Pip install xgboost error

root@0c6c17725a7b:/# pip install xgboost Downloading/unpacking xgboost Could not find a version that satisfies the requirement xgboost (from versions: 0.4a12, 0.4a13) Cleaning up... No distribution...

The stackoverflow suggestion of —pre produced this:

ubuntu@ip-172-31-11-169:~$ sudo pip install —pre xgboost
Downloading/unpacking xgboost
Downloading xgboost-0.4a13.tar.gz (690kB): 690kB downloaded
Running setup.py (path:/tmp/pip_build_root/xgboost/setup.py) egg_info for package xgboost
xgboost/build-python.sh: 13: xgboost/build-python.sh: pushd: not found
make: *** No rule to make target python'. Stop. ----------------------------- Building multi-thread xgboost failed Start to build single-thread xgboost make: *** No rule to make targetclean’. Stop.
make: *** No rule to make target `python’. Stop.
Successfully build single-thread xgboost
If you want multi-threaded version
See additional instructions in doc/build.md
xgboost/build-python.sh: 26: xgboost/build-python.sh: popd: not found
(None, None)
Traceback (most recent call last):
File «», line 17, in
File «/tmp/pip_build_root/xgboost/setup.py», line 20, in
import xgboost
File «./xgboost/init.py», line 8, in
from .core import DMatrix, Booster
File «./xgboost/core.py», line 78, in
_LIB = _load_lib()
File «./xgboost/core.py», line 72, in _load_lib
lib = ctypes.cdll.LoadLibrary(lib_path[0])
File «/usr/lib/python2.7/ctypes/init.py», line 443, in LoadLibrary
return self._dlltype(name)
File «/usr/lib/python2.7/ctypes/init.py», line 365, in init
self._handle = _dlopen(self._name, mode)
OSError: /tmp/pip_build_root/xgboost/xgboost/./wrapper/libxgboostwrapper.so: invalid ELF header
Complete output from command python setup.py egg_info:
xgboost/build-python.sh: 13: xgboost/build-python.sh: pushd: not found

make: *** No rule to make target `python’. Stop.

Building multi-thread xgboost failed

Start to build single-thread xgboost

make: *** No rule to make target `clean’. Stop.

make: *** No rule to make target `python’. Stop.

Successfully build single-thread xgboost

If you want multi-threaded version

See additional instructions in doc/build.md

xgboost/build-python.sh: 26: xgboost/build-python.sh: popd: not found

(None, None)

Traceback (most recent call last):

File «», line 17, in

File «/tmp/pip_build_root/xgboost/setup.py», line 20, in

File «./xgboost/init.py», line 8, in 

from .core import DMatrix, Booster

File «./xgboost/core.py», line 78, in

File «./xgboost/core.py», line 72, in _load_lib

lib = ctypes.cdll.LoadLibrary(lib_path[0])

File «/usr/lib/python2.7/ctypes/init.py», line 443, in LoadLibrary

return self._dlltype(name)

File «/usr/lib/python2.7/ctypes/init.py», line 365, in init

self._handle = _dlopen(self._name, mode)

OSError: /tmp/pip_build_root/xgboost/xgboost/./wrapper/libxgboostwrapper.so: invalid ELF header

Cleaning up…
Command python setup.py egg_info failed with error code 1 in /tmp/pip_build_root/xgboost
Storing debug log for failure in /home/ubuntu/.pip/pip.log
ubuntu@ip-172-31-11-169:~$

Источник

Содержание

  1. [Solved] ImportError: No module named xgboost
  2. How ImportError: No module named xgboost Error Occurs?
  3. How To Solve ImportError: No module named xgboost Error ?
  4. Solution 1: install xgboost from pip
  5. Solution 2: Use conda install in Anaconda
  6. Solution 3: install the whl file directly
  7. Solution 4: Use this
  8. Summary
  9. ModuleNotFoundError: No module named xgboost, simple fix!
  10. ModuleNotFoundError: No module named xgboost
  11. Are you installing packages using Conda or Pip package manager?
  12. Upgrade or install pip for Python
  13. Upgrade or install xgboost package via Conda or Pip
  14. Activate Conda or venv Python environment
  15. Create a new Conda or venv Python environment with xgboost installed
  16. Upgrade Jupyter Notebook package in Conda or Pip
  17. Best practices for managing Python packages and environments
  18. References
  19. Stephen Allwright Twitter
  20. Fit Predict Newsletter
  21. Fit Predict Newsletter

