NetworkX Description
NetworkX is a Python library designed for constructing, altering, and analyzing the intricacies, behaviors, and functionalities of complex networks. It offers generators for various types of graphs, including traditional, random, and synthetic networks. The advantages of using Python further enhance the experience, providing quick prototyping capabilities, ease of learning, and compatibility across multiple platforms. Additionally, it facilitates a comprehensive examination of network structures and the application of various analytical measures. This makes NetworkX an invaluable tool for researchers and practitioners in the field of network science.
NetworkX Alternatives
Paligo
For decades CCMS and content authoring solutions have been lagging behind in the fast-paced world of cloud technology. We’re changing that.
Paligo was founded by people with many years of experience in the field of technical documentation. We’re using that experience to build the modern web platform that we would have wanted to use ourselves.
Our goal is to make structured authoring more accessible to a wider audience by simplifying and demystifying the process. This is achieved through our intuitive and user-friendly CCMS, which is both powerful and robust, enabling our customers to easily author, manage, translate, and publish multichannel content.
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JOpt.TourOptimizer
If you are developing software for Logistics Dispatch Solutions, which contain challenges:
-For staff dispatching, such as sales reps, mobile service, or workforce?
-For truck shipment allocation in daily transportation and logistics (scheduling, tour optimization, etc.)?
-For waste management and District Planning?
-Generally, highly constrained problem sets?
And your product does not have an automized optimization engine?
Then JOpt is the perfect fit for your product and can help you to save money, time, and workforce, letting you concentrate on your core business.
JOpt.TourOptimizer is an adaptable component to solve VRP, CVRP, and VRPTW class problems for any route optimization in logistics or similar fields. It comes as a Java library or in Docker Container utilizing the Spring Framework and Swagger.
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NumPy
Fast and adaptable, the concepts of vectorization, indexing, and broadcasting in NumPy have become the benchmark for array computation in the present day. This powerful library provides an extensive array of mathematical functions, random number generators, linear algebra capabilities, Fourier transforms, and beyond. NumPy is compatible with a diverse array of hardware and computing environments, seamlessly integrating with distributed systems, GPU libraries, and sparse array frameworks. At its core, NumPy is built upon highly optimized C code, which allows users to experience the speed associated with compiled languages while enjoying the flexibility inherent to Python. The high-level syntax of NumPy makes it user-friendly and efficient for programmers across various backgrounds and skill levels. By combining the computational efficiency of languages like C and Fortran with the accessibility of Python, NumPy simplifies complex tasks, resulting in clear and elegant solutions. Ultimately, this library empowers users to tackle a wide range of numerical problems with confidence and ease.
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Scapy
Scapy is an advanced, interactive tool designed for packet manipulation. It excels in crafting and interpreting packets across a multitude of protocols, facilitating their transmission, capturing data, and correlating requests with responses, among various other functionalities. This versatile program can efficiently perform traditional tasks such as scanning, tracerouting, probing, unit testing, executing attacks, and discovering networks, effectively replacing tools like hping, a significant portion of nmap, arpspoof, arp-sk, arping, tcpdump, tshark, and p0f. Furthermore, Scapy stands out in executing specialized tasks that other utilities struggle with, including the transmission of invalid frames and the injection of custom 802.11 frames, as well as employing techniques like VLAN hopping combined with ARP cache poisoning or VOIP decoding over WEP-encrypted channels. It is compatible with various operating systems, including Linux, Windows, OSX, and most Unix variants that utilize libpcap. Notably, the same codebase supports both Python 2 and Python 3, showcasing its versatility. The development of Scapy is managed through the Git version control system, with its primary repository available on GitHub, allowing for collaborative improvements and updates. As a result, users benefit from continuous enhancements that keep pace with the evolving landscape of network security and analysis.
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Pricing
Pricing Starts At:
Free
Free Version:
Yes
Integrations
Company Details
Company:
NetworkX
Website:
networkx.org
Media
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Product Details
Platforms
Windows
Mac
Linux
Types of Training
Training Docs
Customer Support
Online Support
NetworkX Features and Options
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