Name | t-commenter JSON |
Version |
0.1.1
JSON |
| download |
home_page | None |
Summary | A module for working with table metadata (comments on tables, views, materialized views, and columns) in PostgreSQL. |
upload_time | 2025-02-20 19:11:55 |
maintainer | None |
docs_url | None |
author | None |
requires_python | <4.0,>=3.8 |
license | MIT License
Copyright (c) 2025 ArtemXYZ
Permission is hereby granted, free of charge, to any person obtaining a
copyPermission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following condition:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
This software uses SQLAlchemy, which is licensed under the MIT License:
https://opensource.org/licenses/MIT
SQLAlchemy GitHub repository:
https://github.com/sqlalchemy/sqlalchemy
|
keywords |
comments on tables
tables
views
materialized views
columns
postgresql
t-commenter
sqlalchemy
create comments on tables
objects in a database
t-commenter
dags
airflow
airflow
table commentator
set table comment
get table comments
set column comment
|
VCS |
 |
bugtrack_url |
|
requirements |
No requirements were recorded.
|
Travis-CI |
No Travis.
|
coveralls test coverage |
No coveralls.
|
<a id="readme-top"></a>
<!-- PROJECT SHIELDS -->
> # <p align="center">**T-COMMENTER**</p>
<div align="center">
![Version][PyPI Version]
![Downloads][PyPI Downloads]
![Versions][Python Versions]
![License][PyPI License]
![Issues][PyPI Created]
[![Stargazers][GitHub Stars]][stars-url]
[![Forks][GitHub Forks]][forks-url]
[![Contributors][GitHub Contributors]][contributors-url]
[![Issues][GitHub Issues]][issues-url]
[![Discussions][GitHub Discussions]][discussions-url]
</div>
<div style="text-align: center;">
<img src="https://raw.githubusercontent.com/ArtemXYZ/t-commenter/main/docs/images/t-commenter.png"
style="width: 900px; height: 300px;" alt="LOGO">
</div>
## About the project
The T-COMMENTER library is based on the SQLAlchemy library and is designed to
create comments on tables (and other objects) in a database (in the current
version of the library, it is only for PostgreSQL) T-COMMENTER - this is a
modified abbreviation от "Table Commentator". In this context, the meaning of
the word table has a broader meaning than the direct one, and covers objects
such as a view, materialized view (other types of objects are ignored in the
current implementation).
Initially, the library was conceived as a tool for working with metadata in
DAGs (DAG - Directed Acyclic Graph,
https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/dags.html)
"Apache Airflow". The need to rewrite the metadata of database objects arises
when working with pandas, namely with "pandas.Data Frame.to_sql"
(
https://pandas.pydata.org/pandas-docs/stable/reference/api/
pandas.DataFrame.to_sql.html
).
If the method has a the if_exists=replace flag, drops the table
before inserting new values. In this case, all metadata is they are deleted
along with the table. This library was created to solve this kind of problem,
as well as to to ensure the convenience of working without using SQL directly.
## Installation
You can install the library using pip:
```sh
pip install t-commentor
```
<p align="right">(<a href="#readme-top">back to top</a>)</p>
## Usage
#### <p align="center">Creating an instance Сommenter</p>
```python
from tcommenter import Сommenter
from connections import engine # Your SQLAlchemy Engine:
# Creating an instance of a class to work with a specific entity in the database:
commenter = Сommenter(engine=engine, name_table='dags', schema='audit')
```
[//]: # (- Metadata extraction methods:)
#### <p align="center">Metadata extraction methods</p>
```python
# Getting a comment to the table (only to the entity itself, excluding comments to columns):
comments = commenter.get_table_comments()
print(comments) # -> 'The table contains data unloading from Airflow.'
