Saravanan666/pypi-org huggingface dataset:
Package: 102053005-Aditya-Topsis
Topsis Package by Aditya KalhanRoll Number : 102053005
Subgroup : 3COE18
It takes a csv file, weights (seperated by comma) , impacts (+ or -) and outputs a result file.What is TopsisTOPSIS is based on the fundamental premise that the best solution has the shortest distance from the positive-ideal solution, and the longest distance from the negative-ideal one.Selecting an appropriate Multiple Attribute Decision Making (MADM) method for a given MADM problem is always a challenging task.Within the MADM domain, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is highly regarded, applied and adopted MADM method due to its simplicity and underlying concept that the best solution is the one closest to the positive ideal solution and furthest from the negative ideal solution.InstallationUse pip installerpip install 102053005-Aditya-TopsisHow to use itOpen terminal and type102053005 sample.csv "1,1,1,1" "+,+,-,+" result.csvExampleModelStorage SpaceCameraPriceLooksM116122505M21682003M332163004M43282754M516162252weights = [1,1,1,1]impact = ["+","+","-","+"]OutputModelStorage SpaceCameraPriceLooksTopsis ScoreRankM1161225050.5342693M216820030.3083145M3321630040.6916861M432827540.5348072M5161622520.4012224Output will be saved in a CSV file whose name will be provided in the command line.
It will have all the columns along with the Topsis Score and Ranks.
Package: 102116078-topsis-py
Topsis-PyImplementation of Topsis in Python by rno. 102116078Installationpipinstalltopsis-pyUsagetopsis<InputDataFile><Weights><Impacts><ResultFileName>Where<InputDataFile>: Path to the input CSV file.

<Weights>: Comma-separated weights for each criterion.

<Impacts>: Comma-separated impacts ('+' for maximization, '-' for minimization).

<ResultFileName>: Name of the file to save the results.Examplepythontopsisinput.csv'1,1,2,1''+,+,-,+'results.csv
Package: 102183051-topsis
TOPSISSubmitted By:Sarthak Tiwari | 102183051What is TOPSIS?Technique forOrderPreference bySimilarity toIdealSolution
(TOPSIS) originated in the 1980s as a multi-criteria decision making method.How to install this package:>>pipinstall-e.[dev]After installation, in Command Prompt/Terminal in pwd/current dir:>> topsis <InputDataFile> <Weights> <Impacts> <ResultFileName>Weights (weights) may not be normalised but will be normalised in the code.Note:To avoid errors -
Input file must contain three or more columns.
2nd to last columns must contain numeric values only.
Number of weights, number of impacts and number of columns (from 2 nd to last columns) must
be same.
Impacts must be either +ve or -ve.
Impacts and weights must be separated by â€˜,â€™ (comma).InputDataFile (data.csv) - an exampleThe decision matrix should be constructed with each row representing a Model alternative and each column representing a criterion like Correlation, R2, Root Mean Squared Error, Accuracy, etc.ModelCorrRseqRMSEAccuracyM10.790.621.2560.89M20.660.442.8963.07M30.560.311.5762.87M40.820.672.6870.19M50.750.561.380.39Output file (result.csv) -Based on the above input file and setting weights as "1,2,1,1" and impacts as "+,-,-,+".ModelCorrRseqRMSEAccuracyTopsis ScoreRankM10.790.621.2560.890.4237443913596114M20.660.442.8963.070.0.4674263682982973M30.560.311.5762.870.7602309570349031M40.820.672.6870.190.2077725338815665M50.750.561.380.390.5048644578037182The output file contains columns of input file along with two additional columns having Topsis Score and Rank.
