I recently developed a package my_package and am hosting it on GitHub. For easy installation and use, I have following setup.py:
from setuptools import setup
setup(name='my_package',
version='1.0',
description='My super cool package',
url='https://github.com/my_name/my_package',
packages=['my_package'],
python_requieres='3.9',
install_requires=[
'some_package==1.0.0'
])
Now I am trying to install this package in a conda environment:
conda create --name myenv python=3.9
conda activate myenv
pip install git+'https://github.com/my_name/my_package'
So far so good. If I try to use it in the project folder, everything works perfectly. If I try to use the packet outside the project folder (still inside the conda environment), I get the following error:
ModuleNotFoundError: No module named 'my_package'
I am working on windows, if that matters.
EDIT:
I'm verifying that both python and pip are pointing towards the correct version with:
which pip
which python
/c/Anaconda3/envs/my_env/python
/c/Anaconda3/envs/my_env/Scripts/pip
Also, when I run:
pip show my_package
I get a description of my package. So pip finds it, but as soon as I try to import my_package in the script, I get the described error.
I also verified that the package is installed in my environment. So in /c/Anaconda3/envs/my_env/lib/site-packages there is a folder my_package-1.0.dist-info/
Further: python "import sys, print(sys.path)"
shows, among other paths, /c/Anaconda3/envs/my_env/lib/site-packages. So it is in the path.
Check if you are using some explicit shebang in your script pointing to other Python interpreters.
Eg. using the system default Python:
#!/bin/env python
...
While inside your environment myenv, try to uninstall your package first, to do a clean test:
pip uninstall my_package
Also, you have a typo in your setup.py: python_requieres --> python_requires.
And I actually tried to install with your setup.py, and also got ModuleNotFoundError - but because it didn't properly install due to install_requires:
ERROR: Could not find a version that satisfies the requirement some_package==1.0.0
So, check also that everything installs without errors and warnings.
Hope that helps.
First thing I would like to point out (not the solution) regards the following statement you made:
If I try to use it in the project folder [...] If I try to use the packet outside the project folder [...]
I understand "project folder" means the "my_package" folder (inside the git repository). If that is the case, I would like to point out that you are mixing two situations: that of testing a (remote) package installation, while in your (local) repository. Which is not necessarily wrong, but error-prone.
Whenever testing the setup/install process of a package, make sure to move far from your repository (say, "/tmp/" equivalent in Windows) and, preferably, use a fresh environment. That will eliminate "noise" in your tests.
First thing I would tell you to do -- if not already -- is to create a fresh conda env and install your package from an empty/new folder. Eg,
$ conda env create -n test_my_package ipython pip
$ cd /tmp # equivalent temporary or new in your Windows
$ pip install git+https://github.com/my_name/my_package
If that doesn't work (maybe a problem with your pip' git+http code), do another way: create a release for your package (eg, "v1") and then install the released version by indicating the zip package URL (that you get from your "my_package" releases page on Github):
$ pip install https://github.com/my_name/my_package/archive/v1.zip
Related
I am trying to build (and later upload) a conda package which would contain my custom program that I have developed in C++.
Simplifying the problem, I have a following meta.yaml:
package:
name: CoolName
version: "1.0.0"
source:
path: ./source
requirements:
build:
- make
and the following build.sh:
make
I have two questions here:
1) How and where should I copy the binary which is a result of the make compilation so that it is indeed recognized upon environment activation?
2) How should I specify g++ as a dependancy? I would like to have this package be later available for linux-64 and osx-64... In the building process (in the Makefile) I am using only g++.
Edit
I have modified my build script to have:
make
mkdir -p $PREFIX/bin
cp my_binary $PREFIX/bin/my_binary
And now the conda-build is successful. However, when I later try to install the package locally with conda install --use-local I get:
Collecting package metadata (current_repodata.json): done
Solving environment: done
# All requested packages already installed.
But this is not true, my binary is not installed anywhere and is not recognized...
How and where should I copy the binary which is a result of the make compilation so that it is indeed recognized upon environment activation?
As you mentioned in your edit, install somewhere within ${PREFIX}
How should I specify g++ as a dependancy?
To use conda-supplied compilers (rather than your system compiler), use this:
requirements:
build:
- {{ compiler('cxx') }}
I would like to have this package be later available for linux-64 and osx-64... In the building process (in the Makefile) I am using only g++.
