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Aariq/extract_hashes.R

Last active January 31, 2022 15:50
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"hashes" from Elsevier PDF metadata
Raw
extract_hashes.R
# My janky r-code wrapping commandline tool `exiftool`
library(stringr)
library(purrr)
library(glue)
pull_hashes <- function(file) {
xml <- system(glue("exiftool -b -xmp '{file}'"), intern = TRUE)
doi <-
str_extract(xml, '\\b(10[.][0-9]{4,}(?:[.][0-9]+)*/(?:(?!["&\'<>])[[:graph:]])+)\\b') %>%
discard(~is.na(.x)) %>%
pluck(1)
hashes <-
str_match(xml, "<([0-9A-Za-z_.-]{40,})/>") %>% .[,2] %>%
discard(~is.na(.x))
# out <- list(hashes)
list(doi = doi, hash = hashes)
}
pdfs <- list.files("/Users/scottericr/Zotero/storage", pattern = "\\.pdf$", recursive = TRUE, full.names = TRUE)
hash_list <- map_df(pdfs, pull_hashes) %>% discard(~length(.x)==0)
write.csv(hash_list, "hash_list.csv", row.names = FALSE)
Raw
pdf_hashes.csv
doi hash
10.1016/j.actao.2020.103617 Zlkjsntz.y.eJnMiGndePzcNNnteLlwj.n96GywySzgf_otiSzdmLo9ePmtyJot6SmdqTma
10.1016/j.foreco.2020.118845 tprDsndb.ngeNzduGmdj-osNNmd3-lweLndiGmM6Jmtv8otmQn.mPo9ePmMyQndeOod6Tma
10.1016/j.scitotenv.2021.145397 6mIUqzdiOzweKywuGzt6Pn8NNzt2Slwj9yMqGngf_ztaMmMyKmwyNo9ePmtqPmtyRmMiTma
10.1016/j.ecolmodel.2019.108856 HIoninwyOmgeOot6Gz96PyLNNmt-PlwiJyMaGotySnMmPogqRnMeOo9ePmMiNm9ePm9iTma
10.1016/j.ecolmodel.2021.109813 LMfnsztyMnMr8zd-GyPyKnsNNnM37lweLy9eGotr_mM3.zt-QyMuSo9ePndeLm96JndaTma
10.1016/j.ecoinf.2020.101178 LMfnsm.iRnM79nMeGyPz7mLNNot3.lt_.od2GztaQogf-mwf-nM-Qo9ePmtqQmdyJn9eTma
10.1016/j.foodres.2016.10.024 HIoniz9v9mPj.y9eGzt-RncNNnMb7lweSyt-Gytr8nPePndmJyteNo9eOot2Jn9qQntuTma
10.1016/j.ecolmodel.2021.109813 LMfnsztyMnMr8zd-GyPyKnsNNnM37lweLy9eGotr_mM3.zt-QyMuSo9ePndeLm96JndaTma
10.1016/j.foodchem.2018.03.042 zjJBNmtf.mgeMywyGndb8msNNngeKlweSmdaGz9-Kz.qKyM_9n9mQo9eOot2Pn96Nmd2Tma
10.1016/j.ecolmodel.2020.109286 HIoniogyKnM37mwyGm.iNnsNNmd2Slwj7n.mGztf8m.mQmPuJnPyRo9ePmdaQotySm9mTma
10.1016/j.foreco.2016.04.050 TGji2nguOngv.mMyGz.uQocNNmMiLlt7-y.uGn9z_mMz_mM__ywn_o9ePmtyJot6QnMiTma
10.1016/j.csda.2011.02.004 LMfnszgz_y9uMmtaGz9r-osNNzgmLlt-Kz.iGnMqKmtf8mMaLot6Oo9ePmd-Rn9yLndiTma
10.1016/j.tibs.2018.12.004 zjJBNy.eQytv.mteGot6Jz8NNzwyOlt6RnduGzgr9ntj9ztyNod79o9ePmdaRmdmOod2Tma
