I've benn playing with an example taken from here:
https://stackoverflow.com/a/61408325
this is working and was very helpfull, but I'm strugling with the requests-html documentation.
In this example is it possible to get the id value of the element?
from requests_html import AsyncHTMLSession
from collections import defaultdict
import pandas as pd
url = 'https://www.flashscore.com/football/england/premier-league-2018-2019/results/'
asession = AsyncHTMLSession()
async def get_scores():
r = await asession.get(url)
await r.html.arender()
return r
results = asession.run(get_scores)
results = results[0]
times = results.html.find("div.event__time")
home_teams = results.html.find("div.event__participant.event__participant--home")
scores = results.html.find("div.event__scores.fontBold")
away_teams = results.html.find("div.event__participant.event__participant--away")
event_part = results.html.find("div.event__part")
dict_res = defaultdict(list)
for ind in range(len(times)):
dict_res['times'].append(times[ind].text)
dict_res['home_teams'].append(home_teams[ind].text)
dict_res['scores'].append(scores[ind].text)
dict_res['away_teams'].append(away_teams[ind].text)
dict_res['event_part'].append(event_part[ind].text)
df_res = pd.DataFrame(dict_res)
I managed to get the id in a way I don't know if it will be the most suitable.
What I did was search for the of the entire game
match_div = results.html.find("div.event__match")
and then get the id from its atributes
for ind in range(len(times)):
id = match_div[ind].attrs['id']
I think that must be a more 'direct' way of doing this, but not getting there
Related
I'm pulling data from the NHL API for player stats based on individual games. I'm trying to make a loop that calls the data, parses the JSON, creates a dict which I then can create a data frame from for an entire team. The code before my looping looks like this:
API_URL = "https://statsapi.web.nhl.com/api/v1"
response = requests.get(API_URL + "/people/8477956/stats?stats=gameLog", params={"Content-Type": "application/json"})
data = json.loads(response.text)
df_list_dict = []
for game in data['stats'][0]['splits']:
curr_dict = game['stat']
curr_dict['date'] = game['date']
curr_dict['isHome'] = game['isHome']
curr_dict['isWin'] = game['isWin']
curr_dict['isOT'] = game['isOT']
curr_dict['team'] = game['team']['name']
curr_dict['opponent'] = game['opponent']['name']
df_list_dict.append(curr_dict)
df = pd.DataFrame.from_dict(df_list_dict)
print(df)
This gives me a digestible data frame for a single player. (/people/{player}/....
I want to iterate through a list (the list being an NHL team), while adding a column that identifies the player and concatenates the created data frames. My attempt thus far looks like this:
import requests
import json
import pandas as pd
Rangers = ['8478550', '8476459', '8479323', '8476389', '8475184', '8480817', '8480078', '8476624', '8481554', '8482109', '8476918', '8476885', '8479324',
'8482073', '8479328', '8480833', '8478104', '8477846', '8477380', '8477380', '8477433', '8479333', '8479991']
def callapi(player):
response = (requests.get(f'https://statsapi.web.nhl.com/api/v1/people/{player}/stats?stats=gameLog', params={"Content-Type": "application/json"}))
data = json.loads(response.text)
df_list_dict = []
for game in data['stats'][0]['splits']:
curr_dict = game['stat']
curr_dict['date'] = game['date']
curr_dict['isHome'] = game['isHome']
curr_dict['isWin'] = game['isWin']
curr_dict['isOT'] = game['isOT']
curr_dict['team'] = game['team']['name']
curr_dict['opponent'] = game['opponent']['name']
df_list_dict.append(curr_dict)
df = pd.DataFrame.from_dict(df_list_dict)
print(df)
for player in Rangers:
callapi(player)
print(callapi)
When this is printed I can see all the data frames that were created. I cannot use curr_dict[] to add a column based on the list position (the player ID) because must be a slice or integer, not string.
What I'm hoping to do is make this one data frame in which the stats are identified by a player id column.
My python knowledge is very scattered, I feel as if with the progress I've made I should know how to complete this but I've simply hit a wall. Any help would be appreciated.
You can use concurrent.futures to parallelize the requests before concatenating them all together, and json_normalize to parse the json.
import concurrent.futures
import json
import os
import pandas as pd
import requests
class Scrape:
def main(self) -> pd.DataFrame:
rangers = ["8478550", "8476459", "8479323", "8476389", "8475184", "8480817", "8480078",
"8476624", "8481554", "8482109", "8476918", "8476885", "8479324", "8482073",
"8479328", "8480833", "8478104", "8477846", "8477380", "8477380", "8477433",
"8479333", "8479991"]
with concurrent.futures.ProcessPoolExecutor(max_workers=os.cpu_count()) as executor:
return pd.concat(executor.map(self.get_stats, rangers)).reset_index(drop=True).fillna(0)
#staticmethod
def get_stats(player: str) -> pd.DataFrame:
url = f"https://statsapi.web.nhl.com/api/v1/people/{player}/stats?stats=gameLog"
with requests.Session() as request:
response = request.get(url, timeout=30)
if response.status_code != 200:
print(response.raise_for_status())
data = json.loads(response.text)
df = (pd.
