- How to change python packages directory
- 2 Answers 2
- Linked
- Related
- Hot Network Questions
- Subscribe to RSS
- Installing Packages¶
- Requirements for Installing Packages¶
- Ensure you can run Python from the command line¶
- Ensure you can run pip from the command line¶
- Ensure pip, setuptools, and wheel are up to date¶
- Optionally, create a virtual environment¶
- Creating Virtual Environments¶
- How do I find the location of my Python site-packages directory
- Join the world’s most active Tech Community!
- Welcome back to the World’s most active Tech Community!
- Subscribe to our Newsletter, and get personalized recommendations.
- TRENDING CERTIFICATION COURSES
- TRENDING MASTERS COURSES
- COMPANY
- WORK WITH US
- DOWNLOAD APP
- CATEGORIES
- CATEGORIES
How to change python packages directory
I’m using Ubuntu 14.04. I manually installed Python 2.7.9 with this file. But now, site.getsitepackages() method shows like bellow. And I can’t import any installed modules.
>>> import site; site.getsitepackages() ['/usr/local/lib/python2.7/site-packages', '/usr/local/lib/site-python']
The sub-directories must be named «dist-packages» on Ubuntu instead of «site-packages». How can I fix this?
2 Answers 2
A quick solution would be to rename the directories or create a symbolic link:
$ ln -s /usr/local/lib/python2.7/site-packages /usr/local/lib/python2.7/dist-packages
I noticed that was not enogh to solve the problem. In that case, a conflict error will occur like «undefined symbol: PyUnicodeUCS4_FromWideChar». It happens because the Python I run with is not the same Python I built with, and they have different unicode build settings.
if you installed setuptools and pip through apt-get, sitepackages will be installed to the dist-packages directory(see this answer).
In this case, the build-in Python and the manually installed Python can have different unicode build settings.
To avoid this conflict problem, I must install setuptools manually through the manually installed Python. Don’t use apt-get to install anything related to the Ubuntu build-in Python.
Linked
Related
Hot Network Questions
Subscribe to RSS
To subscribe to this RSS feed, copy and paste this URL into your RSS reader.
Site design / logo © 2023 Stack Exchange Inc; user contributions licensed under CC BY-SA . rev 2023.7.14.43533
By clicking “Accept all cookies”, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy.
Installing Packages¶
This section covers the basics of how to install Python packages .
It’s important to note that the term “package” in this context is being used to describe a bundle of software to be installed (i.e. as a synonym for a distribution ). It does not to refer to the kind of package that you import in your Python source code (i.e. a container of modules). It is common in the Python community to refer to a distribution using the term “package”. Using the term “distribution” is often not preferred, because it can easily be confused with a Linux distribution, or another larger software distribution like Python itself.
Requirements for Installing Packages¶
This section describes the steps to follow before installing other Python packages.
Ensure you can run Python from the command line¶
Before you go any further, make sure you have Python and that the expected version is available from your command line. You can check this by running:
You should get some output like Python 3.6.3 . If you do not have Python, please install the latest 3.x version from python.org or refer to the Installing Python section of the Hitchhiker’s Guide to Python.
If you’re a newcomer and you get an error like this:
>>> python3 --version Traceback (most recent call last): File "", line 1, in NameError: name 'python3' is not defined
It’s because this command and other suggested commands in this tutorial are intended to be run in a shell (also called a terminal or console). See the Python for Beginners getting started tutorial for an introduction to using your operating system’s shell and interacting with Python.
If you’re using an enhanced shell like IPython or the Jupyter notebook, you can run system commands like those in this tutorial by prefacing them with a ! character:
In [1]: import sys ! --version Python 3.6.3
It’s recommended to write rather than plain python in order to ensure that commands are run in the Python installation matching the currently running notebook (which may not be the same Python installation that the python command refers to).
Due to the way most Linux distributions are handling the Python 3 migration, Linux users using the system Python without creating a virtual environment first should replace the python command in this tutorial with python3 and the python -m pip command with python3 -m pip —user . Do not run any of the commands in this tutorial with sudo : if you get a permissions error, come back to the section on creating virtual environments, set one up, and then continue with the tutorial as written.
Ensure you can run pip from the command line¶
Additionally, you’ll need to make sure you have pip available. You can check this by running:
If you installed Python from source, with an installer from python.org, or via Homebrew you should already have pip. If you’re on Linux and installed using your OS package manager, you may have to install pip separately, see Installing pip/setuptools/wheel with Linux Package Managers .
If pip isn’t already installed, then first try to bootstrap it from the standard library:
python3 -m ensurepip --default-pip
py -m ensurepip --default-pip
If that still doesn’t allow you to run python -m pip :
- Securely Download get-pip.py1
- Run python get-pip.py . 2 This will install or upgrade pip. Additionally, it will install setuptools and wheel if they’re not installed already.
