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allintitle_scraper.py
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allintitle_scraper.py
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import time
import requests
import random
import xlsxwriter
import pandas as pd
import streamlit as st
import logging as log
from bs4 import BeautifulSoup
from io import BytesIO
def extract_keywords(file) -> list:
keyword_df = pd.DataFrame()
log.debug(f'Filename: {file.name}')
# add logging?
try:
if '.csv' in file.name:
keyword_df = pd.read_csv(file)
log.debug(f'Keyword Dataframe: {keyword_df}')
elif '.xlsx' in file.name:
keyword_df = pd.read_excel(file)
log.debug(f'Keyword Dataframe: {keyword_df}')
except FileNotFoundError as f:
print('File not found. Please check that the file exists ',
'in the resources/input directory :: ', f)
log.error('File not found. Please check that the file exists ',
'in the resources/input directory :: %s', f)
return
except Exception:
print('Unknown error occurred')
log.error('Unknown error occurred')
return
try:
keyword_df.columns = keyword_df.columns.str.lower()
return keyword_df["keyword"].tolist()
except KeyError:
print('Column not found: "keyword"')
log.error('Column not found: "keyword"')
return
def format_cells(kgr) -> str:
# conditional formatting of kgr column (Series)
color = ''
if kgr < 0.25:
color = 'background-color: green'
elif kgr >= 0.25 and kgr < 1:
color = 'background-color: yellow'
else:
color = 'background-color: red'
log.debug(f'Color chosen: {color}')
return color
def create_df(keywords: list) -> pd.DataFrame:
log.info(f'Keywords received: {keywords}')
headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) '
'AppleWebKit/537.36 (KHTML, like Gecko) '
'Chrome/74.0.3729.169 Safari/537.36'}
# stats = []
df = pd.DataFrame({'Keyword': [], 'All In Title': [], 'Search Volume': [], 'KGR': []})
for i in keywords:
search_phrase = 'allintitle:' + i
params = {'q': search_phrase}
url = 'https://www.google.com/search'
# perform request
response = requests.get(url, headers=headers, params=params)
# parse response
soup = BeautifulSoup(response.text, 'html.parser')
result = soup.find("div", {"id": "result-stats"}).text
# assuming Google keeps the number of results in the following format:
# "About <number> results (<time>)"
# have to remove commas from string to make int
# should revert back to string for export
num_of_results = result.split()[1].replace(',', '')
# adding a random number for volume
volume = random.randrange(1, 2)
kgr = round(int(num_of_results)/volume, 2)
df.loc[len(df.index)] = [i, num_of_results, volume, kgr]
# stats[i] = [int(num_of_results.replace(',','')), ]
time.sleep(1)
return df
@st.cache
def convert_df(df: pd.DataFrame, filename: str) -> BytesIO:
# IMPORTANT: Cache the conversion to prevent computation on every rerun
# Write files to in-memory strings using BytesIO
output = BytesIO()
# writer = pd.ExcelWriter(filename, engine='xlsxwriter')
workbook = xlsxwriter.Workbook(output, {'in_memory': True})
workbook.close()
return output
with st.echo(code_location='below'):
uploaded_file = st.file_uploader(
"uploader",
type=['xlsx', 'csv'],
key="1",
help="To activate 'wide mode', go to the hamburger menu > Settings > turn on 'wide mode'",
accept_multiple_files=False
)
if uploaded_file is not None:
file_container = st.expander("Check your uploaded .csv or .xlsx")
keywords = extract_keywords(uploaded_file)
if keywords is None:
log.error('Keywords are empty')
st.stop()
uploaded_file.seek(0)
file_container.write(keywords)
else:
st.info("""👆 Upload a .csv or .xlsx file first.""")
st.stop()
df = create_df(keywords)
output_file = 'allintitle_results.xlsx'
# converted_df = convert_df(df, output_file)
output = convert_df(df, output_file)
st.download_button(
label="Download as XLSX",
data=output.getvalue(),
file_name=output_file,
mime='application/vnd.openxmlformatsofficedocument.spreadsheetml.sheet'
)
st.dataframe(df.style.applymap(format_cells, subset=['KGR']))