From: Kaylea Champion Date: Sat, 28 Mar 2020 21:46:00 +0000 (-0700) Subject: Merge branch 'master' of https://github.com/CommunityDataScienceCollective/COVID... X-Git-Url: https://code.communitydata.science/covid19.git/commitdiff_plain/7b3062ffb143aa1dbd55f4bd1b9e22603622d2b9?hp=ed0641ecc715b4678ff866ce8aa6bd60c84fbca5 Merge branch 'master' of https://github.com/CommunityDataScienceCollective/COVID-19_Digital_Observatory --- diff --git a/transliterations/README.md b/transliterations/README.md new file mode 100644 index 0000000..18df219 --- /dev/null +++ b/transliterations/README.md @@ -0,0 +1,3 @@ +# Transliterations + +This part of the project collects tranliterations of key phrases related to COVID-19 using Wikidata. We search the Wikidata API for entities in `src/wikidata_search.py` and then we make simple SPARQL queries in `src/wikidata_transliterations.py` to collect labels and aliases the entities. The labels come with language metadata. This seems to provide a decent initial list of relevant terms across multiple languages. diff --git a/transliterations/analysis/output/top5_queries_per_term_per_date.csv b/transliterations/analysis/output/top5_queries_per_term_per_date.csv new file mode 100644 index 0000000..5ce1aa7 --- /dev/null +++ b/transliterations/analysis/output/top5_queries_per_term_per_date.csv @@ -0,0 +1,6 @@ +"term","date","query.1","query.2","query.3","query.4","query.5" +"coronavirus","2020-03-27",coronavirus update,corona,coronavirus symptoms,news coronavirus,coronavirus cases +"covid-19","2020-03-27",covid-19 coronavirus,coronavirus,covid,covid-19 cases,covid 19 +"covid-19 pandemic","2020-03-27",coronavirus,covid-19 coronavirus pandemic,coronavirus pandemic,who,is covid-19 a pandemic +"covid19","2020-03-27",covid,covid 19,coronavirus covid19,coronavirus,covid19 cases +"sars-cov-2","2020-03-27",coronavirus,coronavirus sars-cov-2,covid-19,covid-19 sars-cov-2,sars diff --git a/transliterations/analysis/related_searches_example.R b/transliterations/analysis/related_searches_example.R new file mode 100644 index 0000000..2576d4a --- /dev/null +++ b/transliterations/analysis/related_searches_example.R @@ -0,0 +1,28 @@ +### COVID-19 Digital Observatory +### 2020-03-28 +### +### Minimal example analysis file using trending search data + +### Identify data source directory and file +DataDir <- ("../data/output/") +DataFile <- ("related_searches_top.csv") + +### Import and cleanup data +related.searches.top <- read.table(paste(DataDir,DataFile, + sep=""), + sep=",", header=TRUE, + stringsAsFactors=FALSE) + +### Aggregate top 5 search queries by term/day +top5.per.term.date <- aggregate(query ~ term + date, + data=related.searches.top, + head, 5) + +## Might cleanup a bit for further analysis or visualization... +top5.per.term.date$date <- as.Date(top5.per.term.date$date) + +### Export +write.table(top5.per.term.date, + file="output/top5_queries_per_term_per_date.csv", sep=",", + row.names=FALSE) + diff --git a/transliterations/data/input/base_terms.txt b/transliterations/data/input/base_terms.txt new file mode 100644 index 0000000..2d5f865 --- /dev/null +++ b/transliterations/data/input/base_terms.txt @@ -0,0 +1,6 @@ +coronavirus +covid-19 +covid19 +sars-cov-2 +covid-19 pandemic +sars-cov-2 pandemic diff --git a/transliterations/data/output/2020-03-27_wikidata_entity_labels.csv b/transliterations/data/output/2020-03-27_wikidata_entity_labels.csv new file mode 100644 index 0000000..035827b --- /dev/null +++ b/transliterations/data/output/2020-03-27_wikidata_entity_labels.csv @@ -0,0 +1,9300 @@ +entityid,label,langcode,is_alt +http://www.wikidata.org/entity/Q15089,província d'Itàlia,ca,False +http://www.wikidata.org/entity/Q15089,Italienische Provinz,de,False +http://www.wikidata.org/entity/Q15089,επαρχία της Ιταλίας,el,False +http://www.wikidata.org/entity/Q15089,province of Italy,en,False 