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Add notes for 2023-03-18

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Alan Orth 2023-03-18 17:42:40 +03:00
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@ -257,4 +257,146 @@ $ ./ilri/resolve_orcids.py -i /tmp/2023-03-14-orcids.txt -o /tmp/2023-03-14-orci
$ ./ilri/update_orcids.py -i /tmp/2023-03-14-orcids-names.txt -db dspace -u dspace -p 'fuuu' -m 247
```
## 2023-03-15
- Jawoo was asking about possibilities to harvest PDFs from CGSpace for some kind of AI chatbot integration
- I see we have 45,000 PDFs (format ID 2)
```console
localhost/dspacetest= ☘ SELECT COUNT(*) FROM bitstream WHERE NOT deleted AND bitstream_format_id=2;
count
───────
45281
(1 row)
```
- Rework some of my Python scripts to use a common `db_connect` function from util
- I reworked my `post_bitstreams.py` script to be able to overwrite bitstreams if requested
- The use case is to upload thumbnails for all the journal articles where we have these horrible pixelated journal covers
- I replaced JPEG thumbnails for ~896 ILRI publications by exporting a list of DOIs from the 10568/3 collection that were CC-BY, getting their PDFs from Sci-Hub, and then posting them with my new script
## 2023-03-16
- Continue working on the ILRI publication thumbnails
- There were about sixty-four that had existing PNG "journal cover" thumbnails that didn't get replaced because I only overwrote the JPEG ones yesterday
- Now I generated a list of those bitstream UUIDs and deleted them with a shell script via the REST API
- I made a [pull request on DSpace 7 to update the bitstream format registry for PNG, WebP, and AVIF](https://github.com/DSpace/DSpace/pull/8722)
- Export CGSpace to perform mappings to Initiatives collections
- I also used this export to find CC-BY items with DOIs that had JPEGs or PNGs in their provenance, meaning that the submitter likely submitted a low-quality "journal cover" for the item
- I found about 330 of them and got most of their PDFs from Sci-Hub and replaced the crappy thumbnails with real ones where Sci-Hub had them (~245)
- In related news, I realized you can get an [API key from Elsevier and download the PDFs from their API](https://stackoverflow.com/questions/59202176/python-download-papers-from-sciencedirect-by-doi-with-requests):
```python
import requests
api_key = 'fuuuuuuuuu'
doi = "10.1016/j.foodqual.2021.104362"
request_url = f'https://api.elsevier.com/content/article/doi:{doi}'
headers = {
'X-ELS-APIKEY': api_key,
'Accept': 'application/pdf'
}
with requests.get(request_url, stream=True, headers=headers) as r:
if r.status_code == 200:
with open("article.pdf", "wb") as f:
for chunk in r.iter_content(chunk_size=1024*1024):
f.write(chunk)
```
- The question is, how do we know if a DOI is Elsevier or not...
