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These are just a small sample from our library of 10,000+ questions. The actual questions on this test will be non-googleable.
What will the following Python code output?
The function high_sess should compute the highest number of events ...
Below are code lines to create a Python function. Ignoring indentat...
"With Adaface, we were able to optimise our initial screening process by upwards of 75%, freeing up precious time for both hiring managers and our talent acquisition team alike!"
- Brandon Lee, Head of People, Love, Bonito
Customized by subject matter experts to cater to job roles for all experience levels (fresh grads to 8-10 years) within your organization.
Adaface assessments have an average test taking rate of 86% as compared to an industry standard of 50%.
Adaface assessments have relevant questions that test for on-the-job skills. We do not expect candidates to solve puzzles/ trick questions.
Sample Coding Conversation with Ada
"The hiring managers felt that through the technical questions that they asked during the panel interviews, they were able to tell which candidates had better scores, and differentiated with those who did not score as well. They are highly satisfied with the quality of candidates shortlisted with the Adaface screening."
- Human Resources Manager, Singapore Government
Adaface Python Online Test will be customized to accurately evaluate on-the-job skills required for your role.
This assessment test is useful when you are hiring candidates for roles like - Python Developer, Core Python Programmer, Backend Developer, Web Developer, Data scientist, Data analyst.
The Python Online test helps recruiters and hiring managers to identify qualified Python developer candidates from a pool of resumes, and helps in taking objective hiring decisions. It reduces the administrative overhead of interviewing too many candidates and saves expensive engineering time by filtering out unqualified candidates.
The Adaface Python Online Test screen candidates for the typical skills recruiters look for in a Python developer:
The insights generated from this assessment can be used by recruiters and hiring managers to identify the best candidates for the role. Anti-cheating features enable you to be comfortable with conducting assessments online. The Python developer test is ideal for helping recruiters identify which candidates have the technical skills to do well on the job.
The Python test will consist of ~15 MCQ, 1 coding challenge and 1 debugging challenge crafted by experts in the Python programming language and will cover a broad spectrum of topics within Python. This Python Online Quiz is designed to help you streamline your hiring process so that your hiring managers interview only candidates with proven hands-on technical expertise in Python development and programming.
Here is a list of topics Adaface Python Online Test will cover (only for reference, actual topics and questions for your custom assessment will be chosen by our subject matter experts based on your job description/ ideal engineer persona).
Adaface Python tests can be used for any role that requires hands-on experience with Python. Here are popular roles for which Python test can be used:
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You can combine multiple skills into a single custom Adaface Python test. Each of these custom tests will include questions to evaluate candidates on Python coding skills and questions based on other must have skills. For example: a Django and Python test will include questions on Django topics like Django templates in addition to Python topics. If your Python role is oriented towards Machine Learning, then the test will include questions on ML topics like Numpy, Pandas
Here are some popular combinations.
Our subject matter experts customize the test according to seniority in two ways:
Every role is different and requires a custom assessment to identify top candidates efficiently. Adaface subject matter experts understand your job description/ role requirements and pick the most relevant questions from our library of 10000+ questions to create a technical assessment that helps you find the qualified candidates in your candidate pipeline quickly. All custom assessments are set up based on the job description, role requirements, must-have skills, experience level and salary range within a maximum of 48 hours and you will get an email notification once it goes live.
Check out a sample assessment here (no credit card required).
Yes, absolutely. Custom assessments are set up based on your job description, and will include questions on all must-have skills you specify.
We believe that status quo tech assessment platforms are not a fair way for companies to evaluate engineers because they focus on trick questions/ puzzles/ niche algorithms. We started Adaface to help companies find great engineers by assessing on-the-job skills required for a role. Read more about what we do differently at Adaface here.
We have the following anti-cheating features in place:
The primary thing to keep in mind is that an assessment is an elimination tool, not a selection tool. As in an assessment is optimizing to help you eliminate candidates who are not technically qualified for the role, it is not optimized to help you find the best developer for the role. So the ideal way to use an assessment is to decide a threshold score (typically 60%, we help you benchmark) and invite all candidates who score above the threshold for the next rounds of interview.
Each Adaface assessment is customized to your job description/ ideal developer persona (our subject matter experts will pick the right questions for your assessment from our library of 10000+ questions). This assessment can be customized for Java developer roles for any experience level (unless the role is primarily a leadership/ non-programming role, we do not recommend you a use any automated assessments in that case).
Yes, it makes it much easier for you to compare candidates. Options for MCQ questions and the order of questions are randomized. We have anti-cheating features in place. In our enterprise plan, we also have the option to create multiple versions of the same assessment with questions of similar difficulty levels.
No. Unfortunately, we do not support practice tests at the moment.
Please get in touch, we'll create a custom plan for you based on the number of assessments you need.
You can sign up for free and check out the platform here. The dashboard has a sample assessment for you to review the quality of questions and check out the candidate experience of a chat based assessment. Since our questions are premium, we are unable to share sample questions for a particular skill/ technology.
Check out our quick guide on requesting a custom assessment here.
You should expect ~20% of the candidates to do well on Adaface assessments.
The score distribution for our assessments follow the normal curve. This is a good sign- standardized tests like SAT and GRE follow the normal distribution (bell curve).
Status quo assessments typically have the exact opposite of the bell curve (too many candidates getting close to 0, too many candidates getting close to 100 and too few candidates in the middle). This is typically because they focus on theoretical questions or trick questions, which are very binary in nature- either you know the trick/ theory or you don’t.
Python is an interpreted, high-level, general-purpose programming language. Python is dynamically typed and garbage-collected. It supports multiple programming paradigms, including procedural, object-oriented, and functional programming.
