+1 (315) 557-6473 

Creating a PDF Analyzer Application in Python

Are you looking for a convenient way to analyze and search through your PDF files? Look no further! Our PDF Analyzer application simplifies the process of extracting metadata from PDF files and allows you to search for specific PDFs based on their metadata. Whether you need to manage a large collection of PDF documents or find specific files quickly, our PDF Analyzer is the tool you've been searching for. With our PDF Analyzer, you can streamline your document management, saving valuable time and reducing the hassle of manual searching. Say goodbye to the days of hunting for the right document in a sea of PDFs. Our user-friendly tool empowers you to efficiently access the information you need when you need it. Experience the convenience and efficiency of PDF management at its best with our PDF Analyzer.

Developing a PDF Analyzer in Python

Explore how building a Python PDF Analyzer application can significantly assist with your Python assignment. This comprehensive guide equips you with the skills to create a PDF Analyzer in Python, enhancing document management and metadata extraction capabilities. Simplify your workload and strengthen your programming expertise with this guide. Whether you're a student, researcher, or professional, having the ability to efficiently handle PDF documents can be a game-changer. With this knowledge, you can tailor your PDF management solutions to meet your specific needs and work with data more effectively, saving valuable time and streamlining your workflow. Elevate your programming skills by learning to create a powerful tool that simplifies the handling of PDFs, making it a valuable addition to your programming toolbox.

PDF Analyzer Application

This code defines a Python class called `PDFAnalyzer` that uses the `tkinter` library to create a graphical user interface (GUI) application for analyzing PDF files. The application allows users to select a folder containing PDF files, extract metadata from those files, and search for PDFs based on metadata criteria. The main components and their functionality are divided into several blocks as follows:

Block 1: Importing Libraries

```python from tkinter import * from tkinter import filedialog as fd, ttk import pikepdf import csv import re import os from keywords import extract_keywords ```

In this block, the necessary libraries are imported. `tkinter` is used for creating the GUI, `pikepdf` for working with PDF files, `csv` for handling CSV files, `re` for regular expressions, and `os` for file system operations. Additionally, a custom function `extract_keywords` is imported from a module named `keywords`.

Block 2: Class Definition

```python class PDFAnalyzer: def __init__(self) -> None: # Constructor method self.analyzed_pdf_files = [] # List to store analyzed PDFs self.search_results = [] # List to store search results def analyze_pdf(self, pdf_path): # Method to analyze a specific PDF file # Extract metadata and add it to analyzed_pdf_files pass def search_pdf(self, keyword): # Method to search for PDFs based on a keyword # Populate search_results with matching PDFs pass def generate_report(self, output_path): # Method to generate a summary report of analyzed PDFs pass # Create an instance of the PDFAnalyzer class pdf_analyzer = PDFAnalyzer() ```

This block defines the `PDFAnalyzer` class. The class contains various methods and properties for building the PDF analysis application.

Block 3: Initializing the GUI

```python from tkinter import * # Create the root window self.window = Tk() # Set window title self.window.title('PDF Analyzer') # Set window size self.window.geometry("700x600") # Set window background color self.window.config(background="white") ```

This part initializes the main window for the GUI application using `tkinter`. It sets the title, size, and background color for the window.

Block 4: Creating User Interface Elements

```python # Create user interface elements (buttons, labels, input fields) self.btn_select_folder = Button(self.window, text='Select Folder', width=25, command=self.select_dir) self.label_search_folder = Label(self.window, text="Click the button to browse the Folder containing PDF files") self.label_analyze_progress = Label(self.window, text="Status") self.label_search_keyword = Label(self.window, text="Input your keyword...") self.input_search_keyword = ttk.Entry() self.btn_search_keyword = Button(self.window, text="Search", width=25, command=self.search) ```

This section creates various user interface elements, including buttons, labels, and input fields, and sets their properties. These elements are used to interact with the application.

Block 5: Creating PDF File List Table

```python # Creating a table - pdf_file_list self.columns = ("No", "url") self.tree_pdf_files = ttk.Treeview(columns=self.columns, show="headings") self.tree_pdf_files.grid(column=0, columnspan=3, row=0) self.tree_pdf_files.heading("No", text="No") self.tree_pdf_files.column("#1", width=60) self.tree_pdf_files.heading("url", text="url") self.tree_pdf_files.column("#2", width=500) self.scrollbar = ttk.Scrollbar( self.window, orient=VERTICAL, command=self.tree_pdf_files ) self.tree_pdf_files.configure(yscrollcommand=self.scrollbar.set) self.scrollbar.grid(column=3, row=0, rowspan=1, sticky=NS) ```

This section sets up a table (using `ttk.Treeview`) to display a list of PDF files in the selected folder. It configures the table's columns, headings, and scrollbar.

Block 6: Creating Search List Table

```python # Creating a table - search_list self.tree_search_list = ttk.Treeview(columns=self.columns, show="headings") self.tree_search_list.grid(column=0, columnspan=3, row=4) self.tree_search_list.heading("No", text="No") self.tree_search_list.column("#1", width=60) self.tree_search_list.heading("url", text="url") self.tree_search_list.column("#2", width=500) self.scrollbar = ttk.Scrollbar( self.window, orient=VERTICAL, command=self.tree_search_list ) self.tree_search_list.configure(yscrollcommand=self.scrollbar.set) self.scrollbar.grid(column=3, row=4, rowspan=1, sticky=NS) ```

This part is similar to Block 5 but configures a separate table for displaying search results.

