So this is my first time coding an actual project that isn't a small coding task. I've got a bot that runs and responds to a message if it says "hello". I've read the API documentation up and down and really only have a vague understanding of it and I'm not sure how to implement it.
My question right now is how would I go about creating a command that takes informationn from a message the command is replying to (sender's name, message content) and stores it as an object. Also, what would be the best way to store that information?
I want to learn while doing this and not just have the answers handed to me ofc, but I feel very lost. Not sure where to even begin.
I tried to find tutorials on coding discord bots that would have similar functions to what I want to do, but can't find anything.
Intro :
Hi NyssaDuke !
First of all, prefer to paste your code instead of a picture. It's easier for us to take your code and try to produce what you wish.
In second, I see an "issue" in your code since you declare twice the bot. You can specify the intents when you declare your bot as bot = commands.Bot(command_prefix="!", intents=intents)
Finally, as stated by #stijndcl , it's against TOS, but I will try to answer you at my best.
filesystem
My bot needs to store data, like users ID, language, and contents relative to a game, to get contacted further. Since we can have a quite big load of requests in a small time, I prefered to use a file to store instead of a list that would disappear on crash, and file allow us to make statistics later. So I decided to use pytables that you can get via pip install pytables. It looks like a small DB in a single file. The file format is HDF5.
Let say we want to create a table containing user name and user id in a file :
import tables
class CUsers (tables.IsDescription) :
user_name = StringCol(32)
user_id = IntCol()
with tables.open_file("UsersTable.h5", mode="w") as h5file :
groupUser = h5file.create_group("/", "Users", "users entries")
tableUser = h5file.create_table(groupUser, "Users", CUsers, "users table")
We have now a file UsersTable.h5 that has an internal table located in root/Users/Users that is accepting CUsers objects, where, therefore, user_name and user_id are the columns of that table.
getting user info and storing it
Let's now code a function that will register user infos, and i'll call it register. We will get the required data from the Context that is passed with the command, and we'll store it in file.
#bot.command(name='register')
async def FuncRegister (ctx) :
with tables.open_file("UsersTable.h5", mode="a") as h5file :
tableUser = h5file.root.Users.Users
particle = tableUser.row
particle['user_name'] = str(ctx.author)
particle['user_id'] = ctx.author.id
particle.append()
tableUser.flush()
The last two lines are sending the particle, that is the active row, so that is an object CUsers, into the file.
An issue I got here is that special characters in a nickname can make the code bug. It's true for "é", "ü", etc, but also cyrillic characters. What I did to counter is to encode the user name into bytes, you can do it by :
particle['user_name'] = str(ctx.author).encode()
reading file
It is where it starts to be interesting. The HFS5 file allows you to use kind of sql statements. Something you have to take in mind is that strings in the file are UTF-8 encoded, so when you extract them, you have to call for .decode(utf-8). Let's now code a function where a user can remove its entry, based on its id :
#bot.command(name="remove")
async def FuncRemove(ctx) :
with tables.open_file("UsersTable.h5", mode="a") as h5file :
tableUser = h5file.root.Users.Users
positions = tableUser.get_where_list("(user_id == '%d')" % ctx.author.id)
nameuser = tableUser[positions[0]]['user_name'].decode('utf-8')
tableUser.remove_row(positions[0])
.get_where_list() returns a list of positions in the file, that I later address to find the right position in the table.
bot.fetch_user(id)
If possible, prefer saving ID over name, as it complicates the code with encode() and decode(), and that bots have access to a wonderful function that is fetch_user(). Let's code a last function that will get you the last entry in your table, and with the id, print the username with the fetch method :
#bot.command(name="last")
async def FuncLast(ctx) :
with tables.open_file("UsersTable.h5", mode="r") as h5file :
tableUser = h5file.root.Users.Users
lastUserIndex = len(tableUser) - 1
iduser = tableUser[lastUserIndex]['user_id']
member = await bot.fetch_user(iduser)
await ctx.send(member.display_name)
For further documentation, check the manual of discord.py, this link to context in particular.
Related
I need to compare 2 company names, one is from a text file, the other from databases. I import a licence in txt file and if the names are different, a notification on page will pop up asking if I want to rename it (new name will be saved in database).
