MassiveAtoms/albion-shit
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MassiveAtoms 2020-05-28 09:15:38 -03:00
commit 70097239ec
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___quick.py Normal file
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import json
from collections import OrderedDict
with open("items.json", "r") as file:
this = json.load(file)
keys = sorted(this.keys())
newthis = OrderedDict()
for i in keys:
newthis[i] = this[i]
with open("items.json", "w") as file:
json.dump(newthis, file)

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import aiohttp
import asyncio
import json
with open("items.json", "r") as jfile:
items = json.load(jfile)
qualities = {
1: " normal",
2: " good",
3: " outstanding",
4: " excellent",
5: " masterpiece"
}
def gen_urls():
its = sorted(items.keys())
urls = []
for i in range(0, 5850, 200):
curritems = ",".join(its[i:i+200])
url = f"https://www.albion-online-data.com/api/v2/stats/prices/{curritems}@2?locations=3005,3003"
urls.append(url)
return urls
async def fetch(session, url):
"""Execute an http call async
Args:
session: contexte for making the http call
url: URL to call
Return:
responses: A dict like object containing http response
"""
async with session.get(url) as response:
resp = await response.json()
return resp
async def fetch_all(urls):
""" Gather many HTTP call made async
Args:
cities: a list of string
Return:
responses: A list of dict like object containing http response
"""
async with aiohttp.ClientSession() as session:
tasks = []
for url in urls:
tasks.append(
fetch(
session,
url,
)
)
responses = await asyncio.gather(*tasks, return_exceptions=True)
return responses
def run(urls):
responses = asyncio.run(fetch_all(urls))
return responses
def parser(itemdata):
caer = {}
black = {}
for kindajson in itemdata:
thing = json.loads(kindajson)
for item in thing:
name = items[item["item_id"]] + qualities[item["quality"]]
if item["city"] == "Black Market":
black[name] = item["buy_price_max"]
else:
caer[name] = item["sell_price_min"]
profits = []
for k in black.keys():
sell = black[k]
buy = caer[k]
profit = sell * 0.94 - buy
if profit > 0:
row = {
"black" : sell,
"caer" : buy,
"profit" : profit,
"name" : k
}
profits.append(row)
return profits
links=gen_urls()
responses = run(links)
print(parser(responses))
with open("res.json", "w") as jfile:
json.dump(responses, jfile)

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import json
import requests
from datetime import datetime
from rich.console import Console
from rich.table import Column, Table
with open("items.json", "r") as itfile:
itemnames = json.load(itfile)
qualities = {
1 : " normal",
2 : " good",
3 : " outstanding",
4 : " excellent",
5 : " masterpiece"
}
def fetch_data():
step = 200
responses = []
for i in range(0,5850,step):
print(i)
items = ",".join(list(itemnames.keys())[i:i+step])
url = "https://www.albion-online-data.com/api/v2/stats/prices/{}?locations=3005,3003".format(items)
content = requests.get(url).content
toolong = b'<html>\r\n<head><title>414 Request-URI Too Large</title></head>\r\n<body>\r\n<center><h1>414 Request-URI Too Large</h1></center>\r\n<hr><center>nginx/1.16.1</center>\r\n</body>\r\n</html>\r\n'
if content == toolong:
print("TOOOOO LONG")
else:
responses.append(content)
black = {}
caer = {}
for j in responses:
j = json.loads(j)
for item in j:
name = itemnames[item["item_id"]] + qualities[item["quality"]]
if item["city"] == "Black Market":
black[name] = item["buy_price_max"]
else:
caer[name] = item["sell_price_min"]
profits = []
for k in black.keys():
if not black[k] or not caer[k]:
continue
if black[k] < caer[k]:
continue
profit = black[k] * 0.94 - caer[k]
profits.append((profit, black[k] * 0.94, caer[k], k))
profits = sorted(profits)
return profits
def print_data(items):
#list of (blackmarketprice, caer price, itemname)
console = Console()
table = Table(show_header=True, header_style="bold green")
table.add_column("Item")
table.add_column("Profit(tax removed)")
table.add_column("Caer price")
table.add_column("Black market price")
for i in items:
if i[0] < 500:
continue
row = [i[3], str(i[0]/1000) + "k",str(i[2]/1000) + "k", str(i[1]/1000) + "k"]
table.add_row(*row)
console.print(table)
print_data(fetch_data())