This tool connects to Telegram's API. It generates JSON files containing channel's data, including channel's information and posts. You can search for a specific channel, or a set of channels provided in a text file (one channel per line.)

Files are saved by default in a folder called output/data. These folders are created by the script. You can also give a specific output directory to store collected data.

Software required

• Python 3.x
• Telegram API credentials
  • Telegram account
  • App api_id
  • App api_hash

Python required libraries

• Telethon
• Pandas
• Openpyxl
• tqdm
• Networkx
• Matplotlib
• Louvain Community Detection

• Via git clone

git clone https://github.com/estebanpdl/telegram-api.git

This will create a directory called telegram-tracker which contains the Python scripts. Cloning allows you to easily upgrade and switch between available releases.

• From the github download button

Download the ZIP file from github and use your favorite zip utility to unpack the file telegram-tracker.zip on your preferred location.

After cloning or downloding the repository, install the libraries from requirements.txt.

pip install -r requirements.txt

or

pip3 install -r requirements.txt

Once you obtain an API ID and API hash on my.telegram.org, populate the config/config.ini file with the described values.

[Telegram API credentials]
api_id = api_id
api_hash = api_hash
phone = phone

Note: Your phone must be included to authenticate for the first time. Use the format +<code><number> (e.g., +19876543210). Telegram API will send you a code via Telegram app that you will need to include.

This Python script will connect to Telegram's API and handle your API request.

• --telegram-channel Specifies Telegram Channel to download data from.
• --batch-file File containing Telegram Channels to download data from, one channel per line.
• --limit-download-to-channel-metadata Will collect channels metadata only, not channel's messages. (default = False)
• --output, -o Specifies a folder to save collected data. If not given, script will generate a default folder called ./output/data
• --min-id Specifies the offset id. This will update Telegram data with new posts.

├──🗂 output
|   └──🗂 data
|   	└──🗂 <channel_name>
|   		└──<channel_name>.json
|   		└──<channel_name>_messages.json
|   	└──chats.txt // TM channels, groups, or users' IDs found in data.
|   	└──collected_chats.csv // TM channels or groups found in data (e.g., forwards)
|   	└──collected_chats.xlsx // TM channels or groups found in data (e.g., forwards)
|   	└──counter.csv // TM channels, groups or users found in data (e.g., forwards)
|   	└──user_exceptions.txt // From collected_chats, these are mostly TM users' which 
|									metadata was not possible to retrieve via the API
|   	└──msgs_dataset.csv // Posts and messages from the requested channels

python main.py --telegram-channel channelname`

Expected output

• Files of collected channels:
  • chats.txt
  • collected_chats.csv
  • user_exceptions.txt
  • counter.csv
• A new folder: <channel_name> containing
  • A JSON file containing channel's profile metadata
  • A JSON file containing posts from the requested channel

python main.py --batch-file './path/to/channels_text_file.txt'

Expected output

• Files of collected channels:
  • chats.txt
  • collected_chats.csv
  • user_exceptions.txt
  • counter.csv
• New folders - based on the number of requested channels: <channel_name> containing
  • A JSON file containing channel's profile metadata
  • A JSON file containing posts from the requested channel

These examples will retrieve all posts available through the API from the requested channel. If you want to collect channel's information only, without posts, you can run:

python main.py --telegram-channel channelname --limit-download-to-channel-metadata

or, using a set of telegram channels via a text file:

python main.py --batch-file './path/to/channels_text_file.txt' --limit-download-to-channel-metadata

If you want to collect new messages from one channel, you need to identify the message ID from the last post. Once you identify the id, run:

python main.py --telegram-channel channelname --min-id 12345

Expected output

• Files of collected channels:
  • chats.txt
  • collected_chats.csv
  • user_exceptions.txt
  • counter.csv
• A new folder: <channel_name> containing
  • A JSON file containing channel's profile metadata
  • A JSON file containing posts from the requested channel

The script allows you to specify a specific output directory to save collected data. The sxcript will create those folders in case do not exist.

python main.py --telegram-channel channelname --output ./path/to/chosen/directory`

The expected output is the same a described above but data will be save using the chosen directory.

This Python script reads the collected files and creates a new dataset containing messages from the requested channels. By default, the created dataset will be located in the output folder.

If you provided a specific directory to save collected data, you need to provide the same path to use this script.

• --data-path Path were data is located. Will use ./output/data if not given.

If a specific directory was not provided in main.py, run:

python build-datasets.py

If you provided a specific directory using the option --output in main.py, run:

python build-datasets.py --data-path ./path/to/chosen/directory

These option will create the above-mentioned dataset: msgs_dataset.csv, a file containing posts and messages from the requested channels.

This Python script builds a network graph. By default, the file will be located in the output folder. The script also saves a preliminary graph: network.png using the modules matplotlib, networkx, and python-louvain, which implements community detection. You can import the GEFX Graph File using different softwares, including Gephi.

• --data-path Path were data is located. Will use ./output/data if not given.

If a specific directory was not provided in main.py, run:

python channels-to-network.py

If you provided a specific directory using the option --output in main.py, run:

python channels-to-network.py --data-path ./path/to/chosen/directory