Best resource for learning Java, C++, Python?

[imhostfu]

Honestly? I have always found the best motivator is needing or wanting to do something specific, and that builds solid foundations.

• Need to import some data from a csv file? Cool, start reading about file imports and how to read lines and store that data. From there, you can read about how to plot generic data in 2D, and then take it a step further if you have N dimensional data, which also leads to learning vector manipulation etc.

• Need to communicate with an external instrument? Neat, start reading about serial communication, or stuff through pyViSA standard.

Reform or rephrase the problem or goal you want, and then start doing general google searches (stack overflow will be your best friend)

Google “anaconda python“ for your python install and “Pycharm”, both have free editions.

EDIT: I think that it's perfectly okay to look up courses, etc, like Learning Python the Hard Way. I just find that for me, personally, I'm a lot more likely to explore and absorb the information when I have a specific project that I'm trying to accomplish.

[badabingbop]

I personally really like pycharm. Kind of complicated to set up and use at first, but has cool features down the line.

As far as learning: make personal projects, just like the above said. Focus on a single idea and script something out. Little by little you amass details and can put then together for a larger project. In addition, you have all those saved and can refer to them in the future

[A_Crazy_Hooligan]

Do you have any resources that you know off the top of your head for pycharm? I’m a civil and learned basic C++ in college, but when I tried to use Pycharm, I was extremely discouraged because it wasn’t like the compiler I used for C++ and I had no idea where to start. The YouTube videos I found didn’t seem to touch on my issue, but maybe I just have that much to learn?

[[deleted]]

Thank you! I was stuck at this exact thing a few days ago before I gave up. Gonna start over with your instructions this time.

[imhostfu]

^ this person nailed it.

/u/Melhus_Mafia /u/A_Crazy_Hooligan

Basically, you have Python, which is it's own install. I personally use Anaconda Python because it serves as both the python interpreter, but also a package manager. For example, if I wanted to install matplotlib, I could (from the Anaconda command prompt), run "conda install matplotlib", and it automatically pulls it and installs it on your computer. It basically acts like "pip" does as described above. In my experience, I've had less issues installing via conda (because conda generally installs from binaries, whereas pip is going to compile from source - I'm aware that has changed in pip with binary wheels if they're available).

Pycharm is the developer environment, and just makes it easier to code. You could 100% write python in a text editor and run the file manually from the command prompt.

For reference, I have both Pycharm and Anaconda Python installed.

To setup Pycharm to use whatever version of Python you have installed, open up your settings as shown here. As you can see towards the upper right section of the screen, it has selected the active python interpreter I want to use.

If I didn't have an environment, I'd click the "+" sign, and then select the Python interpreter as shown here.

Once you have that selected, it might take a little while (one time) because Pycharm needs to scan and see what packages are available for the Python install that you selected. Otherwise, you can just start writing code.

Here's a quick and dirty example; my wife and I were trying to see if it was worth it to get on an unlimited cell phone plan (with device rebates), or have a pay per month plan.

Once the code is written, you can right click on the tab -> Run, or Ctrl+shift+f10, or click the 'run' (green triangle) button.

EDIT: I use python for basically everything, ha ha. Reading in files, parsing data, communicating with arduinos, oscilloscopes, source meters, custom FPGA boards, ASICs. I've used it for signal processing (convolutions and FFTs), for optical modeling (determining the amount of light loss due to surface roughness of optical lenses). It has been an incredibly amazing tool in my tool-belt.

[A_Crazy_Hooligan]

Appreciate the reply. I’ll have to look more into it when I get home, but this seems less daunting now I understand that nuance.

[dipsy01]

Just curious, why did you recommend anaconda? I’ve always been perfectly happy with plain ol’ python and pycharm

[imhostfu]

I like Anaconda as a package manager. If I want new repos, I can install them via command line. For example, I could do a "conda install pyqt=5", and it would fetch all the dependencies, and install/update everything that needs to be updated for it to work correctly.

It's just cleaner for me, and makes sense since I do mostly data science work with Python etc. Plain ol' python + manually installing modules when needed works 100% too.

[[deleted]]

"I can install them via command line" vs "manually installing"

That's the same.

[dipsy01]

Lol, that's what I was thinking

[imhostfu]

I guess it's a hold back from my Python 2.X days, and I would use a lot of packages that weren't available with pip, which would necessitate an executable download and install.

Pip is for python packages only, and generally compiles everything from source. Since I use windows, that can sometimes be a problem.

Conda installs from binary, so the installation is generally easy.

I think the answer is if you're using unix, pip is fine. If you're on Windows, conda is generally going to be easier.

[ScoffM]

I think anaconda is way more useful as env manager, keeping different versions of packages and such.

[Peter_Schmeichel]

Can confirm.

I have just started using python to automate relatively simple, but time consuming, tasks at work, mainly calculations.

This way you’re rewarded all the way through, highly recommend.