I'd like to write a script that gets the Wikipedia description section only. That is, when I say
/wiki bla bla bla
it will go to the Wikipedia page for bla bla bla, get the following, and return it to the chatroom:
"Bla Bla Bla" is the name of a song
made by Gigi D'Agostino. He described
this song as "a piece I wrote thinking
of all the people who talk and talk
without saying anything". The
prominent but nonsensical vocal
samples are taken from UK band
Stretch's song "Why Did You Do It"
How can I do this?
Here are a few different possible approaches; use whichever works for you. All my code examples below use requests for HTTP requests to the API; you can install requests with pip install requests if you have Pip. They also all use the Mediawiki API, and two use the query endpoint; follow those links if you want documentation.
1. Get a plain text representation of either the entire page or the page "extract" straight from the API with the extracts prop
Note that this approach only works on MediaWiki sites with the TextExtracts extension. This notably includes Wikipedia, but not some smaller Mediawiki sites like, say, http://www.wikia.com/
You want to hit a URL like
https://en.wikipedia.org/w/api.php?action=query&format=json&titles=Bla_Bla_Bla&prop=extracts&exintro&explaintext
Breaking that down, we've got the following parameters in there (documented at https://www.mediawiki.org/wiki/Extension:TextExtracts#query+extracts):
action=query, format=json, and title=Bla_Bla_Bla are all standard MediaWiki API parameters
prop=extracts makes us use the TextExtracts extension
exintro limits the response to content before the first section heading
explaintext makes the extract in the response be plain text instead of HTML
Then parse the JSON response and extract the extract:
>>> import requests
>>> response = requests.get(
... 'https://en.wikipedia.org/w/api.php',
... params={
... 'action': 'query',
... 'format': 'json',
... 'titles': 'Bla Bla Bla',
... 'prop': 'extracts',
... 'exintro': True,
... 'explaintext': True,
... }
... ).json()
>>> page = next(iter(response['query']['pages'].values()))
>>> print(page['extract'])
"Bla Bla Bla" is the title of a song written and recorded by Italian DJ Gigi D'Agostino. It was released in May 1999 as the third single from the album, L'Amour Toujours. It reached number 3 in Austria and number 15 in France. This song can also be heard in an added remixed mashup with L'Amour Toujours (I'll Fly With You) in its US radio version.
2. Get the full HTML of the page using the parse endpoint, parse it, and extract the first paragraph
MediaWiki has a parse endpoint that you can hit with a URL like https://en.wikipedia.org/w/api.php?action=parse&page=Bla_Bla_Bla to get the HTML of a page. You can then parse it with an HTML parser like lxml (install it first with pip install lxml) to extract the first paragraph.
For example:
>>> import requests
>>> from lxml import html
>>> response = requests.get(
... 'https://en.wikipedia.org/w/api.php',
... params={
... 'action': 'parse',
... 'page': 'Bla Bla Bla',
... 'format': 'json',
... }
... ).json()
>>> raw_html = response['parse']['text']['*']
>>> document = html.document_fromstring(raw_html)
>>> first_p = document.xpath('//p')[0]
>>> intro_text = first_p.text_content()
>>> print(intro_text)
"Bla Bla Bla" is the title of a song written and recorded by Italian DJ Gigi D'Agostino. It was released in May 1999 as the third single from the album, L'Amour Toujours. It reached number 3 in Austria and number 15 in France. This song can also be heard in an added remixed mashup with L'Amour Toujours (I'll Fly With You) in its US radio version.
3. Parse wikitext yourself
You can use the query API to get the page's wikitext, parse it using mwparserfromhell (install it first using pip install mwparserfromhell), then reduce it down to human-readable text using strip_code. strip_code doesn't work perfectly at the time of writing (as shown clearly in the example below) but will hopefully improve.
