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https://github.com/kennethreitz/records
SQL for Humans™
https://github.com/kennethreitz/records
forhumans kennethreitz orm postgres python schemas sql sqlalchemy
Last synced: 6 days ago
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SQL for Humans™
- Host: GitHub
- URL: https://github.com/kennethreitz/records
- Owner: kennethreitz
- License: isc
- Created: 2014-12-24T15:20:23.000Z (about 10 years ago)
- Default Branch: master
- Last Pushed: 2024-07-09T11:26:43.000Z (6 months ago)
- Last Synced: 2025-01-02T08:12:15.552Z (10 days ago)
- Topics: forhumans, kennethreitz, orm, postgres, python, schemas, sql, sqlalchemy
- Language: Python
- Homepage: https://pypi.python.org/pypi/records/
- Size: 306 KB
- Stars: 7,176
- Watchers: 186
- Forks: 573
- Open Issues: 41
-
Metadata Files:
- Readme: README.md
- Changelog: HISTORY.rst
- Funding: .github/FUNDING.yml
- License: LICENSE
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README
# Records: SQL for Humans™
[](https://pypi.python.org/pypi/records)
**Records is a very simple, but powerful, library for making raw SQL
queries to most relational databases.**
Just write SQL. No bells, no whistles. This common task can be
surprisingly difficult with the standard tools available. This library
strives to make this workflow as simple as possible, while providing an
elegant interface to work with your query results.
*Database support includes RedShift, Postgres, MySQL, SQLite, Oracle,
and MS-SQL (drivers not included).*
## ☤ The Basics
We know how to write SQL, so let's send some to our database:
``` python
import records
db = records.Database('postgres://...')
rows = db.query('select * from active_users') # or db.query_file('sqls/active-users.sql')
```
Grab one row at a time:
``` python
>>> rows[0]
```
Or iterate over them:
``` python
for r in rows:
print(r.name, r.user_email)
```
Values can be accessed many ways: `row.user_email`, `row['user_email']`,
or `row[3]`.
Fields with non-alphanumeric characters (like spaces) are also fully
supported.
Or store a copy of your record collection for later reference:
``` python
>>> rows.all()
[, , , ...]
```
If you're only expecting one result:
``` python
>>> rows.first()
```
Other options include `rows.as_dict()` and `rows.as_dict(ordered=True)`.
## ☤ Features
- Iterated rows are cached for future reference.
- `$DATABASE_URL` environment variable support.
- Convenience `Database.get_table_names` method.
- Command-line records tool for
exporting queries.
- Safe parameterization:
`Database.query('life=:everything', everything=42)`.
- Queries can be passed as strings or filenames, parameters supported.
- Transactions: `t = Database.transaction(); t.commit()`.
- Bulk actions: `Database.bulk_query()` &
`Database.bulk_query_file()`.
Records is proudly powered by [SQLAlchemy](http://www.sqlalchemy.org)
and [Tablib](https://tablib.readthedocs.io/en/latest/).
## ☤ Data Export Functionality
Records also features full Tablib integration, and allows you to export
your results to CSV, XLS, JSON, HTML Tables, YAML, or Pandas DataFrames
with a single line of code. Excellent for sharing data with friends, or
generating reports.
``` pycon
>>> print(rows.dataset)
username|active|name |user_email |timezone
--------|------|----------|-----------------|--------------------------
model-t |True |Henry Ford|[email protected]|2016-02-06 22:28:23.894202
...
```
**Comma Separated Values (CSV)**
``` pycon
>>> print(rows.export('csv'))
username,active,name,user_email,timezone
model-t,True,Henry Ford,[email protected],2016-02-06 22:28:23.894202
...
```
**YAML Ain't Markup Language (YAML)**
``` python
>>> print(rows.export('yaml'))
- {active: true, name: Henry Ford, timezone: '2016-02-06 22:28:23.894202', user_email: [email protected], username: model-t}
...
```
**JavaScript Object Notation (JSON)**
``` python
>>> print(rows.export('json'))
[{"username": "model-t", "active": true, "name": "Henry Ford", "user_email": "[email protected]", "timezone": "2016-02-06 22:28:23.894202"}, ...]
```
**Microsoft Excel (xls, xlsx)**
``` python
with open('report.xls', 'wb') as f:
f.write(rows.export('xls'))
```
**Pandas DataFrame**
``` python
>>> rows.export('df')
username active name user_email timezone
0 model-t True Henry Ford [email protected] 2016-02-06 22:28:23.894202
```
You get the point. All other features of Tablib are also available, so
you can sort results, add/remove columns/rows, remove duplicates,
transpose the table, add separators, slice data by column, and more.
See the [Tablib Documentation](https://tablib.readthedocs.io/) for more
details.
## ☤ Installation
Of course, the recommended installation method is
[pipenv](http://pipenv.org):
$ pipenv install records[pandas]
✨🍰✨
## ☤ Thank You
Thanks for checking this library out! I hope you find it useful.
Of course, there's always room for improvement. Feel free to [open an
issue](https://github.com/kennethreitz/records/issues) so we can make
Records better, stronger, faster.
--------------
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