Apex is a proprietary language which has been developed by Salesforce.com. Apex is a strongly typed, object-oriented programming language that allows developers to execute flow and transaction control statements on the Force.com platform server in conjunction with calls to the Force.com API.
Apex Code is designed explicitly for expressing business logic and manipulating data, rather than generically supporting other programming tasks such as user interfaces and interaction.
Apex Code is therefore conceptually closer to the stored procedure languages common in traditional database environments, such as PL/SQL and Transact-SQL. But unlike those languages, which due to their heritage can be terse and difficult to use, Apex Code uses a Java-like syntax, making it straightforward for most developers to understand.
And like Java, Apex Code is strongly typed, meaning that the code is compiled by the developer before it is executed, and that variables must be associated with specific object types during this compile process. Control structures are also Java-like, with for/while loops and iterators borrowing that syntax directly. Because Apex Code is a process and data language, developers will primarily interact with APIs to query, manipulate and save information in their custom and standard objects.
Developers can select data using the existing Salesforce Object Query Language (SOQL) syntax already found in the existing Web services API, as well as a new addition to that syntax that can retrieve information from multiple objects via a single query.
Delphi is both an object oriented programming language (OOP) and an Integrated Development Environment (IDE). Published by the Embarcadero company (formerly CodeGear and more formerly Borland), Delphi is an alternative to language such as Visual Basic offering development with both rapidity and good quality.
Delphi includes the RunTime Library (RTL) that provides basic functionality across all the platforms. For Windows it provides the Visual Component Library (VCL), and for cross platform development it includes FireMonkey (FMX).
Delphi includes a code editor, a visual designer, an integrated debugger, a source code control component, and support for third-party plugins. The code editor features Code Insight (code completion), Error Insight (real-time error-checking), and refactoring.
The visual forms designer has traditionally used Visual Component Library (VCL) for native Windows development, but the FireMonkey (FMX) platform was later added for cross-platform development. Database support in Delphi is very strong. A Delphi project of a million lines to compile in a few seconds – one benchmark gave 170,000 lines per second.
It provides interfaces for the programmer to build an application using the Extensible Markup Language (XML), Extensible Stylesheet Language (XSL), Simple Object Access Protocol (SOAP), and Web Services Description Language (WSDL).
MLlib (Spark) is Apache Spark’s machine learning library. Its goal is to make practical machine learning scalable and easy. It consists of common learning algorithms and utilities, including classification, regression, clustering, collaborative filtering, dimensionality reduction, as well as lower-level optimization primitives and higher-level pipeline APIs.
Regression: generalized linear regression, survival regression,...
Decision trees, random forests, and gradient-boosted trees
Recommendation: alternating least squares (ALS)
Clustering: K-means, Gaussian mixtures (GMMs),...
Topic modeling: latent Dirichlet allocation (LDA)
Frequent itemsets, association rules, and sequential pattern mining
Spark revolves around the concept of a resilient distributed dataset (RDD), which is a fault-tolerant collection of elements that can be operated on in parallel. There are two ways to create RDDs: parallelizing an existing collection in your driver program, or referencing a dataset in an external storage system, such as a shared filesystem, HDFS, HBase, or any data source offering a Hadoop InputFormat.
Statsmodels is a Python package that allows users to explore data, estimate statistical models, and perform statistical tests. Statsmodels is built on top of the numerical libraries NumPy and SciPy, integrates with Pandas for data handling and uses Patsy for an R-like formula interface.
Statsmodels is part of the scientific Python stack that is oriented towards data analysis, data science and statistics. Statsmodels is built on top of the numerical libraries NumPy and SciPy, integrates with Pandas for data handling and uses Patsy for an R-like formula interface. Graphical functions are based on the Matplotlib library. Statsmodels provides the statistical backend for other Python libraries. Statmodels in free software released under the Modified BSD (3-clause) license.
Linear regression models:
Mixed Linear Model with mixed effects and variance components
GLM: Generalized linear models with support for all of the one-parameter exponential family distributions
Bayesian Mixed GLM for Binomial and Poisson
GEE: Generalized Estimating Equations for one-way clustered or longitudinal data
Nonparametric statistics: Univariate and multivariate kernel density estimators
Datasets: Datasets used for examples and in testing
Statistics: a wide range of statistical tests
Imputation with MICE, regression on order statistic and Gaussian imputation
Tools for reading Stata .dta files, but pandas has a more recent version
Scapy is a powerful interactive packet manipulation program. It is able to forge or decode packets of a wide number of protocols, send them on the wire, capture them, match requests and replies, and much more. It can easily handle most classical tasks like scanning, tracerouting, probing, unit tests, attacks or network discovery (it can replace hping, 85% of nmap, arpspoof, arp-sk, arping, tcpdump, tethereal, p0f, etc.).
It also performs very well at a lot of other specific tasks that most other tools can’t handle, like sending invalid frames, injecting your own 802.11 frames, combining technics
Scapy is a packet manipulation tool for computer networks, written in Python by Philippe Biondi. It can forge or decode packets, send them on the wire, capture them, and match requests and replies. It can also handle tasks like scanning, tracerouting, probing, unit tests, attacks, and network discovery.
Scapy provides a Python interface into libpcap, (WinPCap/Npcap on Windows), in a similar way to that in which Wireshark provides a view and capture GUI. It can interface with a number of other programs to provide visualization including Wireshark for decoding packets, GnuPlot for providing graphs, graphviz or VPython for visualisation, etc.
The concept behind Scapy is that it is cable of sending and receiving packets and it can sniff packets. The packets to be sent can be created easily using the built-in options and the received packets can be dissected. Sniffing of packets helps in understanding what communication is taking place on the network.
TopoJSON is an extension of GeoJSON that encodes topology. Rather than representing geometries discretely, geometries in TopoJSON files are stitched together from shared line segments called arcs. This technique is similar to Matt Bloch’s MapShaper and the Arc/Info Export format, .e00.
TopoJSON eliminates redundancy, allowing related geometries to be stored efficiently in the same file. For example, the shared boundary between California and Nevada is represented only once, rather than being duplicated for both states. A single TopoJSON file can contain multiple feature collections without duplication, such as states and counties. Or, a TopoJSON file can efficiently represent both polygons (for fill) and boundaries (for stroke) as two feature collections that share the same arc mesh.
A TopoJSON file format is a format that encodes topology. TopoJSON is an extension of geoJSON. This format contains both geospatial data (arcs) and attribute data. In contrast to other GIS formats topoJSON uses arcs. Arcs are sequences of points, while line strings and polygons are defined as sequences of arcs.
Each arc is defined only once, but can be referenced several times by different shapes, thus reducing redundancy and decreasing the file size. The topoJSON format is a format that is used by software like Microsoft PowerBI.