I am new to python just a few weeks back i started using python(Classic Noob-Disclaimer)
Now whenever i install a module by copying the unzipped folder in site-packages under Lib and running the source install by using "c:\python27\lib\site-packages\tweepy-1.2\setup.py install" in command prompt it installs without any errors.
But now when i make a python script (*.py)
and store it on the desktop it wont work
and it gives out an error "No module found"
but when i store it in the same folder as the source it works perfectly.
also if i open the IDLE GUI it also returns the same error.
But this doesnt happen with the win32com module which i use for TTS.
I missing something..but i cudnt find the answer to it.
Plz help me!
i need to use many of these modules..they work great differently but not together as the modules are always missing!
Copying an unzipped folder to site-packages does not install a Python package.
To install manually, unzip the package to a temporary directory, then run:
python setup.py install
in this directory, after that you can remove the directory.
To download and install a pure Python package automatically, run:
pip install tweepy
if you have pip installed.
The simplest way to install Python packages that have C extensions is to use binary installers (*.exe, *.msi files).
To avoid all this use VirtualEnv
Virtualenv is a tool to create isolated Python environments.
The basic problem being addressed is one of dependencies and versions, and indirectly permissions. 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/python2.7/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.
The easiest way to install python packages is by using pip. First you need to install pip as explained here if you use windows. Then you can query some packages, from command line, for example
> pip search twitter
Then to install certain packages, just use pip something like this:
> pip install tweepy
Related
I have a Windows 7 machine running Python 3.8.5 with a very large number of physics/electronics/data analysis/simulation packages. As it turned out, I must have - for some inexplicable reason - installed the 32-bit version of Python instead of the 64-bit one despite having a 64-bit system. And I didn't notice until very recently when I was trying to install some packages that require 64-bit Python. Hence I've now downloaded and installed the latest Python version that is supported by Windows 7, which seems to be 3.8.10.
Question: What is the easiest and also fail-safe way to reinstall all the user packages - that I currently have under 3.8.5 - to 3.8.10?
For some reason, I couldn't find any "canonical" solution for this online. As it seems, Python does not come with any built-in support for updating or system migration and I'm honestly wondering why...
Anyway, my first idea was to get a list of all user (= "local"?) packages currently installed under 3.8.5, but I don't know how. Reason: Doing help('modules') inside the interpreter will list all packages and I don't see a way to "selectively apply" pip to a specific Python version, e.g. something like python-3.8.5 -m pip list --local is not supported.
After getting a list of the user packages, I was thinking to pack it into a batch command pip install package_1 package_2 <...> package_N, thus reinstalling everything to Python 3.8.10. And afterwards uninstalling Python 3.8.5 and removing all environment variables from system PATH.
Is this the proper way to do this?
Anyway, my first idea was to get a list of all user (= "local"?) packages currently installed under 3.8.5, but I don't know how.
Create a list of installed packages with pip freeze > pkglist.txt or pip list --format=freeze. If you already have one, that's great.
Then uninstall 32-bit Python 3.8.5 and clean your path for all Python related variables. Now, install 64-bit Python 3.8.10.
After reinstalling, you can install back all the packages with pip install -r pkglist.txt and it will restore the exact versions of the packages.
If you insist on having both 32-bit and 64-bit versions installed and also have the Python Launcher installed, you could invoke 32 and 64 bit versions separately with py -3.8-64 -m pip and py -3.8-32 -m pip.
I don't see a way to "selectively apply" pip to a specific Python version.
This is possible with the Python Launcher on Windows. But only between major/minor versions and not the patch versions according to its help message.
I would also recommend creating a virtual environment this time before installing the packages and leaving the root environment alone. You can create one named venv with just python -m venv venv, activate it with ./venv/Scripts/activate and proceed with the installation of packages.
Nope, doesn't work. After installing the packages with the newer Python version in PATH, e.g. Jupyter won't start.
If the Jupyter error persists, you could try pinning packages to their most recent patch/minor versions to update them and yet not break your code.
As a last resort, you could try installing Python 3.10 alongside your current Python installation (without uninstall or editing the PATH) and then installing the absolute latest versions of the packages in a 3.10 virtual environment to see if it works for you. You would invoke the two versions with Py Launcher, e.g. py -3.10 and py -3.8.
If I understood correctly, you have multiple packages like NumPy, pandas etc. installed on your machine, and you want to reinstall them "automatically" on a fresh installation of python.
The method (I use) to perform such an operation is by creating a file named setup.py which includes a list of all the packages.
