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|
%global _empty_manifest_terminate_build 0
Name: python-minet
Version: 0.67.1
Release: 1
Summary: A webmining CLI tool & library for python.
License: MIT
URL: http://github.com/medialab/minet
Source0: https://mirrors.nju.edu.cn/pypi/web/packages/a2/80/7b6c09dad64f580c64378f90286e06df1027d849f3377f86c8aef235741f/minet-0.67.1.tar.gz
BuildArch: noarch
Requires: python3-beautifulsoup4
Requires: python3-browser-cookie3
Requires: python3-casanova
Requires: python3-charset-normalizer
Requires: python3-colorama
Requires: python3-dateparser
Requires: python3-ebbe
Requires: python3-json5
Requires: python3-keyring
Requires: python3-lxml
Requires: python3-ndjson
Requires: python3-persist-queue
Requires: python3-pyyaml
Requires: python3-quenouille
Requires: python3-soupsieve
Requires: python3-tenacity
Requires: python3-termcolor
Requires: python3-tqdm
Requires: python3-trafilatura
Requires: python3-twitwi
Requires: python3-ural
Requires: python3-urllib3
%description
[](https://github.com/medialab/minet/actions) [](https://zenodo.org/badge/latestdoi/169059797) [](https://pepy.tech/project/minet)
**minet** is a webmining command line tool & library for python (>= 3.7) that can be used to collect and extract data from a large variety of web sources such as raw webpages, Facebook, CrowdTangle, YouTube, Twitter, Media Cloud etc.
It adopts a very simple approach to various webmining problems by letting you perform a variety of actions from the comfort of the command line. No database needed: raw CSV files should be sufficient to do most of the work.
In addition, **minet** also exposes its high-level programmatic interface as a python library so you can tweak its behavior at will.
**Shortcuts**: [Command line documentation](./docs/cli.md), [Python library documentation](./docs/lib.md).
## Summary
* [What it does](#what-it-does)
* [Documented use cases](#documented-use-cases)
* [Features (from a technical standpoint)](#features-from-a-technical-standpoint)
* [Installation](#installation)
* [Upgrading](#upgrading)
* [Uninstallation](#uninstallation)
* [Documentation](#documentation)
* [Contributing](#contributing)
* [How to cite](#how-to-cite)
## What it does
Minet can single-handedly:
* Extract URLs from a text file (or a table)
* Parse URLs (get useful information, with Facebook- and Youtube-specific stuff)
* Join two CSV files by matching the columns containing URLs
* From a list of URLs, resolve their redirections
* ...and check their HTTP status
* ...and download the HTML
* ...and extract hyperlinks
* ...and extract the text content and other metadata (title...)
* ...and scrape structured data (using a declarative language to define your heuristics)
* Crawl (using a declarative language to define a browsing behavior, and what to harvest)
* Mine or search:
* *[Buzzsumo](https://buzzsumo.com/)* (requires API acess)
* *[Crowdtangle](https://www.crowdtangle.com/)* (requires API access)
* *[Mediacloud](https://mediacloud.org/)* (requires free API access)
* *[Twitter](https://twitter.com)* (requires free API access)
* *[Youtube](https://www.youtube.com/)* (requires free API access)
* Scrape (without requiring special access, often just a user account):
* *[Facebook](https://www.facebook.com/)*
* *[Instagram](https://www.instagram.com/)*
* *[Telegram](https://telegram.org/)*
* *[TikTok](https://www.tiktok.com)*
* *[Twitter](https://twitter.com)*
* *[Google Drive](https://drive.google.com)* (spreadsheets etc.)
* Grab & dump cookies from your browser
* Dump *[Hyphe](https://hyphe.medialab.sciences-po.fr/)* data
## Documented use cases
* [Fetching a large amount of urls](./cookbook/fetch.md)
* [Joining 2 CSV files by urls](./cookbook/url_join.md)
* [Using minet from a Jupyter notebook](./cookbook/notebooks/Minet%20in%20a%20Jupyter%20notebook.ipynb) (*very useful to experiment with the tool or teach students*)
* [Downloading images associated with a given hashtag on Twitter](./cookbook/twitter_images.md)
* [Scraping DSL Tutorial](./cookbook/scraping_dsl.md)
## Features (from a technical standpoint)
* Multithreaded, memory-efficient fetching from the web.
* Multithreaded, scalable crawling using a comfy DSL.
* Multiprocessed raw text content extraction from HTML pages.
* Multiprocessed scraping from HTML pages using a comfy DSL.
* URL-related heuristics utilities such as extraction, normalization and matching.
* Data collection from various APIs such as [CrowdTangle](https://www.crowdtangle.com/).
