pygetpapers 1.2.5

Description:

pygetpapers 1.2.5

Research Papers right from python

What is pygetpapers


pygetpapers is a tool to assist text miners. It makes requests to open access scientific text repositories, analyses the hits, and systematically downloads the articles without further interaction.


Comes with the packages pygetpapers and downloadtools which provide various functions to download, process and save research papers and their metadata.


The main medium of its interaction with users is through a command-line interface.


pygetpapers has a modular design which makes maintenance easy and simple. This also allows adding support for more repositories simple.




















The developer documentation has been setup at readthedocs

History
getpapers is a tool written by Rik Smith-Unna funded by ContentMine at https://github.com/ContentMine/getpapers. The OpenVirus community requires a Python version and Ayush Garg has written an implementation from scratch, with some enhancements.
Formats supported by pygetpapers

pygetpapers gives fulltexts in xml and pdf format.
The metadata for papers can be saved in many formats including JSON, CSV, HTML.
Queries can be saved in form of an ini configuration file.
The additional files for papers can also be downloaded. References and citations for papers are given in XML format.
Log files can be saved in txt format.

Repository Structure
The main code is located in the pygetpapers directory. All the supporting modules for different repositories are described in the pygetpapers/repository directory.
Architecture



About the author and community
pygetpapers has been developed by Ayush Garg under the dear guidance of the OpenVirus community and Peter Murray Rust. Ayush is currently a high school student who believes that the world can only truly progress when knowledge is open and accessible by all.
Testers from OpenVirus have given a lot of useful feedback to Ayush without which this project would not have been possible.
The community has taken time to ensure that everyone can contribute to this project. So, YOU, the developer, reader and researcher can also contribute by testing, developing, and sharing.
Installation
Ensure that pip is installed along with python. Download python from: https://www.python.org/downloads/ and select the option Add Python to Path while installing.
Check out https://pip.pypa.io/en/stable/installing/ if difficulties installing pip. Also, checkout https://packaging.python.org/en/latest/tutorials/installing-packages/ to learn more about installing packages in python.

Method one (recommended):


Enter the command: pip install pygetpapers


Ensure pygetpapers has been installed by reopening the terminal and typing the command pygetpapers


You should see a help message come up.



Method two (Install Directly From Head):


Ensure git cli is installed and is available in path. Check out (https://git-scm.com/book/en/v2/Getting-Started-Installing-Git)


Enter the command: pip install git+https://github.com/petermr/pygetpapers.git


Ensure pygetpapers has been installed by reopening the terminal and typing the command pygetpapers


You should see a help message come up.



Usage
pygetpapers is a commandline tool. You can ask for help by running:
pygetpapers --help

usage: pygetpapers [-h] [--config CONFIG] [-v] [-q QUERY] [-o OUTPUT]
[--save_query] [-x] [-p] [-s] [-z] [--references REFERENCES]
[-n] [--citations CITATIONS] [-l LOGLEVEL] [-f LOGFILE]
[-k LIMIT] [-r] [-u] [--onlyquery] [-c] [--makehtml]
[--synonym] [--startdate STARTDATE] [--enddate ENDDATE]
[--terms TERMS] [--notterms NOTTERMS] [--api API]
[--filter FILTER]

