Spyder is a program ( or App, or Application ) on you computer ( we are going to use full fledged computers, Windows, Mac, or other but not Phone or Tablets ) that help you write Python Programs. Spyder is an IDE and a nice installation of Python to boot. There are many other ways we could get set up to write Python programs, but for SCILs Python course we are going to assume that this is what you will use.
A Brief FAC
- What is an IDE and why should I care? An IDE is an integrated development Environment, it is a software setup that ( for Python ) makes it easier to write, run and debug Python programs.
- How much does it cost? Usually nothing, although there are some IDE's that do require you to purchase a license. We will stick to free stuff.
Spyder from Anaconda: Why this choice?
- You get a pretty good IDE thrown in for free, in our teaching documentation we will assume that this is the environment you are using.
- You get a basic installation of Python plus a whole range of extensions that would otherwise be tedious to install.
- Installation works on all major operating system.
- In our experience installation process is simple.
- Spyder appears to be well maintained and regularly updated.
For now we will use Python 2.7, at this time ( Aug 2016 ) it seems to be a bit better documented and supported than the newer, and in the long run probably better Python 3.x.
You should have your computer and a good internet connection. Installation takes (?) about half an hour, mostly waiting for the computer to do something.
Russ will write this. If you have some experience just Google Spyder Install and ....
I like the Anaconda site for download.... [Anaconda 4.1.1] Use Python 2.7 version and select 32 or 64 bit to fit your system. Save the file somewhere you can find it.
Run the file you saved earlier. Your web browser may help, or just double click on the file from your file manager. Follow the prompts. I will try to do this soon and add some instructions here. You may also find this useful:
With luck you will find an Icon on your desktop, if not use the start menu to search for Spyder.
Russ does not have an Apple so is unsure of the details, but it is pretty much the same as Windows:
- Run the Download to Install
- Spyder is installed run it from your desktop or start menu
Anyone want to help? Its a Wiki...
Download and Install
Most Linux system now have some sort of GUI based package management system.
In my Linux Mint it is Software Manager, so you would:
- Open Software Manager
- Spyder and see the result "spyder ide for scientists" or something similar
- Have the Software Manager Install
Click on the Icon or find in your menu system
If the Install Does Not Work
If the install does not work this may be an occasion where a hands on with your instructor will help. In any case call or email.
Advanced Topic Multiple Versions
Coming soon when it works for me. So I had spyder < 3 and python 2.7 wanted spyder 3 and python 3.6. This involves creating a new environment, and a utility that lets you switch environments. This is what worked for me.
In a dos window ( cmd )
conda create --name python3_spyder3 python=3.6 anaconda
Which does what?
- create the new environment with the name python3_spyder3
- use python 3.6 ( python=3.6 )
- install the package anaconda ( anaconda ) -- as far as I can tell you must install some package to get a new environment.
At the end of a long install I got this useful information:
# To activate this environment, use: # > activate python3_spyder3 # # To deactivate this environment, use: # > deactivate python3_spyder3
After activating the environment my windows menu still opened the old spyder/python. To get the new version I again used cmd and
activate python3_spyder3 spyder
Should be easy to create a bat file and shortcut to execute this.
- FAQ — Conda documentation
- Anaconda Overview | Continuum
- Presentations & Blog Posts — Conda documentation
- Python « Steve Byrnes's Homepage
- Installation — Spyder 2.3 documentation
- Installation of Python, Spyder, Numpy, Sympy, Scipy, Pytest, Matplotlib via Anaconda (2013) — Computational Modelling Blog
- Anaconda FAQ | Continuum Analytics: Documentation
- Anaconda install | Continuum Analytics: Documentation
- Download Anaconda Now! | Continuum
- Installing Jupyter Notebook — Jupyter Documentation 4.1.1 alpha documentation