Unirest

Unirest

Kong
+
+

Related Products

  • SurveyJS
    64 Ratings
    Visit Website
  • HR Partner
    205 Ratings
    Visit Website
  • JOpt.TourOptimizer
    10 Ratings
    Visit Website
  • SaaSify
    71 Ratings
    Visit Website
  • CredentialStream
    190 Ratings
    Visit Website
  • CirrusPrint
    2 Ratings
    Visit Website
  • AuctionMethod
    43 Ratings
    Visit Website
  • KonstructIQ
    7 Ratings
    Visit Website
  • Zahara
    34 Ratings
    Visit Website
  • DataImpulse
    31 Ratings
    Visit Website

About

Unirest is a set of lightweight HTTP libraries available in multiple languages, built and maintained by Kong, who also maintains the open-source API Gateway Kong. To utilize Unirest for node.js install the npm module. You're probably wondering how using Unirest makes creating requests easier. Besides automatically supporting gzip, and parsing responses, you can start with basic examples. A request can be initiated by invoking the appropriate method on the Unirest object, then calling .end() to send the request. Alternatively, you can send the request directly by providing a callback along with the URL. Provides simple and easy-to-use methods for manipulating the request prior to being sent. This object is created when a Unirest method is invoked. This object contains methods that are chainable like other libraries such as jQuery and popular request module Superagent (which this library is modeled after slightly).

About

statsmodels is a Python module that provides classes and functions for the estimation of many different statistical models, as well as for conducting statistical tests and statistical data exploration. An extensive list of result statistics is available for each estimator. The results are tested against existing statistical packages to ensure that they are correct. The package is released under the open-source Modified BSD (3-clause) license. statsmodels supports specifying models using R-style formulas and pandas DataFrames. Have a look at dir(results) to see available results. Attributes are described in results.__doc__ and results methods have their own docstrings. You can also use numpy arrays instead of formulas. The easiest way to install statsmodels is to install it as part of the Anaconda distribution, a cross-platform distribution for data analysis and scientific computing. This is the recommended installation method for most users.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Professional users seeking a solution offering HTTP libraries for parsing responses

Audience

Users and anyone in search of a solution to calculate the estimation of many different statistical models

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Kong
www.npmjs.com/package/unirest

Company Information

statsmodels
www.statsmodels.org/stable/index.html

Alternatives

requests

requests

Python Software Foundation

Alternatives

Categories

Categories

Integrations

Anaconda
Python
jQuery

Integrations

Anaconda
Python
jQuery
Claim Unirest and update features and information
Claim Unirest and update features and information
Claim statsmodels and update features and information
Claim statsmodels and update features and information