semvec/pypi-packages huggingface dataset:
flask-hmac-auth-client-m4l1c3 1.0.0
A client library for computing HMAC values in flask_hmac_auth_client_m4l1c3

# flask-hmac-auth-client
Python client library for flask-hmac-auth

# Use:
- Create an environment variable named APIKEY:

```bash
export APIKEY="WHATEVER_YOU_WANT!!!"
```
```python
from flask_hmac_auth_client import MessageAuthentication()
a = MessageAuthentication()
a.compute('a', 'a')
```
xdmf-dolfin-fix 0.6.2
A tiny package to modify the node order of quadratic triangles and tets in a xdmf-hdf mesh to work with FEniCS/DOLFIN.

# xdmf_dolfin_fix

There is an xdmf import issue in FEniCS/DOLFIN. Quadratic triangles and tetrahedrons
are imported incorrectly. The CLI tool `xdmf-dolfin-fix` fixes this issue by reordering element numbers.

### Example usage
~~~
xdmf-dolfin-fix old.xdmf            # fix old.xdmf
xdmf-dolfin-fix old.xdmf new.xdmf   # create fixed new.xdmf
xdmf-dolfin-fix old.geo -d3         # create fixed old.xdmf from gmsh
xdmf-dolfin-fix old.msh new.xdmf    # create fixed new.xdmf from gmsh
~~~

### Problem

At some point of the simulation FEniCS/DOLFIN orders the vertices of all elements
in numerically accending order. Nodes on the edges of elements -- as present
in quadratic triangles and quadratic tetrahedrons -- are not swapped.

So internally, the node numbers of an arbitrary quadratic tetrahedron

~~~
[ vertices |    edges   ]
[ 51 74 12 | 14 72 1003 ]
~~~

would be reordered to

~~~
[ 12 51 74 | 14 72 1003 ]
~~~

Now, the vertex nodes `[12 51 74]` are sorted, but the edge nodes `[14 72 1003]`
are left unchanged. This results in a twisted geometry.

### Fix

`xdmf-dolfin-fix` sorts the vertex nodes **and** reorders the edge nodes accordingly. This
will result in

~~~
[ 12 51 74 | 1003 14 74 ]
~~~

A further sorting within DOLFIN has no effect and, thus, will not mess up
this ordering.
smalldata 0.0.3
Unix Pipe Fittings For Data Science

# UNIX pipe fittings for statistics

In the quest for [command line data science](https://github.com/jeroenjanssens/data-science-at-the-command-line), 
this kit contains three command line utilities intended to be used in UNIX pipes.

All three process STDIN to STDOUT output their docstrings if run without parameters.

Python 3 is required. 

## sd_c  (smalldata count)

Is a regular expression counter filter, contained in `smalldata/counter.py`. Please see docstring for further help.

## sd_g  (smalldata groupby) 

Concatenates lines from stdin that match a regular expression, contained in `smalldata/groupby.py`. Please see docstring.

## sd_e (smalldata extract)  

In the spirit of [RegExSerDe](https://github.com/apache/hive/blob/trunk/contrib/src/java/org/apache/hadoop/hive/contrib/serde2/RegexSerDe.java), this
tool uses regular expressions to generate a CSV file from a free-form text file. It is contained in `smalldata/extract.py` and has a docstring.


## Other Useful Tools

If you've got CSV files, you should definitively check out [q](http://harelba.github.io/q/). 

## To Do

A cookbook would be nice. Showing how to analyze log files etc.

## History

Used to live in a gist: https://gist.github.com/martinvirtel/94cf47f64bf304e1c66598e93cd565c4
nbspellcheck 0.0.5
Spell checker for jupyter notebooks
Requires Python: >3.5

# npspellcheck  

**spell checking jupyter notebooks**

Writing correctly should be a priority, even for programmers and scientists. 

But this is not easy in jupyter notebooks. 

In english, a good solution is to make use of the spellchecker notebook extension, which highlights incorrect text: 

```
pip install jupyter_contrib_nbextensions
jupyter contrib nbextension install --user
jupyter nbextension enable spellchecker/main
```

However, this extension is currently not able to suggest corrections, and is only available for English. 

Since I write blog posts based on jupyter notebooks in French, I came up with a small script for spell checking. 

Installation: 

```
pip install nbspellcheck
```

Example of use:

```
nbspellcheck.py my_jupyter_notebook.ipynb -l fr
```

A big thank you to the developers of 

* [nltk](http://www.nltk.org/) : python natural language toolkit
* [pyspellchecker](https://pypi.org/project/pyspellchecker/) : python spell checker

that are doing all the heavy lifting. 

I made this real fast, and the user interface can be improved. Please don't hesitate to send a PR.