In case you like Python and need some inspiration when you are down, then consider the following six awesome scientific packages driven by Python to be contented with your decision for the language to be your initial choice. The scientific packages attest to usefulness of Python a language for programming.
This is a compilation of application packages built in Python for utilization in astronomy. Astropy was developed as an element of unprecedented effort by a professional community to build a free, single, core package with astronomical utilities owing to astronomers’ increased use of Python while fostering interoperability between several existing packages of astronomy in python.
This international association is for developers of noncommercial tools in Python for bioinformatics and computational molecular biology. Biopython is among the Bio projects developed to decrease duplication of code.
This python library is for studying networks and graphs. NetworkX application is free and is distributed under BSD-new license. The application is appropriate for operating big graphs in real-world: e.g., graphs with over 10 million joints and 100M edges.
This computing environment as well as open source system of software useful in Python is used by analysts, engineers and scientists performing technical and scientific computing.
This machine learning libraries are open source in Python. scikit-learn incorporates regression, classification as well as clustering algorithms like support for vector machines, random forests, logistic regression, gradient boosting, DBSCAN, k-means and naïve Bayes. The application is developed to integrate Python scientific and numerical libraries SciPy and NumPy.
This library in python for computation in symbols. SymPy offers computer algebra abilities either as library for other applications, Live online like SymPy, or standalone application. The application is small to inspect and install since it is built completely on Python; as well, because it never relies any extra libraries.