semvec/pypi-packages huggingface dataset:
free-robux-generator-robux-free-codes-for-roblox-2023-v-1413 9.548
FREE ROBUX GENERATOR ROBUX FREE CODES FOR ROBLOX 2023
Keywords: free-robux-generator-robux-free-codes-for-roblox-2023

# FREE ROBUX GENERATOR ROBUX FREE CODES FOR ROBLOX 2023

> Daily Updated : FREE ROBUX GENERATOR ROBUX FREE CODES FOR ROBLOX 2023

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================================================

As mentioned above, Robux 2022 is a type of in-game currency that can be used to improve your experience in the game. There are different packages containing different amounts of Robux in the game’s store.


## FREE ROBUX GENERATOR ROBUX FREE CODES FOR ROBLOX 2023

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md-ext 0.0.4
Markdown extensions

README
=======

Extra third party extensions for ``Python-Markdown``

Install
--------

```bash
  $ pip install md_ext
```

Usage
-----

```python

import markdown

data = "![alt](image.png){width=600}"
md = markdown.Markdown(extensions=['md_ext.img'])
html = md.convert(data)
print(html)
```

Output:

```python
'<p><img src="image.png" width="600" /></p>'
```
test-sdk-1114 0.0.1
short package description
Requires Python: >=3.6

# liquidswap-sdk-python

<!--
WIP:
- [x] convertToDecimals
- [ ] calculateRates
- [ ] createSwapTransactionPayload
- [ ] create pypl package -->

<!-- Deprecated

# Python SDK Example

This is a simple example for the Python SDK.

## Functions:

### get your APT and USDT balance

`get_apt_balance()`

`get_usdt_balance()`

### get expected amount out USDT with target `apt_in`

`get_amount_out(apt_in)`

### swap `apt_in` APT to USDT

`swap(from_amount, to_amount)`

## Expected Results:

```python
public key: 0x164eb1af65b9252a01f75e2f6da2bc6624eec64ba19db04be13ce3d182f4c36b
balance: APT 1.272624, USDT 0.009735
apt_in: 0.0001, usdt_out: 0.000748
swap 0.0001 APT to 0.000748 USDT...
txn_hash: 0x493b702a7358dee53ff4f09ce32d126dc62c48c2cc666b2eb658dc94ba9a73b2
```
-->
dbt-spark-cde 1.2.0
The CDE API based Cloudera Spark adapter plugin for dbt
Requires Python: >=3.7

# dbt-spark-cde

The `dbt-spark-cde` adapter allows you to use [dbt](https://www.getdbt.com/) [Cloudera Data Platform](https://cloudera.com) with CDE API server support. This code bases use the dbt-spark project (https://github.com/dbt-labs/dbt-spark), and provides CDE API based connectivity support over it. 

## Getting started

- [Install dbt](https://docs.getdbt.com/docs/installation)
- Read the [introduction](https://docs.getdbt.com/docs/introduction/) and [viewpoint](https://docs.getdbt.com/docs/about/viewpoint/)

### Requirements

Python >= 3.9

dbt-core ~= 1.2.0

requests >= 2.28.1

requests-toolbelt >= 0.9.1

pyspark

sqlparams

### Installing dbt-spark-cde

`pip install dbt-spark-cde`

### Profile Setup

```
demo_project:
  target: dev
  outputs:
    dev:
     type: spark_cde
     method: cde
     schema: my_db
     auth_endpoint: https://service.spark-cde-gateway.my.org.com/
     host: https://spark-cde-gateway.my.org.com/dex/api/v1/
     user: my_user
     password: my_pass
```

- To obtain auth_endpoint follow the steps here: (https://docs.cloudera.com/data-engineering/cloud/api-access/topics/cde-api-get-access-token.html)

### Caveats
- While using cde , in the Livy UI if you notice sessions change state to dead from starting instead of idle, make sure there is a proper mapping for the user in the IDBroker mapping section 
- Actions > Manage Access > IDBroker Mappings . [Reference](https://docs.cloudera.com/cdf-datahub/7.2.15/flink-analyzing-data/topics/cdf-datahub-sa-create-idbroker-mapping.html)
- Also make sure the workload password is set either through UI or CLI. [Reference](https://docs.cloudera.com/management-console/cloud/user-management/topics/mc-setting-the-ipa-password.html)

## Supported features
Please see the original adapter documentation: https://github.com/dbt-labs/dbt-spark and https://docs.getdbt.com/reference/warehouse-profiles/spark-profile
vdk-logging-ltsv 0.1.693641831
Versatile Data Kit SDK plugin that changes logging output to LTSV format.

