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Gradle uses a directed acyclic graph to determine the order in which tasks can be run, through providing dependency management. It runs on the Java Virtual Machine. [4] Gradle was designed for multi-project builds, which can grow to be large. It operates based on a series of build tasks that can run serially or in parallel.
graph-tool is a Python module for manipulation and statistical analysis of graphs (AKA networks). The core data structures and algorithms of graph-tool are implemented in C++ , making extensive use of metaprogramming , based heavily on the Boost Graph Library . [ 1 ]
Data visualization libraries Plotly.js is an open-source JavaScript library for creating graphs and powers Plotly.py for Python, as well as Plotly.R for R, MATLAB, Node.js, Julia, and Arduino and a REST API.
Graph databases are commonly referred to as a NoSQL database. Graph databases are similar to 1970s network model databases in that both represent general graphs, but network-model databases operate at a lower level of abstraction [3] and lack easy traversal over a chain of edges. [4] The underlying storage mechanism of graph databases can vary.
Astropy, a library of Python tools for astronomy and astrophysics. Biopython, a Python molecular biology suite; Gensim, a library for natural language processing, including unsupervised topic modeling and information retrieval; graph-tool, a Python module for manipulation and statistical analysis of graphs.
Matplotlib (portmanteau of MATLAB, plot, and library [3]) is a plotting library for the Python programming language and its numerical mathematics extension NumPy.It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK.
Examples of domain-specific programming languages include HTML, Logo for pencil-like drawing, Verilog and VHDL hardware description languages, MATLAB and GNU Octave for matrix programming, Mathematica, Maple and Maxima for symbolic mathematics, Specification and Description Language for reactive and distributed systems, spreadsheet formulas and ...
Snakemake is a Python-driven implementation for compiling and running bioinformatics workflows. [34] POSIX includes standardization of the basic features and operation of the Make utility, and is implemented with varying degrees of compatibility with Unix-based versions of Make. In general, simple makefiles may be used between various versions ...