Semi-manual python script to download your ride history including prices.

uber-ride-history.py

#!/usr/bin/env python2

"""
Semi-manual script to download trips and cost.

Currently needs manual steps in 2 places. And chrome-selenium.
(or any other Selenium browser)

You also want to adapt the currencies to your needs.

pip3 install uber_rides selenium pandas
"""

import re
import pandas as pd
from selenium import webdriver
from uber_rides.client import UberRidesClient
from uber_rides.auth import AuthorizationCodeGrant

RIDE_DETAILS_URL = 'https://riders.uber.com/trips/{}'

def get_uber_client():
    # register app on https://developer.uber.com
    auth_flow = AuthorizationCodeGrant(
        'XXX',
        {'history', 'request_receipt'},
        'XXX',
        'http://localhost'
    )
    auth_url = auth_flow.get_authorization_url()
    # Confirm auth_url and paste below.
    session = auth_flow.get_session('RESPONSE URL')
    client = UberRidesClient(session)
    return client

def get_rides_df(client):    
    rides = []
    i = 0
    while True:
        resp = client.get_user_activity(limit=50, offset=i)
        i += 50
        if len(resp.json['history']) > 0:
            rides += resp.json['history']
        else:
            break

    rides_sel = [ {'request_id': e['request_id'],
                     'distance': e['distance'], 
                     'city': e['start_city']['display_name'], 
                     'time': e['start_time']} for e in rides]
    df = pd.DataFrame(rides_sel)
    df.time = pd.to_datetime(df.time*1e9)
    return df

driver = webdriver.Chrome()
driver.get('https://riders.uber.com/trips/')
# Login to uber in selenium browser.

def get_price_km(request_id):
    XP_KM = '//*[@id="slide-menu-content"]/div/div[2]/div/div/div[2]/div[3]/div/div[1]/div[2]/div[2]/div/div[2]/h5'
    XP_PRICE = '//td[@class="text--right alpha weight--semibold"]'

    driver.get(RIDE_DETAILS_URL.format(request_id))
    price = driver.find_element_by_xpath(XP_PRICE).text
    km = driver.find_element_by_xpath(XP_KM).text
    return (float(km), price)

def get_eur_price(price):
    currencies = {u'RM': 4.5,
                  u'₫': 25000,
                  u'฿': 40}
    price = re.sub(',', '', price)
    price_float = float(re.findall('\d+\.\d+', price)[0])
    for currency in currencies.keys():
        if currency in price:
            return price_float / currencies[currency]

df['km'], df['price'] = zip(*km)
df['eur'] = df.price.apply(get_eur_price)