dataflows-shell 0.0.2

Integrate DataFlows with shell scripts

# DataFlows Shell

DataFlows Shell enhances [DataFlows](https://github.com/datahq/dataflows) with shell integration.

## Introduction

A lot of the work on the shell, especially for "DevOps" / automation type work, deals with data processing.
The first command a shell user learns is `ls` - which returns a set of data.
The second might by `grep` or `cp` - which filters and performs actions based on this data set.

DataFlows Shell brings the power of the [DataFlows]() data processing framework to the shell.

DataFlows Shell acts as a very minimal and intuitive layer between the shell, the DataFlows framework, and the [Frictionless Data Ecosystem](https://frictionlessdata.io/).

## Quickstart

The only required dependencies are Python3 and Bash

Install the dataflows-shell package

```
$ python3 -m pip install -U dataflows-shell
```

Import required dfs processors to the current shell

```
$ source <(dfs import printer filter_rows kubectl)
```

Run a processor chain to get a list of pods with a specified condition:

```
$ kubectl get pods -c -q \
| dfs 'lambda row: row.update(is_ckan="ckan" in str(row["volumes"]))' --fields=+is_ckan:boolean -q
| filter_rows --args='[[{"is_ckan":true}]]' -q
| printer --kwargs='{"fields":["kind","name","namespace"]}'
```

```
{'count_of_rows': 12, 'bytes': 57584, 'hash': '5febe0c3cfe75d174e242f290f00c289', 'dataset_name': None}
checkpoint:1
{'count_of_rows': 12, 'bytes': 57876, 'hash': '17f446a8f562f10cccc1de1a33c48d91', 'dataset_name': None}
checkpoint:2
{'count_of_rows': 6, 'bytes': 40797, 'hash': '6ab4290efd82478b1677d1f226c4199a', 'dataset_name': None}
checkpoint:3
saving checkpoint to: .dfs-checkpoints/__9
using checkpoint data from .dfs-checkpoints/__8
res_1:
# kind name namespace
(string) (string) (string)
--- ---------- ---------------------------- -----------
1 Pod ckan-5d74747649-92z9x odata-blue
2 Pod ckan-5d74747649-fzvd6 odata-blue
3 Pod ckan-jobs-5d895695cf-wgrzr odata-blue
4 Pod datastore-db-944bfbc74-2nc7b odata-blue
5 Pod db-7dd99b8547-vpf57 odata-blue
6 Pod pipelines-9f4466db-vlzm8 odata-blue
checkpoint saved: __9
{'count_of_rows': 6, 'bytes': 40798, 'hash': 'adc31744dfc99a0d8cbe7b081f31d78b', 'dataset_name': None}
checkpoint:9
```

## Documentation

* [DataFlows Shell Tutorial](TUTORIAL.md)
* [DataFlows Shell Reference](REFERENCE.md)
* [DataFlows Shell Processors Reference](processors/README.md)
* [DataFlows Processors Reference](https://github.com/datahq/dataflows/blob/master/PROCESSORS.md)