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To order parcer development follow this steps

1

Choose information sources

Where you'd like to retrieve information from. For example:Source: Online store of goods.https://blackone.com.ua

2

Define the types of columns

What exactly information you need:- Product names
- Prices
- Links
- Images

3

Choose format of final result

 - Excel- CSV- XML- Graphic

Prepare the information for the order according to the list above and place the order

Why do you need a parser?

    Price monitoring of competitors is a necessity for the owner of an online store in order for his price offers to be relevant for customers. If the store has up to 10 product names, it can be done manually, but if there are more, then the only solution is to automate the process of collecting information.

    Filling sites with content. If you need to quickly fill the store with content, the parser will quickly collect the necessary information. The disadvantage of this method is that the content will not be unique and may also contain intellectual property protection tools. Therefore, parsing should be used carefully in this case.

    Formation of contacts for the client base. The sales department always needs new contacts to increase sales, so a parser will collect and systematize a given data structure to start sales. Relevant channel for the work of realtors.

    Collection of market information on quotes. For example, forex, cryptocurrencies, stock quotes, etc. If you need more in-depth analysis, you can add the data visualization module described above.

    Formation and updating of own database in the selected context, industry or according to certain criteria. For example, the formation of a database of companies, which contains their financial, economic, structural, production indicators. Relevant for investment banks engaged in raising capital and M&A.

What is the parsing and how it works?

Parsing is the process of converting formatted text into a data structure. The data structure type can be any suitable representation of the information embedded in the source text. The most popular and convenient is the presentation of raw data in Excel and CSV (text file separated by commas). The reason for such popularity is a convenient toolkit for manual data manipulation and their graphical presentation for analysis. The most simple tool for graphical representation is, of course, Excel, but for the analysis of large volumes of data (Big Data Science) it is not convenient due to very slow processing of queries. For these purposes, it is convenient to use a Python module called Plotly. A very advanced and effective tool.

Illustration

An example of graphical display of data using Plotly


Parsing stagesThe parser analyzes the output text to match the specified format. If the text does not match the format, you see, or pardons are rotated. As if zbіgaєtsya, rotates "the structure of data".
Scanning is the process of converting a stream of characters into markers. A lexeme represents a "concept" introduced by a format and can be thought of as a label assigned to one or more characters. From a processing perspective: A token is an object that can contain type, token, location information, etc.
● Syntactic analysis examines the resulting structure as "the storage of tokens as they appeared." It also validates and extracts sample data to create the desired data structure. Errors that occur at this stage are called syntax errors.
● Data structure formation. At this stage, we receive information in a "raw" form and transform it into a form convenient for analysis.

AN EXAMPLE OF A PARSER FOR AN INTERNET STORE

1. Save the downloaded file to some folder, for example "Parser" and run it. The file does not contain any hidden features and does not carry any danger.2. At the end of the scan, you will see the received information in the console and in the newly created output.csv file3. Create a new file in Excel4. Go to the Data menu -> From a text file or CSV file -> Download the output.csv file of the same folder that you created in step 1.
Analyse and work with final data.