Formal and Natural Languages
Human languages like English, Spanish, and French are natural languages. These languages evolved spontaneously, despite human attempts to structure them. Understanding human language is challenging due to its complexity. With the exception of relatively small subsets, proper comprehension of natural language frequently necessitates a substantial amount of prior information that is beyond the capability of current technologies. Because natural languages are inherently ambiguous, depending on them may produce unexpected outcomes due to their imprecision.
On the other hand, formal languages are those that are created by individuals for particular uses. The notation used by mathematicians to indicate the relationships between numbers and symbols or by chemists to depict the chemical structure of molecules are examples of formal languages. Syntax requirements in formal languages are typically quite stringent. The fundamental components of language, known as tokens (such as words, numbers, or chemical elements), as well as the arrangement of tokens inside a sentence, are governed by syntax rules.
Formal language
One kind of formal language that was created specifically for expressing computations is programming languages. They function similarly to little languages designed specifically for humans to instruct machines. Because computers take things literally, people communicate with them using specialised languages like programming languages, which enables them to create procedures that are precise and fully comprehensible to both people and computers.
Because there is less ambiguity and fewer exceptions to memorise, computer languages are typically simpler to learn than human languages. One of the clearest and most consistent computer languages is Python. Compared to most computer languages, it has a cleaner syntax and requires less memorisation.
An intermediate between the programmer and the end user, a programming language such as Python provides a standard language for exchanging helpful instruction sequences (programs). Python is used for communication.
Natural Languages
Because natural languages are more complex than computer programming languages, it is currently impossible to translate descriptions written in a natural language, like English, into executable code. Research on artificial intelligence is still ongoing in the field of natural language processing (NLP).
We can investigate the ways in which information from the outside world—which frequently consists of material that was first stated in natural languages—is accessed and processed using formal languages, particularly programming languages like Python.
The Difference Between Formal and Natural Languages Was Discussed:
This is the procedure that uses an automated system to gather data from websites. Investigative journalists, for instance, To assist journalists, programmers have created tools for parsing, analysing, and scraping data from websites.
Because website structures can vary greatly and change frequently, working with data from the Internet can be challenging. Although Python‘s built-in library tools can be used to parse data, PyPI offers a variety of tools that can make the process easier.
One such program designed especially for parsing HTML data gathered from a website is Beautiful Soup. MechanicalSoup is another technology that was described; it is used to interact with website elements such as submitting forms and clicking links. The usual objective while scraping a webpage is to get only relevant information.
Keep in mind that not everyone consents to you retrieving information from their web servers. Before you begin scraping, read the Terms of Use. Also, be considerate of when you time your web requests to avoid overloading a server with traffic.
This may be done to safeguard personal data or because sending a lot of repetitive queries can consume bandwidth, cause other users to experience a slowdown on the website, and possibly overwhelm the server.
Data can also be accessed via interacting with Web APIs (Application Programming Interfaces) in addition to scraping. You can use the Hacker News API to obtain information about submissions and comments on the website without registering for a key.
For instance, a particular URL request can yield details about a top article right now, shown as a dictionary with braces around it. Without improved formatting, this response could be challenging to analyse, indicating the need for programming tools to handle it, such as using the json. dump() method.
Several keys may be present in the data that is obtained from an API call. ‘descendants’ indicates the quantity of comments on a Hacker News item, ‘kids’ gives the IDs of direct comments, ‘title’ gives the article title, and ‘url’ gives a URL to the article. A list of the IDs of the most popular articles on Hacker News right now can be obtained by making another API call.
Each submission ID can then have its own API request made using this list. With this method, you may obtain and analyse data from any API using a comparable procedure. Applications or visualisations could be created using this data. To learn how to extract data from GitHub repositories.One website where a sample program can use web APIs to retrieve information is the Internet Archive’s Wayback Machine.
Essentially, the ability to program in formal languages like Python enables us to create tools that can process and extract data from the web, whether through API interaction with structured data or HTML content scraping. Formal computational techniques are then used to process and analyse this data.By acting as a mediator, the Python language enables people to provide computers with precise instructions [knowledge from the previous turn].