Introduction to Python for Data Engineering

Python has become one of the world's most popular programming languages. Python is becoming the usual programming language for completing numerous data engineering jobs as the demand for data engineers grows. One of the key reasons for its popularity is that it is one of the most widely used languages in data science. Python modules such as Pandas, NLTK, scikit-learn, matplotlib, and others are ideal for accomplishing various data engineering and data science jobs.

Why study Python?

1.It is easy to learn and use

The Python language is extremely simple to use and learn for novices and beginners. Python is one of the most approachable programming languages available due to its simple syntax and lack of complexities.
2.It has hundreds of libraries

Python includes fantastic libraries that you can use to save time and effort throughout the early development cycle. Several cloud media providers provide cross-platform support via library-like tools, which can be quite useful.
3.Aids in Automation

The Python programming language may greatly assist with work automation because there are numerous tools and modules accessible, making things much more convenient. It's remarkable to realize that by simply applying for the proper Python programs, one may easily achieve an advanced level of automation.
4.It has a wide supportive community

Python was founded more than 30 years ago, which is a long time for any programming language ecosystem to evolve and mature enough to serve developers at all levels, from novice to expert. A wealth of material, guidelines and video tutorials are available for the Python programming language that learners and developers of all skill levels and ages can utilize to improve their language knowledge.
5.It is efficient

Any python developer will tell you that the python language is more efficient, dependable, and speedier than most modern languages. Python can be used in almost any setting, and there will be no performance loss regardless of the platform on which it is utilized.

What Python skills does a Data Engineer need to learn?

Basic Python

1). Maths Expressions
2). Strings
3). Variables
4). Loops
5). Functions.
6). List, Tuples, Dictionary, and sets

Connecting With Databases.
1). Boto3
2). Psycopg2
3). MySQL

Working with Data
1). JSON
2). JSONSCHEMA
3). DateTime
4). Pandas
5). Numpy

Connecting to APIs
1). Requests

What do Data Engineers use Python for?

1. Data collection through the use of multiple APIs.
2. Importing data from several file formats
3. Using DAGs to build ETL/ELT pipelines
4. Data processing with Python packages such as NumPy, Pandas, and others.

CONCLUSION
This blog discussed how the Python programming language is useful when working with Big Data. Learning about cloud platforms such as AWS, Google Cloud Platform, and Microsoft Azure. Learning SQL and NoSQL are key steps in becoming a data engineer.