new file and documentation
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Steve Nyemba
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README.md
26
README.md
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# Introduction
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# Introduction
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This project implements an abstraction of objects that can have access to a variety of data stores, implementing read/write with a simple and expressive interface. This abstraction works with **NoSQL** and **SQL** data stores and leverages **pandas**
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This project implements an abstraction of objects that can have access to a variety of data stores, implementing read/write with a simple and expressive interface. This abstraction works with **NoSQL** and **SQL** data stores and leverages **pandas**.
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The supported data store providers :
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The supported data store providers :
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@ -44,12 +44,32 @@ The data-transport can be used within code as a library
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* Read/Write against [mongodb](https://github.com/lnyemba/data-transport/wiki/mongodb)
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* Read/Write against [mongodb](https://github.com/lnyemba/data-transport/wiki/mongodb)
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* Read/Write against tranditional [RDBMS](https://github.com/lnyemba/data-transport/wiki/rdbms)
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* Read/Write against tranditional [RDBMS](https://github.com/lnyemba/data-transport/wiki/rdbms)
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* Read/Write against [bigquery](https://github.com/lnyemba/data-transport/wiki/bigquery)
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* Read/Write against [bigquery](https://github.com/lnyemba/data-transport/wiki/bigquery)
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* ETL CLI/Code [ETL](https://github.com/lnyemba/data-transport/wiki/etl)
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The read/write functions make data-transport a great candidate for **data-science**; **data-engineering** or all things pertaining to data. It enables operations across multiple data-stores(relational or not)
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The read/write functions make data-transport a great candidate for **data-science**; **data-engineering** or all things pertaining to data. It enables operations across multiple data-stores(relational or not)
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## Command Line Interface (CLI)
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## ETL
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**Embedded in Code**
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It is possible to perform ETL within custom code as follows :
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```
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import transport
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import time
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_info = [{source:{'provider':'sqlite','path':'/home/me/foo.csv','table':'me'},target:{provider:'bigquery',private_key='/home/me/key.json','table':'me','dataset':'mydataset'}}, ...]
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procs = transport.factory.instance(provider='etl',info=_info)
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#
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#
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while procs:
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procs = [pthread for pthread in procs if pthread.is_alive()]
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time.sleep(1)
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```
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**Command Line Interface (CLI):**
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---
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---
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The CLI program is called **transport** and it requires a configuratio file
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The CLI program is called **transport** and it requires a configuration file. The program is intended to move data from one location to another. Supported data stores are in the above paragraphs.
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```
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```
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[
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[
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#!/usr/bin/env python
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__doc__ = """
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(c) 2018 - 2021 data-transport
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steve@the-phi.com, The Phi Technology LLC
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https://dev.the-phi.com/git/steve/data-transport.git
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This program performs ETL between 9 supported data sources : Couchdb, Mongodb, Mysql, Mariadb, PostgreSQL, Netezza,Redshift, Sqlite, File
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LICENSE (MIT)
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Copyright 2016-2020, The Phi Technology LLC
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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:
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The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
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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.
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Usage :
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transport --config <path-to-file.json> --procs <number-procs>
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@TODO: Create tables if they don't exist for relational databases
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example of configuration :
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1. Move data from a folder to a data-store
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transport [--folder <path> ] --config <config.json> #-- assuming the configuration doesn't have folder
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transport --folder <path> --provider <postgresql|mongo|sqlite> --<database|db> <name> --table|doc <document_name>
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In this case the configuration should look like :
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{folder:..., target:{}}
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2. Move data from one source to another
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transport --config <file.json>
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{source:{..},target:{..}} or [{source:{..},target:{..}},{source:{..},target:{..}}]
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"""
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import pandas as pd
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import numpy as np
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import json
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import sys
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import transport
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import time
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from multiprocessing import Process
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SYS_ARGS = {}
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if len(sys.argv) > 1:
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N = len(sys.argv)
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for i in range(1,N):
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value = None
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if sys.argv[i].startswith('--'):
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key = sys.argv[i][2:] #.replace('-','')
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SYS_ARGS[key] = 1
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if i + 1 < N:
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value = sys.argv[i + 1] = sys.argv[i+1].strip()
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if key and value and not value.startswith('--'):
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SYS_ARGS[key] = value
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i += 2
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class Post(Process):
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def __init__(self,**args):
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super().__init__()
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if 'provider' not in args['target'] :
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self.PROVIDER = args['target']['type']
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self.writer = transport.factory.instance(**args['target'])
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else:
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self.PROVIDER = args['target']['provider']
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args['target']['context'] = 'write'
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self.store = args['target']
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# self.writer = transport.instance(**args['target'])
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#
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# If the table doesn't exists maybe create it ?
