如何找到网站API提取图形数据？

发布于 2025-02-06 22:11:41 字数 320 浏览 2 评论 0原文

https：//wwwww.okx.com/markets/markets/spot-data/spot-data/btc-btc--btc--btc- USDT 。我想使用R提取数据。尽管我在Stackoverlfow上找到了类似的帖子来做到这一点。我似乎找不到此网站的API。我检查了所有XHR文件，没有链接？这是否意味着隐藏？我只想要“ BTC保证金贷款比率”的API，

谢谢。

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陌若浮生 2025-02-13 22:11:41

XHR请求将数据作为JSON获取以制作图形。解析并复制情节非常简单。

为了使其更有用，您可以将其包装在启动日期和（可选）结束日期的函数中，并返回带有日期和值列的数据框架：

get_BTC_loan_ratio <- function(from, to = as.character(as.Date(Sys.time()) - 1))
{
  from <- as.character(from)
  to <- as.character(to)
  base_url <- "https://www.okx.com/priapi/v5/rubik/stat/margin/loan-ratio?"
  from <- paste0("&begin=", from, "T00:00:00Z")
  to <- paste0("&end=", to, "T23:00:00Z")
  url <- paste0(base_url, from, to, "&period=1D&ccy=BTC")
  df <- setNames(as.data.frame(jsonlite::fromJSON(url)$data), c("Date", "BTC"))
  df$BTC <- as.numeric(df$BTC)
  df$Date <- as.POSIXct(as.numeric(df$Date)/1000, origin = "1970-01-01")
  df[order(df$Date), ]
}

例如，自1月1日以来获取每日值的数据框架我们可以做：

BTC <- get_BTC_loan_ratio(from = "2022-01-01")

head(BTC)
#>                    Date     BTC
#> 163 2022-01-01 16:00:00  2.4766
#> 162 2022-01-02 16:00:00  2.9682
#> 161 2022-01-03 16:00:00  5.1275
#> 160 2022-01-04 16:00:00  3.6736
#> 159 2022-01-05 16:00:00  3.5300
#> 158 2022-01-06 16:00:00 17.6896

我们可以这样绘制它：

library(ggplot2)

ggplot(BTC, aes(Date, BTC)) +
  geom_line(color = "deepskyblue4") +
  theme_light(base_size = 16) +
  scale_x_datetime(date_labels = "%d %b % %Y")

nofollow noreferrer“> reprex软件包（v2.0.1）

The XHR requests fetch the data as json to make the graph. It's pretty straightforward to parse this and replicate the plot.

To make it more useful, you can wrap this in a function that takes a start date and (optional) end date and returns a data frame with a date and value column:

get_BTC_loan_ratio <- function(from, to = as.character(as.Date(Sys.time()) - 1))
{
  from <- as.character(from)
  to <- as.character(to)
  base_url <- "https://www.okx.com/priapi/v5/rubik/stat/margin/loan-ratio?"
  from <- paste0("&begin=", from, "T00:00:00Z")
  to <- paste0("&end=", to, "T23:00:00Z")
  url <- paste0(base_url, from, to, "&period=1D&ccy=BTC")
  df <- setNames(as.data.frame(jsonlite::fromJSON(url)$data), c("Date", "BTC"))
  df$BTC <- as.numeric(df$BTC)
  df$Date <- as.POSIXct(as.numeric(df$Date)/1000, origin = "1970-01-01")
  df[order(df$Date), ]
}

For example, to get a data frame of daily values since 1st January we can do:

BTC <- get_BTC_loan_ratio(from = "2022-01-01")

head(BTC)
#>                    Date     BTC
#> 163 2022-01-01 16:00:00  2.4766
#> 162 2022-01-02 16:00:00  2.9682
#> 161 2022-01-03 16:00:00  5.1275
#> 160 2022-01-04 16:00:00  3.6736
#> 159 2022-01-05 16:00:00  3.5300
#> 158 2022-01-06 16:00:00 17.6896

And we can plot it like this:

library(ggplot2)

ggplot(BTC, aes(Date, BTC)) +
  geom_line(color = "deepskyblue4") +
  theme_light(base_size = 16) +
  scale_x_datetime(date_labels = "%d %b % %Y")