- CGIAR Repositories Working Group meeting
- We discussed controlled vocabularies for funders
- I suggested checking our combined lists against Crossref and ROR
- Export a list of donors from `cg.contributor.donor` on CGSpace:
```console
localhost/dspacetest= ☘ \COPY (SELECT DISTINCT(text_value) FROM metadatavalue WHERE dspace_object_id IN (SELECT uuid FROM item) AND metadata_field_id=248) to /tmp/2023-03-16-donors.txt;
COPY 1521
```
- Then resolve them against Crossref's funders API:
```console
$ ./ilri/crossref_funders_lookup.py -e fuuuu@cgiar.org -i /tmp/2023-03-16-donors.txt -o ~/Downloads/2023-03-16-cgspace-crossref-funders-results.csv -d
$ csvgrep -c matched -m true ~/Downloads/2023-03-16-cgspace-crossref-funders-results.csv | wc -l
472
$ sed 1d ~/Downloads/2023-03-16-cgspace-crossref-funders-results.csv | wc -l
1521
```
- That's a 31% hit rate, but I see some simple things like "Bill and Melinda Gates Foundation" instead of "Bill & Melinda Gates Foundation"
## 2023-03-17
- I did the same lookup of CGSpace donors on ROR's 2022-12-01 data dump:
```console
$ ./ilri/ror_lookup.py -i /tmp/2023-03-16-donors.txt -o ~/Downloads/2023-03-16-cgspace-ror-funders-results.csv -r v1.15-2022-12-01-ror-data.json
$ csvgrep -c matched -m true ~/Downloads/2023-03-16-cgspace-ror-funders-results.csv | wc -l
407
$ sed 1d ~/Downloads/2023-03-16-cgspace-ror-funders-results.csv | wc -l
1521
```
- That's a 26.7% hit rate
- As for the number of funders in each dataset
- Crossref has about 34,000
- ROR has 15,000 if "FundRef" data is a proxy for that:
```console
$ grep -c -rsI FundRef v1.15-2022-12-01-ror-data.json
15162
```
- On a related note, I remembered that DOI.org has a list of DOI prefixes and publishers: https://doi.crossref.org/getPrefixPublisher
- In Python I can look up publishers by prefix easily, here with a nested list comprehension:
```console
In [10]: [publisher for publisher in publishers if '10.3390' in publisher['prefixes']]
Out[10]:
[{'prefixes': ['10.1989', '10.32545', '10.20944', '10.3390', '10.35995'],
'name': 'MDPI AG',
'memberId': 1968}]
```
- And in OpenRefine, if I create a new column based on the DOI using Jython:
```python
import json
with open("/home/aorth/src/git/DSpace/publisher-doi-prefixes.json", "rb") as f:
publishers = json.load(f)
doi_prefix = value.split("/")[3]
publisher = [publisher for publisher in publishers if doi_prefix in publisher['prefixes']]
return publisher[0]['name']
```
- ... though this is very slow and hung OpenRefine when I tried it
- I added the ability to overwrite multiple bitstream formats at once in `post_bitstreams.py`
```console
$ ./ilri/post_bitstreams.py -i test.csv -u https://dspacetest.cgiar.org/rest -e fuuu@example.com -p 'fffnjnjn' -d -s 2B40C7C4E34CEFCF5AFAE4B75A8C52E2 --overwrite JPEG --overwrite PNG -n
Session valid: 2B40C7C4E34CEFCF5AFAE4B75A8C52E2
Opened test.csv
384142cb-58b9-4e64-bcdc-0a8cc34888b3: checking for existing bitstreams in THUMBNAIL bundle
> (DRY RUN) Deleting bitstream: IFPRI Malawi_Maize Market Report_February_202_anonymous.pdf.jpg (16883cb0-1fc8-4786-a04f-32132e0617d4)
> (DRY RUN) Deleting bitstream: AgroEcol_Newsletter_2.png (7e9cd434-45a6-4d55-8d56-4efa89d73813)
> (DRY RUN) Uploading file: 10568-129666.pdf.jpg
```
- I learned how to use Python's built-in `logging` module and it simplifies all my debug and info printing
- I re-factored a few scripts to use the new logging
## 2023-03-18
- I applied changes for publishers on 16,000 items in batches of 5,000
- While working on my `post_bitstreams.py` script I realized the Tomcat Crawler Session Manager valve that groups bot user agents into sessions is causing my login to fail the first time, every time
- I've disabled it for now and will check the Munin session graphs after some time to see if it makes a difference
