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scripts
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README.md

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Processing code and information related to OpenTED (Tenders Electronic Daily).

Data Processing Pipeline

Structured data is in a MongoDB at opented.org/opented

Unstructured cached HTML pages are also in the that DB in a collection called dumps (in future this data should probably go direct to s3!).

1. Get dumps onto s3

Get data out of mongodb.

mongoexport --host opented.org --db opented --username iacc --password gohack --collection dumps --csv --fields "zhtml,doc_id,timestamp" | head -n 5000 > cache/dumps.csv

Decompress the HTML

python scripts/extract.py

This will produce a whole bunch of files in cache/dumps

Upload the decompressed HTML to S3

s3cmd sync --acl-public cache/dumps/ s3://files.opented.org/scraped/

You will find the index of files at: http://files.opented.org.s3.amazonaws.com/scraped/index.json

2. Scraping content

Now it's time to scrape some content!

We've written a nodejs scraper. You will need to install the dependencies first:

npm install cheerio request

Then do:

node scripts/scrape.js

Data will be written to cache/dumps/{docid}/extracted.json

Wishlist

Extra fields to scrape:

  • VAT inclusion (string e.g. "Including VAT", "Excluding VAT", "Including 10% VAT", etc.)
  • Award criteria (string, often multi-line, outlining criteria for choosing this bidder)

We also need to cover the scenario of one contract having multiple winners.

This probably means we're aiming for three content tables in the end (possibly not with these names):

  • contracts (need a better name) - info about a specific
  • companies - info about a company
  • wins - the relation table, i.e. a record in this table has a contract_id and a company_id. Also we can add extra info here that applies to a contract–company relation, eg the proportion of the total contract fee won by this company.

UPDATE from Callum

I attempted to get the entire database by running mongoexport overnight (piping through pv so I could see the progress), and this morning it's only at 43%, after running for 12.5 hours. I think it's stuck, it doesn't seem to be moving.

I've cancelled this now in case it's DOSing the database. I could still run the Python decompression script on the dumps I've got and upload straight to S3 (could leave this running while I'm out today), but it might take ages. Let me know if you want me to try that, or something else - callum.locke at gmail.

About

Tenders Electronic Daily (TED) - OpenTED

opented.org/

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1 watching

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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Processing code and information related to OpenTED (Tenders Electronic Daily).
Data Processing Pipeline
Structured data is in a MongoDB at opented.org/opented
Unstructured cached HTML pages are also in the that DB in a collection called dumps (in future this data should probably go direct to s3!).
1. Get dumps onto s3
Get data out of mongodb.
mongoexport --host opented.org --db opented --username iacc --password gohack --collection dumps --csv --fields "zhtml,doc_id,timestamp" | head -n 5000 > cache/dumps.csv

Decompress the HTML
python scripts/extract.py

This will produce a whole bunch of files in cache/dumps
Upload the decompressed HTML to S3
s3cmd sync --acl-public cache/dumps/ s3://files.opented.org/scraped/

You will find the index of files at: http://files.opented.org.s3.amazonaws.com/scraped/index.json
2. Scraping content
Now it's time to scrape some content!
We've written a nodejs scraper. You will need to install the dependencies first:
npm install cheerio request

Then do:
node scripts/scrape.js

Data will be written to cache/dumps/{docid}/extracted.json
Wishlist
Extra fields to scrape:
  • VAT inclusion (string e.g. "Including VAT", "Excluding VAT", "Including 10% VAT", etc.)
  • Award criteria (string, often multi-line, outlining criteria for choosing this bidder)
We also need to cover the scenario of one contract having multiple winners.
This probably means we're aiming for three content tables in the end (possibly not with these names):
  • contracts (need a better name) - info about a specific
  • companies - info about a company
  • wins - the relation table, i.e. a record in this table has a contract_id and a company_id. Also we can add extra info here that applies to a contract–company relation, eg the proportion of the total contract fee won by this company.
UPDATE from Callum
I attempted to get the entire database by running mongoexport overnight (piping through pv so I could see the progress), and this morning it's only at 43%, after running for 12.5 hours. I think it's stuck, it doesn't seem to be moving.
I've cancelled this now in case it's DOSing the database. I could still run the Python decompression script on the dumps I've got and upload straight to S3 (could leave this running while I'm out today), but it might take ages. Let me know if you want me to try that, or something else - callum.locke at gmail.
About
Tenders Electronic Daily (TED) - OpenTED
opented.org/
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Processing code and information related to OpenTED (Tenders Electronic Daily).
Data Processing Pipeline
Structured data is in a MongoDB at opented.org/opented
Unstructured cached HTML pages are also in the that DB in a collection called dumps (in future this data should probably go direct to s3!).
1. Get dumps onto s3
Get data out of mongodb.
mongoexport --host opented.org --db opented --username iacc --password gohack --collection dumps --csv --fields "zhtml,doc_id,timestamp" | head -n 5000 > cache/dumps.csv