Bellow, I am attaching an example of such a file I use in one of my projects:
from setuptools import setup, find_packages
setup(
name='surface_quality_tools',
version='0.1',
install_requires=["matplotlib", "psutil", "numpy", "scipy", "pandas", "trimesh", "pyglet", "networkx", "protobuf",
"numpy-stl", "sklearn", "opencv-python", "seaborn", "scikit-image", "flask", "tqdm", "pytest"],
package_data={'': ['*.json']},
packages=find_packages(include=[])
)
to run the installation you should open a command prompt from inside the project directory and run:
pip install -e .
You can find a nice example in this blog page
One common way of handling packages in Python is via virtual environments. You can use Anaconda (conda), venv or any of several other solutions. For example, see this post:
https://towardsdatascience.com/virtual-environments-104c62d48c54#:~:text=A%20virtual%20environment%20is%20a,a%20system%2Dwide%20Python).
The way this works in by keeping the Python interpreter separate from the virtual environment that contains all the necessary packages.
Probably the main reason Python doesn't feature migration tools (at least as part of standard library) is because pip - the main package tool - doesn't handle conflict resolution all too well. When you update a version of Python it might so happen (especially with niche packages) that some of them won't work any more and pip often won't be able to solve the dependencies. This is why it's a good idea to keep a separate venv for different Python versions and different projects.
The other tool you could use for easy migration is Docker which is a semi-virtual machine working on top of your host OS and containing usually some linux distribution, Python along with the necessary packages necessary for running and development.
It takes a bit of time to set up a container image initially but afterwards setting everythin on a new machine or in the cloud becomes a breeze.
Listing currently installed packages is done via pip freeze command, the output of which you can then pipe into a file to keep a record of project requirements, for example pip freeze > requirements.txt.
I have pip3, installed via the yum install of python3-pip.
I've done a pip3 global install of some modules I need, but python3 can't find them to import. After a little investigation I see that pip3 installed the modules to /usrlib/python3.6/site-packages/pip/_vendor/
The problem is that python3 doesn't seem to know to look at pip/_vendor, it only finds modules directly installed under site-package. If I just copy the modules from .../site-package/pip/_vendor to .../site-package everything works fine.
The issue doesn't appear to be related to file permissions or ability to read the modules.
I'm wondering how I configure either pip to install directly to site-package or python3 to understand how to look in the pip/_vendor location.
I'm configuring this all with ansible and would like as module an option as possible. For instance I could manually use an argument to tell pip3 to install to the folder I want, but I don't want to hardcode the exact site-package directory if I don't have to.
I recommend starting over with pip by downloading and running get-pip.py. This will not only install the latest version of pip, but it will also install packages to a Python-readable location (the version of Python you use to run get-pip.py).
As an aside, I would avoid installing packages system-wide unless there is a specific need for them. At the very least, you should be installing them as a regular user, and even better you should be using a virtualenv.
Two options in setup.py develop and install are confusing me. According to this site, using develop creates a special link to site-packages directory.
People have suggested that I use python setup.py install for a fresh installation and python setup.py develop after any changes have been made to the setup file.
Can anyone shed some light on the usage of these commands?
python setup.py install is used to install (typically third party) packages that you're not going to develop/modify/debug yourself.
For your own stuff, you want to first install your package and then be able to frequently edit the code without having to re-install the package every time — and that is exactly what python setup.py develop does: it installs the package (typically just a source folder) in a way that allows you to conveniently edit your code after it’s installed to the (virtual) environment, and have the changes take effect immediately.
Note: It is highly recommended to use pip install . (regular install) and pip install -e . (developer install) to install packages, as invoking setup.py directly will do the wrong things for many dependencies, such as pull prereleases and incompatible package versions, or make the package hard to uninstall with pip.
Update:
The develop counterpart for the latest python -m build approach is as follows (as per):
From the documentation. The develop will not install the package but it will create a .egg-link in the deployment directory back to the project source code directory.
So it's like installing but instead of copying to the site-packages it adds a symbolic link (the .egg-link acts as a multiplatform symbolic link).
That way you can edit the source code and see the changes directly without having to reinstall every time that you make a little change. This is useful when you are the developer of that project hence the name develop. If you are just installing someone else's package you should use install
Another thing that people may find useful when using the develop method is the --user option to install without sudo. Ex:
python setup.py develop --user
instead of
sudo python setup.py develop
At work we have python installed, but no additional modules. I want to import some scipy modules but I have no access to the python directory for installation.
Similar questions have been asked on StackOverflow, but the answers always assumed easy install, pip or virtualenv were installed. At my workplace, none of these packages are installed. It's just the plain python installation and nothing else.
Is there still an option for me for installing modules in my local folder and calling them from python? If so, how do I go about it?
