"IPTC text classification example" Code Answer's
You're definitely familiar with the best coding language Python that developers use to develop their projects and they get all their queries like "IPTC text classification example" answered properly. Developers are finding an appropriate answer about IPTC text classification example related to the Python coding language. By visiting this online portal developers get answers concerning Python codes question like IPTC text classification example. Enter your desired code related query in the search bar and get every piece of information about Python code related question on IPTC text classification example.
IPTC text classification example
Clear Crayfish
on Jan 14, 2021
#! /usr/bin/env python
# Created by MeaningCloud Support Team
# Date: 26/02/18
import sys
import meaningcloud
# @param model str - Name of the model to use. Example: "IAB_en" by default = "IPTC_en"
model = 'IAB_en'
# @param license_key - Your license key (found in the subscription section in https://www.meaningcloud.com/developer/)
license_key = '<<<<< your license key >>>>>'
# @param text - Text to use for different API calls
text = 'London is a very nice city but I also love Madrid.'
try:
# We are going to make a request to the Topics Extraction API
topics_response = meaningcloud.TopicsResponse(meaningcloud.TopicsRequest(license_key, txt=text, lang='en',
topicType='e').sendReq())
# If there are no errors in the request, we print the output
if topics_response.isSuccessful():
print("\nThe request to 'Topics Extraction' finished successfully!\n")
entities = topics_response.getEntities()
if entities:
print("\tEntities detected (" + str(len(entities)) + "):\n")
for entity in entities:
print("\t\t" + topics_response.getTopicForm(entity) + ' --> ' +
topics_response.getTypeLastNode(topics_response.getOntoType(entity)) + "\n")
else:
print("\tNo entities detected!\n")
else:
if topics_response.getResponse() is None:
print("\nOh no! The request sent did not return a Json\n")
else:
print("\nOh no! There was the following error: " + topics_response.getStatusMsg() + "\n")
# CLASS API CALL
# class_response = meaningcloud.ClassResponse(
# meaningcloud.ClassRequest(license_key, txt=text, model=model).sendReq())
# SENTIMENT API CALL
# sentiment_response = meaningcloud.SentimentResponse(
# meaningcloud.SentimentRequest(license_key, lang='en', txt=text, txtf='plain').sendReq())
# GENERIC API CALL
# generic = meaningcloud.Request(url="url_of_specific_API",key=key)
# generic.addParam('parameter','value')
# generic_result = generic.sendRequest()
# generic_response = meaningcloud.Response(generic_result)
# We are going to make a request to the Language Identification API
lang_response = meaningcloud.LanguageResponse(meaningcloud.LanguageRequest(license_key, txt=text).sendReq())
# If there are no errors in the request, we will use the language detected to make a request to Sentiment and Topics
if lang_response.isSuccessful():
print("\nThe request to 'Language Identification' finished successfully!\n")
first_lang = lang_response.getFirstLanguage()
if first_lang:
language = lang_response.getLanguageCode(first_lang)
print("\tLanguage detected: " + lang_response.getLanguageName(first_lang) + ' (' + language + ")\n")
else:
print("\tNo language detected!\n")
# We are going to make a request to the Lemmatization, PoS and Parsing API
parser_response = meaningcloud.ParserResponse(
meaningcloud.ParserRequest(license_key, txt=text, lang='en').sendReq())
# If there are no errors in the request, print tokenization and lemmatization
if parser_response.isSuccessful():
print("\nThe request to 'Lemmatization, PoS and Parsing' finished successfully!\n")
lemmatization = parser_response.getLemmatization(True)
print("\tLemmatization and PoS Tagging:\n")
for token, analyses in lemmatization.items():
print("\t\tToken -->", token)
for analysis in analyses:
print("\t\t\tLemma -->", analysis['lemma'])
print("\t\t\tPoS Tag -->", analysis['pos'], "\n")
except ValueError:
e = sys.exc_info()[0]
print("\nException: " + str(e))
Source: pypi.org
IPTC text classification example
Clear Crayfish
on Jan 14, 2021
CURL *curl;
CURLcode res;
curl = curl_easy_init();
if(curl) {
curl_easy_setopt(curl, CURLOPT_CUSTOMREQUEST, "POST");
curl_easy_setopt(curl, CURLOPT_URL, "https://api.meaningcloud.com/class-1.1?key=<your_key>&txt=<text>&model=<model>");
curl_easy_setopt(curl, CURLOPT_FOLLOWLOCATION, 1L);
curl_easy_setopt(curl, CURLOPT_DEFAULT_PROTOCOL, "https");
struct curl_slist *headers = NULL;
curl_easy_setopt(curl, CURLOPT_HTTPHEADER, headers);
res = curl_easy_perform(curl);
}
curl_easy_cleanup(curl);Source: www.meaningcloud.com
All those coders who are working on the Python based application and are stuck on IPTC text classification example can get a collection of related answers to their query. Programmers need to enter their query on IPTC text classification example related to Python code and they'll get their ambiguities clear immediately. On our webpage, there are tutorials about IPTC text classification example for the programmers working on Python code while coding their module. Coders are also allowed to rectify already present answers of IPTC text classification example while working on the Python language code. Developers can add up suggestions if they deem fit any other answer relating to "IPTC text classification example". Visit this developer's friendly online web community, CodeProZone, and get your queries like IPTC text classification example resolved professionally and stay updated to the latest Python updates.
