Develop Reference

Problem after install rospy through conda

I met a problem when I try to install rospy through conda. First, I use command "conda activate mujoco_py" to activate a specific environment I usually use. Then I input the command " conda install -c conda-forge ros-rospy ". Then after I finish installing the rospy, I input the command "env |grep ROS", it shows as below:
ROS_VERSION=1
ROS_PYTHON_VERSION=3.8
ROS_PACKAGE_PATH=/home/shine/anaconda3/envs/mujoco_py/share
ROSLISP_PACKAGE_DIRECTORIES=/home/shine/catkin_final/devel/share/common-lisp:/home/shine/catkin_ws/devel/share/common-lisp
ROS_IP=192.168.1.7
ROS_ETC_DIR=/home/shine/anaconda3/envs/mujoco_py/etc/ros
ROS_MASTER_URI=http://192.168.1.7:11311/
ROS_ROOT=/home/shine/anaconda3/envs/mujoco_py/share/ros
ROS_DISTRO=melodic
My Ubuntu system is ubuntu 20 and install ROS noetic. Does anyone know how to deal with the problem of that? I would like to use ros in my specific conda environment and also without conda it can be also run. I try to use the command "conda uninstall ros-rospy" to uninstall it from my conda environment, but I failed.

Oh! I dealt with the problem with the command "conda uninstall ros-rospy" with three times. Sometimes you need to try several times due to the speed of the internet or your personal device situation.

Installing Tensorflow - not supported wheel

I have installed Python version 3.5 and 3.6 and anaconda.
The following error occures when trying to install tensorflow following the steps here
https://www.tensorflow.org/install/install_windows
unsing anaconda
(tensorflow) C:> pip install --ignore-installed --upgrade https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow-1.0.1-cp35-cp35m-win_amd64.whl
tensorflow-1.0.1-cp35-cp35m-win_amd64.whl is not a supported wheel on this platform.
As I am new to Python, I do not know how to circumvent this probelm.
I am using Win10 with 64bit.
Thanks a lot and best,
Martin

I ran into the same difficulties with the same error. It seems to be that Python 3.6 isn't immediately supported and found a sort of workaround here (note that this involves installing Python 3.5 which I did not already have installed, I don't know if this should be done a different way if its already installed):
If you are using anaconda distribution, you can do the following to use python 3.5 on the new environment "tensorflow":
conda create --name tensorflow python=3.5
activate tensorflow
conda install jupyter
conda install scipy
pip install tensorflow
\# or
\# pip install tensorflow-gpu
It is important to add python=3.5 at the end of the first line, because it will install Python 3.5.
If you've already created the tensorflow environment (the conda create step), you'll have to delete it and start over. Otherwise, you'll run into an error "CondaValueError: Value error: prefix already exists: C:\[your environment location]" (If you run into the unsupported wheel error, then you probably created the environment already.)
To delete your previous environment, according to the Conda Cheat Sheet, you first deactivate from (tensor flow) if needed by calling deactivate, then call conda remove --prefix ~/bioenvcopy --all. For ~/bioenvcopy I believe you use the tensorflow environment path. The location can be found by calling conda info --envs (citing the cheat sheet once again). Mine, for example, was conda remove --prefix ~/Anaconda3/envs/tensorflow
I successfully used this work around on Windows 10.
This solution probably be obsolete when 3.6 is supported.

Creating the tensorflow env without the correct python version did not work for me. So I had to do the following, which worked...
>deactivate tensorflow # start by deactivating the existing tensorflow env
>conda env remove -n tensorflow # remove the env
>conda create -n tensorflow python=3.5
>activate tensorflow

i had the same problem in windows 10 and python 3.6
so i navigated to anaconda navigator ( just search anaconda navigator in start search).
in the Environment tab you can create/delete your environments.
just create an environment, name it tensorflow and choose python 3.5 as python version.
then you can activate tensorflow in your command line:
activate tensorflow
and install tensorflow with :
pip install tensorflow #or tensowrlow-gpu

I had the same problem after hours of searching, I found that to save yourself from installing error problem in tensorflow. The convenient way for installing tensorflow is by creating a virtual environment in Conda with python 3.5.2 and using Conda-forge. This is done by running this commands:
conda create -n tensorflow python=3.5.2
activate tensorflow
conda config --add channels conda-forge
conda install tensorflow

Try installing the 64-bit version of Python 3.6.8:
https://www.python.org/ftp/python/3.6.8/python-3.6.8-amd64.exe
I was getting the same error with the same OS and that's what fixed it. Apparently Tensorflow doesn't work on 32-bit Python even if your OS is 64-bit.