>>> import requests
>>> import mwparserfromhell
>>> response = requests.get(
... 'https://en.wikipedia.org/w/api.php',
... params={
... 'action': 'query',
... 'format': 'json',
... 'titles': 'Bla Bla Bla',
... 'prop': 'revisions',
... 'rvprop': 'content',
... }
... ).json()
>>> page = next(iter(response['query']['pages'].values()))
>>> wikicode = page['revisions'][0]['*']
>>> parsed_wikicode = mwparserfromhell.parse(wikicode)
>>> print(parsed_wikicode.strip_code())
{{dablink|For Ke$ha's song, see Blah Blah Blah (song). For other uses, see Blah (disambiguation)}}
"Bla Bla Bla" is the title of a song written and recorded by Italian DJ Gigi D'Agostino. It was released in May 1999 as the third single from the album, L'Amour Toujours. It reached number 3 in Austria and number 15 in France. This song can also be heard in an added remixed mashup with L'Amour Toujours (I'll Fly With You) in its US radio version.
Background and writing
He described this song as "a piece I wrote thinking of all the people who talk and talk without saying anything". The prominent but nonsensical vocal samples are taken from UK band Stretch's song "Why Did You Do It"''.
Music video
The song also featured a popular music video in the style of La Linea. The music video shows a man with a floating head and no arms walking toward what appears to be a shark that multiplies itself and can change direction. This style was also used in "The Riddle", another song by Gigi D'Agostino, originally from British singer Nik Kershaw.
Chart performance
Chart (1999-00)PeakpositionIreland (IRMA)Search for Irish peaks23
References
External links
Category:1999 singles
Category:Gigi D'Agostino songs
Category:1999 songs
Category:ZYX Music singles
Category:Songs written by Gigi D'Agostino
Use the MediaWiki API, which runs on Wikipedia. You will have to do some parsing of the data yourself.
For instance:
http://en.wikipedia.org/w/api.php?action=query&prop=revisions&rvprop=content&format=json&&titles=Bla%20Bla%20Bla
means
fetch (action=query) the content (rvprop=content) of the most recent revision of Main Page (title=Main%20Page) in JSON format (format=json).
You will probably want to search for the query and use the first result, to handle spelling errors and the like.
You can get wiki data in Text formats. If you need to access many title's informations, you can get all title's wiki data in a single call. Use pipe character ( | ) to separate each titles.
http://en.wikipedia.org/w/api.php?format=json&action=query&prop=extracts&exlimit=max&explaintext&exintro&titles=Yahoo|Google&redirects=
Here this api call return both Googles and Yahoos data.
explaintext => Return extracts as plain text instead of limited HTML.
exlimit = max (now its 20); Otherwise only one result will return.
exintro => Return only content before the first section. If you want full data, just remove this.
redirects= Resolve redirect issues.
You can fetch just the first section using the API:
http://en.wikipedia.org/w/api.php?action=query&prop=revisions&rvsection=0&titles=Bla%20Bla%20Bla&rvprop=content
This will give you raw wikitext, you'll have to deal with templates and markup.
Or you can fetch the whole page rendered into HTML which has its own pros and cons as far as parsing:
http://en.wikipedia.org/w/api.php?action=parse&prop=text&page=Bla_Bla_Bla
I can't see an easy way to get parsed HTML of the first section in a single call but you can do it with two calls by passing the wikitext you receive from the first URL back with text= in place of the page= in the second URL.
UPDATE
Sorry I neglected the "plain text" part of your question. Get the part of the article you want as HTML. It's much easier to strip HTML than to strip wikitext!
DBPedia is the perfect solution for this problem. Here: http://dbpedia.org/page/Metallica, look at the perfectly organised data using RDF. One can query for anything here at http://dbpedia.org/sparql using SPARQL, the query language for the RDF. There's always a way to find the pageID so as to get descriptive text but this should do for the most part.
There will be a learning curve for RDF and SPARQL for writing any useful code but this is the perfect solution.
For example, a query run for Metallica returns an HTML table with the abstract in several different languages:
<table class="sparql" border="1">
<tr>
<th>abstract</th>
</tr>
<tr>
<td><pre>"Metallica is an American heavy metal band formed..."#en</pre></td>
</tr>
<tr>
<td><pre>"Metallica es una banda de thrash metal estadounidense..."#es</pre></td>
...
SPARQL QUERY :
PREFIX dbpedia-owl: <http://dbpedia.org/ontology/>
PREFIX dbpprop: <http://dbpedia.org/property/>
PREFIX dbres: <http://dbpedia.org/resource/>
SELECT ?abstract WHERE {
dbres:Metallica dbpedia-owl:abstract ?abstract.
