instagram-to-sqlite
Save data from a Instagram takeout to a SQLite database.
Mise En Place
git clone https://github.com/gavindsouza/instagram-to-sqlite
pip install -e ./instagram-to-sqlite
This tool only supports JSON data takeouts.
Ricing the potatoes
$ instagram-to-sqlite chats insta-chats.db ~/Downloads/takeout-20190530.zip
This will create a database file called insta-chats.db if one does not already exist.
Serving with the steak
Once you have imported Instagram data into a SQLite database file you can browse your data using Datasette. Install Datasette like so:
$ pip install datasette
Next run
datasette insta-chats.db -o
If you're new to SQL but still want to see what you could do with this, then
- Find out what was the first message ever sent on any of your instagram chat rooms*
SELECT
chat_room "Room", sender_name "Sender", coalesce(content, share, photos, videos, users, audio_files) "Message"
FROM
chats_messages
GROUP BY
chat_room
HAVING
min(timestamp_ms)
ORDER BY
timestamp_ms
Chat rooms refer to any regular, cross-platform or group chat.
- Awhhgee, how about the second messages? A bit unrealistic but still...maybe you really have to KNOW
WITH ordered_messages
AS (SELECT *,
Row_number()
OVER (
partition BY chat_room
ORDER BY timestamp_ms) AS 'rank'
FROM chats_messages
)
SELECT
chat_room "Room", sender_name "Sender", coalesce(content, share, photos, videos, users, audio_files) "Message"
FROM
ordered_messages
WHERE
rank = 2
ORDER BY
timestamp_ms ASC
- Okay cool, what if I just want to start reading my chats from their inception like a...normal person...?
SELECT
type, sender_name, DATETIME(ROUND(timestamp_ms / 1000), 'unixepoch') "Date", coalesce(content, share, photos, videos, users, audio_files) "Message"
FROM
chats_messages
WHERE
chat_room = '{chat_room}'
ORDER BY
timestamp_ms
You will have to figure out the chat_room ID you want to query, but it won't be hard to figure that out.
References
-
Read more about datasette in the docs.
-
Checkout the dogsheep project if you're interested in building your personal data warehouse ;)
Pending stuff
This is the rest of the data available in the Instagram takeout that I haven't built import tools for, yet. Currently, only chat data is covered.
other_data = {
"login_and_account_creation": [
"login_activity.json", "logout_activity.json",
"signup_information.json", "password_change_activity.json",
"account_privacy_changes.json"
],
"shopping": ["recently_viewed_items.json"],
"comments": ["post_comments.json", "comments_reported.json"],
"device_information": ["camera_information.json", "devices.json"],
"ads_and_content": [
"suggested_accounts_viewed.json", "ads_viewed.json",
"posts_viewed.json", "videos_watched.json", "ads_clicked.json"
],
"information_about_you": ["account_based_in.json", "ads_interests.json"],
"likes": ["liked_posts.json", "liked_comments.json"],
"content": [
"posts_1.json", "profile_photos.json", "stories.json",
"archived_posts.json", "other_content.json",
"recently_deleted_content.json"
],
"your_topics": [
"your_reels_topics.json", "your_topics.json",
"your_reels_sentiments.json"
],
"story_sticker_interactions": [
"emoji_reactions.json", "quizzes.json", "questions.json",
"emoji_sliders.json", "polls.json"
],
"comments_settings": ["use_cross-app_messaging.json", "comments_allowed_from.json"],
"recent_searches": ["tag_searches.json", "account_searches.json"],
"saved": ["saved_collections.json", "saved_posts.json"],
"followers_and_following": [
"removed_suggestions.json", "following_hashtags.json",
"following.json", "followers.json", "recent_follow_requests.json",
"pending_follow_requests.json", "close_friends.json"
],
"account_information": [
"account_information.json", "profile_changes.json",
"personal_information.json"
]
}
1 Jan 29, 2022
3 Jun 25, 2022
5 Sep 21, 2022
1 Mar 15, 2022
3 Nov 27, 2022
3 Feb 06, 2022
26 Oct 05, 2022
159 Dec 12, 2022
10 Nov 02, 2022
2 Feb 28, 2022
1 Dec 26, 2021
450 Jan 05, 2023
328 Dec 29, 2022
38 Dec 25, 2022
1 Dec 29, 2021
17 Dec 11, 2022
4 May 05, 2022
56 Dec 29, 2022
9 Aug 25, 2022
11 Nov 05, 2022