Package: 10daysweb
# 10daysWeb**A just-for-learning web framework that can be developed in 10 days.**![PyPI](https://img.shields.io/pypi/pyversions/10daysweb.svg) ![PyPI](https://img.shields.io/pypi/status/10daysweb.svg) ![PyPI](https://img.shields.io/pypi/v/10daysweb.svg)# 啰嗦出于某些原因，我需要一个自己开发的轮子，大约只有十天时间。于是我打算开发一个python web框架，这是我一直想做却又未完成的事。我打算每天迭代，一遍写一遍查阅资料，记录新的想法和发现。这样如果有谁与我处境相似，这个项目也许能够有所帮助。最好能用成品再搭个博客什么的。即使没有成功，也不会一无所获。我们开始吧。## Day 1**万事开头难，相信我不是唯一一个在项目开始时感到无从下手的人。**首先我下载了热门框架Flask的0.1版本的源码，三百余行的代码已经包含了一个web框架所必要的全部功能，还附带了一个使用示例。[如何下载最早的commit代码](#如何下载最早的commit代码)对于我要实现的第一个最简单版本来说，flask仍然过于复杂了，我只提炼出`route`这个关键部件在第一版中实现。`Route`用来管理一个web应用具体响应哪些路径和方法。通过装饰器，框架在启动时注册所有的用户函数，并在符合条件时自动调用。@testApp.route('/', methods=['GET'])def hello():return 'hello world'而`Rule`则具体表示某个需要被响应的路径，它主要由`url`, `methods`和`endpoint`组成。`methods`包含一系列HTTP Method，表示要处理的请求类型。而`endpoint`则是实际产生返回内容的`Callable`对象，可以是函数或者类。关于http包含哪些method，以及后续我们需要参考的报文格式和状态码，参见[RFC 2616](#https://tools.ietf.org/html/rfc2616)。现在我们还缺少一段代码，用于监听和收发http报文，python3.4以后加入的asyncio提供了这个功能，而[官方文档](#http://asyncio.readthedocs.io)恰好给了我们一个极简的示例。`asyncio.start_server`需要三个基本参数，收到请求时的自动调用的`client_connected_cb`，以及需要监听的地址和端口。`client_connected_cb`则需要支持两个参数，`reader`和`writer`，份别用于读取请求报文和回写响应报文。我在`client_connected_cb`中添加了简易的获取请求的路径的代码，用于和注册好的应用函数匹配。同样我也已经定义了包含所有Http method的宏，不过还没有与请求进行匹配。这样我们就得到了一个可以运行的''Web框架''，目前只能算是prototype，不过已经足够让我们印出那句世纪名言了。Hello World!## Day 2**我们有了一个原型，但很多方面亟待完善**我使用了一个开源第三方库来解析http报文，并实现了`Request`和`Response`来抽象请求。我从rfc文档中摘取了http的状态码，和methods一起放在`utils.py`中。尝试定义了一个异常，初步的设向是它可以让框架的使用者随时使用异常直接返回http的错误状态，`content`则是为了支持自定义的错误页面，但这部分仍不确定，也许我会使用`@error_handler`的形式来提供自定义异常时的行为。添加了log，但在我的终端中还没有输出，待解决。我使用了标准库`asyncio`，因为我希望这个框架是支持异步的，调整后的`handle`方法提现了处理一个请求的基本思路，但它看起来仍然很糟糕，对于异步我还未完全理清思路。## Day 3在代码方面，今天的改动并不大。梳理了`handle`方法的逻辑, 我强制规定用户函数必须是协程，但日后也必须提供数据库，文件读写相关的异步封装API，否则框架仍然不是`真*异步`。调整了流读取报文的处理策略，交由第三方解析库来判断报文是否结束。这方面并不用太过纠结，因为真正部署时讲会有nginx/apache之流替我们打理。之后的主要工作：- 完成`Debug模式`，实现自动重加载用户函数- 添加静态文件路由和模式匹配路由支持- 引入模板引擎及其异步调用封装## Day 4添加了动态url匹配支援，现在可以在以如下形式匹配路径:@app.route('/<name>', methods=['GET'])async def show_name(request, name):return Response(content=f'hello {name}')思考以后感觉静态文件路由完全可以由用户自行添加动态匹配来支持，即使不行还有web服务器来做，于是决定先放下这部分。添加了`errorhandler`装饰器，现在可以通过它自定义异常时的行为和返回报文调整了异常捕获机制，现在在找不到对应的用户方法时，能够正确的抛出404异常，而在用户方法中非预期中异常，则统一作为500状态处理## Day 5 & 6加入了`run_before`装饰器，用于在运行启动服务器前的初始化代码，默认传入事件循环loop参数把这个~~丢人~~框架上传到了pip，现在可以通过`pip install 10daysweb`安装使用尝试写一个todolist应用作为演示，康了半天前端觉得有些仓促，决定接入~~Telegram Bot~~微信小程序加入了unitest，初步编写了一个url匹配的测试样例## Day 7新增信号装饰器，初步想法是用于服务器启动前和结束后初始化和关闭数据库连接池@app.signal(type='run_before_start')def foo(loop):'''init database connection pool'''增加了对应的未知信号类型异常，微信小程序api编写中。## 如何下载最早的commit代码作为一个知名的开源项目，Flask在github已经积累了数千此提交。最可恨的是，github在Commit列表页面竟然没有提供一个按页跳转的功能。下面一个不是很优雅，但确实更快的方法首先在本地`git clone`下目标项目使用`--reverse`参数倒置结果，拿到提交历史上最早的commit idgit log --reverse在github上随意打开一个commit，替换掉url中的id即可。哦，你还需要点一下`Browse files`
Package: 111752
