app.py

from typing import Annotated, Optional

from fastapi import FastAPI, Header, Query

import html2text 
import requests
import httpx
import re
import json

from fastapi.middleware.cors import CORSMiddleware

from bs4 import BeautifulSoup


app = FastAPI()

app.add_middleware(
    CORSMiddleware,
    allow_origins=["*"], 
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

@app.get("/linkedin_post_details")
async def linkedin_post_details(post_id: str, url: Optional[str] = None):
    if not url:
        url = "https://www.linkedin.com/posts/"+post_id
    res = requests.get(url, headers={"user-agent":"Googlebot", "accept-language": "en-US"})
    
    soup = BeautifulSoup(res.content, "html.parser")

    script_tags = soup.find_all("script")

    for script_tag in script_tags:
        try:
            script_tag = json.loads(script_tag.string)
            if script_tag.get("datePublished"):
                desc = script_tag.get("articleBody")
                if not desc:
                    desc = script_tag.get("description")
                author = script_tag.get("author")
                full_name = author.get("name")
                username = author.get("url").rsplit("/", 1)[-1]
                user_type = author.get("@type").lower()
                date = script_tag.get("datePublished")
        except Exception as e:
            continue

    
    spans = soup.find_all(
        "span", {"data-test-id": "social-actions__reaction-count"}
    )
    
    if spans:
        reactions = spans[0].text.strip()
    else:
        reactions = '0'
    
    try:
        comments = str(soup.find("a", {"data-test-id": "social-actions__comments"}).get(
            "data-num-comments"
        ))
    except:
        comments = '0'

    return {
        "insights": {
            "likeCount": None,
            # "commentCount": int(comments.replace(",", "")),
            "commentCount": comments,
            "shareCount": None,
            # "reactionCount": int(reactions.replace(",", "")),
            "reactionCount":reactions,
            "reactions": [],
        },
        "description": desc,
        "username": username,
        "name": full_name,
        "userType": user_type,
        "date": date,
    }
# async def linkedin_post_details(post_id: str):
    # url = "https://www.linkedin.com/posts/"+post_id
    # res = requests.get(url, headers={"user-agent":"Googlebot", "accept-language": "en-US"})
    
    # text_maker = html2text.HTML2Text()
    # text_maker.ignore_links = True
    # text_maker.ignore_images = True
    # text_maker.bypass_tables = False

    # docs = text_maker.handle(res.content.decode("utf-8"))

    # chunks = docs.split("\n\n#")
    # linkedin_content = chunks[1]
    # user = linkedin_content.split("\n\n", 5)
    # full_name = user[1]
    # bio = user[2]
    # try:
    #     date, edited = user[3].split("  ")
    #     edited = True
    # except:
    #     date = user[3].strip()
    #     edited = False
    # content = "\n\n".join(user[5:])
    
    # insights = chunks[3].split("\n\n")[2]
    # likes = insights.split(" ", 1)[0].strip()
    # comments = insights.rsplit(" ", 2)[1].strip()

    # username = url.rsplit("/",1)[-1].split("_")[0]
    
    # return {
    #     "userDetails": {"full_name": full_name, "username":username,"bio": bio},
    #     "content": content,
    #     "date": date,
    #     "is_edited": edited,
    #     "insights": {"likeCount": likes, "commentCount": comments, "shareCount": None, "viewCount":None},
    #     "username":username
    # }


@app.get("/facebook_post_detail")
async def fb_post_detail(username: str, post_id: str, url: Optional[str] = None):
    if not url:
        url = f"https://www.facebook.com/{username}/posts/{post_id}"
    user_agent = "Googlebot"

    res = requests.get(
        url,
        headers={
            "user-agent": user_agent,
            "accept-language": "en-US"
        },
        timeout=(10, 27),
    )
    
    soup = BeautifulSoup(res.content, "html.parser")

    script_tags = soup.find_all("script") 
    print(len(script_tags))
    for script_tag in script_tags:
        try:
            if "important_reactors" in script_tag.string:
                splitter = '"reaction_count":{"count":'
                total_react, reaction_split = script_tag.string.split(splitter, 2)[1].split("},", 1)
                total_react = total_react.split(',"')[0]
                pattern = r"\[.*?\]"

                reactions = re.search(pattern, reaction_split)

