我正在开展一个项目，目前需要我每天访问此网站 (https://returntogrounds.virginia.edu/covid-tracker)，并手动将每一天的 date 和 UVA positive cases 值添加到数据框中。有没有我可以在 R 中运行的代码来创建 date 和 UVA positive cases 的数据框，而不是我必须每天手动添加新数据？我看到有a similar question here，但这是我不熟悉的python。
【问题讨论】：
标签： r dataframe web-scraping tableau-api
您需要获取以下画面 URL：
https://public.tableau.com/views/UVACOVIDTracker/Summary?&:embed=y&:showVizHome=no
从那里，您需要执行以下流程（与this post 相同）：
调用以下网址：
GET https://public.tableau.com/views/S07StuP58/Dashboard1?:embed=y&:showVizHome=no
从textarea 中提取JSON 内容，id 为tsConfigContainer
使用 session_id 构建 url
POST https://public.tableau.com/{vizql_path}/bootstrapSession/sessions/{session_id}
从原本不是 JSON 的响应中提取 JSON 数据（正则表达式来拆分数据）
从大型 JSON 配置中提取数据，这并不简单，因为所有字符串数据都位于单个数组中。您需要从各个字段中获取数据索引，以便能够将数据拆分为列，然后构建您的数据框
这个视图上有很多“工作表”，所以我制作了一个脚本，提示用户选择一个，这样你就可以检查哪一个更方便：
library(rvest)
library(rjson)
library(httr)
library(stringr)
#replace the hostname and the path if necessary
host_url <- "https://public.tableau.com"
path <- "/views/UVACOVIDTracker/Summary"
body <- read_html(modify_url(host_url,
path = path,
query = list(":embed" = "y",":showVizHome" = "no")
))
data <- body %>%
html_nodes("textarea#tsConfigContainer") %>%
html_text()
json <- fromJSON(data)
url <- modify_url(host_url, path = paste(json$vizql_root, "/bootstrapSession/sessions/", json$sessionid, sep =""))
resp <- POST(url, body = list(sheet_id = json$sheetId), encode = "form")
data <- content(resp, "text")
extract <- str_match(data, "\\d+;(\\{.*\\})\\d+;(\\{.*\\})")
info <- fromJSON(extract[1,1])
data <- fromJSON(extract[1,3])
worksheets = names(data$secondaryInfo$presModelMap$vizData$presModelHolder$genPresModelMapPresModel$presModelMap)
for(i in 1:length(worksheets)){
print(paste("[",i,"] ",worksheets[i], sep=""))
}
selected <- readline(prompt="select worksheet by index: ");
worksheet <- worksheets[as.integer(selected)]
print(paste("you selected :", worksheet, sep=" "))
columnsData <- data$secondaryInfo$presModelMap$vizData$presModelHolder$genPresModelMapPresModel$presModelMap[[worksheet]]$presModelHolder$genVizDataPresModel$paneColumnsData
i <- 1
result <- list();
for(t in columnsData$vizDataColumns){
if (is.null(t[["fieldCaption"]]) == FALSE) {
paneIndex <- t$paneIndices
columnIndex <- t$columnIndices
if (length(t$paneIndices) > 1){
paneIndex <- t$paneIndices[1]
}
if (length(t$columnIndices) > 1){
columnIndex <- t$columnIndices[1]
}
result[[i]] <- list(
fieldCaption = t[["fieldCaption"]],
valueIndices = columnsData$paneColumnsList[[paneIndex + 1]]$vizPaneColumns[[columnIndex + 1]]$valueIndices,
aliasIndices = columnsData$paneColumnsList[[paneIndex + 1]]$vizPaneColumns[[columnIndex + 1]]$aliasIndices,
dataType = t[["dataType"]],
stringsAsFactors = FALSE
)
i <- i + 1
}
}
dataFull = data$secondaryInfo$presModelMap$dataDictionary$presModelHolder$genDataDictionaryPresModel$dataSegments[["0"]]$dataColumns