In JavaScript React, I have to write code that can read a text file, specifically one line from it. This line contains the name of the company that I need to compare with the second name which is in the database.
const handleDispalyDialogButtonClick = () => {
if (nametxt! == namedatabase) {
setDisplayDialog(true)
}
handleImportButtonClick();
};
nametxt is to be the name of the company in the text file. This name needs to be imported somehow and assigned to nametxt.
[license]
lic_base=xxxx
lic_nip=xxxx
PC_Nazwa1=name of the company1
PC_Nazwa2=name of the company2
PC_Nazwa3=name of the company3
For example it's like Car=BMW.
Does anyone have a solution how to make a code which gonna import information, and assign it?
You need to put the file you want in your public folder and just fetch it:
fetch('/path/to/the/file').then((response) => response.text())
.then((data) => {
// read file lines here
const fileLines = data.split('\n')
// find the value you are looking for and compare it to the value you get from the database
}
Also, the screenshot you shared looks like a TOML file, you might want to parse that with TOML Parser to make things easier.
For the value on the database, you cannot directly interact with a database from your code. You need to have an extra layer like an API and request the data from there.
So I'm trying to create a bot that is more universal and can be added to more than one server. I've managed to reformat commands like announce or join messages etc. by using .find("name", "announcements").
My problem is that the same does not work for roles.
I've tried what little I could find on the internet, such as member.guild.roles.find("name", "Member") or member.guild.roles.find(role => role.name === "Member") but none of these work. A variety of different ways return different errors, but they usually say something along the lines of it not being an integer (I think) or snowflake.
This is the function that I am currently wrestling with:
client.on('guildMemberAdd', (member) => {
var joinResponse = ("Hello **" + member.displayName + "**, welcome to **" + member.guild.name + "**!")
let role = member.guild.roles.find("name", "Member");
member.addRole(role).catch(console.error);
member.guild.channels.find('name', 'general').send(joinResponse);
In short summary, what I'm looking for is the ability to get a role by name and add a user to it.
(I'm nearly certain it's possible, since popular bots like Dyno are capable of using commands to add roles to users.)
client.on('guildMemberAdd', (member) => {
const joinResponse = `Hello **${member.user.username}**, welcome to: **${member.guild.name}**!`
let role = member.guild.roles.get('Member');
if(!role) return console.log("Role doesen't exist.");
member.addRole(role);
const ch = member.guild.channels.get('general');
if(!ch) return console.log("Channel doesen't exist.");
ch.send(joinResponse);
});//You didn't have closing brackets (Could've been a problem)
First of all your string joinResponse was a function and you completely messed up merging it, I recommend using Template literal.
I used get function since it's a lot easier to use and cleaner, you only pass ID or name as a string.
To check if channel exists I used if statements and exclamation mark which means doesen't exist/false.
If I helped you please mark this as answer, thanks <3. If you need anything add comment to answer or message me on Discord (You can find my discriminator on my stack overflow profile).
For further explanation click on Blue words.
I have a model that looks like this:
class Report(models.Model):
updater = models.CharField(max_length=15)
pub_date = models.DateTimeField(auto_add_now=True)
identifier = models.CharField(max_length=100)
... and so on...
There are some more fields but they are irrelevant to the question. Now the site has very simple functions - the users can see older reports and their data, and can edit them or add new ones.
However, the identifier field is actually an integer that symbolizes a log file that is being reported. Most of the times, each report has one log. But sometimes it has more than one. I did it as a CharField because I built the site to replace an older sharepoint 2003 website, where that field was treated as simple text. So I want that in my next version, it would be like it should be, i.e. like this:
class Report(models.Model):
updater = models.CharField(max_length=15)
pub_date = models.DateTimeField(auto_add_now=True)
... and so on...
class Log(models.Model):
report = models.ForeignKey(Report)
identifier = models.IntegerField()
The problem is, since in the old site that field was a CharField, people used this as they liked. Meaning, even if they updated various logs in the same report they just did it like this <logid1>, <logid2>. Sometimes they added some text <logid1> which is related to <logid2>.
So I want to change this, but I don't want to lose all the old data, and I can't fix all those edge cases (the DB contains around 22 thousand reports). I thought about adding this to report:
def disp_id(self):
if self.pub_date < ... #the day I'll do the update
return self.identifier
else:
return ', '.join([log.identifier for log in self.log_set.all()])
But then I'm not really getting rid of the old field now am I? I'm just adding a new one and keeping the original null from a certain date.
