Confluence is project management tool which provide you best platform to create, organize, and discuss work with your team. Confluence makes team to spend less time hunting things down and more time making things happen. Organize your work, create documents, and discuss everything in one place.
Below operation we can perform under Jira confluence tool:
Create anything your team needs - meeting notes, product requirements, knowledge base articles - on the web so everyone can contribute.
Give feedback on any Confluence page or file with inline and pinned comments. No more ridiculous file_names_with_dates.doc or messy track changes.
Capture all the information that's scattered among email inboxes and countless apps in the same place.
Give every team, project, or department its own space to store work. Confluence keeps everything organized and accessible.
Confluence gives you the power to create anything - meeting notes, project plans, product requirements, etc. – thanks to a simple, but powerful editor.
You work with files every day – images, PDFs, spreadsheets, and presentations. You can give feedback directly on your files in Confluence, and it keeps tracks of versions automatically, so you're always working on the right one.
Create reports and charts
Reporting on information stored in JIRA is simple in Confluence. In addition to the JIRA Issues Macro, you can use the JIRA Report blueprint or JIRA Chart macro to show information from your JIRA application visually. It's the best way to give your stakeholders a snapshot of your team or project's progress.
Use the JIRA report blueprint to create a Change Log or Status report.
Use the JIRA Chart Micros to display data as a chart, including pie charts, created vs resolved, and two dimensional charts.
Use JIRA Gadgets to display detailed JIRA reports and charts on pages.
Webware for Python. Webware for Python is an object-oriented, Python web application framework. The suite uses well known design patterns and includes a fast application server, servlets, Python Server Pages (PSP), object-relational mapping, Task Scheduling, Session Management, and many other features.
Webware for Python is a suite of programming tools for constructing web-based applications in Python. It features:
Traditional web development tools:
Python-based Server Pages
Object-relational mapping (ORM)
Webware for Python is well proven and platform-independent. It is compatible with multiple web servers, database servers, and operating systems.
Pyramid is a Python web application framework. It is designed to make creating web applications easier. It is open source. A pyramid is fully compatible with Python 3.
With Pyramid, we can write very small applications without needing to know a lot. And by learning a bit more, you can write very large applications too.
Pyramid will allow you to become productive quickly and will grow with you. It won't hold you back when your application is small, and it won't get in your way when your application becomes large. Other application frameworks seem to fall into two non-overlapping categories: those that support "small apps" and those designed for "big apps".
Pyramid can automatically detect changes you make to template files and code, so your changes are immediately available in your browser. You can debug using plain old print() calls, which will display to your console.
Pyramid has a debug toolbar that allows you to see information about how your application is working right in your browser. See configuration, installed packages, SQL queries, logging statements and more.
MLlib is Spark’s scalable machine learning library consisting of common learning algorithms and utilities, including classification, regression, clustering, collaborative filtering, dimensionality reduction, as well as underlying optimization primitives, as outlined below:
Classification and regression
Feature extraction and transformation
Spark Core is the foundation of the overall project. It provides distributed task dispatching, scheduling, and basic I/O functionalities, exposed through an application programming interface centered on the RDD abstraction This interface mirrors a functional/higher-order model of programming: a "driver" program invokes parallel operations such as map, filter or reduce on an RDD by passing a function to Spark, which then schedules the function's execution in parallel on the cluster.
These operations, and additional ones such as joins, take RDDs as input and produce new RDDs. RDDs are immutable and their operations are lazy; fault-tolerance is achieved by keeping track of the "lineage" of each RDD so that it can be reconstructed in the case of data loss. RDDs can contain any type of Python, Java, or Scala objects.
Light GBM is a fast, distributed, high-performance gradient boosting framework based on decision tree algorithm, used for ranking, classification and many other machine learning tasks.
Since it is based on decision tree algorithms, it splits the tree leaf wise with the best fit whereas other boosting algorithms split the tree depth wise or level wise rather than leaf-wise. So when growing on the same leaf in Light GBM, the leaf-wise algorithm can reduce more loss than the level-wise algorithm and hence results in much better accuracy which can rarely be achieved by any of the existing boosting algorithms. Also, it is surprisingly very fast, hence the word ‘Light’.
Watir (Web Application Testing in Ruby, pronounced water), is an open-source family of Ruby libraries for automating web browsers. It drives Internet Explorer, Firefox, Chrome, Opera and Safari, and is available as a RubyGems gem.
Watir-classic makes use of the fact that Ruby has built in Object Linking and Embedding (OLE) capabilities. As such it is possible to drive Internet Explorer programmatically. Watir-classic operates differently than HTTP based test tools, which operate by simulating a browser. Instead Watir-classic directly drives the browser through the OLE protocol, which is implemented over the Component Object Model (COM) architecture.
The COM permits interprocess communication (such as between Ruby and Internet Explorer) and dynamic object creation and manipulation (which is what the Ruby program does to the Internet Explorer). Microsoft calls this OLE automation, and calls the manipulating program an automation controller. Technically, the Internet Explorer process is the server and serves the automation objects, exposing their methods; while the Ruby program then becomes the client which manipulates the automation objects.
Watir-webdriver is a modern version of the Watir API based on Selenium. Selenium 2.0 (selenium-webdriver) aims to be the reference implementation of the WebDriver specification. In Ruby, Jari Bakken has implemented the Watir API as a wrapper around the Selenium 2.0 API. Not only is Watir-webdriver derived from Selenium 2.0, it is also built from the HTML specification, so Watir-webdriver should always be compatible with existing W3C specifications.
The Spring Web model-view-controller (MVC) framework is designed around a DispatcherServlet that dispatches requests to handlers, with configurable handler mappings, view resolution, locale and theme resolution as well as support for uploading files.
The default handler is based on the @Controller and @RequestMapping annotations, offering a wide range of flexible handling methods. With the introduction of Spring 3.0, the @Controller mechanism also allows you to create RESTful Web sites and applications, through the @PathVariable annotation and other features.
Spring Web MVC you can use any object as a command or form-backing object; you do not need to implement a framework-specific interface or base class. Spring's data binding is highly flexible: for example, it treats type mismatches as validation errors that can be evaluated by the application, not as system errors.
Thus you need not duplicate your business objects' properties as simple, untyped strings in your form objects simply to handle invalid submissions, or to convert the Strings properly. Instead, it is often preferable to bind directly to your business objects.
Spring's view resolution is extremely flexible. A Controller is typically responsible for preparing a model Map with data and selecting a view name but it can also write directly to the response stream and complete the request. View name resolution is highly configurable through file extension or Accept header content type negotiation, through bean names, a properties file, or even a custom ViewResolver implementation.
The model (the M in MVC) is a Map interface, which allows for the complete abstraction of the view technology. You can integrate directly with template based rendering technologies such as JSP, Velocity and Freemarker, or directly generate XML, JSON, Atom, and many other types of content. The model Map is simply transformed into an appropriate format, such as JSP request attributes, a Velocity template model.
Spring MVC, like many other web frameworks, is designed around the front controller pattern where a central Servlet, the DispatcherServlet, provides a shared algorithm for request processing while actual work is performed by configurable, delegate components. This model is flexible and supports diverse workflows.
The DispatcherServlet, as any Servlet, needs to be declared and mapped according to the Servlet specification using Java configuration or in web.xml. In turn the DispatcherServlet uses Spring configuration to discover the delegate components it needs for request mapping, view resolution, exception handling