The current default version of Python running on Google Colab is 3.7, but I need 3.9 for my notebooks to work.
How can I update Google Colab's Python version to 3.9 (or greater)?
In Google Colab you have a Debian-based Linux, and you can do whatever you can on a Debian Linux. Upgrading Python is as easy as upgrading it on your own Linux system.
Detect the current python version in Colab:
!python --version
#Python 3.8.16
Install new python version
Let's first install and upgrade to Python 3.9:
#install python 3.9
!sudo apt-get update -y
!sudo apt-get install python3.9
#change alternatives
!sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.8 1
!sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.9 2
#check python version
!python --version
#3.9.16
Port Colab kernel to the new installed python
As mentioned in the comments, the above commands just add a new python version to your google colab and update the default python for commandline usage. But your runtime packages such as sys are still running on the previous python version. The following commands need to be executed as well, to update the sys version.
# install pip for new python
!sudo apt-get install python3.9-distutils
!wget https://bootstrap.pypa.io/get-pip.py
!python get-pip.py
# credit of these last two commands blongs to #Erik
# install colab's dependencies
!python -m pip install ipython ipython_genutils ipykernel jupyter_console prompt_toolkit httplib2 astor
# link to the old google package
!ln -s /usr/local/lib/python3.8/dist-packages/google \
/usr/local/lib/python3.9/dist-packages/google
Now you can restart runtime and check the sys version. Note that in the new python version you have to install every packages, such as pandas, tensorflow, etc. from scratch.
Also, note that you can see a list of installed Python versions and switch between them at any time with this command:
(If nothing changed after installation, use this command to select python version manually)
!sudo update-alternatives --config python3
#after running, enter the row number of the python version you want.
It's also possible to update the kernel without going through ngrok or conda with some creative package installation.
Raha's answer suggesting making a link between the default google package and the newly installed Python version is the trick that makes this work because, at least with Python 3.9, the version of pandas (0.24.0) that the google package requires fails to build.
Here's the code I used to install and switch my Colab kernel to Python 3.9:
#install python 3.9 and dev utils
#you may not need all the dev libraries, but I haven't tested which aren't necessary.
!sudo apt-get update -y
!sudo apt-get install python3.9 python3.9-dev python3.9-distutils libpython3.9-dev
#change alternatives
!sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.8 1
!sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.9 2
#Check that it points at the right location
!python3 --version
# install pip
!curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
!python3 get-pip.py --force-reinstall
#install colab's dependencies
!python3 -m pip install ipython ipython_genutils ipykernel jupyter_console prompt_toolkit httplib2 astor
# link to the old google package
!ln -s /usr/local/lib/python3.8/dist-packages/google \
/usr/local/lib/python3.9/dist-packages/google
# There has got to be a better way to do this...but there's a bad import in some of the colab files
# IPython no longer exposes traitlets like this, it's a separate package now
!sed -i "s/from IPython.utils import traitlets as _traitlets/import traitlets as _traitlets/" /usr/local/lib/python3.9/dist-packages/google/colab/*.py
!sed -i "s/from IPython.utils import traitlets/import traitlets/" /usr/local/lib/python3.9/dist-packages/google/colab/*.py
If Google updates from Python 3.8, you'll have to change the path to the default package.
Then go the Runtime menu and select Restart runtime. It should reconnect and choose the updated version of Python as the default kernel. You can check that it worked with:
#check python version
import sys
print(sys.version)
!python3 --version
!python --version
To use another python version in google colab, you need to:
1- Installing Anaconda.
2- Adding (fake) google colab library.
3- Starting Jupyterlab.
4- Accessing it with ngrok.
# install Anaconda3
!wget -qO ac.sh https://repo.anaconda.com/archive/Anaconda3-2020.07-Linux-x86_64.sh
!bash ./ac.sh -b
# a fake google.colab library
!ln -s /usr/local/lib/python3.6/dist-packages/google \
/root/anaconda3/lib/python3.8/site-packages/google
# start jupyterlab, which now has Python3 = 3.8
!nohup /root/anaconda3/bin/jupyter-lab --ip=0.0.0.0&
# access through ngrok, click the link
!pip install pyngrok -q
from pyngrok import ngrok
print(ngrok.connect(8888))
you can also use:
# Install the python version
!apt-get install python3.9
# Select the version
!python3.9 setup.py
another way is to use a virtual environment with your desired python version:
virtualenv env --python=python3.9
Update 24.12.2022 - Unfortunately, the method does not work anymore.