}
Change "Metallica" to any resource name (resource name as in wikipedia.org/resourcename) for queries pertaining to abstract.
Alternatively, you can try to load any of the text of wiki pages simply like this
https://bn.wikipedia.org/w/index.php?title=User:ShohagS&action=raw&ctype=text
where change bn to you your wiki language and User:ShohagS will be the page name. In your case use:
https://en.wikipedia.org/w/index.php?title=Bla_bla_bla&action=raw&ctype=text
in browsers, this will return a php formated text file.
You can use the wikipedia package of Python, and specifically the content attribute for the given page.
From the documentation:
>>> import wikipedia
>>> print wikipedia.summary("Wikipedia")
# Wikipedia (/ˌwɪkɨˈpiːdiə/ or /ˌwɪkiˈpiːdiə/ WIK-i-PEE-dee-ə) is a collaboratively edited, multilingual, free Internet encyclopedia supported by the non-profit Wikimedia Foundation...
>>> wikipedia.search("Barack")
# [u'Barak (given name)', u'Barack Obama', u'Barack (brandy)', u'Presidency of Barack Obama', u'Family of Barack Obama', u'First inauguration of Barack Obama', u'Barack Obama presidential campaign, 2008', u'Barack Obama, Sr.', u'Barack Obama citizenship conspiracy theories', u'Presidential transition of Barack Obama']
>>> ny = wikipedia.page("New York")
>>> ny.title
# u'New York'
>>> ny.url
# u'http://en.wikipedia.org/wiki/New_York'
>>> ny.content
# u'New York is a state in the Northeastern region of the United States. New York is the 27th-most exten'...
I think the better option is to use the extracts prop that provides you MediaWiki API. It returns you only some tags (b, i, h#, span, ul, li) and removes tables, infoboxes, references, etc.
http://en.wikipedia.org/w/api.php?action=query&prop=extracts&titles=Bla%20Bla%20Bla&format=xml
gives you something very simple:
<api><query><pages><page pageid="4456737" ns="0" title="Bla Bla Bla"><extract xml:space="preserve">
<p>"<b>Bla Bla Bla</b>" is the title of a song written and recorded by Italian DJ Gigi D'Agostino. It was released in May 1999 as the third single from the album, <i>L'Amour Toujours</i>. It reached number 3 in Austria and number 15 in France. This song can also be heard in an added remixed mashup with <i>L'Amour Toujours (I'll Fly With You)</i> in its US radio version.</p> <p></p> <h2><span id="Background_and_writing">Background and writing</span></h2> <p>He described this song as "a piece I wrote thinking of all the people who talk and talk without saying anything". The prominent but nonsensical vocal samples are taken from UK band Stretch's song <i>"Why Did You Do It"</i>.</p> <h2><span id="Music_video">Music video</span></h2> <p>The song also featured a popular music video in the style of La Linea. The music video shows a man with a floating head and no arms walking toward what appears to be a shark that multiplies itself and can change direction. This style was also used in "The Riddle", another song by Gigi D'Agostino, originally from British singer Nik Kershaw.</p> <h2><span id="Chart_performance">Chart performance</span></h2> <h2><span id="References">References</span></h2> <h2><span id="External_links">External links</span></h2> <ul><li>Full lyrics of this song at MetroLyrics</li> </ul>
</extract></page></pages></query></api>
You can then run it through a regular expression, in JavaScript would be something like this (maybe you have to do some minor modifications:
/^.*<\s*extract[^>]*\s*>\s*((?:[^<]*|<\s*\/?\s*[^>hH][^>]*\s*>)*).*<\s*(?:h|H).*$/.exec(data)
Which gives you (only paragrphs, bold and italic):
"Bla Bla Bla" is the title of a song written and recorded by Italian DJ Gigi D'Agostino. It was released in May 1999 as the third single from the album, L'Amour Toujours. It reached number 3 in Austria and number 15 in France. This song can also be heard in an added remixed mashup with L'Amour Toujours (I'll Fly With You) in its US radio version.
"...a script that gets the Wikipedia description section only..."
For your application you might what to look on the dumps, e.g.: http://dumps.wikimedia.org/enwiki/20120702/
The particular files you need are 'abstract' XML files, e.g., this small one (22.7MB):
http://dumps.wikimedia.org/enwiki/20120702/enwiki-20120702-abstract19.xml
The XML has a tag called 'abstract' which contain the first part of each article.