Warning Be cautious if you’re using a Python install that’s managed by your operating system or another package manager. get-pip.py does not coordinate with those tools, and may leave your system in an inconsistent state. You can use python get-pip.py —prefix=/usr/local/ to install in /usr/local which is designed for locally-installed software.
Ensure pip, setuptools, and wheel are up to date¶
While pip alone is sufficient to install from pre-built binary archives, up to date copies of the setuptools and wheel projects are useful to ensure you can also install from source archives:
python3 -m pip install --upgrade pip setuptools wheel
py -m pip install --upgrade pip setuptools wheel
Optionally, create a virtual environment¶
See section below for details, but here’s the basic venv 3 command to use on a typical Linux system:
python3 -m venv tutorial_env source tutorial_env/bin/activate
py -m venv tutorial_env tutorial_env\Scripts\activate
This will create a new virtual environment in the tutorial_env subdirectory, and configure the current shell to use it as the default python environment.
Creating Virtual Environments¶
Python “Virtual Environments” allow Python packages to be installed in an isolated location for a particular application, rather than being installed globally. If you are looking to safely install global command line tools, see Installing stand alone command line tools .
Imagine you have an application that needs version 1 of LibFoo, but another application requires version 2. How can you use both these applications? If you install everything into /usr/lib/python3.6/site-packages (or whatever your platform’s standard location is), it’s easy to end up in a situation where you unintentionally upgrade an application that shouldn’t be upgraded.
Or more generally, what if you want to install an application and leave it be? If an application works, any change in its libraries or the versions of those libraries can break the application.
Also, what if you can’t install packages into the global site-packages directory? For instance, on a shared host.
In all these cases, virtual environments can help you. They have their own installation directories and they don’t share libraries with other virtual environments.
Currently, there are two common tools for creating Python virtual environments:
- venv is available by default in Python 3.3 and later, and installs pip and setuptools into created virtual environments in Python 3.4 and later.
- virtualenv needs to be installed separately, but supports Python 2.7+ and Python 3.3+, and pip , setuptools and wheel are always installed into created virtual environments by default (regardless of Python version).
The basic usage is like so:
python3 -m venv source /bin/activate
How do I find the location of my Python site-packages directory
- All categories
- ChatGPT (11)
- Apache Kafka (84)
- Apache Spark (596)
- Azure (145)
- Big Data Hadoop (1,907)
- Blockchain (1,673)
- C# (141)
- C++ (271)
- Career Counselling (1,060)
- Cloud Computing (3,469)
- Cyber Security & Ethical Hacking (162)
- Data Analytics (1,266)
- Database (855)
- Data Science (76)
- DevOps & Agile (3,608)
- Digital Marketing (111)
- Events & Trending Topics (28)
- IoT (Internet of Things) (387)
- Java (1,247)
- Kotlin (8)
- Linux Administration (389)
- Machine Learning (337)
- MicroStrategy (6)
- PMP (423)
- Power BI (516)
- Python (3,193)
- RPA (650)
- SalesForce (92)
- Selenium (1,569)
- Software Testing (56)
- Tableau (608)
- Talend (73)
- TypeSript (124)
- Web Development (3,002)
- Ask us Anything! (66)
- Others (2,231)
- Mobile Development (395)
- UI UX Design (24)
Join the world’s most active Tech Community!
Welcome back to the World’s most active Tech Community!
Subscribe to our Newsletter, and get personalized recommendations.
Sign up with Google Signup with Facebook
Thank you for registering Join Edureka Meetup community for 100+ Free Webinars each month JOIN MEETUP GROUP
TRENDING CERTIFICATION COURSES
- DevOps Certification Training
- AWS Architect Certification Training
- Big Data Hadoop Certification Training
- Tableau Training & Certification
- Python Certification Training for Data Science
- Selenium Certification Training
- PMP® Certification Exam Training
- Robotic Process Automation Training using UiPath
- Apache Spark and Scala Certification Training
- Microsoft Power BI Training
- Online Java Course and Training
- Python Certification Course
TRENDING MASTERS COURSES
- Data Scientist Masters Program
- DevOps Engineer Masters Program
- Cloud Architect Masters Program
- Big Data Architect Masters Program
- Machine Learning Engineer Masters Program
- Full Stack Web Developer Masters Program
- Business Intelligence Masters Program
- Data Analyst Masters Program
- Test Automation Engineer Masters Program
- Post-Graduate Program in Artificial Intelligence & Machine Learning
- Post-Graduate Program in Big Data Engineering
COMPANY
WORK WITH US
DOWNLOAD APP
CATEGORIES
CATEGORIES
- Cloud Computing
- DevOps
- Big Data
- Data Science
- BI and Visualization
- Programming & Frameworks
- Software Testing © 2023 Brain4ce Education Solutions Pvt. Ltd. All rights Reserved. Terms & ConditionsLegal & Privacy