Develop Reference

Using jsonpath in api.ai in case we have already our json file to query in?

import json
def makeWebhookResult(req):
if req.get("result").get("action") != "Phdapp":
return {}
result = req.get("result")
parameters = result.get("parameters")
Progr = parameters.get("PhDsubjects")
time = parameters.get("PhdTime")
Levp = parameters.get("PhDDegLevp")
with open('Sheet1.json') as f:
data = f.read()
jsondata = json.loads(data)
match = jsonpath.jsonpath(jsondata,
'$.features[[?(#.ProgramName == Progr && #.Level == Levp && #.StartDate == time)]].UniversityName')
speech = "This is the universities you were looking for " + match
This is the part of my python code which have errors i can't figure it out, I have an intent with action which is "Phdapp" with three parameters that i need to use their values in my jsonpath querying from "sheet1.json" file in the same repository on GitHub in json format. But i can't get data from my intent neither accessing my son file for querying...is it because api.ai is not compatible with jsonpath or it is the problem of my code! or if there is a best to use which easier it can be my pleasure to know it. Thanks

How to parse a single-column text file into a table using python?

I'm new here to StackOverflow, but I have found a LOT of answers on this site. I'm also a programming newbie, so i figured i'd join and finally become part of this community - starting with a question about a problem that's been plaguing me for hours.
I login to a website and scrape a big body of text within the b tag to be converted into a proper table. The layout of the resulting Output.txt looks like this:
BIN STATUS
8FHA9D8H 82HG9F RECEIVED SUCCESSFULLY AWAITING STOCKING PROCESS
INVENTORY CODE: FPBC *SOUP CANS LENTILS
BIN STATUS
HA8DHW2H HD0138 RECEIVED SUCCESSFULLY AWAITING STOCKING PROCESS
8SHDNADU 00A123 #2956- INVALID STOCK COUPON CODE (MISSING).
93827548 096DBR RECEIVED SUCCESSFULLY AWAITING STOCKING PROCESS
There are a bunch of pages with the exact same blocks, but i need them to be combined into an ACTUAL table that looks like this:
BIN INV CODE STATUS
HA8DHW2HHD0138 FPBC-*SOUP CANS LENTILS RECEIVED SUCCESSFULLY AWAITING STOCKING PROCESS
8SHDNADU00A123 FPBC-*SOUP CANS LENTILS #2956- INVALID STOCK COUPON CODE (MISSING).
93827548096DBR FPBC-*SOUP CANS LENTILS RECEIVED SUCCESSFULLY AWAITING STOCKING PROCESS
8FHA9D8H82HG9F SSXR-98-20LM NM CORN CREAM RECEIVED SUCCESSFULLY AWAITING STOCKING PROCESS
Essentially, all separate text blocks in this example would become part of this table, with the inv code repeating with its Bin values. I would post my attempts at parsing this data(have tried Pandas/bs/openpyxl/csv writer), but ill admit they are a little embarrassing, as i cannot find any information on this specific problem. Is there any benevolent soul out there that can help me out? :)
(Also, i am using Python 2.7)

A simple custom parser like the following should do the trick.
from __future__ import print_function
def parse_body(s):
line_sep = '\n'
getting_bins = False
inv_code = ''
for l in s.split(line_sep):
if l.startswith('INVENTORY CODE:') and not getting_bins:
inv_data = l.split()
inv_code = inv_data[2] + '-' + ' '.join(inv_data[3:])
elif l.startswith('INVENTORY CODE:') and getting_bins:
print("unexpected inventory code while reading bins:", l)
elif l.startswith('BIN') and l.endswith('MESSAGE'):
getting_bins = True
elif getting_bins == True and l:
bin_data = l.split()
# need to add exception handling here to make sure:
# 1) we have an inv_code
# 2) bin_data is at least 3 items big (assuming two for
# bin_id and at least one for message)
# 3) maybe some constraint checking to ensure that we have
# a valid instance of an inventory code and bin id
bin_id = ''.join(bin_data[0:2])
message = ' '.join(bin_data[2:])
# we now have a bin, an inv_code, and a message to add to our table
print(bin_id.ljust(20), inv_code.ljust(30), message, sep='\t')
elif getting_bins == True and not l:
# done getting bins for current inventory code
getting_bins = False
inv_code = ''