As far as I know, what I want to do is impossible. I'm only asking because I know that maybe I'm not the first one to deal with this sort of thing and maybe there is a solution that I'm not aware of.
Hope my explanation is clear enough, thanks in advance!
class Report(models.Model):
updater = models.CharField(max_length=15)
pub_date = models.DateTimeField(auto_add_now=True)
identifier = models.CharField(null=True)
... and so on...
logs = models.ManyToManyField(Log,null=True)
class Log(models.Model):
identifier = models.IntegerField()
Make the above model , and then make a script as follow:
ident_list = []
for reports in Report.objects.all():
identifiers = reports.identifiers.split(',')
for idents in identifiers:
if not idents in ident_list:
log = Log.create(**{'identifier' : int(idents)})
ident_list.append(int(idents))
else:
log = Log.objects.get(identifier = int(idents))
report.log.add(log)
Check the data before removing the column identifiers from the table Report.
Does it solves your purpose now ?
I have the following objects: L1User, L2User, L3User (all inherits from User) and Document.
Every user can create the document but depending on the user type, the document will have a different status. So in case it's L1User, the document will be created with L1 status and so on:
Solution 1
Please note that after document is created, it will be saved in the database, so it should be natural to have a method create_document(User user) in Document object. In the method body I could check which type is the user and set manually appropriate status. Such approach seems rather not OOP to me.
Solution 2
Ok, so the next approach would be to have all users implement a common method (say create_document(Document doc)) which will set a status associated with the user and save the document in the database. My doubt here is that the document should be saved in it's own class, not the user.
Solution 3
So the final approach would similar to the above, except that the user will return modified document object to it's create_document(User user) method and save will be performed there. The definition of the method would be like this:
create_document(User user)
{
this = user.create_document(this);
this->save();
}
It also doesn't seems right to me...
Can anyone suggest a better approach?
I think that both Solutions 2 and 3 are ok from the OO point of view, since you are properly delegating the status assignment to the user object (contrary to solution 1, whare you are basically doing a switch based on the user type). Whether to choose 2 or 3 is more a matter of personal tastes.
However, I have a doubt: why do you pass a document to a create_document() method? I would go for a message name that best describes what it does. For example, in solution 3 (the one I like the most) I would go for:
Document>>create_document(User user)
{
this = user.create_document();
this->save();
}
and then
L1User>>create_document()
{
return new Document('L1');
}
or
Document>>create_document(User user)
{
this = new Document()
this = user.set_document_type(this);
this->save();
}
and then
L1User>>set_document_type(document)
{
document.setType('L1');
}
Edit: I kept thinking about this and there is actually a fourth solution. However the following approach works only if the status of a document doesn't change through its lifetime and you can map the DB field with a getter instead of a property. Since the document already knows the user and the status depends on the user, you can just delegate:
Document>>getStatus()
{
return this.user.getDocumentStatus();
}
HTH
I wish to search twitter for a word (let's say #google), and then be able to generate a tag cloud of the words used in twitts, but according to dates (for example, having a moving window of an hour, that moves by 10 minutes each time, and shows me how different words gotten more often used throughout the day).
I would appreciate any help on how to go about doing this regarding: resources for the information, code for the programming (R is the only language I am apt in using) and ideas on visualization. Questions:
How do I get the information?
In R, I found that the twitteR package has the searchTwitter command. But I don't know how big an "n" I can get from it. Also, It doesn't return the dates in which the twitt originated from.
I see here that I could get until 1500 twitts, but this requires me to do the parsing manually (which leads me to step 2). Also, for my purposes, I would need tens of thousands of twitts. Is it even possible to get them in retrospect?? (for example, asking older posts each time through the API URL ?) If not, there is the more general question of how to create a personal storage of twitts on your home computer? (a question which might be better left to another SO thread - although any insights from people here would be very interesting for me to read)
How to parse the information (in R)? I know that R has functions that could help from the rcurl and twitteR packages. But I don't know which, or how to use them. Any suggestions would be of help.
How to analyse? how to remove all the "not interesting" words? I found that the "tm" package in R has this example:
reuters <- tm_map(reuters, removeWords, stopwords("english"))
Would this do the trick? I should I do something else/more ?
Also, I imagine I would like to do that after cutting my dataset according to time (which will require some posix-like functions (which I am not exactly sure which would be needed here, or how to use it).