Try uninstalling everything (python, etc.) and try again using the cmd only, not git bash or PowerShell.
https://github.com/tensorflow/tensorflow/issues/9264

In Anaconda prompt, follow the instruction on Installing with Anaconda,
conda create -n tensorflow
activate tensorflow
Then the third step is a little different, try:
pip install tensorflow
This should work, good luck! If anything wrong happens, please let me know.

Tensorflow GPU - Spyder

I am having a problem with importing tensorflow GPU on spyder.
This is what I get when I type import tensorflow on iPython using Spyder 3 (on MacOS)
When I checked what packages I have within tensorflow I get this list, which I see that iPython, and Spyder are not included.
Also in anaconda, when I click on tensorflow in Environments, I have the option to open it with Python, with terminal, but not with iPython or Spyder (or Jupyter)
I would very much appreciate any help.
UPDATE 1:
Ok I managed to get Spyder on tensorflow's ENV but when I run the command 'import tensorflow' on iPython I get this error (when I run the same command on Python's tab everything seems to work just fine.

Finally I solved this mystery. If you have installed Spyder from the Anaconda, go to the Anaconda launcher. There go to environments, you will see two of them: root and tensorflow. The latter one is created due to the instructions by tensorflow.org. Just run all those instructions on the root, don't activate tensorflow environment, it will work. Everything will be available in spyder.

The instructions mentioned on the (https://www.tensorflow.org/install/install_windows) link do NOT work for the Ananconda/Spyder setups on windows. Having struggled through this for hours below is the easiest solution to get this working. Hope this helps!
Basically you do NOT need to create a seperate tensorflow environment if you want to run this on spyder. Use the below commands to install tensorflow on the ananconda client.
1) Open the Ananconda prompt from the installation folder in the start menu.
2) Run below commands:
conda install pyqt
conda install tensorflow

Spyder is picking up the default Anaconda Env, whereas you have tensorflow install in a separate environment tensorflow
To work with Spyder & tensorflow, install tensor flow and openssl in default ENV

I figured out how to get this working using the instruction on Tensorflow link. Once you create the tensorflow enviroment you can Spyder(Tensorflow) in your ananconda start menu folder. If you run your code by opening this the tensorflow should work.

Using the Anaconda Navigator:
It works for me in a different way:
As tensorflow is separately created environment, install spyder in tensorflow envirnment.
(Anaconda>Home>Applications on>tensorflow>spyder>install ... wait for installation to complete and ten launch)

I have seen another issue in anaconda. If you install Tensor flow in root or custom environment (like 'tensorflow') its not accessible from jupyter notebook or spyder. The best way to do this is to install it in the administrator mode. Follow these steps:
Open "Anaconda Prompt" as an administrator.
Verify the status on top written "Administrator: Anaconda Prompt"
DON'T Activate any of the environments, root or tensorflow.
Type in the command "pip install --ignore-installed --upgrade tensorflow-gpu" to install Tensorflow with GPU support.
To install Keras type "conda install -c conda-forge keras"
To verify installation, type 'python' and then inside python env. type 'import tensorflow as tf'. If all is well it will work without error.

I faced the same issue and solved by performing following steps in order.
Assuming that you have created conda environment, installed tensorflow and activated it and also installed spyder.
Check the executable python of your conda environment
>>import sys
>>sys.executable
Note the path of python executable.
Go to Spyder preferences and set the interpreter path to the one noted above.

How to install xgboost in Anaconda Python (Windows platform)?

I am a new Python user. I downloaded the latest Anaconda 3 2.4.1 (Python 3.5) from the below link:
https://www.continuum.io/downloads
My PC Configurations are: Windows 10, 64 bit, 4GB RAM
I have spent hours trying to find the right way to download the package after the 'pip install xgboost' failed in the Anaconda command prompt but couldn't find any specific instructions for Anaconda.
Can anyone help on how to install xgboost from Anaconda?

The easiest way (Worked for me) is to do the following:
anaconda search -t conda xgboost
You will get a list of install-able features like this:
for example if you want to install the first one on the list mndrake/xgboost (FOR WINDOWS-64bits):
conda install -c mndrake xgboost
If you're in a Unix system you can choose any other package with "linux-64" on the right.
Update on 22/10/2020:
Without searching in conda list of channels, you can install it using (source: https://anaconda.org/anaconda/py-xgboost) :
conda install -c anaconda py-xgboost

Anaconda's website addresses this problem here: https://anaconda.org/anaconda/py-xgboost.
conda install -c anaconda py-xgboost
This fixed the problem for me with no problems.

