{"id":12684,"date":"2020-03-04T07:36:26","date_gmt":"2020-03-04T12:36:26","guid":{"rendered":"https:\/\/rud.is\/b\/?p=12684"},"modified":"2020-03-04T07:36:26","modified_gmt":"2020-03-04T12:36:26","slug":"catchpole-redux-and-hashing-files-websites-with-ssdeepr","status":"publish","type":"post","link":"https:\/\/rud.is\/b\/2020\/03\/04\/catchpole-redux-and-hashing-files-websites-with-ssdeepr\/","title":{"rendered":"{catchpole} Redux and Hashing Files & Websites with {ssdeepr}"},"content":{"rendered":"

\u00dcber Tuesday has come and almost<\/em> gone (some state results will take a while to coalesce) and I’m relieved to say that {catchpole} did indeed work, with the example code from before<\/a> producing this on first run:<\/p>\n

\"\"<\/a><\/p>\n

If we tweak the buffer space around the squares, I think the cartogram looks better:<\/p>\n

\"\"<\/a><\/p>\n

but, you should likely use a different palette (see this Twitter thread<\/a> for examples).<\/p>\n

I noted in the previous post that borders might be possible. While I haven’t solved that use-case for individual states, I did manage to come up with a method for making a light version of the cartogram usable:<\/p>\n