10.1016/j.ecolmodel.2019.03.011 DpairyM7_zweLyPiGz.r.yLNNmwyNlt6Oz9-Gn9z-ytmRngv_nweKo9ePmMiNm9eOm96Tma
10.1016/j.ejbt.2017.05.010 ZtV1wzgeKnMz.mduGy9n_ncNNnwmNlwf.zduGz937yM2Mzdf8nMv.o9ePmdaJod6Rnd-Tma
10.1016/j.ecolmodel.2019.108870 lXLf8yMuNn9eJntuGywqQm8NNod79lt_9ogqGn92LotmKmtuJyweNo9eOnM-Pmd-Jod6Tma
10.1016/j.ecolmodel.2019.03.007 DpairyMf9ot6OmdiGz9qRyLNNzwiJlweLn9-GmwyQmMqPnteRotb-o9ePm9aJntyJn9aTma
10.1016/j.aca.2015.02.012 D2ei2z9b_yteQmMuGnwf8ocNNm.yKlweRy9qGmt_.mtqLntj8m.iQo9ePmdaMntiNnM-Tma
10.1016/j.csda.2011.02.004 LMfnszgz_y9uMmtaGz9r-osNNzgmLlt-Kz.iGnMqKmtf8mMaLot6Oo9ePmd-Rn9yLndiTma
10.1016/j.tree.2016.07.002 w8arlzdn_mguMywyGzd38nsNNn.iJlweKotaGnM7_mMr9ot2OytiQo9ePm9qMmduLmdeTma
10.1016/j.csda.2011.02.004 tprDsztz.od2OywuGy9uRysNNmweLlt6Rzt2Got-MyM2PmdiOnd-Jo9ePm92NotiQndiTma
10.1016/j.tifs.2020.05.015 D2ei2mwv-ytuRzgyGndyNn8NNyt-Llt-SntuGmd-Sz9-Nmd2Sztf.o9ePmdyQntuJn9yTma
10.1016/j.ecolmodel.2021.109813 LMfnsztyMnMr8zd-GyPyKnsNNnM37lweLy9eGotr_mM3.zt-QyMuSo9ePndeLm96JndaTma
10.1016/j.biocon.2020.108948 Ml8ZFodmKz9aMnMeGnMyOnLNNmMmMlweSot-GzweLy.r8z9f8z9v-o9ePmtiRotmKmduTma
10.1016/j.arabjc.2017.05.011 lXLf8mMz-odj_nt6Gz9-MzsNNyMmRlt_-mdmGmt6KmMn.mgmQzwqLo9ePndmNmdiQodmTma
10.1016/j.ecolmodel.2019.108877 6U7vczdb-mdn9nMmGy9mNmsNNm9uLlt6SnMmGnMyNmMb_y9z_z9b-o9ePmMiNm9eNoduTma
10.1016/j.ecolmodel.2021.109815 lXLf8n9b9zd-Ln92GzdmOmLNNnwuRlwiKmgyGzwySn9mPmtr8mMiMo9ePndeLm92SmMqTma
10.1016/j.sajb.2017.03.010 6U7vcm9uMzgz8nPeGzgv.nLNNmt7.lweSodiGmd38yt3_zwv8z96Jo9ePmMeLmdiNmM-Tma
10.1016/j.phytochem.2020.112515 XlEDunduMm9_-n96Gzd3-ncNNnMeKlweQmtyGztr8ztz-mwf9z.qOo9ePmdeMmdqQmMaTma
10.1016/j.atmosres.2020.105111 w8arlyMaLz96Omd2Gy97_mLNNyM6Nlwf_otyGnPeSn.j7ytuOn.n-o9ePmt-Qmd6RodyTma
10.1016/j.ecoinf.2020.101136 Zlkjsn.mMnt2Rmd-Gngf7mcNNywmNlt6SotuGzdmJmtv7yMuKodmJo9eOot-OotuOndmTma
10.1016/j.tree.2021.10.009 X9O3Czgz.ytr-ndyGnwj7ysNNm9qPlt79otuGmtqMy9eMywz-md__o9ePmM2KnM2RmdqTma
10.1016/j.tree.2016.07.002 w8arlzdn_mguMywyGzd38nsNNn.iJlweKotaGnM7_mMr9ot2OytiQo9ePm9qMmduLmdeTma
10.1016/j.arabjc.2017.05.011 zjJBNyPv9mwqRnPuGnd6RncNNnd37lt6Sn9-Gn9eOmdaPywyJm9b8o9ePndmNmdiSodmTma
10.1016/j.tree.2011.09.008 Dpairown-mgeLn9mGyPn.msNNod6LlwiNotqGowuLngeQnweMmwmLo9ePmtqPmMyOntiTma
10.1016/j.tree.2021.11.003 X9O3CyMmMotmMzdeGnPeSnsNNmgyRlt-Qy96GmweLmM6Motf8ytuOo9ePmM6Jn96Nm9aTma