## Installation
**minet** can be installed as a standalone CLI tool (currently only on mac >= 10.14, ubuntu & similar) by running the following command in your terminal:
```shell
curl -sSL https://raw.githubusercontent.com/medialab/minet/master/scripts/install.sh | bash
```
Don't trust us enough to pipe the result of a HTTP request into `bash`? We wouldn't either, so feel free to read the installation script [here](./scripts/install.sh) and run it on your end if you prefer.
On ubuntu & similar you might need to install `curl` and `unzip` before running the installation script if you don't already have it:
```shell
sudo apt-get install curl unzip
```
Else, **minet** can be installed directly as a python CLI tool and library using pip:
```shell
pip install minet
```
If you need more help to install and use **minet** from scratch, you can check those [installation documents](./docs/install.md).
Finally if you want to install the standalone binaries by yourself (even for windows) you can find them in each release [here](https://github.com/medialab/minet/releases).
## Upgrading
To upgrade the standalone version, simply run the install script once again:
```shell
curl -sSL https://raw.githubusercontent.com/medialab/minet/master/scripts/install.sh | bash
```
To upgrade the python version you can use pip thusly:
```shell
pip install -U minet
```
## Uninstallation
To uninstall the standalone version:
```shell
curl -sSL https://raw.githubusercontent.com/medialab/minet/master/scripts/uninstall.sh | bash
```
To uninstall the python version:
```shell
pip uninstall minet
```
## Documentation
* [minet as a command line tool](./docs/cli.md)
* [minet as a python library](./docs/lib.md)
## Contributing
To contribute to **minet** you can check out [this](./CONTRIBUTING.md) documentation.
## How to cite
**minet** is published on [Zenodo](https://zenodo.org/) as [](https://zenodo.org/badge/latestdoi/169059797)
You can cite it thusly:
> Guillaume Plique, Pauline Breteau, Jules Farjas, Héloïse Théro, Jean Descamps, Amélie Pellé, & Laura Miguel. (2019, October 14). Minet, a webmining CLI tool & library for python. Zenodo. http://doi.org/10.5281/zenodo.4564399
%package -n python3-minet
Summary: A webmining CLI tool & library for python.
Provides: python-minet
BuildRequires: python3-devel
BuildRequires: python3-setuptools
BuildRequires: python3-pip
%description -n python3-minet
[](https://github.com/medialab/minet/actions) [](https://zenodo.org/badge/latestdoi/169059797) [](https://pepy.tech/project/minet)
**minet** is a webmining command line tool & library for python (>= 3.7) that can be used to collect and extract data from a large variety of web sources such as raw webpages, Facebook, CrowdTangle, YouTube, Twitter, Media Cloud etc.
It adopts a very simple approach to various webmining problems by letting you perform a variety of actions from the comfort of the command line. No database needed: raw CSV files should be sufficient to do most of the work.
In addition, **minet** also exposes its high-level programmatic interface as a python library so you can tweak its behavior at will.
**Shortcuts**: [Command line documentation](./docs/cli.md), [Python library documentation](./docs/lib.md).
## Summary
* [What it does](#what-it-does)
* [Documented use cases](#documented-use-cases)
* [Features (from a technical standpoint)](#features-from-a-technical-standpoint)
* [Installation](#installation)
* [Upgrading](#upgrading)
* [Uninstallation](#uninstallation)
* [Documentation](#documentation)
* [Contributing](#contributing)
* [How to cite](#how-to-cite)
## What it does
Minet can single-handedly:
* Extract URLs from a text file (or a table)
* Parse URLs (get useful information, with Facebook- and Youtube-specific stuff)
* Join two CSV files by matching the columns containing URLs
* From a list of URLs, resolve their redirections
* ...and check their HTTP status
* ...and download the HTML
* ...and extract hyperlinks
* ...and extract the text content and other metadata (title...)
* ...and scrape structured data (using a declarative language to define your heuristics)
* Crawl (using a declarative language to define a browsing behavior, and what to harvest)
* Mine or search:
* *[Buzzsumo](https://buzzsumo.com/)* (requires API acess)
* *[Crowdtangle](https://www.crowdtangle.com/)* (requires API access)
* *[Mediacloud](https://mediacloud.org/)* (requires free API access)
* *[Twitter](https://twitter.com)* (requires free API access)
* *[Youtube](https://www.youtube.com/)* (requires free API access)
* Scrape (without requiring special access, often just a user account):
* *[Facebook](https://www.facebook.com/)*
* *[Instagram](https://www.instagram.com/)*
* *[Telegram](https://telegram.org/)*
* *[TikTok](https://www.tiktok.com)*
* *[Twitter](https://twitter.com)*
* *[Google Drive](https://drive.google.com)* (spreadsheets etc.)
