semvec/pypi-packages huggingface dataset:
RoboNpmAudit 1.0.1
Robot Framework Library for NPM Audit Source Composition Analysis
License: MIT

## RoboNpmAudit

Robot Framework Library for NPM Audit Source Composition Analysis

**Supports Python 2.7.x for now**

### Install Instructions
* You need docker to run this program
* Pull the brakeman docker image: `docker pull abhaybhargav/npmaudit`
* Install the RoboNpmAudit Library with `pip install RoboNpmAudit`
* Create a `.robot` file that includes the keywords used by RoboNpmAudit Library


### Keywords

`run npmaudit against source`

`| run npmaudit against source  | source code path  | results path`

* source code path: where your ruby source code is located currently
* Your nodejs Source code needs to have a package.json file for `npm audit` to scan
* results path: where your results will be stored. An `.json` is generated as outputs
auto-red-test 0.2.1
Auto Create PyTest Frame and Fake Test Parameters For Red
License: MIT
Keywords: auto red test

## 项目描述
通过解析IDL自动生成PyTest单测框架,
通过Faker库辅助生成部分参数,
并且支持单测参数和单测逻辑的向后兼容

## 安装
```javascript
    pip install pytest
    pip install pyaml
    pip install Faker==1.0.4
    pip install bson
    pip install dictdiffer
```

## 示例代码
```javascript
from auto_red_test import generate_red_test
from frame import ENV
from handler.stockage_handler import StockageHandler  # 需要单测的handler
import stockage_service.request.ttypes as test_request  # idl的request文件
import stockage_service.StockageService as test_service  # idl的service文件
root_path = ENV['root']  # 项目的根目录
# 第二个参数可以是handler列表，但必须属于同一个service
generate_red_test(root_path, StockageHandler, test_service, test_request)
```
* 自动生成的单测框架如下：
* ![image](https://raw.githubusercontent.com/qjjayy/red_test/master/image/test_red.jpg)

## 补充内容
* 第一次运行会生成request_config.yaml，可以自定义单测方法的参数，用于解决一个单测方法用到多个request的特殊情况，
格式如下：
```javascript
# 配置单测参数
methodA:
  request_A_name: request_A_obj_name
  request_B_name: request_A_obj_name
methodB:
  request_B_name: request_B_obj_name
  request_C_name: request_C_obj_name
```
methodA为单测方法名， request_A_name为请求参数名，request_A_obj_name为请求参数对应的IDL Request名
Popet 0.0.1
The Useless Easy Tool to Handle Pope's Data
License: MIT

The Useless Easy Tool to Handle Pope's Data
===========================================
Powered by [Yamato Nagata](https://twitter.com/514YJ)

Data by [Tako](https://twitter.com/TLE_Maker)

[GitHub](https://github.com/delta114514/Popet)

[ReadTheDocs](https://popet.readthedocs.io/en/latest/)


```python
from datetime import date

from popet import Popet

pope = Popet.who(date(1970, 5, 1))

print(pope)
    # <Pope: Servant of God Paul VI, 21/06/1963-06/08/1978>
print(vars(pope))
    # {'start': datetime.date(1963, 6, 21), 'end': datetime.date(1978, 8, 6), 'english_name': 'Servant of God Paul VI', 'regnal_name': 'PAULUS Sextus', 'personal_name': 'Giovanni Battista Enrico Antonio Maria Montini'}

```
subtr 0.0.5
Subtitle Translator
License: MIT

# Subtitle Translator

subtr is subtitle translator that translate a subtitle file `eg: .srt` using Google Cloud Translation API v3.

*For now only .srt that supported*

## Getting Started

subtr using Cloud Translation API v3. It's Free, but requires you to create a service account and activate the billing to use it.

Try [GCP Free Tier](https://cloud.google.com/free/)

### Install subtr using pip

```bash
pip install subtr
```

### Getting Google Cloud Service Account Key

#### Using Google Cloud SDK

Set Environment Variables

```bash
export SA_NAME=YOUR_SERVICEACCOUNT_NAME
export SA_DISPLAY_NAME=YOUR_SERVICEACCOUNT_DISPLAY_NAME
export PROJECT_ID=YOUR_GCLOUD_PROJECT_ID
```

Enable Google Cloud Translation API

```bash
gcloud services enable translate.googleapis.com
```

Create Service Account

```bash
gcloud iam service-accounts create ${SA_NAME}
    --display-name ${SA_DISPLAY_NAME}
```

