Metadata-Version: 2.1
Name: tableconv
Version: 1.9697.20211202
Summary: CLI data plumbing tool
Home-page: https://github.com/Ridecell/tableconv
Author: John Miller
Author-email: john@johngm.com
License: MIT
Description: 
        # tableconv
        
        tableconv converts tabular data from any format to any format.
        
        ## Install
        
        ```
        pip install tableconv
        ```
        
        ## Usage
        
        ```
        usage: tableconv SOURCE_URL [-q QUERY_SQL] [-o DEST_URL]
        
        positional arguments:
          SOURCE_URL            Specify the data source URL.
        
        optional arguments:
          -h, --help            show this help message and exit
          -q SOURCE_QUERY, --query SOURCE_QUERY
                                Query to run on the source. Even for non-SQL datasources (e.g. csv or json), SQL querying is still supported, try `SELECT * FROM data`.
          -F INTERMEDIATE_FILTER_SQL, --filter INTERMEDIATE_FILTER_SQL
                                Filter (aka transform) the input data using a SQL query operating on the dataset in memory using DuckDB SQL.
          -o DEST_URL, --dest DEST_URL, --out DEST_URL
                                Specify the data destination URL. If this destination already exists, be aware that the default behavior is to overwrite.
          -i, --interactive     Enter interactive REPL query mode
          --open                Open resulting file/url (not supported for all destination types)
          -v, --verbose, --debug
                                Show debug details, including all API calls.
          --quiet               Only display errors.
        
        supported url schemes:
        - ascii:- (dest only)
        - asciibox:- (dest only)
        - asciifancygrid:- (dest only)
        - asciigrid:- (dest only)
        - asciilite:- (dest only)
        - asciipipe:- (dest only)
        - asciiplain:- (dest only)
        - asciipresto:- (dest only)
        - asciipretty:- (dest only)
        - asciipsql:- (dest only)
        - asciisimple:- (dest only)
        - awsathena://eu-central-1 
        - awsdynamodb://eu-central-1/example_table (source only)
        - csa:- 
        - example.csv 
        - example.dta 
        - example.feather 
        - example.h5 
        - example.hdf5 
        - example.json 
        - example.jsonl 
        - example.orc (source only)
        - example.parquet 
        - example.py 
        - example.python 
        - example.tsv 
        - example.xls 
        - example.xlsx 
        - example.yaml 
        - gsheets://:new: 
        - html:- (dest only)
        - jiracloud://mycorpname (source only)
        - jsonarray:- 
        - latex:- (dest only)
        - list:- 
        - markdown:- (dest only)
        - md:- (dest only)
        - mediawikiformat:- (dest only)
        - moinmoinformat:- (dest only)
        - mssql://127.0.0.1:5432/example_db 
        - mysql://127.0.0.1:5432/example_db 
        - oracle://127.0.0.1:5432/example_db 
        - postgis://127.0.0.1:5432/example_db 
        - postgres://127.0.0.1:5432/example_db 
        - postgresql://127.0.0.1:5432/example_db 
        - pylist:- 
        - rst:- (dest only)
        - smartsheet://SHEET_ID (source only)
        - sqlite3://127.0.0.1:5432/example_db 
        - sqlite://127.0.0.1:5432/example_db 
        - sumologic://?from=2021-03-01T00:00:00Z&to=2021-05-03T00:00:00Z (source only)
        - tex:- (dest only)
        - yamlsequence:-
        ```
        
        ## Examples
        
        ### Basic conversion
        
        Convert JSON to CSV
        
        ```
        tableconv test.json -o test.csv
        ```
        
        Convert CSV to JSON
        
        ```
        tableconv test.csv -o test.json
        ```
        
        Dump a postgres table as JSON
        
        ```
        tableconv postgresql://192.168.0.10:5432/test_db/my_table -o my_table.json
        ```
        
        Display a parquet file's data in a human-readable format
        
        ```
        tableconv test.parquet -o ascii:-
        ```
        
        Convert CSV to a Markdown table
        
        ```
        tableconv test.csv -o md:-
        ```
        
        ### Data transformation with SQL
        
        Dump the first 100 rows of a postgres table as JSON
        
        ```
        tableconv postgresql://192.168.0.10:5432/test_db -q 'SELECT * FROM my_table ORDER BY id LIMIT 100' -o my_table.json
        ```
        
        Copy a few columns from one CSV into a new CSV.
        (in general, all functionality works on all of the supported data formats. So you can of course query with SQL on an Oracle database but it's also supported to query with SQL on JSON, SQL on Excel, and, here SQL on CSV)
        
        ```
        tableconv test.csv -q 'SELECT time, name FROM data ORDER BY time DESC' -o output.csv
        ```
        
        Append a few columns from a CSV into MySQL
        
        ```
        tableconv test.csv -q 'SELECT time, name FROM data ORDER BY time DESC' -o mysql://localhost:3306/test_db/my_table?if_exists=append
        ```
        
        Extract a report from a SQLite database into a new Google Spreadsheet
        
        ```
        tableconv sqlite3://my_db.db -q 'SELECT name, COUNT(*) from occurences ORDER BY 2 DESC LIMIT 10' -o "gsheets://:new:/?name=top_occurences_$(date +'%Y_%m_%d')"
        ```
        
        ### Interactive mode
        
        Launch an interactive SQL shell to inspect data from a CSV file in the terminal
        
        ```
        tableconv test.csv -i -o ascii:-
        ```
        
        ### Arrays
        
        Convert a copy/pasted newline-deliminated list into a python list
        
        ```
        pbpaste | tableconv list:- -o python:-
        ```
        
        
        ## Details
        
        As a prototype, tableconv is usable as a quick and dirty CLI ETL tool for converting data between any of the formats, or usable for performing basic bulk data transformations and joins defined in a unified language (SQL) but operating across disparate data in wildly different formats. That is the immediate value proposition of tableconv, but it was created within the mental framework of a larger vision: The tableconv vision of computing is that all software fundamentally interfaces via data tables; that all UIs and APIs can be interpreted as data frames or data tables. Instead of requiring power users to learn interface after interface and build their own bespoke tooling to extract and manipulate the data at scale in each interface, the world needs a highly interoperable operating system level client for power users to directly interact with, join, and manipulate the data with SQL (or similar) using the universal "table" abstraction provided in a consistent UI across each service. Tableconv is that tool. It is meant to have adapters written to support any/all services and data formats.
        
        However, this is just a prototype. The software is slow in all ways and memory+cpu intensive. It has no streaming support and loads all data into memory before converting it. Its most efficient adapters cannot handle tables over 10 million cells, and the least efficient cannot handle over 100000 cells. Schemas can migrate inconsistently depending upon the data available. It has experimental features that will not work reliably, such as schema management, the unorthodox URL scheme, and special array (1 dimensional table) support. All parts of the user interface are expected to be overhauled at some point. The code quality is mediocre and inconsistent. Most obscure adapter options are untested. It has an incomplete story on how to use it outside the CLI in other software, as a library. It has no story or documentation for service authentication, aside from SQL DBs. Lastly, the documentation is weak and _no_ documentation has been written to document the standard options available for each adapter, nor documentation of any adapter-specific options.
        
        
        ## Main Influences
        - odo
        - Singer
        - ODBC/JDBC
        - osquery
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: Implementation :: CPython
Requires-Python: >=3.7.0
Description-Content-Type: text/markdown
