Quick and easy packages list

I created a new project and knew at some point I would have to look into how requirements.txt files are created. I'm still in the early stages of the project though, so I didn't really look into it. As luck would have it, I accidentally came across it while looking up something else. It's so easy! All I have to do is run a command while my virtual environment is active.

pip freeze > requirements.txt

Running the command pip freeze alone would list out all the third party packages that have been installed along with their version numbers. Using the command above puts it all into a file named requirements.txt. Technically I could name the file anything I want but it appears to be convention to name it thus. This way, anyone who clones your project can easily install the packages and run the project.

Reference: https://towardsdatascience.com/virtual-environments-104c62d48c54

Comments

Deviants in a normal world

It's definitely been a bit since I've seen this graphy. Anyone who has learnt about standard deviation knows this graph. Standard Deviation Standard deviation shows us how spread out all the values in a set are from the mean. The higher the standard deviation, the more spread out the values are over a wider range and the flatter this curve. In a normal distribution, most values are within 1 standard deviation from the mean(the green part of the graph). Apparently NumPy can calculate standard deviation too! import numpy numSet = [ *lots of numbers* ] numSetStdDev = numpy.std(numSet) Variance The variance also indicates how spread out the values in a set are. It measures the average degree to which each value differs from the mean. variance = standard deviation ^2 import numpy numSet = [ *lots of numbers * ] numSetVar = numpy.var(numSet) Source: https://www.w3schools.com/python/python_ml_standard_deviation.asp

I gotta feeling...

I've been helping a colleague with his portfolio site. He's making it retro video game themed at my suggestion. He found an interesting pixelated font called arcade classic and used it for the headings on his page. Unfortunately, some of the letters almost overlapped, making it not quite readable. Before letter spacing I looked into typography ages ago and learnt about letter and word spacing and wondered if that was something that I could fiddle with using CSS. Turns out it is a property you can customise. I opened up Chrome Dev tools and added 3 pixels of letter spacing and it looked so much better. And there's letter spacing too, so that's pretty neat. After letter spacing Can't say CSS is my favourite thing ever but it's always nice to learn something new in unexpected ways.

Snakes and ladders

I've started on my Python course. So far, the code has been familiar because the first few basic codes are similar to Javascript. And then modules happened. Confusion and despair! What is the world is 'if __name__ == "__main__": ' and why must I reach this section of my course on a public holiday when none of the instructors are in :( Stack overflow to the rescue, providing me a lifeline while I was drowning in a pit of serpents. I feel eternally indebted to a particular Mr Fooz. Picture from here From my understanding, when the Python interpreter reads a source file, it first sets the variable __name__ and then it executes all the code in the file. If that particular file that you are running(i.e. your module) is the main program, the interpreter will assign '__name__ = "__main__" '. Thereafter, any code in the aforementioned 'if' statement is run. If you have, instead, imported a module, the interpreter assigns '__name__ ...

I do it for my cat

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