Granting Roles to Service Account

```bash
gcloud projects add-iam-policy-binding ${PROJECT_ID} \
  --member serviceAccount:${SA_NAME}@${PROJECT_ID}.iam.gserviceaccount.com \
  --role roles/cloudtranslate.admin
gcloud projects add-iam-policy-binding ${PROJECT_ID} \
  --member serviceAccount:${SA_NAME}@${PROJECT_ID}.iam.gserviceaccount.com \
  --role roles/cloudtranslate.editor
gcloud projects add-iam-policy-binding ${PROJECT_ID} \
  --member serviceAccount:${SA_NAME}@${PROJECT_ID}.iam.gserviceaccount.com \
  --role roles/cloudtranslate.user
gcloud projects add-iam-policy-binding ${PROJECT_ID} \
  --member serviceAccount:${SA_NAME}@${PROJECT_ID}.iam.gserviceaccount.com \
  --role roles/cloudtranslate.viewer
```

Create Service Account Key

```bash
gcloud iam service-accounts keys create ${HOME}/.subtr-sa-key.json
  --iam-account ${SA_NAME}@${PROJECT_ID}.iam.gserviceaccount.com
```

#### Using Google Cloud Console

See [Cloud Translation Quickstart](https://cloud.google.com/translate/docs/quickstart-client-libraries-v3)

## How To Use

Set the environment variable. `PROJECT_ID` is your google cloud project id that associated with the service account that already created above. `GOOGLE_APPLICATION_CREDENTIALS` is file path of the JSON file that contains your service account key

```bash
export PROJECT_ID=YOUR_GCLOUD_PROJECT_ID
export GOOGLE_APPLICATION_CREDENTIALS=${HOME}/.subtr-sa-key.json
```

Usage

```bash
subtr -h
usage: subtr [-h] -s SOURCE_LANG -t TARGET_LANG -f FILE_PATH

Subtitle translator.

optional arguments:
  -h, --help            show this help message and exit
  -s SOURCE_LANG, --source_lang SOURCE_LANG
                        Source language translate from.
  -t TARGET_LANG, --target_lang TARGET_LANG
                        Target language translate to.
  -f FILE_PATH, --file FILE_PATH
                        PATH to subtitle file.
```

Example

```bash
subtr -s en-US -t id-ID -f sample/ns-01.srt
```
Toca 0.1.5
Automatic Testing
License: MIT

# Toca
Automatic Testing


## 命令行
```
# toca help
usage: toca ACTION [-c toca.toml]

ACTION should be:
    ls           列出所有 API
    run          运行所有 API
    help, -h, --help    打印帮助

optional arguments:
    -c toca.toml  指定配置文件, 默认为当前路径下的 toca.toml
```

## 配置文件示例
```
[env]
class_id  = "123456"
school_id = "123456"

# 静态参数可以出现在所有地方
# 动态参数只允许出现在 uri/headers/params 中

[liteApp]
scheme = "http"
port = 4000
host = "localhost"
    [liteApp.headers]
    content-type = "application/json"
    [liteApp.Duration]
        [liteApp.Duration.CreateDuration]
        method = "post"
        uri    = "/liteapp/duration"
            [liteApp.Duration.CreateDuration.headers]
            content-type = "application/json"
            [liteApp.Duration.CreateDuration.params]
            begin_time = "2019-01-01"
            end_time   = "2019-06-01"
            class_id   = "{{class_id}}"
            school_id  = "{{school_id}}"
        [liteApp.Duration.GetDuration]
        method = "get"
        uri    = "/liteapp/duration/{$ liteApp.Duration.CreateDuration.response.data.uid $}"
        [liteApp.Duration.ListDuration]
        method = "get"
        uri    = "/liteapp/duration/list"
    
    [liteApp.Duty]
        [liteApp.Duty.CreateDuty]
        method = "post"
        uri = "/liteapp/duty/"
            [liteApp.Duty.CreateDuty.headers]
            content-type = "application/json"
            [liteApp.Duty.CreateDuty.params]
            duration_id = "{$ liteApp.Duration.CreateDuration.response.data.uid $}"
            duties      = "{$ _functions.loadJsonFromFile('duties.json') $}"
        [liteApp.Duty.GetDuty]
        method = "get"
        uri    = "/liteapp/duty/{$ liteApp.Duty.CreateDuty.response.data.uid $}"
    
    [liteApp.Section]
        [liteApp.Section.ListSection]
        method = "get"
        uri    = "/liteapp/school/{{school_id}}/sections/"
```

## Todo
1. 执行单个命令
2. 执行单个命令时，可以在命令行中指定参数
3. 执行单个 Group
4. env 中的参数支持动态生成