Otherwise wikipedia2text uses, e.g., w3m to download the page with templates expanded and formatted to text. From that you might be able to pick out the abstract via a regular expression.
You can try WikiExtractor: http://medialab.di.unipi.it/wiki/Wikipedia_Extractor
It's for Python 2.7 and 3.3+.
First check here.
There are a lot of invalid syntaxes in MediaWiki's text markup.
(Mistakes made by users...)
Only MediaWiki can parse this hellish text.
But still there are some alternatives to try in the link above.
Not perfect, but better than nothing!
You can try the BeautifulSoup HTML parsing library for python,but you'll have to write a simple parser.
There is also the opportunity to consume Wikipedia pages through a wrapper API like JSONpedia, it works both live (ask for the current JSON representation of a Wiki page) and storage based (query multiple pages previously ingested in Elasticsearch and MongoDB).
The output JSON also include plain rendered page text.
Related
So, I am trying to get "Amenities and More" portion of the Yelp page for a few restaurants. The issue is that I can get to the Amenities from the restaurant's yelp page that are displayed first. It however has "n more" button that when clicked gives more amenities. Using BeautifulSoup and selenium with the webpage url and using BeautifulSoup with requests gives exact same results and I am stuck as to how to open the whole Amenities before grabbing them in my code. Two pictures below show what happens before and after click of the button.
"Before clicking '5 More Attributes': The first pic shows 4 "div" within which lies "span" that I can get to using any of the above methods.
"After clicking '5 More Attributes': The second pic shows 9 "div" within which lies "span" that I am trying to get to.
Here is the code using selenium/beautifulsoup
import selenium
from selenium import webdriver
from bs4 import BeautifulSoup
URL ='https://www.yelp.com/biz/ziggis-coffee-longmont'
driver =
webdriver.Chrome(r"C:\Users\Fariha\AppData\Local\Programs\chromedriver_win32\chromedriver.exe")
driver.get(URL)
yelp_page_source_page1 = driver.page_source
soup = BeautifulSoup(yelp_page_source_page1,'html.parser')
spans = soup.find_all('span')
Result: There are 990 elements in "spans". I am only showing what is relevant for my question:
An alternative approach would be to extract the data directly from the JSON api on the site. This could be done without the overhead of selenium as follows:
from bs4 import BeautifulSoup
import requests
import json
session = requests.Session()
r = session.get('https://www.yelp.com/biz/ziggis-coffee-longmont')
#r = session.get('https://www.yelp.com/biz/menchies-frozen-yogurt-lafayette')
soup = BeautifulSoup(r.content, 'lxml')
# Locate the business ID to use (from JSON inside one of the script entries)
for script in soup.find_all('script', attrs={"type" : "application/json"}):
json_text = script.text.strip('<!->')
if "businessId" in json_text:
gaConfig = json.loads(json_text)
try:
biz_id = gaConfig["legacyProps"]["bizDetailsProps"]["bizDetailsMetaProps"]["businessId"]
break
except KeyError:
pass
# Build a suitable JSON request for the required information
json_post = [
{
"operationName": "GetBusinessAttributes",
"variables": {
"BizEncId": biz_id
},
"extensions": {
"documentId": "35e0950cee1029aa00eef5180adb55af33a0217c64f379d778083eb4d1c805e7"
}
},
{
"operationName": "GetBizPageProperties",
"variables": {
"BizEncId": biz_id
},
"extensions": {
"documentId": "f06d155f02e55e7aadb01d6469e34d4bad301f14b6e0eba92a31e635694ebc21"
}
},
]
r = session.post('https://www.yelp.com/gql/batch', json=json_post)
j = r.json()
business = j[0]['data']['business']
print(business['name'], '\n')
for property in j[1]['data']['business']['organizedProperties'][0]['properties']:
print(f'{"Yes" if property["isActive"] else "No":5} {property["displayText"]}')
This would give you the following entries:
Ziggi's Coffee
Yes Offers Delivery
Yes Offers Takeout
Yes Accepts Credit Cards
Yes Private Lot Parking
Yes Bike Parking
Yes Drive-Thru
No No Outdoor Seating
No No Wi-Fi
Reviews could be obtained as follows:
r_reviews = session.get(f'https://www.yelp.com/biz/{biz_id}/review_feed', params={"start" : "0", "sort_by" : "relevance_desc", "q" : ""})
reviews = r_reviews.json()
for review in reviews["reviews"]:
print(review["user"]["markupDisplayName"])
print(review["comment"]["text"])
print("----------")
Giving something like:
Jennifer C.
