sqlparse
parser
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| sqlparse | parser | |
|---|---|---|
| 7 | 3 | |
| 3,581 | 1,395 | |
| - | 1.0% | |
| 8.2 | 3.2 | |
| 7 days ago | 5 months ago | |
| Python | Go | |
| BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
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sqlparse
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Show HN: Databasediagram.com – Private, Text to Entity-Relationship Diagram Tool
Suggest checking out the sqlparse library for a way to do the different flavours without needing to address each case directly: https://github.com/andialbrecht/sqlparse
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Data Load Diagram
Gotcha, since we haven't actually written all of this yet I don't have any useful code snippets to share but we've discussed tackling the problem internally using something like sqlparse. You'd need to identify the relevant sql chunks, parse them for table dependency information and then create the relevant entities in whichever data lineage tool you were using.
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This Week In Python
sqlparse – A non-validating SQL parser module for Python
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Open Source SQL Parsers
Regular expressions is a popular approach to extract information from SQL statements. However, regular expressions quickly become too complex to handle common features like WITH, sub-queries, windows clauses, aliases and quotes. sqlparse is a popular python package that uses regular expressions to parse SQL.
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Automated SQL formatting checks
This one is not bad: https://github.com/andialbrecht/sqlparse.
- Let's write a compiler, part 5: A code generator
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BigQuery Lineage
We used this repo for this: https://github.com/andialbrecht/sqlparse. I may have miscommunicated. We didn't write the parser from scratch, we created a way for the parser to detect downstream and upstream dependencies of the resource.
parser
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sqlc: Generating go code from sql statements
For MySQL the situation is a bit different. sqlc uses the parser of TiDB (https://github.com/pingcap/parser), which is a parser that aims to be basically compatible with MySQL, but is quite young and is not a MySQL parser. The most basic queries work, but even simple joins or aggregations usually result in variables with unknown data types or wrong nullability. So you loose a lot of the benefits of sqlc. Manual type annotations for MySQL also do not work most of the time. They are simply ignored and forwarded to MySQL as invalid query if they do not occur on a place where sqlc is expecting them.
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Wp-SQLite: WordPress running on an SQLite database
This is a disaster waiting to happen. Regular expressions should never be used to parse non-regular languages, of which SQL is one.
There are a variety of mature MySQL dialect parsers available[1][2], and MySQL should have its own public APIs for transforming a query into an AST. Any of those would be a safer and more correct alternative.
[1]: https://github.com/pingcap/parser
[2]: https://github.com/square/mysql-parser
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Open Source SQL Parsers
Pingcap parser is a MySQL parser in Go.
What are some alternatives?
zetasql - ZetaSQL - Analyzer Framework for SQL
ANTLR - ANTLR (ANother Tool for Language Recognition) is a powerful parser generator for reading, processing, executing, or translating structured text or binary files.
pyparsing - Python library for creating PEG parsers [Moved to: https://github.com/pyparsing/pyparsing]
mo-sql-parsing - Let's make a SQL parser so we can provide a familiar interface to non-sql datastores!
Lark - Lark is a parsing toolkit for Python, built with a focus on ergonomics, performance and modularity.
pg_query - Ruby extension to parse, deparse and normalize SQL queries using the PostgreSQL query parser
PLY - Python Lex-Yacc
sqlfluff - A modular SQL linter and auto-formatter with support for multiple dialects and templated code.
pg-query-emscripten - Emscripten Port of pg_query to easily play with it in the browser
Pygments
pglast - PostgreSQL Languages AST and statements prettifier: master branch covers PG10, v2 branch covers PG12, v3 covers PG13, v4 covers PG14, v5 covers PG15, v6 covers PG16