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Package: 115wangpan
115 Wangpan (115网盘 or 115云) is an unofficial Python API and SDK for 115.com. Supported Python verisons are 2.6, 2.7, 3.3, 3.4.Documentation:http://115wangpan.readthedocs.orgGitHub:https://github.com/shichao-an/115wangpanPyPI:https://pypi.python.org/pypi/115wangpan/FeaturesAuthenticationPersistent sessionTasks management: BitTorrent and linksFiles management: uploading, downloading, searching, and editingInstallationlibcurlis required. Install dependencies before installing the python package:Ubuntu:$sudoapt-getinstallbuild-essentiallibcurl4-openssl-devpython-devFedora:$sudoyumgroupinstall"Development Tools"$sudoyuminstalllibcurllibcurl-develpython-develThen, you can install with pip:$pipinstall115wangpanOr, if you want to install the latest from GitHub:$pipinstallgit+https://github.com/shichao-an/115wangpanUsage>>>importu115>>>api=u115.API()>>>api.login('username@example.com','password')True>>>tasks=api.get_tasks()>>>task=tasks[0]>>>printtask.name咲-Saki-阿知賀編episodeofside-A>>>printtask.status_humanTRANSFERRED>>>printtask.size_human1.6GiB>>>files=task.list()>>>files[<File:第8局修行.mkv>]>>>f=files[0]>>>f.urlu'http://cdnuni.115.com/some-very-long-url.mkv'>>>f.directory<Directory:咲-Saki-阿知賀編episodeofside-A>>>>f.directory.parent<Directory:离线下载>CLI commands115 down: for downloading files115 up: for creating tasks from torrents and links
Package: 11x-wagtail-blog
11x Wagtail Blog11x Wagtail Blog11x-wagtail-blogis a wagtail app implementing basic blog features for a wagtail site. This project started as an
implementation of the blogging features of11x.engineering, but since it is intended to be used as the first series
of articles, it has been open sourced and published here. It is intended to demonstrate how to develop a fully featured
package published to PyPI.Quick StartTo install:pip install 11x-wagtail-blogAddx11x_wagtail_blogto yourINSTALLED_APPS:INSTALLED_APPS = [
    ...,
    'x11x_wagtail_blog',
    ...,
]Since this package only gives you the common features of every blogging application, you will need to define your own page
models and derive them fromExtensibleArticlePage:>>> from x11x_wagtail_blog.models import ExtensibleArticlePage
>>> from wagtail.admin.panels import FieldPanel
>>> from wagtail.blocks import TextBlock
>>> from wagtail.fields import StreamField>>> class MyArticlePage(ExtensibleArticlePage):
...     body = StreamField([
...         ("text", TextBlock()),
...     ], use_json_field=True)
...