I am a huge local fan of Ziggi's. I find every experience with them them to be good. I love that they have an app so you can order ahead if you happen to be closer to Main St vs Hover. The app is easy to use and lets me customize everything. <br><br>I love that they have two drive thru locations and they are easy to navigate to and from. Their staff is always so nice too. <br><br>Their rewards program has been great for me since I go often enough to get the free drinks. <br><br>And the drinks!! From coffee to lattes to italian sodas!! The frozen chocolate peanut butter drink!! The Colorado Sunrise and Limesicle!! Their citrus green tea! I mean really?? Its all so good. <br><br>Another favorite of mine is their large kids drink menu. Its so nice to take my son for a treat there. <br><br>I am so glad they are part of Longmont and definitely have indefinite plans to remain a permanent customer.
----------
Judd O.
My wife was sold a defective gift-card as a gift for a colleague's wedding, it didn't work when the new bride attempted to use it at an Estes Park Ziggi's. Funnily enough, the recipient's mother had said the same thing happened with a GC she'd bought from this same location. We brought it back here and were told that, without the receipt that was the size of a thimble, we were boned.<br><br>That being said, we did get our second card's free drink and it'll be our last.<br><br>We're just lucky we only spent 25 bucks.<br><br>Edit: Also, the manager's name is Pristine, there's some grand irony in that.
----------
How was this solved?
Your best friend here is your browser's network dev tools. With this you can watch the requests made to obtain the information. The normal process flow is the initial HTML page is downloaded, this runs the javascript and requests more data to further fill the page.
The trick is to first locate where the data you want is (often returned as JSON), then determine what you need to recreate the parameters needed to make the request for it.
To further understand this code, use print(). Print everything, it will show you how each part builds on the next part. It is how the script was written, one bit at a time.
Approaches using Selenium allow the javascript to work, but most times this is not needed as it is just making requests and formatting the data for display.
I am trying to scrape the mail ID with Scrapy, Python and RegEx from this page: https://allevents.in/bangalore/project-based-summer-training-program/1851553244864163 .
For that purpose, I wrote the following commands, each of which returned an empty list:
response.xpath('//a/*[#href = "#"]/text()').extract()
response.xpath('//a/#onclick').extract()
response.xpath('//a/#onclick/text()').extract()
response.xpath('//span/*[#class = ""]/a/text()').extract()
response.xpath('//a/#onclick/text()').extract()
Apart from these, I had a plan to scrape the email ID from the description using RegEx. For that I wrote command to scrape the description which scraped everything except the email Id at the end of the description:
response.xpath('//*[#property = "schema:description"]/text()').extract()
The output of the above command is:
[u'\n\t\t\t\t\t\t\t "Your Future is created by what you do today Let\'s shape it With Summer Training Program \u2026\u2026\u2026 ."', u'\n', u'\nWith ever changing technologies & methodologies, the competition today is much greater than ever before. The industrial scenario needs constant technical enhancements to cater to the rapid demands.', u'\nHT India Labs is presenting Summer Training Program to acquire and clear your concepts about your respective fields. ', u'\nEnroll on ', u' and avail Early bird Discounts.', u'\n', u'\nFor Registration or Enquiry call 9911330807, 7065657373 or write us at ', u'\t\t\t\t\t\t']
I don't have much knowledge on onclick event attribute. I suppose, when it is set to return false then the request usually skips that portion. However, if you try the way I showed below, you may get the result very close to what you want.
import requests
from scrapy import Selector
res = requests.get("https://allevents.in/bangalore/project-based-summer-training-program/1851553244864163")
sel = Selector(res)
for items in sel.css("div[property='schema:description']"):
emailid = items.css("span::text").extract_first()
print(emailid)
Output:
htindialabsworkshops | gmail ! com
I have the following text:
"It's the show your only friend and pastor have been talking about!
