semvec/pypi-packages huggingface dataset:
bigquery-dry-run 0.3.1
This package is used to perform a BigQuery dry run of all `.sql` files in a folder and its subfolders.
License: MIT
Requires Python: >=3.6,<3.10
Keywords: bigquery

# Overview

This application is used to perform a BigQuery dry run of all `.sql` files in a folder and its subfolders.

Its purpose it so ensure that all SQL files do not have any syntactic errors and make it easier for team members to quickly check a large number of files.

# GCP configuration

Allowing access to GCP should be done following one of the methods detailed in the [GCP documentation.](https://cloud.google.com/docs/authentication) 

The application will rely on your environment having been set up for authentication to GCP (e.g. through `gcloud init` or `environement variable` containing service account credentials), it does not provide a mechanism to receive authentication credentials directly.

# Usage

The application will install a shell command called `bqdry` which is simply passed a folder. It will then traverse the folder and perform a dry run of all `.sql` files found in the folder and any sub folders. The results will be displayed on in the terminal.

For example:
```
$ bqdry my-awesome-project

>File: my-awesome-project/demo.sql
>  Result: Failed
>  Errors: None
>
>Total: 3
>Succeeded: 2
>Failed: 1
```

`bqdry -h` will provide usage information. E.g.

```
usage: bqdry [-h] [-t THREADS] [-v] folder

Dry run of all `.sql` files in folder and subfolders.

positional arguments:
  folder                Top level folder to start scanning for `.sql` files.

optional arguments:
  -h, --help            show this help message and exit
  -t THREADS, --threads THREADS
                        Number of threads for concurrent running of queries. Defaults to 2.
  -v, --verbose         Show all file results, not just failures.
```