Welcome to Pygetpapers version 0.0.9.3. -h or --help for help

optional arguments:
-h, --help show this help message and exit
--config CONFIG config file path to read query for pygetpapers
-v, --version output the version number
-q QUERY, --query QUERY
query string transmitted to repository API. Eg.
"Artificial Intelligence" or "Plant Parts". To escape
special characters within the quotes, use backslash.
Incase of nested quotes, ensure that the initial quotes
are double and the qutoes inside are single. For eg:
`'(LICENSE:"cc by" OR LICENSE:"cc-by") AND
METHODS:"transcriptome assembly"' ` is wrong. We should
instead use `"(LICENSE:'cc by' OR LICENSE:'cc-by') AND
METHODS:'transcriptome assembly'"`
-o OUTPUT, --output OUTPUT
output directory (Default: Folder inside current working directory named current date and time)
--save_query saved the passed query in a config file
-x, --xml download fulltext XMLs if available or save metadata as
XML
-p, --pdf [E][A] download fulltext PDFs if available (only eupmc
and arxiv supported)
-s, --supp [E] download supplementary files if available (only eupmc
supported)
-z, --zip [E] download files from ftp endpoint if available (only
eupmc supported)
--references REFERENCES
[E] Download references if available. (only eupmc
supported)Requires source for references
(AGR,CBA,CTX,ETH,HIR,MED,PAT,PMC,PPR).
-n, --noexecute [ALL] report how many results match the query, but don't
actually download anything
--citations CITATIONS
[E] Download citations if available (only eupmc
supported). Requires source for citations
(AGR,CBA,CTX,ETH,HIR,MED,PAT,PMC,PPR).
-l LOGLEVEL, --loglevel LOGLEVEL
[All] Provide logging level. Example --log warning
<<info,warning,debug,error,critical>>, default='info'
-f LOGFILE, --logfile LOGFILE
[All] save log to specified file in output directory as
well as printing to terminal
-k LIMIT, --limit LIMIT
[All] maximum number of hits (default: 100)
-r, --restart [E] Downloads the missing flags for the corpus.Searches
for already existing corpus in the output directory
-u, --update [E][B][M][C] Updates the corpus by downloading new
papers. Requires -k or --limit (If not provided, default
will be used) and -q or --query (must be provided) to be
given. Searches for already existing corpus in the output
directory
--onlyquery [E] Saves json file containing the result of the query in
storage. (only eupmc supported)The json file can be given
to --restart to download the papers later.
-c, --makecsv [All] Stores the per-document metadata as csv.
--makehtml [All] Stores the per-document metadata as html.
--synonym [E] Results contain synonyms as well.
--startdate STARTDATE
[E][B][M] Gives papers starting from given date. Format:
YYYY-MM-DD
--enddate ENDDATE [E][B][M] Gives papers till given date. Format: YYYY-MM-
DD
--terms TERMS [All] Location of the file which contains terms
serperated by a comma or an ami dict which will beOR'ed
among themselves and AND'ed with the query
--notterms NOTTERMS [All] Location of the txt file which contains terms
serperated by a comma or an ami dict which will beOR'ed
among themselves and NOT'ed with the query
--api API API to search [eupmc,
crossref,arxiv,biorxiv,medrxiv,rxivist] (default: eupmc)
--filter FILTER [C] filter by key value pair (only crossref supported)

Queries are build using -q flag. The query format can be found at http://europepmc.org/docs/EBI_Europe_PMC_Web_Service_Reference.pdf A condensed guide can be found at https://github.com/petermr/pygetpapers/wiki/query-format
Repository-specific flags
To convey the repository specificity, we've used the first letter of the repository in square brackets in its description.
What is CProject?
A CProject is a directory structure that the AMI toolset uses to gather and process data. Each paper gets its folder.

A CTree is a subdirectory of a CProject that deals with a single paper.

Tutorial
pygetpapers was on version 0.0.9.3 when the tutorials were documented.
pygetpapers supports multiple APIs including eupmc, crossref,arxiv,biorxiv,medrxiv,rxivist-bio,rxivist-med. By default, it queries EPMC. You can specify the API by using --api flag.
You can also follow this colab notebook as part of the tutorial.



Features
EPMC
crossref
arxiv
biorxiv
medarxiv
rxvist




Fulltext formats
xml, pdf
NA
pdf
xml
xml
xml


Metdata formats
json, html, csv
json, xml, csv
json, csv, html, xml
json, csv, html
json, csv, html
json, html, csv


--query
yes
yes
yes
NA
NA
NA


--update
yes
NA
NA
yes
yes



--restart
yes
NA
NA
NA
NA
NA


--citation
yes
NA
NA
NA
NA
NA


--references
yes
NA
NA
NA
NA
NA


--terms
yes
yes
yes
NA
NA
NA



EPMC (Default API)
Example Query
Let's break down the following query:
pygetpapers -q "METHOD: invasive plant species" -k 10 -o "invasive_plant_species_test" -c --makehtml -x --save_query




Flag
What it does
In this case pygetpapers...




