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https://github.com/toadlyBroodle/spam-bot-3000

Social media research and promotion, semi-autonomous CLI bot
https://github.com/toadlyBroodle/spam-bot-3000

automation bot cli command-line-tool facebook firefox geckodriver hashtag instagram keyword marketing promotion python reddit research scrape-dumps scraper selenium social-media twitter

Last synced: 3 months ago
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Social media research and promotion, semi-autonomous CLI bot

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# spam-bot-3000

A python command-line (CLI) bot for automating research and promotion on popular social media platforms (reddit, twitter, facebook, [TODO: instagram]). With a single command, scrape social media sites using custom queries and/or promote to all relevant results.



Please use with discretion: i.e. choose your input arguments wisely, otherwise your bot could find itself, along with any associated accounts, banned from platforms very quickly. The bot has some built in anti-spam filter avoidance features to help you remain undetected; however, no amount of avoidance can hide blatantly abusive use of this tool.



## features

- reddit

	- scrape subreddit(s) for lists of keyword, dump results in local file (red_scrape_dump.txt)

		- separate keyword lists for AND, OR, NOT search operations (red_subkey_pairs.json)

		- search new, hot, or rising categories

	- reply to posts in red_scrape_dump.txt with random promotion from red_promos.txt

		- ignore posts by marking them in dump file with "-" prefix

	- praw.errors.HTTPException handling

	- write all activity to log (log.txt)

- twitter

	- maintain separate jobs for different promotion projects

	- update user status

	- unfollow users who don't reciprocate your follow

	- scan twitter for list of custom queries, dump results in local file (twit_scrape_dump.txt)

		- scan continuously or in overwatch mode

	- optional bypassing of proprietary twitter APIs and their inherent limitations

	- promotion abilities

        - tweepy api

		    - follow original posters

		    - favorite relevant tweets

		    - direct message relevant tweets

		    - reply to relevant tweets with random promotional tweet from file (twit_promos.txt)

        - Selenium GUI browser

            - favorite, follow, reply to scraped results while bypassing API limits	    

        - ignore tweets by marking them in dump file with "-" prefix

	- script for new keyword, hashtag research by gleening scraped results

	- script for filtering out irrelevant keywords, hashtags, screen names

	- script for automating scraping, filtering, and spamming only most relevant results

	- relatively graceful exception handling

	- write all activity to log (log.txt)

- facebook

	- zero reliance on proprietary facebook APIs and their inherent limitations

	- Selenium GUI browser agent

	- scrape public and private user profiles for keywords using AND, OR, NOT operators

		- note: access to private data requires login to authorized account with associated access

	- scrape public and private group feeds for keywords using AND, OR, NOT operators



## dependencies

- install dependencies you probably don't have already, errors will show up if you're missing any others

	- install pip3 `sudo apt install python3-pip`

	- install dependencies `pip3 install --user tweepy bs4 praw selenium`



## reddit initial setup

- update 'praw.ini' with your reddit app credentials

	- how to register a new reddit app

- replace example promotions (red_promos.txt) with your own

- replace example subreddits and keywords (red_subkey_pairs.json) with your own

	- you'll have to follow the existing json format

	- `keywords_and`: all keywords in this list must be present for positive matching result

	- `keywords_or`: at least one keyword in this list must be present for positive match

	- `keywords_not`: none of these keywords can be present in a positive match

	- any of the three lists may be omitted by leaving it empty - e.g. `"keywords_not": []`



```

...



[bot1]

client_id=Y4PJOclpDQy3xZ

client_secret=UkGLTe6oqsMk5nHCJTHLrwgvHpr

password=pni9ubeht4wd50gk

username=fakebot1

user_agent=fakebot 0.1

```



```

{"sub_key_pairs": [

{

  "subreddits": "androidapps",

  "keywords_and": ["list", "?"],

  "keywords_or": ["todo", "app", "android"],

  "keywords_not": ["playlist", "listen"]

}

]}

```



## reddit usage

```

usage: spam-bot-3000.py reddit [-h] [-s N] [-n | -H | -r] [-p]



optional arguments:

  -h,	--help		show this help message and exit

  -s N,	--scrape N	scrape subreddits in subreddits.txt for keywords in red_keywords.txt; N = number of posts to scrape

  -n,	--new		scrape new posts

  -H,	--hot		scrape hot posts

  -r,	--rising	scrape rising posts

  -p,	--promote	promote to posts in red_scrape_dump.txt not marked with a "-" prefix

