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Joined EatingHabits as CTO

Very recently, I've started a new journey by joining a Barcelona based startup, EatingHabits, as the Chief Technology Officer (CTO).

I'm actually the technical co-founder of the startup, where my job is basically to handle all the tech related stuff, and making sure everything is properly synchronized as far as the tech stack is concerned.

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Dear Developers, Let's bring some empathy to the table!

I won't probably be too wrong to say that, System administration is probably the most underappreciated and thankless genre among work units in any software development organization nowadays. So let’s talk about that in urging the snarky developers to change their point of view towards fellow system administrators.

We're living in the era of web applications, and almost all softwares are run on the someone else’s computer AKA cloud. So, software engineering/development has changed a lot; we've come from developing host-native apps to developing cloud-native apps. To keep up the pace, System administration has changed a lot as well; from manually building systems from scratch, we've introduced fully automated system building, packaging and what not!

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Python : Can we use magic/dunder methods as instance attributes directly instead of putting them in type definition?

No, we can't.

The magic/dunder methods are looked up implicitly on the type definition while special functions, keywords, or operators are to be resolved by the runtime. They don't follow the regular attribute lookup procedure i.e. doesn't follow the __getattribute__ chain. This makes them fast to access as the runtime only needs to search on the type, not on instance dict.

So, what about classes themselves? What dunder methods should be used when any special function is called on them?

As any class is an instance of a metaclass, the dunder methods defined on the metaclass would be used.


Let's see a few examples to get a clear overview of all these. We'll be using the repr function, for which the interpreter will call __repr__ dunder method implicitly, in order to get the representation of an object.

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Why exception name bindings are deleted while exiting the `except` block in Python, and how to break reference cycles in traceback object's stack frame local namespace

Why exception name bindings are deleted while exiting the except block?

TL;DR: To prevent the creation of reference cycles.

Traceback object attached with any exception object has a stack frame of execution containing the local, global, builtin namespaces, the code object, and other necessary entities attached. This might seem complex at first but when we follow the attribute chain to get a higher level view, it would be easier to reason about.

Let's define a simple function that will do thing but return an intentionally raised exception (which is a bad idea, i'll explain the why in a jiffy):

def foobar(num):
    spam = 'egg'
    baz = num
    try:
        raise RuntimeError
    # Bind `RuntimeError` object to name `exc`
    except RuntimeError as exc:
        return exc

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Async `requests` in Python : Do async I/O on a blocking object

After the introduction of the send method of generators in Python 2.5, it was possible to send values into generators, essentially making them a two-way object. This leads to the possibility of single-threaded coroutine-based co-operative multitasking. Before 3.5, one could create a coroutine by the asyncio.coroutine (or types.coroutine) decorator, and pause a coroutine (when doing I/O) by using yield from which basically is a syntactic sugar for yield-ing values from another generator (using a for loop, for example).

In Python 3.5, the async-await keywords were introduced to support the Async operations natively, with:

  • The async keyword replaces the need for an explicit decorator to create a coroutine
  • The await is just a syntactic sugar for yield from

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Brief intro to `strace` : Finding all files a process is opening in GNU/Linux

Many times while debugging, we need to find all the files (e.g. shared libraries, configuration files, caches, logs, dumps, state files, journals, and so on) a process is opening for reading data from to get hints about the program's design and workflow.

Otherwise we want to follow the lengthy route of reading the source code of the program, we could leverage the powerful system call tracing tool strace to get the job done fairly easily.

Background:

strace binary comes with the strace package; so we need to install it first (if not done already):

% dpkg -S "$(command -v strace)"
strace: /usr/bin/strace

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Nightwatch.js Selenium e2e test: input field clearing issue

While doing e2e (end to end) tests for Dealiable.com frontend (Vue.JS), i've bumped into something interesting, which was really fun to fix/find a workaround of.

Firstly, for e2e tests, i've used Nightwatch.js, which uses the Selenium API, and is written in Node.js.

The problem was that, I was not being able to clear some input tag field data using the API provided by Nightwatch -- browser.clearValue. For example:

browser.clearValue('input[type="text"]')

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Intrepid Inceptions : The Inception

So, it happened! My long plan of putting the projects I'm working on (and potentially the future ones) under the same umbrella has come into existence -- introducing Intrepid Inceptions, the startup/company/brand (in the usual term) that will be used formally behind all my projects.

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Introducing Dealiable.com!

My recent work, Dealiable.com, has entered the public beta phase and will be stable soon! The domain was registered on 29 June, 2018 (Friday) and then made public the same day. This was a really fun one work on, with so many challenges, so many corner cases, and so many more to come and tackle. But it feels really awesome to get this piece of work rolling and seeing people appreciating the idea and work.

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