Vacuum in scientific terminology refers to the volume of space that has no matter contained in it and is empty. Science defines further that in vacuum the gaseous pressure is zero or lesser than atmospheric pressure. Quantum theory does not account for a total perfect vacuum but defines near perfect situation that can exist.
History records that the great scientists Plato and Aristotle both did not believe that a vacuum was possible and could not imagine a reality where nothing exists. The first vacuum test was successfully conducted by Evangelista Torricelli in 1643 and the experiment has hence forth been referred to as torricellian vacuum.
With rapid industrialization and advancement of science, the concept of vacuum began to be adopted for common day to day applications very successfully.
We today use a variety of appliances and equipments which run based on vacuum theory and principles. The most widely used appliances are vacuum cleaners and vacuum pumps. All vacuum based applications use the suction produced by vacuum to carry out their functions.
Vacuum based applications are many in industrial sector. Automotive sector used this principle to make vacuum driven brakes on trains and other vehicles which were later replaced with air brakes. Even the windscreen wipers in the car were working based on vacuum pumps for a long time before better technology took over.
Vacuum sealing is widely used in packaging process especially in food and other items. Vacuum sealing neutralizes chemical action. Lot many processes like vacuum frying, cold welding, dry etching etc are found based on this principle.
Vacuum technology is further being widely used to make gaskets and seals for various field applications. Medical and surgical field usage is also being explored in various laboratories.
Most interesting aspect of vacuum can be found in the study of outer space which has very less atmospheric pressure and has stabilized on a near perfect vacuum situation. Scientists are conducting lots of experiments to understand the vacuum in space which enables the various stars and planets to travel freely on their own gravitational paths. Space travel and placing of satellites in the outer space etc involve detailed understanding of the atmospheric conditions in the outer space.
Human beings and living things if exposed to a vacuum will immediately loose consciousness and can die of hypoxia. Astronauts wear a protective space suit called Crew Altitude Protection Suit to prevent embolism which results due to low pressure. On the reverse the Astronauts cannot immediately remove their suits and expose themselves to the atmosphere when they come from a vacuum space and need time for the body to adjust itself to normal atmospheric pressure and get acclimatized.
The Future Scope of a Python Developer:The world is getting digitized. Data is king! With the ongoing digital transformation, we will slowly move towards an era of exabytes of data, and then to an era of zettabytes and yottabytes, and so on. The future is all about automating processes and utilizing the heaps of data to make intelligent decisions. This puts to the forefront technologies such as artificial intelligence (AI), machine and deep learning, Internet of Things (IoT), etc.
As these technologies lay the foundation for the future, programming languages associated with these emerging technologies are already gaining popularity. Therefore, this makes the position of languages such as R and Python, among others extremely powerful. With this blogpost, we will discuss the future scope of Python as a programming language and a career option for developer.
So, what is the future scope for Python developers? The answer is simple - promising!
Future Technologies are banking on Python:
Artificial Intelligence (AI) overarching technologies like machine learning, deep learning, neural networks and natural language processing (NLP) along with Big Data heavily bank on Python.
Released in 1989, 웹개발 Python is an object-oriented programming language (groups data and code into objects capable of modifying each other), which allows easy execution of tasks, enhanced stability and code readability. The programming language is easy to use, requires writing less codes and is therefore less time-consuming. Unlike earlier, the Anaconda platform has spruced up the speed. Another reason is its compatibility with Hadoop, themost popular open source Big Data platform. Read more on this here and some mistakes that Python developers must avoid while using it for Big Data here (link the previous blogpost).
In fact, Python is slowly yet steadily becoming the most preferred language for the field of Data Science. According to the interactive list of top programming languages by IEEE Spectrum, Python sits on the top of the table. It enjoys the top spot followed by C, Java and C++. A HackerRank survey sings to a similar tune. It reveals how Python is preferred by developers across all ages, citing the Love-Hate index. The report further adds, "Python is also the most popular language that developers want to learn overall, and a significant share already knows it."
