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When working with big data, the first and most crucial step is to ensure a reliable data source. Our approach involves using Python to scrape data from government websites, focusing on the three major financial reports—profit statements, balance sheets, and cash flow statements—from industries such as banking, securities, stocks, and trusts. Once collected, the data undergoes analysis and is then stored in a structured database. To perform the data analysis, we use Java programming, which allows for efficient and scalable processing of the financial reports.
The program design follows the principles of object-oriented programming (OOP) in Java. By leveraging features like inheritance, encapsulation, and polymorphism, we have created a modular and maintainable system. This design ensures that previously written classes can be reused, reducing redundancy and making future modifications easier.
The overall architecture of the system is built around a parent class called `ParentTable`, which contains three core methods:
- `matchStartLine()`: This method identifies the starting line of the financial reports within a document.
- `matchEndLine()`: This method locates the end of the report section.
- `anla()`: This method parses the rows of the report and extracts meaningful data.
When dealing with different PDF formats, these methods can be overridden to handle various table structures, allowing the system to adapt to different layouts. A new class called `PDFFile` is introduced, which uses the `anla()` method from the `ParentTable` class to process all tables found in a given PDF file.
Here’s an example of how the parsing function works:
```java
public boolean anla() {
for (ParentTable table : tables) {
int nIndexStart = table.matchStartLine(lines);
int nIndexEnd = table.matchEndLine(lines);
// Remove the table content from the original lines
String[] arrTableLines = new String[nIndexEnd - nIndexStart + 1];
System.arraycopy(lines, nIndexStart, arrTableLines, 0, nIndexEnd - nIndexStart + 1);
if (arrTableLines.length <= 0)
continue;
table.setTableLines(arrTableLines);
table.anla();
}
}
```
By calling the `anla()` method in the `PDFFile` class, the entire set of tables in the provided PDF files will be processed sequentially, ensuring that each table is correctly matched and analyzed.
In the next section, we will explore how to implement multithreading to improve the efficiency of parsing multiple PDF files simultaneously, enabling faster data processing and better resource utilization.
Consumer Electronics
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