<i>Wonder Showzen</i> is a hilarious glimpse into the black
heart of childhood innocence! Get ready as the complete first season of MTV2's<i> Wonder Showzen</i> tackles valuable life lessons like birth,
nature, diversity, and history – all inside the prison of
your mind! Where else can you..."
What I want to do with this is remove the html tags and encode it into unicode. I am currently doing:
def remove_tags(text):
return TAG_RE.sub('', text)
Which only strips the tag. How would I correctly encode the above for database storage?
You could try passing your text through a HTML parser. Here is an example using BeautifulSoup:
from bs4 import BeautifulSoup
text = '''It's the show your only friend and pastor have been talking about!
<i>Wonder Showzen</i> is a hilarious glimpse into the black
heart of childhood innocence! Get ready as the complete first season of MTV2's<i> Wonder Showzen</i> tackles valuable life lessons like birth,
nature, diversity, and history – all inside the prison of
your mind! Where else can you...'''
soup = BeautifulSoup(text)
>>> soup.text
u"It's the show your only friend and pastor have been talking about! \nWonder Showzen is a hilarious glimpse into the black \nheart of childhood innocence! Get ready as the complete first season of MTV2's Wonder Showzen tackles valuable life lessons like birth, \nnature, diversity, and history \u2013 all inside the prison of \nyour mind! Where else can you..."
You now have a unicode string with the HTML entities converted to unicode escaped characters, i.e. – was converted to \u2013.
This also removes the HTML tags.
I am trying to crawl pubmed with python and get the pubmed ID for all papers that an article was cited by.
For example this article (ID: 11825149)
http://www.ncbi.nlm.nih.gov/pubmed/11825149
Has a page linking to all articles that cite it:
http://www.ncbi.nlm.nih.gov/pubmed?linkname=pubmed_pubmed_citedin&from_uid=11825149
The problem is it has over 200 links but only shows 20 per page. The 'next page' link is not accessible by url.
Is there a way to open the 'send to' option or view the content on the next pages with python?
How I currently open pubmed pages:
def start(seed):
webpage = urlopen(seed).read()
print webpage
citedByPage = urlopen('http://www.ncbi.nlm.nih.gov/pubmedlinkname=pubmed_pubmed_citedin&from_uid=' + pageid).read()
print citedByPage
From this I can extract all the cited by links on the first page, but how can I extract them from all pages? Thanks.
I was able to get the cited by IDs using a method from this page
http://www.bio-cloud.info/Biopython/en/ch8.html
Back in Section 8.7 we mentioned ELink can be used to search for citations of a given paper. Unfortunately this only covers journals indexed for PubMed Central (doing it for all the journals in PubMed would mean a lot more work for the NIH). Let’s try this for the Biopython PDB parser paper, PubMed ID 14630660:
>>> from Bio import Entrez
>>> Entrez.email = "A.N.Other#example.com"
>>> pmid = "14630660"
>>> results = Entrez.read(Entrez.elink(dbfrom="pubmed", db="pmc",
... LinkName="pubmed_pmc_refs", from_uid=pmid))
>>> pmc_ids = [link["Id"] for link in results[0]["LinkSetDb"][0]["Link"]]
>>> pmc_ids
['2744707', '2705363', '2682512', ..., '1190160']
Great - eleven articles. But why hasn’t the Biopython application note been found (PubMed ID 19304878)? Well, as you might have guessed from the variable names, there are not actually PubMed IDs, but PubMed Central IDs. Our application note is the third citing paper in that list, PMCID 2682512.
So, what if (like me) you’d rather get back a list of PubMed IDs? Well we can call ELink again to translate them. This becomes a two step process, so by now you should expect to use the history feature to accomplish it (Section 8.15).
But first, taking the more straightforward approach of making a second (separate) call to ELink:
>>> results2 = Entrez.read(Entrez.elink(dbfrom="pmc", db="pubmed", LinkName="pmc_pubmed",
... from_uid=",".join(pmc_ids)))
>>> pubmed_ids = [link["Id"] for link in results2[0]["LinkSetDb"][0]["Link"]]
>>> pubmed_ids
['19698094', '19450287', '19304878', ..., '15985178']
This time you can immediately spot the Biopython application note as the third hit (PubMed ID 19304878).