-q
specifies the query
queries for 'invasive plant species' in METHODS section


-k
number of hits (default 100)
limits hits to 10


-o
specifies output directory
outputs to invasive_plant_species_test


-x
downloads fulltext xml



-c
saves per-paper metadata into a single csv
saves single CSV named europe_pmc.csv


--makehtml
saves per-paper metadata into a single HTML file
saves single HTML named europe_pmc.html


--save_query
saves the given query in a config.ini in output directory
saves query to saved_config.ini



pygetpapers, by default, writes metadata to a JSON file within:

individual paper directory for corresponding paper (epmc_result.json)
working directory for all downloaded papers (epmc_results.json)

OUTPUT:
INFO: Final query is METHOD: invasive plant species
INFO: Total Hits are 17910
0it [00:00, ?it/s]WARNING: Keywords not found for paper 1
WARNING: Keywords not found for paper 4
1it [00:00, 164.87it/s]
INFO: Saving XML files to C:\Users\shweata\invasive_plant_species_test\*\fulltext.xml
100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [00:21<00:00, 2.11s/it]

Scope the number of hits for a query
If you are just scoping the number of hits for a given query, you can use -n flag as shown below.
pygetpapers -n -q "essential oil"

OUTPUT:
INFO: Final query is essential oil
INFO: Total number of hits for the query are 190710

Update an existing CProject with new papers by feeding the metadata JSON
The --update command is used to update a CProject with a new set of papers on same or different query.
If let's say you have a corpus of a 30 papers on 'essential oil' (like before) and would like to download 20 more papers to the same CProject directory, you use --update command.
To update your Cproject, you would give it the -o flag the already existing CProject name. Additionally, you should also add --update flag.
INPUT:
pygetpapers -q "invasive plant species" -k 10 -x -o lantana_test_5 --update

OUTPUT:
INFO: Final query is invasive plant species
INFO: Please ensure that you are providing the same --api as the one in the corpus or you may get errors
INFO: Total Hits are 32956
0it [00:00, ?it/s]WARNING: html url not found for paper 5
WARNING: pdf url not found for paper 5
WARNING: Keywords not found for paper 6
WARNING: Keywords not found for paper 7
WARNING: Author list not found for paper 10
1it [00:00, 166.68it/s]
INFO: Saving XML files to C:\Users\shweata\lantana_test_5\*\fulltext.xml
100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 20/20 [01:03<00:00, 3.16s/it]

How is --update different from just downloading x number of papers to the same output directory?
By using --update command you can be sure that you don't overwrite the existing papers.
Restart downloading papers to an existing CProject
--restart flag can be used for two purposes:

To download papers in different format. Let's say you downloaded XMLs in the first round. If you want to download pdfs for same set of papers, you use this flag.
Continue the download from the stage where it broke. This feature would particularly come in handy if you are on poor lines.
Let's start off by forcefully interrupting the download.
INPUT:

pygetpapers -q "pinus" -k 10 -o pinus_10 -x

OUTPUT:
INFO: Final query is pinus
INFO: Total Hits are 32086
0it [00:00, ?it/s]WARNING: html url not found for paper 10
WARNING: pdf url not found for paper 10
1it [00:00, 63.84it/s]
INFO: Saving XML files to C:\Users\shweata\pinus_10\*\fulltext.xml
60%|██████████████████████████████████████████████████████████████████████████████▌ | 6/10 [00:20<00:13, 3.42s/it]
Traceback (most recent call last):
...
KeyboardInterrupt
^C

If you take a look at the CProject directory, there are 6 papers downloaded so far.
C:.
│ eupmc_results.json
│
├───PMC8157994
│ eupmc_result.json
│ fulltext.xml
│
├───PMC8180188
│ eupmc_result.json
│ fulltext.xml
│
├───PMC8198815
│ eupmc_result.json
│ fulltext.xml
│
├───PMC8216501
│ eupmc_result.json
│ fulltext.xml
│
├───PMC8309040
│ eupmc_result.json
│ fulltext.xml
│
└───PMC8325914
eupmc_result.json
fulltext.xml

