In comparison, Perl/Python/Javascript, which also have the latter property, have other false-like values (0 and empty string), which make || differ from a null-coalescing operator in many more cases (numbers and strings being two of the most frequently used data types). This is what led Perl/Python/Javascript to add a separate operator while Ruby hasn't.

Say goodbye to the headaches of setting up Python locally. No more installations or configurations, you can execute Python code right in your web browser. Just input your code, hit RUN, and watch the magic happen! Compile, run, and share Python code online with our powerful integrated Python development environment (IDE). Want to show off your work? Use the SHARE option to make your code accessible to anyone, anywhere.

What are the tools that comes on your mind when someone say “debug”? Let me guess: a memory leak detector (e.g. Valgrind); a profiler (e.g. GNU gprof); a function that stops your program and gives you a REPL (e.g. Python’s breakpoint and Ruby’s byebug); something that we call a “debugger” (like GDB, or something similar embedded on the IDEs); or even our old friend, the print function. So, in this text I’ll try to convince you to add Git to your debug toolbelt.

How can I add, subtract, and compare binary numbers in Python without converting to decimal?

'handlers': { 'console': { 'level': 'INFO', 'class': 'logging.StreamHandler', 'stream': sys.stdout, 'formatter': 'verbose' }, },

16 August 2011

So why aren't more people using Nim? I don't know! It's the closest thing to a perfect language that I've used by far.

What object-oriented means

The difference between object-oriented design and object-orientedprogramming

SSL is disabled by default in jdbc, npgsql, node-postgres, and pgx.

What is not OK is what I perceive as the dominant attitude today: sell SciPy as a great easy-to-use tool for all scientists, and then, when people get bitten by breaking changes, tell them that it’s their fault for not having a solid maintenance plan for their code.

Then, if the string can be represented as ASCII, only one byte of memory is used per character. If the string uses more extended characters, it might end up using as many as 4 bytes per character. We can see how much memory an object needs using sys.getsizeof()

Using named arguments is nice for languages that support it, but this is not always a possibility. Even in Python, where time.sleep is defined with a single argument named secs, we can’t call sleep(secs=300) due to implementation reasons. In that case, we can give the value a name instead.Instead of this:time.sleep(300)Do this:sleep_seconds = 300 time.sleep(sleep_seconds)Now the code is unambiguous, and readable without having to consult the documentation.

Python

you want to pass a function as an argument to higher-order functions

You can use container values, that wraps actual success or error value into a thin wrapper with utility methods to work with this value. That’s exactly why we have created @dry-python/returns project. So you can make your functions return something meaningful, typed, and safe.

I'm not a fan of listing exceptions functions can throw, especially here in Python, where it's easier to ask forgiveness than permission.

Turning my Jupyter-compatible Python code into Flask-compatible Python code took dozens of hours. I ran into small bugs and errors

use code to parameterize calls:

python -c "
from mymodule import set_dragon_feeding_schedule, Creatures, Date
set_dragon_feeding_schedule(
    feeding_times=['10:00', '14:00', '18:00'],
    dishes={Creatures.Tiger: 2, Creatures.Human: 1},
    start_day=Date('1020-03-01'),
)
"

python -m mymodule \
    set_dragon_feeding_schedule \
    --feeding-times ['10:00','14:00','18:00'] # hopefully this way it gets recognized \
    # how will you define parsing a dict with enum to integer mapping? 
    --dishes=Creatures.Tiger:2 \
    --dishes=Creatures.Human:1 \
    --start-day=1020-03-21 # BTW bash allows no comments in multiline calls

That’s it. Types are parsed, checked and converted. Defaults and description are picked from function itself. Even provides bash completions you can install. You wrote no code for that!

import typer
from pathlib import Path

app = typer.Typer()

@app.command()
def find_dragon(name: str, path: Path, min_age_years: int = 200):
    <implementation goes here>

@app.command()
def feed_dragon(dragon_name: str, n_humans: int = 3):
    <implementation goes here>

if __name__ == "__main__":
    app()

python example.py find_dragon 'Drake' --path /on/my/planet

in Python - setting up basic logger is very simple

import logging
logging.basicConfig(
    filename='application.log',
    level=logging.WARNING,
    format= '[%(asctime)s] {%(pathname)s:%(lineno)d} %(levelname)s - %(message)s',
    datefmt='%H:%M:%S'
)

logging.error("Some serious error occurred.")
logging.warning('Function you are using is deprecated.')

