semvec/pypi-packages huggingface dataset:
gradools 0.1a2
gradools
Requires Python: >=3.6

# Grading tools

Some tools I use when grading [Canvas](https://www.instructure.com/canvas)
assignments.

There are command line tools, and some utilities for working with Canvas outputs.

The main use is when doing by-hand grading of assignments with multiple components, and you want to keep track of the scores per component, with notes from grading.

To do this, I make a Markdown marking log file, with specifications at the top,
then one second-level heading per student, like this:

```
# 2018 Marking log for assessment Foo

Ordinary maxima:

* quality: 20
* does_task: 15
* skill_range: 10
* elegance: 10
* functions_variables: 10
* display: 10
* usable: 15
* comments_safety: 10

Total: 100

## mbr110

* quality: 14.0
* does_task: 11.0
* skill_range: 7.0
* elegance: 6.0
* functions_variables: 7.0
* display: 8.0
* usable: 10.0
* comments_safety: 8.0

Total: 71

Martin Brett

You did a good job generally.  Etc.  More comments on specifics.

## vrr101

* quality: 5.0
* does_task: 6.0
* skill_range: 3.0
* elegance: 2.0
* functions_variables: 3.0
* display: 4.0
* usable: 5.0
* comments_safety: 3.0

Total: 55.0

Valia Rodriguez Rodriguez

You did not do a very good job, generally.  Etc.
```

## Command line tools

Commands need a file `gdconfig.toml` in the current directory.

Example:

```
log = "markingb_log.md"
year = "2018"
assignment = "Data Analysis Due (000000)"

[fudges]
2018 = 10
```

* gdo-check : analyzes a marking log in Markdown, with headings per student,
  and sub-totals for component.  Checks sub-totals match specification at top
  of file, checks and prints totals per student.
* gdo-year : prints "year" field value from config file (above).
* gdo-mkstable : makes template CSV file to upload to Canvas, using exported
  CSV file from Canvas as input.
* gdo-stinit : makes section in marking log for student with specified login.
  If field `nb_template` exists in config file, make matching notebook for
  student.
* gdo-mkfb : splits marking log into one file per student, builds PDFs for each
  student.
* gdo-report : write marks CSV from report.

## Utilities

* `canvastools` - various utilities for interpreting Canvas output filenames,
  reading Canvas output CSV files.

## Installation, development

Install from pip, usually:

```
pip install gradools
```

To install locally from the repository, you will need [flit](https://pypi.org/project/flit).


```
flit install --user
```

For development I use:

```
flit install --user -s
```

Test with:

```
pip install -r test-requirements.txt
pytest gradools
```
hep-cli 0.1.2
A basic CLI app
Requires Python: >=3.10,<3.13

# python-cli-template
A template repository for creating CLI apps 


## Dependencies

- poetry https://python-poetry.org/
- typer https://typer.tiangolo.com/


## Commands

```bash
poetry new <package-name>

poetry add <dep-package-name>
```
fx-py-sdk 0.7.3
Python library for FunctionX
Requires Python: >=3.7
Keywords: FunctionX,blockchain

# FunctionX Python SDK

[![PyPI version](https://badge.fury.io/py/fx-py-sdk.svg)](https://badge.fury.io/py/fx-py-sdk)

## Install

```shell
pip install fx-py-sdk
```

## Use

```python
from fxsdk.client.grpc import Client
from fxsdk.wallet.builder import TxBuilder
from fxsdk.x.cosmos.base.v1beta1.coin_pb2 import Coin

if __name__ == '__main__':
    grpc_cli = Client(url='127.0.0.1:9090')
    mnemonic = 'test test test test test test test test test test test junk'
    prefix = 'fx'
    
    tx_builder = TxBuilder.from_mnemonic(mnemonic=mnemonic, prefix=prefix)
    to = tx_builder.from_address().to_string()
    amount = [Coin(amount='100', denom='FX')]
    tx_response = grpc_cli.bank_send(tx_builder, to, amount)
    print(tx_response)
```

## Development

### 1. Clone the code to local

```shell
git clone https://github.com/functionx/fx-py-sdk.git

cd fx-py-sdk
```

### 2. Build the Python virtual environment for the current project

* Create the virtual directory venv

```
python -m venv venv
```

* Activating the Virtual Environment

```
source ./venv/bin/activate
```
> Windows: venv\Scripts\activate

### 3. Installation Project Dependence

```
pip install -r requirements.txt
```

### 4. Compile Proto files as Python files

> If does not have execution permission, run 'chmod +x ./gen-proto.sh`

```shell
# Pull external code
git submodule update --init --recursive --remote

./gen-proto.sh
```

### 5. Build Project

```shell
python -m build
```

## License

[Apache License 2.0](LICENSE)