Decompress the HTML
python scripts/extract.py

This will produce a whole bunch of files in cache/dumps
Upload the decompressed HTML to S3
s3cmd sync --acl-public cache/dumps/ s3://files.opented.org/scraped/

You will find the index of files at: http://files.opented.org.s3.amazonaws.com/scraped/index.json
2. Scraping content
Now it's time to scrape some content!
We've written a nodejs scraper. You will need to install the dependencies first:
npm install cheerio request

Then do:
node scripts/scrape.js

Data will be written to cache/dumps/{docid}/extracted.json
Wishlist
Extra fields to scrape:
  • VAT inclusion (string e.g. "Including VAT", "Excluding VAT", "Including 10% VAT", etc.)
  • Award criteria (string, often multi-line, outlining criteria for choosing this bidder)
We also need to cover the scenario of one contract having multiple winners.
This probably means we're aiming for three content tables in the end (possibly not with these names):
  • contracts (need a better name) - info about a specific
  • companies - info about a company
  • wins - the relation table, i.e. a record in this table has a contract_id and a company_id. Also we can add extra info here that applies to a contract–company relation, eg the proportion of the total contract fee won by this company.
UPDATE from Callum
I attempted to get the entire database by running mongoexport overnight (piping through pv so I could see the progress), and this morning it's only at 43%, after running for 12.5 hours. I think it's stuck, it doesn't seem to be moving.
I've cancelled this now in case it's DOSing the database. I could still run the Python decompression script on the dumps I've got and upload straight to S3 (could leave this running while I'm out today), but it might take ages. Let me know if you want me to try that, or something else - callum.locke at gmail.
About
Tenders Electronic Daily (TED) - OpenTED
opented.org/
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
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Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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scripts
scripts
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README.md
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Processing code and information related to OpenTED (Tenders Electronic Daily).
Data Processing Pipeline
Structured data is in a MongoDB at opented.org/opented
Unstructured cached HTML pages are also in the that DB in a collection called dumps (in future this data should probably go direct to s3!).
1. Get dumps onto s3
Get data out of mongodb.
mongoexport --host opented.org --db opented --username iacc --password gohack --collection dumps --csv --fields "zhtml,doc_id,timestamp" | head -n 5000 > cache/dumps.csv

Decompress the HTML
python scripts/extract.py

This will produce a whole bunch of files in cache/dumps
Upload the decompressed HTML to S3
s3cmd sync --acl-public cache/dumps/ s3://files.opented.org/scraped/

You will find the index of files at: http://files.opented.org.s3.amazonaws.com/scraped/index.json
2. Scraping content
Now it's time to scrape some content!
We've written a nodejs scraper. You will need to install the dependencies first:
npm install cheerio request

Then do:
node scripts/scrape.js

Data will be written to cache/dumps/{docid}/extracted.json
Wishlist
Extra fields to scrape:
  • VAT inclusion (string e.g. "Including VAT", "Excluding VAT", "Including 10% VAT", etc.)
  • Award criteria (string, often multi-line, outlining criteria for choosing this bidder)
We also need to cover the scenario of one contract having multiple winners.
This probably means we're aiming for three content tables in the end (possibly not with these names):
  • contracts (need a better name) - info about a specific
  • companies - info about a company
  • wins - the relation table, i.e. a record in this table has a contract_id and a company_id. Also we can add extra info here that applies to a contract–company relation, eg the proportion of the total contract fee won by this company.
UPDATE from Callum
I attempted to get the entire database by running mongoexport overnight (piping through pv so I could see the progress), and this morning it's only at 43%, after running for 12.5 hours. I think it's stuck, it doesn't seem to be moving.
I've cancelled this now in case it's DOSing the database. I could still run the Python decompression script on the dumps I've got and upload straight to S3 (could leave this running while I'm out today), but it might take ages. Let me know if you want me to try that, or something else - callum.locke at gmail.
About
Tenders Electronic Daily (TED) - OpenTED
opented.org/
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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NameName
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scripts
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README.md
Repository files navigation
Processing code and information related to OpenTED (Tenders Electronic Daily).
Data Processing Pipeline
Structured data is in a MongoDB at opented.org/opented
Unstructured cached HTML pages are also in the that DB in a collection called dumps (in future this data should probably go direct to s3!).
1. Get dumps onto s3
Get data out of mongodb.
mongoexport --host opented.org --db opented --username iacc --password gohack --collection dumps --csv --fields "zhtml,doc_id,timestamp" | head -n 5000 > cache/dumps.csv

