semvec/pypi-packages huggingface dataset:
bq-loader 0.1.7
Interactive Command Line Interface for Google BigQuery
License: MIT
Keywords: BigQuery,Google,Bucket,Cloud,Storage,Data Analytic

# bq_loader - Interactive Command Line Interface for Google BigQuery

[![PyPI - Downloads](https://img.shields.io/pypi/dm/bq_loader)](https://pypi.org/project/bq_loader/)
[![License](https://img.shields.io/github/license/naustica/bq_loader)](https://github.com/naustica/bq_loader/blob/master/LICENSE.txt)
[![PyPI - Version](https://img.shields.io/pypi/v/bq_loader)](https://pypi.org/project/bq_loader/)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/bq_loader)](https://pypi.org/project/bq_loader/)

## Install

```bash
pip install bq_loader
```

## Authentication

This package is built on top of Google libraries. To use this package you need to authenticate with your google account. For more information see: https://cloud.google.com/storage/docs/authentication.

You can use the package [gcloud](https://pypi.org/project/gcloud/) to authenticate yourself.

```bash
gcloud auth
```

## Usage

### Command Line Interface

```bash
bqloader
```

![Demo](https://raw.githubusercontent.com/naustica/bq_loader/master/media/demo.gif)

### API

#### Create a table from a local file or directory

```python
from bq_loader import create_table_from_local

 create_table_from_local(table_id='snapshot',
                         project_id='subugoe-collaborative',
                         dataset_id='resources',
                         file_path='test_data/*',
                         schema_file_path='test_schema/schema_crossref.json',
                         source_format='jsonl',
                         write_disposition='WRITE_APPEND',
                         table_description='Test Table generated by bq_loader',
                         ignore_unknown_values=True)
```

#### Create a table from a Google Bucket

```python
from bq_loader import create_table_from_bucket

create_table_from_bucket(uri='gs://bigschol/tests/*',
                         table_id='bq_loader_test',
                         project_id='subugoe-collaborative',
                         dataset_id='resources',
                         schema_file_path='test_schema/schema_crossref.json',
                         source_format='jsonl',
                         write_disposition='WRITE_EMPTY',
                         table_description='Test Table generated by bq_loader',
                         ignore_unknown_values=True)
```

#### Upload local files to a Google Bucket

```python
from bq_loader import upload_files_to_bucket

upload_files_to_bucket(bucket_name='bigschol',
                       file_path='test_data/*',
                       gcb_dir='tests')
```
preacher 0.15.11
Web API Verification without Coding.
License: MIT
Requires Python: >=3.7,<4.0

# Preacher: Web API Verification without Coding

[![PyPI version](https://badge.fury.io/py/preacher.svg)][PyPI]
[![Documentation Status](https://readthedocs.org/projects/preacher/badge/?version=latest)][Read the Docs]
[![CircleCI](https://circleci.com/gh/ymoch/preacher.svg?style=svg)][Circle CI]
[![Codecov](https://codecov.io/gh/ymoch/preacher/branch/master/graph/badge.svg)][Codecov]
[![Language grade: Python](https://img.shields.io/lgtm/grade/python/g/ymoch/preacher.svg?logo=lgtm&logoWidth=18)][LGTM]
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)][Black]

Preacher verifies API servers,
which requests to the servers and verify the responses along to given scenarios.

Test scenarios are written only in [YAML][] declaratively, without coding.
In spite of that, Preacher can validate your web API flexibly,
which enables you to test using real (neither mocks nor sandboxes) backends.

- Responses are analyzed [jq][] or [XPath][] queries
- Validation rules are based on [Hamcrest][] (implemented by [PyHamcrest][]).

The full documentation is available at [preacher.readthedocs.io][Read the Docs].

## Targets

- Flexible validation to test with real backends: neither mocks nor sandboxes.
  - Matcher-based validation.
- CI Friendly to automate easily.
  - A CLI application and YAML-based scenarios.

## Usage

First, install Preacher.