- In any case I have much better spider user agent lists in DSpace now than I did years ago when I started using the Crawler Session Manager valve
<!-- vim: set sw=2 ts=2: -->

159
docs/2023-03/index.html
View File

@ -16,7 +16,7 @@ I finally got through with porting the input form from DSpace 6 to DSpace 7
<meta property="og:type" content="article" />
<meta property="og:url" content="https://alanorth.github.io/cgspace-notes/2023-03/" />
<meta property="article:published_time" content="2023-03-01T07:58:36+03:00" />
<meta property="article:modified_time" content="2023-03-13T21:22:25+03:00" />
<meta property="article:modified_time" content="2023-03-15T08:03:48+03:00" />
@ -38,9 +38,9 @@ I finally got through with porting the input form from DSpace 6 to DSpace 7
"@type": "BlogPosting",
"headline": "March, 2023",
"url": "https://alanorth.github.io/cgspace-notes/2023-03/",
"wordCount": "1984",
"wordCount": "2804",
"datePublished": "2023-03-01T07:58:36+03:00",
"dateModified": "2023-03-13T21:22:25+03:00",
"dateModified": "2023-03-15T08:03:48+03:00",
"author": {
"@type": "Person",
"name": "Alan Orth"
@ -401,7 +401,158 @@ pd.options.mode.nullable_dtypes = True
<li>Then update them in the database:</li>
</ul>
<div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-console" data-lang="console"><span style="display:flex;"><span>$ ./ilri/update_orcids.py -i /tmp/2023-03-14-orcids-names.txt -db dspace -u dspace -p <span style="color:#e6db74">&#39;fuuu&#39;</span> -m <span style="color:#ae81ff">247</span>
</span></span></code></pre></div><!-- raw HTML omitted -->
</span></span></code></pre></div><h2 id="2023-03-15">2023-03-15</h2>
<ul>
<li>Jawoo was asking about possibilities to harvest PDFs from CGSpace for some kind of AI chatbot integration
<ul>
<li>I see we have 45,000 PDFs (format ID 2)</li>
</ul>
</li>
</ul>
<div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-console" data-lang="console"><span style="display:flex;"><span>localhost/dspacetest= ☘ SELECT COUNT(*) FROM bitstream WHERE NOT deleted AND bitstream_format_id=2;
</span></span><span style="display:flex;"><span> count
</span></span><span style="display:flex;"><span>───────
</span></span><span style="display:flex;"><span> 45281
</span></span><span style="display:flex;"><span>(1 row)
</span></span></code></pre></div><ul>
<li>Rework some of my Python scripts to use a common <code>db_connect</code> function from util</li>
<li>I reworked my <code>post_bitstreams.py</code> script to be able to overwrite bitstreams if requested
<ul>
<li>The use case is to upload thumbnails for all the journal articles where we have these horrible pixelated journal covers</li>
<li>I replaced JPEG thumbnails for ~896 ILRI publications by exporting a list of DOIs from the 10568/3 collection that were CC-BY, getting their PDFs from Sci-Hub, and then posting them with my new script</li>
</ul>
</li>
</ul>
<h2 id="2023-03-16">2023-03-16</h2>
<ul>
<li>Continue working on the ILRI publication thumbnails
<ul>
<li>There were about sixty-four that had existing PNG &ldquo;journal cover&rdquo; thumbnails that didn&rsquo;t get replaced because I only overwrote the JPEG ones yesterday</li>
<li>Now I generated a list of those bitstream UUIDs and deleted them with a shell script via the REST API</li>
</ul>
</li>
<li>I made a <a href="https://github.com/DSpace/DSpace/pull/8722">pull request on DSpace 7 to update the bitstream format registry for PNG, WebP, and AVIF</a></li>
<li>Export CGSpace to perform mappings to Initiatives collections</li>
<li>I also used this export to find CC-BY items with DOIs that had JPEGs or PNGs in their provenance, meaning that the submitter likely submitted a low-quality &ldquo;journal cover&rdquo; for the item
<ul>
