It is recommended to use mlflow on .py file instead of a jupyter nootebook. Why?
If I use it directly on the notebook, will I have problems in the future?
It’s works fine in a notebook, in fact that’s where it’s arguably the most helpful. If you use it in a notebook, you will have no problems in the future.
Related
I m doing my first steps on Linux and I know I will need to look up a lot of installation codes I already made ones but will have to do it also on another VM.
What is the best way to save the snippets to find them later faster and no need to look them up again on youtube?
Is there a nice way or do I just save them as .txt-files in my folders?
THX
I tried searching docker hub to find for antlr4 Images. As far I know, we don't have any official image as of now for antlr on dockerhub. Does anyone know, which is most suitable and standard image, preferable for JavaScript Parser related works?
I saw couple of image suggestions with individual account, but not sure which is reliable and robust enough.
Please don't suggest the general suggestions like, one with most downloads etc. is better. Please suggest if you have used or any other valid point you have.
ANTLR has a repo for docker image on Github:
This Docker image wraps current version of ANTLR4 inclusive Java
runtime environment so it can be executed as transparent command line
tool even on machines without installed Java.
https://github.com/antlr/antlr4/tree/master/docker
I started looking into docker lately and I understand a lot of the benefits it offers I think, you can quickly create a docker container and run it on different machines. Building (compiling) is also relatively easy, you can download the maven image for example and just build your code. That works fine. So, building is easy, testing is easy and deploying (and running) in production is easy.
What I don't understand is how docker can make the development phase easier. And what I mean with the development phase is, starting up your IDE, reading code, quickly navigate through your methods definition using the methods the IDE provides, use intelliSense, etc. Then change something, run a unit test, try a different third party library, etc. All things you can do with your IDE. But I don't understand how to do this with a docker image. I've read a few posts about starting the IDE from within your docker container, but that requires setting things up with a windows manager and I am not sure if that's the way to go.
Of course I can set up my laptop in such a way that I can do all of this with my IDE, but that way I bypass all of the benefits docker should offer. I still have to download dependencies, set up environment variables, do a lot of manual settings etc. And not just me, but everyone in the team.
So, not a very concrete question, possibly a duplicate, but I just can't wrap my head around it, how to use an IDE together with docker?
Yeah it's hard. It also depends on what language/framework you're using. But the things you mention are all easy to accomplish. For example we use Ruby a lot and someone in my team uses RubyMine to work with his code. That source code is mapped onto the container so the changes are reflected immediately. If you want to run a test, I'm sure you can override the command your IDE brings by default with something custom like docker run --rm myapp ./run_tests.sh or similar. At least that's what I do with VIM.
Probably the most important missing part when doing dev with Docker is debugging. I think JetBrains is starting to add features to their IDE's but I'm not sure on the status of that.
Also, almost every IDE or good editor has an integrated console. You could maintain a docker exec sessions opened there and run all your app commands, like tests, generators or any other. Even do some basic debugging.
Hope it helps.
I used to use ipython notebook for displaying equations while using simpy module. As can be seen from the figure below it is neat and elegant.
It seems I have made some updates and I no more have ipython notebook; every time I run it, it switches back to Jupyter (I guess that is a new name after 4). Unfortunately, printing equation doesn't work as it used to yet I can type latex as Markdown text(see figure below). Am I missing something?
So finally it is working thanks to this reddit post. I just needed to update sympy module.
pip install -U sympy
I am having problems saving the Python code in Anaconda. I write code, Go to File Save as the file is saved but when I open it is empty, no code. I read that IDLE does not save code, it erases it when I close Anaconda.
I have searched in books, youtube tutorials and nothing. I could not find this topic. I can find advanced topics, but this one no.
Thank you for your help!
Best,
Tiberiu
This somewhat depends on what OS you are on. I can speak from my experience. I would highly recommend using PyCharm as an IDE.
But more fundamentally than that, lets talk about saving files. On Mac OS X or Ubuntu 14.04 (or the like), lets say you want to create a python file. One way is to do the following in a terminal:
nano hello.py
This opens up a text editor whose instructions for use are on the bottom of the screen. On Windows you could do:
notepad hello.py
In both cases you then write your code. Lets say the content was:
#content of hello.py
print "Hello World!"
Then you need to save the file and execute it with Python.
Which brings us to the Python issue.
Once you have installed Anaconda, and assuming that there are no other Python installations on your computer. The Anaconda Python should be the active Python on system.
Suffice to say that there are other ways of saving files rather than using IDLE. Personally I have found PyCharm to be a much better IDE for writing Python code.
To address the IDLE issue more directly once you type in the terminal/command prompt idle to launch an IDLE session, likely the IDLE Shell will open up. Perhaps you are trying to save this, in which case you will only save the Shell session.
So go to File - New - Save. This should work without any problem (it does on my system). Good luck! Hope this helps.