This worked for me (copied from GitHub), I successfully installed Python 3.10.
#The code below installs 3.10 (assuming you now have 3.8) and restarts environment, so you can run your cells.
import sys #for version checker
import os #for restart routine
if '3.10' in sys.version:
print('You already have 3.10')
else:
#install python 3.10 and dev utils
#you may not need all the dev libraries, but I haven't tested which aren't necessary.
!sudo apt-get update -y
!sudo apt-get install python3.10 python3.10-dev python3.10-distutils libpython3.10-dev
!sudo apt-get install python3.10-venv binfmt-support #recommended in install logs of the command above
#change alternatives
!sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.8 1
!sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.10 2
# install pip
!curl -sS https://bootstrap.pypa.io/get-pip.py | python3.10
!python3 get-pip.py --force-reinstall
#install colab's dependencies
!python3 -m pip install setuptools ipython ipython_genutils ipykernel jupyter_console prompt_toolkit httplib2 astor
#minor cleanup
!sudo apt autoremove
#link to the old google package
!ln -s /usr/local/lib/python3.8/dist-packages/google /usr/local/lib/python3.10/dist-packages/google
#this is just to verify if 3.10 folder was indeed created
!ls /usr/local/lib/python3.10/
#restart environment so you don't have to do it manually
os.kill(os.getpid(), 9)
In addition to Kaveh's answer, I added the following code. (This colab python version is python 3.8 and I tried to downgrade to python 3.7)
!pip install google-colab==1.0.0
# install colab's dependencies
!python -m pip install ipython==7.9.0 ipython_genutils==0.2.0 ipykernel==5.3.4 jupyter_console==6.1.0 prompt_toolkit==2.0.10 httplib2==0.17.4 astor==0.8.1 traitlets==5.7.1 google==2.0.3
This way, I solved the crashing runtime error.
Simple as that: -
!wget -O mini.sh https://repo.anaconda.com/miniconda/Miniconda3-py39_4.9.2-Linux-x86_64.sh
!chmod +x mini.sh
!bash ./mini.sh -b -f -p /usr/local
!conda install -q -y jupyter
!conda install -q -y google-colab -c conda-forge
!python -m ipykernel install --name "py39" --user
Source: https://colab.research.google.com/drive/1m47aWKayWTwqJG--x94zJMXolCEcfyPS?usp=sharing#scrollTo=r3sLiMIs8If3
Related
While i am try to install scrapy on ubuntu mechine using
**pip install scrapy**
it's not going to workout.
can anyone suggest us?
ERROR: Command errored out with exit status 1: python setup.py egg_info Check the logs for full command output.
In the documentation, it was mentioned that to install scrapy in a venv on ubuntu based os, we need to install these dependencies sudo apt-get install python3 python3-dev python3-pip libxml2-dev libxslt1-dev zlib1g-dev libffi-dev libssl-dev
I want to have access to features from TensorFlow federated (tff.python.research) which aren't present with the pip3 install method.
I'm working on a remote server that does not have bazel, thus I cannot build from source. Are there other ways to get and install the latest working version of TFF from its GitHub REPO?
(https://github.com/tensorflow/federated)
To install the latest Tensorflow 2.0 federated, you may follow the steps below.
Install TensorFlow Federated using pip
Install the Python development environment
On Ubuntu:
$ sudo apt update
$ sudo apt install python3-dev python3-pip # Python 3
$ sudo pip3 install --upgrade virtualenv # system-wide install
On macOS:
$ /usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
$ export PATH="/usr/local/bin:/usr/local/sbin:$PATH"
$ brew update
$ brew install python # Python 3
$ sudo pip3 install --upgrade virtualenv # system-wide install
Create a virtual environment
$ virtualenv --python python3 "venv"
$ source "venv/bin/activate"
(venv) $ pip install --upgrade pip
Note: To exit the virtual environment, run deactivate.
Install the TensorFlow Federated pip package.
(venv) $ pip install --upgrade tensorflow_federated
(Optional) Test Tensorflow Federated.
(venv) $ python -c "import tensorflow_federated as tff; print(tff.federated_computation(lambda: 'Hello World')())"
Build the TensorFlow Federated pip package
Install the Python development environment.
