I'm setting up integration between a webflow store and shippo to assist with creating labels and managing shipping. Webflow passes the data as one huge object for address information, however to create a new order in shippo, I need the information parsed, separated as individual line items. I have attempted to use formatter which allows one to extract text, split text, use regex to match data and more.
import re
details = re.search(r'(?<=city:\s).*$', input_data[All Addresses])
Regex in Python is my best option, yet the result will not find and/or display the data.
Please any experts in Zapier integrations, I need assistance in figuring out a way to parse the incoming data from webflow, pass it to the 'create a order' action with shippo.
Structure of Data:
addressee: string
city: string
country: string
more....
You can try this one:
Combine all the data in one whole string
import re
details = re.finall(r'(?<=city:\s).*$', all_addresses)
return details
It will you give the list of all matches in the text.
Related
I'm using Open Refine to do something that I KNOW Python can do. I'm using it to convert a csv into an XML metadata document. I can figure out most of it, but the one thing that trips me up, is this GREL line:
{{forEach(cells["subjectTopicsLocal"].value.split('; '), v, '<subject authority="local"><topic>'+v.escape("xml")+'</topic></subject>')}}
What this does, is beautiful for me. I've got a "subject" field in my Excel spreadsheet. My volunteers enter keywords, separated with a "; ". I don't know how many keywords they'll come up with, and sometimes there is only one. That GREL line creates a new <subject authority="local"><topic></topic></subject> for each term created, and of course slides it into the field.
I know there has to be a Python expression that can do this. Could someone recommend best practice for this? I'd appreciate it!
Basically you want to use 'split' in Python to convert the string from your subject field into a Python list, and then you can iterate over the list.
So assuming you've read the content of the 'subject' field from a line in your csv/excel document already and assigned it to a string variable 'subj' you could do something like:
subjList = subj.split(";")
for subject in subjList:
#do what you need to do to output 'subject' in an xml element here
This Python expression is the equivalent to your GREL expression:
['<subject authority="local"><topic>'+escape(v)+'</topic></subject>') for v in split(value,'; ')]
It will create an array of XML snippets containing your subjects. It assumes that you've created or imported an appropriate escape function, such as
from xml.sax.saxutils import escape
I am using docx library to read files from a word doc, I am trying to extract only the questions using regex search and match. I found infinite ways of doing it but I keep getting a "TypeError".
The data I am trying to extract is this:
Will my financial aid pay for housing?
Off Campus Housing - After financial aid applies toward your tuition and fees, any remaining funds will be sent to you as a refund that will either be directly deposited (which can be set up through your account) or mailed to you as a paper check. You can then use the refund to pay your rent. It is important to note that financial aid may not be available when rent is due, so make sure to have a plan in place to pay your rent. Will my financial aid pay for housing?
"financial" "help" "house"
funds "univ oak"
"money" "chisho"
"pay" "chap"
"grant" "laurel"
What are the requirements to receive a room and grant?
How do I pay for my housing?
How do I pay for housing?
If there's also an easier method of exporting the word doc into a different type of file, that'll be great to know for feedback. Thank you
I am using regex 101, I've tried the following regex expressions to match only the sentences that end in a question mark
".*[?=?]$"
"^(W|w).*[?=?]$"
"^[A-Za-z].*[?=?]$"
import re
import sys
from docx import Document
wordDoc = Document('botDoc.docx')
result = re.search('.*[?=?]$', wordDoc)
print(result)
if result:
print(result.group(0))
for table in wordDoc.tables:
for row in table.rows:
for cell in row.cells:
print("test")
I expect to save the matching patterns into directories so I can export the data to a csv file
Your error:
result = re.search('.*[?=?]$', wordDoc)
I believe that this line is the cause of the problem. search() is expecting a string as a second parameter, but is receiving a Document object.
What you should do is use the findall() function. search() only finds the first match for a pattern; findall() finds all the matches and returns them as a list of strings, with each string representing one match.