Note: On Mac, it will use clang++, not g++. Make sure your Makefile respects the ${CXX} environment variable instead of hard-coding g++.
However, when I later try to install the package locally with conda install --use-local I get:
That is strange. conda install --use-local CoolName should do what you want. But here are some things to try:
Double-check the contents of the environment you're trying to install it into:
conda list
Try installing to a fresh environment:
conda create -n my-new-env --use-local CoolName
Delete any obsolete versions of the package you might have created before you successfully built the package:
# Inspect the packages you've created,
# and consider deleting all but the most recent one.
ls $(conda info --base)/conda-bld/linux-64/CoolName*.tar.bz2
...then try running conda install again.
I'm having issues with pip failing to install editable packages from a local directory. I was able to install the packages manually using commands like pip install -e pkg1. I wanted to use a requirements.txt file to automate future installs, because my coworkers will be working on the same packages. My ideal development workflow is for each developer to checkout the source from version control and run pip install -r requirements.txt. The requirements file would designate all the packages as editable so we can import our code without the need for .pth files but we wouldn't have to keep updating our environments. And by using namespace packages, we can decouple the import semantics from the file structures.
But it's not working out.
I have a directory with packages like so:
index/
pkg1/
src/
pkg1/
__init__.py
pkg1.py
setup.py
pkg2/
src/
...etc.
Each setup.py file contains something like:
from setuptools import setup, find_packages
setup(
name="pkg1",
version="0.1",
packages=find_packages('src'),
package_dir={'':'src'},
)
I generated my requirements.txt file using pip freeze, which yielded something like this:
# Editable install with no version control (pkg1==0.1)
-e c:\source\pkg1
# Editable install with no version control (pkg2==0.1)
-e c:\source\pkg2
...etc...
I was surprised when pip choked on the requirements file that it created for itself:
(venv) C:\Source>pip install -r requirements.txt
c:sourcepkg1 should either be a path to a local project or a VCS url beginning with svn+, git+, hg+, or bzr+
Also, some of our packages rely on other of our packages and pip has been absolutely useless at identifying these dependencies. I have resorted to manually installing packages in dependency order.
Maybe I'm pushing pip to its limits here. The documentation and help online has not been helpful, so far. Most sources discuss editable installation, installation from requirements files, package dependencies, or namespace packages, but never all these concepts at once. Usually when the online help is scarce, it means that I'm trying to use a tool for something it wasn't intended to do or I've discovered a bug.
Is this development process viable? Do I need to make a private package index or something?
I have used a YAML file and have imported PyYAML into my project.
The code works fine in PyCharm, however on creation of an egg and running the egg gives an error as module not found on command prompt.
You have not provided quite enough information for an exact answer, but, for missing python modules, simply run
py -m pip install PyYaml
or, in some cases
python pip install PyYaml
You may have imported it in your project (on PyCharm) but you have to make sure it is installed and imported outside of the IDE, and on your system, where the python interpreter runs it
I have not made an .egg for some time (you really should be consider using wheels for distributing packages), but IIRC an .egg should have a requires.txt file with an entry that specifies dependency on pyyaml.
You normally get that when setup() in your setup.py has an argument install_requires:
setup(
...
install_requires=['pyyaml<4']
...
)
(PyYAML 4.1 was retracted because there were problems with that version, but it might be in your local cache of PyPI as it was in my case, hence the <4, which restricts installation to the latest 3.x release)
Jython Package installation issue, using pip
Hi, I have installed Jython2.7 configured with pydev in eclipse neon, also configured python 3.6 package
I am able to install packages for python using pip installer?
pip install "packagename"
Below are some of the packages in python/Lib/Site-packages directory
I was able to install all the packages
How do I use pip installer to install packages for jython?
I tried to install Jip package with
jython install setup.py
The binary File got installed in the Jython/Lib/Site-packages folder
However, I am not able to use it.
where and how do I get Jython package binaries like jip?
Also, Please let me know how to search jython packages?
Also, How to make pip install library packages in jython?
Any other configuration like jython home, etc that should be made?
This answer is going to be really generic but I just recently have slogged my way through the setup for jython/jip/pip and here's roughly what I had to do.
