How to add dependencies inside setup.py file ? Like, I am writing this script on VM and want to check whether certain dependencies like, jdk or docker is there or not, and if there is no dependencies installed, then need to install automatically on VM using this script.
Please do tell me as soon as possible, as it is required for my project.
In simplest form, you can add (python) dependencies which can be install via pip as follow:
from setuptools import setup
setup(
...
install_requires=["install-jdk", "docker>=4.3"],
...
)
Alternatively, write down a requirement.txt file and then use it:
with open("requirements.txt") as requirements_file:
requirements = requirements_file.readlines()
requirements = [x[:-1] for x in requirements]
setup(
...
install_requires=requirements,
...
)
Whenever you'll execute python setup.py install then these dependencies will be checked against the available libraries in your VM and if they are not available (or version mismatch) then it will be installed (or replaced). More information can be found here.
Refer the https://github.com/boto/s3transfer/blob/develop/setup.py and check the requires variables.
You can refer many other open source projects
You can add dependencies using setuptools, however it can only check dependencies on python packages.
Because of that, you could check jdk and docker installation before setup(), manually.
You could call system like the code below and check the reponse.
import os
os.system("java -version")
os.system("docker version --format \'{{.Server.Version}}\'")
Related
I use it on my windows machine by downloading its binary. I also use it in Heroku from its herokus build pack. I don't know what operating system replit use. But I try every possible commed like.
!pip install ta-lib
!pip install talib-binary
It's not working with replit. I thought it work like google co-lab but its not the same.
can anyone use TA-LIB with replit. if so. How you install it?
Getting TA-Lib work on Replit
(by installing it from sources)
Create a new replit with Nix toolset with a Python template.
In main.py write:
import talib
print (talib.__ta_version__)
This will be our test case. If ta-lib is installed the python main.py (executed in Shell) will return something like:
$ python main.py
b'0.6.0-dev (Jan 1 1980 00:00:00)'
We need to prepare a tools for building TA-Lib sources. There is a replit.nix file in your project's root folder (in my case it was ~/BrownDutifulLinux). Every time you execute a command like cmake the Nix reports that:
cmake: command not installed. Multiple versions of this command were found in Nix.
Select one to run (or press Ctrl-C to cancel):
cmake.out
cmakeCurses.out
cmakeWithGui.out
cmakeMinimal.out
cmake_2_8.out
If you select cmake.out it will add a record about it into the replit.nix file. And next time you call cmake, it will know which cmake version to launch. Perhaps you may manually edit replit.nix file... But if you're going to add such commands in a my way, note that you must execute them in Shell in your project root folder as replit.nix file is located in it. Otherwise Nix won't remember your choice.
After all my replit.nix file (you may see its content with cat replit.nix) content was:
{ pkgs }: {
deps = [
pkgs.libtool
pkgs.automake
pkgs.autoconf
pkgs.cmake
pkgs.python38Full
];
env = {
PYTHON_LD_LIBRARY_PATH = pkgs.lib.makeLibraryPath [
# Needed for pandas / numpy
pkgs.stdenv.cc.cc.lib
pkgs.zlib
# Needed for pygame
pkgs.glib
# Needed for matplotlib
pkgs.xorg.libX11
];
PYTHONBIN = "${pkgs.python38Full}/bin/python3.8";
LANG = "en_US.UTF-8";
};
}
Which means I executed libtool, autoconf, automake and cmake in Shell. I always choose a generic suggestion from Nix, without a specific version. Note: some commands may report errors as we executing them in a wrong way just to add to a replit.nix.
3.
Once build tools are set up we need to get and build TA-Lib C library sources. To do that execute in Shell:
git clone https://github.com/TA-Lib/ta-lib.git
then
cd ta-lib/
libtoolize
autoreconf --install
./configure
If configure script is completed without any problems, build the library with:
make -j4
It will end up with some compilation errors, but they are related to some additional tools which are used to add new TA-Lib indicators and build at the end, but not the library itself. The library will be successfully compiled and you should be able to see it with:
$ ls ./src/.libs/
libta_lib.a libta_lib.lai libta_lib.so.0
libta_lib.la libta_lib.so libta_lib.so.0.0.0
Now we have our C library built, but we can't install it to a system default folders. So we have to use the library as is from the folders where it was build. All we need is just one more additional preparation:
mkdir ./include/ta-lib
cp ./include/*.h ./include/ta-lib/
This will copy a library headers to a subfolder, as they are designed to be used from a such subfolder (which they don't have due to impossibility to perform the installation step).
