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The goal of datasource is to abstract some of the file system operations when dealing with data files so the researcher doesn't have to know all the low-level details. Through datasource, a researcher can obtain and use a file with one function call, regardless of location of the file.

DataSource is meant to augment standard python libraries, not replace them. It should work seamlessly with standard file IO operations and the os module.

DataSource files can originate locally or remotely:

A file interface for handling local and remote data files.

A file interface for handling local and remote data files.

The goal of datasource is to abstract some of the file system operations when dealing with data files so the researcher doesn't have to know all the low-level details. Through datasource, a researcher can obtain and use a file with one function call, regardless of location of the file.

DataSource is meant to augment standard python libraries, not replace them. It should work seamlessly with standard file IO operations and the os module.

DataSource files can originate locally or remotely:

Examples

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

numpy.lib._datasource._FileOpeners

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them


GitHub : /numpy/lib/_datasource.py#0
type: <class 'module'>
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