Tools to Test and Compare Internet Bandwidth Speeds

Description

The ‘Ookla’ ‘Speedtest’ site http://beta.speedtest.net/about provides interactive and programmatic services to test and compare bandwidth speeds from a source node on the Internet to thousands of test servers. Tools are provided to obtain test server lists, identify target servers for testing and performing speed/bandwidth tests.

What’s Inside The Tin

The following functions are implemented:

  • spd_best_servers: Find “best” servers (latency-wise) from master server list
  • spd_closest_servers: Find “closest” servers (geography-wise) from master server list
  • spd_compute_bandwidth: Compute bandwidth from bytes transferred and time taken
  • spd_config: Retrieve client configuration information for the speedtest
  • spd_download_test: Perform a download speed/bandwidth test
  • spd_servers: Retrieve a list of SpeedTest servers
  • spd_upload_test: Perform an upload speed/bandwidth test
  • spd_test: Test your internet speed/bandwidth

Make a CLI utility

While you can run spd_test() from an R console, it was desgined to be an easily wrapped into a bash (et al) alias or put into a small batch script. Or, you can just type out the following if you’re fleet-of-finger/have dexterous digits:

Rscript --quiet -e 'speedtest::spd_test()'

which will look something like:

TODO

Folks interested in contributing can take a look at the TODOs and pick as many as you like! Ones with question marks are truly a “I dunno if we shld” kinda thing. Ones with exclamation marks are essentials.

  • [ ] Cache config in memory at startup vs pass around to functions?
  • [ ] Figure out how to use beta sockets hidden API vs the old Flash API?
  • [ ] Ensure the efficacy of relying on the cURL timings for speed measures for the Flash API
  • [ ] Figure out best way to capture the results for post-processing
  • [ ] Upload results to speedtest (tis only fair)!
  • [ ] Incorporate more network or host measures for better statistical determination of the best target!
  • [ ] autoplot support!
  • [ ] RStudio Add-in
  • [ ] Shiny app?

Installation

devtools::install_github("hrbrmstr/speedtest")
options(width=120)

Usage

library(speedtest)
library(stringi)
library(hrbrthemes)
library(ggbeeswarm)
library(tidyverse)

# current verison
packageVersion("speedtest")
## [1] '0.1.0'

Download Speed

config <- spd_config()

servers <- spd_servers(config=config)
closest_servers <- spd_closest_servers(servers, config=config)
only_the_best_severs <- spd_best_servers(closest_servers, config)

Individual download tests

glimpse(spd_download_test(closest_servers[1,], config=config))
## Observations: 1
## Variables: 15
## $ url     <chr> "http://speedtest.pilotfiber.com:8080/speedtest/upload.php"
## $ lat     <dbl> 40.7127
## $ lng     <dbl> -74.0059
## $ name    <chr> "New York, NY"
## $ country <chr> "United States"
## $ cc      <chr> "US"
## $ sponsor <chr> "Pilot"
## $ id      <chr> "13098"
## $ host    <chr> "speedtest.pilotfiber.com:8080"
## $ url2    <chr> NA
## $ min     <dbl> 422.2482
## $ mean    <dbl> 1785.507
## $ median  <dbl> 2055.092
## $ max     <dbl> 3003.25
## $ sd      <dbl> 891.7389
glimpse(spd_download_test(only_the_best_severs[1,], config=config))
## Observations: 1
## Variables: 17
## $ total_time     <dbl> 0.002756
## $ retrieval_time <dbl> 1.2e-05
## $ url            <chr> "http://speedtest.pilotfiber.com:8080/speedtest/upload.php"
## $ lat            <dbl> 40.7127
## $ lng            <dbl> -74.0059
## $ name           <chr> "New York, NY"
## $ country        <chr> "United States"
## $ cc             <chr> "US"
## $ sponsor        <chr> "Pilot"
## $ id             <chr> "13098"
## $ host           <chr> "speedtest.pilotfiber.com:8080"
## $ url2           <chr> NA
## $ min            <dbl> 1837.427
## $ mean           <dbl> 2602.224
## $ median         <dbl> 2571.093
## $ max            <dbl> 3312.199
## $ sd             <dbl> 408.9314

Individual upload tests

glimpse(spd_upload_test(only_the_best_severs[1,], config=config))
## Observations: 1
## Variables: 17
## $ total_time     <dbl> 0.002756
## $ retrieval_time <dbl> 1.2e-05
## $ url            <chr> "http://speedtest.pilotfiber.com:8080/speedtest/upload.php"
## $ lat            <dbl> 40.7127
## $ lng            <dbl> -74.0059
## $ name           <chr> "New York, NY"
## $ country        <chr> "United States"
## $ cc             <chr> "US"
## $ sponsor        <chr> "Pilot"
## $ id             <chr> "13098"
## $ host           <chr> "speedtest.pilotfiber.com:8080"
## $ url2           <chr> NA
## $ min            <dbl> 339.0728
## $ mean           <dbl> 803.9145
## $ median         <dbl> 811.5256
## $ max            <dbl> 1221.137
## $ sd             <dbl> 327.4945
glimpse(spd_upload_test(closest_servers[1,], config=config))
## Observations: 1
## Variables: 15
## $ url     <chr> "http://speedtest.pilotfiber.com:8080/speedtest/upload.php"
## $ lat     <dbl> 40.7127
## $ lng     <dbl> -74.0059
## $ name    <chr> "New York, NY"
## $ country <chr> "United States"
## $ cc      <chr> "US"
## $ sponsor <chr> "Pilot"
## $ id      <chr> "13098"
## $ host    <chr> "speedtest.pilotfiber.com:8080"
## $ url2    <chr> NA
## $ min     <dbl> 510.7232
## $ mean    <dbl> 1007.564
## $ median  <dbl> 1073.592
## $ max     <dbl> 1285.599
## $ sd      <dbl> 297.7289