Download package from this website.
I downloaded xgboost-0.6-cp36-cp36m-win_amd64.whl for anaconda 3 (python 3.6)
Put the package in directory C:\
Open anaconda 3 prompt
Type cd C:\
Type pip install C:\xgboost-0.6-cp36-cp36m-win_amd64.whl
Type conda update scikit-learn

After trying some things the only thing that worked for me is:
conda install -c anaconda py-xgboost

I was able to install xgboost for Python in Windows yesterday by following this link. But when I tried to import using Anaconda, it failed. I recognized this is due to the fact that Anaconda has a different Python distribution. I then searched again and found this great article which made it!
The trick is after installing successfully for regular Python, to have it work for Anaconda, you just need to pull up the Anaconda prompt and cd into this folder "code\xgboost\python-package", then run:
python setup.py install
And voila! The article says you need to add the path, but for me it worked directly. Good luck!
Also copied below the original contents in case the link is not available...
Once the last command completes the build is done. We can now install
the Python module. What follows depends on the Python distribution
you are using. For Anaconda, I will simply use the Anaconda prompt,
and type the following in it (after the prompt, in my case [Anaconda3]
C:\Users\IBM_ADMIN>):
[Anaconda3] C:\Users\IBM_ADMIN>cd code\xgboost\python-package
The point is to move to the python-package directory of XGBoost. Then type:
[Anaconda3] C:\Users\IBM_ADMIN\code\xgboost\python-package>python setup.py install
We are almost done. Let's launch a notebook to test XGBoost.
Importing it directly causes an error. In order to avoid it we must
add the path to the g++ runtime libraries to the os environment path
variable with:
import os
mingw_path = 'C:\\Program Files\\mingw-w64\\x86_64-5.3.0-posix-seh-rt_v4-rev0\\mingw64\\bin'
os.environ['PATH'] = mingw_path + ';' + os.environ['PATH']
We can then import xgboost and run a small example.
import xgboost as xgb
import numpy as np
data = np.random.rand(5,10) # 5 entities, each contains 10 features
label = np.random.randint(2, size=5) # binary target
dtrain = xgb.DMatrix( data, label=label)
dtest = dtrain
param = {'bst:max_depth':2, 'bst:eta':1, 'silent':1, 'objective':'binary:logistic' }
param['nthread'] = 4
param['eval_metric'] = 'auc'
evallist = [(dtest,'eval'), (dtrain,'train')]
num_round = 10
bst = xgb.train( param, dtrain, num_round, evallist )
bst.dump_model('dump.raw.txt')
We are all set!

I'm able to install using the following commands (in Windows 10) :
conda install -c mikesilva xgboost
conda install -c conda-forge xgboost

GUYS ITS NOT THAT EASY:-
PLEASE FOLLOW BELOW STEP TO GET TO MARK
So here's what I did to finish a 64-bit build on Windows:
Download and install MinGW-64: sourceforge.net /projects/mingw-w64/
On the first screen of the install prompt make sure you set the Architecture to x86_64 and the Threads to win32
I installed to C:\mingw64 (to avoid spaces in the file path) so I added this to my PATH environment variable: C:\ mingw64 \ mingw64 \ bin(Please remove spaces)
I also noticed that the make utility that is included in bin\mingw64 is called mingw32-make so to simplify things I just renamed this to make
Open a Windows command prompt and type gcc. You should see something like "fatal error: no input file"
Next type make. You should see something like "No targets specified and no makefile found"
Type git. If you don't have git, install it and add it to your PATH.
These should be all the tools you need to build the xgboost project. To get the source code run these lines:
cd c:\
git clone --recursive https://github.com/dmlc/xgboost
cd xgboost
git submodule init
git submodule update
cp make/mingw64.mk config.mk
make -j4
Note that I ran this part from a Cygwin shell. If you are using the Windows command prompt you should be able to change cp to copy and arrive at the same result. However, if the build fails on you for any reason I would recommend trying again using cygwin.
If the build finishes successfully, you should have a file called xgboost.exe located in the project root. To install the Python package, do the following:
cd python-package
python setup.py install
Now you should be good to go. Open up Python, and you can import the package with:
import xgboost as xgb
To test the installation, I went ahead and ran the basic_walkthrough.py file that was included in the demo/guide-python folder of the project and didn't get any errors.

if you found an issue when you try to import xgboost (my case it is Windows 10 and anaconda spyder) do the following:
Click on the windows icon (start button!)
Select and expand the anaconda folder
Run the Anaconda Prompt (as Administrator)
Type the following command as it is mentioned in https://anaconda.org/anaconda/py-xgboost
conda install -c anaconda py-xgboost
That's all...Good luck.

