This program performs ETL between 9 supported data sources : Couchdb, Mongodb, Mysql, Mariadb, PostgreSQL, Netezza,Redshift, Sqlite, File
LICENSE (MIT)
Copyright 2016-2020, The Phi Technology LLC
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Usage :
transport --config <path-to-file.json> --procs <number-procs>
@TODO: Create tables if they don't exist for relational databases
# This function determines the most common delimiter from a subset of possible delimiters.
# It uses a statistical approach (distribution) to guage the distribution of columns for a given delimiter
# :sample sample string/content expecting matrix i.e list of rows
# """
# m = {',':[],'\t':[],'|':[],'\x3A':[]}
# delim = m.keys()
# for row in sample:
# for xchar in delim:
# if row.split(xchar) > 1:
# m[xchar].append(len(row.split(xchar)))
# else:
# m[xchar].append(0)
# #
# # The delimiter with the smallest variance, provided the mean is greater than 1
# # This would be troublesome if there many broken records sampled
# #
# m = {id: np.var(m[id]) for id in m.keys() if m[id] != [] and int(np.mean(m[id]))>1}
# index = m.values().index( min(m.values()))
# xchar = m.keys()[index]
# return xchar
# def col_count(self,sample):
# """
# This function retirms the number of columns of a given sample
# @pre self.xchar is not None
# """
# m = {}
# i = 0
# for row in sample:
# row = self.format(row)
# id = str(len(row))
# #id = str(len(row.split(self.xchar)))
# if id not in m:
# m[id] = 0
# m[id] = m[id] + 1
# index = m.values().index( max(m.values()) )
# ncols = int(m.keys()[index])
# return ncols;
# def format (self,row):
# """
# This function will clean records of a given row by removing non-ascii characters
# @pre self.xchar is not None
# """
# if isinstance(row,list) == False:
# #
# # We've observed sometimes fields contain delimiter as a legitimate character, we need to be able to account for this and not tamper with the field values (unless necessary)
# cols = self.split(row)
# #cols = row.split(self.xchar)
# else:
# cols = row ;
# return [ re.sub('[^\x00-\x7F,\n,\r,\v,\b,]',' ',col.strip()).strip().replace('"','') for col in cols]
# def split (self,row):
# """
# This function performs a split of a record and tries to attempt to preserve the integrity of the data within i.e accounting for the double quotes.