[Solved] ImportError: No module named xgboost

Hello Guys, How are you all? Hope You all Are Fine. Today I am trying to import xgboost but I am facing following error ImportError: No module named xgboost in Python. So Here I am Explain to you all the possible solutions here.

Without wasting your time, Let’s start This Article to Solve This Error.

How ImportError: No module named xgboost Error Occurs?

I am trying to import xgboost but I am facing following error.

How To Solve ImportError: No module named xgboost Error ?

  1. How To Solve ImportError: No module named xgboost Error ?

To Solve ImportError: No module named xgboost Error You just need to properly install xgboost from pip. So Just Open terminal and run this command: pip install xgboost. Second solution is Just Use conda install in Anaconda and then use pip install: conda install -c conda-forge xgboost and then pip install xgboost.

ImportError: No module named xgboost

To Solve ImportError: No module named xgboost Error You just need to properly install xgboost from pip. So Just Open terminal and run this command: pip install xgboost. Second solution is Just Use conda install in Anaconda and then use pip install: conda install -c conda-forge xgboost and then pip install xgboost.

Solution 1: install xgboost from pip

You just need to properly install xgboost from pip. So Just Open terminal and run this command.

Solution 2: Use conda install in Anaconda

Just Use conda install in Anaconda and then use pip install.

Solution 3: install the whl file directly

Just need to Install the whl file directly.

  1. First of all download and install the whl file directly from here.
  2. just double click on the whl file and install it.
  3. And then run this command.
  4. pip install yourFile.whl(Your filename here)
  5. Now, your error should be fixed.

Solution 4: Use this

Summary

It’s all About this issue. Hope all solution helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which solution worked for you?

Источник

ModuleNotFoundError: No module named xgboost, simple fix!

The error “ModuleNotFoundError: No module named xgboost» is a common error experienced by data scientists when developing in Python. The error is likely an environment issue whereby the xgboost package has not been installed correctly on your machine.

The error “ModuleNotFoundError: No module named xgboost» is a common error experienced by data scientists when developing in Python. The error is likely an environment issue whereby the xgboost package has not been installed correctly on your machine, thankfully there are a few simple steps to go through to troubleshoot the problem and find a solution.

ModuleNotFoundError: No module named xgboost

Your error, whether in a Jupyter Notebook or in the terminal, probably looks like one of the following:

No module named ‘xgboost’
ModuleNotFoundError: No module named ‘xgboost’

In order to find the root cause of the problem we will go through the following potential fixes:

  1. Upgrade pip version
  2. Upgrade or install xgboost package
  3. Check if you are activating the environment before running
  4. Create a fresh environment
  5. Upgrade or install Jupyer Notebook package

Are you installing packages using Conda or Pip package manager?

It is common for developers to use either Pip or Conda for their Python package management. It’s important to know what you are using before we continue with the fix.

If you have not explicitly installed and activated Conda, then you are almost definitely going to be using Pip. One sanity check is to run conda info in your terminal, which if it returns anything likely means you are using Conda.

Upgrade or install pip for Python

First things first, let’s check to see if we have the up to date version of pip installed. We can do this by running:

Upgrade or install xgboost package via Conda or Pip

The most common reason for this error is that the xgboost package is not installed in your environment or an outdated version is installed. So let’s update the package or install it if it’s missing.

Activate Conda or venv Python environment

It is highly recommended that you use isolated environments when developing in Python. Because of this, one common mistake developers make is that they don’t activate the correct environment before they run the Python script or Jupyter Notebook. So, let’s make sure you have your correct environment running.