To download the rest, we can use --restart flag.
INPUT
pygetpapers -q "pinus" -o pinus_10 --restart -x

OUTPUT:
INFO: Saving XML files to C:\Users\shweata\pinus_10\*\fulltext.xml
80%|████████████████████████████████████████████████████████████████████████████████████████████████████████▊ | 8/10 [00:27<00:07, 3.51s/it 90%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▉ | 9/10 [00:38<00:05, 5.95s/it100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [00:40<00:00, 4.49s/it100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [00:40<00:00, 4.01s/it]

Now if we inspect the CProject directory, we see that we have 10 papers as specified.
C:.
│ eupmc_results.json
│
├───PMC8157994
│ eupmc_result.json
│ fulltext.xml
│
├───PMC8180188
│ eupmc_result.json
│ fulltext.xml
│
├───PMC8198815
│ eupmc_result.json
│ fulltext.xml
│
├───PMC8199922
│ eupmc_result.json
│ fulltext.xml
│
├───PMC8216501
│ eupmc_result.json
│ fulltext.xml
│
├───PMC8309040
│ eupmc_result.json
│ fulltext.xml
│
├───PMC8309338
│ eupmc_result.json
│ fulltext.xml
│
├───PMC8325914
│ eupmc_result.json
│ fulltext.xml
│
├───PMC8399312
│ eupmc_result.json
│ fulltext.xml
│
└───PMC8400686
eupmc_result.json
fulltext.xml

Under the hood, pygetpapers looks for eupmc_results.json, reads it and resumes the download.
You could also use --restart to download the fulltext or metadata in different format other than the ones that you've already downloaded. For example, if I want all the fulltext PDFs of the 10 papers on pinus, I can run:
INPUT:
pygetpapers -q "pinus" -o pinus_10 --restart -p --makehtml

OUTPUT:
>pygetpapers -q "pinus" -o pinus_10 --restart -p --makehtml
100%|█████████████████████████████████████████████| 10/10 [03:26<00:00, 20.68s/it]

Now, if we take a look at the CProject:
C:.
│ eupmc_results.json
│
├───PMC8157994
│ eupmc_result.html
│ eupmc_result.json
│ fulltext.pdf
│ fulltext.xml
│
├───PMC8180188
│ eupmc_result.html
│ eupmc_result.json
│ fulltext.pdf
│ fulltext.xml
│
├───PMC8198815
│ eupmc_result.html
│ eupmc_result.json
│ fulltext.pdf
│ fulltext.xml
...

We find that each paper now has fulltext PDFs and metadata in HTML.
Difference between --restart and --update

If you aren't looking download new set of papers but would want to download a papers in different format for existing papers, --restart is the flag you'd want to use
If you are looking to download a new set of papers to an existing Cproject, then you'd use --update command. You should note that the format in which you download papers would only apply to the new set of papers and not for the old.

Downloading citations and references for papers, if available


--references and --citations flags can be used to download the references and citations respectively.


It also requires source for references (AGR,CBA,CTX,ETH,HIR,MED,PAT,PMC,PPR)
pygetpapers -q "lantana" -k 10 -o "test" -c -x --citation PMC


Downloading only the metadata
If you are looking to download just the metadata in the supported formats--onlyquery is the flag you use. It saves the metadata in the output directory.
You can use --restart feature to download the fulltexts for these papers.
INPUT:
pygetpapers --onlyquery -q "lantana" -k 10 -o "lantana_test" -c

OUTPUT:
INFO: Final query is lantana
INFO: Total Hits are 1909
0it [00:00, ?it/s]WARNING: html url not found for paper 1
WARNING: pdf url not found for paper 1
WARNING: Keywords not found for paper 2
WARNING: Keywords not found for paper 3
WARNING: Author list not found for paper 5
WARNING: Author list not found for paper 8
WARNING: Keywords not found for paper 9
1it [00:00, 407.69it/s]

Download papers within certain start and end date range
By using --startdate and --enddate you can specify the date range within which the papers you want to download were first published.
pygetpapers -q "METHOD:essential oil" --startdate "2020-01-02" --enddate "2021-09-09"

