I can't say, that python is a perfect choice for big data. At least for production ready (real-time) data analysis.
Python has significant limitation from performance point of view.
But in the other hand, Python has a low entrance requirements (requirements to researcher as to programmer), and wide assortment of semi-automized tools for research of a data. Thus, Python is good choice for big data research, and prototyping, but in a real-world applications can raise problem with performance.
Thus:
"+" Low requirements to programmers skills => more attention to scientific side
"+" Wide assortment of semi-automized tools for data research and APIs to production ready frameworks.
"-" Limited performance (at least in case, than the chosen framework has not enough functionality.
"-" Low quality of initial code (as consequence of the 1st point).
Additionally, python has a big community which is good for research stage, but can raise a headache, if you wants to use research code for production ready systems (due a zoo of licenses and problems with environments).
Python is a popular programming language that offers several features and advantages that make it a suitable choice for working with big data. Here are some reasons why Python is often considered a good fit for big data:
Overall, Python's combination of ease of use, extensive libraries, scalability, and community support make it a popular choice for working with big data. Its flexibility, performance optimizations, and integration capabilities enable developers and data scientists to efficiently process, analyze, and derive insights from large and complex datasets.
Dear Doctor
"Python provides a huge number of libraries to work on Big Data. You can also work – in terms of developing code – using Python for Big Data much faster than any other programming language. These two aspects are enabling developers worldwide to embrace Python as the language of choice for Big Data projects."
Python is a powerful and flexible programming language that is being used more and more for big data apps.
It's very common because it has many features that make it good at working with big, complicated datasets.
Python's simplicity, rich ecosystem of libraries, scalability, interpretability, versatility, active community, and open-source nature make it an ideal choice for big data applications.
As the volume and complexity of data continue to grow, Python is poised to play an even more prominent role in the field of big data analytics and machine learning.
Python Spark, also known as PySpark, is an open-source Python API for Apache Spark, a distributed computing framework designed for processing large datasets.
PySpark provides a familiar and easy-to-use Python interface to Spark's powerful features, enabling developers to leverage Spark's capabilities for big data analysis and manipulation.
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