semvec/pypi-packages huggingface dataset:
WrikePy 1.0.4
A Python wrapper for the Wrike API.
Requires Python: >=3.6

# WrikePy
WrikePy is a Python Wrapper for the [Wrike.com](https://www.wrike.com/) API.

## Getting Started
### Import WrikePy
```python
from WrikePy import *
```
### Initialize API
Every Wrike API call requires a Wrike object parameter in order to send a request.
```python
wrike = Wrike(base_url, perm_access_token, ssl_verify)
```
 - The **base_url** parameter is the base URL for every Wrike API
   request. The default value is "https://www.wrike.com/api/v4". 
 - The **perm_access_token** parameter is the API key that you generate from your Wrike account (Apps & Integrations >  API). The default value is "None".
  - The **ssl_verify** parameter is a security feature that comes
   with secure urls. The default value is "True".
### Wrike API
The format of WrikePy mirrors that of the [Wrike API](https://developers.wrike.com/) documentation methods. WrikePy includes a class for each API method and a function for each API call type. As an example, the following will get a folders and/or projects from within a folder...
```python
folders = FoldersProjects(wrike, ["folderId"], {"paramKey": "paramValue"}).query__folders_folderId_folders()
```
### Function Naming Conventions
Functions following the naming conventions put forth in the API documentation.
| Name | Request Type |
|--|--|
| query__ | GET |
| create__ | POST |
| update__ | PUT |
| delete__ | DELETE |
| create_files__ | POST (Upload Files) |
| update_files__ | PUT (Update Files) |
Tacoma-lib 1.0.1
TACOMA lib

# TACOMA lib 
A python library for applying Machine Learning in CFD. This library is on active deveplopment and expect the API to change overtime.
At the moment, most of the classes and functions are centered on Reduce Order Modelling techniques (ROMs).

The authors of this library are:
* Jaime Bowen Varela (jbowvar(at)inta.es)
* Rodrigo Castellanos (rcasgar(at)inta.es)
* Alejandro Gorgues (gorguesva(at)inta.es)
## How to install
The official Pypi distribution can be downloaded from Pypi with:
```bash
pip install Tacoma-lib
```
## Documentation
The official documentation is under construction. There are couple of examples available to understand some of the inner workings of the library. 
## Modules of the library
The modules of the libray are divided into:
* rom: contains the Reduced Order Modelling classes
* interpolator: contains interpolars and redefyined classes
* metrics: contains clasess for metrics

There are a couple of more of modules that contains utils and stuff. This will surely change in the future. 
## Examples
The examples are contained in [here](https://github.com/jaimebw/tacoma_lib/tree/main/examples). The examples show some implemetations of the Tacoma lib for ROMs:
* [An example on how to use ROMs with Sklearn](https://github.com/TACOMA-INTA/tacoma-lib/blob/main/examples/rom_regression_example.py)
* [An example on how to do hyperoptimization with Sklearn and Optuna](https://github.com/TACOMA-INTA/tacoma-lib/blob/main/examples/rom_sklearn_optuna_example.py)
* [An example on how to use ROMs with PyTorch](https://github.com/TACOMA-INTA/tacoma-lib/blob/main/examples/rom_pytorch_example.py)

More examples to be added in the future