1, 1.3.0rc2, 1.3.0, 1.4.0rc0, 1.4.0rc1, 1.4.0, 1.5.0rc0, 1.5.0rc1, 1.5.0, 1.5.1, 1.6.0rc0, 1.6.0rc1, 1.6.0, 1.7.0rc0, 1.7.0rc1, 1.7.0)"
I did this when I wanted to downgrade from 1.7 to 1.4

Pay attention: you cannot install arbitrary versions of tensorflow, they have to correspond to your python installation, which isn't conveyed by most of the answers here. This is also true for the current wheels like here (from this answer above). For this example, the cp35-cp35m found inside the url hints that it is for Python 3.5.x
A huge list of different wheels/compatibilities can be found here on github.
By using this, you can downgrade to almost every availale version in combination with the respective for python. For example:
pip install tensorflow==2.0.0
(note that previous to installing Python 3.7.8 alongside version 3.8.3 in my case, you would get this:
ERROR: Could not find a version that satisfies the requirement tensorflow==2.0.0 (from versions: 2.2.0rc1, 2.2.0rc2, 2.2.0rc3, 2.2.0rc4, 2.2.0, 2.3.0rc0, 2.3.0rc1)
ERROR: No matching distribution found for tensorflow==2.0.0
this also holds true for other non-compatible combinations.)
This should also be useful for legacy CPU without AVX support or GPUs with a compute capability that's too low.
If you only need the most recent releases (which it doesn't sound like in your question) a list of urls for the current wheel packages is available on this tensorflow page. That's from this SO-answer.
Note: This link to a list of different versions didn't work for me.

You can try to use the options of --no-cache-dir together with -I to overwrite the cache of the previous version and install the new version. For example:
pip3 install --no-cache-dir -I tensorflow==1.1
Then use the following command to check the version of tensorflow:
python3 -c ‘import tensorflow as tf; print(tf.__version__)’
It should show the right version got installed.

If you have anaconda, you can just install desired version and conda will automatically downgrade the current package for you.
For example:
conda install tensorflow=1.1

Click to green checkbox on installed tensorflow and choose needed version

You can downgrade TensorFlow version to a lower version by running:
1.Check the version of TensorFlow that currently installed by:
pip3 show tensorflow
2.Then, Downgrade TensorFlow to a lower version by running:
pip3 install --upgrade tensorflow==<version>
Set the version to a lower number than the currently installed release. When choosing, make sure the version is compatible with the Python release.
If you are using a Notebook environment, run the following command and restart the kernel when the installation completes:
!pip install --upgrade tensorflow==<version>
Although the best practice is to use the latest version of Python and
TensorFlow since older versions have vulnerability issues. So be
cautious when downgrading.