Saving query for later use
To save a query for later use, you can use --save_query. What it does is that it saves the query in a .ini file in the output directory.
pygetpapers -q "lantana" -k 10 -o "lantana_query_config"--save_query

Here is an example config file pygetpapers outputs
Feed query using config.ini file
Using can use the config.ini file you created using --save_query, you re-run the query. To do so, you will give --config flag the absolute path of the saved_config.ini file.
pygetpapers --config "C:\Users\shweata\lantana_query_config\saved_config.ini"
Querying using a term list
--terms flag
If your query is complex with multiple ORs, you can use --terms feature. To do so, you will:

Create a .txt file with list of terms separated by commas or an ami-dictionary (Click here to learn how to create dictionaries).
Give the --terms flag the absolute path of the .txt file or ami-dictionary (XML)

-q is optional.The terms would be OR'ed with each other ANDed with the query, if given.
INPUT:
pygetpapers -q "essential oil" --terms C:\Users\shweata\essential_oil_terms.txt -k 10 -o "terms_test_essential_oil" -x

OUTPUT:
C:\Users\shweata>pygetpapers -q "essential oil" --terms C:\Users\shweata\essential_oil_terms.txt -k 10 -o "terms_test_essential_oil"
INFO: Final query is (essential oil AND (antioxidant OR antibacterial OR antifungal OR antiseptic OR antitrichomonal agent))
INFO: Total Hits are 43397
0it [00:00, ?it/s]WARNING: Author list not found for paper 9
1it [00:00, 1064.00it/s]
100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [00:19<00:00, 1.99s/it]

You can also use this feature to download papers by using the PMC Ids. You can feed the .txt file with PMC ids comman-separated. Make sure to give a large enough hit number to download all the papers specified in the text file.
Example text file can be found, here
INPUT:
pygetpapers --terms C:\Users\shweata\PMCID_pygetpapers_text.txt -k 100 -o "PMCID_test"

OUTPUT:
INFO: Final query is (PMC6856665 OR PMC6877543 OR PMC6927906 OR PMC7008714 OR PMC7040181 OR PMC7080866 OR PMC7082878 OR PMC7096589 OR PMC7111464 OR PMC7142259 OR PMC7158757 OR PMC7174509 OR PMC7193700 OR PMC7198785 OR PMC7201129 OR PMC7203781 OR PMC7206980 OR PMC7214627 OR PMC7214803 OR PMC7220991
)
INFO: Total Hits are 20
WARNING: Could not find more papers
1it [00:00, 505.46it/s]
100%|█████████████████████████████████████████████| 20/20 [00:32<00:00, 1.61s/it]

--notterms
Excluded papers that have certain keywords might also be of interest for you. For example, if you want papers on essential oil which doesn't mention antibacterial , antiseptic or antimicrobial, you can run either create a dictionary or a text file with these terms (comma-separated), specify its absolute path to --notterms flag.
INPUT:
pygetpapers -q "essential oil" -k 10 -o essential_oil_not_terms_test --notterms C:\Users\shweata\not_terms_test.txt

OUTPUT:
INFO: Final query is (essential oil AND NOT (antimicrobial OR antiseptic OR antibacterial))
INFO: Total Hits are 165557
1it [00:00, ?it/s]
100%|█| 10/10 [00:49<00:00, 4.95s/

The number of papers are reduced by a some proportion. For comparision, "essential oil" query gives us 193922 hits.
C:\Users\shweata>pygetpapers -q "essential oil" -n
INFO: Final query is essential oil
INFO: Total number of hits for the query are 193922

Using --terms with dictionaries
We will take the same example as before.

Assuming you have ami3 installed, you can create ami-dictionaries

Start off by listing the terms in a .txt file

antimicrobial
antiseptic
antibacterial


Run the following command from the directory in which the text file exists

amidict -v --dictionary pygetpapers_terms --directory pygetpapers_terms --input pygetpapers_terms.txt create --informat list --outformats xml



That's it! You've now created a simple ami-dictionary. There are ways of creating dictionaries from Wikidata as well. You can learn more about how to do that in this Wiki page.

You can also use standard dictionaries that are available.
we, then, pass the absolute path of the dictionary to --terms flag.

