Hello everyone, today in the post I am going to talk about some basic questions asked almost in every python interview and try to answer them to make your python interview journey easier. Let's have a look
Separation operator print function` Unicode brass Error Management `_front_` module
Although Python 2 is officially inherited at this point, its use is widespread enough that it is important for an engineer to see the difference between Python 2 and 3.
Here are some of the major differences a builder should be aware of:
Text and data instead of Unicode and 8-bit cables. Python 3.0 uses text and data (binary) concepts instead of Unicode cables and 8-bit cables. The great ramification of this is that any attempt to mix text and data in Python 3.0 suggests TypeError (to merge the two securely, you must decrypt or merge Unicode, but you need to be able to enter the appropriate code, e.g., UTF-8)
This speaks volumes about the naïve Python editors. In Python 2, Unicode mixing with 8-bit data will only work if the cable contains only 7-bit bytes (ASCII), but you will get UnicodeDecodeError if it contains non-ASCII values. In addition, the exception will occur at the junction, not where non-ASCII characters are inserted into the object str. This behavior has been a common source of confusion and panic about the neophyte Python system.
print function. Print statement has been replaced by a print job ()
xrange - buh-bye. The xrange () no longer exists (range () now behaves like the xrange () used for behavior, except that it operates with counter-size values)
Zip (), map () and filter () all now return the iterators to the list.
dict.keys (), dict.items () and dict.values () are now replacing 'views'.
dict.iterkeys (), dict.iteritems () and dict.itervalues () are no longer supported.
Operator comparison. Comparison operators (<, <=,> =,>) now suggest TypeError variants where operators do not have purposeful natural configurations. Some examples of the consequences of this include:
Expressions like 1 <'', 0> None or len <= len are no longer valid
None <None now suggests TypeError instead of returning False
Sorting a different list is no longer logical.
Everything has to be compared
Python is a highly developed, translated, interactive, and directed language. Python is designed to be highly readable. It uses English keywords more often where other languages use punctuation and has fewer synthetic structures than other languages.
Python is a highly programmed programming language that can be used in many different stages of problems.
Language comes with a large general library that includes areas such as thread processing such as standard definitions, Unicode, file differentiation, Internet protocols such as HTTP, FTP, SMTP, XML-RPC, POP, IMAP, CGI programming, software like unit checking, logging, printing, processing Python code, and integration of operating systems such as system calls, file systems, TCP / IP sockets.
Although the likes and dislikes are personal, the developer "deserves his salt" will highlight Python's language features that are considered beneficial (which also help answer the question of what Python is "good for". The most common answers to this question include:
Easy to use and easy to recreate, thanks to Python syntax flexibility, which makes it especially useful for fast displays.
Combined code, also thanks to Python syntax, as well as a wealth of rich Python-based libraries (freely distributed with many Python language implementations).
Strongly typed and tightly typed language, which provides an unusual combination of code flexibility while simultaneously avoiding pesky-type-converter-bugs.
For free and open source! Do we need to say more?
Concerning the question of whether using Python is the "right choice" for a project, the complete answer also depends on many language-related issues, such as investing in previous technologies, a set of team skills, and so on. While the question as mentioned above implies an interest in a strong technical answer, the engineer who will address these additional issues in the discussion will always “get more points” with me because it shows awareness, and sensitivity to the “big picture” (i.e., more than just the technology used). On the other hand, the answer that Python has always been a good one is a clear indication of a skilled engineer.
First, if you know the language well, you know its problems, so answers like "I don't like it" or "there are no obstacles" tell us a lot.
The two most common answers to this question (not to mention the full list) are:
Global Interpreter Lock (GIL). CPython (the most common use of Python) is not completely secure. To support multi-threaded Python programs, CPython provides a global key to hold the current cable before securely accessing Python objects. As a result, no matter how many threads or processors are available, only one thread is made at a time. In comparison, it is important to note that the implementation of PyPy discussed at the beginning of this article provides a rootless mode that supports small strands of large amounts.
Execution speed. Python may be slower than merged languages because it is translated. (Yes, what kind. See our previous discussion on this topic.)
That's right. To be yourself, you have to accept your mistakes. Only then can you continue to work on them. Python also has its drawbacks:
The environment translated by Python puts a speed penalty on it. While Python is good for many things, it is weak on the laptop, as well as in browsers.
For dynamic typing, Python uses duck typing (If it looks like a duck, it must be a duck). This can increase operating time errors.
Python has inaccessible layers of database access. This gives you an under-selection option for large data apps.
And behind these traps, that's right. Simplicity makes it addictive. Once Python-coder, always Python coder.
So while it has problems, it is also a good tool for many things.
Disclaimer # 1. The differences between Java and Python are numerous and maybe the appropriate title for its (long) post. Below is just a brief sample of the significant differences between the two languages.
Liberation # 2. The purpose here is not to start a religious war over the merits of Python vs. Java (as fun as it can be!). Instead, the question is simply to see how well the engineer understands the practical differences between the two languages. The list below, therefore, avoids deliberate discussion of Python's controversial advantages over Java from a production program perspective.
With the free ideas above in mind, here’s a sample of some important differences to keep in mind when encoding Python vs. Java:
Dynamic vs static typing: Another major difference between the two languages is that Java is restricted to fixed typing and Python supports dynamic typing.
Static vs. class methods: Stable mode in Java does not translate into the Python class method.
In Python, the calling class method includes more
allocation of memory that calls for a stationary or inactive function.
In Java, dotted words (e.g., Foo.bar.method) are highly regarded by the compiler, so during operation, it does not matter how many values you have. In Python, however, detection occurs during operation, so "each dot is calculated".
Method overload: While Java requires a clear specification of many functions with the same name with different signatures, the same can be achieved in Python with a single function that includes optional values with default values if not specified by the caller.
Single vs. double-quotes. While the use of single quotations vs. Double quotes is important to Java, they can be used differently in Python (but no, it won't allow you to start the same thread twice and try to finish it in one measure, or the same way!).
Getters and setters (no!). Getterterterterter in Python is not required; instead, you should use the built-in 'property' (that's what it's made for!). In Python, Getterterterterterterter is a waste of both CPU and system time.
Classes can be selected. While Java requires that all functions be defined in the context of the closed class definition, Python does not have that requirement.
Indent is important… Python. This bites most newbie Python programmers.
Python's technical knowledge extends beyond the technical minutiae of language. A Python expert will have an in-depth understanding and appreciation of Python's benefits and limitations. Therefore, here are some sample questions that may be of help to assess the potential for baptism.
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Hello, I am Harendra Kumar Kanojiya - Owner of this website and a Fullstack web developer. I have expertise in full-stack web development using Angular, PHP, Node JS, Python, Laravel, Codeigniter and, Other web technologies. I also love to write blogs on the latest web technology to keep me and others updated. Thank you for reading the articles.