Since you are working with docx, you would have to extract the contents of the docx and use them as second parameter of the findall() method. If I remember correctly, this is done by first extracting all the paragraphs, and then extracting the text of the individual paragraphs. Refer to this question.
FYI, the way you would do this for a simple text file is the following:
# Open file
f = open('test.txt', 'r')
# Feed the file text into findall(); it returns a list of all the found strings
strings = re.findall(r'your pattern', f.read())
Your Regex:
Unfortunately, your regex is not quite correct, because although logically it makes sense to match only sentences that end on a ?, one of your matches is place to pay your rent. Will my financial aid pay for housing?, for example. Only the second part of that sentence is an actual question. So discard any lower case letters. Your regex should be something like:
[A-Z].*\?$
I currently want to scrape some data from an amazon page and I'm kind of stuck.
For example, lets take this page.
https://www.amazon.com/NIKE-Hyperfre3sh-Athletic-Sneakers-Shoes/dp/B01KWIUHAM/ref=sr_1_1_sspa?ie=UTF8&qid=1546731934&sr=8-1-spons&keywords=nike+shoes&psc=1
I wanted to scrape every variant of shoe size and color. That data can be found opening the source code and searching for 'variationValues'.
There we can see sort of a dictionary containing all the sizes and colors and, below that, in 'asinToDimentionIndexMap', every product code with numbers indicating the variant from the variationValues 'dictionary'.
For example, in asinToDimentionIndexMap we can see
"B01KWIUH5M":[0,0]
Which means that the product code B01KWIUH5M is associated with the size '8M US' (position 0 in variationValues size_name section) and the color 'Teal' (same idea as before)
I want to scrape both the variationValues and the asinToDimentionIndexMap, so i can associate the IndexMap numbers to the variationValues one.
Another person in the site (thanks for the help btw) suggested doing it this way.
script = response.xpath('//script/text()').extract_frist()
import re
# capture everything between {}
data = re.findall(script, '(\{.+?\}_')
import json
d = json.loads(data[0])
d['products'][0]
I can sort of understand the first part. We get everything that's a 'script' as a string and then get everything between {}. The issue is what happens after that. My knowledge of json is not that great and reading some stuff about it didn't help that much.
Is it there a way to get, from that data, 2 dictionaries or lists with the variationValues and asinToDimentionIndexMap? (maybe using some regular expressions in the middle to get some data out of a big string). Or explain a little bit what happens with the json part.
Thanks for the help!
EDIT: Added photo of variationValues and asinToDimensionIndexMap
I think you are close Manuel!
The following code will turn your scraped source into easy-to-select boxes:
import json
d = json.loads(data[0])
JSON is a universal format for storing object information. In other words, it's designed to interpret string data into object data, regardless of the platform you are working with.
https://www.w3schools.com/js/js_json_intro.asp
I'm assuming where you may be finding things a challenge is if there are any errors when accessing a particular "box" inside you json object.
Your code format looks correct, but your access within "each box" may look different.
Eg. If your 'asinToDimentionIndexMap' object is nested within a smaller box in the larger 'products' object, then you might access it like this (after running the code above):
d['products'][0]['asinToDimentionIndexMap']
I've hacked and slash a little bit so you can better understand the structure of your particular json file. Take a look at the link below. On the right-hand side, you will see "which boxes are within one another" - which is precisely what you need to know for accessing what you need.