INPUT:
pygetpapers -q "essential oil" --terms C:\Users\shweata\pygetpapers_terms\pygetpapers_terms.xml -k 10 -o pygetpapers_dictionary_test -x

OUTPUT:
INFO: Final query is (essential oil AND (antibacterial OR antimicrobial OR antiseptic))
INFO: Total Hits are 28365
0it [00:00, ?it/s]WARNING: Keywords not found for paper 5
WARNING: Keywords not found for paper 7
1it [00:00, ?it/s]
INFO: Saving XML files to C:\Users\shweata\pygetpapers_dictionary_test\*\fulltext.xml
100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [00:36<00:00, 3.67s/it]

Log levels
You can specify the log level using the -l flag. The default as you've already seen so far is info.
INPUT:
pygetpapers -q "lantana" -k 10 -o lantana_test_10_2 --loglevel debug -x

Log file
You can also choose to write the log to a .txt file in your HOME directory, while simultaneously printing it out.
INPUT:
pygetpapers -q "lantana" -k 10 -o lantana_test_10_4 --loglevel debug -x --logfile test_log.txt

Here is the log file.
Crossref
You can query crossref api for the metadata only.
Sample query

The metadata formats flags are applicable as described in the EPMC tutorial
--terms and -q are also applicable to crossref
INPUT:

pygetpapers --api crossref -q "essential oil" --terms C:\Users\shweata\essential_oil_terms.txt -k 10 -o "terms_test_essential_oil_crossref_3" -x -c --makehtml

OUTPUT:
INFO: Final query is (essential oil AND (antioxidant OR antibacterial OR antifungal OR antiseptic OR antitrichomonal agent))
INFO: Making request to crossref
INFO: Got request result from crossref
INFO: Making csv files for metadata at C:\Users\shweata\terms_test_essential_oil_crossref_3
100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [00:00<00:00, 185.52it/s]
INFO: Making html files for metadata at C:\Users\shweata\terms_test_essential_oil_crossref_3
100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [00:00<00:00, 87.98it/s]
INFO: Making xml files for metadata at C:\Users\shweata\terms_test_essential_oil_crossref_3
100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [00:00<00:00, 366.97it/s]
INFO: Wrote metadata file for the query
INFO: Writing metadata file for the papers at C:\Users\shweata\terms_test_essential_oil_crossref_3
100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [00:00<00:00, 996.82it/s]

We have 10 folders in the CProject directory.
C:\Users\shweata>cd terms_test_essential_oil_crossref_3

C:\Users\shweata\terms_test_essential_oil_crossref_3>tree
Folder PATH listing for volume Windows-SSD
Volume serial number is D88A-559A
C:.
├───10.1016_j.bcab.2021.101913
├───10.1055_s-0029-1234896
├───10.1080_0972060x.2016.1231597
├───10.1080_10412905.1989.9697767
├───10.1111_j.1745-4565.2012.00378.x
├───10.17795_bhs-24733
├───10.23880_oajmms-16000131
├───10.34302_crpjfst_2019.11.2.8
├───10.5220_0008855200960099
└───10.5220_0009957801190122

--update
--update works the same as in EPMC. You can use this flag to increase the number of papers in a given CProject.
INPUT
pygetpapers --api crossref -q "essential oil" --terms C:\Users\shweata\essential_oil_terms.txt -k 5 -o "terms_test_essential_oil_crossref_3" -x -c --makehtml --update

OUTPUT:
INFO: Final query is (essential oil AND (antioxidant OR antibacterial OR antifungal OR antiseptic OR antitrichomonal agent))
INFO: Please ensure that you are providing the same --api as the one in the corpus or you may get errors
INFO: Reading old json metadata file
INFO: Making request to crossref
INFO: Got request result from crossref
INFO: Wrote metadata file for the query
INFO: Writing metadata file for the papers at C:\Users\shweata\terms_test_essential_oil_crossref_3
100%|██████████████████████████████████████████████| 5/5 [00:00<00:00, 346.84it/s]

