Software Alternatives, Accelerators & Startups

NumPy VS Codility

Compare NumPy VS Codility and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

Codility logo Codility

Codility provides a SaaS platform with advanced validation, security and protection features to evaluate the skills of software engineers.
  • NumPy Landing page
    Landing page //
    2023-05-13
  • Codility Landing page
    Landing page //
    2021-07-20

The Codility platform includes:

CodeCheck - Design role-specific remote skills assessments to screen your technical candidates before moving them to the interview stage.

CodeLive - Host technical remote or onsite interviews via our shared editor using a range of templates and whiteboards.

CodeEvent - Assess thousands of candidates at a time via technical recruiting events and find the best talent faster.

NumPy features and specs

  • Performance
    NumPy operations are executed with highly optimized C and Fortran libraries, making them significantly faster than standard Python arithmetic operations, especially for large datasets.
  • Versatility
    NumPy supports a vast range of mathematical, logical, shape manipulation, sorting, selecting, I/O, and basic linear algebra operations, making it a versatile tool for scientific and numeric computing.
  • Ease of Use
    NumPy provides an intuitive, easy-to-understand syntax that extends Python's ability to handle arrays and matrices, lowering the barrier to performing complex scientific computations.
  • Community Support
    With a large and active community, NumPy offers extensive documentation, tutorials, and support for troubleshooting issues, as well as continuous updates and enhancements.
  • Integrations
    NumPy integrates seamlessly with other libraries in Python's scientific stack like SciPy, Matplotlib, and Pandas, facilitating a streamlined workflow for data science and analysis tasks.

Possible disadvantages of NumPy

  • Memory Consumption
    NumPy arrays can consume large amounts of memory, especially when working with very large datasets, which can become a limitation on systems with limited memory capacity.
  • Learning Curve
    For users new to scientific computing or coming from different programming backgrounds, understanding the intricacies of NumPy's operations and efficient usage can take time and effort.
  • Limited GPU Support
    NumPy primarily runs on the CPU and doesn't natively support GPU acceleration, which can be a disadvantage for extremely compute-intensive tasks that could benefit from parallel processing.
  • Dependency on Python
    Since NumPy is a Python library, it depends on the Python runtime environment. This can be a limitation in environments where Python is not the primary language or isn't supported.
  • Indexing Complexity
    Although NumPy's slicing and indexing capabilities are powerful, they can sometimes be complex or unintuitive, especially for multi-dimensional arrays, leading to potential errors and confusion.

Codility features and specs

  • Automated Assessment
    Codility provides automated coding assessments that save time for both recruiters and candidates by quickly identifying technical abilities.
  • Standardized Testing
    Codility offers standardized tests, ensuring evaluations are consistent and unbiased across all candidates.
  • Diverse Question Bank
    The platform has a large repository of coding problems that cover a wide range of topics and difficulty levels, catering to various roles and expertise levels.
  • Real-Time Code Execution
    Codility allows for real-time code execution and validation, enabling candidates to see the results of their code immediately.
  • Customizable Tests
    Recruiters can create custom tests tailored to the specific needs of their company or position, making the assessments more relevant.
  • Detailed Reports
    Codility provides detailed reports and analytics on candidate performance, helping hiring managers to make data-driven decisions.
  • Integration Capabilities
    The platform integrates with various Applicant Tracking Systems (ATS) and other HR tools, streamlining the recruiting process.

Possible disadvantages of Codility

  • Cost
    Codility can be relatively expensive, especially for small companies or startups with limited recruitment budgets.
  • Learning Curve
    There might be a learning curve for both recruiters and candidates to get accustomed to the platform and its features.
  • Language Limitations
    While Codility supports multiple programming languages, some niche or less commonly used languages may not be available.
  • Potential Stress for Candidates
    Automated assessments can induce stress for candidates, which might not accurately reflect their true abilities in a real-world setting.
  • Internet Connection Dependency
    A stable internet connection is required to complete assessments, which can be a limitation in areas with unreliable internet access.
  • Limited Collaboration Features
    Codility's focus on individual assessments means it has limited support for evaluating collaborative or team-based coding skills.
  • Algorithm Focus
    The platform often emphasizes algorithmic problem-solving, which may not fully represent the day-to-day coding skills required for certain positions.

NumPy videos

Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

Codility videos

An Introduction to Codility: The Tech Hiring Platform for Engineering Teams

Category Popularity

0-100% (relative to NumPy and Codility)
Data Science And Machine Learning
Hiring And Recruitment
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Online Learning
0 0%
100% 100

User comments

Share your experience with using NumPy and Codility. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare NumPy and Codility

NumPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

Codility Reviews

Examining Top 22 Alternatives to LeetCode
Codility is a platform that helps companies assess the coding skills of developers. They offer a range of online coding tests and assessments that enable employers to evaluate candidates' technical abilities.
Source: www.inven.ai

Social recommendations and mentions

Based on our record, NumPy seems to be a lot more popular than Codility. While we know about 119 links to NumPy, we've tracked only 2 mentions of Codility. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

NumPy mentions (119)

  • Building an AI-powered Financial Data Analyzer with NodeJS, Python, SvelteKit, and TailwindCSS - Part 0
    The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / 3 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / 8 months ago
  • Intro to Ray on GKE
    The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as... - Source: dev.to / 8 months ago
  • Streamlit 101: The fundamentals of a Python data app
    It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”. - Source: dev.to / 9 months ago
  • A simple way to extract all detected objects from image and save them as separate images using YOLOv8.2 and OpenCV
    The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 9 months ago
View more

Codility mentions (2)

  • How to Hire Mobile App Developers
    - Technical skills: have they got the walk to match the talk? Programming languages on a resume mean little if candidates are unable to demonstrate their hard coding skills. You can test these skills with technical skill tests, such as the ones created by Codility or HackerRank. - Source: dev.to / about 1 year ago
  • Best Websites Every Programmer Should Visit
    Codility : Verify and improve coding skills. - Source: dev.to / about 4 years ago

What are some alternatives?

When comparing NumPy and Codility, you can also consider the following products

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

HackerRank - HackerRank is a platform that allows companies to conduct interviews remotely to hire developers and for technical assessment purposes.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

CodeSignal - CodeSignal is the leading assessment platform for technical hiring.

OpenCV - OpenCV is the world's biggest computer vision library

iMocha - Make intelligent talent decisions.