...     content_panels = ExtensibleArticlePage.with_body_panels([
...         FieldPanel("body"),
...     ])This can be done in any valid Wagtail app.Next, generate your migrations as usual:python manage.py makemigrations
python manage.py migrateYou will have to define a template. The default template used isx11x_wagtail_blog/article_page.html, but you should
override theget_template()method to return your own template.<!DOCTYPE html><html><head>...</head><body><h1>{{ self.title }}</h1>{% include_block self.body %}<h2>About the authors</h2>{% for author in self.authors %}
    {% include "myblog/about_the_author_section.html" with author=author.value %}
    {% endfor %}<h2>Related Articles</h2><ul>{% for article in self.related_articles %}<li><ahref="{% pageurl article %}">{{ article.title }}</a></li>{% endfor %}</ul></body></html>
Package: 12306-booking
12306-booking12306订票工具12306booking vs 12306 vs 第三方订票平台为什么要写一个订票工具？12306订票体验太差。验证码识别太逆天，人眼无法识别。刷新、刷新、刷新，刷到手疼。票就在那里，你就是定不上第三方订票平台太流氓。收集用户数据，还收不可接受的手续费（美其名曰技术服务费，其实就是 CPU和 RAM），最恐怖的是还要将用户数据拿到市场交易解决了什么问题，有什么优点？两次扫码就完成了登录、查询余票、下单到支付的所有流程本地运行，不收集任何用户数据，不用输入用户密码，不用担心任何数据泄露、交易行为完全开源，没有任何黑箱操作刷新、订票流程快，先人一步抢到票支持多车次、多席别、多乘客抢票使用说明安装pipinstall12306-booking-U--user;如果使用MacOS，使用虚拟环境安装virtualenv venv; source venv/bin/activate; pip install 12306-booking -U订票12306-booking--train-date2020-01-01--train-namesK571--seat-types硬卧--from-station北京--to-station麻城--pay-channel微信--passengers任正非,王石多车次、多席别、多乘客之间用英文的','分割订票流程订票状态机赞助如果有帮助到你订到票，请扫描二维码赞赏我们，你的鼓励是我们持续改进优化的动力。
Package: 125softNLP
pysoftnlp--- 河南863软件孵化器有限公司大数据事业部商机雷达项目自然语言处理工具包--- pysoftNLP是一个提供常用NLP功能的工具包， 宗旨是直接提供方便快捷的解析、词典类的面向中文的工具接口，并提供一步到位的查阅入口。功能主要包括：中文分词（tokenizer）文本清洗（clean）文本分类（classification）命名实体识别（公司，ner)文本数据增强（enhancement）句义相似度计算（similarities）关键字提取（extraction）持续更新中...安装 Installationwin环境:pipinstallpysoftNLP==0.0.4-ihttps://pypi.python.org/simple资源包下载和使用#下载所使用的资源包frompysoftNLP.utilsimportdowndown.download_resource()使用 Features1.分类模型使用frompysoftNLP.classificationimportbert_dnn#分类模型--训练train_data='x_tr_863.csv'test_data='x_te_863.csv'train_df,test_df=bert_dnn.read_data(train_data,test_data)#encode:词向量模型（目前只支持bert） ，sentence_lenth: 50(句子的长度)， num_classes（9分类）args={'encode':'bert','sentence_length':50,'num_classes':9,'batch_size':128,'epochs':100}bert_dnn.train(train_df,test_df,args)frompysoftNLP.classificationimportpre#分类模型--预测model_name='863_classify_hy.h5'label_map={0:'it',1:'电力热力',2:'化工',3:'环保',4:'建筑',5:'交通 ',6:'教育文化',7:'矿业',8:'绿化',9:'能源',10:'农林',11:'市政',12:'水利',13:'通信',14:'医疗',15:'制造业'}texts=['广西打好“电力牌”组合拳助力工业企业从复产到满产中国新闻网','分别是吕晓雪、唐禄俊、梁秋语、王翠翠、杨兴亮、吕桃桃、张耀夫、郭建波、中国医护服务网','富拉尔基区市场监管局开展《优化营商环境条例》宣传活动齐齐哈尔市人民政府','2020上海（国际）胶粘带与薄膜技术展览会制造交易网']pre.predict(model_name,texts,label_map)2、数据增强frompysoftNLP.enhancementimportaugmentinput='D:\pysoftNLP_resources\enhancement\Test\Trian_hy.csv'output='D:\pysoftNLP_resources\enhancement\Test\Trian_out.csv'num_aug=20#一条数据可以扩展到多少条alpha=0.05#一条数据量变化的百分比augment.gen_eda(input,output,alpha,num_aug)3、命名实体识别（公司）frompysoftNLP.nerimporttrainargs={'sentence_length':100,'batch_size':512,'epochs':20}# 参数output_path='ner_company'#模型的输出train.train(args,output_path)#单句预测frompysoftNLP.nerimportpretext='这是一个单句'#model_name='ner'pre.single_sentence(text,model_name)#多句预测out_path='D:\pysoftNLP_resources\entity_recognition'list=['中广核新能源湖南分公司','该公司','中广核新能源公司']pre.multi_sentence(list,output_path,model_name)4、相似度计算#文本相似度计算frompysoftNLP.similaritiesimportsimilartest_vec='自然语言处理与人工智能'sentences=['逍遥派掌门人无崖子为寻找一个色艺双全、聪明伶俐的徒弟，设下“珍珑”棋局，为少林寺虚字辈弟子虚竹误撞解开。','慕容复为应召拒绝王语嫣的爱情；众人救起伤心自杀的王语嫣，后段誉终于获得她的芳心。','鸠摩智贪练少林武功，走火入魔，幸被段誉吸去全身功力，保住性命，大彻大悟，成为一代高僧。','张无忌历尽艰辛，备受误解，化解恩仇，最终也查明了丐帮史火龙之死乃是成昆、陈友谅师徒所为','武氏与柯镇恶带着垂死的陆氏夫妇和几个小孩相聚，不料李莫愁尾随追来，打伤武三通','人工智能亦称智械、机器智能，指由人制造出来的机器所表现出来的智能。','人工智能的研究是高度技术性和专业的，各分支领域都是深入且各不相通的，因而涉及范围极广。','自然语言认知和理解是让计算机把输入的语言变成有意思的符号和关系，然后根据目的再处理。']