The CProject after updating:
C:.
├───10.1002_mbo3.459
├───10.1016_j.bcab.2021.101913
├───10.1055_s-0029-1234896
├───10.1080_0972060x.2014.895156
├───10.1080_0972060x.2016.1231597
├───10.1080_0972060x.2017.1345329
├───10.1080_10412905.1989.9697767
├───10.1080_10412905.2021.1941338
├───10.1111_j.1745-4565.2012.00378.x
├───10.15406_oajs.2019.03.00121
├───10.17795_bhs-24733
├───10.23880_oajmms-16000131
├───10.34302_crpjfst_2019.11.2.8
├───10.5220_0008855200960099
└───10.5220_0009957801190122

We started off with 10 paper folders, and increased the number to 15.
Filter
arxiv
pygetpapers allows you to query arxiv for full text PDF and metadata in all supported formats.
Sample query
INPUT
pygetpapers --api arxiv -k 10 -o arxiv_test_3 -q "artificial intelligence" -x -p --makehtml -c

OUTPUT

INFO: Final query is artificial intelligence
INFO: Making request to Arxiv through pygetpapers
INFO: Got request result from Arxiv through pygetpapers
INFO: Requesting 10 results at offset 0
INFO: Requesting page of results
INFO: Got first page; 10 of 10 results available
INFO: Downloading Pdfs for papers
100%|█████████████████████████████████████████████| 10/10 [01:02<00:00, 6.27s/it]
INFO: Making csv files for metadata at C:\Users\shweata\arxiv_test_3
100%|████████████████████████████████████████████| 10/10 [00:00<00:00, 187.31it/s]
INFO: Making html files for metadata at C:\Users\shweata\arxiv_test_3
100%|████████████████████████████████████████████| 10/10 [00:00<00:00, 161.87it/s]
INFO: Making xml files for metadata at C:\Users\shweata\arxiv_test_3
100%|█████████████████████████████████████████████████████| 10/10 [00:00<?, ?it/s]
100%|███████████████████████████████████████████| 10/10 [00:00<00:00, 1111.22it/s]

Note: --update isn't supported for arxiv
Biorxiv and Medrxiv
You can query biorxiv and medrxiv for fulltext and metadata (in all supported formats). However, passing a query string using -q flag isn't supported for both the Repositories. You can only provide a date range.
Sample Query - biorxiv
INPUT:
pygetpapers --api biorxiv -k 10 -x --startdate 2021-01-01 -o biorxiv_test_20210831

OUTPUT:
WARNING: Currently biorxiv api is malfunctioning and returning wrong DOIs
INFO: Making Request to rxiv
INFO: Making xml for paper
100%|██████████████████████████████████████████████████████████████████████████████████| 10/10 [00:23<00:00, 2.34s/it]
INFO: Wrote metadata file for the query
INFO: Writing metadata file for the papers at C:\Users\shweata\biorxiv_test_20210831
100%|█████████████████████████████████████████████████████████████████████████████████| 10/10 [00:00<00:00, 684.72it/s]

--update command
INPUT
pygetpapers --api biorxiv -k 10 -x --startdate 2021-01-01 -o biorxiv_test_20210831 --update

OUTPUT
WARNING: Currently biorxiv api is malfunctioning and returning wrong DOIs
INFO: Please ensure that you are providing the same --api as the one in the corpus or you may get errors
INFO: Reading old json metadata file
INFO: Making Request to rxiv
INFO: Making xml for paper
100%|██████████████████████████████████████████████████████████████████████████████████| 10/10 [00:22<00:00, 2.23s/it]
INFO: Wrote metadata file for the query
INFO: Writing metadata file for the papers at C:\Users\shweata\biorxiv_test_20210831
100%|█████████████████████████████████████████████████████████████████████████████████| 10/10 [00:00<00:00, 492.39it/s]

The CProject now has 20 papers, in total after updating.
├───10.1101_008326
├───10.1101_010553
├───10.1101_035972
├───10.1101_046052
├───10.1101_060012
├───10.1101_067736
├───10.1101_086710
├───10.1101_092205
├───10.1101_092619
├───10.1101_093237
├───10.1101_121061
├───10.1101_135749
├───10.1101_145664
├───10.1101_145896
├───10.1101_165845
├───10.1101_180273
├───10.1101_181198
├───10.1101_191858
├───10.1101_194266
└───10.1101_196105

