You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
280 lines
9.7 KiB
Python
280 lines
9.7 KiB
Python
5 years ago
|
# -*- coding: utf-8 -*-
|
||
|
# Natural Language Toolkit: Twitter client
|
||
|
#
|
||
|
# Copyright (C) 2001-2019 NLTK Project
|
||
|
# Author: Ewan Klein <ewan@inf.ed.ac.uk>
|
||
|
# Lorenzo Rubio <lrnzcig@gmail.com>
|
||
|
# URL: <http://nltk.org/>
|
||
|
# For license information, see LICENSE.TXT
|
||
|
|
||
|
"""
|
||
|
Utility functions for the :module:`twitterclient` module which do not require
|
||
|
the `twython` library to have been installed.
|
||
|
"""
|
||
|
from __future__ import print_function
|
||
|
|
||
|
import csv
|
||
|
import gzip
|
||
|
import json
|
||
|
|
||
|
from nltk import compat
|
||
|
|
||
|
HIER_SEPARATOR = "."
|
||
|
|
||
|
|
||
|
def extract_fields(tweet, fields):
|
||
|
"""
|
||
|
Extract field values from a full tweet and return them as a list
|
||
|
|
||
|
:param json tweet: The tweet in JSON format
|
||
|
:param list fields: The fields to be extracted from the tweet
|
||
|
:rtype: list(str)
|
||
|
"""
|
||
|
out = []
|
||
|
for field in fields:
|
||
|
try:
|
||
|
_add_field_to_out(tweet, field, out)
|
||
|
except TypeError:
|
||
|
raise RuntimeError(
|
||
|
'Fatal error when extracting fields. Cannot find field ', field
|
||
|
)
|
||
|
return out
|
||
|
|
||
|
|
||
|
def _add_field_to_out(json, field, out):
|
||
|
if _is_composed_key(field):
|
||
|
key, value = _get_key_value_composed(field)
|
||
|
_add_field_to_out(json[key], value, out)
|
||
|
else:
|
||
|
out += [json[field]]
|
||
|
|
||
|
|
||
|
def _is_composed_key(field):
|
||
|
if HIER_SEPARATOR in field:
|
||
|
return True
|
||
|
return False
|
||
|
|
||
|
|
||
|
def _get_key_value_composed(field):
|
||
|
out = field.split(HIER_SEPARATOR)
|
||
|
# there could be up to 3 levels
|
||
|
key = out[0]
|
||
|
value = HIER_SEPARATOR.join(out[1:])
|
||
|
return key, value
|
||
|
|
||
|
|
||
|
def _get_entity_recursive(json, entity):
|
||
|
if not json:
|
||
|
return None
|
||
|
elif isinstance(json, dict):
|
||
|
for key, value in json.items():
|
||
|
if key == entity:
|
||
|
return value
|
||
|
# 'entities' and 'extended_entities' are wrappers in Twitter json
|
||
|
# structure that contain other Twitter objects. See:
|
||
|
# https://dev.twitter.com/overview/api/entities-in-twitter-objects
|
||
|
|
||
|
if key == 'entities' or key == 'extended_entities':
|
||
|
candidate = _get_entity_recursive(value, entity)
|
||
|
if candidate is not None:
|
||
|
return candidate
|
||
|
return None
|
||
|
elif isinstance(json, list):
|
||
|
for item in json:
|
||
|
candidate = _get_entity_recursive(item, entity)
|
||
|
if candidate is not None:
|
||
|
return candidate
|
||
|
return None
|
||
|
else:
|
||
|
return None
|
||
|
|
||
|
|
||
|
def json2csv(
|
||
|
fp, outfile, fields, encoding='utf8', errors='replace', gzip_compress=False
|
||
|
):
|
||
|
"""
|
||
|
Extract selected fields from a file of line-separated JSON tweets and
|
||
|
write to a file in CSV format.
|
||
|
|
||
|
This utility function allows a file of full tweets to be easily converted
|
||
|
to a CSV file for easier processing. For example, just TweetIDs or
|
||
|
just the text content of the Tweets can be extracted.
|
||
|
|
||
|
Additionally, the function allows combinations of fields of other Twitter
|
||
|
objects (mainly the users, see below).