[12:52:35] {<stdin>:1} ERROR - Some serious error occurred.
[12:52:35] {<stdin>:1} WARNING - Function you are using is deprecated.

logging.getLoggerClass().root.handlers[0].baseFilename

Programming languages These will probably expose my ignorance pretty nicely.

In Python, when trying to do a dubious operation, you get an error pretty soon. In JavaScript… an undefined can fly through a few layers of abstraction, causing an error in a seemingly unrelated piece of code.

function add(a,b) { return + (a + b) }
add(2,2)
add('2', 2)

Sometimes, the best way to learn is to mimic others. Here are some great examples of projects that use documentation well:

Class method docstrings should contain the following: A brief description of what the method is and what it’s used for Any arguments (both required and optional) that are passed including keyword arguments Label any arguments that are considered optional or have a default value Any side effects that occur when executing the method Any exceptions that are raised Any restrictions on when the method can be called

From examining the type hinting, you can immediately tell that the function expects the input name to be of a type str, or string. You can also tell that the expected output of the function will be of a type str, or string, as well.

def hello_name(name: str) -> str:
    return(f"Hello {name}")

Docstrings can be further broken up into three major categories: Class Docstrings: Class and class methods Package and Module Docstrings: Package, modules, and functions Script Docstrings: Script and functions

Docstring conventions are described within PEP 257. Their purpose is to provide your users with a brief overview of the object.

All multi-lined docstrings have the following parts: A one-line summary line A blank line proceeding the summary Any further elaboration for the docstring Another blank line

"""This is the summary line

This is the further elaboration of the docstring. Within this section,
you can elaborate further on details as appropriate for the situation.
Notice that the summary and the elaboration is separated by a blank new
line.

# Notice the blank line above. Code should continue on this line.

say_hello.__doc__ = "A simple function that says hello... Richie style"

def say_hello(name):
    print(f"Hello {name}, is it me you're looking for?")

say_hello.__doc__ = "A simple function that says hello... Richie style"

def say_hello(name):
    """A simple function that says hello... Richie style"""
    print(f"Hello {name}, is it me you're looking for?")

>>> help(say_hello)

Help on function say_hello in module __main__:

say_hello(name)
    A simple function that says hello... Richie style

class constructor parameters should be documented within the __init__ class method docstring

Scripts are considered to be single file executables run from the console. Docstrings for scripts are placed at the top of the file and should be documented well enough for users to be able to have a sufficient understanding of how to use the script.

Documenting your code, especially large projects, can be daunting. Thankfully there are some tools out and references to get you started

Along with these tools, there are some additional tutorials, videos, and articles that can be useful when you are documenting your project

If you use argparse, then you can omit parameter-specific documentation, assuming it’s correctly been documented within the help parameter of the argparser.parser.add_argument function. It is recommended to use the __doc__ for the description parameter within argparse.ArgumentParser’s constructor.

There are specific docstrings formats that can be used to help docstring parsers and users have a familiar and known format.

Daniele Procida gave a wonderful PyCon 2017 talk and subsequent blog post about documenting Python projects. He mentions that all projects should have the following four major sections to help you focus your work:

Since everything in Python is an object, you can examine the directory of the object using the dir() command

Documenting your Python code is all centered on docstrings. These are built-in strings that, when configured correctly, can help your users and yourself with your project’s documentation.

Along with docstrings, Python also has the built-in function help() that prints out the objects docstring to the console.

The general layout of the project and its documentation should be as follows:

project_root/
│
├── project/  # Project source code
├── docs/
├── README
├── HOW_TO_CONTRIBUTE
├── CODE_OF_CONDUCT
├── examples.py

In all cases, the docstrings should use the triple-double quote (""") string format.

Since we have much faster CPUs now, numerical calculations are done in Python which is much slower than Fortran. So numerical calculations basically take the same amount of time as they did 20 years ago.

Python unit testing libraries, like unittest, can be used within a notebook, but standard CI/CD tooling has trouble dealing with notebooks for the same reasons that notebook diffs are hard to read.

All you can do is send a message (AYCDISAM) = Actors model - there is no direct manipulation of objects, only communication with (or invocation of) them. The presence of fields in Java violates this.

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Python was created by Guido Van Rossum in the early 90s. It is now one of the most popular languages in existence. I fell in love with Python for its syntactic clarity. It’s basically executable pseudocode.

The goal of this site is to provide a set of materials in support of my Python for Informatics: Exploring Information book to allow you to learn Python on your own. This page serves as an outline of the materials to support the textbook.

The hard part is teaching the consequences of each choice.

Three things are required to fully guarantee a repeatable installation using requirements files.