args={'encode':'bert','sentence_length':50,'num_classes':9,'batch_size':128,'epochs':100}similar.similar(sentences,test_vec,args,3)5、关键词抽取frompysoftNLP.extractionimportkeywordtext='6月19日,《2012年度“中国爱心城市”公益活动新闻发布会》在京举行。'+\'中华社会救助基金会理事长许嘉璐到会讲话。基金会高级顾问朱发忠,全国老龄'+\'办副主任朱勇,民政部社会救助司助理巡视员周萍,中华社会救助基金会副理事长耿志远,'+\'重庆市民政局巡视员谭明政。'print(text)pos=Trueseg_list=keyword.seg_to_list(text,pos)filter_list=keyword.word_filter(seg_list,pos)print('TF-IDF模型结果：')keyword.tfidf_extract(filter_list)print('TextRank模型结果：')keyword.textrank_extract(text)print('LSI模型结果：')keyword.topic_extract(filter_list,'LSI',pos)print('LDA模型结果：')keyword.topic_extract(filter_list,'LDA',pos)
Package: 12factor-configclasses
configclassesLike dataclasses but for config.Specify your config with a class and load it with your env vars or env files.# .env
HOST=0.0.0.0
PORT=8000
...importhttpxfromconfigclassesimportconfigclass@configclassclassClientConfig:host:strport:intclassUserAPIClient(httpx.AsyncClient):def__init__(self,config:ClientConfig,*args,**kwargs):self.config=config...config=ClientConfig.from_path(".env")asyncwithUserAPIClient(config)asclient:...FeaturesFill your configclasses with existent env vars.Define default values in case these variables have no value at all.Load your config files in env vars following12factor appsrecommendations.Support for.env,yaml,toml,iniandjson.Convert your env vars with specified type in configclass:int,float,strorbool.Use nested configclasses to more complex configurations.Specify a prefix with@configclass(prefix="<PREFIX>")to append this prefix to your configclass'  attribute names.Config groups (TODO):https://cli.dev/docs/tutorial/config_groups/RequirementsPython 3.8+InstallationDepending on your chosen config file format you can install:.env  ->pip install 12factor-configclasses[dotenv].yaml ->pip install 12factor-configclasses[yaml].toml ->pip install 12factor-configclasses[toml].ini  ->pip install 12factor-configclasses.json ->pip install 12factor-configclassesOr install all supported formats with:pip install 12factor-configclasses[full]UsageThere are three ways to use it.Loading an .env file:# .env
HOST=0.0.0.0
PORT=8000
DB_URL=sqlite://:memory:
GENERATE_SCHEMAS=True
DEBUG=True
HTTPS_ONLY=False
GZIP=True
SENTRY=False#config.pyfromconfigclassesimportconfigclass@configclassclassDB:user:strpassword:strurl:str@configclassclassAppConfig:host:strport:intdb:DBgenerate_schemas:booldebug:boolhttps_only:boolgzip:boolsentry:bool# app.pyfromapi.configimportAppConfigapp_config=AppConfig.from_path(".env")app=Starlette(debug=app_config.debug)ifapp_config.https_only:app.add_middleware(HTTPSRedirectMiddleware)ifapp_config.gzip:app.add_middleware(GZipMiddleware)ifapp_config.sentry:app.add_middleware(SentryAsgiMiddleware)...register_tortoise(app,db_url=app_config.db.url,modules={"models":["api.models"]},generate_schemas=app_config.generate_schemas,)if__name__=="__main__":uvicorn.run(app,host=app_config.host,port=app_config.port)Loading predefined environmental variables:The same than before, but instead of:app_config = AppConfig.from_path(".env")You will do:app_config = AppConfig.from_environ()Loading a file from a string:test_env="""HOST=0.0.0.0PORT=8000DB_URL=sqlite://:memory:GENERATE_SCHEMAS=TrueDEBUG=TrueHTTPS_ONLY=FalseGZIP=TrueSENTRY=False"""app_config=AppConfig.from_string(test_env,".env")