Python developers are in high demand - not only because the language is so popular and widely used but mostly due to the fact that Python became a solution in many different areas. From web applications to data science and machine learning.
Typical Python Developer responsibilities might include:
Candidates who pass Adaface Python Online test can be taken for second round interviews directly. Here are some interview questions for intermediate and experienced candidates:
Lists and Tuples are both sequence data types that can store a collection of objects in Python. The objects stored in both sequences can have different data types. Lists are represented with square brackets ['sara', 6, 0.19], while tuples are represented with parantheses ('ansh', 5, 0.97).
But what is the real difference between the two? The key difference between the two is that while lists are mutable, tuples on the other hand are immutable objects. This means that lists can be modified, appended or sliced on-the-go but tuples remain constant and cannot be modified in any manner.
Global variables are public variables that are defined in the global scope. To use the variable in the global scope inside a function, we use the global keyword. Protected attributes are attributes defined with a underscore prefixed to their identifier eg. _sara. They can still be accessed and modified from outside the class they are defined in but a responsible developer should refrain from doing so. Private attributes are attributes with double underscore prefixed to their identifier eg. __ansh. They cannot be accessed or modified from the outside directly and will result in an AttributeError if such an attempt is made.
Pass by value: Copy of the actual object is passed. Changing the value of the copy of the object will not change the value of the original object.
Pass by reference: Reference to the actual object is passed. Changing the value of the new object will change the value of the original object.
In Python, arguments are passed by reference, i.e., reference to the actual object is passed.
Python private heap space takes place of memory management in Python. It contains all Python objects and data structures. The interpreter is responsible to take care of this private heap and the programmer does not have access to it. The Python memory manager is responsible for the allocation of Python heap space for Python objects. The programmer may access some tools for the code with the help of the core API. Python also provides an inbuilt garbage collector, which recycles all the unused memory and frees the memory and makes it available to heap space.
Upon exiting, Python’s built-in effective cleanup mechanism comes into play and try to deallocate or destroy every other object. However, Python modules that are having circular references to other objects or the objects that are referenced from the global namespaces aren’t always deallocated or destroyed. This is because it is not possible to deallocate those portions of the memory that are reserved by the C library.
In Python, some amount of coding is done at compile time, but most of the checking such as type, name, etc. are postponed until code execution. Consequently, if the Python code references a user-defined function that does not exist, the code will compile successfully. The Python code will fail only with an exception when the code execution path does not exist.
We should use the threading module to implement, control and destroy threads for parallel execution of the server code. Locks and Semaphores are available as synchronization objects to manage data between different threads.
Parameter 'self' is used to refer to the object properties of a class. 'self' parameter is supposed to be prefixed to the class object properties.
In simple words, abstraction can be defined as hiding of unnecessary data and showing or executing necessary data. In technical terms, abstraction can be defined as hiding internal process and showing only the functionality. In Python abstraction can be achieved using encapsulation.
Yes, this is valid. The function will then return a None object. The end of a function is defined by the block of code is executed (i.e., the indenting) not by any explicit keyword.
We use a shallow copy when a new instance type gets created. It keeps the values that are copied in the new instance. Just like it copies the values, the shallow copy also copies the reference pointers. Reference points copied in the shallow copy reference to the original objects. Any changes made in any member of the class affect the original copy of the same. Shallow copy enables faster execution of the program.
Deep copy is used for storing values that are already copied. Unlike shallow copy, it doesn’t copy the reference pointers to the objects. Deep copy makes the reference to an object in addition to storing the new object that is pointed by some other object. Changes made to the original copy will not affect any other copy that makes use of the referenced or stored object. Contrary to the shallow copy, deep copy makes execution of a program slower. This is due to the fact that it makes some copies for each object that is called.
Even though Python comes with a multi-threading package, if the motive behind multithreading is to speed the code then using the package is not the go-to option.
The package has something called the GIL or Global Interpreter Lock, which is a construct. It ensures that one and only one of the threads execute at any given time. A thread acquires the GIL and then do some work before passing it to the next thread.
This happens so fast that to a user it seems that threads are executing in parallel. Obviously, this is not the case as they are just taking turns while using the same CPU core. Moreover, GIL passing adds to the overall overhead to the execution.
Hence, if you intend to use the threading package for speeding up the execution, using the package is not recommended.
When we want a function with a single expression, we can define it anonymously. A lambda expression may take input and returns a value. To define the above function as a lambda expression, we type the following code in the interpreter:
Objects and data structures in Python lie on a private heap. The Python memory manager internally manages this. It delegates some work to object-specific allocators while ensuring they operate only within the private heap. Actually, the interpreter manages this heap; the user has no control over it- not even if they manipulate object pointers to memory blocks inside the heap. The Python memory manager allocates heap space to objects and other internal buffers on demand.
Arrays in python can only contain elements of same data types i.e., data type of array should be homogeneous. It is a thin wrapper around C language arrays and consumes far less memory than lists. Lists in python can contain elements of different data types i.e., data type of lists can be heterogeneous. It has the disadvantage of consuming large memory.
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2. Start inviting candidates to
complete the assesment
Conversational assessments are the most candidate friendly way to get insights into a candidate's on-the-job skills and suitability for a role, while providing for a delightful candidate experience. Candidates love conversational assessments because they are fast, intuitive and feel like an interview rather than a test.
Tired of traditional assessments with trick questions and low completion rates?
Adaface conversational assessments are reflective of on-the-job skills and see an 86% completion rate as compared to ~50% for traditional assessment platforms.
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