```
```python
# Getting comments on all columns of an entity:
comments = commenter.get_column_comments()
print(comments) # -> {'dag_id': 'pass', 'description': 'pass', 'tags': 'pass', pass}
```
```python
# Getting a comment on a column by column name:
comments = commenter.get_column_comments('tags')
print(comments) # -> {'tags': 'pass'}'
````
```python
# Getting comments on columns by index (ordinal number in essence):
comments = commenter.get_column_comments(1, 2)
print(comments) # -> {'dag_id': 'pass', 'description': 'pass'}
````
```python
# Getting all available comments on an entity and its columns:
comments = commenter.get_all_comments()
print(comments) # -> '{'table': 'pass', 'columns': {'dag_id': 'pass', 'description': 'pass', pass}}'
````
<p align="right">(<a href="#readme-top">back to top</a>)</p>
[//]: # (- Metadata recording methods:)
#### <p align="center">Metadata recording methods</p>
```python
# Writing a comment on an entity:
commenter.set_table_comment('The table contains data unloading from Airflow.')
comments = commenter.get_table_comments()
print(comments) # -> 'The table contains data unloading from Airflow.'
````
*Similarly for methods:*
* set_view_comment()
* set_materialized_view_comment()
```python
# Record comments on an entity by column tag:
commenter.set_column_comment(description='description_test', dag_id='dag_id_test')
comments = commenter.get_column_comments('description', 'dag_id')
print(comments) # -> {'dag_id': 'dag_id_test', 'description': 'description_test'}
````
<p align="right">(<a href="#readme-top">back to top</a>)</p>
[//]: # (# -------------------------------Service methods:)
#### <p align="center">Service methods</p>
```python
# Method for determining the type of entity ('table', 'view', 'mview', ...)
type_entity = commenter.get_type_entity()
print(type_entity) # -> 'table'
````
<p align="right">(<a href="#readme-top">back to top</a>)</p>
[//]: # (# ------------------------------- Examples of metadata overload:)
#### <p align="center">Examples of metadata overload</p>
Getting comments of a special kind compatible with the "save_comments()" method.
If it is necessary to overload all available comments (first to receive, and
after your intermediate logic) immediately save to the same or another entity
(with the same structure), there is a method _"save_comments()"_.
A universal method for saving comments of any type (to entities or their columns):
- _commenter.save_comments(comments)_
It takes a special kind of data that allows you to explicitly indicate the
affiliation of comments from all methods to receive comments:
_"get_table_comments()", "get_column_comments()", "get_all_comments()"_.
However, for the first two it is necessary to set the flag: "service_mode=True"
(by default service_mode=False).
There is no "service_mode" in _"get_all_comments()"_, but the output corresponds
to this flag. The universal _"save_comments()"_ method allows you to save all
metadata for both columns and entities at once, limited to just one line of code.
```python
# We receive comments in "service_mode" mode before overloading:
comments = commenter.get_table_comments(service_mode=True)
print(comments) # -> {'table': 'The table contains data unloading from Airflow.'}
commenter.save_comments(comments)
````
````python
# We receive comments in "service_mode" mode before overloading:
comments = commenter.get_column_comments(2, 3, service_mode=True)
print(comments) # -> {'columns': {'description': 'pass', 'tags': 'pass'}}
commenter.save_comments(comments)
````
````python
# We receive all available comments:
comments = commenter.get_all_comments()
print(comments) # -> {'table': 'pass', 'columns': {pass}}
commenter.save_comments(comments)
````
## Examples
- Download the examples file: [`examples/example_usage.py`][examples-url]
<p align="right">(<a href="#readme-top">back to top</a>)</p>
<!-- LICENSE -->
## License
- Distributed under the MIT License. See [`LICENSE`][license-url]
<p align="right">(<a href="#readme-top">back to top</a>)</p>