The working of medarxiv is same as biorxiv
rxivist
Lets you specify a queries string to both biorxiv and medarxiv. The results you get would be a mixture of papers from both repository since rxivist doesn't differentiate.
Another caveat here is that you can only retrieve metadata from rxivist.
INPUT:
pygetpapers --api rxivist -q "biomedicine" -k 10 -c -x -o "biomedicine_rxivist" --makehtml -p

OUTPUT:
WARNING: Pdf is not supported for this api
INFO: Final query is biomedicine
INFO: Making Request to rxivist
INFO: Making csv files for metadata at C:\Users\shweata\biomedicine_rxivist
100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [00:00<00:00, 125.54it/s]
INFO: Making html files for metadata at C:\Users\shweata\biomedicine_rxivist
100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [00:00<00:00, 124.71it/s]
INFO: Making xml files for metadata at C:\Users\shweata\biomedicine_rxivist
100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [00:00<00:00, 633.38it/s]
INFO: Wrote metadata file for the query
INFO: Writing metadata file for the papers at C:\Users\shweata\biomedicine_rxivist
100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [00:00<00:00, 751.09it/s]

Query hits only
Like any other repositories under pygetpapers, you can use the -n flag to get only the hit number
INPUT:
C:\Users\shweata>pygetpapers --api rxivist -q "biomedical sciences" -n

OUTPUT:
INFO: Final query is biomedical sciences
INFO: Making Request to rxivist
INFO: Total number of hits for the query are 62

Update
--update works the same as many other repositories. Make sure to provide rxvist as api.
INPUT:
pygetpapers --api rxivist -q "biomedical sciences" -k 20 -c -x -o "biomedicine_rxivist" --update

OUPUT:
INFO: Final query is biomedical sciences
INFO: Please ensure that you are providing the same --api as the one in the corpus or you may get errors
INFO: Reading old json metadata file
INFO: Making Request to rxivist
INFO: Making csv files for metadata at C:\Users\shweata\biomedicine_rxivist
100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [00:00<00:00, 203.69it/s]
INFO: Making xml files for metadata at C:\Users\shweata\biomedicine_rxivist
100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [00:00<00:00, 1059.17it/s]
INFO: Wrote metadata file for the query
INFO: Writing metadata file for the papers at C:\Users\shweata\biomedicine_rxivist
100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10/10 [00:00<00:00, 1077.12it/s]

Run pygetpapers within the module
def run_command(output=False, query=False, save_query=False, xml=False, pdf=False, supp=False, zip=False, references=False, noexecute=False, citations=False, limit=100, restart=False, update=False, onlyquery=False, makecsv=False, makehtml=False, synonym=False, startdate=False, enddate=False, terms=False, notterms=False, api='europe_pmc', filter=None, loglevel='info', logfile=False, version=False)

Here's an example script to download 50 papers from EPMC on 'lantana camara'.
from pygetpapers import Pygetpapers
pygetpapers_call=Pygetpapers()
pygetpapers_call.run_command(query='lantana camara',limit=-50 ,output= lantana_camara, xml=True)

Test pygetpapers
To run automated testing on pygetpapers, do the following:

Install pygetpapers
Clone into pygetpapers repository
Install pytest
Run the command, pytest

Contributions
https://github.com/petermr/pygetpapers/blob/main/resources/CONTRIBUTING.md
Feature Requests
To request features, please put them in issues
Legal Implications
If you usepygetpapers, you should be careful to understand the law as it applies to their content mining, as they assume full responsibility for their actions when using the software.
Countries with copyright exceptions for content mining:

UK
Japan

Countries with proposed copyright exceptions:

Ireland
EU countries

Countries with permissive interpretations of 'fair use' that might allow content mining:

Israel
USA
Canada

General summaries and guides:

"The legal framework of text and data mining (TDM)", carried out for the European Commission in March 2014 (PDF)
"Standardisation in the area of innovation and technological development, notably in the field of Text and Data Mining", carried out for the European Commission in 2014 (PDF)