Package: 153957-theme
Theme 153957View demo album herePhoto gallery templateWeb photo gallery templates adapted to my personal preferences.UsageThis section describes how to install and use this theme.InstallationInstall the153597-themepackage:$ pip install 153957-themeConfigureInsigal.conf.pyconfiguration for an album thethemesetting should be
a path to a theme directory. However, since this theme is provided as a Python
package its location might be harder to get. Two options are available for
configuration:The theme can be configured as a plugin or you can get the path by importing
the package. By setting is as plugin the theme is automatically set.Setthemeto an empty string and add the theme and menu plugins:theme = ''
plugins = ['theme_153957.theme', 'theme_153957.full_menu', …]The alternative:from theme_153957 import theme
theme = theme.get_path()
plugins = ['theme_153957.full_menu', …]Wrapping albumUse the settingshead,body_prefix, andbody_suffixto add additional
code to the templates. The value ofheadis appended to theheadelement,
thebodysettings are placed just after the body opening tag (prefix) and
just before the closing body tag (suffix). This allows embedding the album
in your own website.
Package: 15five-django-ajax-selects
Edit ForeignKey, ManyToManyField and CharField in Django Admin using jQuery UI AutoComplete.Customize search queryQuery other resources besides Django ORMFormat results with HTMLCustomize stylingCustomize security policyAdd additional custom UI alongside widgetIntegrate with other UI elements elsewhere on the page using the javascript APIWorks in Admin as well as in normal viewsDjango >=1.6, <=1.10Python >=2.7, <=3.5
Package: 15five-snowplow-tracker
OverviewAdd analytics to your Python apps and Python games with theSnowplowevent tracker forPython.With this tracker you can collect event data from your Python-based applications, games or Python web servers/frameworks.Find out moreTechnical DocsSetup GuideRoadmapContributingTechnical DocsSetup GuideRoadmapContributingContributing quickstartAssuming Git,VagrantandVirtualBoxare installed:host$ git clone git@github.com:snowplow/snowplow-python-tracker.git
 host$ vagrant up && vagrant ssh
guest$ cd /vagrant
guest$ ./run-tests.sh deploy
guest$ ./run-tests.sh testPublishinghost$ vagrant pushCopyright and licenseThe Snowplow Python Tracker is copyright 2013-2014 Snowplow Analytics Ltd.Licensed under theApache License, Version 2.0(the “License”);
you may not use this software except in compliance with the License.Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an “AS IS” BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Package: 170051277-trab-final-gces
Resumo do funcionamentoA biblioteca desenvolvida auxilia desenvolvedores a explorar os dados com funções essenciais para a identificação de outliers e anomalias e uma interface que auxilia a visualizar as informações de acordo com o arquivo de configuração.A biblioteca recebe um arquivo yaml com as configurações de cada etapa do pipeline de dados, e do endereço do banco de dados.