```



## twitter initial setup

- create new directory to store new job data in (e.g. studfinder_example/)

- create new 'credentials.txt' file in job directory to store your twitter app's credentials

	- a good guide for how to get twitter credentials



```

your_consumer_key

your_consumer_secret

your_access_token

your_access_token_secret

your_twitter_username

your_twitter_password

```



- create new 'twit_promos.txt' in job directory to store your job's promotions to spam

	- individual tweets on seperate lines

	- each line must by <= 140 characters long

- create new 'twit_queries.txt' in job directory to store your job's queries to scrape twitter for

	- individual queries on seperate lines

	- guide to constructing twitter queries

- create new 'twit_scrape_dump.txt' file to store your job's returned scrape results



## twitter usage

```

usage: spam-bot-3000.py twitter [-h] [-j JOB_DIR] [-t] [-u UNF] [-s] [-c] [-e] [-b]

                          [-f] [-p] [-d]

spam-bot-3000

optional arguments:

 -h, --help		show this help message and exit

 -j JOB_DIR, --job JOB_DIR

	                choose job to run by specifying job's relative directory

 -t, --tweet-status 	update status with random promo from twit_promos.txt

 -u UNF, --unfollow UNF

                        unfollow users who aren't following you back, UNF=number to unfollow



 query:

 -s, --scrape		scrape for tweets matching queries in twit_queries.txt

 -c, --continuous	scape continuously - suppress prompt to continue after 50 results per query

 -e, --english         	return only tweets written in English



spam -> browser:

 -b, --browser          favorite, follow, reply to all scraped results and

                        thwart api limits by mimicking human in browser!



spam -> tweepy api:

 -f, --follow		follow original tweeters in twit_scrape_dump.txt

 -p, --promote		favorite tweets and reply to tweeters in twit_scrape_dump.txt with random promo from twit_promos.txt

 -d, --direct-message	direct message tweeters in twit_scrape_dump.txt with random promo from twit_promos.txt

```



## twitter example workflows

1) continuous mode

	- `-cspf` scrape and promote to all tweets matching queries

2) overwatch mode

	- `-s` scrape first

	- manually edit twit_scrape_dump.txt

		- add '-' to beginning of line to ignore

		- leave line unaltered to promote to

	- `-pf` then promote to remaining tweets in twit_scrape_dump.txt

3) gleen common keywords, hashtags, screen names from scrape dumps

	- `bash gleen_keywords_from_twit_scrape.bash`

		- input file: twit_scrape_dump.txt

		- output file: gleened_keywords.txt

            - results ordered by most occurrences first

4) filter out keywords/hashtags from scrape dump

    - manually edit gleened_keywords.txt by removing all relevent results

    - `filter_out_strings_from_twit_scrape.bash`

        - keywords input file: gleened_keywords.txt		

        - input file: twit_scrape_dump.txt

		- output file: twit_scrp_dmp_filtd.txt

5) browser mode

    - `-b` thwart api limits by promoting to scraped results directly in firefox browser

		- add username and password to lines 5 and 6 of credentials.txt respectively

6) automatic scrape, filter, spam

	- `auto_spam.bash`

		- automatically scrape twitter for queries, filter out results to ignore, and spam remaining results

7) specify job

    - `-j studfinder_example/` specify which job directory to execute



Note: if you don't want to maintain individual jobs in separate directories, you may create single credentials, queries, promos, and scrape dump files in main working directory.



## facebook initial setup

- create new client folder in 'facebook/clients/YOUR_CLIENT'

- create new 'jobs.json' file to store your client's job information in the following format:



```

{"client_data":

	{"name": "",

	"email": "",

	"fb_login": "",

	"fb_password": "",

	"jobs": [

		{"type": "groups",

			"urls": ["",""],

			"keywords_and": ["",""],

			"keywords_or": ["",""],

			"keywords_not": ["",""] },

		{"type": "users",

			"urls": [],

			"keywords_and": [],

			"keywords_or": [],

			"keywords_not": [] }

	]}

}

```



## facebook usage

- scrape user and group feed urls for keywords

	- `facebook-scraper.py clients/YOUR_CLIENT/`

		- results output to 'clients/YOUR_CLIENT/results.txt'



## TODO

- Flesh out additional suite of promotion and interaction tool for facebook platform

- Organize platforms and their associated data and tools into their own folders and python scripts

- Future updates will include modules for scraping and promoting to Instagram.