library(sf)\nlibrary(hrbrthemes) \nlibrary(catchpole)\nlibrary(tidyverse)\n\ndelegates <- read_delegates()\n\ncandidates_expanded <- expand_candidates()\n\ngsf <- left_join(delegates_map(), candidates_expanded, by = c(\"state\", \"idx\"))\n\nm <- delegates_map()\n\n# split off each \"area\" on the map so we can make a border+background\nlist(\n  setdiff(state.abb, c(\"HI\", \"AK\")),\n  \"AK\", \"HI\", \"DC\", \"VI\", \"PR\", \"MP\", \"GU\", \"DA\", \"AS\"\n) %>% \n  map(~{\n    suppressWarnings(suppressMessages(st_buffer(\n      x = st_union(m[m$state %in% .x, ]),\n      dist = 0.0001,\n      endCapStyle = \"SQUARE\"\n    )))\n  }) -> m_borders\n\ngg <- ggplot()\nfor (mb in m_borders) {\n  gg <- gg + geom_sf(data = mb, col = \"#2b2b2b\", size = 0.125)\n}\n\ngg + \n  geom_sf(\n    data = gsf,\n    aes(fill = candidate),\n    col = \"white\", shape = 22, size = 3, stroke = 0.125\n  ) +\n  scale_fill_manual(\n    name = NULL,\n    na.value = \"#f0f0f0\",\n    values = c(\n      \"Biden\" = '#f0027f',\n      \"Sanders\" = '#7fc97f',\n      \"Warren\" = '#beaed4',\n      \"Buttigieg\" = '#fdc086',\n      \"Klobuchar\" = '#ffff99',\n      \"Gabbard\" = '#386cb0',\n      \"Bloomberg\" = '#bf5b17'\n    ),\n    limits = intersect(unique(delegates$candidate), names(delegates_pal))\n  ) +\n  guides(\n    fill = guide_legend(\n      override.aes = list(size = 4)\n    )\n  ) +\n  coord_sf(datum = NA) +\n  theme_ipsum_es(grid=\"\") +\n  theme(legend.position = \"bottom\")\n<\/code><\/pre>\n
\"\"<\/a><\/p>\n
{ssdeepr}<\/h3>\n
Researcher pals over at Binary Edge added web page hashing<\/a> (pre- and post-javascript scraping) to their platform using ssdeep<\/a>. This approach is in the category of context triggered piecewise hashes (CTPH) (or local sensitivity hashing) similar to my R adaptation\/packaging<\/a> of Trend Micro’s tlsh<\/a>.<\/p>\n
Since I’ll be working with BE’s data off-and-on and the ssdeep project has a well-crafted library (plus we might add ssdeep support at $DAYJOB), I went ahead and packaged that up as well<\/a>.<\/p>\n
I recommend using the hash_con()<\/code> function if you need to read large blobs since it doesn’t require you to read everything into memory first (though hash_file()<\/code> doesn’t either, but that’s a direct low-level call to the underlying ssdeep library file reader and not as flexible as R connections are).<\/p>\n
These types of hashes are great at seeing if something has changed on a website (or see how similar two things are to each other). For instance, how closely do CRAN mirror match the mothership?<\/p>\n
library(ssdeepr) # see the links above for installation\n\ncran1 <- hash_con(url(\"https:\/\/cran.r-project.org\/web\/packages\/available_packages_by_date.html\"))\ncran2 <- hash_con(url(\"https:\/\/cran.biotools.fr\/web\/packages\/available_packages_by_date.html\"))\ncran3 <- hash_con(url(\"https:\/\/cran.rstudio.org\/web\/packages\/available_packages_by_date.html\"))\n\nhash_compare(cran1, cran2)\n## [1] 0\n\nhash_compare(cran1, cran3)\n## [1] 94\n<\/code><\/pre>\n
I picked on cran.biotools.fr<\/code> as I saw they were well-behind CRAN-proper on the monitoring page.<\/p>\n
I noted that BE was doing pre- and post-javascript hashing as well. Why, you may ask? Well, websites behave differently with javascript running, plus they can behave differently when different user-agents are set. Let’s grab a page from Wikipedia a few different ways to show how they are not alike at all, depending on the retrieval context. First, let’s grab some web content!<\/p>\n
library(httr)\nlibrary(ssdeepr)\nlibrary(splashr)\n\n# regular grab\nh1 <- hash_con(url(\"https:\/\/en.wikipedia.org\/wiki\/Donald_Knuth\"))\n\n# you need Splash running for javascript-enabled scraping this way\nsp <- splash(host = \"mysplashhost\", user = \"splashuser\", pass = \"splashpass\")\n\n# js-enabled with one ua\nsp %>%\n  splash_user_agent(ua_macos_chrome) %>%\n  splash_go(\"https:\/\/en.wikipedia.org\/wiki\/Donald_Knuth\") %>%\n  splash_wait(2) %>%\n  splash_html(raw_html = TRUE) -> js1\n\n# js-enabled with another ua\nsp %>%\n  splash_user_agent(ua_ios_safari) %>%\n  splash_go(\"https:\/\/en.wikipedia.org\/wiki\/Donald_Knuth\") %>%\n  splash_wait(2) %>%\n  splash_html(raw_html = TRUE) -> js2\n\nh2 <- hash_raw(js1)\nh3 <- hash_raw(js2)\n\n# same way {rvest} does it\nres <- httr::GET(\"https:\/\/en.wikipedia.org\/wiki\/Donald_Knuth\")\n\nh4 <- hash_raw(content(res, as = \"raw\"))\n<\/code><\/pre>\n
Now, let’s compare them:<\/p>\n
hash_compare(h1, h4) # {ssdeepr} built-in vs httr::GET() => not surprising that they're equal\n## [1] 100\n\n# things look way different with js-enabled\n\nhash_compare(h1, h2)\n## [1] 0\nhash_compare(h1, h3)\n## [1] 0\n\n# and with variations between user-agents\n\nhash_compare(h2, h3)\n## [1] 0\n\nhash_compare(h2, h4)\n## [1] 0\n\n# only doing this for completeness\n\nhash_compare(h3, h4)\n## [1] 0\n<\/code><\/pre>\n
For this example, just content size would have been enough to tell the difference (mostly, note how the hashes are equal despite more characters coming back with the {httr} method):<\/p>\n
length(js1)\n## [1] 432914\n\nlength(js2)\n## [1] 270538\n\nnchar(\n  paste0(\n    readLines(url(\"https:\/\/en.wikipedia.org\/wiki\/Donald_Knuth\")),\n    collapse = \"\\n\"\n  )\n)\n## [1] 373078\n\nlength(content(res, as = \"raw\"))\n## [1] 374099\n<\/code><\/pre>\n
FIN<\/h3>\n
If you were in a U.S. state with a primary yesterday and were eligible to vote (and had something to vote for, either a (D) candidate or a state\/local bit of business) I sure hope you did!<\/p>\n
The ssdeep library works on Windows, so I’ll be figuring out how to get that going in {ssdeepr} fairly soon (mostly to try out the Rtools 4.0 toolchain vs deliberately wanting to support legacy platforms).<\/p>\n
As usual, drop issues\/PRs\/feature requests where you’re comfortable for any of these or other packages.<\/p>\n","protected":false},"excerpt":{"rendered":"
\u00dcber Tuesday has come and almost gone (some state results will take a while to coalesce) and I’m relieved to say that {catchpole} did indeed work, with the example code from before producing this on first run: If we tweak the buffer space around the squares, I think the cartogram looks better: but, you should […]<\/p>\n","protected":false},"author":1,"featured_media":12687,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"activitypub_content_warning":"","activitypub_content_visibility":"","activitypub_max_image_attachments":3,"activitypub_interaction_policy_quote":"anyone","activitypub_status":"","footnotes":""},"categories":[91],"tags":[],"class_list":["post-12684","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-r"],"yoast_head":"\n{catchpole} Redux and Hashing Files & Websites with {ssdeepr} - 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