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+covid-19 symptoms,Q87369504,86603314,1,2020-03-28T21:01:30Z +covid-19 updates,Q87461514,86691755,0,2020-03-28T21:01:31Z +covid-19 updates,Q87223238,86459413,1,2020-03-28T21:01:31Z diff --git a/transliterations/requirements.txt b/transliterations/requirements.txt new file mode 100644 index 0000000..46b2967 --- /dev/null +++ b/transliterations/requirements.txt @@ -0,0 +1,2 @@ +pytrends>=4.7.2 +mwapi>=0.5.1 diff --git a/transliterations/src/__init__.py b/transliterations/src/__init__.py new file mode 100644 index 0000000..5211ac6 --- /dev/null +++ b/transliterations/src/__init__.py @@ -0,0 +1,2 @@ +from wikidata_api_calls import * +from find_entities import * diff --git a/transliterations/src/collect_trends.py b/transliterations/src/collect_trends.py new file mode 100644 index 0000000..16a5c93 --- /dev/null +++ b/transliterations/src/collect_trends.py @@ -0,0 +1,76 @@ +# this follows a similar approach to nick's trends.js but in python +from pytrends.request import TrendReq +from datetime import datetime +from os import path +import csv +from itertools import islice, chain, zip_longest +import pandas as pd + + +# from itertools recipes +#https://docs.python.org/3.6/library/itertools.html#itertools-recipes +def grouper(iterable, n, fillvalue=None): + "Collect data into fixed-length chunks or blocks" + # grouper('ABCDEFG', 3, 'x') --> ABC DEF Gxx" + args = [iter(iterable)] * n + return zip_longest(*args, fillvalue=fillvalue) + +def get_daily_trends(): + trendReq = TrendReq(backoff_factor=0.2) + today_trending = trendReq.today_searches() + daily_trends_outfile = path.join("..","data","output","daily_google_trends.csv") + + write_header = False + header = ['date','term','top'] + + if not path.exists(daily_trends_outfile): + write_header = True + + with open("../data/output/daily_google_trends.csv",'a',newline='') as of: + writer = csv.writer(of) + if write_header: + writer.writerow(header) + + for i, trend in enumerate(today_trending): + writer.writerow([str(datetime.now().date()),trend,i]) + +def get_related_queries(stems): + # we have to batch these in sets of 5 + trendReq = TrendReq(backoff_factor=0.2) + def _get_related_queries(chunk): + kw_list = list(filter(lambda x: x is not None, chunk)) + trendReq.build_payload(kw_list=kw_list) + related_queries = trendReq.related_queries() + for term, results in related_queries.items(): + for key, df in results.items(): + if df is not None: + df["term"] = term + yield (key,df) + + l = chain(*map(_get_related_queries, grouper(stems,5))) + out = {} + for key, value in l: + if key in out: + out[key].append(value) + else: + out[key] = [value] + + for k in out.keys(): + df = pd.concat(out[k]) + df['date'] = str(datetime.now().date()) + out[k] = df + outfile = path.join('..','data','output',f"related_searches_{k}.csv") + if path.exists(outfile): + mode = 'a' + header = False + else: + mode = 'w' + header = True + + df.to_csv(outfile, mode=mode, header=header,index=False) + +stems = [t.strip() for t in open("../data/input/base_terms.txt",'r')] + +get_daily_trends() + +get_related_queries(stems) diff --git a/transliterations/src/compile_transliterated_phrases.sh b/transliterations/src/compile_transliterated_phrases.sh new file mode 100755 index 0000000..55fe211 --- /dev/null +++ b/transliterations/src/compile_transliterated_phrases.sh @@ -0,0 +1,16 @@ +#!