4.
Now we have TA-Lib C library built and prepared to be used locally from its build folders. All we need after that - is to compile the Python wrapper for it. But Python wrapper will look for a library only in system default folders, so we need to instruct it where our library is.
To do this, execute pwd and remember the absolute path to your project's root folder. In my case it was:
/home/runner/FormalPleasedOffice
Then adjust the paths (there are two) in a following command to lead to your project path:
TA_INCLUDE_PATH=/home/runner/FormalPleasedOffice/ta-lib/include/ TA_LIBRARY_PATH=/home/runner/FormalPleasedOffice/ta-lib/src/.libs/ pip install ta-lib
This is one line command, not a two commands.If the paths would be shorter it would look like:
TA_INCLUDE_PATH=/path1/ TA_LIBRARY_PATH=/path2/ pip install ta-lib.
After execution of this command the wrapper will be installed with two additional paths where it will look for a library and its header files.
That's actually all.
An alternative way would be to clone the wrapper sources, edit its setup.py and install wrapper manually. Just for the record this would be:
cd ~/Your_project
git clone https://github.com/mrjbq7/ta-lib.git ta-lib-wrapper
cd ta-lib-wrapper
Here edit the setup.py. Find the lines include_dirs = [ and library_dirs = [ and append your paths to these lists. Then you just need to:
python setup.py build
pip install .
Note the dot at the end.
5.
Go to the project's folder and try our python script:
$python main.py
b'0.6.0-dev (Jan 1 1980 00:00:00)'
Bingo!
The #truf answer is correct.
after you add the
pkgs.libtool
pkgs.automake
pkgs.autoconf
pkgs.cmake
in the replit.nix dippendancies.
git clone https://github.com/TA-Lib/ta-lib.git
cd ta-lib/
libtoolize
autoreconf --install
./configure
make -j4
mkdir ./include/ta-lib
cp ./include/*.h ./include/ta-lib/
TA_INCLUDE_PATH=/home/runner/FormalPleasedOffice/ta-lib/include/ TA_LIBRARY_PATH=/home/runner/FormalPleasedOffice/ta-lib/src/.libs/ pip install ta-lib
Note : FormalPleasedOffice should be your project name
Done.
Here is the youtube video :
https://www.youtube.com/watch?v=u20y-nUMo5I
I am writing a python application which dependents on Scrapy module. It works fine locally but failed when I run it from aws lambda test console. My python project has a requirements.txt file with below dependency:
scrapy==1.6.0
I packaged all dependencies by following this link: https://docs.aws.amazon.com/lambda/latest/dg/lambda-python-how-to-create-deployment-package.html. And also, I put my source code *.py at the root level of in the zip file. My package script can be found https://github.com/zhaoyi0113/quote-datalake/blob/master/bin/deploy.sh.
It basically does two things, first run command pip install -r requirements.txt -t dist to download all dependencies to dist directory. second, copy app python source code to dist directory.
The deployment is done via terraform and below is the configuration file.
provider "aws" {
profile = "default"
region = "ap-southeast-2"
}
variable "runtime" {
default = "python3.6"
}
data "archive_file" "zipit" {
type = "zip"
source_dir = "crawler/dist"
output_path = "crawler/dist/deploy.zip"
}
resource "aws_lambda_function" "test_lambda" {
filename = "crawler/dist/deploy.zip"
function_name = "quote-crawler"
role = "arn:aws:iam::773592622512:role/LambdaRole"
handler = "handler.handler"
source_code_hash = "${data.archive_file.zipit.output_base64sha256}"
runtime = "${var.runtime}"
}
It zip the directory and upload the file to lambda.
I found I get the runtime error in lambda Unable to import module 'handler': cannot import name 'etree' when there is a statement import scrapy. I didn't use etree in my code so I believe there is something used by scrapy.
My source code can be found at https://github.com/zhaoyi0113/quote-datalake/tree/master/crawler. There are only two simple python files.
It works fine if I run them locally. The error only appears in lambda. Is there a different way to package scrapy to lambda?
Based on the communication with Tim, the issue is caused by incompatible library versions between local and lambda.
The easiest way to resolve this issue is to use the docker image lambci/lambda to build a package with the command:
$ docker run -v $(pwd):/outputs -it --rm lambci/lambda:build-python3.6 pip install scrapy -t /outputs/
You need to provide the entire dependency tree, scrapy also has a set of dependencies (and they may also have dependencies).