On Ubuntu:
$ sudo apt update
$ sudo apt install python3-dev python3-pip # Python 3
$ sudo pip3 install --upgrade virtualenv # system-wide install
On macOS:
$ /usr/bin/ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"
$ export PATH="/usr/local/bin:/usr/local/sbin:$PATH"
$ brew update
$ brew install python # Python 3
$ sudo pip3 install --upgrade virtualenv # system-wide install
Install Bazel
Install Bazel, the build tool used to compile Tensorflow Federated.
Clone the Tensorflow Federated repository.
$ git clone https://github.com/tensorflow/federated.git
$ cd "federated"
Create a virtual environment.
$ virtualenv --python python3 "venv"
$ source "venv/bin/activate"
(venv) $ pip install --upgrade pip
Note: To exit the virtual environment, run deactivate.
Install Tensorflow Federated dependencies.
(venv) $ pip install --requirement "requirements.txt"
(Optional) Test Tensorflow Federated.
(venv) $ bazel test //tensorflow_federated/...
Create a new project.
$ mkdir "/tmp/project"
$ cd "/tmp/project"
$ virtualenv --python python3 "venv"
$ source "venv/bin/activate"
(venv) $ pip install --upgrade pip
Note: To exit the virtual environment run deactivate.
Install the pip package.
(venv) $ pip install --upgrade "/tmp/tensorflow_federated/tensorflow_federated-"*".whl"
Test Tensorflow Federated.
(venv) $ python -c "import tensorflow_federated as tff; print(tff.federated_computation(lambda: 'Hello World')())"
Reference: https://www.tensorflow.org/federated/install
screen shot
As Python2.7 will be deprecated on 01/01/2020. I was planning to start using python3. So, I tried to install the tensorflow==1.14.0 on the raspberry pi and it was successful, but when I am loading the Tensorflow for further operations then it throws a load error.
Python - 3.7 (Default installed by Raspbian OS)
Any suggestions why am I facing this issue?
Thanks for your time
You can't install later versions of Tensorflow on the Raspberry Pi using pip. You have to install from source. I made a video doing this: https://youtu.be/GNRg2P8Vqqs
Installing Tensorflow requires some extra steps on the Pi's ARM architecture.
This is how I installed tf 2.0 on my Pi 4:
Make your project directory:
cd Desktop
mkdir tf_pi
cd tf_pi
Make a virtual environment:
python3 -m pip install virtualenv
virtualenv env
source env/bin/activate
Run the commands based on https://github.com/PINTO0309/Tensorflow-bin/#usage:
sudo apt-get install -y libhdf5-dev libc-ares-dev libeigen3-dev
python3 -m pip install keras_applications==1.0.8 --no-deps
python3 -m pip install keras_preprocessing==1.1.0 --no-deps
python3 -m pip install h5py==2.9.0
sudo apt-get install -y openmpi-bin libopenmpi-dev
sudo apt-get install -y libatlas-base-dev
python3 -m pip install -U six wheel mock
Pick a tensorflow release from https://github.com/lhelontra/tensorflow-on-arm/releases (I picked 2.0.0). Picking a higher version of Tensorflow (like 2.1.0) requires a higher version of scipy that wasn't compatible with my Raspberry Pi:
wget https://github.com/lhelontra/tensorflow-on-arm/releases/download/v2.0.0/tensorflow-2.0.0-cp37-none-linux_armv7l.whl
python3 -m pip uninstall tensorflow
python3 -m pip install tensorflow-2.0.0-cp37-none-linux_armv7l.whl
RESTART YOUR TERMINAL
Reactivate your virtual environment:
cd Desktop
cd tf_pi
source env/bin/activate
Test:
Open a python interpreter by executing:
python3
import tensorflow
tensor.__version__
This should have no errors and output: 2.0.0
I got the same issue today when trying to run the fresh tf installation on my pi 3+
With a new SD card and Raspbian version Stretch 2018-11-13:
sudo apt install -y python3-pip python3-dev python-virtualenv
virtualenv -p python3.5 --system-site-packages myenv
source myenv/bin/activate
pip3 install --upgrade tensorflow
$ python3
Python 3.5.3 (default, Sep 27 2018, 17:25:39)
[GCC 6.3.0 20170516] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow
/home/pi/myenv/lib/python3.5/importlib/_bootstrap.py:222: RuntimeWarning: compiletime version 3.4 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.5
return f(*args, **kwds)
/home/pi/myenv/lib/python3.5/importlib/_bootstrap.py:222: RuntimeWarning: builtins.type size changed, may indicate binary incompatibility. Expected 432, got 412
return f(*args, **kwds)
>>>
Check if your Python environment is already configured (requires Python 3.4, 3.5, or 3.6):
The version of the tensorflow package that is installed by sudo python3 -m pip install --user --upgrade tensorflow has been upgraded since this question was originally posted. When this answer was last edited it required Python 3.7, 3.8, or 3.9. Check the current version of tensorflow at https://pypi.org/project/tensorflow/ before you install it.
