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ddlgenerator-0.1.9
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مشاهده بیشترتوضیحات
Generates SQL DDL that will accept Python data
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | ddlgenerator-0.1.9 |
| نام | ddlgenerator |
| نسخه کتابخانه | 0.1.9 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Catherine Devlin |
| ایمیل نویسنده | catherine.devlin@gmail.com |
| آدرس صفحه اصلی | https://github.com/catherinedevlin/ddl-generator |
| آدرس اینترنتی | https://pypi.org/project/ddlgenerator/ |
| مجوز | MIT |
=============
DDL Generator
=============
Infers SQL DDL (Data Definition Language) from table data.
Use at command line::
$ ddlgenerator -i postgresql '[{"Name": "Alfred", "species": "wart hog", "kg": 22}]'
DROP TABLE generated_table;
CREATE TABLE generated_table (
name VARCHAR(6) NOT NULL,
kg INTEGER NOT NULL,
species VARCHAR(8) NOT NULL
)
;
INSERT INTO generated_table (kg, Name, species) VALUES (22, 'Alfred', 'wart hog');
Reads data from files::
$ ddlgenerator postgresql mydata.yaml > mytable.sql
Enables one-line creation of tables with their data
$ ddlgenerator --inserts postgresql mydata.json | psql
To use in Python::
>>> from ddlgenerator.ddlgenerator import Table
>>> table = Table([{"Name": "Alfred", "species": "wart hog", "kg": 22}])
>>> sql = table.sql('postgresql', inserts=True)
Supported data formats
----------------------
- Pure Python
- YAML
- JSON
- CSV
- Pickle
- HTML
Features
--------
- Supports all SQL dialects supported by SQLAlchemy
- Coerces data into most specific data type valid on all column's values
- Takes table name from file name
- Guesses format of input data if unspecified by file extension
- with ``-i``/``--inserts`` flag, adds INSERT statements
- with ``-u``/``--uniques`` flag, surmises UNIQUE constraints from data
- Handles nested data, creating child tables as needed
- Reads HTML tables, including those embedded in noisy websites
Options
-------
::
-h, --help show this help message and exit
-k KEY, --key KEY Field to use as primary key
-r, --reorder Reorder fields alphabetically, ``key`` first
-u, --uniques Include UNIQUE constraints where data is unique
-t, --text Use variable-length TEXT columns instead of VARCHAR
-d, --drops Include DROP TABLE statements
-i, --inserts Include INSERT statements
--no-creates Do not include CREATE TABLE statements
--save-metadata-to FILENAME
Save table definition in FILENAME for later --use-
saved-metadata run
--use-metadata-from FILENAME
Use metadata saved in FROM for table definition, do
not re-analyze table structure
-l LOG, --log LOG log level (CRITICAL, FATAL, ERROR, DEBUG, INFO, WARN)
Generate SQLAlchemy models
--------------------------
Use ``sqlalchemy`` as the model to generate Python for defining SQLAlchemy
models::
$ ddlgenerator sqlalchemy '[{"Name": "Alfred", "species": "wart hog", "kg": 22}]'
Table0 = Table('Table0', metadata,
Column('species', Unicode(length=8), nullable=False),
Column('kg', Integer(), nullable=False),
Column('name', Unicode(length=6), nullable=False),
schema=None)
Generate Django models
----------------------
If Django is installed on the path then using ``django`` as the model will run the
generated ddl through Django's ``inspectdb`` management command to produce a model
file::
$ ddlgenerator django '[{"Name": "Alfred", "species": "wart hog", "kg": 22}]'
# This is an auto-generated Django model module.
# You'll have to do the following manually to clean this up:
# * Rearrange models' order
# * Make sure each model has one field with primary_key=True
# * Remove `managed = False` lines if you wish to allow Django to create and delete the table
# Feel free to rename the models, but don't rename db_table values or field names.
#
# Also note: You'll have to insert the output of 'django-admin.py sqlcustom [appname]'
# into your database.
from __future__ import unicode_literals
from django.db import models
class Table0(models.Model):
species = models.CharField(max_length=8)
kg = models.IntegerField()
name = models.CharField(max_length=6)
class Meta:
managed = False
db_table = 'Table0'
Large tables
------------
As of now, ``ddlgenerator`` is not well-designed for table sizes approaching
your system's available memory.
One approach to save time and memory for large tables is to break your input data into multiple
files, then run ``ddlgenerator`` with ``--save-metadata`` against a small
but representative sample. Then run with ``--no-creates`` and ``-use-saved-metadata``
to generate INSERTs from the remaining files without needing to re-determine the
column types each time.
Installing
----------
Requires Python3.
From PyPI::
pip3 install ddlgenerator
From source::
git clone https://github.com/catherinedevlin/ddl-generator.git
cd ddl-generator
pip3 install .
Alternatives
------------
* `csvkit.csvsql <https://csvkit.readthedocs.org/en/0.7.3/scripts/csvsql.html>`_
* `pandas.read_*` methods
* `prequel <https://github.com/timClicks/prequel.git>`_ for SQLite
Credits
-------
- Mike Bayer for sqlalchemy
- coldfix and Mark Ransom for their StackOverflow answers
- Audrey Roy for cookiecutter
- Brandon Lorenz for Django model generation
History
-------
0.1.0 (2014-03-22)
++++++++++++++++++
* First release on PyPI.
0.1.2 (2014-07-15)
++++++++++++++++++
* ``data_dispenser`` moved to separate module
0.1.3 (2014-07-16)
++++++++++++++++++
* Bugfix for long integers found after short strings
0.1.4 (2014-07-25)
++++++++++++++++++
* Fixed bug: external ``data_dispenser`` unused by 0.1.3!
0.1.5 (2014-07-25)
++++++++++++++++++
* ``sqlalchemy`` pseudo-dialect added
0.1.6 (2014-07-25)
++++++++++++++++++
* Generate sqlalchemy inserts
0.1.7 (2014-09-14)
++++++++++++++++++
* Read via HTTP
* Support HTML format
* Generate Django models
0.1.7.1 (2014-09-14)
++++++++++++++++++++
* Require data-dispenser 0.2.3
0.1.7.3 (2014-10-19)
++++++++++++++++++++
* Require all formerly recommended dependencies, for simplicity
* Several bugfixes for complex number-like fields
0.1.8 (2015-02-01)
++++++++++++++++++
* UNIQUE contstraints handled properly in sqlalchemy output
0.1.8.2 (2015-02-05)
++++++++++++++++++++
* Cleaner SQLAlchemy generation for fixtures
0.1.9 (2015-02-10)
++++++++++++++++++
* README fixes from Anatoly Technonik, Mikhail Podgurskiy
* Parse args passed to ``generate(args, namespace)`` for non-command-line use
نحوه نصب
نصب پکیج whl ddlgenerator-0.1.9:
pip install ddlgenerator-0.1.9.whl
نصب پکیج tar.gz ddlgenerator-0.1.9:
pip install ddlgenerator-0.1.9.tar.gz