The easiest way to download all the required dependencies is to use pip
$ pip -t packages/ install scrapy
This will download scrapy and all its dependencies into the folder packages.
Scrapy has lxml and pyOpenSSL as dependencies that include compiled components. Unless they are statically compiled they will likely require that the c-libraries they require are also installed on the lambda VM.
From the lxml documentation it requires:
libxml2 version 2.9.2 or later.
libxslt version 1.1.27 or later.
We recommend libxslt 1.1.28 or later.
Maybe try adding installation of these to your deploy script. You should be able to use (I'm making a guess at the package names) yum -y install libxml2 libxslt
Another good idea is to test your scripts on an Amazon Linux EC2 instance as this is close to the environment that Lambda executes in.
I am trying to install pdfMiner to work with CollectiveAccess. My host (pair.com) has given me the following information to help in this quest:
When compiling, it will likely be necessary to instruct the
installation to use your account space above, and not try to install
into the operating system directories. Typically, using "--
home=/usr/home/username/pdfminer" at the end of the install command
should allow for that.
I followed this instruction when trying to install.
The result was:
running install
running build
running build_py
running build_scripts
running install_lib
running install_scripts
changing mode of /usr/home/username/pdfminer/bin/latin2ascii.py to 755
changing mode of /usr/home/username/pdfminer/bin/pdf2txt.py to 755
changing mode of /usr/home/username/pdfminer/bin/dumppdf.py to 755
running install_egg_info
Removing /usr/home/username/pdfminer/lib/python/pdfminer-20140328.egg-info
Writing /usr/home/username/pdfminer/lib/python/pdfminer-20140328.egg-info
I don't see anything wrong with that (I'm very new to python), but when I try to run the sample command $ pdf2txt.py samples/simple1.pdf I get this error:
Traceback (most recent call last): File "pdf2txt.py", line 3, in <module>
from pdfminer.pdfdocument import PDFDocument ImportError: No module named pdfminer.pdfdocument
I'm running python 2.7.3. I can't install from root (shared hosting). The most recent version of pdfminer, which is 2014/03/28.
I've seen some posts on similar issues ("no module named. . . " but nothing exactly the same. The proposed solutions either don't help (such as installing with sudo - not an option; specifying the path for python (which doesn't seem to be the issue), etc.).
Or is this a question for my host? (i.e., something amiss or different about their setup)
I had an error like this:
No module named 'pdfminer.pdfinterp'; 'pdfminer' is not a package
My problem was that I had named my script pdfminer.py which for the reasons that I don't know, Python took it for the original pdfminer package files and tried to compiled it.
I renamed my script to something else, deleted all the *.pyc file and __pycache__ directory and my problem was solved.
use this command worked for me and removed the error
pip install pdfminer.six
Since the package pdfminer is installed to a non-standard/non-default location, Python won't be be able to find it. In order to use it, you will need to add it to your 'pythonpath'. Three ways:
At run time, put this in your script pdf2txt.py:
import sys
# if there are no conflicting packages in the default Python Libs =>
sys.path.append("/usr/home/username/pdfminer")
or
import sys
# to always use your package lib before the system's =>
sys.path.insert(1, "/usr/home/username/pdfminer")
Note: The install path specified with --home is used as the Lib for all packages which you might want to install, not just this one. You should delete that folder and re-install with --
home=/usr/home/username/myPyLibs (or any generic name) so that when you install other packages with that install path, you would only need the one path to add to your local Lib to be able to import them:
import sys
sys.path.insert(1, "/usr/home/username/myPyLibs")
Add it to PYTHONPATH before executing your script:
export PYTHONPATH="${PYTHONPATH}:/usr/home/username/myPyLibs"
And then put that in your ~/.bashrc file (/usr/home/username/.bashrc) or .profile as applicable. This may not work for programs which are not executed from the console.
Create a VirtualEnv and install the packages you need to that.