## Clone the repo
````
git clone https://github.com/ArtemXYZ/t-commentor.git
````
<!-- CONTACT -->
## Contact
- GitHub - [ArtemXYZ](https://github.com/ArtemXYZ)
- Telegram - [ArtemP_khv](https://t.me/ArtemP_khv)
<p align="right">(<a href="#readme-top">back to top</a>)</p>
<!-- MARKDOWN LINKS -------------------------------------------->
[PyPI Version]: https://img.shields.io/pypi/v/t-commenter?label=Version
[PyPI Downloads]: https://img.shields.io/pypi/dm/t-commenter?label=Downloads
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[PyPI License]: https://img.shields.io/pypi/l/t-commenter?label=License
[PyPI Created]: https://img.shields.io/github/created-at/ArtemXYZ/t-commenter
[GitHub Stars]: https://img.shields.io/github/stars/ArtemXYZ/t-commenter?style
[GitHub Forks]: https://img.shields.io/github/forks/ArtemXYZ/t-commenter?style
[GitHub Contributors]: https://img.shields.io/github/contributors/ArtemXYZ/t-commenter
[GitHub Issues]: https://img.shields.io/github/issues/ArtemXYZ/t-commenter
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[license-url]: https://github.com/ArtemXYZ/t-commenter/blob/main/LICENSE
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"description": "<a id=\"readme-top\"></a>\r\n\r\n<!-- PROJECT SHIELDS --> \r\n> # <p align=\"center\">**T-COMMENTER**</p>\r\n\r\n<div align=\"center\">\r\n\r\n![Version][PyPI Version]\r\n![Downloads][PyPI Downloads]\r\n![Versions][Python Versions]\r\n![License][PyPI License]\r\n![Issues][PyPI Created]\r\n\r\n[![Stargazers][GitHub Stars]][stars-url]\r\n[![Forks][GitHub Forks]][forks-url]\r\n[![Contributors][GitHub Contributors]][contributors-url]\r\n[![Issues][GitHub Issues]][issues-url]\r\n[![Discussions][GitHub Discussions]][discussions-url]\r\n\r\n</div>\r\n\r\n\r\n<div style=\"text-align: center;\">\r\n <img src=\"https://raw.githubusercontent.com/ArtemXYZ/t-commenter/main/docs/images/t-commenter.png\" \r\n style=\"width: 900px; height: 300px;\" alt=\"LOGO\">\r\n</div> \r\n\r\n## About the project\r\n\r\n The T-COMMENTER library is based on the SQLAlchemy library and is designed to \r\n create comments on tables (and other objects) in a database (in the current \r\n version of the library, it is only for PostgreSQL) T-COMMENTER - this is a \r\n modified abbreviation \u043e\u0442 \"Table Commentator\". In this context, the meaning of \r\n the word table has a broader meaning than the direct one, and covers objects \r\n such as a view, materialized view (other types of objects are ignored in the \r\n current implementation). \r\n\r\n Initially, the library was conceived as a tool for working with metadata in \r\n DAGs (DAG - Directed Acyclic Graph, \r\n https://airflow.apache.org/docs/apache-airflow/stable/core-concepts/dags.html) \r\n \"Apache Airflow\". The need to rewrite the metadata of database objects arises \r\n when working with pandas, namely with \"pandas.Data Frame.to_sql\"\r\n (\r\n https://pandas.pydata.org/pandas-docs/stable/reference/api/\r\n pandas.DataFrame.to_sql.html\r\n ). \r\n If the method has a the if_exists=replace flag, drops the table \r\n before inserting new values. In this case, all metadata is they are deleted \r\n along with the table. This library was created to solve this kind of problem, \r\n as well as to to ensure the convenience of working without using SQL directly.\r\n\r\n## Installation\r\n\r\nYou can install the library using pip:\r\n\r\n```sh\r\n pip install t-commentor\r\n```\r\n\r\n<p align=\"right\">(<a href=\"#readme-top\">back to top</a>)</p>\r\n\r\n## Usage\r\n\r\n#### <p align=\"center\">Creating an instance \u0421ommenter</p>\r\n\r\n```python\r\nfrom tcommenter import \u0421ommenter\r\nfrom connections import engine # Your SQLAlchemy Engine:\r\n\r\n# Creating an instance of a class to work with a specific entity in the database:\r\ncommenter = \u0421ommenter(engine=engine, name_table='dags', schema='audit')\r\n```\r\n\r\n[//]: # (- Metadata extraction methods:)\r\n\r\n#### <p align=\"center\">Metadata extraction methods</p>\r\n\r\n```python\r\n\r\n# Getting a comment to the table (only to the entity itself, excluding comments to columns):\r\ncomments = commenter.get_table_comments()\r\nprint(comments) # -> 'The table contains data unloading from Airflow.'