semvec/pypi-packages huggingface dataset:
vodek 0.0.7
qr like code
Requires Python: >=3.6

# vodek
### response code like qrcode
creating code
-------------
this will convert the given string to code and return the code
##### usage:
```python
import vodek
code=vodek.make('string')
print(code)
```
reading code
------------
this will convert the given code to string and return the value
##### using vodek from terminal
converting string to code and print code
```bash
$ vodek --write 'string'
```
converting code to string and print value
```bash
$ vodek --read 'code'
```
for more help from terminal
##### use
```bash
vodek -h
```
### OR
```bash
vodek --help
```
<h6 style="text-align: center">by vkv-onfire</h6>
igqloo 0.1
A simple command-line tool for writing GQL queries
Requires Python: >=3.8, <4
Keywords: graphql,gql,cli,queries,development

# igqloo

A small tool for interacting with GQL APIs

Arguments, mutations, aliases are all supported. Other features, such as
fragments, are left unsupported with the opinion that, when a query becomes
large enough to warrant them, you might be best feeding in a file containing
your query.

```bash
igqloo <graphql_uri> customer(name:"gerhalt@gmail.com").id,firstName,lastName
```

Under the surface, generates a GraphQL query that looks like:

```gql
query {
    customer(name:"gerhalt@gmail.com") {
        id, firstName, lastName
    }
}
```

Queries are made simple using three key concepts:

1. Dot-notation, with `.` indicating the beginning of a nested query level
2. A comma `,` indicates a field on the same level as the prior field
3. Parenthesis `()` for filters and "quoting" aliases
pan-cortex-data-lake 2.0.0b1
Python idiomatic SDK for Cortex™ Data Lake.
Requires Python: >=3.5
Keywords: cortex,data,lake,datalake,sdk,api,palo alto networks

![Tests](https://github.com/PaloAltoNetworks/pan-cortex-data-lake-python/workflows/Tests/badge.svg) ![PyPI upload](https://github.com/PaloAltoNetworks/pan-cortex-data-lake-python/workflows/PyPI%20upload/badge.svg?branch=master) [![PyPI version](https://badge.fury.io/py/pan-cortex-data-lake.svg)](https://badge.fury.io/py/pan-cortex-data-lake)

# Palo Alto Networks Cortex™ Data Lake SDK

Python idiomatic SDK for the Cortex™ Data Lake.

The Palo Alto Networks Cortex Data Lake Python SDK was created to assist
developers with programmatically interacting with the Palo Alto Networks
Cortex™ Data Lake API.

The primary goal is to provide full, low-level API coverage for the
following Cortex™ Data Lake services:

-   Query Service

The secondary goal is to provide coverage, in the form of helpers, for
common tasks/operations.

-   Log/event pagination
-   OAuth 2.0 and token refreshing
-   More, coming soon!

-   Documentation: <https://cortex.pan.dev>
-   Free software: ISC license

---

## Features

-   HTTP client wrapper for the popular Requests library with full access to its features.
-   Language bindings for Query Service.
-   Helper methods for performing common tasks, such as log/event pagination.
-   Support for OAuth 2.0 grant code authorization flow.
-   Library of example scripts illustrating how to leverage the SDK.
-   Support for API Explorer Developer Tokens for easier access to API!

## Status

The Palo Alto Networks Cortex™ Data Lake Python SDK is considered **alpha** at this time.

## Installation

From PyPI:

    $ pip install pan-cortex-data-lake

## Obtaining and Using OAuth 2.0 Tokens

If you're an app developer, work with your Developer Relations representative to obtain your OAuth2 credentials. API Explorer may optionally be used to generate a Developer Token, which can also be used to authenticate with the API. For details on API Explorer developer tokens, please visit <https://cortex.pan.dev/docs/learn/developer_tokens>.

# Example

```python
>>> from pan_cortex_data_lake import Credentials, QueryService
>>> c = Credentials()
>>> qs = QueryService(credentials=c)
>>> query_params = {
...     "query": "SELECT * FROM `1234567890.firewall.traffic` LIMIT 1",
... }
>>> q = qs.create_query(query_params=query_params)
>>> q.status_code
201
>>> q.json()
{'jobId': '40fedce6-ddf5-44cf-9af2-7c3d5303f388', 'uri': '/query/v2/jobs/40fedce6-ddf5-44cf-9af2-7c3d5303f388'}
>>> results = qs.get_job_results(job_id='40fedce6-ddf5-44cf-9af2-7c3d5303f388')
>>> results.json()
```

# Contributors

-   Kevin Steves - [github](https://github.com/kevinsteves)
-   Steven Serrata - [github](https://github.com/sserrata)