I have a virtual environment and I had to activate it before I did a pip3 install to have the venv see it.
source ~/venv/bin/activate
I'm developing my own module in python 2.7. It resides in ~/Development/.../myModule instead of /usr/lib/python2.7/dist-packages or /usr/lib/python2.7/site-packages. The internal structure is:
/project-root-dir
/server
__init__.py
service.py
http.py
/client
__init__.py
client.py
client/client.py includes PyCachedClient class. I'm having import problems:
project-root-dir$ python
Python 2.7.2+ (default, Jul 20 2012, 22:12:53)
[GCC 4.6.1] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> from server import http
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "server/http.py", line 9, in <module>
from client import PyCachedClient
ImportError: cannot import name PyCachedClient
I didn't set PythonPath to include my project-root-dir, therefore when server.http tries to include client.PyCachedClient, it tries to load it from relative path and fails. My question is - how should I set all paths/settings in a good, pythonic way? I know I can run export PYTHONPATH=... in shell each time I open a console and try to run my server, but I guess it's not the best way. If my module was installed via PyPi (or something similar), I'd have it installed in /usr/lib/python... path and it'd be loaded automatically.
I'd appreciate tips on best practices in python module development.
My Python development workflow
This is a basic process to develop Python packages that incorporates what I believe to be the best practices in the community. It's basic - if you're really serious about developing Python packages, there still a bit more to it, and everyone has their own preferences, but it should serve as a template to get started and then learn more about the pieces involved. The basic steps are:
Use virtualenv for isolation
setuptools for creating a installable package and manage dependencies
python setup.py develop to install that package in development mode
virtualenv
First, I would recommend using virtualenv to get an isolated environment to develop your package(s) in. During development, you will need to install, upgrade, downgrade and uninstall dependencies of your package, and you don't want
your development dependencies to pollute your system-wide site-packages
your system-wide site-packages to influence your development environment
version conflicts
Polluting your system-wide site-packages is bad, because any package you install there will be available to all Python applications you installed that use the system Python, even though you just needed that dependency for your small project. And it was just installed in a new version that overrode the one in the system wide site-packages, and is incompatible with ${important_app} that depends on it. You get the idea.
Having your system wide site-packages influence your development environment is bad, because maybe your project depends on a module you already got in the system Python's site-packages. So you forget to properly declare that your project depends on that module, but everything works because it's always there on your local development box. Until you release your package and people try to install it, or push it to production, etc... Developing in a clean environment forces you to properly declare your dependencies.
So, a virtualenv is an isolated environment with its own Python interpreter and module search path. It's based on a Python installation you previously installed, but isolated from it.
To create a virtualenv, install the virtualenv package by installing it to your system wide Python using easy_install or pip:
sudo pip install virtualenv
Notice this will be the only time you install something as root (using sudo), into your global site-packages. Everything after this will happen inside the virtualenv you're about to create.
Now create a virtualenv for developing your package:
cd ~/pyprojects
virtualenv --no-site-packages foobar-env
This will create a directory tree ~/pyprojects/foobar-env, which is your virtualenv.
To activate the virtualenv, cd into it and source the bin/activate script:
~/pyprojects $ cd foobar-env/
~/pyprojects/foobar-env $ . bin/activate
(foobar-env) ~/pyprojects/foobar-env $
Note the leading dot ., that's shorthand for the source shell command. Also note how the prompt changes: (foobar-env) means your inside the activated virtualenv (and always will need to be for the isolation to work). So activate your env every time you open a new terminal tab or SSH session etc..
If you now run python in that activated env, it will actually use ~/pyprojects/foobar-env/bin/python as the interpreter, with its own site-packages and isolated module search path.
A setuptools package
Now for creating your package. Basically you'll want a setuptools package with a setup.py to properly declare your package's metadata and dependencies. You can do this on your own by by following the setuptools documentation, or create a package skeletion using Paster templates. To use Paster templates, install PasteScript into your virtualenv:
pip install PasteScript
Let's create a source directory for our new package to keep things organized (maybe you'll want to split up your project into several packages, or later use dependencies from source):
mkdir src
cd src/
Now for creating your package, do
paster create -t basic_package foobar
and answer all the questions in the interactive interface. Most are optional and can simply be left at the default by pressing ENTER.
This will create a package (or more precisely, a setuptools distribution) called foobar. This is the name that
people will use to install your package using easy_install or pip install foobar
the name other packages will use to depend on yours in setup.py
what it will be called on PyPi
Inside, you almost always create a Python package (as in "a directory with an __init__.py) that's called the same. That's not required, the name of the top level Python package can be any valid package name, but it's a common convention to name it the same as the distribution. And that's why it's important, but not always easy, to keep the two apart. Because the top level python package name is what
people (or you) will use to import your package using import foobar or from foobar import baz
So if you used the paster template, it will already have created that directory for you:
cd foobar/foobar/
Now create your code:
vim models.py
models.py
class Page(object):
"""A dumb object wrapping a webpage.
