Metadata-Version: 2.1
Name: spectron
Version: 0.1.7
Summary: AWS Redshift Spectrum utilities.
Home-page: https://github.com/j4c0bs/spectron
Author: Jeremy Jacobs
Author-email: pub@j4c0bs.net
License: UNKNOWN
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: black (>=19.10b0)
Provides-Extra: json
Requires-Dist: ujson (>=1.35) ; extra == 'json'

# [WIP] spectron

Generate AWS Spectrum DDL from JSON


## CLI Usage:

```
spectron -lj nested_big_data.json > nested_big_data.sql
```

---

```
auto generate Spectrum DDL from JSON

positional arguments:
  infile                JSON to convert

optional arguments:
  -h, --help            show this help message and exit
  -v, --version         show program's version number and exit
  -r, --retain_hyphens  disable auto convert hypens to underscores
  -l, --lowercase       enable case insensitivity and force all fields to
                        lowercase - applied before field lookup in mapping
  -e, --error_nested_arrarys
                        raise exception for nested arrays
  -m MAPPING_FILE, --mapping MAPPING_FILE
                        JSON filepath to use for mapping field names e.g.
                        {field_name: new_field_name}
  -y TYPE_MAP_FILE, --type_map TYPE_MAP_FILE
                        JSON filepath to use for mapping field names to known
                        data types e.g. {key: value}
  -f IGNORE_FIELDS, --ignore_fields IGNORE_FIELDS
                        Comma separated fields to ignore
  -p PARTITIONS_FILE, --partitions_file PARTITIONS_FILE
                        DDL: JSON filepath to map parition column(s) e.g.
                        {column: dtype}
  -j, --ignore_malformed_json
                        DDL: ignore malformed json
  -s SCHEMA, --schema SCHEMA
                        DDL: schema name
  -t TABLE, --table TABLE
                        DDL: table name
  --s3 S3_KEY           DDL: S3 Key prefix e.g. bucket/dir
  ```