* Grab & dump cookies from your browser
* Dump *[Hyphe](https://hyphe.medialab.sciences-po.fr/)* data
## Documented use cases
* [Fetching a large amount of urls](./cookbook/fetch.md)
* [Joining 2 CSV files by urls](./cookbook/url_join.md)
* [Using minet from a Jupyter notebook](./cookbook/notebooks/Minet%20in%20a%20Jupyter%20notebook.ipynb) (*very useful to experiment with the tool or teach students*)
* [Downloading images associated with a given hashtag on Twitter](./cookbook/twitter_images.md)
* [Scraping DSL Tutorial](./cookbook/scraping_dsl.md)
## Features (from a technical standpoint)
* Multithreaded, memory-efficient fetching from the web.
* Multithreaded, scalable crawling using a comfy DSL.
* Multiprocessed raw text content extraction from HTML pages.
* Multiprocessed scraping from HTML pages using a comfy DSL.
* URL-related heuristics utilities such as extraction, normalization and matching.
* Data collection from various APIs such as [CrowdTangle](https://www.crowdtangle.com/).
## Installation
**minet** can be installed as a standalone CLI tool (currently only on mac >= 10.14, ubuntu & similar) by running the following command in your terminal:
```shell
curl -sSL https://raw.githubusercontent.com/medialab/minet/master/scripts/install.sh | bash
```
Don't trust us enough to pipe the result of a HTTP request into `bash`? We wouldn't either, so feel free to read the installation script [here](./scripts/install.sh) and run it on your end if you prefer.
On ubuntu & similar you might need to install `curl` and `unzip` before running the installation script if you don't already have it:
```shell
sudo apt-get install curl unzip
```
Else, **minet** can be installed directly as a python CLI tool and library using pip:
```shell
pip install minet
```
If you need more help to install and use **minet** from scratch, you can check those [installation documents](./docs/install.md).
Finally if you want to install the standalone binaries by yourself (even for windows) you can find them in each release [here](https://github.com/medialab/minet/releases).
## Upgrading
To upgrade the standalone version, simply run the install script once again:
```shell
curl -sSL https://raw.githubusercontent.com/medialab/minet/master/scripts/install.sh | bash
```
To upgrade the python version you can use pip thusly:
```shell
pip install -U minet
```
## Uninstallation
To uninstall the standalone version:
```shell
curl -sSL https://raw.githubusercontent.com/medialab/minet/master/scripts/uninstall.sh | bash
```
To uninstall the python version:
```shell
pip uninstall minet
```
## Documentation
* [minet as a command line tool](./docs/cli.md)
* [minet as a python library](./docs/lib.md)
## Contributing
To contribute to **minet** you can check out [this](./CONTRIBUTING.md) documentation.
## How to cite
**minet** is published on [Zenodo](https://zenodo.org/) as [](https://zenodo.org/badge/latestdoi/169059797)
You can cite it thusly:
> Guillaume Plique, Pauline Breteau, Jules Farjas, Héloïse Théro, Jean Descamps, Amélie Pellé, & Laura Miguel. (2019, October 14). Minet, a webmining CLI tool & library for python. Zenodo. http://doi.org/10.5281/zenodo.4564399
%package help
Summary: Development documents and examples for minet
Provides: python3-minet-doc
%description help
[](https://github.com/medialab/minet/actions) [](https://zenodo.org/badge/latestdoi/169059797) [](https://pepy.tech/project/minet)
**minet** is a webmining command line tool & library for python (>= 3.7) that can be used to collect and extract data from a large variety of web sources such as raw webpages, Facebook, CrowdTangle, YouTube, Twitter, Media Cloud etc.
It adopts a very simple approach to various webmining problems by letting you perform a variety of actions from the comfort of the command line. No database needed: raw CSV files should be sufficient to do most of the work.
In addition, **minet** also exposes its high-level programmatic interface as a python library so you can tweak its behavior at will.
**Shortcuts**: [Command line documentation](./docs/cli.md), [Python library documentation](./docs/lib.md).
## Summary
* [What it does](#what-it-does)
* [Documented use cases](#documented-use-cases)
* [Features (from a technical standpoint)](#features-from-a-technical-standpoint)
* [Installation](#installation)
* [Upgrading](#upgrading)
* [Uninstallation](#uninstallation)
* [Documentation](#documentation)
* [Contributing](#contributing)
* [How to cite](#how-to-cite)
## What it does
Minet can single-handedly:
* Extract URLs from a text file (or a table)
* Parse URLs (get useful information, with Facebook- and Youtube-specific stuff)
* Join two CSV files by matching the columns containing URLs
* From a list of URLs, resolve their redirections
* ...and check their HTTP status
* ...and download the HTML
* ...and extract hyperlinks
* ...and extract the text content and other metadata (title...)
