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Microsoft 98-381 : Introduction to Programming Using Python Exam

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Test Number : 98-381
Test Name : Introduction to Programming Using Python
Vendor Name : Microsoft
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98-381 test Format | 98-381 Course Contents | 98-381 Course Outline | 98-381 test Syllabus | 98-381 test Objectives

Perform Operations using Data Types and Operators (20-25%)
Evaluate an expression to identify the data type Python will assign to each variable
Identify str, int, float, and bool data types
Perform data and data type operations
Convert from one data type to another type; construct data structures; perform indexing and slicing operations
Determine the sequence of execution based on operator precedence
Assignment; Comparison; Logical; Arithmetic; Identity (is); Containment (in)
Select the appropriate operator to achieve the intended result
Assignment; Comparison; Logical; Arithmetic; Identity (is); Containment (in)
Control Flow with Decisions and Loops (25-30%)
Construct and analyze code segments that use branching statements
if; elif; else; nested and compound conditional expressions
Construct and analyze code segments that perform iteration
while; for; break; continue; pass; nested loops and loops that include compound conditional expressions
Perform Input and Output Operations (20-25%)
Construct and analyze code segments that perform file input and output operations
Open; close; read; write; append; check existence; delete; with statement
Construct and analyze code segments that perform console input and output operations
Read input from console; print formatted text; use of command line arguments
Document and Structure Code (15-20%)
Document code segments using comments and documentation strings
Use indentation, white space, comments, and documentation strings; generate documentation by using pydoc
Construct and analyze code segments that include function definitions
Call signatures; default values; return; def; pass
Perform Troubleshooting and Error Handling (5-10%)
Analyze, detect, and fix code segments that have errors
Syntax errors; logic errors; runtime errors
Analyze and construct code segments that handle exceptions
Try; except; else; finally; raise
Perform Operations Using Modules and Tools (1-5%)
Perform basic operations using built-in modules
Math; datetime; io; sys; os; os.path; random
Solve complex computing problems by using built-in modules
Math; datetime; random

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Microsoft Python test success

Programming language Python is a huge hit for computing device getting to know. but now it should trade | 98-381 Q&A and cheat sheet

Open-source programming language Python has develop into one of the crucial few languages that won't disappear each time soon. it's the proper or one of the vital right two languages in most exquisite language popularity indexes, and even appears set to beat Java at the moment.

but 35-12 months-old Python does have its weaknesses. not necessarily for the facts-science and desktop-studying communities constructed round Python extensions like NumPy and SciPy, but as a generic programming language.

Python is the true language in accordance with IEEE Spectrum's electrical engineering audience, yet you can not run Python in a browser and you may't easily run it on a smartphone. Plus no person builds games in Python at the present time.

SEE: Hiring kit: Python developer (TechRepublic top rate)

To construct browser purposes, developers are inclined to go for JavaScript, Microsoft's classification-protection tackle it, TypeScript, Google-made Go, and even historic however trusty php. On mobile, why would software developers use Python when there may be Java, Java-appropriate Kotlin, Apple's Swift, or Google's Dart?

Python doesn't even aid compilation to the WebAssembly runtime, a web software normal supported through Mozilla, Microsoft, Google, Apple, Intel, Fastly, RedHat and others.

These are only one of the most barriers raised by means of Armin Ronacher, a developer with a long background in Python who 10 years ago created the regular Flask Python microframework to solve complications he had when writing internet applications in Python.

Austria-based mostly Ronacher is the director of engineering at US startup Sentry – an open-source venture and tech enterprise used with the aid of engineering and product groups at GitHub, Atlassian, Reddit and others to computer screen consumer app crashes as a result of glitches on the frontend, backend or within the cellular app itself.

Armin Ronacher: "i'm now not asserting you can not fix Python. I suppose you can make a new edition of Python that fixes loads of these things."

graphic: Maria Ronacher

plenty of Sentry is written in Python, putting it within the equal classification of Python-heavy tech firms like Instagram, Netflix, and Dropbox, from which Python's creator Guido van Rossum introduced his retirement a yr in the past. He stepped down as Python's 'Benevolent Dictator for life' in 2018.

while Ronacher contributes little to Flask these days – as a result of new Python points for records science don't activity him – it's turn into familiar for deploying machine-researching fashions because of an abundance of tutorials and institution courses that teach it. Flask become the most accepted web framework, forward of Django, in IDE-maker JetBrains's 2018 Python developer survey.

Python at Sentry is in general legacy code nevertheless it's still used on the backend for integrating Sentry with other programs, equivalent to when a crash document in Sentry must be passed to Atlassian's Jira challenge-monitoring gadget.

