问题描述
该片段由@Andrej Kesely 提供,运行良好,但需要进一步简化结果数据以提高可读性。用于实现所需改进的其他想法将非常有帮助。
plot!
电流输出:
import requests
from bs4 import BeautifulSoup
from itertools import groupby
from time import sleep
url = "https://bscscan.com/tokentxns"
soup = BeautifulSoup(requests.get(url).content,"html.parser")
data = []
for tr in soup.select("tr:has(td)"):
tds = [td.get_text(strip=True) for td in tr.select("td")]
_,txn_hash,tm,age,from_,_,to_,value,token = tds
a = tr.select("a")[-1]["href"][7:]
data.append((a,token))
data = sorted(data)
for _,g in groupby(data,lambda k: k[0]):
g = list(map(list,g))
total = sum(float(s.replace(",","").replace("'","")) for _,s,*_ in g)
total = [f"{total:,} TOTAL",*[""] * (len(g) - 1)]
trans = [f"{len(g)} TRANS",*[""] * (len(g) - 1)]
for subl in g[1:]:
subl[0] = ""
for tr,t,subl in zip(trans,total,g):
print("{:<10} {:<45} {:<35} {:<30} {:<10}".format(tr,*subl,t))
print()
需要改进的输出:#-- 汇总结果集
3 TRANS 0x5941f87eb62737ec5ebbecab3e373c40fe40566b 148.549751978 Moon Nation ...(MNG) 6,981.838342967 TOTAL
148.549751978 Moon Nation ...(MNG)
6,684.738839011 Moon Nation ...(MNG)
2 TRANS 0xacb2d47827c9813ae26de80965845d80935afd0b 0.020495049504950495 MacaronSwap ...(MCRN) 0.22544554455445542 TOTAL
0.20495049504950495 MacaronSwap ...(MCRN)
8 TRANS 0xbb4cdb9cbd36b01bd1cbaebf2de08d9173bc095c 0.007499944888796266 Wrapped BNB (WBNB) 2.2045111407858444 TOTAL
0.013925651474219129 Wrapped BNB (WBNB)
0.0317943 Wrapped BNB (WBNB)
0.063495493859384612 Wrapped BNB (WBNB)
0.069626394590622519 Wrapped BNB (WBNB)
0.227799277696211921 Wrapped BNB (WBNB)
0.310825078276609791 Wrapped BNB (WBNB)
1.479545 Wrapped BNB (WBNB)
解决方法
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