\r\n\r\n```\r\n\r\n```python\r\n\r\n# Getting comments on all columns of an entity:\r\ncomments = commenter.get_column_comments()\r\nprint(comments) # -> {'dag_id': 'pass', 'description': 'pass', 'tags': 'pass', pass}\r\n\r\n```\r\n\r\n```python\r\n\r\n# Getting a comment on a column by column name:\r\ncomments = commenter.get_column_comments('tags')\r\nprint(comments) # -> {'tags': 'pass'}'\r\n\r\n````\r\n\r\n```python\r\n\r\n# Getting comments on columns by index (ordinal number in essence):\r\ncomments = commenter.get_column_comments(1, 2)\r\nprint(comments) # -> {'dag_id': 'pass', 'description': 'pass'}\r\n\r\n````\r\n\r\n```python\r\n\r\n# Getting all available comments on an entity and its columns:\r\ncomments = commenter.get_all_comments()\r\nprint(comments) # -> '{'table': 'pass', 'columns': {'dag_id': 'pass', 'description': 'pass', pass}}'\r\n\r\n````\r\n\r\n<p align=\"right\">(<a href=\"#readme-top\">back to top</a>)</p>\r\n\r\n[//]: # (- Metadata recording methods:)\r\n\r\n#### <p align=\"center\">Metadata recording methods</p>\r\n\r\n```python\r\n\r\n# Writing a comment on an entity:\r\ncommenter.set_table_comment('The table contains data unloading from Airflow.')\r\ncomments = commenter.get_table_comments()\r\nprint(comments) # -> 'The table contains data unloading from Airflow.'\r\n\r\n````\r\n\r\n*Similarly for methods:*\r\n\r\n* set_view_comment()\r\n* set_materialized_view_comment()\r\n\r\n```python\r\n\r\n# Record comments on an entity by column tag:\r\ncommenter.set_column_comment(description='description_test', dag_id='dag_id_test')\r\ncomments = commenter.get_column_comments('description', 'dag_id')\r\nprint(comments) # -> {'dag_id': 'dag_id_test', 'description': 'description_test'}\r\n\r\n````\r\n\r\n<p align=\"right\">(<a href=\"#readme-top\">back to top</a>)</p>\r\n\r\n[//]: # (# -------------------------------Service methods:)\r\n\r\n#### <p align=\"center\">Service methods</p>\r\n\r\n```python\r\n\r\n# Method for determining the type of entity ('table', 'view', 'mview', ...)\r\ntype_entity = commenter.get_type_entity()\r\nprint(type_entity) # -> 'table'\r\n\r\n````\r\n\r\n<p align=\"right\">(<a href=\"#readme-top\">back to top</a>)</p>\r\n\r\n[//]: # (# ------------------------------- Examples of metadata overload:)\r\n\r\n#### <p align=\"center\">Examples of metadata overload</p>\r\n\r\nGetting comments of a special kind compatible with the \"save_comments()\" method.\r\nIf it is necessary to overload all available comments (first to receive, and\r\nafter your intermediate logic) immediately save to the same or another entity\r\n(with the same structure), there is a method _\"save_comments()\"_.\r\n\r\nA universal method for saving comments of any type (to entities or their columns):\r\n\r\n- _commenter.save_comments(comments)_\r\n\r\nIt takes a special kind of data that allows you to explicitly indicate the\r\naffiliation of comments from all methods to receive comments:\r\n_\"get_table_comments()\", \"get_column_comments()\", \"get_all_comments()\"_.\r\nHowever, for the first two it is necessary to set the flag: \"service_mode=True\"\r\n(by default service_mode=False).\r\nThere is no \"service_mode\" in _\"get_all_comments()\"_, but the output corresponds\r\nto this flag. The universal _\"save_comments()\"_ method allows you to save all\r\nmetadata for both columns and entities at once, limited to just one line of code.\r\n\r\n```python\r\n\r\n# We receive comments in \"service_mode\" mode before overloading:\r\ncomments = commenter.get_table_comments(service_mode=True)\r\nprint(comments) # -> {'table': 'The table contains data unloading from Airflow.'