For virtual environments:

Create a new Conda or venv Python environment with xgboost installed

During the development process, a developer will likely install and update many different packages in their Python environment, which can over time cause conflicts and errors.

Therefore, one way to solve the module error for xgboost is to simply create a new environment with only the packages that you require, removing all of the bloatware that has built up over time. This will provide you with a fresh start and should get rid of problems that installing other packages may have caused.

For virtual environments:

Upgrade Jupyter Notebook package in Conda or Pip

If you are working within a Jupyter Notebook and none of the above has worked for you, then it could be that your installation of Jupyter Notebooks is faulty in some way, so a reinstallation may be in order.

Best practices for managing Python packages and environments

Managing packages and environments in Python is notoriously problematic, but there are some best practices which should help you to avoid package the majority of problems in the future:

  1. Always use separate environments for your projects and avoid installing packages to your root environment
  2. Only install the packages you need for your project
  3. Pin your package versions in your project’s requirements file
  4. Make sure your package manager is kept up to date

References

Stephen Allwright Twitter

I’m a Data Scientist currently working for Oda, an online grocery retailer, in Oslo, Norway. These posts are my way of sharing some of the tips and tricks I’ve picked up along the way.

Fit Predict Newsletter

The simple weekly roundup of all the latest news, tools, packages, and use cases from the world of Data Science 📥

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The simple weekly roundup of all the latest news, tools, packages, and use cases from the world of Data Science 📥

Want to have a read before you subscribe? See the archive here

Источник

Источник

Hello Guys, How are you all? Hope You all Are Fine. Today I am trying to import xgboost but I am facing following error ImportError: No module named xgboost in Python. So Here I am Explain to you all the possible solutions here.

Without wasting your time, Let’s start This Article to Solve This Error.

Contents

  1. How ImportError: No module named xgboost Error Occurs?
  2. How To Solve ImportError: No module named xgboost Error ?
  3. Solution 1: install xgboost from pip
  4. Solution 2: Use conda install in Anaconda
  5. Solution 3: install the whl file directly
  6. Solution 4: Use this
  7. Summary

How ImportError: No module named xgboost Error Occurs?

I am trying to import xgboost but I am facing following error.

ImportError: No module named xgboost

How To Solve ImportError: No module named xgboost Error ?

  1. How To Solve ImportError: No module named xgboost Error ?

    To Solve ImportError: No module named xgboost Error You just need to properly install xgboost from pip. So Just Open terminal and run this command: pip install xgboost. Second solution is Just Use conda install in Anaconda and then use pip install: conda install -c conda-forge xgboost and then pip install xgboost.

  2. ImportError: No module named xgboost

    To Solve ImportError: No module named xgboost Error You just need to properly install xgboost from pip. So Just Open terminal and run this command: pip install xgboost. Second solution is Just Use conda install in Anaconda and then use pip install: conda install -c conda-forge xgboost and then pip install xgboost.

Solution 1: install xgboost from pip

You just need to properly install xgboost from pip. So Just Open terminal and run this command.

pip install xgboost

Solution 2: Use conda install in Anaconda

Just Use conda install in Anaconda and then use pip install.

conda install -c conda-forge xgboost

Then

pip install xgboost

Solution 3: install the whl file directly

Just need to Install the whl file directly.

  1. First of all download and install the whl file directly from here.
  2. just double click on the whl file and install it.
  3. And then run this command.
  4. pip install yourFile.whl (Your filename here)
  5. Now, your error should be fixed.

Solution 4: Use this

git clone --recursive https://github.com/dmlc/xgboost
cd xgboost
sudo cp make/minimum.mk ./config.mk;
sudo make -j4;
sh build.sh
cd python-package
python setup.py install

Summary

It’s all About this issue. Hope all solution helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which solution worked for you?