JSON Object Viewer
For example, the following would yield "companyCompliancePolicies_feature_div":
import json
d = json.loads(data[0])
d['updateDivLists']['full'][0]['divToUpdate']
The person helping you before outlined a general case for you, but you'll need to go in an look at structure this way to truly find what you're looking for.
variationValues = re.findall(r'variationValues\" : ({.*?})', ' '.join(script))[0]
asinVariationValues = re.findall(r'asinVariationValues\" : ({.*?}})', ' '.join(script))[0]
dimensionValuesData = re.findall(r'dimensionValuesData\" : (\[.*\])', ' '.join(script))[0]
asinToDimensionIndexMap = re.findall(r'asinToDimensionIndexMap\" : ({.*})', ' '.join(script))[0]
dimensionValuesDisplayData = re.findall(r'dimensionValuesDisplayData\" : ({.*})', ' '.join(script))[0]
Now you can easily convert them to json as use them combine as you wish.
I am going through a json file and using a regex to pull out info around company financial KPIs and their corresponding values. For example, the regex for
"grossProfits":{"raw":19805000000,"fmt":"19.8B","longFmt":"19,805,000,000"}
would return the 19.8B. The issue is when the KPI does not have any info. For example
"returnOnEquity":{}.
In this case returnOnEquity would return the next number the regex finds.
"returnOnEquity":{},"grossProfits":{"raw":19805000000,"fmt":"19.8B","longFmt":"19,805,000,000"}.
So the value returned for returnOnEquity will be that of grossProfits (19.8B).
Here is my current regex r'.*?"(\d{1,8}\.\d{1,8}M?B?K?|[{}])%?'
In a perfect world, I would want it to return 0 but even a '{' or '}' will suffice.
Any help is much appreciated.
As suggested by the earlier commentators, the json module is the way to go (see Docs)
In your case,
import json
with open('sample.txt') as js:
data = json.load(js)
for firm in data:
print(firm)
print(data[firm]['grossProfits']['raw'])
print(data[firm]['returnOnEquity'])
It turns your data into a dictionary of dictionaries, so you don't have to worry about parsing.
I'm kinda new to Python. And I'm trying to find out how to do parsing in Python?
I've got a task: to do parsing with some piece of unknown for me symbols and put it to DB. I guess I can create DB and tables with help of SQLAlchemy, but I have no idea how to do parsing and what all these symbols below mean?
http://joxi.ru/YmEVXg6Iq3Q426
http://joxi.ru/E2pvG3NFxYgKrY
$$HDRPUBID 112701130020011127162536
H11127011300UNIQUEPONUMBER120011127
D11127011300UNIQUEPONUMBER100001112345678900000001
D21127011300UNIQUEPONUMBER1000011123456789AR000000001
D11127011300UNIQUEPONUMBER200002123456987X000000001
D21127011300UNIQUEPONUMBER200002123456987XIR000000000This item is inactive. 9781605600000
$$EOFPUBID 1127011300200111271625360000005
Thanks in advance those who can give me some advices what to start from and how the parsing is going on?
The best approach is to first figure out where each token begins and ends, and write a regular expression to capture these. The site RegexPal might help you design the regex.
As other suggest take a look to some regex tutorials, and also re module help.
Probably you're looking to something like this:
import re
headerMapping = {'type': (1,5), 'pubid': (6,11), 'batchID': (12,21),
'batchDate': (22,29), 'batchTime': (30,35)}
poaBatchHeaders = re.findall('\$\$HDR\d{30}', text)
parsedBatchHeaders = []
batchHeaderDict = {}
for poaHeader in poaBatchHeaders:
for key in headerMapping:
start = headerMapping[key][0]-1
end = headerMapping[key][1]
batchHeaderDict.update({key: poaHeader[start:end]})
parsedBatchHeaders.append(batchHeaderDict)
Then you have list with dicts, each dict contains data for each attribute. I assume that you have your datafile in text which is string. Each dict is made for one found structure (POA Batch Header in example).
If you want to parse it further, you have to made a function to parse each date in each attribute.
def batchDate(batch):
return (batch[0:2]+'-'+batch[2:4]+'-20'+batch[4:])
for header in parsedBatchHeaders:
header.update({'batchDate': batchDate( header['batchDate'] )})
Remember, that's an example and I don't know documentation of your data! I guess it works like that, but rest is up to you.