You can download the xgboost package to your local computer, and you better place the xgboost source file under D:\ or C:\ (ps: download address: http://www.lfd.uci.edu/~gohlke/pythonlibs/#xgboost, and select "xgboost-0.6-cp35-cp35m-win_amd64.whl",but it is up to your operation system), and you open the Anaconda prompt, type in pip install D:\xgboost-0.6-cp35-cp35m-win_amd64.whl, then you can successful install xgboost into your anaconda

Try running this on Anaconda prompt
pip install xgboost
This worked for me on Spyder with Python 3.5

I figured out easy way to install XgBoost by mix of what is mentioned here.
Step 1:
Install gitbash from here and start gitbash.
Step 2: git clone --recursive https://github.com/dmlc/xgboost
Step 3: git submodule init
git submodule update
step 4: alias make='mingw32-make'
step 5: cp make/mingw64.mk config.mk; make -j4
step 6: Goto Anaconda prompt and if you have a conda environment then activate that environment like my was py35 so I activate it by typing activate py35
cd python-package
python setup.py install
step 7: setup the Path in system environment variable to the path where you installed xgboost/python-package.

Use this in your conda prompt:
python -m pip install xgboost

The following worked for me:
conda install libxgboost

The package directory states that xgboost is unstable for windows and is disabled:
pip installation on windows is currently disabled for further invesigation, please install from github.
https://pypi.python.org/pypi/xgboost/

Anaconda3 version 4.4.0check image
Go to Anaconda -> Environments -> from the dropdown select not installed -> If you can see xgboost pr Py-xgboost select and click apply.

There are a lot of dependencies of anaconda that have changed over the past years and won't work if you used them now. Some of the answers need serious updation.
I found this command did the job for me :
conda install -c conda-forge xgboost
You may also want to look at the official documentation of anaconda for xgboost:
https://anaconda.org/conda-forge/xgboost

I have used this command and it worked for me.
import sys
!{sys.executable} -m pip install xgboost

Open anaconda prompt and run
pip install xgboost

You can install it using pip:
pip3 install --default-timeout=100 xgboost

This simple helped me you don't have to include anything at the end because if you include something, some of your packages will be upgraded but some will be downgraded.
You can get this from this url: https://anaconda.org/anaconda/py-xgboost
conda install -c anaconda py-xgboost

Look here https://github.com/Rafi993/xgboost/ for building xgboost on your machine. There are many different varieties of the solution above, but it seems that the version in the link above is the good one. At least that worked for me: I've tested it on Windows 7 and Windows Server 2008.
Then run the following commands in cmd in order to install python bindings:
cd python-package
python setup.py install
You might also need a proper mingw (google for tdm-gcc)
and the latest setuptools from anaconda.
I hope it will help

Tensorflow and Anaconda on Ubuntu?

On my Ubuntu 14.04, I have installed tensorflow, using "pip", as specified in the Tensorflow Installation instructions and I made sure it was working by importing it in python and it did work.
Then, I installed Anaconda and it changed my .bashrc file by adding the following line to it:
export PATH="/home/sonny/anaconda2/bin:$PATH"
But because of this change, now it looks into the PATH above, which doesn't contain tensorflow. now I can't import tensorflow in my python code.
What is the proper way to extend the $PATH environment variable so that it stays using everything from anaconda2 but it becomes able to import "tensorflow"?

I solved the problem but in a different way!
I found a link where the tensorflow.whl files were converted to conda packages, so I went ahead and installed it using the command:
conda install -c https://conda.anaconda.org/jjhelmus tensorflow
and it worked, since the $PATH points to anaconda packages, I can import it now!
Source is here

Since v0.10.0, tensorflow is a community maintained conda package in the conda-forge channel. Hence, it can be installed directly with the following command:
conda install -c conda-forge tensorflow
The instructions on the TensorFlow documentation has also been updated.
To facilitate future updates, it is probably a good idea to add conda-forge channel into your conda config:
conda config --add channels conda-forge
In fact, tensorflow=0.10.0rc0 was recently added onto the Anaconda default channel and will be installed instead if the conda-forge channel is not specified:
conda install tensorflow

I had the same problem and decided it was easiest to start over, install Anaconda first and then TensorFlow after that.

I suspect that pip is giving you a TensorFlow installation in cpython, not anaconda.
How about a virtualenv?
# Create env
$ virtualenv --python=/path/to/anaconda /path/to/your/env
# Activate env
$ source /path/to/your/env/bin/activate
# Install Tensorflow
$ pip install https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-0.5.0-cp27-none-linux_x86_64.whl

Install tensorflow from the following command. Conda will take care of the installation process.
conda install -c conda-forge tensorflow

I solved the problem using this:
conda create --name=tensorenv python=3.4
source activate tensorenv

Actually, the TensorFlow Official website made every detail of installing.
The Operation System Windows, Mac OS, Ubuntu; the environment with GPU or just CPU, every single detail of problems you may come up with.
Check this out
Installing TensorFlow on Ubuntu with Anaconda
you will not regret.
Once you visit that you may also find like
Installing TensorFlow on Windows with Anaconda