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#!/usr/bin/env python
# -*- coding: utf-8 -*-
from __future__ import print_function
from os.path import dirname, basename, abspath
from itertools import chain
from datetime import datetime
import logging
import git
from elasticsearch import Elasticsearch
from elasticsearch.helpers import bulk, streaming_bulk
def create_git_index(client, index):
# create empty index
client.indices.create(
index=index,
body={
'settings': {
# just one shard, no replicas for testing
'number_of_shards': 1,
'number_of_replicas': 0,
# custom analyzer for analyzing file paths
'analysis': {
'analyzer': {
'file_path': {
'type': 'custom',
'tokenizer': 'path_hierarchy',
'filter': ['lowercase']
}
}
}
}
},
# ignore already existing index
ignore=400
)
# we will use user on several places
user_mapping = {
'properties': {
'name': {
'type': 'multi_field',
'fields': {
'raw': {'type' : 'string', 'index' : 'not_analyzed'},
'name': {'type' : 'string'}
}
}
}
}
client.indices.put_mapping(
index=index,
doc_type='repos',
body={
'repos': {
'properties': {
'owner': user_mapping,
'created_at': {'type': 'date'},
'description': {
'type': 'string',
'analyzer': 'snowball',
},
'tags': {
'type': 'string',
'index': 'not_analyzed'
}
}
}
}
)
client.indices.put_mapping(
index=index,
doc_type='commits',
body={
'commits': {
'_parent': {
'type': 'repos'
},
'properties': {
'author': user_mapping,
'authored_date': {'type': 'date'},
'committer': user_mapping,
'committed_date': {'type': 'date'},
'parent_shas': {'type': 'string', 'index' : 'not_analyzed'},
'description': {'type': 'string', 'analyzer': 'snowball'},
'files': {'type': 'string', 'analyzer': 'file_path'}
}
}
}
)
def parse_commits(repo, name):
"""
Go through the git repository log and generate a document per commit
containing all the metadata.
"""
for commit in repo.log():
yield {
'_id': commit.id,
'_parent': name,
'committed_date': datetime(*commit.committed_date[:6]),
'committer': {
'name': commit.committer.name,
'email': commit.committer.email,
},
'authored_date': datetime(*commit.authored_date[:6]),
'author': {
'name': commit.author.name,
'email': commit.author.email,
},
'description': commit.message,
'parent_shas': [p.id for p in commit.parents],
# we only care about the filenames, not the per-file stats
'files': list(chain(commit.stats.files)),
'stats': commit.stats.total,
}
def load_repo(client, path=None, index='git'):
"""
Parse a git repository with all it's commits and load it into elasticsearch
using `client`. If the index doesn't exist it will be created.
"""
path = dirname(dirname(abspath(__file__))) if path is None else path
repo_name = basename(path)
repo = git.Repo(path)
create_git_index(client, index)
# create the parent document in case it doesn't exist
client.create(
index=index,
doc_type='repos',
id=repo_name,
body={},
ignore=409 # 409 - conflict - would be returned if the document is already there
)
# we let the streaming bulk continuously process the commits as they come
# in - since the `parse_commits` function is a generator this will avoid
# loading all the commits into memory
for ok, result in streaming_bulk(
client,
parse_commits(repo, repo_name),
index=index,
doc_type='commits',
chunk_size=50 # keep the batch sizes small for appearances only
):
action, result = result.popitem()
doc_id = '/%s/commits/%s' % (index, result['_id'])
# process the information from ES whether the document has been
# successfully indexed
if not ok:
print('Failed to %s document %s: %r' % (action, doc_id, result))
else:
print(doc_id)
# we manually create es repo document and update elasticsearch-py to include metadata
REPO_ACTIONS = [
{'_type': 'repos', '_id': 'elasticsearch', '_source': {
'owner': {'name': 'Shay Bannon', 'email': 'kimchy@gmail.com'},
'created_at': datetime(2010, 2, 8, 15, 22, 27),
'tags': ['search', 'distributed', 'lucene'],
'description': 'You know, for search.'}
},
{'_type': 'repos', '_id': 'elasticsearch-py', '_op_type': 'update', 'doc': {
'owner': {'name': 'Honza Král', 'email': 'honza.kral@gmail.com'},
'created_at': datetime(2013, 5, 1, 16, 37, 32),
'tags': ['elasticsearch', 'search', 'python', 'client'],
'description': 'For searching snakes.'}
},
]
if __name__ == '__main__':
# get trace logger and set level
tracer = logging.getLogger('elasticsearch.trace')
tracer.setLevel(logging.INFO)
tracer.addHandler(logging.FileHandler('/tmp/es_trace.log'))
# instantiate es client, connects to localhost:9200 by default
es = Elasticsearch()
# we load the repo and all commits
load_repo(es)
# run the bulk operations
success, _ = bulk(es, REPO_ACTIONS, index='git', raise_on_error=True)
print('Performed %d actions' % success)
# now we can retrieve the documents
es_repo = es.get(index='git', doc_type='repos', id='elasticsearch')
print('%s: %s' % (es_repo['_id'], es_repo['_source']['description']))
# update - add java to es tags
es.update(
index='git',
doc_type='repos',
id='elasticsearch',
body={
"script" : "ctx._source.tags += tag",
"params" : {
"tag" : "java"
}
}
)
# refresh to make the documents available for search
es.indices.refresh(index='git')
# and now we can count the documents
print(es.count(index='git')['count'], 'documents in index')
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