Is it possible to get database dumps of EA Forum content? I think it would be useful for data analysis, such as building a topic model of EA causes and estimating how much the forum talks about them.




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We have a GraphQL interface that people can use to scrape Forum data.

We block web crawlers from the All Posts page so that they don't click "load more" a thousand times and slow down the site. But you can use your own crawlers on the page if you're willing to click "Load More" a lot.

Let me know if you have more questions, and I'll make sure they get answered (that is, I'll ask the tech team).

You don't need to use the allPosts page to get a list of all the posts. You can just ask the GraphQL API for the ids of all of them.

If someone wants to put up an extract of the data on Kaggle or Github it might be useful.

[comment deleted]1y1

I was trying out OpenAI Codex after getting access this morning and the task of getting EA Forum data seems ideal for testing it out. 

Using Codex, I got code that seems like it downloads plain text comments from the forum at the rate of thousands per minute. 

It's a lot faster than writing the script by hand, and does nice things quickly (see time zone fixing).

I thought it was neat!

(This isn't hardcore code, but in case the OP, or anyone else needs raw forum data, and doesn't feel like writing the snippets, feel free to comment or send a message.)


Here's a picture OpenAI interface with the "prompt":

Actual Code (bottom half generated by OpenAI Codex):

1. Get the last 100 comments from this internet forum  -
2. Put the contents and createdAt results of the query into a list called comments
4. Clean up the 'plaintextMainText' field by removing all formatting extra line returns
5. Save to dataframe and adjust to PST (Pacific Time Zones)

import pandas as pd
import json
import requests

# Get the last 100 comments from this internet forum  -

# Use this GraphQL Query
query = """
{comments(input: {terms: {view: "recentComments", limit: 100}}) {
    results {
      post {
      user {
      contents {


# Put the postedAt and plaintextMainTextinto a list called comments, with error handling for missing values

comments = []

for i in range(0,1):
    url = ''
    headers = {'Content-Type': 'application/json'}
    r =, json={'query': query}, headers=headers)
    data = json.loads(r.text)
    for comment in data['data']['comments']['results']:
            comments.append([comment['post']['postedAt'], comment['contents']['plaintextMainText']])

# Clean up the 'plaintextMainText' field by removing all formatting extra line returns

for comment in comments:
    comment[1] = comment[1].replace('\n', ' ')

# Save to dataframe and adjust to PST (Pacific Time Zones)

df = pd.DataFrame(comments, columns=['postedAt', 'plaintextMainText'])
df['postedAt'] = pd.to_datetime(df['postedAt'])
df['postedAt'] = df['postedAt'].dt.tz_convert('US/Pacific')
df['postedAt'] = df['postedAt'].dt.tz_localize(None)

# Save to csv

df.to_csv('effective_altruism_comments.csv', index=False)

Here's an example of the output.


  1. You need to provide a GraphQL query to get Codex to work, it isn't going to figure it out. A tutorial for creating GraphQL is here. I made a simple query to get comments, as you can see above. The interface for GraphQL seems pretty good and you can create queries to get posts and a lot of other information.
  2. I haven't let this run to try to get the "entire forum". API/backend limits or other issues might block this.
  3. I can see there's at least one error in my GraphQL query, I think PostedAt gives a timestamp for the post, not the comment. There's other typos (I spent 10x more time writing this forum comment than writing the instructions for Codex to generate the code!)

Here is some code you can use to get the most essential data from all the forum posts:

Also, I used that data to build a topic model of the forum as you mentioned. You can see it here

I tried running this code, but it sends a query that gets:

  "errors": [
      "message": "Exceeded maximum value for skip",
      "locations": [
          "line": 3,
          "column": 3
      "path": [
      "extensions": {
        "code": "INTERNAL_SERVER_ERROR"
  "data": {
    "posts": null

Looking at ForumMagnum code this is:

  // Don't allow API requests with an offset provided >2000. This prevents some
  // extremely-slow queries.
  if (terms.offset &&
... (read more)
When I tried repurposing this code I got a similar error, so that portion in my code now looks like this: query = """ { posts(input: { terms: { view: "new" after: "%s" before: "%s" limit: %d meta: null } }) { results { _id title postedAt postedAtFormatted user { username displayName } wordCount voteCount baseScore commentCount tags { name } } } } """ def send_graphql_request(input_query): r =, json={"query": input_query}, headers=headers) data = json.loads(r.text) return data def return_data(input_query): # Initialize an empty list to store the data data_list = [] # Set the initial date and the end date for the time intervals start_date = pd.Timestamp("1960-01-01") end_date = pd.Timestamp("2019-01-01") # Define the time interval (4-month chunks) for iteration delta = pd.DateOffset(months=4) # Iterate over the time intervals while start_date < print(start_date) # Construct the query with the current time interval query = input_query % ( start_date.strftime("%Y-%m-%d"), end_date.strftime("%Y-%m-%d"), 3000, ) # Call the function to send the GraphQL request and extract the data response = send_graphql_request(query) results = response["data"]["posts"]["results"] # Add the current iteration's data to the list data_list.extend(results) # Increment the dates for the next iteration start_date = end_date end_date += delta # Create a DataFrame from the collected data df = pd.DataFrame(data_list) df["postedAt"] = pd.to_datetime(df["postedAt"]) # Return the final DataFrame return df So ~3000 seemed to be a fine chunksize to get every post, and I use the date strings to iterate through t
Jeff Kaufman
Thanks! I tried extending this for comments, but it looks like it ignores terms; filed an issue.
Sorted by Click to highlight new comments since: Today at 7:23 AM

I recently used GraphQL to download all comments and posts, here and on LW, and the code I used is on github.

Really curious to see what you're going to do with it!

Btw, I think we should use for automated queries

Really curious to see what you're going to do with it!

Thanks, I'd missed that! If I ever do more scraping I'll use that instead: commmit.