| import pandas as pd
|
| import sqlite3
|
| import csv
|
| import json
|
| import time
|
| import os
|
| import re
|
| from utils import TEMP_DIR
|
|
|
| def is_file_done_saving(file_path):
|
| try:
|
| with open(file_path, 'r') as f:
|
| contents = f
|
|
|
| if contents:
|
| return True
|
| else:
|
| return False
|
| except PermissionError:
|
| return False
|
|
|
| def get_delimiter(file_path, bytes = 4096):
|
| sniffer = csv.Sniffer()
|
| data = open(file_path, "r").read(bytes)
|
| delimiter = sniffer.sniff(data).delimiter
|
| return delimiter
|
|
|
| def read_file(file):
|
| if file.endswith(('.csv', '.tsv', '.txt')) :
|
| df = pd.read_csv(file, sep=get_delimiter(file))
|
| elif file.endswith('.json'):
|
| with open(file, 'r') as f:
|
| contents = json.load(f)
|
| df = pd.json_normalize(contents)
|
| elif file.endswith('.ndjson'):
|
| with open(file, 'r') as f:
|
| contents = f.read()
|
| data = [json.loads(str(item)) for item in contents.strip().split('\n')]
|
| df = pd.json_normalize(data)
|
| elif file.endswith('.xml'):
|
| df = pd.read_xml(file)
|
| elif file.endswith(('.xls','xlsx')):
|
| df = pd.read_excel(file)
|
| else:
|
| raise ValueError(f'Unsupported filetype: {file}')
|
| return df
|
|
|
| def process_data_upload(data_file, session_hash):
|
| try:
|
| total_time = 0
|
| while not is_file_done_saving(data_file):
|
| total_time += .5
|
| time.sleep(.5)
|
| if total_time > 10:
|
| break
|
|
|
| df = read_file(data_file)
|
|
|
|
|
|
|
|
|
|
|
| df.columns = df.columns.str.replace(' ', '_')
|
| df.columns = df.columns.str.replace('/', '_')
|
|
|
| for column in df.columns:
|
| if type(column) is str:
|
| if "date" in column.lower() or "time" in column.lower():
|
| try:
|
| df[column] = pd.to_datetime(df[column])
|
| except:
|
| pass
|
| if 'year' in column.lower():
|
| try:
|
| df[column] = pd.to_datetime(df[column], format='%Y')
|
| except:
|
| pass
|
| if df[column].dtype == 'object' and isinstance(df[column].iloc[0], list):
|
| df[column] = df[column].explode()
|
|
|
| session_path = 'file_upload'
|
|
|
| dir_path = TEMP_DIR / str(session_hash) / str(session_path)
|
| os.makedirs(dir_path, exist_ok=True)
|
|
|
| connection = sqlite3.connect(f'{dir_path}/data_source.db')
|
| print("Opened database successfully")
|
|
|
| df.to_sql('data_source', connection, if_exists='replace', index = False)
|
|
|
| cur=connection.execute('select * from data_source')
|
| columns = [i[0] for i in cur.description]
|
| print(columns)
|
|
|
| connection.commit()
|
| connection.close()
|
|
|
| return ["success","<p style='color:green;text-align:center;font-size:18px;'>Data upload successful</p>", columns]
|
| except Exception as e:
|
| print("UPLOAD ERROR")
|
| print(e)
|
| return ["error",f"<p style='color:red;text-align:center;font-size:18px;font-weight:bold;'>ERROR: {e}</p>"] |