Not exactly installing modules on your local folder, but a solution nonetheless:
I used to work for a company that used windows and didn't have admin access, so I ended up using Portable python.
It seems portable python is no longer mantained, but you can see some other portable python solutions on their site, most of which you can run straight from your usb.
You can download pip from here http://pip.readthedocs.org/en/stable/installing/ and install it without root privileges by typing:
python get-pip.py --user
This will install to directory with prefix $HOME/.local so the pip executable will be in the directory $HOME/.local/bin/pip, for your convenience you can add this directory to $PATH by adding to end of .bashrc file this string
export PATH=$HOME/.local/bin/:$PATH
After this you can install any packages by typing
pip install package --user
Or you can alternatively compile the python distribution from source code and install to your home directory to directory $HOME/.local or $HOME/opt or any subfolder of $HOME you prefer, let's call this path $PREFIX. For doing this you have to download python source code from official site, unpack it and then run
./configure --prefix=$PREFIX --enable-shared
make install
And then add python binary to $PATH, python libraries to $LD_LIBRARY_PATH, by adding to the end of $HOME/.bashrc file whit strings
export PATH=$PREFIX/bin:$PATH
export LD_LIBRARY_PATH=$PREFIX/lib
and when after restarting bash you can also run
python get-pip.py
and pip and will be installed automatically to your $PREFIX directory. And all other packages those you will install with pip will be automatically installed also to $PREFIX directory. This way is more involved, but it allows you to have the last version of python.
I would like to figure out a "fool-proof" installation instruction to put in the README of a Python project, call it footools, such that other people in our group can install the newest SVN version of it on their laptops and their server accounts.
The problem is getting the user-installed libs to be used by Python when they call the scripts installed by pip. E.g., we're using a server that has an old version of footools in /opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/.
If I do python2.7 setup.py install --user and run the main entry script, it uses the files in /Users/unhammer/Library/Python/2.7/lib/python/site-packages/. This is what I want, but setup.py alone doesn't install dependencies.
If I (revert the installation and) instead do pip-2.7 install --user . and run the main entry script, it uses the old files in /opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/ – that's not what I want.
If I (revert the installation and) instead do pip-2.7 install --user -e . and run the main entry script, it uses the files in . – that's not what I want, the user should be able to remove the source dir (and be able to svn up without that affecting their install).
I could use (and recommend other people to use) python2.7 setup.py install --user – but then they have to first do
pip-2.7 install -U --user -r requirements.txt -e .
pip-2.7 uninstall -y footools
in order to get the dependencies installed (since pip has no install --only-deps option). That's rather verbose though.
What is setup.py doing that pip is not doing here?
(Edited to make it clear I'm looking for simpler+safer installation instructions.)
Install virtualenvwrapper. I allows setting up separate python environments to alleviate any conflicts you might be having. Here is a tutorial for installing and using virtualenv.
Related:
https://virtualenvwrapper.readthedocs.org/en/latest/
Console scripts generated by pip in the process of installation should use user installed versions of libraries as according to PEP 370:
The user site directory is added before the system site directories
but after Python's search paths and PYTHONPATH. This setup allows the
user to install a different version of a package than the system
administrator but it prevents the user from accidently overwriting a
stdlib module. Stdlib modules can still be overwritten with
PYTHONPATH.
Sidenote
Setuptools use hack by inserting code in easy_install.pth file which is placed in site-packages directory. This code makes packages installed with setuptools come before other packages in sys.path so they shadow other packages with the same name. This is referred to as sys.path modification in the table comparing setuptools and pip. This is the reason console scripts use user installed libraries when you install with setup.py install instead of using pip.
Taking all of the above into account the reason for what you observe might be caused by:
PYTHONPATH pointing to directories with system-wide installed libraries
Having system-wide libraries installed using sudo python.py install (...)
Having OS influence sys.path construction in some way
In the first case either clearing PYTHONPATH or adding path to user installed library to the beginning of PYTHONPATH should help.
In the second case uninstalling system-wide libraries and installing them with distro package manager instead might help (please note that you never should use sudo with pip or setup.py to install Python packages).
In the third case it's necessary to find out how does OS influence sys.path construction and if there's some way of placing user installed libraries before system ones.
You might be interested in reading issue pip list reports wrong version of package installed both in system site and user site where I asked basically the same question as you:
Does it mean that having system wide Python packages installed with easy_install thus having them use sys.path manipulation breaks scripts from user bin directory? If so is there any workaround?
Last resort solution would be to manually place directory/directories with user installed libraries in the beginning of sys.path from your scripts before importing these libraries.
Having said that if your users do not need direct access to source code I would propose packaging your app together with all dependencies using tool like pex or Platter into self-contained bundle.