}\r\ncommenter.save_comments(comments)\r\n\r\n````\r\n\r\n````python\r\n\r\n# We receive comments in \"service_mode\" mode before overloading:\r\ncomments = commenter.get_column_comments(2, 3, service_mode=True)\r\nprint(comments) # -> {'columns': {'description': 'pass', 'tags': 'pass'}}\r\ncommenter.save_comments(comments)\r\n\r\n````\r\n\r\n````python\r\n\r\n# We receive all available comments:\r\ncomments = commenter.get_all_comments()\r\nprint(comments) # -> {'table': 'pass', 'columns': {pass}}\r\ncommenter.save_comments(comments)\r\n\r\n````\r\n\r\n## Examples\r\n\r\n- Download the examples file: [`examples/example_usage.py`][examples-url]\r\n\r\n<p align=\"right\">(<a href=\"#readme-top\">back to top</a>)</p>\r\n\r\n<!-- LICENSE -->\r\n\r\n## License\r\n\r\n- Distributed under the MIT License. See [`LICENSE`][license-url]\r\n\r\n<p align=\"right\">(<a href=\"#readme-top\">back to top</a>)</p>\r\n\r\n## Clone the repo\r\n\r\n````\r\ngit clone https://github.com/ArtemXYZ/t-commentor.git\r\n````\r\n\r\n<!-- CONTACT -->\r\n\r\n## Contact\r\n\r\n- GitHub - [ArtemXYZ](https://github.com/ArtemXYZ)\r\n- Telegram - [ArtemP_khv](https://t.me/ArtemP_khv)\r\n\r\n<p align=\"right\">(<a href=\"#readme-top\">back to top</a>)</p>\r\n\r\n\r\n\r\n\r\n\r\n<!-- MARKDOWN LINKS -------------------------------------------->\r\n[PyPI Version]: https://img.shields.io/pypi/v/t-commenter?label=Version\r\n[PyPI Downloads]: https://img.shields.io/pypi/dm/t-commenter?label=Downloads\r\n[Python Versions]: https://img.shields.io/pypi/pyversions/t-commenter?label=Python\r\n[PyPI License]: https://img.shields.io/pypi/l/t-commenter?label=License\r\n[PyPI Created]: https://img.shields.io/github/created-at/ArtemXYZ/t-commenter\r\n\r\n\r\n[GitHub Stars]: https://img.shields.io/github/stars/ArtemXYZ/t-commenter?style\r\n[GitHub Forks]: https://img.shields.io/github/forks/ArtemXYZ/t-commenter?style\r\n[GitHub Contributors]: https://img.shields.io/github/contributors/ArtemXYZ/t-commenter \r\n[GitHub Issues]: https://img.shields.io/github/issues/ArtemXYZ/t-commenter\r\n[GitHub Discussions]: https://img.shields.io/github/discussions/ArtemXYZ/t-commenter\r\n\r\n[stars-url]: https://github.com/ArtemXYZ/t-commenter/stargazers\r\n[forks-url]: https://github.com/ArtemXYZ/t-commenter/network/members\r\n[contributors-url]: https://github.com/ArtemXYZ/t-commenter/contributors\r\n[issues-url]: https://github.com/ArtemXYZ/t-commenter/issues\r\n[discussions-url]: https://github.com/ArtemXYZ/t-commenter/discussions\r\n\r\n\r\n[license-url]: https://github.com/ArtemXYZ/t-commenter/blob/main/LICENSE\r\n[examples-url]: https://github.com/ArtemXYZ/t-commenter/blob/main/examples/example_usage.py\r\n<!-- MARKDOWN LINKS ----------------------------------------------------->\r\n\r\n\r\n\r\n\r\n",
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"license": "MIT License\r\n \r\n Copyright (c) 2025 ArtemXYZ\r\n \r\n Permission is hereby granted, free of charge, to any person obtaining a\r\n copyPermission is hereby granted, free of charge, to any person obtaining a copy\r\n of this software and associated documentation files (the \"Software\"), to deal\r\n in the Software without restriction, including without limitation the rights\r\n to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\r\n copies of the Software, and to permit persons to whom the Software is\r\n furnished to do so, subject to the following condition:\r\n \r\n The above copyright notice and this permission notice shall be included in all\r\n copies or substantial portions of the Software.\r\n \r\n THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\r\n IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\r\n FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\r\n AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\r\n LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\r\n OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\r\n THE SOFTWARE.\r\n \r\n This software uses SQLAlchemy, which is licensed under the MIT License:\r\n https://opensource.org/licenses/MIT\r\n \r\n SQLAlchemy GitHub repository:\r\n https://github.com/sqlalchemy/sqlalchemy\r\n ",
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