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Is there a Scrum plugin for the Roundup Issue Tracker similar to Agilo for Trac? I realize that Roundup is an issue tracking system, whereas Trac is designed to be an integrated project management, SCM, and issue tracker. Therefore, maybe a better question would be—Is anyone aware of a, preferably Python based, Scrum tool to use in conjunction with Roundup? Although, that may be a bit too subjective for this forum.
After researching this some more, it appears that there is not a Scrum plugin for the Roundup Issue Tracker similar to Agilo for Trac. However, I was able to find Ajellito (formerly Agilito). From the Ajellito website:
Simple, web-based Agile / Scrum project management tool built in Django
Ajellito aims to do just enough for you to effectively and efficiently manage projects using an Agile methodology.
Given that Ajellito is written in Django—a Python web framework—this may be a nice complement to Roundup.
Using Ajellito for tracking user stories and tasks/actions and Roundup to track bugs/defects presents a new problem in terms of integration, or lack thereof, between the actions/tasks and bugs/defects.
Agile Database Integration http://img.skitch.com/20100104-t3crikk3hjb1mrmmnuipsk5fj7.jpg
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My goal is to land a job in Data Science and I would like to ask the people who already work in this field and who can give me advise which Python Framework (Flask or Django) should I master / focus on?
My plan is to create machine learning projects and deploy them to a server, and present them as my experience since I don't have any actual work experience in this field. But I don't want to make a mistake spending hours and hours mastering framework that no one use and then learn again.
Thank You.
Both are good options.
Flask for small scope.
Django is complete, has feature for almost everything out of the box.
You might also include in your stack: pandas, spark, tensor flow, Apache Bean, Google Data Flow, and other related stuff.
Start doing small projects from the courses and tutorials to begin a portfolio, always go for the official documentation to tie up things.
The most important is one Python. Getting really good with Python is the most important pre-requisite.
Then learn data Science Python libraries, first NumPy, and then Pandas.
After that move on to advanced tools like TensorFlow, or the programming language R.
One of the best places to learn more about these technologies, take free courses on freecodecamp.org, first do the course on Python computing, then TensorFlow, both of these are great.
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I'm about to take a project that communicates with a BT device, receiving continuous physiological data (skin resistance) on a Windows PC.
The program I create will show a real-time graph of the data, and log it.
I program in Python and Visual Basic, and in order to optimize my investment in this project I'm hoping to get a suggestion for the best approach - preferably, I'll not have to learn a new programming language.
This app will be used by users with no technical skills, so I need it to be plug&play.
Is it worth it to combine Python and VB? For instance creating the interface in VB, but using Python for the data processing and graphing (i.e., saving figures as files and updating in the main window)?
Thanks
I suspect the trickiest piece to find answers to will be the Bluetooth piece. How tricky that is will depend a little bit on what device you are communicating with and what level of security it has on it.
On the Python side, In Python 3.9 there is support for Bluetooth Classic RFCOMM/SPP in the standard sockets library. Example of how to do that can be found at:
https://blog.kevindoran.co/bluetooth-programming-with-python-3/
If you Bluetooth device is Bluetooth Low Energy (BLE) then the Bleak library may be helpful
For packaging your application up for end users, then there looks to be good information in the following question:
https://stackoverflow.com/a/2937/7721752
I'd just stick with Python for the whole project. Python's UI libraries are good enough for a project like this, and all the Python data science resources should come in handy for graphing, analysis, and logging.
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I do not even know how to start to ask this question. So here is my best effort. Please guide me along. I have always been interested in GAE. Now I would like to develop an application that uses GAE. But I am having trouble selecting the appropriate technology stack to use with GAE. For example, should I use Python or Java in GAE? Should I use GWT or some other tool to develop the end user interface (GUI).
Right now, I tend to favor using Python on the GAE. But I don't know about the end user interface (GUI). Is GWT the only option?
About my little application:
The application will allow the user to input information/photos about an inspection (common stuff) and create a record of the inspection. Then the application will generated an inspection report (common format) of a selected record.
I hope this is enough to describe my dilemma. Thanks,
App Engine Python applications have built in support for webapp2 which itself inherently support Django templates out of the box. GWT is definitely not the only option.
As Thomas Orozco said in his answer, you can use a myriad of front end technologies. Although I've never tried it, if you wrote your app in Python I'm sure you could use Cheetah, Jinja2, or some other templating language.
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What are the best (more or less mature, supporting more advanced logic, having acceptable performance, scalable to some extent) open source Semantic Web libraries and tools (RDF storage, reasoning, rules, queries) for Python nowadays? Historically Python tools (cwm) were among the first to appear, but it still seems that everyone uses Java back-ends for performance and Python as mere client if at all. My purpose is to learn the technology and maybe some future use in production system if it proves itself up to the task. The task is not yet defined, but as I see it its building a knowledge base, linked with some external resources, and customized facet-navigable web front-end.
If some building blocks based on Python are not good enough, then what is the suitable piece from Java/C/C++/whatever world.
Typical stack is also of interest, if there are one or two clear winners.
Thanks.
A survey of of Python libraries and tools for Semantic Web programming is available here. It includes libraries for working with RDF as well as Python-friendly triple stores.
Toby Segaran's book Programming the Semantic Web also has a lot of programming examples in Python.
You could check out the pyswip. It could work with the SWI-Prolog. Wish it would fit for requirement. :)
To name some, check out RDFLib and CubicWeb.
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Ok, I am not sure I want to use Request Tracker and RTFM, which is a possible solution.
I'd like to have a knowledge base with my bug tracker/todo list , so that when
I solve a problem, I would have a record of its resolution for myself or others later.
What python based solutions are available?
A highly flexible issue tracker in Python I would recommend is "Roundup":
http://roundup.sourceforge.net/.
An example of its use can be seen online at http://bugs.python.org/.
Try Trac
I do have experience using probably 20-30 different bug trackers, installed or hosted and so far if you are up to deal with a big number of bugs and you want to spend less time coding-the-issues-tracker, to get Atlassian Jira, which is free for open-source projects.
Yes, it's not Python, it is Java, starts slowly and requires lots of resources. At the same time, RAM is far less expensive than your own time and if you want to extend the system you can do it in Python by using https://pypi.python.org/pypi/jira-python/
Do you think that Jira is the most used bug tracker for no reason? It wasn't the first on the market, in fact is quite new compared with others.
Once deployed you can focus on improving the workflows instead of patching the bug tracker.
One of the best features that it has is the ability to link to external issues and be able to see their status, without having to click on them. As an warning, for someone coming from another tracekr you may discover that there are some design limitations, like the fact that a bug can have a single assignee. Don't be scared about it, if you look further you will find that there are way to assign tickets to groups of peoples.