I'm trying to connect RabbitMQ to Graphite(0.9.9) using https://github.com/somic/graphite-rabbitmq
However, I'm not entirely sure which directory in Graphite the graphite-rabbitmq files should be placed.
When I run carbon-agent-rabbitm1.py I get
Failed to import the graphite package. Please verify that this package
was properly installed and that your PYTHONPATH environment variable
includes the directory in which it is installed.
For example, you may need to run the following command:
export PYTHONPATH="/home/myusername/lib/python/:$PYTHONPATH"
Help would be very much appreciated
The convention with python modules, you can just put the downloaded files in an arbitrary temp directory, cd into that directory, and run:
python setup.py install
The standard distutils package will do the work of making sure everything gets to the right place.
You may also want to download pip which will manage the process of downloading and installing these packages for you, in which case you can then just type:
pip install graphite-web
But aside from all that, you really can put the files anywhere, so long as you add the directory to an environment variable called PYTHONPATH, just like the error message you quoted says.
Unless you've got a specific reason for using the scripts in that github repo, I wouldn't as they appear to be about 3 years old and graphite now has support for RabbitMQ by way of the Twisted Python AMQP library (txamqp), which makes those scripts completely unnecessary.
Related
Say you have a project, and you want to export it so that you can run it on another machine that:
You don't have root access on
You cannot assume any python packages to be installed other than python itself (not even pip)
Is there a way to export the project, even if it is just a simple script, with everything that it imports, and then everything that the imports need etc.
For example, my project uses a library called python-telegram-bot. It has a list of requirements, and I have tried running pip -r requirements.txt --target myapp to install the requirements into the app's folder, but this is not recursive. For example, requests is not in the library, yet it is needed by the app. And if I manually add requests, there are things that requests needs that aren't part of that.
Is there a way to collect every last bit of requirements into a single folder so that my script functions on an entirely vanilla installation of python?
Pyinstaller creates an executable and you can either roll all dependencies into 1 file (makes it a bit slow to load though) or create a folder with all the packages, modules, imports etc. your script will need to run on any machine. You can Google the docs for pyinstaller, it's all pretty well covered.
Hope that helps, Kuda
First, my reasons to do this - I know it's a bad idea but I am out of ideas.
I want to install a package which requires a ld version, which is higher than the one in the repo of my Centos 6.5. So I should either go for setting up everything in a Docker and running it in production - something I lack experience with and I don't feel comfortable doing for a serious project. Or upgrade ld manually building from external source. Which I read, could result in devastation of my Centos. So the last option I am left with is install the packed on other machine and manually copy it to site-packages.
I have successfully installed the package on my home laptop under Debian.
I encountered everywhere advice to copy the whole site-packages directory. Something which I don't want to do as I have different packages on both machines and I want to avoid messing up with other stuff.
I copied the .so build and .egginfo of the package. Then, on the target machine, pip freeze indeed showed me the transferred package. However, Python can't find it when I try to import and use it.
Am I missing something else?
Not any of that.
Don't mess with system Python's site-packages dir, this belongs to the system Python env only. You should only add/remove code in there by using the package manager of your OS (that's yum for CentOS). This is especially true in Linux where many OS services can rely on system Python.
So what to do instead? Use a virtualenv and/or pipx to isolate any other dependencies of the package you want to install from the system versions.
I made a package that bundles some utilities I'm using across projects. What's an easy way to import this package each time I start a new project?
There's some private work data stored as variables in there, so I won't be uploading it onto PyPi.
I am using Python 3.7 and PyCharm, and in Project Interpreter attempted to put the /zhou_utils/dist as a 'URL' of repositories it searches for, but it threw an error.
Another solution I saw someone present was to change their local PATH, but I don't have admin privileges on my work computer so don't know if I can do that.
Running this in my terminal from my 2nd project worked:
pip install -e C:\Users\Uname\PycharmProjects\zhou_utils\
I have 10 django projects that use over 50 django apps. Each app is separated in its own project and added to pypi and is getting use by few project. Every thing if fine except every time i work on a project and i want to change some code that is in one of my modules (that happens a lot) I have to open the module project, make my changes, test and publish to pypi then come back to my project update requirements.txt file and get the updated module from pip.
I'm looking for a way to be able to edit module right away from all of my projects. For example instead of getting it from pypi i want to get it from git and be able to commit to the git repository in my venv folder!
I know it seems a little bit crazy but i could save a lot of time! publisher and user of all of the modules is me so I don't mind the user to be able to change as well.
Any thought or suggestion will be appreciated. Also any none pip solution will be fine as well like writing a custom shell script.
I don't know about editing in your venv folder, which I think is not a good practice, but you can install from github by pip. You can use 'pip install git+https://github.com/urltoproject/repository.git'. Fill in the necessary details yourself of course. This also works with other systems like gitlab. You could have a separate development requirement file and a production requirement file to separate the two environments, or you install on the commandline directly with pip.
I'm a Java/Scala dev transitioning to Python for a work project. To dust off the cobwebs on the Python side of my brain, I wrote a webapp that acts as a front-end for Docker when doing local Docker work. I'm now working on packaging it up and, as such, am learning about setup.py and virtualenv. Coming from the JVM world, where dependencies aren't "installed" so much as downloaded to a repository and referenced when needed, the way pip handles things is a bit foreign. It seems like best practice for production Python work is to first create a virtual environment for your project, do your coding work, then package it up with setup.py.
My question is, what happens on the other end when someone needs to install what I've written? They too will have to create a virtual environment for the package but won't know how to set it up without inspecting the setup.py file to figure out what version of Python to use, etc. Is there a way for me to create a setup.py file that also creates the appropriate virtual environment as part of the install process? If not — or if that's considered a "no" as this respondent stated to this SO post — what is considered "best practice" in this situation?
You can think of virtualenv as an isolation for every package you install using pip. It is a simple way to handle different versions of python and packages. For instance you have two projects which use same packages but different versions of them. So, by using virtualenv you can isolate those two projects and install different version of packages separately, not on your working system.
Now, let's say, you want work on a project with your friend. In order to have the same packages installed you have to share somehow what versions and which packages your project depends on. If you are delivering a reusable package (a library) then you need to distribute it and here where setup.py helps. You can learn more in Quick Start
However, if you work on a web site, all you need is to put libraries versions into a separate file. Best practice is to create separate requirements for tests, development and production. In order to see the format of the file - write pip freeze. You will be presented with a list of packages installed on the system (or in the virtualenv) right now. Put it into the file and you can install it later on another pc, with completely clear virtualenv using pip install -r development.txt
And one more thing, please do not put strict versions of packages like pip freeze shows, most of time you want >= at least X.X version. And good news here is that pip handles dependencies by its own. It means you do not have to put dependent packages there, pip will sort it out.
Talking about deploy, you may want to check tox, a tool for managing virtualenvs. It helps a lot with deploy.
Python default package path always point to system environment, that need Administrator access to install. Virtualenv able to localised the installation to an isolated environment.
For deployment/distribution of package, you can choose to
Distribute by source code. User need to run python setup.py --install, or
Pack your python package and upload to Pypi or custom Devpi. So the user can simply use pip install <yourpackage>
However, as you notice the issue on top : without virtualenv, they user need administrator access to install any python package.
In addition, the Pypi package worlds contains a certain amount of badly tested package that doesn't work out of the box.
Note : virtualenv itself is actually a hack to achieve isolation.