                if reactions:
                    reactions = json.loads(reactions.group(0))
                else:
                    reactions = []

                reactions = [
                    dict(
                        name=reaction["node"]["localized_name"].lower(),
                        count=reaction["reaction_count"],
                        is_visible=reaction["visible_in_bling_bar"],
                    )
                    for reaction in reactions
                ]

                splitter = '"share_count":{"count":'

                shares = script_tag.string.split(splitter, 2)[1].split(",")[0]
                splitter = '"comments":{"total_count":'
                comments = script_tag.string.split(splitter, 2)[1].split("}")[0]
                likes = [x.get("count") for x in reactions if x.get("name") == "like"][0]

                print(total_react, reactions, shares, comments, likes)
            if '"message":{"text":"' in script_tag.string:
                desc = script_tag.string.split('"message":{"text":"', 1)[-1].split('"},')[0]
        except Exception as e:
            print(e)
            continue

    name = soup.find("meta", {"property": "og:title"}).get("content")


    return {
        "insights": {
            "likeCount": likes,
            "commentCount": comments,
            "shareCount": shares,
            "reactionCount": total_react,
            "reactions": reactions,
        },
        "description": desc,
        "username": username,
        "name": name,
        "date": None,
    }
    

@app.get("/google_search")
async def google_search(q: str, delimiter: str = "\n---\n", sites: Annotated[list[str] | None, Query()] = None):
    print(sites)
    print(type(sites))
    url = f"https://www.google.com/search?q={q} "
    if sites:
        url += " OR ".join(["site:"+site for site in sites]) 
        
    texts = ""
    soup = BeautifulSoup(requests.get(url).content, "html.parser")
  
    for div in soup.find_all("div")[24:]:
      if len(div.find_parents("div")) == 8:  # Depth 4 means 3 parent divs (0-indexed)
          # print(div.get_text().strip())
          href = div.find(href=True, recursive=True)
          text = div.find(text=True, recursive=False)
          if href and text:
            print(text)
            text = f'[{text}]({href["href"].split("/url?q=")[-1]})'
          if text != None and text.strip():
            texts += text + delimiter
    return {"results":texts}


@app.get("/tiktok_video_details")
async def tiktok_video_details(username: str, video_id:str, url: Optional[str] = None):
    if not url:
        if username[0] != "@":
            username = "@" + username
        url = f"https://www.tiktok.com/{username}/video/{video_id}"
        
    # user_agent = "LinkedInBot"
    user_agent = "Mozilla/5.0 (compatible; YandexBot/3.0; +http://yandex.com/bots)"
    
    res = requests.get(url, headers={"user-agent": user_agent})

    # soup = BeautifulSoup(res.content, "html.parser")

    # insights = soup.find("meta", {"property": "og:description"}).get("content")
    # likes = insights.split(" ", 1)[0]
    # desc = insights.rsplit(" comments. “", 1)[-1][:-1]
    # comments = insights.split(", ", 1)[-1].split(" ", 1)[0]

    # name = soup.find("meta", {"property": "og:title"}).get("content")[9:]

    # return {
    #     "insights": {"likeCount": likes, "commentCount": comments, "shareCount":None, "viewCount":None},
    #     "description": desc,
    #     "username": username,
    #     "name": name,
    # }

    text_maker = html2text.HTML2Text()
    text_maker.ignore_links = True
    text_maker.ignore_images = True
    text_maker.bypass_tables = False

    print("RESPONSE DETAIlL", res.content.decode("utf-8"))
    
    docs = text_maker.handle(res.content.decode("utf-8"))

    print("DOCS", docs)

    content_detail = docs.split("###")[5]

    likes, comments, bookmarks, shares = re.findall(r'\*\*([\w.]+)\*\*', content_detail)
    
    
    profile = [x.strip() for x in content_detail.split("\n\nSpeed\n\n", 1)[1].split("\n", 6) if x.strip()]
    username = profile[0]
    date = profile[1].rsplit(" · ", 1)[-1]
    desc = profile[-1][2:].replace("**", "")
    
    return {
        "insights":{
            "likeCount":likes,
            "commentCount":comments,
            "bookmarkCount":bookmarks,
            "shareCount":shares
        },
        "username":username,
        "date":date,
        "description":desc
    }