* ...and scrape structured data (using a declarative language to define your heuristics)
* Crawl (using a declarative language to define a browsing behavior, and what to harvest)
* Mine or search:
* *[Buzzsumo](https://buzzsumo.com/)* (requires API acess)
* *[Crowdtangle](https://www.crowdtangle.com/)* (requires API access)
* *[Mediacloud](https://mediacloud.org/)* (requires free API access)
* *[Twitter](https://twitter.com)* (requires free API access)
* *[Youtube](https://www.youtube.com/)* (requires free API access)
* Scrape (without requiring special access, often just a user account):
* *[Facebook](https://www.facebook.com/)*
* *[Instagram](https://www.instagram.com/)*
* *[Telegram](https://telegram.org/)*
* *[TikTok](https://www.tiktok.com)*
* *[Twitter](https://twitter.com)*
* *[Google Drive](https://drive.google.com)* (spreadsheets etc.)
* Grab & dump cookies from your browser
* Dump *[Hyphe](https://hyphe.medialab.sciences-po.fr/)* data
## Documented use cases
* [Fetching a large amount of urls](./cookbook/fetch.md)
* [Joining 2 CSV files by urls](./cookbook/url_join.md)
* [Using minet from a Jupyter notebook](./cookbook/notebooks/Minet%20in%20a%20Jupyter%20notebook.ipynb) (*very useful to experiment with the tool or teach students*)
* [Downloading images associated with a given hashtag on Twitter](./cookbook/twitter_images.md)
* [Scraping DSL Tutorial](./cookbook/scraping_dsl.md)
## Features (from a technical standpoint)
* Multithreaded, memory-efficient fetching from the web.
* Multithreaded, scalable crawling using a comfy DSL.
* Multiprocessed raw text content extraction from HTML pages.
* Multiprocessed scraping from HTML pages using a comfy DSL.
* URL-related heuristics utilities such as extraction, normalization and matching.
* Data collection from various APIs such as [CrowdTangle](https://www.crowdtangle.com/).
## Installation
**minet** can be installed as a standalone CLI tool (currently only on mac >= 10.14, ubuntu & similar) by running the following command in your terminal:
```shell
curl -sSL https://raw.githubusercontent.com/medialab/minet/master/scripts/install.sh | bash
```
Don't trust us enough to pipe the result of a HTTP request into `bash`? We wouldn't either, so feel free to read the installation script [here](./scripts/install.sh) and run it on your end if you prefer.
On ubuntu & similar you might need to install `curl` and `unzip` before running the installation script if you don't already have it:
```shell
sudo apt-get install curl unzip
```
Else, **minet** can be installed directly as a python CLI tool and library using pip:
```shell
pip install minet
```
If you need more help to install and use **minet** from scratch, you can check those [installation documents](./docs/install.md).
Finally if you want to install the standalone binaries by yourself (even for windows) you can find them in each release [here](https://github.com/medialab/minet/releases).
## Upgrading
To upgrade the standalone version, simply run the install script once again:
```shell
curl -sSL https://raw.githubusercontent.com/medialab/minet/master/scripts/install.sh | bash
```
To upgrade the python version you can use pip thusly:
```shell
pip install -U minet
```
## Uninstallation
To uninstall the standalone version:
```shell
curl -sSL https://raw.githubusercontent.com/medialab/minet/master/scripts/uninstall.sh | bash
```
To uninstall the python version:
```shell
pip uninstall minet
```
## Documentation
* [minet as a command line tool](./docs/cli.md)
* [minet as a python library](./docs/lib.md)
## Contributing
To contribute to **minet** you can check out [this](./CONTRIBUTING.md) documentation.
## How to cite
**minet** is published on [Zenodo](https://zenodo.org/) as [](https://zenodo.org/badge/latestdoi/169059797)
You can cite it thusly:
> Guillaume Plique, Pauline Breteau, Jules Farjas, Héloïse Théro, Jean Descamps, Amélie Pellé, & Laura Miguel. (2019, October 14). Minet, a webmining CLI tool & library for python. Zenodo. http://doi.org/10.5281/zenodo.4564399
%prep
%autosetup -n minet-0.67.1
%build
%py3_build
%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .
%files -n python3-minet -f filelist.lst
%dir %{python3_sitelib}/*
%files help -f doclist.lst
%{_docdir}/*
%changelog
* Wed Apr 12 2023 Python_Bot <Python_Bot@openeuler.org> - 0.67.1-1
- Package Spec generated
|