A rather complex one, but this might get you started:
import re, pandas as pd
from pandas import DataFrame
rx = re.compile(r'''
(?:INVENTORY\ CODE:)\s*
(?P<inv>.+\S)
[\s\S]+?
^BIN.+[\n\r]
(?P<bin_msg>(?:(?!^\ ).+[\n\r])+)
''', re.MULTILINE | re.VERBOSE)
string = your_string_here
# set up the dataframe
df = DataFrame(columns = ['BIN', 'INV', 'MESSAGE'])
for match in rx.finditer(string):
inv = match.group('inv')
bin_msg_raw = match.group('bin_msg').split("\n")
rxbinmsg = re.compile(r'^(?P<bin>(?:(?!\ {2}).)+)\s+(?P<message>.+\S)\s*$', re.MULTILINE)
for item in bin_msg_raw:
for m in rxbinmsg.finditer(item):
# append it to the dataframe
df.loc[len(df.index)] = [m.group('bin'), inv, m.group('message')]
print(df)
Explanation
It looks for INVENTORY CODE and sets up the groups (inv and bin_msg) for further processing in afterwork() (note: it would be easier if you had only one line of bin/msg as you need to split the group here afterwards).
Afterwards, it splits the bin and msg part and appends all to the df object.

I had a code written for a website scrapping which may help you.
Basically what you need to do is write click on the web page go to html and try to find the tag for the table you are looking for and using the module (i am using beautiful soup) extract the information. I am creating a json as I need to store it into mongodb you can create table.
#! /usr/bin/python
import sys
import requests
import re
from BeautifulSoup import BeautifulSoup
import pymongo
def req_and_parsing():
url2 = 'http://businfo.dimts.in/businfo/Bus_info/EtaByRoute.aspx?ID='
list1 = ['534UP','534DOWN']
for Route in list1:
final_url = url2 + Route
#r = requests.get(final_url)
#parsing_file(r.text,Route)
outdict = []
outdict = [parsing_file( requests.get(url2+Route).text,Route) for Route in list1 ]
print outdict
conn = f_connection()
for i in range(len(outdict)):
insert_records(conn,outdict[i])
def parsing_file(txt,Route):
soup = BeautifulSoup(txt)
table = soup.findAll("table",{"id" : "ctl00_ContentPlaceHolder1_GridView2"})
#trtags = table[0].findAll('tr')
tdlist = []
trtddict = {}
"""
for trtag in trtags:
print 'print trtag- ' , trtag.text
tdtags = trtag.findAll('td')
for tdtag in tdtags:
print tdtag.text
"""
divtags = soup.findAll("span",{"id":"ctl00_ContentPlaceHolder1_ErrorLabel"})
for divtag in divtags:
for divtag in divtags:
print "div tag - " , divtag.text
if divtag.text == "Currently no bus is running on this route" or "This is not a cluster (orange bus) route":
print "Page not displayed Errored with below meeeage for Route-", Route," , " , divtag.text
sys.exit()
trtags = table[0].findAll('tr')
for trtag in trtags:
tdtags = trtag.findAll('td')
if len(tdtags) == 2:
trtddict[tdtags[0].text] = sub_colon(tdtags[1].text)
return trtddict
def sub_colon(tag_str):
return re.sub(';',',',tag_str)
def f_connection():
try:
conn=pymongo.MongoClient()
print "Connected successfully!!!"
except pymongo.errors.ConnectionFailure, e:
print "Could not connect to MongoDB: %s" % e
return conn
def insert_records(conn,stop_dict):
db = conn.test
print db.collection_names()
mycoll = db.stopsETA
mycoll.insert(stop_dict)
if __name__ == "__main__":
req_and_parsing()

Libtorrent not working when loading infohash from json?

I am trying to make a python script that downloads just the metadata of a torrent given an infohash. This infohash is loaded from a json file, with the contents like such:
{"infohash":"someinfohash"}
If I manually encode the infohash into the link string, or I make it personally using a dictionary, like this:
link = 'magnet:?xt=urn:btih:someinfohash'
or like this:
foo = {}
foo['infohash'] = 'someinfohash'
link = 'magnet:?xt=urn:btih:' + foo['infohash']
I can always download the metadata, no problem. But for some reason, when I load it from a json file, it consistently times out.
thedata = open(sys.argv[1]).read()
thedata = json.loads(thedata)
ses = lt.session()
ses.listen_on(6881, 6891)
params = {
'save_path': '.', # doesn't matter because we're only downloading metadata
}
link = 'magnet:?xt=urn:btih:' + thedata['infohash']
handle = lt.add_magnet_uri(ses, link, params)
ses.add_dht_router('dht.transmissionbt.com', 6881)
ses.add_dht_router('router.bittorrent.com', 6881)
ses.add_dht_router('router.utorrent.com', 6881)
ses.start_dht()
sys.stdout.write('Downloading metadata...')
sys.stdout.flush()
timeout = time.time()
while (not handle.has_metadata()):
if (time.time() >= 300 + timeout):
print 'timed out'
sys.exit(1)
time.sleep(1)
print 'done'
ses.pause()
If I check if the strings are equal, like so:
link = 'magnet:?xt=urn:btih:' + thedata['infohash']
link2 = 'magnet:?xt=urn:btih:someinfohash'
print link == link2
It prints true.
Does anybody have any idea what is going on?

