I finished scripting a a computer vision algorithm in python that rely heavily on opencv. I want to be able to deploy a standalone application to work under Mac OS that you don't have to preinstall any dependencies for.
After hours of searching the web I found people voting for py2app, however not many details on how to include opencv libraries for building.
If you successfully deploy a similar application, please tell me what did you do?
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I have python scripts for automated trading for currency and I want to deploy them by running on Jupter Lab on a cloud instance. I have no experience with cloud computing or linux, so I have been trying weeks to get into this cloud computing mania, but I found it very difficult to participate in it.
My goal is to set up a full-fledged Python infrastructure on a cloud instance from whichever provider so that I can run my trading bot on the cloud.
I want to set up a cloud instance on whichever provider that has the latest python
installation plus the typically needed scientific packages (such as NumPy and pandas and others) in combination with a password-protected and Secure Sockets Layer (SSL)-encrypted Jupyter
Lab server installation.
So far I have gotten no where. I am currently looking at the digital ocean website for setting jupter lab up but there are so many confusing terms.
What is Ubuntu or Debian? Is it like a sub-variant of Linux operating system? Why do I have only 2 options here? I use neither of the operating system, I use the windows operating system on my laptop and it is also where I developed my python script. Do I need a window server or something?
How can I do this? I tried a lot of tutorials but I just got more confused.
Your question raises several more about what you are trying to accomplish. Are you just trying to run your script on cloud services? Or do you want to schedule a server to spin up and execute your code? Are you running a bot that trades for you? These are just some initial questions after reading your post.
Regarding your specific question regarding Ubuntu and Debian, they are indeed Linux distributions which are popular option for servers. You can set up a Windows server on AWS or another cloud provider, but Linux distributions being much more popular are going to have lots of documentation, articles, stackoverflow posts around a Linux based server.
If you just want to run a script on a cloud on demand, you would probably have a lot of success following Wayne's comment around PythonAnywhere or Google Colab.
If you want your own cloud server, I would suggest starting small and slow with a small or free tier EC2 instance by following a tutorial such as this https://dataschool.com/data-modeling-101/running-jupyter-notebook-on-an-ec2-server/ Alternatively, you could splurge for an AWS AMI which will have much more compute power and be configured.
I have similar problem and the most suiteble solution to me is using docker container for jupyter notebooks. The instructions on how to install Docker can be found at https://docs.docker.com/engine/install/ubuntu/ There is ready to use Docker image docker pull jupyter/datascience-notebook for jupyter notebook python stack. The docker compose files und sone addional insruction you will fid at https://github.com/stefanproell/jupyter-notebook-docker-compose/blob/master/README.md.
We working on a project which involves ML/AI integration to the native mobile application. We are programing our ML/AI code in python. Python code has dependencies, that we need to include in our mobile application.
We have tried with kivy but they only create .apk files and apk files can't be called from other apks. So, we need to create libraries that can be included in the android and ios projects.
Also, we tried chequopy but that doesn't support mediapipe which is in heart of our implementation.
Any guidance in that direction will go long way for us.
If your app was entirely self-contained in python including dependencies using recipes should be possible. If rewriting the native app is not an option maybe one idea is to serve the ML over an HTTP API running on a local server (eg flask). Quite cumbersome as users would need to install two apps
I am currently learning Python as part of my job and was interested in the possibility of creating android applications using what I am learning. Unfortunately I only have access to a computed at work and the system is pretty locked down in that I cannot export work I create etc and the only device I have during my leisure time is my android phone.
I have heard about the possibility of using Kivy but have only seen reference to this being used on MacOS, Linux or Windows making me think my only choice would be running a virtual machine which would be less convenient than running a native tool. I have also seen that AIDE is a great tool for android app development on mobile but can only be used with C++/Java which would involve learning additional languages and PyDroid3 being a great python tool but don't know how this could be used to create android apps.
Any experience or knowledge in this area would be much appreciated. I understand the best scenario would be to either buy a laptop/pc and use PyCharm and/or Kivy or to learn Java and used the official Android development suite but in my current situation this is not possible.
Just download pydroid3 from play store and follow the steps to create an android app.
Install kivymd module using pip in pydroid3.
Watch kivymd tutorials on youtube to learn kivymd module , you can also refer to kivymd documentation on google.
Develop application using kivymd module in pydroid3.
Convert your python file to apk using kivy buildozer in google colab in chrome on your mobile phone.
I haven't used kivymd but I have used kivy in pyroid3 and it works really well on a phone. Also when you run the code it gives a really good indication of how the final app will look on the phone. But that said I have only used Buildozer to compile the .APK and this only works in Linux so for me that ment virtual Linux system.
So I was following along this Python tutorial teaching how to make a mobile app using Kivy, and at the end they used Buildozer to package it for Android. I discovered that Buildozer doesn't work for Windows. I tried looking for other ways, but have not found any straightforward way that works for Windows.
Would anyone be able to link me a relevant instruction page or explain how can I package my Kivy app for Android from a Windows WITHOUT using a virtual machine?
I have developed a web-based application for end-users that resides in a docker container. The container itself hosts a few python dependencies, a few public repositories, and a flask based web front-end with a MongoDB back-end that is started when the container is initialized.
It's fairly straightforward to download the container and run it on a docker host. However, most docker hosts (if not all) are not free.
Therefore, if an end-user wanted to use my application off the cloud they would have to download and install docker and associated dependencies on their local machine prior to being able to use the image (which is even more complicated on a system like Windows or Mac OSX)
With that being said, my question is: Is there any tool that has been developed to help ease this requirement on the end-user for deployment to users local desktop environments? I understand installing and using docker is not THAT hard, but some people are still very afraid of command-lines and I was hoping to find a method that would help alleviate some of these 'scary' requirements.
Did you look at Boot2Docker? It packages up the Docker CLI compiled for Windows or OSX, a VirtualBox VM to run Linux for the containers, with an easy-to-use installer.
Also https://kitematic.com adds more point-and-click for Mac users.
Overall, however, Docker is a developer/devops tool, and I haven't seen much aimed at helping non-technical folks use it.