Python's versatility has made it a cornerstone of modern software development. Its frameworks and tools are integral to creating robust services and managing complex infrastructures. Among the myriad of Python frameworks, Django and FastAPI stand out for their distinct features and capabilities, making them popular choices for developing web services. Additionally, Python's extensive tooling ecosystem and ability to integrate with modern SaaS applications make it a very productive programming language.
According to the TIOBE programming index for the past several years Python is the world's most popular programming language.
The latest reports from Jetbrains indicate about 28% developers globally use Python as their No1 choice language.
For Netzary since inception Python was the language of choice for everything. We have used Python to built everything from this web site and previous avatars to most of our inhouse tooling systems. So whether it is Kora our ticketing system, or InfraOps our Unified Endpoint Management System, it’s core lies in Python.
We keep a strong set of developers whose proficiency in Python is off global standards. Some of our expertise lies in.
Django is a high-level Python web framework that encourages rapid development and clean, pragmatic design. Known for its "batteries-included" philosophy, Django provides a plethora of built-in features, such as an ORM (Object-Relational Mapping), authentication, and an admin panel, reducing the need for external libraries and boilerplate code. This makes it an excellent choice for developers aiming to build robust, scalable web applications quickly.
Django's ORM simplifies database interactions, allowing developers to write database queries using Python code instead of SQL. This abstraction not only enhances productivity but also ensures code readability and maintainability. Furthermore, Django's templating engine facilitates the creation of dynamic web pages by separating the HTML structure from the business logic, promoting the MVC (Model-View-Controller) design pattern.
Some of us have been using Django since 2004. We have delivered over 200 projects in Django over past decade
FastAPI is a modern, fast (high-performance) web framework for building APIs with Python 3.6+ based on standard Python type hints. Its main selling points are speed, both in terms of development and performance, and its automatic interactive API documentation.
FastAPI's speed is largely attributed to its use of asynchronous programming, making it an ideal choice for high-performance applications requiring real-time data processing, such as chat applications, games, or real-time dashboards. It leverages Python's asyncio library to handle concurrent requests efficiently, significantly outperforming traditional synchronous frameworks.
Moreover, FastAPI’s automatic generation of interactive API documentation using Swagger UI and Redoc enhances developer productivity. The framework’s ability to validate, serialize, and deserialize data using Python type hints reduces bugs and streamlines development.
Apache Airflow is an open-source platform for orchestrating complex workflows and data pipelines. Written in Python, it allows developers to programmatically author, schedule, and monitor workflows. Airflow's flexibility comes from its use of Python code to define tasks and their dependencies, which can be extended with custom Python operators, hooks, and plugins to integrate with various data sources and services. We can help you extend Airflow functionality
PyTorch, a leading machine learning library, is known for its dynamic computation graph and ease of use in Python. Developed by Facebook's AI Research lab, PyTorch is widely used for deep learning applications. Python's compatibility with PyTorch enables developers to create custom neural network layers, perform tensor computations, and leverage GPU acceleration, making it a favorite among data scientists and researchers.
Apache Spark is a unified analytics engine for large-scale data processing. Although originally written in Scala, PySpark, the Python API for Spark, allows users to write Spark applications using Python. This integration provides the benefits of Spark's powerful distributed data processing capabilities while leveraging Python's extensive data science libraries, such as Pandas and NumPy, for enhanced data manipulation and analysis.
We can help you process gargantuan data sets with Apache Spark
OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning software library. Although the core library is written in C++, it has a comprehensive Python API that allows for easy integration and extension. Python's use with OpenCV facilitates rapid prototyping and development of computer vision applications, from image and video processing to complex object detection and recognition systems.
Netzary can help you develop applications with OpenCV at core for various applications across use cases such as Surveillance, Monitoring, Discovery among others.
SaltStack is an open-source automation and configuration management tool. Written in Python, it uses a high-speed communication bus to provide real-time automation and remote execution capabilities. SaltStack's modular design allows developers to extend its functionality with custom Python modules, enabling sophisticated automation workflows and seamless integration with other systems and services.
Deep inside our product InfraOPs, we use Salt for automation.
Ansible is another open-source tool for IT automation, configuration management, and deployment. It uses Python extensively for its core engine and modules. Ansible's playbooks, written in YAML, allow for defining automation tasks, while Python is used to develop custom modules and plugins, providing flexibility and extensibility in automating complex IT operations across diverse environments.
We have customers using over 1000 Ansible templates for automation.
Prometheus is an open-source monitoring and alerting toolkit designed for reliability and scalability. While Prometheus itself is written in Go, it has Python clients and libraries that facilitate integration with Python applications. These clients allow developers to instrument their code, expose metrics, and query data from Prometheus, enabling comprehensive monitoring and analysis of Python-based systems.
We do write plugins for Prometheus for tasks which are fairly complex.
Wazuh is an open-source security monitoring platform that integrates with the ELK Stack (Elasticsearch, Logstash, Kibana) for threat detection, integrity monitoring, and incident response. Wazuh's agents, written in Python, perform security monitoring on endpoints and send data to a central server. Python's flexibility allows for extending Wazuh's capabilities with custom scripts and integrations, enhancing its effectiveness in various security scenarios.