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@@ -42,11 +42,13 @@ Once installed **data-transport** can be used as a library in code or a command
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## Data Transport as a Library (in code)
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---
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-The data-transport can be used within code as a library
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+The data-transport can be used within code as a library, and offers the following capabilities:
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+
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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 [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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+* Support for pre/post conditions i.e it is possible to specify queries to run before or after a read or write
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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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@@ -60,7 +62,7 @@ It is possible to perform ETL within custom code as follows :
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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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+ _info = [{source:{'provider':'sqlite','path':'/home/me/foo.csv','table':'me',"pipeline":{"pre":[],"post":[]}},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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