Após a execução do banco de dados, o banco de dados de dados é atualizado com os resultados da análise e os resultados podem ser visualizados por meio de dashboards no metabase.
Package: 17MonIP
IP search based on 17mon.cn, the best IP database for china.Source:http://tool.17mon.cnInstallSupports python2.6 to python3.4 and pypy.$pipinstall17monipUsage>>>importIP>>>IP.find("www.baidu.com")'中国\t浙江\t杭州'>>>IP.find("127.0.0.1")'本机地址\t本机地址'CMD Util$iplocele.me中国北京北京$iplocaliyun.com中国浙江杭州Changeloghttps://github.com/lxyu/17monip/blob/master/CHANGES.rst
Package: 199Fix
===============199Fix===============199Fix provides a logging handler to push exceptions and other errors to https://199fix.com/.Installation============Installation with ``pip``:::$ pip install 199fixGet an API Key here https://199fix.com/signup/Add ``'199fix.handlers.I99FixHandler'`` as a logging handler:::LOGGING = {'version': 1,'disable_existing_loggers': False,'filters': {'require_debug_false': {'()': 'django.utils.log.RequireDebugFalse'}},'handlers': {'199fix': {'level': 'ERROR','class': 'i99fix.handlers.I99FixHandler','filters': ['require_debug_false'],'api_key': '[your-api-key]','env_name': 'production',},},'loggers': {'django': {'handlers': ['199fix'],'level': 'ERROR','propagate': True,},}}Settings========``level`` (built-in setting)Change the ``level`` to ``'ERROR'`` to disable logging of 404 error messages.``api_key`` (required)API key , Get one here https://199fix.com/.``env_name`` (required)Name of the environment (e.g. production, development)Contributing============* Fork the repository on GitHub and start hacking.* Run the tests.* Send a pull request with your changes.
Package: 1app
Hello, ONEUsagepip install 1appThen, simply use the command periodically:1app –params…This will save data to:settings.BASE_DIR/data/1app:default/ItemN-SpacingIf you want to seprate different sessions and sources, just use name param:1app –params… –name UsernameThis will save to:settings.BASE_DIR/data/1app:Name/TypeThe–namevalue can be arbitray filesystem-compatible filename sub-string, so, you can use it to separate data by accounts, languages, or other features.NOTE: Corresponding auth and session data will be stored insettings.BASE_DIR/sessionsfolder.Saving to specific DIRSaving to custom folder simply pass–pathparameter, like:1app –params –name Name –path /home/mindey/Desktop/mydata
Package: 1c-utilites
1C Utils=========**1C Utils** это набор скриптов для управления и обслуживания серверов 1С.Репозиторий:https://gitlab.com/onegreyonewhite/1c-utilitesДля вопросов и предложений используйте трекер задач:https://gitlab.com/onegreyonewhite/1c-utilites/issuesВозможности--------На данный момент поддерживается только архивация PostgreSQL и файловых БД 1С.Quickstart----------Поддерживается любая Linux-система с наличием в ней Python 2.7/3.4/3.5и необходимых утилит обслуживания:* pg_dump для архивации PostgreSQL баз* tar для упаковывания файловых базУстановка:.. sourcecode:: bashpip install 1c-utilites1c-utilites --help