Posts

  • Feb 22, 2021

    cli-ui

    Terminal user interface library

    gem install cli-ui

    or add the following to your Gemfile:

    gem 'cli-ui'

    In your code, simply add a require 'cli/ui'. Most options assume CLI::UI::StdoutRouter.enable has been called.

    Tags: #ruby

  • Feb 22, 2021

    pg-listen

    📡 PostgreSQL LISTEN & NOTIFY for node.js that finally works.

        📡  Send and subscribe to messages

        ⏳  Continuous connection health checks

        ♻️  Reconnects automatically

        ❗️  Proper error handling

        👌  Type-safe API

    Tags: #typescript • postgresql • nodejs

  • Feb 22, 2021

    investpy

    Financial Data Extraction from Investing.com with Python

    To get this package working you will need to install it via pip (with a Python 3.6 version or higher) on the terminal by typing:

    $ pip install investpy

    Additionally, if you want to use the latest investpy version instead of the stable one, you can install it from source with the following command:

    $ pip install git+https://github.com/alvarobartt/investpy.git@master

    The master branch ensures the user that the most updated version will always be working and fully operative so as not to wait until the the stable release comes out (which eventually may take some time depending on the number of issues to solve).

    Tags: #python • investing-api • historical-data

  • Feb 21, 2021

    pwntools-ruby

    pwntools on Ruby!

    Always sad when playing CTF that there’s nothing equivalent to pwntools in Python. While pwntools is awesome, I always love Ruby far more than Python… So this is an attempt to create such library.

    Would try to have consistent naming with original pwntools, and do things in Ruby style.

    Tags: #ruby

  • Feb 21, 2021

    yii2-export

    A library to export server/db data in various formats (e.g. excel, html, pdf, csv etc.)

    You can see detailed documentation and demonstration on usage of the extension.

    Tags: #php • spreadsheet • yii2

  • Feb 21, 2021

    magpie

    Deep neural network framework for multi-label text classification

    >>> magpie = Magpie()
>>> magpie.init_word_vectors('/path/to/corpus', vec_dim=100)
>>> magpie.train('/path/to/corpus', ['label1', 'label2', 'label3'], epochs=3)
Training...
>>> magpie.predict_from_text('Well, that was quick!')
[('label1', 0.96), ('label3', 0.65), ('label2', 0.21)]

    Tags: #python • neural-network • nlp

  • Feb 20, 2021

    Generamba

    This codegenerator is too brilliant to be real!

    • Supports work with .xcodeproj files out of the box. All generated class files are automatically placed to specific folders and groups of Xcode project.
    • Can generate both code itself and tests adding them to right targets.
    • Based on work with liquid-templates that have plain and readable syntax in comparison with templates for Xcode.
    • It is very easy to create a new module: generamba gen [MODULE_NAME] [TEMPLATE_NAME]. You do not need to input a bunch of data each time because each project corresponds to only one configuration file that holds standard file system and Xcode-project pathes, names of targets, information about the author.

    Tags: #ruby

  • Feb 20, 2021

    ballerina-lang

    The Ballerina Programming Language

    Ballerina is an open source programming language and platform for cloud-era application programmers to easily write software that just works.

    Tags: #java • programming-language • language

  • Feb 19, 2021

    graphql-modules

    Enterprise Grade Tooling For Your GraphQL Server

    • Reusable modules - Modules are defined by their GraphQL schema (Schema first design). They can be shared between apps.
    • Scalable structure - Manage multiple teams and features, multiple micro-services and servers.
    • Gradual growth - A clear, gradual path from a very simple and fast, single-file modules, to scalable multi-file, multi-teams, multi-repo, multi-server modules.
    • Testable - A rich toolset around testing, mocking and separation.

    Tags: #typescript • graphql • graphql-server

  • Feb 19, 2021

    reinforcement-learning-car

    Using reinforcement learning to teach a car to avoid obstacles.

    NOTE: If you’re coming here from parts 1 or 2 of the Medium posts, you want to visit the releases section and check out version 1.0.0, as the code has evolved passed that.

    This is a hobby project I created to learn the basics of reinforcement learning. It uses Python3, Pygame, Pymunk, Keras and Theanos. It employes a Q-learning (unsupervised) algorithm to learn how to move an object around a screen (drive itself) without running into obstacles.

    The purpose of this project is to eventually use the learnings from the game to operate a real-life remote-control car, using distance sensors. I am carrying on that project in another GitHub repo here: https://github.com/harvitronix/rl-rc-car

    This version of the code attempts to simulate the use of sensors to get us a step closer to being able to use this in the real world.

    Full writeups that pertain to version 1.0.0 can be found here:

    Part 1: https://medium.com/@harvitronix/using-reinforcement-learning-in-python-to-teach-a-virtual-car-to-avoid-obstacles-6e782cc7d4c6

    Part 2: https://medium.com/@harvitronix/reinforcement-learning-in-python-to-teach-a-virtual-car-to-avoid-obstacles-part-2-93e614fcd238#.vbakopk4o

    Part 3 (for this version of the code): https://medium.com/@harvitronix/reinforcement-learning-in-python-to-teach-an-rc-car-to-avoid-obstacles-part-3-a1d063ac962f

    Tags: #python

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