
Boostero is a social media marketing (SMM) panel, a single dashboard where creators, brands, and agencies grow across 23+ platforms including Instagram, TikTok, YouTube, Facebook, X, Spotify, Telegram and LinkedIn. Followers, likes, views and engagement are ordered from one place instead of one network at a time.
Operating since 2020 from Delaware, Boostero has delivered over 12 million orders for 211,000 registered users in 125+ countries, across 1,600 services, with localized pages for 19 markets and 16 languages plus English.
What separates it is what is visible before you pay: the price per 1,000, the minimum and maximum order, the refill terms and an average delivery time computed from completed orders are all shown on the service itself, not promised site-wide. Ordering needs a public link or username, never a password.
Key features:
23+ platforms and 1,600 services in one dashboard
Service quality tiers and refill terms stated on each service before checkout
Average delivery time shown per service, computed from completed orders
REST API with ten documented calls and examples in PHP, Python, Node and curl
White-label child panels for agencies and resellers
Payments: cards, PayPal, cryptocurrency, Payoneer
24/7 support via Telegram, email and the ticket system
Encrypted checkout, no password required
Learn more

SurveyJS is a set of four open-source JavaScript libraries that offer the benefits of a tailor-made in-house survey application, while considerably reducing the time and resources needed to deploy the system. These libraries are independent of specific server code or database requirements and seamlessly integrate with popular JavaScript frameworks, including React, Angular, Vue.js, jQuery, Knockout, and more. They are designed to communicate with any server that can handle JSON requests, ensuring compatibility with various server architectures and databases.
The product family is composed of:
- An open-source MIT-licensed rendering library that renders dynamic JSON-based forms in your web application, and collects responses.
- A self-hosted drag & drop form builder that features an integrated CSS-based theme editor and a GUI for conditional rules. It automatically generates JSON definitions (schemas) of your forms in real time.
- PDF Generator, a library that renders SurveyJS surveys and forms as PDF files in a browser;
- The Dashboard library that allows you to simplify survey data analysis with interactive and customizable charts and tables.
Visit our website to try out and evaluate our full-scale demo for free.
Learn more
broot
The ROOT data analysis framework is widely utilized in High Energy Physics (HEP) and features its own file output format (.root). It seamlessly integrates with software developed in C++, while for Python users, there is an interface called pyROOT. However, pyROOT has compatibility issues with python3.4. To address this, broot is a compact library designed to transform data stored in Python's numpy ndarrays into ROOT files, structuring them with a branch for each array. This library aims to offer a standardized approach for exporting Python numpy data structures into ROOT files. Furthermore, it is designed to be portable and compatible with both Python2 and Python3, as well as ROOT versions 5 and 6, without necessitating changes to the ROOT components themselves—only a standard installation is needed. Users should find that installing the library requires minimal effort, as they only need to compile the library once or choose to install it as a Python package, making it a convenient tool for data analysis. Additionally, this ease of use encourages more researchers to adopt ROOT in their workflows.
Learn more
Mako
Mako offers a user-friendly, non-XML syntax that compiles into Python modules, ensuring optimal performance. Its syntax and API draw inspiration from various sources, such as Django, Jinja2, Cheetah, Myghty, and Genshi, integrating the best elements from each. At its core, Mako functions as an embedded Python language (akin to Python Server Pages), enhancing conventional concepts of componentized layout and inheritance to create a highly efficient and adaptable model. This design maintains a close relationship with Python's calling and scoping semantics, allowing for seamless integration. Since templates are ultimately compiled into Python bytecode, Mako's methodology is remarkably efficient, having been designed to match the speed of Cheetah initially. Presently, Mako's performance is nearly on par with Jinja2, which employs a similar technique and was influenced by Mako. Furthermore, it can access variables from both its enclosing scope and the request context of the template, providing additional flexibility for developers. This capability allows for greater dynamic content generation in web applications.
Learn more