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LibreTaxi VS NumPy

Compare LibreTaxi VS NumPy and see what are their differences

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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
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LibreTaxi logo LibreTaxi

Open source alternative to Uber/Lyft for Telegram

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • LibreTaxi Landing page
    Landing page //
    2021-07-23
  • NumPy Landing page
    Landing page //
    2023-05-13

LibreTaxi features and specs

  • Open Source
    LibreTaxi is an open-source platform, allowing for transparency and enabling users and developers to modify and improve the platform as needed.
  • Affordable
    LibreTaxi often offers more affordable rates compared to traditional ride-hailing services because it does not charge service fees.
  • Decentralized
    As a decentralized service, LibreTaxi operates without a central authority, providing more autonomy and potentially increased privacy for users.
  • No Service Fees
    LibreTaxi does not take a commission from fares, meaning drivers may retain more of their earnings.
  • Global Reach
    Since it is not limited by geographic restrictions imposed by corporations, LibreTaxi can be used anywhere in the world.

Possible disadvantages of LibreTaxi

  • Lack of Regulation
    The decentralized nature means there is less oversight, which could lead to issues with driver or passenger safety and service quality.
  • Limited Drivers
    As a less well-known platform, it may have fewer drivers available, particularly in less populated or less tech-savvy areas.
  • No In-app Payments
    LibreTaxi does not handle payments within the app, meaning users must arrange payment methods independently, which could be inconvenient.
  • User Interface
    The user interface and overall user experience may not be as polished or feature-rich as established proprietary ride-hailing apps.
  • Customer Support
    Due to its open-source and decentralized nature, customer support may be less reliable and less centralized compared to traditional ride-hailing services.

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.

Analysis of LibreTaxi

Overall verdict

  • LibreTaxi can be considered a good option for certain users.

Why this product is good

  • LibreTaxi is an open-source platform that offers a decentralized and affordable alternative to traditional taxi services. It connects drivers and passengers directly through Telegram, minimizing fees and allowing for greater flexibility. The platform is especially attractive for users who value open-source solutions, privacy, and those in regions where traditional ride-hailing services are not prevalent or too costly.

Recommended for

  • Individuals seeking an affordable ride-hailing service.
  • Users who prefer open-source platforms.
  • Regions where major ride-hailing services are unavailable.
  • Privacy-conscious users who want to avoid mainstream apps.
  • Communities looking for a customizable and scalable solution for local transportation.

Analysis of NumPy

Overall verdict

  • Yes, NumPy is considered good. It is a foundational library in the Python ecosystem for numerical computing and is used globally by researchers, engineers, and data scientists.

Why this product is good

  • NumPy is widely regarded as a good library because it offers fast, flexible, and efficient array handling that is integral to scientific computing in Python. It provides tools for integrating C/C++ and Fortran code, useful linear algebra, random number capabilities, and a vast collection of mathematical functions. Its array broadcasting capabilities and versatility make complex mathematical computations straightforward.

Recommended for

  • Scientists and researchers working with large-scale scientific computations.
  • Data scientists engaged in data analysis and manipulation.
  • Engineers and developers needing performance-optimized mathematical computations.
  • Educators and students in STEM fields.

LibreTaxi videos

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NumPy videos

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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 LibreTaxi and NumPy)

LibreTaxi

NumPy

Ride Sharing
100 100%
Ride Sharing
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Taxi
100 100%
Taxi
0% 0
Data Science Tools
0 0%
Data Science Tools
100% 100

User comments

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Reviews

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

LibreTaxi Reviews

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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 LibreTaxi. While we know about 119 links to NumPy, we've tracked only 6 mentions of LibreTaxi. 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.

LibreTaxi mentions (6)

  • Open source projects for community?
    Why doesn't india have more open source projects? I found [Libre taxi][https://libretaxi.org/] which is basically free open source ride sharing similar to uber\ola but saves the cut of company. This could potentially enable the lower class for higher profit margins. For a country that's a big player in software, we sure don't have many open source projects :(. Source: about 2 years ago
  • Expropriation of surplus value by capital
    Saw this alternative a while back. Haven't tried it, so dunno how good it is: https://libretaxi.org/. Source: almost 3 years ago
  • Fuck Doordash. Fuck UberEats. I'm launching my own open-source non-profit food delivery platform.
    Have you seen LibreTaxi (https://libretaxi.org/)? You might want to build on top on that. Source: about 3 years ago
  • Has Uber/Ola gotten basically unusable or is it just me ?
    There is this app that works using telegram API. It's called libre taxi. https://libretaxi.org/ One advantage with this project is that it is self hosted and federated. Source: about 3 years ago
  • Would anyone like to build a full stack project together?
    A project like libretaxi allows drivers to set their own prices and "haggle" with customers. I think it's a turn off for a customer to not know the price beforehand, and nobody appears to use that service. We would have a way that we democratically decide on a price to set and a percentage that the driver gets, giving drivers the ability to make decisions about how the company is run and ways it can benefit the... Source: over 3 years ago
View more

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 / 4 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 / 9 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 / 10 months ago
View more

What are some alternatives?

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

Uber - Uber is a website and mobile app that allows you to get a ride similar to a taxi service from your phone.

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

Lyft - Lyft is a mobile app that lets you get rides from pace to place for a fee. If you want to be a Lyft driver, you can go to their website and easily sign up to start driving for them. Read more about Lyft.

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

GO-JEK - Home & Family and Online Services

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

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