I finally found what was wrong with it.
I got the idea to examine the programmer-friendly text representation of the json-generated dictionary as opposed to my one made manually.
thedata = open(sys.argv[1]).read()
thedata = json.loads(thedata)
print thedata
thedata = {}
thedata['infohash'] = 'someinfohash'
print thedata
What came up was this:
{u'infohash', u'someinfohash'}
{'infohash', 'someinfohash'}
Apparently the json-made dict was encoded in unicode, and this somehow prevented libtorrent from connecting to seeders. After un-unicoding all the keys and values, the script runs perfectly.

Optimize Python Script to parse xml

I'm parsing the US Patent XML files (downloaded from Google patent dumps) using Python and Beautifulsoup; parsed data is exported to MYSQL database.
Each year's data contains close to 200-300K patents - which means parsing 200-300K xml files.
The server on which I'm running the python script is pretty powerful - 16 cores, 160 gigs of RAM, etc. but still it is taking close to 3 days to parse one year's worth of data.
I've been learning and using python since 2 years - so I can get stuff done but do not know how to get it done in the most efficient manner. I'm reading on it.
How can I optimize the below script to make it efficient?
Any guidance would be greatly appreciated.
Below is the code:
from bs4 import BeautifulSoup
import pandas as pd
from pandas.core.frame import DataFrame
import MySQLdb as db
import os
cnxn = db.connect('xx.xx.xx.xx','xxxxx','xxxxx','xxxx',charset='utf8',use_unicode=True)
def separated_xml(infile):
file = open(infile, "r")
buffer = [file.readline()]
for line in file:
if line.startswith("<?xml "):
yield "".join(buffer)
buffer = []
buffer.append(line)
yield "".join(buffer)
file.close()
def get_data(soup):
df = pd.DataFrame(columns = ['doc_id','patcit_num','patcit_document_id_country', 'patcit_document_id_doc_number','patcit_document_id_kind','patcit_document_id_name','patcit_document_id_date','category'])
if soup.findAll('us-citation'):
cit = soup.findAll('us-citation')
else:
cit = soup.findAll('citation')
doc_id = soup.findAll('publication-reference')[0].find('doc-number').text
for x in cit:
try:
patcit_num = x.find('patcit')['num']
except:
patcit_num = None
try:
patcit_document_id_country = x.find('country').text
except:
patcit_document_id_country = None
try:
patcit_document_id_doc_number = x.find('doc-number').text
except:
patcit_document_id_doc_number = None
try:
patcit_document_id_kind = x.find('kind').text
except:
patcit_document_id_kind = None
try:
patcit_document_id_name = x.find('name').text
except:
patcit_document_id_name = None
try:
patcit_document_id_date = x.find('date').text
except:
patcit_document_id_date = None
try:
category = x.find('category').text
except:
category = None
print doc_id
val = {'doc_id':doc_id,'patcit_num':patcit_num, 'patcit_document_id_country':patcit_document_id_country,'patcit_document_id_doc_number':patcit_document_id_doc_number, 'patcit_document_id_kind':patcit_document_id_kind,'patcit_document_id_name':patcit_document_id_name,'patcit_document_id_date':patcit_document_id_date,'category':category}
df = df.append(val, ignore_index=True)
df.to_sql(name = 'table_name', con = cnxn, flavor='mysql', if_exists='append')
print '1 doc exported'
i=0
l = os.listdir('/path/')
for item in l:
f = '/path/'+item
print 'Currently parsing - ',item
for xml_string in separated_xml(f):
soup = BeautifulSoup(xml_string,'xml')
if soup.find('us-patent-grant'):
print item, i, xml_string[177:204]
get_data(soup)
else:
print item, i, xml_string[177:204],'***********************************soup not found********************************************'
i+=1
print 'DONE!!!'

Here is a tutorial on multi-threading, because currently that code will run on 1 thread, 1 core.
Remove all try/except statements and handle the code properly. Exceptions are expensive.
Run a profiler to find the chokepoints, and multi-thread those or find a way to do them less times.

So, you're doing two things wrong. First, you're using BeautifulSoup, which is slow, and second, you're using a "find" call, which is also slow.
As a first cut, look at lxml's ability to pre-compile xpath queries (Look at the heading "The Xpath class). That will give you a huge speed boost.
Alternatively, I've been working on a library to do this kind of parsing declaratively, using best practices for lxml speed, including precompiled xpath called yankee.
Yankee on PyPI |
Yankee on GitHub
You could do the same thing with yankee like this:
from yankee.xml import Schema, fields as f
# Create a schema for citations
class Citation(Schema):
num = f.Str(".//patcit")
country = f.Str(".//country")
# ... and so forth for the rest of your fields
# Then create a "wrapper" to get all the citations
class Patent(Schema):
citations = f.List(".//us-citation|.//citation")
# Then just feed the Schema your lxml.etrees for each patent:
import lxml.etree as ET
schema = Patent()
for _, doc in ET.iterparse(xml_string, "xml"):
result = schema.load(doc)
The result will look like this:
{
"citations": [
{
"num": "<some value>",
"country": "<some value>",
},
{
"num": "<some value>",
"country": "<some value>",
},
]
}
I would also check out Dask to help you multithread it more efficiently. Pretty much all my projects use it.