cstring <- list();
for(t in dataFull) {
if(t$dataType == "cstring"){
cstring <- t
break
}
}
data_index <- 1
name_index <- 1
frameData <- list()
frameNames <- c()
for(t in dataFull) {
for(index in result) {
if (t$dataType == index["dataType"]){
if (length(index$valueIndices) > 0) {
j <- 1
vector <- character(length(index$valueIndices))
for (it in index$valueIndices){
vector[j] <- t$dataValues[it+1]
j <- j + 1
}
frameData[[data_index]] <- vector
frameNames[[name_index]] <- paste(index$fieldCaption, "value", sep="-")
data_index <- data_index + 1
name_index <- name_index + 1
}
if (length(index$aliasIndices) > 0) {
j <- 1
vector <- character(length(index$aliasIndices))
for (it in index$aliasIndices){
if (it >= 0){
vector[j] <- t$dataValues[it+1]
} else {
vector[j] <- cstring$dataValues[abs(it)]
}
j <- j + 1
}
frameData[[data_index]] <- vector
frameNames[[name_index]] <- paste(index$fieldCaption, "alias", sep="-")
data_index <- data_index + 1
name_index <- name_index + 1
}
}
}
}
df <- NULL
lengthList <- c()
for(i in 1:length(frameNames)){
lengthList[i] <- length(frameData[[i]])
}
max <- max(lengthList)
for(i in 1:length(frameNames)){
if (length(frameData[[i]]) < max){
len <- length(frameData[[i]])
frameData[[i]][(len+1):max]<-""
}
df[frameNames[[i]]] <- frameData[i]
}
options(width = 1200)
df <- as.data.frame(df, stringsAsFactors = FALSE)
print(df)
与this post 相反，dataType 字段需要与来自presModelHolder$genVizDataPresModel$paneColumnsData 的字段相同（描述每列中的所有索引）
此脚本的输出：
Loading required package: xml2
[1] "[1] Active inpatient"
[1] "[2] Employee tests 2 weeks ago"
[1] "[3] Employee tests last week"
[1] "[4] Hosp all line"
[1] "[5] Hosp yesterday"
[1] "[6] Pos all UVA count line"
[1] "[7] Pos all UVA total"
[1] "[8] Pos student count line"
[1] "[9] Pos student total"
[1] "[10] Resources"
[1] "[11] Room isolation bar"
[1] "[12] Room quarantine bar"
[1] "[13] Student cases yesterday"
[1] "[14] Student new case 10-day total"
[1] "[15] Student test last week"
[1] "[16] Student tests 2 weeks ago"
[1] "[17] Tests UVA Lab TAT"
[1] "[18] Title"
[1] "[19] UVA 2 weeks ago"
[1] "[20] UVA Cases 10 subtotal"
[1] "[21] UVA Cases yesterday"
[1] "[22] UVA tests - last week"
[1] "[23] avg cases - 2 wks ago"
[1] "[24] avg cases - 3 wks ago"
[1] "[25] avg cases - last wk"
[1] "[26] avg new cases - this week"
[1] "[27] avg student cases - 2 weeks ago"
[1] "[28] avg student cases - 3 weeks ago"
[1] "[29] avg student cases - last week"
[1] "[30] avg student cases - this week"
select worksheet by index: 6
[1] "you selected : Pos all UVA count line"
X.Calculation_246290626693455872..value X.Event_Date..value
1 29 2020-10-01 00:00:00
2 33 2020-09-30 00:00:00
3 45 2020-09-29 00:00:00
4 4 2020-09-28 00:00:00
5 17 2020-09-27 00:00:00
6 23 2020-09-26 00:00:00
7 41 2020-09-25 00:00:00
..............................................................