Now, let’s do that all again but with the history …TODO.
And finally, don’t forget to include your own email address in the Entrez calls.
I've written a Scrapy spider that extracts text from a page. The spider parses and outputs correctly on many of the pages, but is thrown off by a few. I'm trying to maintain line breaks and formatting in the document. Pages such as http://www.state.gov/r/pa/prs/dpb/2011/04/160298.htm are formatted properly like such:
April 7, 2011
Mark C. Toner
2:03 p.m. EDT
MR. TONER: Good afternoon, everyone. A couple of things at the top,
and then I’ll take your questions. We condemn the attack on innocent
civilians in southern Israel in the strongest possible terms, as well
as ongoing rocket fire from Gaza. As we have reiterated many times,
there’s no justification for the targeting of innocent civilians,
and those responsible for these terrorist acts should be held
accountable. We are particularly concerned about reports that indicate
the use of an advanced anti-tank weapon in an attack against civilians
and reiterate that all countries have obligations under relevant
United Nations Security Council resolutions to prevent illicit
trafficking in arms and ammunition. Also just a brief statement --
QUESTION: Can we stay on that just for one second?
MR. TONER: Yeah. Go ahead, Matt.
QUESTION: Apparently, the target of that was a school bus. Does that
add to your outrage?
MR. TONER: Well, any attack on innocent civilians is abhorrent, but
certainly the nature of the attack is particularly so.
While pages like http://www.state.gov/r/pa/prs/dpb/2009/04/121223.htm have output like this with no line breaks:
April 2, 2009
Robert Wood
11:53 a.m. EDTMR. WOOD: Good morning, everyone. I think it’s just
about still morning. Welcome to the briefing. I don’t have anything,
so – sir.QUESTION: The North Koreans have moved fueling tankers, or
whatever, close to the site. They may or may not be fueling this
missile. What words of wisdom do you have for the North Koreans at
this moment?MR. WOOD: Well, Matt, I’m not going to comment on, you
know, intelligence matters. But let me just say again, we call on the
North to desist from launching any type of missile. It would be
counterproductive. It’s provocative. It further inflames tensions in
the region. We want to see the North get back to the Six-Party
framework and focus on denuclearization.Yes.QUESTION: Japan has also
said they’re going to call for an emergency meeting in the Security
Council, you know, should this launch go ahead. Is this something that
you would also be looking for?MR. WOOD: Well, let’s see if this test
happens. We certainly hope it doesn’t. Again, calling on the North
not to do it. But certainly, we will – if that test does go forward,
we will be having discussions with our allies.
The code I'm using is as follows:
def parse_item(self, response):
self.log('Hi, this is an item page! %s' % response.url)
hxs = HtmlXPathSelector(response)
speaker = hxs.select("//span[contains(#class, 'official_s_name')]") #gets the speaker
speaker = speaker.select('string()').extract()[0] #extracts speaker text
date = hxs.select('//*[#id="date_long"]') #gets the date
date = date.select('string()').extract()[0] #extracts the date
content = hxs.select('//*[#id="centerblock"]') #gets the content
content = content.select('string()').extract()[0] #extracts the content
texts = "%s\n\n%s\n\n%s" % (date, speaker, content) #puts everything together in a string
filename = ("/path/StateDailyBriefing-" + '%s' ".txt") % (date) #creates a file using the date
#opens the file defined above and writes 'texts' using utf-8
with codecs.open(filename, 'w', encoding='utf-8') as output:
output.write(texts)
I think they problem lies in the formatting of the HTML of the page. On the pages that output the text incorrectly, the paragraphs are separated by <br> <p></p>, while on the pages that output correctly the paragraphs are contained within <p align="left" dir="ltr">. So, while I've identified this, I'm not sure how to make everything output consistently in the correct form.
The problem is that when you getting text() or string(), <br> tags are not converted to newline.
Workaround - replace <br> tags before doing XPath requests. Code:
response = response.replace(body=response.body.replace('<br />', '\n'))
hxs = HtmlXPathSelector(response)
And let me give some advice, if you know, that there is only one node, you can use text() instead string():
date = hxs.select('//*[#id="date_long"]/text()').extract()[0]
Try this xpath:
//*[#id="centerblock"]//text()