The most basic way to install Preacher is using `pip`. Supports only Python 3.7+.

```sh
$ pip install preacher
$ preacher-cli --version
```

Instead of `pip`, Docker images are also available on
[Docker Hub](https://hub.docker.com/r/ymoch/preacher)
as `ymoch/preacher`.
By default, the container working directory is `/work`,
and the host directory may be mounted here.

```sh
$ docker pull ymock/preacher
$ docker run -v $PWD:/work ymoch/preacher preacher-cli --version
```

Second, write your own scenario.

```yaml
# scenario.yml
label: An example of a scenario
cases:
  - label: An example of a case
    request: /path/to/foo
    response:
      status_code: 200
      body:
        - describe: .foo
          should:
            equal: bar
```

Then, run ``preacher-cli`` command.

```sh
$ preacher-cli -u http://your.domain.com/base scenario.yml
```

For more information such as grammer of scenarios,
see [the full documentation][Read the Docs].

## License

[![MIT License](https://img.shields.io/badge/License-MIT-brightgreen.svg)][MIT License]

Copyright (c) 2019 Yu MOCHIZUKI


[YAML]: https://yaml.org/
[jq]: https://stedolan.github.io/jq/
[XPath]: https://www.w3.org/TR/xpath/all/
[Hamcrest]: http://hamcrest.org/
[PyHamcrest]: https://pyhamcrest.readthedocs.io/
[MIT License]: https://opensource.org/licenses/MIT

[Read the Docs]: https://preacher.readthedocs.io/
[PyPI]: https://badge.fury.io/py/preacher
[Circle CI]: https://circleci.com/gh/ymoch/preacher
[Codecov]: https://codecov.io/gh/ymoch/preacher
[LGTM]: https://lgtm.com/projects/g/ymoch/preacher/context:python
[Black]: https://github.com/psf/black
pep621 0.4.0.post2
PEP 621 metadata parsing
License: MIT
Requires Python: >=3.7

# pep621

[![pre-commit.ci status](https://results.pre-commit.ci/badge/github/FFY00/python-pep621/main.svg)](https://results.pre-commit.ci/latest/github/FFY00/python-pep621/main)
[![checks](https://github.com/FFY00/python-pep621/actions/workflows/checks.yml/badge.svg)](https://github.com/FFY00/python-pep621/actions/workflows/checks.yml)
[![tests](https://github.com/FFY00/python-pep621/actions/workflows/tests.yml/badge.svg)](https://github.com/FFY00/python-pep621/actions/workflows/tests.yml)
[![codecov](https://codecov.io/gh/FFY00/python-pep621/branch/main/graph/badge.svg?token=9chBjS1lch)](https://codecov.io/gh/FFY00/python-pep621)
[![Documentation Status](https://readthedocs.org/projects/pep621/badge/?version=latest)](https://pep621.readthedocs.io/en/latest/?badge=latest)

###### DEPRECATED! The project was renamed to `pyproject-metadata`.

> Dataclass for PEP 621 metadata with support for [core metadata] generation

This project does not implement the parsing of `pyproject.toml`
containing PEP 621 metadata.

Instead, given a Python data structure representing PEP 621 metadata (already
parsed), it will validate this input and generate a PEP 643-compliant metadata
file (e.g. `PKG-INFO`).


## Usage

After [installing `pep621`](https://pypi.org/project/pep621/),
you can use it as a library in your scripts and programs:

```python
from pep621 import StandardMetadata

parsed_pyproject = { ... }  # you can use parsers like `tomli` to obtain this dict
metadata = StandardMetadata.from_pyproject(parsed_pyproject)
print(metadata.entrypoints)  # same fields as defined in PEP 621

pkg_info = metadata.as_rfc822()
print(str(pkg_info))  # core metadata
```


[core metadata]: https://packaging.python.org/specifications/core-metadata/
bstmapcbe 0.0.1
A Package used for finding the routes for important places in Coimbatore,India By Arjun K PSG ICE
License: MIT
Keywords: map

This python package is developed by Arjun K PSG ICE (20-24) which can be used for searching the available places on the Coimbatore map
Just call the startmap() to run our map

Change Log
====================

0.0.1 (14/06/22)
--------------------
- First Release