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Travis CI VS NumPy

Compare Travis CI VS NumPy and see what are their differences

LibHunt
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives. featured
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Travis CI logo Travis CI

Focus on writing code. Let Travis CI take care of running your tests and deploying your apps.

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Travis CI Landing page
    Landing page //
    2023-01-06
  • NumPy Landing page
    Landing page //
    2023-05-13

Travis CI videos

+ Add

GitHub, Travis CI - Lecture 9 - CS50's Web Programming with Python and JavaScript 2018

More videos:

  • Tutorial - How to run Android tests on Travis CI

NumPy videos

+ Add

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

Category Popularity

0-100% (relative to Travis CI and NumPy)

Travis CI

NumPy

Continuous Integration
100 100%
Continuous Integration
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
DevOps Tools
100 100%
DevOps Tools
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

Share your experience with using Travis CI and NumPy. For example, how are they different and which one is better?
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Reviews

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

Travis CI Reviews

10 Jenkins Alternatives in 2021 for Developers
You might find that Travis CI proudly promotes the fact that they have more than 900,000 open-source projects and 600,000 users on their platform with Travis CI. Automated deployment can be quickly established by following the tutorials and documentation that are currently available on their website.
Source: solutionsuggest.com
The Best Alternatives to Jenkins for Developers
Travis CI is a continuous integration and testing CI/CD tool. It is free of cost for open source projects and provides seamless integration with GitHub. It supports more than 20 languages, like Node.js, PHP, Python, etc. along with Docker.
Source: www.lambdatest.com
Continuous Integration. CircleCI vs Travis CI vs Jenkins
Travis CI is recommended for cases when you are working on the open-source projects, that should be tested in different environments.
Source: djangostars.com

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.
Source: www.analyticsvidhya.com
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

Social recommendations and mentions

Based on our record, NumPy seems to be a lot more popular than Travis CI. While we know about 108 links to NumPy, we've tracked only 6 mentions of Travis CI. 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.

Travis CI mentions (6)

  • Front-end Guide
    We used Travis CI for our continuous integration (CI) pipeline. Travis is a highly popular CI on Github and its build matrix feature is useful for repositories which contain multiple projects like Grab's. We configured Travis to do the following:. - Source: dev.to / over 1 year ago
  • Flutter
    CI/CD for autobuild + autotests (Codemagic or Travis CI). Source: over 1 year ago
  • How To Build Your First CI/CD Pipeline With Travis CI?
    Step 2: Log on to Travis CI and sign up with your GitHub account used above. - Source: dev.to / almost 2 years ago
  • What does a DevOps engineer actually do?
    Some other hosted CI products, such as CircleCI and Travis Cl, are completely hosted in the cloud. It is becoming more popular for small organizations to use hosted CI products, as they allow engineering teams to begin continuous integration as soon as possible. Source: almost 3 years ago
  • Hosting an Angular application on GitHub Pages using Travis CI
    1. Let's create the account. Access the site https://travis-ci.com/ and click on the button Sign up. - Source: dev.to / almost 3 years ago
View more

NumPy mentions (108)

  • 2 Minutes to JupyterLab Notebook on Docker Desktop
    Below is an example of a code cell. We'll visualize some simple data using two popular packages in Python. We'll use NumPy to create some random data, and Matplotlib to visualize it. - Source: dev.to / 9 months ago
  • Element-wise vs Matrix vs Dot multiplication
    In NumPy with * or multiply(). ` or multiply()` can multiply 0D or more D arrays by element-wise multiplication. - Source: dev.to / 3 months ago
  • JSON in data science projects: tips & tricks
    Data science projects often use numpy. However, numpy objects are not JSON-serializable and therefore require conversion to standard python objects in order to be saved:. - Source: dev.to / 3 months ago
  • Introducing Flama for Robust Machine Learning APIs
    Numpy: A library for scientific computing in Python. - Source: dev.to / 6 months ago
  • A Comprehensive Guide to NumPy Arrays
    Python has become a preferred language for data analysis due to its simplicity and robust library ecosystem. Among these, NumPy stands out with its efficient handling of numerical data. Let’s say you’re working with numbers for large data sets—something Python’s native data structures may find challenging. That’s where NumPy arrays come into play, making numerical computations seamless and speedy. - Source: dev.to / 7 months ago
View more

What are some alternatives?

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

Jenkins - Jenkins is an open-source continuous integration server with 300+ plugins to support all kinds of software development

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

CircleCI - CircleCI gives web developers powerful Continuous Integration and Deployment with easy setup and maintenance.

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

Codeship - Codeship is a fast and secure hosted Continuous Delivery platform that scales with your needs.

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

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