Two simple functions

• One used to convert an elastic search collection into a dataframe. See the code for the various parameters.
• One used to convert a dataframe into an elastic search collection

pip install elastic-helper

the pypi page (https://pypi.org/project/elastic-helper/):

• es -- The elastic connection object
• index -- The elastic index
• query -- (optional) The elastic query in lucene format Example: "module: *"
• start -- (optional) The time range start if any
• end -- (optional) The time range start if any
• timestampfield -- (optional) The timestamp field used by the start and stop parameters
• datecolumns -- (optional) A collection of columns that must be converted to dates
• scrollsize -- (optional) The size of the scroll to use
• size -- (optional) The maximum number of records to retrieve
• _source -- (optional) The fields to retrieve

from elastic_helper import es_helper 

dataframe=es_helper.elastic_to_dataframe(es,index="docker_stats*"
                                ,_source=['read', 'cpu_percent', 'name']
                                ,datecolumns=["read"]
                                ,timestampfield="read"
                                ,start=datetime.now()-timedelta(hours=1)
                                ,end=datetime.now())                                                               

• Use an _index column in the dataframe to specify the target index
• Use an _id column in the dataframe to specify the id

from elastic_helper import es_helper 

es_helper.dataframe_to_elastic(es,my_df)