"""
def __init__(self, content, url):
self.content = content
self.original_url = url
def __repr__(self):
return "<Page retrieved from '%s' (%s bytes)>" % (self.original_url, len(self.content))
And a client.py in the same directory that uses models.py:
client.py
import requests
from foobar.models import Page
url = 'http://www.stackoverflow.com'
response = requests.get(url)
page = Page(response.content, url)
print page
Declare the dependency on the requests module in setup.py:
install_requires=[
# -*- Extra requirements: -*-
'setuptools',
'requests',
],
Version control
src/foobar/ is the directory you'll now want to put under version control:
cd src/foobar/
git init
vim .gitignore
.gitignore
*.egg-info
*.py[co]
git add .
git commit -m 'Create initial package structure.
Installing your package as a development egg
Now it's time to install your package in development mode:
python setup.py develop
This will install the requests dependency and your package as a development egg. So it's linked into your virtualenv's site-packages, but still lives at src/foobar where you can make changes and have them be immediately active in the virtualenv without re-installing your package.
Now for your original question, importing using relative paths: My advice is, don't do it. Now that you've got a proper setuptools package, that's installed and importable, your current working directory shouldn't matter any more. Just do from foobar.models import Page or similar, declaring the fully qualified name where that object lives. That makes your source code much more readable and discoverable, for yourself and other people that read your code.
You can now run your code by doing python client.py from anywhere inside your activated virtualenv. python src/foobar/foobar/client.py works just as fine, your package is properly installed and your working directory doesn't matter any more.
If you want to go one step further, you can even create a setuptools entry point for your CLI scripts. This will create a bin/something script in your virtualenv that you can run from the shell.
setuptools console_scripts entry point
setup.py
entry_points='''
# -*- Entry points: -*-
[console_scripts]
run-fooobar = foobar.main:run_foobar
''',
client.py
def run_client():
# ...
main.py
from foobar.client import run_client
def run_foobar():
run_client()
Re-install your package to activate the entry point:
python setup.py develop
And there you go, bin/run-foo.
Once you (or someone else) installs your package for real, outside the virtualenv, the entry point will be in /usr/local/bin/run-foo or somewhere simiar, where it will automatically be in $PATH.
Further steps
Creating a release of your package and uploading it PyPi, for example using zest.releaser
Keeping a changelog and versioning your package
Learn about declaring dependencies
Learn about Differences between distribute, distutils, setuptools and distutils2
Suggested reading:
The Hitchhiker’s Guide to Packaging
The pip cookbook
So, you have two packages, the first with modules named:
server # server/__init__.py
server.service # server/service.py
server.http # server/http.py
The second with modules names:
client # client/__init__.py
client.client # client/client.py
If you want to assume both packages are in you import path (sys.path), and the class you want is in client/client.py, then in you server you have to do:
from client.client import PyCachedClient
You asked for a symbol out of client, not client.client, and from your description, that isn't where that symbol is defined.
I personally would consider making this one package (ie, putting an __init__.py in the folder one level up, and giving it a suitable python package name), and having client and server be sub-packages of that package. Then (a) you could do relative imports if you wanted to (from ...client.client import something), and (b) your project would be more suitable for redistribution, not putting two very generic package names at the top level of the python module hierarchy.
how can I make setup.py file for my own script? I have to make my script global.
(add it to /usr/bin) so I could run it from console just type: scriptName arguments.
OS: Linux.
EDIT:
Now my script is installable, but how can i make it global? So that i could run it from console just name typing.
EDIT: This answer deals only with installing executable scripts into /usr/bin. I assume you have basic knowledge on how setup.py files work.
Create your script and place it in your project like this:
yourprojectdir/
setup.py
scripts/
myscript.sh
In your setup.py file do this:
from setuptools import setup
# you may need setuptools instead of distutils
setup(
# basic stuff here
scripts = [
'scripts/myscript.sh'
]
)
Then type
python setup.py install
Basically that's it. There's a chance that your script will land not exactly in /usr/bin, but in some other directory. If this is the case, type
python setup.py install --help
and search for --install-scripts parameter and friends.
I know that this question is quite old, but just in case, I post how I solved the problem for myself, that was wanting to setup a package for PyPI, that, when installing it with pip, would install it as a system package, not just for Python.
setup(
# rest of setup
console_scripts={
'console_scripts': [
'<app> = <package>.<app>:main'
]
},
)
Details