Fetching language detection from Google api

I have a CSV with keywords in one column and the number of impressions in a second column.
I'd like to provide the keywords in a url (while looping) and for the Google language api to return what type of language was the keyword in.
I have it working manually. If I enter (with the correct api key):
http://ajax.googleapis.com/ajax/services/language/detect?v=1.0&key=myapikey&q=merde
I get:
{"responseData": {"language":"fr","isReliable":false,"confidence":6.213709E-4}, "responseDetails": null, "responseStatus": 200}
which is correct, 'merde' is French.
so far I have this code but I keep getting server unreachable errors:
import time
import csv
from operator import itemgetter
import sys
import fileinput
import urllib2
import json
E_OPERATION_ERROR = 1
E_INVALID_PARAMS = 2
#not working
def parse_result(result):
"""Parse a JSONP result string and return a list of terms"""
# Deserialize JSON to Python objects
result_object = json.loads(result)
#Get the rows in the table, then get the second column's value
# for each row
return row in result_object
#not working
def retrieve_terms(seedterm):
print(seedterm)
"""Retrieves and parses data and returns a list of terms"""
url_template = 'http://ajax.googleapis.com/ajax/services/language/detect?v=1.0&key=myapikey&q=%(seed)s'
url = url_template % {"seed": seedterm}
try:
with urllib2.urlopen(url) as data:
data = perform_request(seedterm)
result = data.read()
except:
sys.stderr.write('%s\n' % 'Could not request data from server')
exit(E_OPERATION_ERROR)
#terms = parse_result(result)
#print terms
print result
def main(argv):
filename = argv[1]
csvfile = open(filename, 'r')
csvreader = csv.DictReader(csvfile)
rows = []
for row in csvreader:
rows.append(row)
sortedrows = sorted(rows, key=itemgetter('impressions'), reverse = True)
keys = sortedrows[0].keys()
for item in sortedrows:
retrieve_terms(item['keywords'])
try:
outputfile = open('Output_%s.csv' % (filename),'w')
except IOError:
print("The file is active in another program - close it first!")
sys.exit()
dict_writer = csv.DictWriter(outputfile, keys, lineterminator='\n')
dict_writer.writer.writerow(keys)
dict_writer.writerows(sortedrows)
outputfile.close()
print("File is Done!! Check your folder")
if __name__ == '__main__':
start_time = time.clock()
main(sys.argv)
print("\n")
print time.clock() - start_time, "seconds for script time"
Any idea how to finish the code so that it will work? Thank you!

Try to add referrer, userip as described in the docs:
An area to pay special attention to
relates to correctly identifying
yourself in your requests.
Applications MUST always include a
valid and accurate http referer header
in their requests. In addition, we
ask, but do not require, that each
request contains a valid API Key. By
providing a key, your application
provides us with a secondary
identification mechanism that is
useful should we need to contact you
in order to correct any problems. Read
more about the usefulness of having an
API key
Developers are also encouraged to make
use of the userip parameter (see
below) to supply the IP address of the
end-user on whose behalf you are
making the API request. Doing so will
help distinguish this legitimate
server-side traffic from traffic which
doesn't come from an end-user.
Here's an example based on the answer to the question "access to google with python":
#!/usr/bin/python
# -*- coding: utf-8 -*-
import json
import urllib, urllib2
from pprint import pprint
api_key, userip = None, None
query = {'q' : 'матрёшка'}
referrer = "https://stackoverflow.com/q/4309599/4279"
if userip:
query.update(userip=userip)
if api_key:
query.update(key=api_key)
url = 'http://ajax.googleapis.com/ajax/services/language/detect?v=1.0&%s' %(
urllib.urlencode(query))
request = urllib2.Request(url, headers=dict(Referer=referrer))
json_data = json.load(urllib2.urlopen(request))
pprint(json_data['responseData'])
Output
{u'confidence': 0.070496580000000003, u'isReliable': False, u'language': u'ru'}
Another issue might be that seedterm is not properly quoted:
if isinstance(seedterm, unicode):
value = seedterm
else: # bytes
value = seedterm.decode(put_encoding_here)
url = 'http://...q=%s' % urllib.quote_plus(value.encode('utf-8'))