Block 7: Placing GUI Elements

```python # Placing user interface elements in the window self.label_search_folder.grid(column=0, row=1) self.btn_select_folder.grid(column=2, row=1) self.label_analyze_progress.grid(column=0, row=2) self.label_search_keyword.grid(column=0, row=3) self.input_search_keyword.grid(column=1, row=3, sticky=NSEW, padx=10) self.btn_search_keyword.grid(column=2, row=3) ```

This block positions the previously created UI elements in the window, specifying their layout within the application's interface.

Block 8: Window Event Handling

```python # Window event handling def on_closing(): self.window.destroy() self.window.protocol("WM_DELETE_WINDOW", on_closing) self.window.mainloop() ```

This block defines an event handler for the window's close button, allowing the application to gracefully exit when the user closes the window.

Block 9: Selecting a Folder

```python def select_dir(self): try: folder_path = fd.askdirectory(initialdir="./", title="Select a directory") if folder_path != '': self.label_search_folder.config(text=folder_path) self.label_analyze_progress.config(text="Analyzing files...") self.generate_csv(folder_path) else: pass except Exception as e: raise e ```

This method is called when the "Select Folder" button is pressed. It opens a file dialog for the user to choose a folder containing PDF files and then triggers the PDF analysis process.

Block 10: Generating CSV Metadata

```python def generate_csv(self, path): pdf_file_list = [] fieldnames = ['Name', 'Title', 'Author', 'CreationDate', 'Keywords', 'Short summary'] meta_info = {} index = 0 # Clear pdf_file_tree view for i in self.tree_pdf_files.get_children(): self.tree_pdf_files.delete(i) # Get lists of names for all PDF files in the folder for dirpath, dirnames, filenames in os.walk(path): for filename in filenames: if filename.endswith('.pdf'): pdf_file_list.append(os.path.join(dirpath, filename)) index = index + 1 self.tree_pdf_files.insert("", END, values=(index, os.path.join(dirpath, filename))) self.label_analyze_progress.config(text='Loading files finished.') # Save metadata to a CSV file with open('metadata.csv', 'w', encoding='UTF8', newline='') as f: writer = csv.DictWriter(f, fieldnames=fieldnames) writer.writeheader() for pdf_file in pdf_file_list: pdf = pikepdf.Pdf.open(pdf_file) # Open the PDF file docinfo = pdf.docinfo # Get info from the PDF file meta_info.clear() meta_info = { 'Name': pdf_file, 'Title': '', 'Author': '', 'CreationDate': '', 'Keywords': '', 'Short summary': '' } for key, value in docinfo.items(): # Make metadata from info key_data = key[1:] if key_data in fieldnames: if value != '': meta_info[key_data] = value keywords = extract_keywords(pdf_file) # Get keywords from the PDF file keywords_str_version = "" for keyword in keywords: keywords_str_version += f'{keyword}. ' meta_info['Keywords'] = keywords_str_version writer.writerow(meta_info) # Write data to the CSV file self.label_analyze_progress.config(text="Analyzing finished.") ```

This method extracts metadata from PDF files within the selected folder, including information such as the file name, title, author, creation date, keywords, and a short summary. It stores this metadata in a CSV file named "metadata.csv."

Block 11: Searching for PDFs

```python def search(self): search_text = self.input_search_keyword.get() # Get search text index = 0 pattern = f".*{search_text}.*".lower() for i in self.tree_search_list.get_children(): self.tree_search_list.delete(i) with open('metadata.csv', 'r', encoding='UTF8') as f: # Open the CSV file containing metadata csv_reader = csv.reader(f) for line_no, line in enumerate(csv_reader, 1): if ( re.findall(pattern, line[0].lower()) or re.findall(pattern, line[1].lower()) or re.findall(pattern, line[2].lower()) or re.findall(pattern, line[4].lower()) ): # Find text in metadata (title, author, keywords, etc.) index = index + 1 self.tree_search_list.insert("", END, values=(index, line[0])) ```

This method is called when the "Search" button is pressed. It searches for PDF files in the metadata CSV file that match the user-provided search criteria (keywords). Matching files are displayed in the search results table.

Block 12: Application Entry Point

```python pdfAnalyzer = PDFAnalyzer() ```

Finally, an instance of the `PDFAnalyzer` class is created, which initiates the GUI application when the script is executed.


Simplify the management of your PDF documents with the PDF Analyzer. This tool is designed to enhance your document organization and retrieval, making it a valuable asset for students, researchers, professionals, and anyone dealing with PDF files. The PDF Analyzer is not just a time-saver; it's a productivity booster, ensuring you can spend less time on administrative tasks and more time on what truly matters – your work and research. Say goodbye to the frustration of disorganized PDFs and welcome a new era of streamlined document management. Experience the difference today with the PDF Analyzer – your gateway to efficient and stress-free PDF handling.