10.1016/j.biopha.2017.09.024 6U7vcoteOndeOotaGm9iMm8NNmPn9lt-Ly9uGn9-QyMz-ztyQmPyPo9ePmMuRmdeSmdyTma
10.1016/j.envexpbot.2021.104557 TGji2yMmQnM2On92GoteJm8NNz96OlwiNz92Gz.n7nPqNmgv7m9_9o9ePm9qLodaMndyTma
10.1016/j.biocon.2020.108520 zjJBNy9r.yPj8otuGod-LmLNNndeOlt-LmMyGodr_z.yQnM2Smwn.o9ePmtiRodiSod2Tma
10.1016/j.jinsphys.2012.06.008 eMmMVyMyLmduQz9-GyMyPocNNmMn7lt-Nn9uGmwn8mt__y.ePnMuSo9eOn96KntqKoty
10.1016/j.ecoinf.2020.101178 ZlkjsnwuKy9uOz9mGngf7zsNNnMyJlt_-mM6GndeKnd6KzgiSy9_-o9ePmdyRntiQnd2Tma
10.1016/j.econedurev.2010.06.010 D2ei2yMv_odj.yM2Gy.iRn8NNodn.lt_8yMuGngiJn.eNm9mNodiNo9eOotqPndyNodiTma
10.1016/j.ecoinf.2021.101251 eMmMVnPeLmdiJy.mGyMuLz8NNz.qJlwf7nt2GmtiKy97-otn8nd6Po9ePmtuMmtqKnMeTma
10.1016/j.envexpbot.2020.104001 TGji2zt2MyMmJoteGod-SnLNNz.z_lt6KztuGz9f.nPyPy.mMzdmJo9ePmduJmt-NodiTma
10.1016/j.csda.2011.02.004 LMfnszgz_y9uMmtaGz9r-osNNzgmLlt-Kz.iGnMqKmtf8mMaLot6Oo9ePmd-Rn9yLndiTma
10.1016/j.actao.2014.05.009 zjJBNywj_mMj_n9eGn9qPzcNNm9_-lt7.ntqGnPyOywiQn.j7mPf-o9ePmt-KmduOndaTma
10.1016/j.foreco.2020.118845 tprDsndb.ngeNzduGmdj-osNNmd3-lweLndiGmM6Jmtv8otmQn.mPo9ePmMyQndeOod6Tma
10.1016/j.ecoinf.2021.101235 HIonim9z.mtz9n92GyMuNnLNNzdn8lt-Pm9mGm.qOn.yOmPqMz.r8o9ePmtqKmdqJntyTma
10.1016/j.cois.2016.07.004 zjJBNzdmJywiPnMeGnMmSosNNm9j7lt6Rnt-GzgeQnPyPot6Lmtf7o9ePmd6Jn9aSodeTma
10.1016/j.ecolmodel.2019.108797 DpairntyLn.iQm.qGztiJncNNyPqMlt-PytmGmdv_ztyKmwiPmd6Po9ePmMiNm9eOoduTma
10.1016/j.econedurev.2010.07.009 D2ei2mtf-mPf-mMuGy9-LmLNNyt6Rlt6JnteGy.n7mwmRowj.odr_o9eOoteQmMqPn9mTma
10.1016/j.envexpbot.2020.104001 TGji2zt2MyMmJoteGod-SnLNNz.z_lt6KztuGz9f.nPyPy.mMzdmJo9ePmduJmt-NodiTma
10.1016/j.arabjc.2017.05.011 d2UUdndiSmdeLmMuGzt6JmsNNzdeOlt-SmwuGy96Jzgz7zwqLmduJo9ePndmNmdiRm9iTma
10.1016/j.foodres.2020.109347 XlEDungr7mdqRogyGztf.nsNNm.uRlwiPnduGnwj7ytr.y9mMnteJo9eOotqKntiOod2Tma
10.1016/j.jinsphys.2012.06.008 eMmMVyMyLmduQz9-GyMyPocNNmMn7lt-Nn9uGmwn8mt__y.ePnMuSo9eOn96KntqKoty
10.1016/j.ecolmodel.2021.109457 d2UUdnd79nPf-mwyGndz8zsNNmMz9lt-LytmGmd-PoduKmd6LnPyLo9ePmtuMmtqMnteTma
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Aariq commented Jan 31, 2022

There's definitely some pattern here with most of them ending in "Tma" and just one in "Koty". Repeated beginnings include DpairyM, HIoni, LMfns, and D2ei2

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