Decompress the HTML
python scripts/extract.py

This will produce a whole bunch of files in cache/dumps
Upload the decompressed HTML to S3
s3cmd sync --acl-public cache/dumps/ s3://files.opented.org/scraped/

You will find the index of files at: http://files.opented.org.s3.amazonaws.com/scraped/index.json
2. Scraping content
Now it's time to scrape some content!
We've written a nodejs scraper. You will need to install the dependencies first:
npm install cheerio request

Then do:
node scripts/scrape.js

Data will be written to cache/dumps/{docid}/extracted.json
Wishlist
Extra fields to scrape:
  • VAT inclusion (string e.g. "Including VAT", "Excluding VAT", "Including 10% VAT", etc.)
  • Award criteria (string, often multi-line, outlining criteria for choosing this bidder)
We also need to cover the scenario of one contract having multiple winners.
This probably means we're aiming for three content tables in the end (possibly not with these names):
  • contracts (need a better name) - info about a specific
  • companies - info about a company
  • wins - the relation table, i.e. a record in this table has a contract_id and a company_id. Also we can add extra info here that applies to a contract–company relation, eg the proportion of the total contract fee won by this company.
UPDATE from Callum
I attempted to get the entire database by running mongoexport overnight (piping through pv so I could see the progress), and this morning it's only at 43%, after running for 12.5 hours. I think it's stuck, it doesn't seem to be moving.
I've cancelled this now in case it's DOSing the database. I could still run the Python decompression script on the dumps I've got and upload straight to S3 (could leave this running while I'm out today), but it might take ages. Let me know if you want me to try that, or something else - callum.locke at gmail.
About
Tenders Electronic Daily (TED) - OpenTED
opented.org/
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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13 Commits
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NameName
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scripts
scripts
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.gitignore
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README.md
Repository files navigation
Processing code and information related to OpenTED (Tenders Electronic Daily).
Data Processing Pipeline
Structured data is in a MongoDB at opented.org/opented
Unstructured cached HTML pages are also in the that DB in a collection called dumps (in future this data should probably go direct to s3!).
1. Get dumps onto s3
Get data out of mongodb.
mongoexport --host opented.org --db opented --username iacc --password gohack --collection dumps --csv --fields "zhtml,doc_id,timestamp" | head -n 5000 > cache/dumps.csv

Decompress the HTML
python scripts/extract.py

This will produce a whole bunch of files in cache/dumps
Upload the decompressed HTML to S3
s3cmd sync --acl-public cache/dumps/ s3://files.opented.org/scraped/

You will find the index of files at: http://files.opented.org.s3.amazonaws.com/scraped/index.json
2. Scraping content
Now it's time to scrape some content!
We've written a nodejs scraper. You will need to install the dependencies first:
npm install cheerio request

Then do:
node scripts/scrape.js

Data will be written to cache/dumps/{docid}/extracted.json
Wishlist
Extra fields to scrape:
  • VAT inclusion (string e.g. "Including VAT", "Excluding VAT", "Including 10% VAT", etc.)
  • Award criteria (string, often multi-line, outlining criteria for choosing this bidder)
We also need to cover the scenario of one contract having multiple winners.
This probably means we're aiming for three content tables in the end (possibly not with these names):
  • contracts (need a better name) - info about a specific
  • companies - info about a company
  • wins - the relation table, i.e. a record in this table has a contract_id and a company_id. Also we can add extra info here that applies to a contract–company relation, eg the proportion of the total contract fee won by this company.
UPDATE from Callum
I attempted to get the entire database by running mongoexport overnight (piping through pv so I could see the progress), and this morning it's only at 43%, after running for 12.5 hours. I think it's stuck, it doesn't seem to be moving.
I've cancelled this now in case it's DOSing the database. I could still run the Python decompression script on the dumps I've got and upload straight to S3 (could leave this running while I'm out today), but it might take ages. Let me know if you want me to try that, or something else - callum.locke at gmail.
About
Tenders Electronic Daily (TED) - OpenTED
opented.org/
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
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Latest commit
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13 Commits
Folders and files
NameName
Last commit message
Last commit date
scripts
scripts
.gitignore
.gitignore
README.md
README.md
Repository files navigation
Processing code and information related to OpenTED (Tenders Electronic Daily).
Data Processing Pipeline
Structured data is in a MongoDB at opented.org/opented
Unstructured cached HTML pages are also in the that DB in a collection called dumps (in future this data should probably go direct to s3!).
1. Get dumps onto s3
Get data out of mongodb.
mongoexport --host opented.org --db opented --username iacc --password gohack --collection dumps --csv --fields "zhtml,doc_id,timestamp" | head -n 5000 > cache/dumps.csv