40 2 2020-08-23 00:00:00
41 5 2020-08-22 00:00:00
42 3 2020-08-21 00:00:00
43 5 2020-08-20 00:00:00
44 3 2020-08-19 00:00:00
45 4 2020-08-18 00:00:00
46 4 2020-08-17 00:00:00
我注意到可以使用的工作表是“Pos all UVA count line”和“Pos student count line”
同样的脚本写在python：
import requests
from bs4 import BeautifulSoup
import json
import re
import pandas as pd
#replace the hostname and the path if necessary
host_url = "https://public.tableau.com"
path = "/views/UVACOVIDTracker/Summary"
url = f"{host_url}{path}"
r = requests.get(
url,
params= {
":embed": "y",
":showVizHome": "no"
}
)
soup = BeautifulSoup(r.text, "html.parser")
tableauData = json.loads(soup.find("textarea",{"id": "tsConfigContainer"}).text)
dataUrl = f'{host_url}{tableauData["vizql_root"]}/bootstrapSession/sessions/{tableauData["sessionid"]}'
r = requests.post(dataUrl, data= {
"sheet_id": tableauData["sheetId"],
})
dataReg = re.search('\d+;({.*})\d+;({.*})', r.text, re.MULTILINE)
info = json.loads(dataReg.group(1))
data = json.loads(dataReg.group(2))
worksheets = list(data["secondaryInfo"]["presModelMap"]["vizData"]["presModelHolder"]["genPresModelMapPresModel"]["presModelMap"].keys())
for idx, ws in enumerate(worksheets):
print(f"[{idx}] {ws}")
selected = input("select worksheet by index: ")
worksheet = worksheets[int(selected)]
print(f"you selected : {worksheet}")
columnsData = data["secondaryInfo"]["presModelMap"]["vizData"]["presModelHolder"]["genPresModelMapPresModel"]["presModelMap"][worksheet]["presModelHolder"]["genVizDataPresModel"]["paneColumnsData"]
result = [
{
"fieldCaption": t.get("fieldCaption", ""),
"valueIndices": columnsData["paneColumnsList"][t["paneIndices"][0]]["vizPaneColumns"][t["columnIndices"][0]]["valueIndices"],
"aliasIndices": columnsData["paneColumnsList"][t["paneIndices"][0]]["vizPaneColumns"][t["columnIndices"][0]]["aliasIndices"],
"dataType": t.get("dataType"),
"paneIndices": t["paneIndices"][0],
"columnIndices": t["columnIndices"][0]
}
for t in columnsData["vizDataColumns"]
if t.get("fieldCaption")
]
dataFull = data["secondaryInfo"]["presModelMap"]["dataDictionary"]["presModelHolder"]["genDataDictionaryPresModel"]["dataSegments"]["0"]["dataColumns"]
def onAlias(it, value, cstring):
return value[it] if (it >= 0) else cstring["dataValues"][abs(it)-1]
frameData = {}
cstring = [t for t in dataFull if t["dataType"] == "cstring"][0]
for t in dataFull:
for index in result:
if (t["dataType"] == index["dataType"]):
if len(index["valueIndices"]) > 0:
frameData[f'{index["fieldCaption"]}-value'] = [t["dataValues"][abs(it)] for it in index["valueIndices"]]
if len(index["aliasIndices"]) > 0:
frameData[f'{index["fieldCaption"]}-alias'] = [onAlias(it, t["dataValues"], cstring) for it in index["aliasIndices"]]
df = pd.DataFrame.from_dict(frameData, orient='index').fillna(0).T
with pd.option_context('display.max_rows', None, 'display.max_columns', None, 'display.width', 1000):
print(df)
编辑：我改进了脚本以包含提供更多数据的别名值
我制作了一个包含 Python 和 R 脚本的 repo here
【讨论】：
查找 rvest/xml2 以获取可解析的 HTML。不幸的是，对于 Tableau/PowerBI 应用程序，这并不简单。对于此类带有构建对象的页面，最好访问底层数据。
您强调的另一个答案是正确的。获取 JSON 格式的数据（通常来自 API 请求）并提取所需的值。但是，您会发现另一个问题是会话 ID 不是持久的。当您访问页面的 URL 时，您可能需要捕获所有 XHR 对象，然后通过一些混乱的逻辑来识别正确的对象。
（如果您需要查看页面访问中访问的所有资源，请在浏览器中按F12，然后转到“网络”选项卡。）
在这个阶段，如果 API 是公开可用的，或者他们是否可以在报告中提供数据集下载功能，询问 Tableau 作者可能不会有什么坏处。
祝你好运。
【讨论】：