Last active
May 6, 2019 12:45
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Luigi pipeline that:
1. Reads a tdf file using pandas with html on the 'content' column and created another tdf with just the text of the html (beautifulsoup)
2. Indexes the text into a Solr collection using mysolr
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import re | |
import json | |
import luigi | |
import pandas as pd | |
from mysolr import Solr | |
from bs4 import BeautifulSoup | |
class InputText(luigi.ExternalTask): | |
def output(self): | |
return luigi.LocalTarget('html.tdf') | |
class CleanHTML(luigi.Task): | |
def requires(self): | |
return InputText() | |
def output(self): | |
return luigi.LocalTarget('text.tdf') | |
def run(self): | |
df = pd.read_csv(self.input().open('r'), sep='\t') | |
df = df[df['content'].notnull()] | |
def clean(x): | |
x = re.sub(r'<br>', r'<br>\n', x) | |
x = re.sub(r'<br />', r'<br>\n', x) | |
x = re.sub(r'<br/>', r'<br>\n', x) | |
x = re.sub(r'<p>', r'\n<p>', x) | |
x = re.sub(r'</p>', r'</p>\n', x) | |
return BeautifulSoup(x, 'html.parser').getText(' ') | |
df['text'] = df['content'].apply(clean) | |
# output data | |
f = self.output().open('w') | |
df.to_csv(f, sep='\t', encoding='utf-8', index=None) | |
f.close() | |
class SolrIndex(luigi.Task): | |
def requires(self): | |
return CleanHTML() | |
def run(self): | |
df = pd.read_csv(self.input().open('r'), sep='\t') | |
df['id'] = df['url'] | |
solr = Solr('SOLR_HOST') | |
# Index 10 docs at a time | |
start = 0 | |
increment = 10 | |
while len(df[start:start+increment]) > 0: | |
sliced = df[start:start+increment] | |
docs = [] | |
for index, row in sliced.iterrows(): | |
doc = json.loads(row.to_json()) | |
docs.append(doc) | |
solr.update(docs, 'json') | |
if start % 1000 == 0: | |
# Just to see that is working | |
print start | |
start += increment | |
if __name__ == '__main__': | |
luigi.run() | |
# luigi.run(main_task_cls=CleanHTML) | |
# luigi.run(main_task_cls=SolrIndex) |
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