KayPacha
SQL data extraction for Scienti and Colav parners Oracle databases
Description
Package extract the data from SQL databases from Oracle Databases from Scienti or Colav parners Models are defined here, filters etc..
Dependecies needed before installation
Before installing the package, you need to install Graphviz
Ubuntu and Debian
sudo apt-get install graphviz graphviz-dev
If you need more information about the installation, visit: https://pygraphviz.github.io/documentation/stable/install.html
Installation
Package
pip install kaypacha
Usage
Scienti
Oracle DB Colav docker database for scienti have to be already loaded, take a look here
Remember you only can use max 2 threads due a Oracle XE version limitation more information here
Saving the model product for scienti on MongoDB (default users are UDEA_CV,UDEA_GR,UDEA_IN)
kaypacha_scienti --mongo_dbname scienti_udea_2022 --model product --max_threads 2 --checkpoint
Saving all models for scienti on MongoDB
kaypacha_scienti --mongo_dbname scienti_udea_2022 --max_threads 2 --checkpoint
Getting a JSon file sample for the model product for scienti (WARNING: getting the full DB in a file require a huge amount of RAM, use it with careful.)
kaypacha_scienti --mongo_dbname scienti_udea_2022 --model product --json prod.json --max_threads 2 --sample
Example U externado
kaypacha_scienti --mongo_dbname scienti_uec_2022 --model product --max_threads 2 --cvlac_user UEC_CV --gruplac_user UEC_GR --institulac_user UEC_IN --checkpoint
or
kaypacha_scienti --mongo_dbname scienti_uec_2022 --model endorsement --max_threads 2 --cvlac_user UEC_CV --gruplac_user UEC_GR --institulac_user UEC_IN --checkpoint
Example Unaula
kaypacha_scienti --mongo_dbname scienti_ual_2023 --max_threads 2 --cvlac_user UNAULA_CV --gruplac_user UNAULA_GR --institulac_user UNAULA_IN --checkpoint
Example Univalle
kaypacha_scienti --mongo_dbname scienti_univalle_2023 --max_threads 2 --cvlac_user UVALLE_CV --gruplac_user UVALLE_GR --institulac_user UVALLE_IN --checkpoint
Entities models supported fo Scienti
- product (EN_PRODCUTO)
- netowrk (EN_RED)
- project (EN_PROYECTO)
- event (EN_EVENTO)
- patent (EN_PATENTE)
- author (EN_RECURSO_HUMANO)
TODO
- implement all the main tables for Scienti.
- resgiter "EN_REGISTRO"
- industrial_secret "EN_SECRETO_INDUSTRIAL"
- recognition "EN_RECONOCIMIENTO"
- art_product "EN_PROD_ARTISTICA_DETALLE"
SIIU
Oracle DB Colav docker database for siiu have to be already loaded, take a look here
Remember you only can use max 2 threads due a Oracle XE version limitation more information here
Saving the model project for siiu on MongoDB
kaypacha_siiu --model project --max_threads 2 --checkpoint
Saving all models for siiu on MongoDB
kaypacha_siiu --max_threads 2 --checkpoint
Getting a JSON file sample for the model product for scienti (WARNING: getting the full DB in a file require a huge amount of RAM, use it with careful.)
Getting the first 100 registers
kaypacha_siiu --model project --json project.json --max_threads 2 --sample
Getting a random sample, 5.5% of the total amount of registers
kaypacha_siiu --model project --json project.json --max_threads 2 --rand_sample --sample_percent 5.5
Making a graph of the model (There are two types of files supported: svg and png)
kaypacha_siiu --make_diagram project svg
Entities models supported fo SIIU
- project (SIIU_PROYECTO)
Some errors
[WARNING] ORA-12504: TNS:listener was not given the SERVICE_NAME in CONNECT_DATA
A possible solution is to use --ora_dburi 0.0.0.0:1521/XE
Generating Diagrams with BlockDiag
Exaple for patent on scienti.
Also support formats such as SVG and PDF.
kaypacha_blockdiag --model scienti --submodel patent --filename patent.png
License
BSD-3-Clause License
Links
Metadata
Release files for KayPacha 0.0.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| KayPacha-0.0.5.tar.gz | 22.0 kB | Without provenance | Details for KayPacha-0.0.5.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| KayPacha-0.0.5-py3-none-any.whl | Python 3 | none | any | Details for KayPacha-0.0.5-py3-none-any.whl |
Total release size: 55.8 kB
Release files / KayPacha-0.0.5.tar.gz
| Download URL | KayPacha-0.0.5.tar.gz |
|---|---|
| Size | 22.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
6e35f05034780e3f39e19899fd41c3399e32e4c773ccb0cce01ede6c186a3e4e
|
|
BLAKE2b-256 checksum How to use checksums |
8eedf96c4e00ed89f3daefe61d9384aebebeef4e352668e789f5179a46d13d4b
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.12.0
|
Release files / KayPacha-0.0.5-py3-none-any.whl
| Download URL | KayPacha-0.0.5-py3-none-any.whl |
|---|---|
| Size | 33.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
0ecafd19fd308c73e4ee31782f9135b38fefe9bcb2dee9e2f5408360c659badc
|
|
BLAKE2b-256 checksum How to use checksums |
8afba7edaabe4e157b711f36205644db26553decbc14cfab2f6a8d26f7c65a17
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.12.0
|
Security for KayPacha 0.0.5
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.