"The sync between Sentry and Jira is written in Python," Ronacher tells ZDNet. "lots of the backend enterprise good judgment it is connected to Sentry's frontend is written in Python. The event processing and all that complexity is slowly getting into Rust for efficiency explanations."

Ronacher is a tremendous fan of Rust, a programming language created at Mozilla research five years ago. Microsoft is eyeing it as a memory-safe replacement for materials of its C and C++ codebases in home windows and office.

regardless of Python's success as a language, Ronacher reckons it be prone to dropping its attraction as a widespread-goal programming language and being relegated to a particular domain, similar to Wolfram's Mathematica, which has also found a spot in statistics science and computing device gaining knowledge of.

"Your expectation isn't going to be that i'll boost a desktop software in Mathematica," talked about Ronacher.

"in the mean time, it looks like the entire fields for Python are super applicable and increasing, but they can already see that there'll always be smartphones – or anything that replaces smartphones – and there can be browser purposes. Python can't serve these two issues presently and springs with lots of restrictions," he says.

Peter Wang, co-founder and CEO of Anaconda, maker of the commonplace Anaconda Python distribution for facts science, cringes at Python's boundaries for building laptop and cell functions.

Peter Wang: "Of path, Python's cost as a lingua franca for backend device automation and scripting is a troublesome element to displace. however it shouldn't be content material just to be relegated to that,"

picture: Anaconda

"it's an embarrassing admission, however's particularly awkward to use Python to construct and distribute any functions which have specific graphical person interfaces," he tells ZDNet.

"On computers, Python isn't the first-classification language of the operating system, and it should motel to 3rd-birthday party frameworks like Qt or wxPython."

Packaging and redistribution of Python computer functions are additionally truly difficult, he says.

"On the web, the frontend is always JavaScript or a spinoff. And on cell, Python is barely used in any respect. or not it's kind of a miracle that Python is even on the radar, lots less ranked in the desirable three languages. In an ironic approach, it's a bit a testament to the energy and recognition of Python for backend and information-science workloads."

The Python group realizes that app distribution is its Achilles heel, but Ronacher doesn't see a means ahead without fracturing the Python community.

The ultimate time Python developers tried to introduce predominant changes was Python three, released in 2008. Yet by using 2014, van Rossum turned into virtually begging developers to "stream on to Python 3". At that stage, agencies like Instagram with big Python codebases nonetheless hadn't made the transition to Python three.

"Python boxed itself into a corner where it be very complicated to innovate with out breaking americans's code. final time it turned into attempted to make some greater changes to Python, which become Python three, a lot of people's code broke. It took 10 years for the ecosystem to heal up once more," says Ronacher.

Why can not Python run in the browser?

in line with Ronacher, Python's barriers come right down to design, the chance of breaking Python code utilized in production programs, and alienating significant components of its significant consumer base.

Python's interpreter and its C-language utility binary interface (ABI) and application protocol interface (API) has hindered innovation in the browser, says Ronacher.

whereas JavaScript builders can embed their code in a browser and have every tab working its own JavaScript engine, Python can't because the present ABI, which is uncovered to Python extensions like NumPy. This prevents it from having two types of its interpreter within the same system space in what's normal because the 'international interpreter lock'.

"when you've got two interpreters, they'd share the same object," explains Ronacher. "So, if 'tab one' would regulate an object, 'tab two' would additionally look at that modification."

though he admits working Python in a browser is unpopular anyway, that challenge has different ramifications for its future and use as a widespread programming language.

"it might have been satisfactory if they may run numerous processes and have one pinned to 1 CPU core and do message passing to get the world interpreter lock. however really the publicity of this C API prevents an entire range of these things.

"To put in force this, you could possibly have to take away or change the C API, which might break Python's largest ecosystem: NumPy, SciPy, and the entire machine-researching ambiance."

SEE: 10 ways to keep away from developer burnout (free PDF) (TechRepublic)

Ronacher says Python has been "stuck like this for a long time". Time and again, efforts to "kill the global interpreter lock" fail since it would cause troubles for extensions like NumPy.

it be much less a core technical problem than one of making enough individuals care satisfactory about an innovation for one neighborhood that may well be painful for an additional group in the ecosystem.

"If what you might be doing goes to destroy NumPy, and that factor isn't going to advantage the NumPy group, it be doubtful if you will get the backing to execute on that," he features out.

in its place, the Python group has moved in opposition t computer discovering and data science, which is less thinking with Python's efficiency issues because they can be overcome via relocating code to a GPU or a cluster where many techniques are operating independently.