Moar download tests

Choose closest, “best” and randomly (there can be, and are, some dups as a result for best/closest), run the test and chart the results. This will show just how disparate the results are from these core/crude tests. Most of the test servers compensate when they present the results. Newer, “socket”-based tests are more accurate but there are no free/hidden exposed APIs yet for most of them.

set.seed(8675309)

bind_rows(

  closest_servers[1:3,] %>%
    mutate(type="closest"),

  only_the_best_severs[1:3,] %>%
    mutate(type="best"),

  filter(servers, !(id %in% c(closest_servers[1:3,]$id, only_the_best_severs[1:3,]$id))) %>%
    sample_n(3) %>%
    mutate(type="random")

) %>%
  group_by(type) %>%
  ungroup() -> to_compare

select(to_compare, sponsor, name, country, host, type)
## # A tibble: 9 x 5
##   sponsor                  name            country       host                                    type   
##   <chr>                    <chr>           <chr>         <chr>                                   <chr>  
## 1 Pilot                    New York, NY    United States speedtest.pilotfiber.com:8080           closest
## 2 Spectrum                 New York, NY    United States speedtest.nyc.rr.com:8080               closest
## 3 AT&T                     New York, NY    United States nyc.speedtest.sbcglobal.net:8080        closest
## 4 Pilot                    New York, NY    United States speedtest.pilotfiber.com:8080           best   
## 5 ISPnet, Inc              New York, NY    United States speedtest1.ispnet.net:8080              best   
## 6 Optimum Online           New York, NY    United States vspeedgauge.optonline.net:8080          best   
## 7 31173 Services AB        Frankfurt       Germany       fra-eq5-tptest1.31173.se:8080           random 
## 8 GorillaServers           Los Angeles, CA United States lax1a-speedtest.gorillaservers.com:8080 random 
## 9 Vidatel Telecomunicações Serra Talhada   Brazil        ns2.redevidatel.com.br:8080             random
map_df(1:nrow(to_compare), ~{
  spd_download_test(to_compare[.x,], config=config, summarise=FALSE, timeout=30)
}) -> dl_results_full
mutate(dl_results_full, type=stri_trans_totitle(type)) %>%
  ggplot(aes(type, bw, fill=type)) +
  geom_quasirandom(aes(size=size, color=type), width=0.15, shape=21, stroke=0.25) +
  scale_y_continuous(expand=c(0,5)) +
  scale_size(range=c(2,6)) +
  scale_color_manual(values=c(Random="#b2b2b2", Best="#2b2b2b", Closest="#2b2b2b")) +
  scale_fill_ipsum() +
  labs(x=NULL, y=NULL, title="Download bandwidth test by selected server type",
       subtitle="Circle size scaled by size of file used in that speed test") +
  theme_ipsum_rc(grid="Y") +
  theme(legend.position="none")

Moar upload tests

Choose closest and “best” and filter duplicates out since we’re really trying to measure here vs show the disparity:

bind_rows(
  closest_servers[1:3,] %>% mutate(type="closest"),
  only_the_best_severs[1:3,] %>% mutate(type="best")
) %>%
  distinct(.keep_all=TRUE) -> to_compare

select(to_compare, sponsor, name, country, host, type)
## # A tibble: 6 x 5
##   sponsor        name         country       host                             type   
##   <chr>          <chr>        <chr>         <chr>                            <chr>  
## 1 Pilot          New York, NY United States speedtest.pilotfiber.com:8080    closest
## 2 Spectrum       New York, NY United States speedtest.nyc.rr.com:8080        closest
## 3 AT&T           New York, NY United States nyc.speedtest.sbcglobal.net:8080 closest
## 4 Pilot          New York, NY United States speedtest.pilotfiber.com:8080    best   
## 5 ISPnet, Inc    New York, NY United States speedtest1.ispnet.net:8080       best   
## 6 Optimum Online New York, NY United States vspeedgauge.optonline.net:8080   best
map_df(1:nrow(to_compare), ~{
  spd_upload_test(to_compare[.x,], config=config, summarise=FALSE, timeout=30)
}) -> ul_results_full
ggplot(ul_results_full, aes(x="Upload Test", y=bw)) +
  geom_quasirandom(aes(size=size, fill="col"), width=0.1, shape=21, stroke=0.25, color="#2b2b2b") +
  scale_y_continuous(expand=c(0,0.5)) +
  scale_size(range=c(2,6)) +
  scale_fill_ipsum() +
  labs(x=NULL, y=NULL, title="Upload bandwidth test by selected server type",
       subtitle="Circle size scaled by size of file used in that speed test") +
  theme_ipsum_rc(grid="Y") +
  theme(legend.position="none")

speedtest Metrics

Lang # Files (%) LoC (%) Blank lines (%) # Lines (%)
R 13 0.87 215 0.72 70 0.55 167 0.68
Rmd 1 0.07 63 0.21 49 0.38 78 0.32
make 1 0.07 20 0.07 9 0.07 0 0.00

Code of Conduct

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.