# This plugin is deprecated, please use vdk-logging-format instead.


This is a POC level implementation of a plugin which changes the logging format of vdk-core to LTSV for the purposes of structured data visualization.

The new format has the following fields, separated by tabs:
* timestamp: a timestamp of when the log is made;
* created: the same timestamp in the unix epoch format;
* jobname: the name of the data job;
* level: the logging level - one of INFO, WARNING, DEBUG, ERROR;
* modulename: the name of the module, inside of which the logging call is made;
* filename: the name of the file containing the logging call being made;
* lineno: the number of the line of code, at which the logging call is made;
* funcname: the name of the function, inside which the loggin call is made;
* attemptid: string identifying this particular execution of the data job;
* message: any additional logged information.

The label names follow the labelling recommendations found at http://ltsv.org/.

# Usage

Switching vdk logging can be done by simply installing the plugin:

```python
pip install vdk-logging-ltsv
```

And all logs will be automatically formatted to LTSV format. They would start to look something like this:
```
@timestamp:2021-08-04T12:51:11	created:1628070671	jobname:example-job	level:DEBUG	modulename:vdk.internal.trino_connection	filename:managed_connection_base.py	lineno:69	funcname:connect	attemptid:1628070671-452613-739749	message:Established <trino.dbapi.Connection object at 0x10b9b1d30>
@timestamp:2021-08-04T12:51:11	created:1628070671	jobname:example-job	level:DEBUG	modulename:vdk.internal.trino_connection	filename:managed_cursor.py	lineno:29	funcname:execute	attemptid:1628070671-452613-739749	message:Executing query: select 1
```
vdk-logging-json 0.1.693641831
Versatile Data Kit SDK plugin that changes logging output to JSON format.

# This plugin is deprecated, please use vdk-logging-format instead.


This is a POC level implementation of a plugin which changes the logging format of vdk-core to JSON for the purposes of structured data visualization in a log aggregator.

The new format has the following fields:
 * @timestamp: a timestamp of when the log is made;
 * jobname: the name of the data job;
 * level: the logging level - one of INFO, WARNING, DEBUG, ERROR;
 * modulename: the name of the module, inside of which the logging call is made;
 * filename: the name of the file containing the logging call being made;
 * lineno: the number of the line of code, at which the logging call is made;
 * funcname: the name of the function, inside which the loggin call is made;
 * attemptid: string identifying this particular execution of the data job;
 * message: any additional logged information.

If the log record contains an error, it will also contain the following fields:
 * error.message: the message of the exception;
 * error.stack_trace: a stack trace of the exception;
 * error.type: the type of exception.

The label names follow the labelling recommendations found at http://ltsv.org/.
The reason we chose the LTSV naming standard is due to the fact that this plugin was based on a previous LTSV-formatting plugin,
as well as the fact that there is no single JSON naming standard.

Additionally, double quote characters within the message are escaped.

# Usage

Switching vdk logging can be done by simply installing the plugin:

```python
pip install vdk-logging-json
```

And all logs will be automatically formatted to JSON. They will appear like this:
```
{"@timestamp": "2021-10-14T11:37:44.703Z", "message": "Checking if job should be skipped:", "level": "INFO", "lineno": 102, "filename": "execution_skip.py", "modulename": "vdk.plugin.control_cli_plugin.execution_skip", "funcname": "_skip_job_if_necessary", "jobname": "gg-job4", "attemptid": "1634211464-1ee897-a3f0eb"}```