python3 --version
pip3 --version
virtualenv --version
Install these packages if necessary:
sudo apt update
sudo apt install python3 python3-pip
TensorFlow requirements for the Raspbian operating system:
sudo apt update
sudo apt install python3-dev python3-pip
sudo apt install libatlas-base-dev # required for numpy
sudo python3 -m pip install --upgrade pip
sudo python3 -m pip install --upgrade virtualenv # system-wide install
Create a new virtual environment by choosing a Python interpreter and making a myenv directory to hold it:
virtualenv --system-site-packages -p python3 myenv
As you mentioned in your question, the python3 package version in Debian Stretch is 3.5.
Install TensorFlow (system install):
sudo python3 -m pip install --user --upgrade tensorflow
Verify the install:
python3 -c "import tensorflow as tf; tf.enable_eager_execution(); print(tf.reduce_sum(tf.random_normal([1000, 1000])))"
Success: TensorFlow is now installed. Read the tutorials to get started.
I installed the latest Tensorflow 0.5.0 from source via git clone.
and want to update to Tensorflow 0.6.0
git pull
./configure
bazel build -c opt --config=cuda //tensorflow/cc:tutorials_example_trainer
but the Tensorflow library in the directory /usr/lib/python2.7/site-packages still has the version 0.5.0
the version in the result of "pip show tensorflow" also is 0.5.0
To install the TensorFlow library from source, you need to build a PIP package and install it. The steps are as follows:
$ git pull
$ ./configure
$ bazel build -c opt //tensorflow/tools/pip_package:build_pip_package
# ...or, with GPU support
$ bazel build -c opt --config=cuda //tensorflow/tools/pip_package:build_pip_package
$ bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg
# The name of the .whl file will depend on your platform.
$ pip install /tmp/tensorflow_pkg/tensorflow-0.6.0-cp27-none-linux_x86_64.whl
git pull doesn't work for me since some local files are modified by the last build so with a slight modification I update like this:
git fetch --all
git reset --hard origin/master
./configure
bazel build -c opt --config=cuda //tensorflow/tools/pip_package:build_pip_package
bazel-bin/tensorflow/tools/pip_package/build_pip_package /tmp/tensorflow_pkg
sudo pip install /tmp/tensorflow_pkg/tensorflow-0.8.0-py2-none-any.whl
Tested to work as of today. The Installation from Source instructions in tensorflow docs are misleading in the sense they only include the real pip wheel installation commands for Mac and the example-trainer build command exists instead in Linux instructions.
To show the version:
python -c "import tensorflow; print(tensorflow.__version__);"
And if it is not the latest, you have uninstall it via pip uninstall:
sudo pip uninstall tensorflow
and subsequently install it:
export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow-0.9.0-cp27-none-linux_x86_64.whl
sudo pip install $TF_BINARY_URL
Before trying to update tensorflow try updating pip
pip install --upgrade pip
If you are upgrading from a previous installation of TensorFlow < 0.7.1, you should uninstall the previous TensorFlow and protobuf using,
pip uninstall
first to make sure you get a clean installation of the updated protobuf dependency.
Uninstall the TensorFlow on your system, and check out Download and Setup to reinstall again.
If you are using pip install, go check the available version over https://storage.googleapis.com/tensorflow, search keywords with linux/cpu/tensorflow to see the availabilities.
Then, set the path for download and execute in sudo.
$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.0.0-py2-none-any.whl
$ sudo pip install --upgrade $TF_BINARY_URL
For more detail, follow this link in here
If you get the error saying not a supported wheel on this platform. You might be updating tensorflow for python3. For that you will need pip3
Try installing pip3
sudo apt-get -y install python3-pip
Then, set the path for download if you haven't already set the path
$ export TF_BINARY_URL=https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.1.0rc0-cp35-cp35m-linux_x86_64.whl
$ pip3 install --ignore-installed --upgrade $TF_BINARY_URL
updating tensorflow install with sudo pip install --upgrade https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.7.1-cp27-none-linux_x86_64.whl.
I find it in the below issue,mohamed-ali's comment. https://github.com/tensorflow/tensorflow/issues/1105