Create Orig file

Orig file

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+import gradio as gr
+import pandas as pd
+import logging
+import requests
+from urllib.parse import quote
+import yaml
+
+class Products:
+    data = []  # Список, в котором будут словари
+
+    def read_yaml_file(self, filename):
+        """Read the data from a YAML file and return a list of dictionaries"""
+        with open(filename, 'r') as file:
+            self.data = yaml.load(file, Loader=yaml.FullLoader)
+
+    def write_yaml_file(self, filename):
+        """Write the data in YAML format to a file"""
+        with open(filename, 'w') as file:
+            yaml.dump(self.data, file)
+
+    def sortProducts(self, criteria: str, order: bool = False):
+        """Sort list of products by given criteria:
+        \n price - price of a product
+        \n rating - total rating of a seller
+        \n sold - the amount of items sold
+        \n\n order - asc=0, desc=1
+        """
+        self.data.sort(key=operator.itemgetter(criteria), reverse=order)
+
+    def parseAPI(self, query):
+        """Find all elements on page and store them into the dictionary using plati.ru API"""
+        self.data = []
+        pagesize = 499
+        contents = requests.get(f"https://plati.io/api/search.ashx?query={quote(query)}&pagesize={pagesize}&visibleOnly=true&response=json").json()
+        total_pages = int(contents['Totalpages'])
+        for entry in contents['items']:
+            self.data.append(
+                {'name': entry['name'], 'link': entry['url'], 'price': int(entry['price_rur']), 'rating': float(entry['seller_rating']), 'sold': int(entry['numsold'])})
+        if total_pages > 1:
+            for i in range(2, total_pages + 1):
+                contents = requests.get(f"https://plati.io/api/search.ashx?query={quote(query)}&pagesize={pagesize}&pagenum={i}&visibleOnly=true&response=json").json()
+                for entry in contents['items']:
+                    self.data.append(
+                        {'name': entry['name'], 'link': entry['url'], 'price': int(entry['price_rur']), 'rating': float(entry['seller_rating']), 'sold': int(entry['numsold'])})
+
+# Функция поиска, которая будет вызываться из интерфейса Gradio
+def search(query):
+    logging.info(f"Search started with query: {query}")
+    products = Products()
+    products.parseAPI(query)
+    products.write_yaml_file("cache.yaml")
+    products.read_yaml_file("cache.yaml")
+    logging.info(f"Search results: {products.data}")
+
+    # Создаем новый DataFrame из списка словарей products.data
+    df = pd.DataFrame(products.data)
+    return df  # Возвращаем DataFrame
+
+# Добавляем функцию greet для демонстрации
+def greet(name):
+    return "Hello " + name + "!!"
+
+# Создание Gradio интерфейса
+def create_interface():
+    with gr.Blocks() as demo:
+        gr.Markdown("# Plati.market Parser and Greet Function")
+        gr.Markdown("### Greeting Section")
+        greet_input = gr.Textbox(label="Enter your name")
+        greet_button = gr.Button("Greet")
+        greet_output = gr.Textbox(label="Greeting")
+        greet_button.click(fn=greet, inputs=greet_input, outputs=greet_output)
+        
+        gr.Markdown("### Plati.market Search Section")
+        gr.Markdown("Input what you like to find in the field below. The results will be displayed in the table.")
+        search_input = gr.Textbox(label="Search Query")
+        search_button = gr.Button("Search")
+        data_table = gr.Dataframe(headers=["name", "link", "price", "rating", "sold"], interactive=True, label="Search Results")
+        search_button.click(fn=search, inputs=search_input, outputs=data_table)
+
+    return demo
+
+if __name__ == "__main__":
+    # Настройка логирования
+    logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
+    
+    demo = create_interface()
+    demo.launch()