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#
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self.rows = args['rows'].fillna('')
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def run(self):
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_info = {"values":self.rows} if 'couch' in self.PROVIDER else self.rows
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ltypes = self.rows.dtypes.values
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columns = self.rows.dtypes.index.tolist()
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# if not self.writer.has() :
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# self.writer.make(fields=columns)
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# ETL.logger.info(module='write',action='make-table',input={"name":self.writer.table})
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for name in columns :
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if _info[name].dtype in ['int32','int64','int','float','float32','float64'] :
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value = 0
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else:
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value = ''
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_info[name] = _info[name].fillna(value)
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writer = transport.factory.instance(**self.store)
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writer.write(_info)
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writer.close()
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class ETL (Process):
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logger = None
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def __init__(self,**_args):
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super().__init__()
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self.name = _args['id']
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if 'provider' not in _args['source'] :
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#@deprecate
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self.reader = transport.factory.instance(**_args['source'])
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else:
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#
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# This is the new interface
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_args['source']['context'] = 'read'
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self.reader = transport.instance(**_args['source'])
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#
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# do we have an sql query provided or not ....
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# self.sql = _args['source']['sql'] if 'sql' in _args['source'] else None
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self.cmd = _args['source']['cmd'] if 'cmd' in _args['source'] else None
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self._oargs = _args['target'] #transport.factory.instance(**_args['target'])
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self.JOB_COUNT = _args['jobs']
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self.jobs = []
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# self.logger = transport.factory.instance(**_args['logger'])
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def log(self,**_args) :
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_args['name'] = self.name
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print (_args)
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def run(self):
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if self.cmd :
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idf = self.reader.read(**self.cmd)
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else:
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idf = self.reader.read()
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idf = pd.DataFrame(idf)
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# idf = idf.replace({np.nan: None}, inplace = True)
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idf.columns = [str(name).replace("b'",'').replace("'","").strip() for name in idf.columns.tolist()]
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ETL.logger.info(rows=idf.shape[0],cols=idf.shape[1],jobs=self.JOB_COUNT)
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#
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# writing the data to a designated data source
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#
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try:
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ETL.logger.info(module='write',action='partitioning')
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rows = np.array_split(np.arange(0,idf.shape[0]),self.JOB_COUNT)
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#
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# @TODO: locks
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for i in np.arange(self.JOB_COUNT) :
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# _id = ' '.join([str(i),' table ',self.name])
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indexes = rows[i]
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segment = idf.loc[indexes,:].copy() #.to_dict(orient='records')
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if segment.shape[0] == 0 :
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continue
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proc = Post(target = self._oargs,rows = segment,name=str(i))
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self.jobs.append(proc)
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proc.start()
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ETL.logger.info(module='write',action='working',segment=str(id),table=self.name,rows=segment.shape[0])
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# while poc :
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# proc = [job for job in proc if job.is_alive()]
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# time.sleep(1)
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except Exception as e:
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print (e)
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def is_done(self):
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self.jobs = [proc for proc in self.jobs if proc.is_alive()]
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return len(self.jobs) == 0
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def instance(**_args):
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"""
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:param _info list of objects with {source,target}`
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:param logger
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"""
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logger = _args['logger'] if 'logger' in _args else None
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_info = _args['info']
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if logger :
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ETL.logger = logger
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else:
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ETL.logger = transport.factory.instance(provider='console',lock=True)
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if type(_info) in [list,dict] :
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_config = _info if type(_info) != dict else [_info]
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#
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# The assumption here is that the objects within the list are {source,target}
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jobs = []
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for _item in _info :
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_item['jobs'] = 5 if 'procs' not in _args else int(_args['procs'])
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_job = ETL(**_item)
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_job.start()
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jobs.append(_job)
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return jobs
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else:
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return None
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if __name__ == '__main__' :
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_info = json.loads(open (SYS_ARGS['config']).read())
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index = int(SYS_ARGS['index']) if 'index' in SYS_ARGS else None
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procs = []
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for _config in _info :
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if 'source' in SYS_ARGS :
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_config['source'] = {"type":"disk.DiskReader","args":{"path":SYS_ARGS['source'],"delimiter":","}}
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_config['jobs'] = 3 if 'jobs' not in SYS_ARGS else int(SYS_ARGS['jobs'])
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print (_config)
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print ()
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etl = ETL (**_config)
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if index is None:
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etl.start()
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procs.append(etl)
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elif _info.index(_config) == index :
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# print (_config)
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procs = [etl]
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etl.start()
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break
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#
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#
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N = len(procs)
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while procs :
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procs = [thread for thread in procs if not thread.is_done()]
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if len(procs) < N :
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print (["Finished ",(N-len(procs)), " remaining ", len(procs)])
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N = len(procs)
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time.sleep(1)
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# print ("We're done !!")
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