semvec/pypi-packages huggingface dataset:
mydebug 0.1.1
A simple debugging tool for Python

# DebugMode

## Overview
DebugMode is a class that provides functionality for debugging, logging, and printing messages with different colors.

## Methods

### `__init__(self, debugMode=True, logFile=None)`
Initializes the DebugMode instance.
- **Args:**
  - `debugMode` (bool): A flag to enable or disable debug mode. Default is True.
  - `logFile` (str): The path to a log file. If provided, logs will be written to this file. Default is None.

### `setDebugMode(self, debugMode)`
Sets the debug mode.
- **Args:**
  - `debugMode` (bool): A flag to enable or disable debug mode.

### `getDebugMode(self)`
Returns the current debug mode.
- **Returns:**
  - `bool`: The current debug mode.

### `debugPrint(self, message=None, fonction=None)`
Prints a debug message or executes a function if provided.
- **Args:**
  - `message` (str): The message to print. Default is None.
  - `fonction` (callable): A function to execute. Default is None.

### `warningPrint(self, message)`
Prints a warning message.
- **Args:**
  - `message` (str): The warning message to print.

### `logPrint(self, message)`
Logs a message to the log file if it is open.
- **Args:**
  - `message` (str): The message to log.
- **Raises:**
  - `ValueError`: If the log file is not open.
tempo-api-python-client 0.12.0
Python bindings for Tempo (https://apidocs.tempo.io/)
Requires Python: >=3.10.14

# tempo-api-python-client

Python bindings for Tempo Rest API.

This is a Tempo API client library to simplify the interaction with Tempo timesheets. The implementation supports Tempo API v3 and v4.

Pip release is available: https://pypi.org/project/tempo-api-python-client/

Tempo Rest API documentation can be found at https://apidocs.tempo.io/


## Installation

Install current release by pip

```
pip install tempo-api-python-client
```


## Getting Started

You need an API token for communicating with tempo REST APIs. 

### For v3 use

    from tempoapiclient import client_v3

    tempo = client_v3.Tempo(
        auth_token="<your_tempo_api_key>",
        )

    worklogs = tempo.get_worklogs(
        dateFrom="2019-11-10",
        dateTo="2019-11-11"
        )

    for i in worklogs:
        print(i)

### For v4 use

    from tempoapiclient import client_v4

    tempo = client_v4.Tempo(
        auth_token="<your_tempo_api_key>",
        )

#### Retrieve Worklogs

    worklogs = tempo.get_worklogs(
        dateFrom="2019-11-10",
        dateTo="2019-11-11"
        )

    for i in worklogs:
        print(i)

There are also functions to retrieve `user` and `team`-specific worklogs.


#### Create Worklog

    logged_worklog = tempo.create_worklog(
        accountId="<your_jira_account_id>",
        issueId=12345,
        dateFrom="2019-11-11",
        timeSpentSeconds=3600,
        description="Something",
        startTime="17:00:00"
        attributes=[{_WorkType_: "Development"}]
    )

#### Update Worklog

    logged_worklog = tempo.update_worklog(
        id="<id_of_the_worklog_to_be_updated>"  # required
        accountId="<your_jira_account_id>",     # required
        dateFrom="2019-11-11",                  # required
        timeSpentSeconds=3600,                  # required
        description="Something",                # optional
        startTime="17:00:00"                    # optional
    )

#### Delete Worklog

    delete_response = tempo.delete_worklog(<worklog_id>)


## Code Format

- Flake8: `flake8 --max-line-length=120 tempoapiclient/*`

- Pylint: `pylint --max-line-length=120 tempoapiclient`


## Contributing

Contribution is welcome. See [CONTRIBUTING.md](CONTRIBUTING.md) for more details.