Decompress the HTML
python scripts/extract.py

This will produce a whole bunch of files in cache/dumps
Upload the decompressed HTML to S3
s3cmd sync --acl-public cache/dumps/ s3://files.opented.org/scraped/

You will find the index of files at: http://files.opented.org.s3.amazonaws.com/scraped/index.json
2. Scraping content
Now it's time to scrape some content!
We've written a nodejs scraper. You will need to install the dependencies first:
npm install cheerio request

Then do:
node scripts/scrape.js

Data will be written to cache/dumps/{docid}/extracted.json
Wishlist
Extra fields to scrape:
  • VAT inclusion (string e.g. "Including VAT", "Excluding VAT", "Including 10% VAT", etc.)
  • Award criteria (string, often multi-line, outlining criteria for choosing this bidder)
We also need to cover the scenario of one contract having multiple winners.
This probably means we're aiming for three content tables in the end (possibly not with these names):
  • contracts (need a better name) - info about a specific
  • companies - info about a company
  • wins - the relation table, i.e. a record in this table has a contract_id and a company_id. Also we can add extra info here that applies to a contract–company relation, eg the proportion of the total contract fee won by this company.
UPDATE from Callum
I attempted to get the entire database by running mongoexport overnight (piping through pv so I could see the progress), and this morning it's only at 43%, after running for 12.5 hours. I think it's stuck, it doesn't seem to be moving.
I've cancelled this now in case it's DOSing the database. I could still run the Python decompression script on the dumps I've got and upload straight to S3 (could leave this running while I'm out today), but it might take ages. Let me know if you want me to try that, or something else - callum.locke at gmail.
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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Processing code and information related to OpenTED (Tenders Electronic Daily).
Data Processing Pipeline
Structured data is in a MongoDB at opented.org/opented
Unstructured cached HTML pages are also in the that DB in a collection called dumps (in future this data should probably go direct to s3!).
1. Get dumps onto s3
Get data out of mongodb.
mongoexport --host opented.org --db opented --username iacc --password gohack --collection dumps --csv --fields "zhtml,doc_id,timestamp" | head -n 5000 > cache/dumps.csv

Decompress the HTML
python scripts/extract.py

This will produce a whole bunch of files in cache/dumps
Upload the decompressed HTML to S3
s3cmd sync --acl-public cache/dumps/ s3://files.opented.org/scraped/

You will find the index of files at: http://files.opented.org.s3.amazonaws.com/scraped/index.json
2. Scraping content
Now it's time to scrape some content!
We've written a nodejs scraper. You will need to install the dependencies first:
npm install cheerio request

Then do:
node scripts/scrape.js

Data will be written to cache/dumps/{docid}/extracted.json
Wishlist
Extra fields to scrape:
  • VAT inclusion (string e.g. "Including VAT", "Excluding VAT", "Including 10% VAT", etc.)
  • Award criteria (string, often multi-line, outlining criteria for choosing this bidder)
We also need to cover the scenario of one contract having multiple winners.
This probably means we're aiming for three content tables in the end (possibly not with these names):
  • contracts (need a better name) - info about a specific
  • companies - info about a company
  • wins - the relation table, i.e. a record in this table has a contract_id and a company_id. Also we can add extra info here that applies to a contract–company relation, eg the proportion of the total contract fee won by this company.
UPDATE from Callum
I attempted to get the entire database by running mongoexport overnight (piping through pv so I could see the progress), and this morning it's only at 43%, after running for 12.5 hours. I think it's stuck, it doesn't seem to be moving.
I've cancelled this now in case it's DOSing the database. I could still run the Python decompression script on the dumps I've got and upload straight to S3 (could leave this running while I'm out today), but it might take ages. Let me know if you want me to try that, or something else - callum.locke at gmail.
About
Tenders Electronic Daily (TED) - OpenTED
opented.org/
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
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Contributors