/bin/bash + +# For now these scripts don't accept command line arguments. It's an MVP + +echo "Reading Google trends" +python3 collect_trends.py + +echo "Searching for Wikidata entities using base_terms.txt" +python3 wikidata_search.py ../data/input/base_terms.txt --output ../data/output/wikidata_search_results.csv + +echo "Searching for Wikidata entities using Google trends" +python3 wikidata_search.py ../data/output/related_searches_rising.csv ../data/output/related_searches_top.csv --use-gtrends --output ../data/output/wikidata_search_results_from_gtrends.csv + +echo "Finding transliterations from Wikidata using sparql" +python3 wikidata_transliterations.py ../data/output/wikidata_search_results_from_gtrends.csv ../data/output/wikidata_search_results.csv --topN 10 20 --output ../data/output/$(date '+%Y-%m-%d')_wikidata_entity_labels.csv + diff --git a/transliterations/src/defaults.py b/transliterations/src/defaults.py new file mode 100644 index 0000000..3d6168f --- /dev/null +++ b/transliterations/src/defaults.py @@ -0,0 +1 @@ +user_agent = "COVID-19 Digital Observatory, a Community Data Science Collective project. (https://github.com/CommunityDataScienceCollective/COVID-19_Digital_Observatory)" diff --git a/transliterations/src/wikidata_api_calls.py b/transliterations/src/wikidata_api_calls.py new file mode 100644 index 0000000..212ed4f --- /dev/null +++ b/transliterations/src/wikidata_api_calls.py @@ -0,0 +1,35 @@ +# File defines functions for making api calls to find translations and transliterations for key terms. +import mwapi +import requests +import sys +import time +from defaults import user_agent + +def get_wikidata_api(): + session = mwapi.Session(host="https://wikidata.org/w/api.php", user_agent=user_agent) + return session + +def search_wikidata(session, term, *args, **kwargs): + search_results = session.get(action='query', + list='search', + srsearch=term, +# srqiprofile='popular_inclinks_pv', + srlimit='max', + srnamespace=0, + *args, + **kwargs) + + + query = search_results.get('query', None) + results = query.get('search', None) + + if results is None: + raise mwapi.session.APIError(f"No results for query: {term}") + + return results + +def run_sparql_query(q): + results = requests.get("https://query.wikidata.org/bigdata/namespace/wdq/sparql",params={"format":"json","query":q}) + time.sleep(2) + return results + diff --git a/transliterations/src/wikidata_search.py b/transliterations/src/wikidata_search.py new file mode 100644 index 0000000..a3abbc0 --- /dev/null +++ b/transliterations/src/wikidata_search.py @@ -0,0 +1,95 @@ +# generate a list of wikidata entities related to keywords +from os import path +from sys import stdout +from wikidata_api_calls import search_wikidata, get_wikidata_api +import csv +from itertools import chain + +class Wikidata_ResultSet: + def __init__(self): + self.results = [] + + def extend(self, term, results): + self.results.append( + (Wikidata_Result(term, result, i) + for i, result in enumerate(results)) + ) + + def to_csv(self, outfile=None, mode='w'): + if outfile is None: + of = stdout + + else: + if path.exists(outfile) and mode != 'w': + of = open(outfile,'a',newline='') + else: + of = open(outfile,'w',newline='') + writer = csv.writer(of) + writer.writerow(Wikidata_Result.__slots__) + writer.writerows(map(Wikidata_Result.to_list, chain(* self.results))) + + +class Wikidata_Result: + # store unique entities found in the search results, the position in the search result, and the date + __slots__=['search_term','entityid','pageid','search_position','timestamp'] + + def __init__(self, + term, + search_result, + position): + + self.search_term = term.strip() + self.entityid = search_result['title'] + self.pageid = int(search_result['pageid']) + self.search_position = int(position) + self.timestamp = search_result['timestamp'] + + def to_list(self): + return [self.search_term, + self.entityid, + self.pageid, + self.search_position, + self.timestamp] + +def run_wikidata_searches(terms): + api = get_wikidata_api() + resultset = Wikidata_ResultSet() + for term in terms: + search_results = search_wikidata(api, term) + resultset.extend(term, search_results) + return resultset + +def read_google_trends_files(terms_files): + def _read_file(infile): + return csv.DictReader(open(infile,'r',newline='')) + + for