The Zacks Analyst Recommendations API allows developers to access and integrate the functionality and data of Zacks Analyst Recommendations database. This database offers analysts recommendations for over 5000 publicly traded companies as calculated by Zacks Research.
The following is a list of SDKs from our SDK directory that matched your search term. Though your definition of an SDK may differ, in our world, we define SDKs as platform- specific tools for consuming existing APIs of the sort we list in our API directory. For example, the Ruby SDK for consuming the Twitter Ads API. If you think an SDK, API, or other asset is missing from our directory, be sure to check our guidelines for making contributions to ProgrammableWeb.
The Zacks Data C# SDK by HubertJ access the financial analysis, earnings, and trends features of the API. Resources include a tutorial that explains data validation before a request. Download references available. To know more about how the API works, visit https://www.quandl.com/help/api
The Zacks Data Java SDK by Jim Moores aims to be a complete resource to interact with the API features of financial analysis, earnings and trends. Available at a website named Quandl4j, developers can find design principles, release notes, tutorial, documentation, roadmap, contribution, community, versioning, bugs, and copyright.
The Zacks Data Ruby SDK by Zacks/Quandl allows data interaction with financial analysis, earnings, and estimate trends. It contains gem installation and Api key configuration. Guides explain how to retrieve data and work with the results. Because this is the official gem resource, developers can work with the latest RESTful version of the API. By Clement Leung.
With the Zacks Data Python SDK by Quandl, developers can access the API data of financial analysis, earnings, and estimate trends. Resources encompass usage with search, get, and push examples. Installation via pip. Authored by Matthew Basset. Developers require previous knowledge of Pandas, a Python data analysis library available at http://pandas.pydata.org/