<li>I found about 330 of them and got most of their PDFs from Sci-Hub and replaced the crappy thumbnails with real ones where Sci-Hub had them (~245)</li>
</ul>
</li>
<li>In related news, I realized you can get an <a href="https://stackoverflow.com/questions/59202176/python-download-papers-from-sciencedirect-by-doi-with-requests">API key from Elsevier and download the PDFs from their API</a>:</li>
</ul>
<div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-python" data-lang="python"><span style="display:flex;"><span><span style="color:#f92672">import</span> requests
</span></span><span style="display:flex;"><span>
</span></span><span style="display:flex;"><span>api_key <span style="color:#f92672">=</span> <span style="color:#e6db74">&#39;fuuuuuuuuu&#39;</span>
</span></span><span style="display:flex;"><span>doi <span style="color:#f92672">=</span> <span style="color:#e6db74">&#34;10.1016/j.foodqual.2021.104362&#34;</span>
</span></span><span style="display:flex;"><span>request_url <span style="color:#f92672">=</span> <span style="color:#e6db74">f</span><span style="color:#e6db74">&#39;https://api.elsevier.com/content/article/doi:</span><span style="color:#e6db74">{</span>doi<span style="color:#e6db74">}</span><span style="color:#e6db74">&#39;</span>
</span></span><span style="display:flex;"><span>
</span></span><span style="display:flex;"><span>headers <span style="color:#f92672">=</span> {
</span></span><span style="display:flex;"><span> <span style="color:#e6db74">&#39;X-ELS-APIKEY&#39;</span>: api_key,
</span></span><span style="display:flex;"><span> <span style="color:#e6db74">&#39;Accept&#39;</span>: <span style="color:#e6db74">&#39;application/pdf&#39;</span>
</span></span><span style="display:flex;"><span>}
</span></span><span style="display:flex;"><span>
</span></span><span style="display:flex;"><span><span style="color:#66d9ef">with</span> requests<span style="color:#f92672">.</span>get(request_url, stream<span style="color:#f92672">=</span><span style="color:#66d9ef">True</span>, headers<span style="color:#f92672">=</span>headers) <span style="color:#66d9ef">as</span> r:
</span></span><span style="display:flex;"><span> <span style="color:#66d9ef">if</span> r<span style="color:#f92672">.</span>status_code <span style="color:#f92672">==</span> <span style="color:#ae81ff">200</span>:
</span></span><span style="display:flex;"><span> <span style="color:#66d9ef">with</span> open(<span style="color:#e6db74">&#34;article.pdf&#34;</span>, <span style="color:#e6db74">&#34;wb&#34;</span>) <span style="color:#66d9ef">as</span> f:
</span></span><span style="display:flex;"><span> <span style="color:#66d9ef">for</span> chunk <span style="color:#f92672">in</span> r<span style="color:#f92672">.</span>iter_content(chunk_size<span style="color:#f92672">=</span><span style="color:#ae81ff">1024</span><span style="color:#f92672">*</span><span style="color:#ae81ff">1024</span>):
</span></span><span style="display:flex;"><span> f<span style="color:#f92672">.</span>write(chunk)
</span></span></code></pre></div><ul>
<li>The question is, how do we know if a DOI is Elsevier or not&hellip;</li>
<li>CGIAR Repositories Working Group meeting
<ul>
<li>We discussed controlled vocabularies for funders</li>
<li>I suggested checking our combined lists against Crossref and ROR</li>
</ul>
</li>
<li>Export a list of donors from <code>cg.contributor.donor</code> on CGSpace:</li>
</ul>
<div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-console" data-lang="console"><span style="display:flex;"><span>localhost/dspacetest= ☘ \COPY (SELECT DISTINCT(text_value) FROM metadatavalue WHERE dspace_object_id IN (SELECT uuid FROM item) AND metadata_field_id=248) to /tmp/2023-03-16-donors.txt;
</span></span><span style="display:flex;"><span>COPY 1521
</span></span></code></pre></div><ul>