Firstly, I'm running Windows 7 64 Bit from behind a proxy (work machine.)
Had to install jython 2.7.0 instead of 2.7.1 because (I think anyway) 2.7.1 requires admin privileges which I don't have on my work PC.
Pip didn't install correctly during the Jython installation and I spent an obscene amount of time trying to get it installed and functioning as I knew it from my cpython days. NOTE: Just because you get pip installed, doesn't mean you can use any package on a python package repo. As of 2.7.0, Jython doesn't have end to end capability to interpret/compile some libraries that rely on certain python wrappers of native OS function calls. I believe 2.7.1 makes solid progress in the direction of supporting all needed native calls but don't quote me on that. For example, I tried to use wxPython to make a simple GUI to test my jython install. Trying to install it from pip kept causing really non-specific error info that took me a lot of time to figure out that the cause was jython simply couldn't compile the wxPython source so beware.
I had to set environment variables 'http_proxy' and 'https_proxy' in the form of http://proxyhosturl:port and https://proxyhosturl:port respectively to get out from behind the proxies without having to invoke pip with the proxy switch every time I called it.
To actually install pip, have a look here. These instructions are for Python and Linux/Unix but the principle is roughly the same. Just use jython -m instead of python -m and ignore the '$' at the start of each command line.
Also be sure to CD to your python_home/bin folder when invoking the ez_install exe.
If that doesn't work (didn't for me), try using get-pip.py script with these instructions https://pip.pypa.io/en/stable/installing/ (remember jython instead of python etc.). Download it, cd to the download location and follow the noted install steps. Worth noting is about half way down the install instructions where it details installing from local archives (source/binary zip or tar.gz archives of pip and setuptools as better described here: https://packaging.python.org/tutorials/installing-packages/#installing-from-local-archives).
The links to the bin archives of pip and setuptools are here:
https://pypi.python.org/pypi/setuptools
https://pypi.python.org/pypi/pip
It may also be worth making sure that your PATH environment variable has the jython/bin path in the variable value. The jython installer should do this but, again, mine did not.
If all goes well, you should be able to invoke pip with the --version switch and if it prints a line with the installed pip version info then you should be good to go
Another quirky issue I had was I could invoke a function of pip one time and any subsequent times I would get a stack trace ending with something along the lines of an object not having a certain property. I fixed that by finding my temp directory by opening a windows explorer instance and typing %TEMP% in the address bar and hitting enter, it should take you to a subdir of your AppData folder and there you may see a folder with the name of the package you were trying to install and the text "_pip" somewhere in the directory name. Delete the directory and try the pip install command again. I had to do this + invoke pip install pip -U to update my install to the latest version. Then pip began behaving correctly in my instance.
pip search numpy (or your library name) will generate a list of results with the same logic it uses to locate your desired package when you call pip install but, again, just because it returns a matching package doesn't mean it will compile when you install it (numpy doesn't work because of the missing java to C native function calls I described earlier.) The trade off is that you can import code artifacts from Java JAR files in your Jython script files and leverage their functionality with relative ease. Between the public Java APIs available and the python packages that work with the jython interpretor, you can (in my experience) come up with a way to accomplish your task. See the following info on JIP, Maven and IDEs.
IDE and jython integration (Eclipse)
- If you are stuck using Eclipse (like me) it actually has pretty decent support for python development. Install the PyDev plugin for Eclipse from Help -> Install Software. Put in this URL https://marketplace.eclipse.org/content/pydev-python-ide-eclipse, hit tab, and select the PyDev plugin and hit 'finish.'
- Setup the jython interpretor info from Windows -> Preferences -> PyDev. Provide the path to your jython.jar file.
- You should now be able to use File -> New PyDev project to create a basic python project and configure it to use your version of Jython and Java.
Brief Overview of Jip and Maven
- jip is a jython package that is invoked very similarly to pip but instead will download JAR files from the Maven Central Repository instead of python packages from pypi.com, for example. See the install instructions described here. Note the install procedure for a global jip install which differ from just pip install jip. https://pypi.python.org/pypi/jip/
- I never got jip to work exactly as I wished because there's not a ton of documentation on it outside of what I already linked. However, if you install a JAR using jip, you have to go to your project in Eclipse and actually add the JARs themselves to your PYTHONPATH in order for import statements and editing to have intellisense and so that you don't get a classnotfound exception at runtime. See following screen shot.
