| Name | Version | Summary | date |
| streamlit-sqlalchemy |
0.1.1 |
Some templating for streamlit and sqlalchemy |
2024-02-23 16:42:02 |
| llama-index-packs-vanna |
0.1.4 |
llama-index packs vanna integration |
2024-02-22 03:21:56 |
| llama-index-tools-database |
0.1.3 |
llama-index tools database integration |
2024-02-21 22:15:45 |
| llama-index-readers-database |
0.1.3 |
llama-index readers database integration |
2024-02-21 19:42:31 |
| llama-index-readers-athena |
0.1.3 |
llama-index readers athena integration |
2024-02-21 19:27:33 |
| bquest |
0.5.0 |
Effortlessly validate and test your Google BigQuery queries with the power of pandas DataFrames in Python. |
2024-02-20 18:26:57 |
| beatdrop |
0.1.0a9 |
Simplified, scalable task scheduling with typechecking. |
2024-02-20 01:49:32 |
| inline-sql |
0.1.2 |
Inline SQL in any Python program, on local dataframes |
2024-02-17 00:49:35 |
| vaultdb |
0.10.1.dev802 |
VaultDB embedded database |
2024-02-16 19:13:46 |
| exif2pandas |
2.1 |
Extract EXIF to pandas / SQL / Excel / Feather |
2024-02-15 13:26:59 |
| df-to-azure |
0.9.1 |
Automatically write pandas DataFrames to SQL by creating pipelines in Azure Data Factory with copy activity from blob to SQL |
2024-02-15 09:53:49 |
| rpa-cooperativa |
1.1.20 |
Classes referente automação com python para... api fluid, api whatsapp, api sms, sql, acc |
2024-02-14 15:25:56 |
| bigquery-test-kit |
0.5.0 |
BigQuery test kit |
2024-02-05 09:28:40 |
| heimdallm |
1.0.3 |
Construct trusted SQL queries from untrusted input |
2024-02-03 08:47:43 |
| sqlalchemy_exasol |
5.0.0 |
EXASOL dialect for SQLAlchemy |
2024-02-02 08:21:40 |
| llm-sql-prompt |
0.3.0 |
Utility to generate ChatGPT prompts for SQL writing, offering table structure snapshots and sample row data from Postgres and sqlite databases. |
2024-01-31 18:39:08 |
| mockTestIC |
3.0.10 |
O código utiliza a biblioteca Faker para gerar dados fictícios com base em um mapeamento pré-definido. A função fakeJson recebe um dicionário representando dados em formato JSON e substitui os valores associados às chaves de acordo com o mapeamento fornecido. Cada chave do JSON é mapeada para uma função correspondente da biblioteca Faker, gerando assim dados fictícios variados, como nomes, endereços, datas e números. Se uma chave não estiver no mapeamento, a função levanta uma exceção de valor inválido. |
2024-01-30 19:10:45 |
| sql-inspect |
1.0.0 |
A django middleware package for logging database SQL queries to console |
2024-01-30 18:39:19 |
| lckytools |
0.0.22 |
|
2024-01-30 09:17:09 |
| query-exporter |
2.10.0 |
Export Prometheus metrics generated from SQL queries |
2024-01-28 17:31:19 |