Python community can easily rely on the frameworks and libraries created especially for Artificial Intelligence and handling Big Data abilities.
Let's take a look at the vast frameworks and libraries available for Python:
Python enthusiasts are continuously adding new libraries and frameworks. As aforesaid, some of these are especially handy at emerging technologies. For instance, in the field of Artificial Intelligence, PyML, PyBrain, scikit-learn, MIPy, etc. are readily available for machine learning; SimpleAI for General AI; neurolab, PyAnn, etc. for neural networks and Quepy for natural language and text processing. Similarly, for Big Data, toolkits and libraries such as NumPy, Pandas, Scikit-Learn, Bokeh are readily available.
Leading companies are already using Python programming language:
Going by the report from Cleveroad, some of the world-class companies are using Python either as a core language or in combination with other languages. We've mentioned some of these below:
Instagram:
This popular image sharing site has implemented Python 3 along with the popular Python framework Django, citing reasons like friendly relationship that the language shares with engineers and the speed of development, among others.
Spotify:
Reportedly, 80 percent of Spotify's back-end services are based on Python, and the remaining on Java and C/C++. It deploys the Python language for back-end services as well as data analysis.
Amazon:
Amazon is believed to be among the companies using the Python programming language. It uses Python machine learning engine to analyzing consumer habits and making accurate product recommendations.
Disney:
The renowned Disney company uses Python along with other technologies such as Hadoop and Apache.
YouTube:
Google's popular video service, YouTube, makes it to the list of companies using Python in combination with Apache Spark for its real-time analytics.
Facebook:
The world's largest social network, Facebook, also uses Python as the core language for back-end applications with image processing.
The list also includes Quora, Reddit, NASA, Nokia, among other renowned companies. The adoption of the programming language is a testament to its ease of use and efficiency. This also widens the scope of the demand for Python developers in the future.
Python Success Stories:
Here's a list of Python's success stories in various domains from administration and Web 2.0 to embedded systems and scalability:
1)Honeywell Avoids Documentation Costs with Python and other Open Standards
2)Gusto! Chooses Python for Travel Social Network Transition
3)D-Link Australia Uses Python to Control Firmware Updates
4)Python Enterprise-Wide at the University of St Andrews in Scotland
5)At Philips, The Semiconductor Line in Fishkill Runs on Python
6)ForecastWatch.com Uses Python To Help Meteorologists
7)Verity Ultraseek: Building Successful Enterprise Solutions with Python
8)ERP5: Mission-critical ERP/CRM with Python and Zope
9)Industrial Light & Magic Runs on Python
10)Wordstream Uses Python as Their Platform of Choice
The job scenario for Python programming and its developers:
By learning Python, you could take one of these profiles namely, Python Developer, Software Engineer, Senior Software Engineer, Software Developer, DevOps Engineer and Data Scientist.
Going by Indeed.com, as of June 2018, the average salary a Python Developer is $114,391 per year in the United States.
In India, the demand for Python developers is gradually seen a rise. The PayScale data points out the median salary for Python developers as per job and also city-wise.
Python Median Salary by Jobs (Source: Payscale)
Software Engineer - Rs 543,463
Data Scientist - Rs 802,840
Senior Software Engineer - Rs 939,617
Python Median Salary by City (Source: Payscale)
Bangalore, Karnataka - Rs 892,106
Pune, Maharashtra - Rs 639,249
Hyderabad, Andhra Pradesh - Rs 728,545
As aforementioned, several factors including but not limited to ease of use for emerging technologies, vast network of libraries and growing demand by world-class companies, Python is not just the most preferred language but also means a big demand for Python developers.
Whether you're a student or professional, it is now easy to learn Python programming course as per your convenience and through certified industry experts. LearnTek offers a series of certifications for students and experienced professional, whether it's a step-by-step