Multicorn | Multicorn Python Wrapper for Postgresql | Database library

by Segfault-Inc Python Version: v1.3.2 License: PostgreSQL

X-Ray Key Features Code Snippets Community Discussions(4)Vulnerabilities Install Support

kandi X-RAY | Multicorn Summary

Multicorn is a Python library typically used in Database, PostgresSQL applications. Multicorn has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Multicorn Python Wrapper for Postgresql 9.2+ Foreign Data Wrapper. The Multicorn Foreign Data Wrapper allows you to fetch foreign data in Python in your PostgreSQL server. Documentation available at : Multicorn is distributed under the PostgreSQL license. See the LICENSE file for details.

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Quality

Security

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Support

Multicorn has a low active ecosystem.

It has 675 star(s) with 151 fork(s). There are 66 watchers for this library.

It had no major release in the last 12 months.

There are 75 open issues and 117 have been closed. On average issues are closed in 586 days. There are 21 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of Multicorn is v1.3.2

Quality

Multicorn has 0 bugs and 0 code smells.

Security

Multicorn has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Multicorn code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Multicorn is licensed under the PostgreSQL License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

Multicorn releases are available to install and integrate.

Build file is available. You can build the component from source.

Multicorn saves you 984 person hours of effort in developing the same functionality from scratch.

It has 2238 lines of code, 201 functions and 24 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed Multicorn and discovered the below as its top functions. This is intended to give you an instant insight into Multicorn implemented functionality, and help decide if they suit your requirements.

Parse a filesystem pattern
Tokenize a pattern
Update the contents of a file
Create a new item from a dictionary
Create an Item from a filename
Create a new Item instance
Execute the query
Creates a condition
Extracts conditions from a query
Import a schema
Calculate the size of the column
Pre - commit transaction
Insert a new file into the database
Yields the lines of the table
Import a class
Execute the parser
Roll back the current transaction
Return a list of sortkeys that can sort the query
Parse the given scope
Returns an instance of the IMAP agent
Delete a file from the filesystem
Execute google query
Find the version number
Return row id column
Create a basic conversion function for a given type
Creates a function that turns a length string into a length
Create a basic type converter function

Get all kandi verified functions for this library.

Multicorn Key Features

No Key Features are available at this moment for Multicorn.

Multicorn Examples and Code Snippets

No Code Snippets are available at this moment for Multicorn.

Community Discussions

Trending Discussions on Multicorn

Makefile shell function and environment vars

Port data from MySQL database to PostgreSQL

FDW in Postgres: Batching ids for an external request?

pg_config not found while I have it installed

QUESTION

Makefile shell function and environment vars

Asked 2019-Sep-19 at 16:45

I'm playing around with Multicorn for Postgres, and its Makefile doesn't seem to play nice with Python virtual environments. It wants to install itself to the system Python in spite of pyenv. I think this is happening because its Makefile is doing this to find the Python version:

...

ANSWER

Answered 2019-Sep-19 at 16:45

You can pass the pyenv version via the PYENV_VERSION environment variable. I'd imagine something like:

Source https://stackoverflow.com/questions/57896997

QUESTION

Port data from MySQL database to PostgreSQL

Asked 2019-May-22 at 10:28

I have a requirement to create a staging table in our data ware house which is running on PostgreSQL and import data from our Magento website which is using MySQL database,I'm trying with Python.

I have created the below query for the importing purpose,

1. Can you please check and confirm whether this is fine? Or any alternative methods are there for doing it?

2. Also i want to know how we can manage the DATATYPE mismatch issues while porting?

3. Is there anything we can do with Foreign data rapper(FDW) such as multicorn?How can we do that?I only need few columns from the source(Source have 50+ columns and i need only 15 columns) to be transferred into destination,So FDW will work?

If someone can post a sample or edit the below code it will be of great help.

...

ANSWER

Answered 2019-May-22 at 10:28

Done with he comment from jaisus.

Thanks for your comment I think the most simple is indeed to use a FDW to do this particular task. You can find the mysql_fdw on github (github.com/EnterpriseDB/mysql_fdw). What do you need specifically and what is your difficulty on this matter? – Jaisus May 9 at 12:26

Source https://stackoverflow.com/questions/56058133

QUESTION

FDW in Postgres: Batching ids for an external request?

Asked 2017-Apr-25 at 12:42

I'm developing a collection of foreign data wrappers using multicorn and I've run into an issue with batching data.

So, I have two foreign tables, search and data, that are each backed by a foreign data wrapper that I'm writing.

I need to do a basic join on these tables:

...

ANSWER

Answered 2017-Apr-25 at 09:11

You should look at the EXPLAIN output for your query, and then you'll probably see that PostgreSQL is performing a nested loop join, i.e. it scans search for the matching rows, and for each result row scans data for matching rows.

PostgreSQL has other join strategies like hash joins, but for that it would have to read the whole data table, which is probably not a win. You might want to try it by setting enable_nestloopto off and testing query performance. If that is an improvement, you might want to adjust the cost values for the foreign table scan on data to reflect the high “startup costs” so that the planner becomes more reluctant to choose a nested loop join.

There is no such join strategy as you propose – while it may well be a win for FDW joins, it does not offer advantages in regular joins. So if the join strategy you envision is really the optimal one, you'd have to first fetch the data_ids from search, construct a query for data and implement the join in the application.

Source https://stackoverflow.com/questions/43592192

QUESTION

pg_config not found while I have it installed

Asked 2017-Mar-26 at 08:34

I have installed postgresql development packages and I have it in C:/pgsql96 (in bin directory I have packages, such as pg_config, I also added the path to my environment variables. Now that I want to install Multicorn (a postgresql python package), I cloned the git repository of Multicorn in C:/Multicorn, and when I want to run make && make install command, I get the following error:

...

ANSWER

Answered 2017-Feb-13 at 11:58

Try

Source https://stackoverflow.com/questions/42200754

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install Multicorn

You can download it from GitHub.
You can use Multicorn like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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