- There is a JIP config file that you can use similar to the pip config ini file but I have yet to find any exhaustive documentation on it's setup.
Note in the above screen shot the first entry in the External libraries entries. By default, pip places installed packages in that directory so to enable eclipse to find them, you need to also ensure that location is entered.
In Conclusion
- I have more to add to this answer and I will do so as soon as possible. In the meantime, see this example project I've loaded into github.
https://github.com/jheidlage1222/jython_java_integration_example
It shows basic config and how to interface with JARs from python code. I used the apache httpcomponents library as an example. Good luck amigo.
I'm working on a support library for a large Python project which heavily uses relative imports by appending various project directories to sys.path.
Using The Hitchhiker's Guide to Packaging as a template I attempted to create a package structure which will allow me to do a local install, but can easily be changed to a global install later if desired.
One of the dependencies of my package is the pyasn1 package for the encoding and decoding of ASN.1 annotated objects. I have to include the pyasn1 library separately as the version supported by the CentOS 6.3 default repositories is one major version back and has known bugs that will break my custom package.
The top-level of the library structure is as follows:
MyLibrary/
setup.py
setup.cfg
LICENSE.txt
README.txt
MyCustomPackage/
pyasn1-0.1.6/
In my setup configuration file I define the install directory for my library to be a local directory called .lib. This is desirable as it allows me to do absolute imports by running the command import site; site.addsitedir("MyLibrary/.lib") in the project's main application without requiring our engineers to pass command line arguments to the setup script.
setup.cfg
[install]
install-lib=.lib
setup.py
setup(
name='MyLibrary',
version='0.1a',
package_dir = {'pyasn1': 'pyasn1-0.1.6/pyasn1'},
packages=[
'MyCustomPackage',
'pyasn1',
'pyasn1.codec',
'pyasn1.compat','
pyasn1.codec.ber',
'pyasn1.codec.cer',
'pyasn1.codec.der',
'pyasn1.type'
],
license='',
long_description=open('README.txt').read(),
data_files = []
)
The problem I've run into with doing the installation this way is that when my package tries to import pyasn1 it imports the global version and ignores the locally installed version.
As a possible workaround I have tried installing the pyasn1 package under a different name than the global package (eg pyasn1_0_1_6) by doing package_dir = {'pyasn1_0_1_6':'pyasn1-0.1.6/pyasn1'}. However, this fails since the imports used internally to the pyasn1 package do not use the pyasn1_0_1_6 name.
Is there some way to either a) force Python to import a locally installed package over a globally installed one or b) force a package to install under a different name?
Use virtualenv to ensure that your application runs in a fully known configuration which is independent from the OS version of libraries.
EDIT: a quick (unix) solution is setting the PYTHONPATH environment variable, which works just like PATH for Python modules (module loaded from first path in which is found, so simply append you directory at the beginning of the PYTHONPATH). Anwyay, I strongly recommend you to proceed with virtualenv, since it was specifically engineered for handling situations like the one you are facing.
Rationale
The process is easily automatable if you write a setuptools script specifying dependencies with install_requires. For a complete example, refer to this one I wrote
Setup
Note that you can easily insert the steps below in a setup.sh shell script.
First create a virtualenv and enter it:
$ virtualenv $name
$ cd $name
Activate it:
$ source bin/activate
Now cd to your project directory and run the installer script:
$ cd $my_project_dir
$ python ./setup.py --prefix $path_to_virtualenv
Note the --prefix $path_to_virtualenv, which is used to tell the script to install in the virtualenv instead of system-wide. Call this after activating the virtualenv. Note that all the depencies are automatically downloaded and installed in the virtualenv.
Then you are done. When you want to leave the virtualenv, issue:
$ deactivate
On subsequent calls, you will only need to activate the virtualenv (step 2), maybe using a runawesomeproject.sh if you really want.
As noted on the virtualenv website, you should use virtualenv >= 1.9, as the previous versions did not download dependencies via HTTPS. If you consider plain HTTP to be sufficient, then any version should do.
You might also try relocatable virtualenvs: setup it and copy the folder to your host. Anyway, note that this feature is still experimental.