keyword_analytic_web/main.py

from fastapi import FastAPI
from fastapi.staticfiles import StaticFiles
from apis.general_pages.route_homepage import general_pages_router
from core.config import settings


# import pandas as pd
# from fastapi import FastAPI, File, UploadFile, Request
# from fastapi.middleware.cors import CORSMiddleware
# import dataset
# from functools import reduce
# from fastapi.staticfiles import StaticFiles
# from fastapi.templating import Jinja2Templates
# from fastapi.responses import HTMLResponse



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

# templates = Jinja2Templates(directory="templates")
#
# app.mount("/static", StaticFiles(directory="static"), name="static")

# @app.get("/")
# def hello_api():
#     return {"msg":"Hello API"}

def include_router(app):
    app.include_router(general_pages_router)

def configure_static(app):
    app.mount("/static", StaticFiles(directory="static"), name="static")

def start_application():
    app = FastAPI(title=settings.PROJECT_NAME,version=settings.PROJECT_VERSION)
    include_router(app)
    return app


app = start_application()


# @app.post("/write/")
# async def writecsv(file: UploadFile = File(...)):
#
#     # read csv
#     repls = (' Stats ', '_'), (' at ', '_'), ('-', '_'), \
#             (' ', ''), ('.csv', '')
#     filename = file.filename
#     filename = reduce(lambda a, kv: a.replace(*kv), repls, filename)
#
#     data = file.file
#     df = pd.read_csv(data, sep=",",
#                      skiprows=0, na_values='NULL')
#
#     # db connect
#     # db = dataset.connect(
#     #     'mysql://choozmo:pAssw0rd@db.ptt.cx:3306/keywordweb?charset=utf8mb4'
#     # )
#     db = dataset.connect(
#         'mysql://root:pAssw0rd@localhost:3306/keywordweb?charset=utf8mb4'
#     )
#     sql = "CREATE TABLE IF NOT EXISTS "\
#           + filename +\
#           "(ID INT NOT NULL PRIMARY KEY AUTO_INCREMENT, " \
#           "keyword VARCHAR(100), " \
#           "currency VARCHAR(100), avg_monthly_searches VARCHAR(100), " \
#           "three_month_change VARCHAR(100), " \
#           "yearly_change VARCHAR(100), competition VARCHAR(100), " \
#           "competition_indexed VARCHAR(100), " \
#           "top_page_bid_low_range VARCHAR(100), " \
#           "top_page_bid_hi_range VARCHAR(100)" \
#           ");"
#
#     db.query(sql)
#
#     # write to db
#     table = db[filename]
#     lines = df.shape
#     i = 0
#
#     rows = lines[0]
#
#     for i in range(rows):
#         row1 = df.iloc[i]
#         k = row1[0]
#         c = row1[1]
#         a = row1[2]
#         t = row1[3]
#         y = row1[4]
#         c1 = row1[5]
#         c2 = row1[6]
#         t1 = row1[7]
#         t2 = row1[8]
#
#         dbdata = dict(keyword=k, currency=c, avg_monthly_searches=a,
#                       three_month_change=t, yearly_change=y, competition=c1,
#                       competition_indexed=c2, top_page_bid_low_range=t1,
#                       top_page_bid_hi_range=t2)
#         table.insert(dbdata)
#
#     db.close()
#
#
#
# @app.get("/items/{id}", response_class=HTMLResponse)
# async def read_item(request: Request, id: int):
#     x = 0
#     nums = x + 11
#     title = "報表"
#     keyword = "關鍵字1"
#     return templates.TemplateResponse(
#         "item.html",
#         {"request": request, "id": id,
#          "num": nums, "titles": title, "keyword":keyword
#          })
#