Also, Read

  • ImportError: No module named google.protobuf

Источник

When I installed xgboost package using «Alteryx.installPackages(«xgboost==0.71») in Python tool, but it show the following error,   it looks like the package has been located,  but «No files/directories in C:UsersWilburAppDataLocalTemppip-build-t1k7mi6fxgboostpip-egg-info (from PKG-INFO)»

what does it mean？  how to fix it?   thanks.

---------------------------------------------------------------------------
CalledProcessError                        Traceback (most recent call last)
<ipython-input-2-2ec7b7fa4742> in <module>
      1 from ayx import Alteryx
----> 2 Alteryx.installPackages("xgboost==0.71")
      3 
      4 # First XGBoost model for Pima Indians dataset
      5 from numpy import loadtxt

c:program filesalteryxbinminiconda3pythontool_venvlibsite-packagesayxexport.py in installPackage(package, install_type, debug, **kwargs)
    151     This function will install a package or list of packages into the virtual environment used by the Python tool. If using an admin installation of Alteryx, you must run Alteryx as administrator in order to use this function and install packages.
    152     """
--> 153     __installPackages__(package, install_type=install_type, debug=debug, **kwargs)
    154 
    155 

c:program filesalteryxbinminiconda3pythontool_venvlibsite-packagesayxPackage.py in installPackages(package, install_type, debug)
    112     print(pip_install_result['msg'])
    113     if not pip_install_result['success']:
--> 114         raise pip_install_result['err']

c:program filesalteryxbinminiconda3pythontool_venvlibsite-packagesayxUtils.py in runSubprocess(args_list, debug)
     39         result = subprocess.check_output(
     40             args_list,
---> 41             stderr = subprocess.STDOUT
     42             )
     43         if debug:

C:Program FilesAlteryxbinMiniconda3libsubprocess.py in check_output(timeout, *popenargs, **kwargs)
    334 
    335     return run(*popenargs, stdout=PIPE, timeout=timeout, check=True,
--> 336                **kwargs).stdout    337 
    338 

C:Program FilesAlteryxbinMiniconda3libsubprocess.py in run(input, timeout, check, *popenargs, **kwargs)
    416         if check and retcode:
    417             raise CalledProcessError(retcode, process.args,
--> 418                                      output=stdout, stderr=stderr)    419     return CompletedProcess(process.args, retcode, stdout, stderr)
    420 

CalledProcessError: Command '['c:\program files\alteryx\bin\miniconda3\pythontool_venv\scripts\python.exe', '-m', 'pip', 'install', 'xgboost==0.71']' returned non-zero exit status 1.
Источник

The error “ModuleNotFoundError: No module named xgboost» is a common error experienced by data scientists when developing in Python. The error is likely an environment issue whereby the xgboost package has not been installed correctly on your machine, thankfully there are a few simple steps to go through to troubleshoot the problem and find a solution.

Your error, whether in a Jupyter Notebook or in the terminal, probably looks like one of the following:

No module named 'xgboost'
ModuleNotFoundError: No module named 'xgboost'

In order to find the root cause of the problem we will go through the following potential fixes:

  1. Upgrade pip version
  2. Upgrade or install xgboost package
  3. Check if you are activating the environment before running
  4. Create a fresh environment
  5. Upgrade or install Jupyer Notebook package

Are you installing packages using Conda or Pip package manager?

It is common for developers to use either Pip or Conda for their Python package management. It’s important to know what you are using before we continue with the fix.

If you have not explicitly installed and activated Conda, then you are almost definitely going to be using Pip. One sanity check is to run conda info in your terminal, which if it returns anything likely means you are using Conda.

Upgrade or install pip for Python

First things first, let’s check to see if we have the up to date version of pip installed. We can do this by running:

pip install --upgrade pip

Upgrade or install xgboost package via Conda or Pip

The most common reason for this error is that the xgboost package is not installed in your environment or an outdated version is installed. So let’s update the package or install it if it’s missing.