<li>Then resolve them against Crossref&rsquo;s funders API:</li>
</ul>
<div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-console" data-lang="console"><span style="display:flex;"><span>$ ./ilri/crossref_funders_lookup.py -e fuuuu@cgiar.org -i /tmp/2023-03-16-donors.txt -o ~/Downloads/2023-03-16-cgspace-crossref-funders-results.csv -d
</span></span><span style="display:flex;"><span>$ csvgrep -c matched -m true ~/Downloads/2023-03-16-cgspace-crossref-funders-results.csv | wc -l
</span></span><span style="display:flex;"><span>472
</span></span><span style="display:flex;"><span>$ sed 1d ~/Downloads/2023-03-16-cgspace-crossref-funders-results.csv | wc -l
</span></span><span style="display:flex;"><span>1521
</span></span></code></pre></div><ul>
<li>That&rsquo;s a 31% hit rate, but I see some simple things like &ldquo;Bill and Melinda Gates Foundation&rdquo; instead of &ldquo;Bill &amp; Melinda Gates Foundation&rdquo;</li>
</ul>
<h2 id="2023-03-17">2023-03-17</h2>
<ul>
<li>I did the same lookup of CGSpace donors on ROR&rsquo;s 2022-12-01 data dump:</li>
</ul>
<div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-console" data-lang="console"><span style="display:flex;"><span>$ ./ilri/ror_lookup.py -i /tmp/2023-03-16-donors.txt -o ~/Downloads/2023-03-16-cgspace-ror-funders-results.csv -r v1.15-2022-12-01-ror-data.json
</span></span><span style="display:flex;"><span>$ csvgrep -c matched -m true ~/Downloads/2023-03-16-cgspace-ror-funders-results.csv | wc -l
</span></span><span style="display:flex;"><span>407
</span></span><span style="display:flex;"><span>$ sed 1d ~/Downloads/2023-03-16-cgspace-ror-funders-results.csv | wc -l
</span></span><span style="display:flex;"><span>1521
</span></span></code></pre></div><ul>
<li>That&rsquo;s a 26.7% hit rate</li>
<li>As for the number of funders in each dataset
<ul>
<li>Crossref has about 34,000</li>
<li>ROR has 15,000 if &ldquo;FundRef&rdquo; data is a proxy for that:</li>
</ul>
</li>
</ul>
<div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-console" data-lang="console"><span style="display:flex;"><span>$ grep -c -rsI FundRef v1.15-2022-12-01-ror-data.json
</span></span><span style="display:flex;"><span>15162
</span></span></code></pre></div><ul>
<li>On a related note, I remembered that DOI.org has a list of DOI prefixes and publishers: <a href="https://doi.crossref.org/getPrefixPublisher">https://doi.crossref.org/getPrefixPublisher</a>
<ul>
<li>In Python I can look up publishers by prefix easily, here with a nested list comprehension:</li>
</ul>
</li>
</ul>
<div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-console" data-lang="console"><span style="display:flex;"><span>In [10]: [publisher for publisher in publishers if &#39;10.3390&#39; in publisher[&#39;prefixes&#39;]]
</span></span><span style="display:flex;"><span>Out[10]:
</span></span><span style="display:flex;"><span>[{&#39;prefixes&#39;: [&#39;10.1989&#39;, &#39;10.32545&#39;, &#39;10.20944&#39;, &#39;10.3390&#39;, &#39;10.35995&#39;],
</span></span><span style="display:flex;"><span> &#39;name&#39;: &#39;MDPI AG&#39;,
</span></span><span style="display:flex;"><span> &#39;memberId&#39;: 1968}]
</span></span></code></pre></div><ul>
<li>And in OpenRefine, if I create a new column based on the DOI using Jython:</li>
</ul>
<div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-python" data-lang="python"><span style="display:flex;"><span><span style="color:#f92672">import</span> json
</span></span><span style="display:flex;"><span>
</span></span><span style="display:flex;"><span><span style="color:#66d9ef">with</span> open(<span style="color:#e6db74">&#34;/home/aorth/src/git/DSpace/publisher-doi-prefixes.json&#34;</span>, <span style="color:#e6db74">&#34;rb&#34;</span>) <span style="color:#66d9ef">as</span> f:
</span></span><span style="display:flex;"><span> publishers <span style="color:#f92672">=</span> json<span style="color:#f92672">.</span>load(f)
</span></span><span style="display:flex;"><span>
</span></span><span style="display:flex;"><span>doi_prefix <span style="color:#f92672">=</span> value<span style="color:#f92672">.</span>split(<span style="color:#e6db74">&#34;/&#34;</span>)[<span style="color:#ae81ff">3</span>]
</span></span><span style="display:flex;"><span>
</span></span><span style="display:flex;"><span>publisher <span style="color:#f92672">=</span> [publisher <span style="color:#66d9ef">for</span> publisher <span style="color:#f92672">in</span> publishers <span style="color:#66d9ef">if</span> doi_prefix <span style="color:#f92672">in</span> publisher[<span style="color:#e6db74">&#39;prefixes&#39;</span>]]
</span></span><span style="display:flex;"><span>
</span></span><span style="display:flex;"><span><span style="color:#66d9ef">return</span> publisher[<span style="color:#ae81ff">0</span>][<span style="color:#e6db74">&#39;name&#39;</span>]
</span></span></code></pre></div><ul>
<li>&hellip; though this is very slow and hung OpenRefine when I tried it</li>
<li>I added the ability to overwrite multiple bitstream formats at once in <code>post_bitstreams.py</code></li>
</ul>
<div class="highlight"><pre tabindex="0" style="color:#f8f8f2;background-color:#272822;-moz-tab-size:4;-o-tab-size:4;tab-size:4;"><code class="language-console" data-lang="console"><span style="display:flex;"><span>$ ./ilri/post_bitstreams.py -i test.csv -u https://dspacetest.cgiar.org/rest -e fuuu@example.com -p <span style="color:#e6db74">&#39;fffnjnjn&#39;</span> -d -s 2B40C7C4E34CEFCF5AFAE4B75A8C52E2 --overwrite JPEG --overwrite PNG -n
</span></span><span style="display:flex;"><span>Session valid: 2B40C7C4E34CEFCF5AFAE4B75A8C52E2
</span></span><span style="display:flex;"><span>Opened test.csv
</span></span><span style="display:flex;"><span>384142cb-58b9-4e64-bcdc-0a8cc34888b3: checking for existing bitstreams in THUMBNAIL bundle
</span></span><span style="display:flex;"><span>&gt; <span style="color:#f92672">(</span>DRY RUN<span style="color:#f92672">)</span> Deleting bitstream: IFPRI Malawi_Maize Market Report_February_202_anonymous.pdf.jpg <span style="color:#f92672">(</span>16883cb0-1fc8-4786-a04f-32132e0617d4<span style="color:#f92672">)</span>
</span></span><span style="display:flex;"><span>&gt; <span style="color:#f92672">(</span>DRY RUN<span style="color:#f92672">)</span> Deleting bitstream: AgroEcol_Newsletter_2.png <span style="color:#f92672">(</span>7e9cd434-45a6-4d55-8d56-4efa89d73813<span style="color:#f92672">)</span>
</span></span><span style="display:flex;"><span>&gt; <span style="color:#f92672">(</span>DRY RUN<span style="color:#f92672">)</span> Uploading file: 10568-129666.pdf.jpg
</span></span></code></pre></div><ul>
<li>I learned how to use Python&rsquo;s built-in <code>logging</code> module and it simplifies all my debug and info printing
<ul>
<li>I re-factored a few scripts to use the new logging</li>
</ul>
</li>
</ul>
<h2 id="2023-03-18">2023-03-18</h2>
<ul>
<li>I applied changes for publishers on 16,000 items in batches of 5,000</li>
<li>While working on my <code>post_bitstreams.py</code> script I realized the Tomcat Crawler Session Manager valve that groups bot user agents into sessions is causing my login to fail the first time, every time
<ul>
<li>I&rsquo;ve disabled it for now and will check the Munin session graphs after some time to see if it makes a difference</li>
<li>In any case I have much better spider user agent lists in DSpace now than I did years ago when I started using the Crawler Session Manager valve</li>
</ul>
</li>
</ul>
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