"however it's intended that Python isn't utilized in computing device games anymore, no longer being compiled to the browser, and is also much less well-known in net functions," he says.

'New Python' is feasible but may split the group

Wang and Ronacher agree that a successor to Python might emerge – one which is never tied to latest design choices that restrict its use in fields outdoor information science and backend programs.

"If Python is to be lengthy-term aggressive with different utility construction languages outside facts analysis, it have to have a coherent imaginative and prescient of what it stands for and that vision ought to be differentiated," says Anaconda's Wang.

"Programmers are always searching for brand new vivid objects, so languages hardly get rewarded for doing many things neatly. Of direction, Python's price as a lingua franca for backend device automation and scripting is a tricky aspect to displace. however it shouldn't be content just to be relegated to that," he provides.

"lots of Python's core ideas and objects are intrinsically tied to a 'single-node computer' computation mannequin. truly next-gen languages should movement past this paradigm."

Ronacher is confident that Python may also be reinvented but additionally elements to the destiny of Perl, a hit for programming on the net within the early 2000s but now smartly backyard of Tiobe's precise 10. Perl is now called Raku as a result of fractures inside the community over its future and legacy.

the use of Perl as a yardstick suggests why bending Python's future will take a courageous and committed character.

"i'm not announcing you cannot repair Python. I think you could make a new edition of Python that fixes loads of those issues, but someone would ought to are available and say, 'it be ok for us to plot a path towards a future edition of the language it really is incompatible'," says Ronacher.

"Some efforts the place individuals tried to try this ended up setting apart communities. Perl 6 isn't any longer even referred to as Perl since the group on no account completely subscribed to it and the cost of going to the new edition turned into writing code from scratch."

The other chance of large breaking changes is that former devotees of a language comfortably switch to a contemporary alternative.

"The second you say, 'might they try this basically cool edition of Python that fixes all these issues?', is that it doesn't appear to be Python anymore and there is no clear migration path," says Ronacher.

"there's all the time a possibility that people go to yet another language wholly. I have no idea what that path may be but when Python desires to have a future as a language it really is commonly relevant, then it likely should beginning exploring some radical improvements."

What of latest languages like Rust and Julia?

Ronacher says he felt the same "high-quality emotions" the usage of Rust as when he started using Python. despite the fact, Rust has adolescence on its side, making it extraordinarily well preferred yet now not widespread.

"that you may make contributions, or not it's interesting to work on, and each six weeks you get an update of the compiler and also you read the changelog. It makes you chuffed to upgrade and it has a very respectable ecosystem round it."

Ronacher reckons Rust's mission observation is critical to its recognition, regardless of low adoption, since it helps define what elements of the language follow to some developers and never others.

"I feel the group self-segregates into individuals who may and could not use Rust. through the years, Python on no account had that," he says.

Ronacher aspects to Python guide for windows. as an example, until home windows 10 1903, the might also 2019 update, home windows turned into the best mainstream working system that didn't include a Python interpreter.

"These have been always independent community efforts and it on no account felt adore it changed into part of the language," he says.

it be a special story with Rust due to its lack of baggage and its mission commentary, in response to Ronacher.

"When individuals all started porting Rust to work on windows, that in reality grew to be a core effort within the language," he says.

as an instance, there's a group of Rust contributors who're responsible for making sure it works on windows, which comprises help from Rust sponsor, Microsoft.

however in Python, Ronacher says initiatives like porting it to windows "was at all times an afterthought".

"It was like, if a person is willing to do it, they will do it, but when not, it became additionally no longer a priority. and you are feeling it. In Rust, they determined that first rate packaging is essential for the language, so despite the fact that there become a separate group doing it, it grew to become everyone's responsibility."

Python also has emerging competitors in data science, equivalent to Julia, a language born out of MIT's CSAIL artificial-intelligence lab. however's yet to profit mainstream recognition.

Wang reckons Julia is attractive and its makers pitch it as being as convenient-to-use as Python, however with the most excellent qualities of R for statistics and Matlab for algebra. however, he sees Python and R's popularity as an obstacle for builders who understand those languages and ecosystems already.

"Julia as a language has a lot of great features. but languages are a viral technology, in that there is a network impact," says Wang.

"except a undeniable percentage of the person base is actively the usage of it and pushing it onto their friends and teams, then adoption is terribly sluggish. One challenge Julia has is that for a lot of teams, Python and R already exist and while they are removed from excellent, they can be 'respectable enough'."

extra on Python and programming languages

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