json_normalize(data=data, record_path=["stats", "splits"])
.rename(columns={"team.id": "team_id", "team.name": "team_name",
"opponent.id": "opponent_id", "opponent.name": "opponent_name"})
).assign(player_id=player)
df = df[df.columns.drop(list(df.filter(regex="link|gamePk")))]
df.columns = df.columns.str.split(".").str[-1]
if "faceOffPct" not in df.columns:
df["faceOffPct"] = 0
return df
if __name__ == "__main__":
stats = Scrape().main()
print(stats)
The ultimate goal of this is to output select data columns to a .csv. I had it working once to where it only got the first table on the page but I needed both. Now it says this. Im quite new to python and IDK how I got to this point in the first place. I needed the call and put table but on the web page the calls came first and when I did .find I only got the calls. I am working on this with a friend and he put in the last two functions. He could get the columns I wanted but now we only get the calls. I tried to fix it and now it say the error in the title.
import bs4
import requests
import pandas as pd
import csv
from bs4 import BeautifulSoup
#sets desired ticker. in the future you could make this long
def ticker():
ticker = ['GME','NYMT']
return ticker
#creates list of urls for scrapet to grab
def ticker_site():
ticker_site = ['https://finance.yahoo.com/quote/'+x+'/options?p='+x for x in ticker()]
return ticker_site
optionRows = []
for i in range(len(ticker_site())):
optionRows.append([])
def ticker_gets():
option_page = ticker_site()
requested_page = requests.get(option_page[i])
ticker_soup = BeautifulSoup(requested_page.text,'html.parser')
return ticker_soup
def soup_search():
table = ticker_gets()
both_tables = table.find_all('table')
call_table = both_tables[0]
put_table= both_tables[1]
call_rows = call_table.find('tr')
put_rows = put_table.find('tr')
#makes the call table
for call in call_rows:
whole_call_table = call.find_all('td')
call_row = [y.text for y in whole_call_table]
optionRows[call].append(call_row)
#makes the put table
for put in put_rows:
whole_put_table = put.find_all('td')
put_row = [z.text for z in whole_put_table]
optionRows[put].append(put_row)
for i in range(len(optionRows)):
optionRows[i] = optionRows[i][1:len(optionRows[i])]
return optionRows
def getColumns(columnIndexes=[2, 4, 5]):
newList = []
for tickerIndex in range(len(soup_search())):
newList.append([])
indexCount = 0
for j in soup_search()[tickerIndex]:
newList[tickerIndex].append([])
for i in columnIndexes:
newList[tickerIndex][indexCount].append(j[i])
indexCount += 1
return newList
def csvOutputer():
rows = getColumns()
fields = ["Ticker", "Strike", "Bid", "Ask"]
with open('newcsv', 'w') as f:
write = csv.writer(f)
write.writerow(fields)
for i in range(len(ticker())):
for j in rows[i]:
j.insert(0, ticker()[i])
write.writerow(j)
csvOutputer()
Please find below code am trying to get Seller Proceeds value in Website, but it has $0, when i tried in console $0.value am getting 598.08 but am getting Calculate when i tried using this
sel_proc = web.find_elements(id="afn-seller-proceeds")[0].text
'''
Full Code :
import pandas as pd
from webbot import Browser
from bs4 import BeautifulSoup
web = Browser()
##web.set_window_position(-10000,0)
df = pd.read_excel('sample.xlsx')
soafees = []
fulfees = []
selproc = []
for ind in df.index:
web.go_to('https://somelink')
## web.set_window_position(-10000,0)
web.click(id='link_continue')
print("Login Successful")
asin = df['ASIN'][ind]
sp = int(df['Selling Price'][ind])
print(sp)
cp = int(df['Cost of Product'][ind])
print(cp)
web.type(df['ASIN'][ind] , into = 'Enter your product name, UPC, EAN, ISBN or ASIN',clear = True)
web.click(id='a-autoid-0')
web.type(sp,tag='input',id='afn-pricing',clear = True)
web.type(cp,tag='input',id='afn-cost-of-goods',clear = True)
web.click(id='update-fees-link')
res = web.find_elements(id="afn-selling-fees")[0].text
ful_fees = web.find_elements(id="afn-amazon-fulfillment-fees")[0].text
sel_proc = web.find_elements(id="afn-seller-proceeds")[0].text
## sel_proc = web.execute_script('return arguments[0].value;', element);
print("soa fees : "+res)
print("Fulfillment fees : "+ful_fees)
print("Seller Proceeds : "+sel_proc)
soafees.append(res)
fulfees.append(ful_fees)
selproc.append(sel_proc)
print(soafees)
print(fulfees)
print(selproc)
df_soa = pd.DataFrame(soafees,columns = ['SOA Fees'])
df_ful = pd.DataFrame(fulfees,columns = ['FBA Fees'])
df_sel = pd.DataFrame(selproc,columns = ['Seller Proceeds'])
print(df)
print(df_soa)
print(df_ful)
print(df_sel)
Snapshot for reference:
thanks in advance for your support
In the sel_proc variable, you are storing the text, Instead, you should look for the attribute which has the value. I believe, in this case, it should be a "value" attribute.