|
||
|
|
||
|
For Twitter entities (e.g. hashtags of a Tweet), and for geolocation, see
|
||
|
`json2csv_entities`
|
||
|
|
||
|
:param str infile: The name of the file containing full tweets
|
||
|
|
||
|
:param str outfile: The name of the text file where results should be\
|
||
|
written
|
||
|
|
||
|
:param list fields: The list of fields to be extracted. Useful examples\
|
||
|
are 'id_str' for the tweetID and 'text' for the text of the tweet. See\
|
||
|
<https://dev.twitter.com/overview/api/tweets> for a full list of fields.\
|
||
|
e. g.: ['id_str'], ['id', 'text', 'favorite_count', 'retweet_count']\
|
||
|
Additionally, it allows IDs from other Twitter objects, e. g.,\
|
||
|
['id', 'text', 'user.id', 'user.followers_count', 'user.friends_count']
|
||
|
|
||
|
:param error: Behaviour for encoding errors, see\
|
||
|
https://docs.python.org/3/library/codecs.html#codec-base-classes
|
||
|
|
||
|
:param gzip_compress: if `True`, output files are compressed with gzip
|
||
|
"""
|
||
|
(writer, outf) = outf_writer_compat(outfile, encoding, errors, gzip_compress)
|
||
|
# write the list of fields as header
|
||
|
writer.writerow(fields)
|
||
|
# process the file
|
||
|
for line in fp:
|
||
|
tweet = json.loads(line)
|
||
|
row = extract_fields(tweet, fields)
|
||
|
writer.writerow(row)
|
||
|
outf.close()
|
||
|
|
||
|
|
||
|
def outf_writer_compat(outfile, encoding, errors, gzip_compress=False):
|
||
|
"""
|
||
|
Identify appropriate CSV writer given the Python version
|
||
|
"""
|
||
|
if compat.PY3:
|
||
|
if gzip_compress:
|
||
|
outf = gzip.open(outfile, 'wt', encoding=encoding, errors=errors)
|
||
|
else:
|
||
|
outf = open(outfile, 'w', encoding=encoding, errors=errors)
|
||
|
writer = csv.writer(outf)
|
||
|
else:
|
||
|
if gzip_compress:
|
||
|
outf = gzip.open(outfile, 'wb')
|
||
|
else:
|
||
|
outf = open(outfile, 'wb')
|
||
|
writer = compat.UnicodeWriter(outf, encoding=encoding, errors=errors)
|
||
|
return (writer, outf)
|
||
|
|
||
|
|
||
|
def json2csv_entities(
|
||
|
tweets_file,
|
||
|
outfile,
|
||
|
main_fields,
|
||
|
entity_type,
|
||
|
entity_fields,
|
||
|
encoding='utf8',
|
||
|
errors='replace',
|
||
|
gzip_compress=False,
|
||
|
):
|
||
|
"""
|
||
|
Extract selected fields from a file of line-separated JSON tweets and
|
||
|
write to a file in CSV format.
|
||
|
|
||
|
This utility function allows a file of full Tweets to be easily converted
|
||
|
to a CSV file for easier processing of Twitter entities. For example, the
|
||
|
hashtags or media elements of a tweet can be extracted.
|
||
|
|
||
|
It returns one line per entity of a Tweet, e.g. if a tweet has two hashtags
|
||
|
there will be two lines in the output file, one per hashtag
|
||
|
|
||
|
:param tweets_file: the file-like object containing full Tweets
|
||
|
|
||
|
:param str outfile: The path of the text file where results should be\
|
||
|
written
|
||
|
|
||
|
:param list main_fields: The list of fields to be extracted from the main\
|
||
|
object, usually the tweet. Useful examples: 'id_str' for the tweetID. See\
|
||
|
<https://dev.twitter.com/overview/api/tweets> for a full list of fields.
|
||
|
e. g.: ['id_str'], ['id', 'text', 'favorite_count', 'retweet_count']
|
||
|
If `entity_type` is expressed with hierarchy, then it is the list of\
|
||
|
fields of the object that corresponds to the key of the entity_type,\
|
||
|
(e.g., for entity_type='user.urls', the fields in the main_fields list\
|
||
|
belong to the user object; for entity_type='place.bounding_box', the\
|
||
|
files in the main_field list belong to the place object of the tweet).