row in chain(* [_read_file(terms_file) for terms_file in terms_files]): + yield row['query'] + + +def trawl_google_trends(terms_files, outfile = None, mode='w'): + terms = list(read_google_trends_files(terms_files)) + resultset = run_wikidata_searches(terms) + resultset.to_csv(outfile, mode) + +def trawl_base_terms(infiles, outfile = None, mode='w'): + terms = list(chain(* (open(infile,'r') for infile in infiles))) + resultset = run_wikidata_searches(terms) + resultset.to_csv(outfile, mode) + + ## search each of the base terms in wikidata + + # store unique entities found in the search results, the position in the search result, and the date + +if __name__ == "__main__": + import argparse + parser = argparse.ArgumentParser("Search wikidata for entities related to a set of terms.") + parser.add_argument('inputs', type=str, nargs='+', help='one or more files to read') + parser.add_argument('--use-gtrends', action='store_true', help = 'toggle whether the input is the output from google trends') + parser.add_argument('--output', type=str, help='an output file. defaults to stdout') + parser.add_argument('--overwrite', action='store_true', help = 'overwrite existing output files instead of appending') + args = parser.parse_args() + if args.use_gtrends: + trawl_google_trends(args.inputs, args.output) + else: + trawl_base_terms(args.inputs, args.output) diff --git a/transliterations/src/wikidata_transliterations.py b/transliterations/src/wikidata_transliterations.py new file mode 100644 index 0000000..0856c9c --- /dev/null +++ b/transliterations/src/wikidata_transliterations.py @@ -0,0 +1,96 @@ +from wikidata_api_calls import run_sparql_query +from itertools import chain, islice +import csv +from json import JSONDecodeError + +class LabelData: + __slots__ = ['entityid','label','langcode','is_alt'] + + def __init__(self, wd_res, is_alt): + obj = wd_res.get('label',None) + self.label = obj.get('value',None) + self.langcode = obj.get('xml:lang',None) + self.entityid = wd_res.get('entity',None).get('value',None) + self.is_alt = is_alt + + def to_list(self): + return [self.entityid, + self.label, + self.langcode, + self.is_alt] + +def GetAllLabels(in_csvs, outfile, topNs): + + def load_entity_ids(in_csv, topN=5): + with open(in_csv,'r',newline='') as infile: + reader = list(csv.DictReader(infile)) + for row in reader: + if int(row['search_position']) < topN: + yield row["entityid"] + + ids = set(chain(* map(lambda in_csv, topN: load_entity_ids(in_csv, topN), in_csvs, topNs))) + + labeldata = GetEntityLabels(ids) + + with open(outfile, 'w', newline='') as of: + writer = csv.writer(of) + writer.writerow(LabelData.__slots__) + writer.writerows(map(LabelData.to_list,labeldata)) + + +def GetEntityLabels(entityids): + + def run_query_and_parse(query, is_alt): + results = run_sparql_query(query) + try: + jobj = results.json() + + res = jobj.get('results',None) + if res is not None: + res = res.get('bindings',None) + if res is None: + raise requests.APIError(f"got invalid response from wikidata for {query % entityid}") + + for info in res: + yield LabelData(info, is_alt) + + except JSONDecodeError as e: + print(e) + print(query) + + def prep_query(query, prop, entityids): + values = ' '.join(('wd:{0}'.format(id) for id in entityids)) + return query.format(prop, values) + + base_query = """ + SELECT DISTINCT ?entity ?label WHERE {{ + ?entity {0} ?label; + VALUES ?entity {{ {1} }} + }}""" + + # we can't get all the entities at once. how about 100 at a time? + chunksize = 100 + entityids = (id for id in entityids) + chunk = list(islice(entityids, chunksize)) + calls = [] + while len(chunk) > 0: + label_query = prep_query(base_query, "rdfs:label", chunk) + altLabel_query = prep_query(base_query, "skos:altLabel", chunk) + label_results = run_query_and_parse(label_query, is_alt=False) + altLabel_results = run_query_and_parse(altLabel_query, is_alt=True) + calls.extend([label_results, altLabel_results]) + chunk = list(islice(entityids, chunksize)) + + return chain(*calls) + + +if __name__ == "__main__": + import argparse + parser = argparse.ArgumentParser("Use wikidata to find transliterations of terms") + parser.add_argument('inputs', type=str, nargs='+', help='one or more files to read. the inputs are generated by wikidata_search.py') + parser.add_argument('--topN', type=int, nargs='+', help='limit number of wikidata search results to use, can pass one arg for each source.') + parser.add_argument('--output', type=str, help='an output file. defaults to stdout',default=20) + + args = parser.parse_args() + + GetAllLabels(args.inputs, args.output, topNs=args.topN) diff --git a/data/dailyviews2020032600.json b/wikipedia_views/data/dailyviews2020032600.json similarity index 100% rename from data/dailyviews2020032600.json rename to wikipedia_views/data/dailyviews2020032600.json diff --git a/data/dailyviews2020032600.tsv b/wikipedia_views/data/dailyviews2020032600.tsv similarity index 100% rename from data/dailyviews2020032600.tsv rename to wikipedia_views/data/dailyviews2020032600.tsv diff --git a/resources/articles.txt b/wikipedia_views/resources/articles.txt similarity index 100% rename from resources/articles.txt rename to wikipedia_views/resources/articles.txt diff --git a/bin/fetch_daily_views.py b/wikipedia_views/scripts/fetch_daily_views.py similarity index 67% rename from bin/fetch_daily_views.py rename to wikipedia_views/scripts/fetch_daily_views.py index ac925ed..b604e26 100755 --- a/bin/fetch_daily_views.py +++ b/wikipedia_views/scripts/fetch_daily_views.py @@ -10,12 +10,6 @@ ############################################################################### -#1 Load up the list of article names - -#2 Repeatedly call the API with that list of names - -#3 Save results as a TSV - import requests import argparse import json @@ -26,7 +20,6 @@ import datetime #import feather - def parse_args(): parser = argparse.ArgumentParser(description='Call the views API repeatedly.') @@ -55,31 +48,32 @@ def main(): articleList = [] - with open(articleFile, 'r') as infileHandle: - #theInfile = csv.reader(infileHandle, quotechar='"') - theInfile = csv.reader(infileHandle) - next(theInfile) #skip header - for currentLine in theInfile: - articleList.append(currentLine) + #1 Load up the list of article names + + j_Out = f"{outputPath}dailyviews{queryDate}.json" + t_Out = f"{outputPath}dailyviews{queryDate}.tsv" - j_Out = outputPath + "dailyviews" + queryDate + ".json" - t_Out = outputPath + "dailyviews" + queryDate + ".tsv" + with open(articleFile, 'r') as infile: + next(infile) #skip header + articleList = list(infile) j = [] - i = 0 #iterator to deal with end of file + #2 Repeatedly call the API with that list of names for a in articleList: - a = a[0] #destringify - i = i+1 - url= "https://wikimedia.org/api/rest_v1/metrics/pageviews/per-article/en.wikipedia/all-access/all-agents/" - url= url + a + "/daily/" + queryDate + "/" + queryDate #for now, single date at a time + a = a.strip("\"\n") #destringify + url= f"https://wikimedia.org/api/rest_v1/metrics/pageviews/per-article/en.wikipedia/all-access/all-agents/{a}/daily/{queryDate}/{queryDate}" + response = requests.get(url) if response.ok: jd = json.loads(response.content) j.append(jd["items"][0]) time.sleep(.1) + else: + print(f"Not ok response: {response.status_code} from {url}") + #3 Save results as a JSON and TSV #all data in j now, make json file with open(j_Out, 'w') as j_outfile: @@ -91,8 +85,8 @@ def main(): dw.writerows(j) - f_Out = outputPath + "dailyviews" + queryDate + ".feather" - #read the json back in and make a feather file? + # f_Out = outputPath + "dailyviews" + queryDate + ".feather" + # read the json back in and make a feather file? if __name__ == "__main__":