sel_proc = web.find_elements(id="afn-seller-proceeds")[0].get_attribute(<attribute_name>)
Your code will look something like this:
sel_proc = web.find_elements(id="afn-seller-proceeds")[0].get_attribute("value")
Want to pass a range for the web-scraping function, not sure how it's done. This is to make my code more reusable so that I can scrape different ranges with different dates, say 2016... 2017... 2018... Code looks like this:
import numpy as np
import pandas as pd
import requests
def game_id2017(game_id):
games_played_2017 = []
games_played_2018 = []
print('Getting data...')
for game_id in range():
url = 'https://statsapi.web.nhl.com/api/v1/game/{}/boxscore'.format(game_id)
r_2017 = requests.get(url)
game_data_2017 = r_2017.json()
for homeaway in ['home','away']:
game_dict_2017 = dict()
game_dict_2017['team'] = game_data_2017.get('teams').get(homeaway).get('team').get('name')
game_dict_2017['teamID'] = game_data_2017.get('teams').get(homeaway).get('team').get('id')
game_dict_2017['homeaway'] = homeaway
game_dict_2017['game_id'] = game_id
games_played_2017.append(game_dict_2017)
game_id2017(20170201, 20170210, 1)
TypeError: game_id2017() takes 1 positional argument but 3 were given
game_id2017(*game_id)
for id in game_id:
then use game_id like a list
Pass a list:
import numpy as np
import pandas as pd
import requests
def game_id2017(game_id):
print('Getting data...')
for a_game_id in range(len(game_id)):
# use a_game_id
game_id2017([20170201, 20170210, 1])
I'm trying to parse a JSON of a sites stock.
The JSON: https://www.ssense.com/en-us/men/sneakers.json
So I want to take some keywords from the user. Then I want to parse the JSON using these keywords to find the name of the item and (in this specific case) return the ID, SKU and the URL.
So for example:
If I inputted "Black Fennec" I want to parse the JSON and find the ID,SKU, and URL of Black Fennec Sneakers (that have an ID of 3297299, a SKU of 191422M237006, and a url of /men/product/ps-paul-smith/black-fennec-sneakers/3297299 )
I have never attempted doing anything like this. Based on some guides that show how to parse a JSON I started out with this:
r = requests.Session()
stock = r.get("https://www.ssense.com/en-us/men/sneakers.json",headers = headers)
obj json_data = json.loads(stock.text)
However I am now confused. How do I find the product based off the keywords and how do I get the ID,Url and the SKU or it?
Theres a number of ways to handle the output. not sure what you want to do with it. But this should get you going.
EDIT 1:
import requests
r = requests.Session()
obj_json_data = r.get("https://www.ssense.com/en-us/men/sneakers.json").json()
products = obj_json_data['products']
keyword = input('Enter a keyword: ')
for product in products:
if keyword.upper() in product['name'].upper():
name = product['name']
id_var = product['id']
sku = product['sku']
url = product['url']
print ('Product: %s\nID: %s\nSKU: %s\nURL: %s' %(name, id_var, sku, url))
# if you only want to return the first match, uncomment next line
#break
I also have it setup to store it into a dataframe, and or a list too. Just to give some options of where to go with it.
import requests
import pandas as pd
r = requests.Session()
obj_json_data = r.get("https://www.ssense.com/en-us/men/sneakers.json").json()
products = obj_json_data['products']
keyword = input('Enter a keyword: ')
products_found = []
results = pd.DataFrame()
for product in products:
if keyword.upper() in product['name'].upper():
name = product['name']
id_var = product['id']
sku = product['sku']
url = product['url']
temp_df = pd.DataFrame([[name, id_var, sku, url]], columns=['name','id','sku','url'])
results = results.append(temp_df)
products_found = products_found.append(name)
print ('Product: %s\nID: %s\nSKU: %s\nURL: %s' %(name, id_var, sku, url))
if products_found == []:
print ('Nothing found')
EDIT 2: Here is another way to do it by converting the json to a dataframe, then filtering by those rows that have the keyword in the name (this is actually a better solution in my opinion)
import requests
import pandas as pd
from pandas.io.json import json_normalize
r = requests.Session()
obj_json_data = r.get("https://www.ssense.com/en-us/men/sneakers.json").json()
products = obj_json_data['products']
products_df = json_normalize(products)
keyword = input('Enter a keyword: ')
products_found = []
results = pd.DataFrame()
results = products_df[products_df['name'].str.contains(keyword, case = False)]
#print (results[['name', 'id', 'sku', 'url']])
products_found = list(results['name'])
if products_found == []:
print ('Nothing found')
else:
print ('Found: '+ str(products_found))