from fastapi import FastAPI, UploadFile, File
from fastapi.responses import HTMLResponse
import pandas as pd
import io
import time
app = FastAPI()
@app.get("/", response_class=HTMLResponse)
async def analyze_logs():
return """
"""
@app.post("/upload/")
async def upload_file(file: UploadFile = File(...)):
contents = await file.read()
logs_df = pd.read_parquet(io.BytesIO(contents))
processing_message = "\n\n Processing files...\n\n"
time.sleep(3) # Simulate processing time (3 seconds)
logs_df['datetime'] = pd.to_datetime(logs_df['datetime'], format='%d/%m/%Y:%H:%M:%S')
logs_df['day'] = logs_df['datetime'].apply(lambda x: x.day)
logs_df['hour'] = logs_df['datetime'].apply(lambda x: x.hour)
logs_df['minute'] = logs_df['datetime'].apply(lambda x: x.minute)
ip_address_count_df = (
logs_df.groupby(['method', 'client'], as_index=False)
.size()
.rename(columns={'size': 'count'})
.sort_values('count', ascending=False)
)
ip_address_count_df = ip_address_count_df.assign(
perc=ip_address_count_df['count'].div(ip_address_count_df['count'].sum()),
cum_perc=lambda df: df['perc'].cumsum(),
)
dataframe_styled = (
ip_address_count_df.head(1000)
.style.background_gradient(subset=['count', 'perc', 'cum_perc'], cmap='cividis')
.format({'count': '{:,}', 'perc': '{:.1%}', 'cum_perc': '{:.1%}'})
)
# Render the styled DataFrame to HTML
styled_html = dataframe_styled.render()
result = (
"Redundant IP Requests....
"
"The Total API Requests from the sample logs are : {total_requests}
"
"The Redundant API Requests from the sample logs are : {redundant_requests}
"
"The percentage of Redundant API Requests from the sample logs is : {redundant_percentage:.2f}%
"
"{dataframe_html}"
).format(
total_requests=logs_df.shape[0],
redundant_requests=ip_address_count_df.shape[0],
redundant_percentage=(ip_address_count_df.shape[0] / logs_df.shape[0]) * 100,
dataframe_html=styled_html,
)
return HTMLResponse(content=result)