For Conda:

# To install in the root environment 
conda install -c conda-forge xgboost 

# To install in a specific environment 
conda install -n MY_ENV xgboost

For Pip:‌

# To install in the root environment
python3 -m pip install -U xgboost

# To install in a specific environment
source MY_ENV/bin/activate
python3 -m pip install -U xgboost

Activate Conda or venv Python environment

It is highly recommended that you use isolated environments when developing in Python. Because of this, one common mistake developers make is that they don’t activate the correct environment before they run the Python script or Jupyter Notebook. So, let’s make sure you have your correct environment running.

For Conda:

conda activate MY_ENV

For virtual environments:

source MY_ENV/bin/activate

Create a new Conda or venv Python environment with xgboost installed

During the development process, a developer will likely install and update many different packages in their Python environment, which can over time cause conflicts and errors.

Therefore, one way to solve the module error for xgboost is to simply create a new environment with only the packages that you require, removing all of the bloatware that has built up over time. This will provide you with a fresh start and should get rid of problems that installing other packages may have caused.

For Conda:

# Create the new environment with the desired packages
conda create -n MY_ENV python=3.9 xgboost 

# Activate the new environment 
conda activate MY_ENV 

# Check to see if the packages you require are installed 
conda list

For virtual environments:

# Navigate to your project directory 
cd MY_PROJECT 

# Create the new environment in this directory 
python3 -m venv MY_ENV 

# Activate the environment 
source MY_ENV/bin/activate 

# Install xgboost 
python3 -m pip install xgboost

Upgrade Jupyter Notebook package in Conda or Pip

If you are working within a Jupyter Notebook and none of the above has worked for you, then it could be that your installation of Jupyter Notebooks is faulty in some way, so a reinstallation may be in order.

For Conda:

conda update jupyter

For Pip:

pip install -U jupyter

Best practices for managing Python packages and environments

Managing packages and environments in Python is notoriously problematic, but there are some best practices which should help you to avoid package the majority of problems in the future:

  1. Always use separate environments for your projects and avoid installing packages to your root environment
  2. Only install the packages you need for your project
  3. Pin your package versions in your project’s requirements file
  4. Make sure your package manager is kept up to date

References

Conda managing environments documentation
Python venv documentation

Источник

The Reason for modulenotfounderror: no module named ‘xgboost’ is either xgboost is not installed or misconfigured in the system. The best way to fix this error is to reinstall this xgboost python module. Since most of the Machine Learning Algorithm come in a bundle all together for example scikit-learn. But that is not the case with XGBOOST. For this package, we need to externally install this.

In this article, we will understand the best and quick ways to install the xgboost module. We will also explore a bit on XGBOOST importance and brief usages to give you the complete depth of this error.

As we have already discussed that the installation of XGBOOST is the best solution for this modulenotfounderror so let’s see with real code and command in this section.

Solution 1: Using pip package manager –

pip is the easiest and best way to install this XGBOOST module. Here is the command for installation (pip should be in the system )

pip install xgboost

pip install xgboost

pip install xgboost

Solution 2: Using Anaconda to install XGBOOST –

Just like pip, The Anaconda distribution for scientific python libraries is quite convenient. Under Anaconda there is conda package manager ( similar to pip ). Under the same, Please use the below command to install XGBOOST.

conda install -c conda-forge xgboost

modulenotfounderror no module named 'xgboost' fix

modulenotfounderror no module named ‘xgboost’ fix

Solution 3: Using source code setup file –

This is the longest path but it gives a deeper version for XGBOOST. Let me make you understand with one small scenario, Suppose there is a fix in the XGBOOST package dev branch but unfortunately it is not officially moved to master or any stable branch. In this case above two methods will not be sufficient. You have to go with this path.

git clone --recursive https://github.com/dmlc/xgboost
git submodule init
git submodule update
alias make='mingw32-make'
cp make/mingw64.mk config.mk; make -j4
cd xgboostpython-package  
python setup.py install

Solution 4 : Using Whl file –

Whl is a packaging extension of Python. Use the XGBOOST whl and install the same using the below command.

pip install downloaded.whl

Thanks
Data Science Learner Team

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