And lastly, there is the question of visualization. How do I create a tag cloud of the words? I found a solution for this here, any other suggestion/recommendations?
I believe I am asking a huge question here but I tried to break it to as many straightforward questions as possible. Any help will be welcomed!
Best,
Tal
Word/Tag cloud in R using "snippets" package
www.wordle.net
Using openNLP package you could pos-tag the tweets(pos=Part of speech) and then extract just the nouns, verbs or adjectives for visualization in a wordcloud.
Maybe you can query twitter and use the current system-time as a time-stamp, write to a local database and query again in increments of x secs/mins, etc.
There is historical data available at http://www.readwriteweb.com/archives/twitter_data_dump_infochimp_puts_1b_connections_up.php and http://www.wired.com/epicenter/2010/04/loc-google-twitter/
As for the plotting piece: I did a word cloud here: http://trends.techcrunch.com/2009/09/25/describe-yourself-in-3-or-4-words/ using the snippets package, my code is in there. I manually pulled out certain words. Check it out and let me know if you have more specific questions.
I note that this is an old question, and there are several solutions available via web search, but here's one answer (via http://blog.ouseful.info/2012/02/15/generating-twitter-wordclouds-in-r-prompted-by-an-open-learning-blogpost/):
require(twitteR)
searchTerm='#dev8d'
#Grab the tweets
rdmTweets <- searchTwitter(searchTerm, n=500)
#Use a handy helper function to put the tweets into a dataframe
tw.df=twListToDF(rdmTweets)
##Note: there are some handy, basic Twitter related functions here:
##https://github.com/matteoredaelli/twitter-r-utils
#For example:
RemoveAtPeople <- function(tweet) {
gsub("#\\w+", "", tweet)
}
#Then for example, remove #d names
tweets <- as.vector(sapply(tw.df$text, RemoveAtPeople))
##Wordcloud - scripts available from various sources; I used:
#http://rdatamining.wordpress.com/2011/11/09/using-text-mining-to-find-out-what-rdatamining-tweets-are-about/
#Call with eg: tw.c=generateCorpus(tw.df$text)
generateCorpus= function(df,my.stopwords=c()){
#Install the textmining library
require(tm)
#The following is cribbed and seems to do what it says on the can
tw.corpus= Corpus(VectorSource(df))
# remove punctuation
tw.corpus = tm_map(tw.corpus, removePunctuation)
#normalise case
tw.corpus = tm_map(tw.corpus, tolower)
# remove stopwords
tw.corpus = tm_map(tw.corpus, removeWords, stopwords('english'))
tw.corpus = tm_map(tw.corpus, removeWords, my.stopwords)
tw.corpus
}
wordcloud.generate=function(corpus,min.freq=3){
require(wordcloud)
doc.m = TermDocumentMatrix(corpus, control = list(minWordLength = 1))
dm = as.matrix(doc.m)
# calculate the frequency of words
v = sort(rowSums(dm), decreasing=TRUE)
d = data.frame(word=names(v), freq=v)
#Generate the wordcloud
wc=wordcloud(d$word, d$freq, min.freq=min.freq)
wc
}
print(wordcloud.generate(generateCorpus(tweets,'dev8d'),7))
##Generate an image file of the wordcloud
png('test.png', width=600,height=600)
wordcloud.generate(generateCorpus(tweets,'dev8d'),7)
dev.off()
#We could make it even easier if we hide away the tweet grabbing code. eg:
tweets.grabber=function(searchTerm,num=500){
require(twitteR)
rdmTweets = searchTwitter(searchTerm, n=num)
tw.df=twListToDF(rdmTweets)
as.vector(sapply(tw.df$text, RemoveAtPeople))
}
#Then we could do something like:
tweets=tweets.grabber('ukgc12')
wordcloud.generate(generateCorpus(tweets),3)
I would like to answer your question in making big word cloud.
What I did is
Use s0.tweet <- searchTwitter(KEYWORD,n=1500) for 7 days or more, such as THIS.
Combine them by this command :
rdmTweets = c(s0.tweet,s1.tweet,s2.tweet,s3.tweet,s4.tweet,s5.tweet,s6.tweet,s7.tweet)
The result:
This Square Cloud consists of about 9000 tweets.
Source: People voice about Lynas Malaysia through Twitter Analysis with R CloudStat
Hope it help!