|
||
|
|
||
|
:param list entity_type: The name of the entity: 'hashtags', 'media',\
|
||
|
'urls' and 'user_mentions' for the tweet object. For a user object,\
|
||
|
this needs to be expressed with a hierarchy: `'user.urls'`. For the\
|
||
|
bounding box of the Tweet location, use `'place.bounding_box'`.
|
||
|
|
||
|
:param list entity_fields: The list of fields to be extracted from the\
|
||
|
entity. E.g. `['text']` (of the Tweet)
|
||
|
|
||
|
:param error: Behaviour for encoding errors, see\
|
||
|
https://docs.python.org/3/library/codecs.html#codec-base-classes
|
||
|
|
||
|
:param gzip_compress: if `True`, ouput files are compressed with gzip
|
||
|
"""
|
||
|
|
||
|
(writer, outf) = outf_writer_compat(outfile, encoding, errors, gzip_compress)
|
||
|
header = get_header_field_list(main_fields, entity_type, entity_fields)
|
||
|
writer.writerow(header)
|
||
|
for line in tweets_file:
|
||
|
tweet = json.loads(line)
|
||
|
if _is_composed_key(entity_type):
|
||
|
key, value = _get_key_value_composed(entity_type)
|
||
|
object_json = _get_entity_recursive(tweet, key)
|
||
|
if not object_json:
|
||
|
# this can happen in the case of "place"
|
||
|
continue
|
||
|
object_fields = extract_fields(object_json, main_fields)
|
||
|
items = _get_entity_recursive(object_json, value)
|
||
|
_write_to_file(object_fields, items, entity_fields, writer)
|
||
|
else:
|
||
|
tweet_fields = extract_fields(tweet, main_fields)
|
||
|
items = _get_entity_recursive(tweet, entity_type)
|
||
|
_write_to_file(tweet_fields, items, entity_fields, writer)
|
||
|
outf.close()
|
||
|
|
||
|
|
||
|
def get_header_field_list(main_fields, entity_type, entity_fields):
|
||
|
if _is_composed_key(entity_type):
|
||
|
key, value = _get_key_value_composed(entity_type)
|
||
|
main_entity = key
|
||
|
sub_entity = value
|
||
|
else:
|
||
|
main_entity = None
|
||
|
sub_entity = entity_type
|
||
|
|
||
|
if main_entity:
|
||
|
output1 = [HIER_SEPARATOR.join([main_entity, x]) for x in main_fields]
|
||
|
else:
|
||
|
output1 = main_fields
|
||
|
output2 = [HIER_SEPARATOR.join([sub_entity, x]) for x in entity_fields]
|
||
|
return output1 + output2
|
||
|
|
||
|
|
||
|
def _write_to_file(object_fields, items, entity_fields, writer):
|
||
|
if not items:
|
||
|
# it could be that the entity is just not present for the tweet
|
||
|
# e.g. tweet hashtag is always present, even as [], however
|
||
|
# tweet media may not be present
|
||
|
return
|
||
|
if isinstance(items, dict):
|
||
|
# this happens e.g. for "place" of a tweet
|
||
|
row = object_fields
|
||
|
# there might be composed keys in de list of required fields
|
||
|
entity_field_values = [x for x in entity_fields if not _is_composed_key(x)]
|
||
|
entity_field_composed = [x for x in entity_fields if _is_composed_key(x)]
|
||
|
for field in entity_field_values:
|
||
|
value = items[field]
|
||
|
if isinstance(value, list):
|
||
|
row += value
|
||
|
else:
|
||
|
row += [value]
|
||
|
# now check required dictionaries
|
||
|
for d in entity_field_composed:
|
||
|
kd, vd = _get_key_value_composed(d)
|
||
|
json_dict = items[kd]
|
||
|
if not isinstance(json_dict, dict):
|
||
|
raise RuntimeError(
|
||
|
"""Key {0} does not contain a dictionary
|
||
|
in the json file""".format(
|
||
|
kd
|
||
|
)
|
||
|
)
|
||
|
row += [json_dict[vd]]
|
||
|
writer.writerow(row)
|
||
|
return
|
||
|
# in general it is a list
|
||
|
for item in items:
|
||
|
row = object_fields + extract_fields(item, entity_fields)
|
||
|
writer.writerow(row)
|