Category Archives: Programming

Spyder on MX Linux

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This is another example that non-commercial (open-source) Linux/Python does not have a feel of a finished product: things break out of the box when installed fresh, in the most simple, expected ways, without any tweaks.

Again, don’t get me wrong, open-source free software are good stuff (more modern concepts and people working on it for free), but it’s never going to beat professional companies (like Microsoft/MATLAB) in how well-funded they are so they can maintain their software and the user experience using their profits. So far, users are still expected to put up with a bunch of unjustifiably unnecessary work to get to where they want to go with community-maintained software like Linux/Python.

This time I’m installing Spyder on MX Linux. Look at how many damn hoops I have to jump to get Spyder 3 to function properly there:

  1. I installed python3-spyder from MX Package Installer
  2. Spyder complained about missing rope on start
  3. Installed python-rope on MX Package Installer. The complaint still won’t go away
  4. I tried follow the instruction sudo pip3 install rope_py3k  and realized pip3 was not installed already with the Python that came with Spyder! (Didn’t have the problem with the Windows counterpart).
  5. Installed python3-pip from MX Package Installer.
  6. Came back and run pip3 install rope_py3k. It choked at "Command 'python  setup.oy egg_info' failed with error code 1 in /tmp/pip-build-0nnknjhi/rope-py3k". Again, known problem.
  7. Followed the solution in the comments pip3 install --upgrade setuptools
  8. Then come back and run pip3 install rope_py3k again. It says "Failed building wheel for rope-py3k" in between, but nonetheless I’ll try to move on since it says "Successfully installed rope-py3k-0.9.4.post1"

Then Spyder launch uneventfully.

These are not design decisions (sacrificing one quality for another), but inter-operability wrinkles that nobody are paid enough to do the grunt-work babysitting it. So if your business profits heavily from it, consider sponsoring the developers!

It’s also slightly annoying that the version of Spyder maitained in MX Linux’s most recent repository is a little older than what’s actually available (3.1.3+dfsg1-3 instead of 3.3.4).

At first I followed instructions to have PIP to update it: pip3 install -U spyder, but it doesn’t work. I got a lot of “failed building wheel for (package)” error.

I also realized the Python that came with it is 3.5, not the 3.7(.3) I had in Windows. I checked the MX package manager and indeed it stopped at 3.5. After some searching, I learned the base system package was frozen in 2016! MX Test Repo (at your own risk) has Python 3.7 though.

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Watch out for ‘const’ method in Python

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One thing I feel a little bit not quite as intuitive when I switch to Python is I constantly have to look up whether the method directly updates the contents or it’ll return a different object (of the same type) that I’ll have to overwrite the input variable myself.

An example would be strings and bytes object. replace() sounded like an updating method, but it’s actually a ‘const’ method (a term borrowed from C++ to say that the method does not have side-effects) that does not change the state of the object.

I initially thought this has to do with whether the object is immutable or not, but I tried it on bytearray objects (which is mutable), replace() behaves consistently with the identically named methods in other immutable objects (bytes object, string object): you’ll need to assign the output to self (basically bind the name to the temporary and throw away the original).

bts = b'test'
bts.replace('es', 'oas')       # dumps the output to workspace (can be accessed by _) and do nothing else
bts = bts.replace('es', 'oas') # actually updates bts

 

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Anonymous Functions (MATLAB) vs Lambdas (Python) Anonymous Functions in MATLAB is closure while Lambdas in Python are not

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Lambdas in Python does not play by the same rules as anonymous functions in MATLAB

  • MATLAB takes a snapshot of (capture) the workspace variables involved in the anonymous function AT the time the anonymous function handle is created, thus the captured values will live on afterwards (by definition a proper closure).
  • Lambda in Python is NOT closure! [EDIT: I’ll need to investigate the definition of closure more closely before I use the term here] The free variables involved in lambda expressions are simply read on-the-fly (aka, the last state) when the functor is executed.

It’s kind of a mixed love-and-hate situation for both. Either design choice will be confusing for some use cases. I was at first thrown off by MATLAB’s anonymous function’s full variable capture behavior, then after I get used to it, Python’s Lambda’s non-closure tripped me. Even in the official FAQ, it address the surprise that people are not getting what they expected creating lambdas in a for-loop.

To enable capture in Python, you assign the value you wanted to capture to a lambda input argument (aka, using a bound variable as an intermediary and initialize it with the free variable that needs to be captured), then use the intermediary in the expression. For example:

lambda: ser.close()      # does not capture 'ser'
lambda s=ser: s.close()  # 'ser' is captured by s.

I usually keep the usage of nested functions to the minimum, even in MATLAB, because effectively it’s kind of a compromised ‘global’ between nested levels, or a little bit like protected classes in C++. It breaks encapsulation (intentionally) for functions in your inner circle (nest).

It’s often useful for coding up GUI in MATLAB quick because you need to share access to the UI controls within the same group. For GUI that gets more complicated, I actually avoided nested functions altogether and used *appdata() to share UI object handles.

Functors of nested functions are closures in both MATLAB and Python! Only Lambdas in Python behave slightly differently.

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Python startup management

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The startup script is simply startup.m in whatever folder MATLAB start with.

Now how about Python? For plain Python (anything that you launch in command line, NOT Spyder though), you’ll need to ADD a new environment variable PYTHONSTARTUP to point to your startup script (same drill for Windows and Linux).

For Spyder, it’s Tools>Preferences>IPython console>Startup>”Run a file”:

but you don’t need that if you already have new environment variable PYTHONSTARTUP correctly setup.

 

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