Tools to Test and Compare Internet Bandwidth Speeds
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.
The following functions are implemented:
spd_best_servers
: Find “best” servers (latency-wise) from master server listspd_closest_servers
: Find “closest” servers (geography-wise) from master server listspd_compute_bandwidth
: Compute bandwidth from bytes transferred and time takenspd_config
: Retrieve client configuration information for the speedtestspd_download_test
: Perform a download speed/bandwidth testspd_servers
: Retrieve a list of SpeedTest serversspd_upload_test
: Perform an upload speed/bandwidth testspd_test
: Test your internet speed/bandwidth
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:
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?
devtools::install_github("hrbrmstr/speedtest")
options(width=120)
library(speedtest)
library(stringi)
library(hrbrthemes)
library(ggbeeswarm)
library(tidyverse)
# current verison
packageVersion("speedtest")
## [1] '0.1.0'
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)
glimpse(spd_download_test(closest_servers[1,], config=config))
## Observations: 1
## Variables: 15
## $ url <chr> "http://speed0.xcelx.net/speedtest/upload.php"
## $ lat <dbl> 42.3875
## $ lng <dbl> -71.1
## $ name <chr> "Somerville, MA"
## $ country <chr> "United States"
## $ cc <chr> "US"
## $ sponsor <chr> "Axcelx Technologies LLC"
## $ id <chr> "5960"
## $ host <chr> "speed0.xcelx.net:8080"
## $ url2 <chr> "http://speed1.xcelx.net/speedtest/upload.php"
## $ min <dbl> 14.40439
## $ mean <dbl> 60.06834
## $ median <dbl> 55.28457
## $ max <dbl> 127.9436
## $ sd <dbl> 34.20695
glimpse(spd_download_test(only_the_best_severs[1,], config=config))
## Observations: 1
## Variables: 18
## $ ping_time <dbl> 0.02712567
## $ total_time <dbl> 0.059917
## $ retrieval_time <dbl> 2.3e-05
## $ url <chr> "http://speed0.xcelx.net/speedtest/upload.php"
## $ lat <dbl> 42.3875
## $ lng <dbl> -71.1
## $ name <chr> "Somerville, MA"
## $ country <chr> "United States"
## $ cc <chr> "US"
## $ sponsor <chr> "Axcelx Technologies LLC"
## $ id <chr> "5960"
## $ host <chr> "speed0.xcelx.net:8080"
## $ url2 <chr> "http://speed1.xcelx.net/speedtest/upload.php"
## $ min <dbl> 14.64922
## $ mean <dbl> 56.15303
## $ median <dbl> 51.89162
## $ max <dbl> 107.5084
## $ sd <dbl> 31.8866
glimpse(spd_upload_test(only_the_best_severs[1,], config=config))
## Observations: 1
## Variables: 18
## $ ping_time <dbl> 0.02712567
## $ total_time <dbl> 0.059917
## $ retrieval_time <dbl> 2.3e-05
## $ url <chr> "http://speed0.xcelx.net/speedtest/upload.php"
## $ lat <dbl> 42.3875
## $ lng <dbl> -71.1
## $ name <chr> "Somerville, MA"
## $ country <chr> "United States"
## $ cc <chr> "US"
## $ sponsor <chr> "Axcelx Technologies LLC"
## $ id <chr> "5960"
## $ host <chr> "speed0.xcelx.net:8080"
## $ url2 <chr> "http://speed1.xcelx.net/speedtest/upload.php"
## $ min <dbl> 6.240858
## $ mean <dbl> 9.527599
## $ median <dbl> 9.303148
## $ max <dbl> 12.56686
## $ sd <dbl> 2.451778
glimpse(spd_upload_test(closest_servers[1,], config=config))
## Observations: 1
## Variables: 15
## $ url <chr> "http://speed0.xcelx.net/speedtest/upload.php"
## $ lat <dbl> 42.3875
## $ lng <dbl> -71.1
## $ name <chr> "Somerville, MA"
## $ country <chr> "United States"
## $ cc <chr> "US"
## $ sponsor <chr> "Axcelx Technologies LLC"
## $ id <chr> "5960"
## $ host <chr> "speed0.xcelx.net:8080"
## $ url2 <chr> "http://speed1.xcelx.net/speedtest/upload.php"
## $ min <dbl> 6.764702
## $ mean <dbl> 9.896179
## $ median <dbl> 10.3605
## $ max <dbl> 12.85389
## $ sd <dbl> 2.359868
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
## <chr> <chr> <chr>
## 1 Axcelx Technologies LLC Somerville, MA United States
## 2 Comcast Boston, MA United States
## 3 Starry, Inc. Boston, MA United States
## 4 Axcelx Technologies LLC Somerville, MA United States
## 5 Norwood Light Broadband Norwood, MA United States
## 6 CCI - New England Providence, RI United States
## 7 PirxNet Gliwice Poland
## 8 Interoute VDC Los Angeles, CA United States
## 9 UNPAD Bandung Indonesia
## # ... with 2 more variables: host <chr>, type <chr>
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), labels=c(sprintf("%s", seq(0,150,50)), "200 Mb/s"), limits=c(0,200)) +
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")
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
## <chr> <chr> <chr>
## 1 Axcelx Technologies LLC Somerville, MA United States
## 2 Comcast Boston, MA United States
## 3 Starry, Inc. Boston, MA United States
## 4 Axcelx Technologies LLC Somerville, MA United States
## 5 Norwood Light Broadband Norwood, MA United States
## 6 CCI - New England Providence, RI United States
## # ... with 2 more variables: host <chr>, type <chr>
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), breaks=seq(0,16,4),
labels=c(sprintf("%s", seq(0,12,4)), "16 Mb/s"), limits=c(0,16)) +
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")
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.