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  1. Stackups
  2. Utilities
  3. API Tools
  4. Mapping Apis
  5. Leaf vs Leaflet

Leaf vs Leaflet

OverviewComparisonAlternatives

Overview

Leaflet
Leaflet
Stacks1.5K
Followers1.1K
Votes112
GitHub Stars43.9K
Forks6.0K
Leaf
Leaf
Stacks18
Followers42
Votes0
GitHub Stars5.5K
Forks269

Leaf vs Leaflet: What are the differences?

Introduction:

In website development, Leaf and Leaflet are two popular tools used for interactive and dynamic mapping. While they share similarities, there are key differences between them that set them apart.

  1. Architecture: Leaf and Leaflet have different architectural designs. Leaf is a stand-alone JavaScript library that provides a comprehensive set of mapping features and functionalities out of the box. On the other hand, Leaflet is a lightweight open-source library that focuses on simplicity and customization. It provides a core set of mapping features but allows developers to choose and add additional plugins for specific functionalities.

  2. Complexity: Leaf is considered more complex and feature-rich compared to Leaflet. It includes a wide range of built-in mapping capabilities such as animated marker transitions, interactive layers, and advanced vector rendering. Leaflet, on the other hand, is simpler and lighter, providing a basic set of features that can be extended with plugins depending on specific project requirements.

  3. Documentation and Community Support: Leaf has a well-established and extensive documentation along with a large and active community of developers. This makes it easier to find resources, tutorials, and support for implementing complex functionalities. Leaflet also has a good documentation and community, but it may not have the same level of resources and support as Leaf.

  4. Compatibility: Leaf supports a wide variety of web browsers, including older versions, providing better compatibility for different user environments. Leaflet is also compatible with most modern web browsers, but it may require additional polyfills or workarounds for some older browsers.

  5. Development Philosophy: Leaf is built to be a complete solution for complex mapping applications, while Leaflet focuses more on simplicity and modularity. Leaf follows an all-in-one approach, aiming to provide a comprehensive set of features that cover various mapping requirements. Leaflet, on the other hand, follows a modular approach, allowing developers to choose and combine specific plugins to create a tailored mapping solution.

  6. Popularity and Adoption: Both Leaf and Leaflet have a significant user base and are widely adopted in the web development community. However, Leaf has been around for a longer time and has gained more popularity, being used in numerous large-scale projects. Leaflet has also gained significant adoption, especially for smaller projects or simple mapping needs.

In Summary, Leaf and Leaflet differ in terms of architecture, complexity, documentation and support, compatibility, development philosophy, and popularity. These differences make them suited for different mapping requirements and project scopes.

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Detailed Comparison

Leaflet
Leaflet
Leaf
Leaf

Leaflet is an open source JavaScript library for mobile-friendly interactive maps. It is developed by Vladimir Agafonkin of MapBox with a team of dedicated contributors. Weighing just about 30 KB of gzipped JS code, it has all the features most developers ever need for online maps.

Leaf is a Machine Intelligence Framework engineered by software developers, not scientists. It was inspired by the brilliant people behind TensorFlow, Torch, Caffe, Rust and numerous research papers and brings modularity, performance and portability to deep learning. Leaf is lean and tries to introduce minimal technical debt to your stack.

Tile layers;Drag panning with inertia;Scroll wheel zoom;Multi-touch zoom;Zoom animation;Hardware acceleration on iOS;Smart polyline/polygon rendering
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Statistics
GitHub Stars
43.9K
GitHub Stars
5.5K
GitHub Forks
6.0K
GitHub Forks
269
Stacks
1.5K
Stacks
18
Followers
1.1K
Followers
42
Votes
112
Votes
0
Pros & Cons
Pros
  • 34
    Light weight
  • 29
    Free
  • 12
    Evolutive via plugins
  • 11
    OpenStreetMap
  • 10
    Strong community
No community feedback yet
Integrations
No integrations available
Rust
Rust

What are some alternatives to Leaflet, Leaf?

Google Maps

Google Maps

Create rich applications and stunning visualisations of your data, leveraging the comprehensiveness, accuracy, and usability of Google Maps and a modern web platform that scales as you grow.

Mapbox

Mapbox

We make it possible to pin travel spots on Pinterest, find restaurants on Foursquare, and visualize data on GitHub.

TensorFlow

TensorFlow

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

OpenStreetMap

OpenStreetMap

OpenStreetMap is built by a community of mappers that contribute and maintain data about roads, trails, cafés, railway stations, and much more, all over the world.

OpenLayers

OpenLayers

An opensource javascript library to load, display and render maps from multiple sources on web pages.

scikit-learn

scikit-learn

scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.

PyTorch

PyTorch

PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.

Keras

Keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/

ArcGIS

ArcGIS

It is a geographic information system for working with maps and geographic information. It is used for creating and using maps, compiling geographic data, analyzing mapped information, sharing and much more.

Kubeflow

Kubeflow

The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.

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