Need a Python developer for analyzing the movement of funds in the TRON network (USDT TRC-20)

Good day, I am engaged in the development of bots and automation of betting on Binance, I would be happy to try to do a project for you)

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I can implement your task for tracking the movement of TRON address funds. I can implement various types of representation, whether as a graph with edges or a table. I develop in Python. As a result, you will receive a GitHub repository, clean structured code with documentation, and a demonstration of the work.

Optionally, I can implement a web interface, a Telegram bot, or a desktop application. The graph can be networkx or neo4j - at your choice.

Write to me - I will create a fast and convenient program with a pleasant interface.

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Hello! It's an interesting task, but my experience points to some critical moments and potential problems:

In TronGrid / Tronscan, there are strict limits on the limit and the sum of start+limit, so the full history of TRC-20 will need to be pulled with paging and cached, otherwise the tool will stop working on large addresses.

The API returns not only USDT, so filtering by contract TR7NHqjeKQxGTCi8q8ZY4pL8otSzgjLj6t is needed, as well as by transaction status (confirmed, without internal error), otherwise the graph will be cluttered.

OKLink has AML-oriented endpoints with additional information (usdAmount, direction, risk-tags), but they often require an API key and have a rate limit, so throttling and local caching of address metadata need to be considered.

Regarding the graphs:
… 1-3 hops are BFS/DFS from the starting address with a depth limit, while separately controlling the number of vertices, because exchange nodes can provide thousands of addresses in one hop and expect memory overload.

It makes sense to implement two limits: maximum depth (1-3) + maximum number of unique addresses/transactions, with the option --truncate, so that the tool does not crash but marks the trimmed branches.

To determine the main flows, it is better not just to count the sum across the edges, but to apply weights and aggregation by paths: the sum of USDT across simple paths of length less than or equal to 3, grouped by the final recipient.

There are many nuances that we can discuss.

Best regards,
Georgiy,
Senior Python Developer

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I will create a tool for analyzing USDT TRC-20 on TRON:
• Obtaining all transactions for an address via API (TronGrid/OKLink/TronScan)
• Building a graph of movement for 1–3 "jumps" (addresses → transactions)
• Identifying main flows, key nodes, and final recipients
• Supporting public tags (exchanges/services) in the report
• Exporting results to JSON/CSV (graph, main flows, top recipients)

Stack: Python 3, requests/httpx, networkx (optional neo4j), README + example run on a test address.

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Good day. I am ready to take on this project. I have sufficient experience for developing such a tool. I am currently practicing in developing exactly such projects as this one. It would be interesting to work and improve my skills. Write to me if I suit you, we will discuss all the details. We will also agree on the price, unfortunately, it cannot be set lower here.

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Hello!
I have experience in developing analytical tools for blockchains (Ethereum, Tron, BSC).
I will implement a complete parser for USDT TRC-20 transactions for you, with graph construction (1-3 "hops"), detection of key addresses, exchange tags, and output in JSON/CSV.

The output will be working code + a short instruction + an example on a test address.
The budget for this type of work is from $500.

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Hello! I am doing a similar thing, but for altcoins on the Ethereum network. Doing almost the same for USDT TRC-20 will not be a problem. The Tronscan API is almost identical to the Etherscan API that I use, so I would gladly take your project to work on.

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Good day! I am ready to complete this project. Great experience in developing various applications.

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Good day, Kateryna.
I have carefully reviewed your task. I have extensive experience in process automation.
Regarding your project:
I have a ready template version that requires refinement by 7-9%:

- Implemented components: integration with API, graph construction, speed limits
- Remaining: recursive traversal for 1-3 hops, identification of key addresses, integration of exchange tags, export to json/csv, and documentation

Timeline: 2-4 days
… I am ready to start immediately after agreeing on the details. Write to me, and we will discuss all the nuances!

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Good day
I can implement it in Python + NetworkX for processing + NebulaDB
I have already implemented something similar for the Ethereum network.
The only point is that, considering the limits of third-party API scanners, for wallets with a large number of transactions, data collection may take a long time. Therefore, I would recommend separately implementing a constant collection of USDT transactions into a database, for example, Postgres, so that you can retrieve data from there later. This will significantly speed up queries and processing.
It is also desirable to see a sample format that you want to receive as output. That is, how you want to see the main streams.

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Hello.

I see you need a clear tool that shows the movement of USDT TRC-20 for any TRON address: from a raw list of transactions to a visual graph with 1-3 "steps" showing the main flows and final recipients. Additionally, it is important to immediately see exchanges and services based on public tags and export everything in JSON/CSV for further analysis.

I do similar things in Python: working with blockchain APIs, collecting transactions, normalizing data, building graphs (networkx/Neo4j), and analytical exports. I can neatly wrap TronGrid/Tronscan/OKLink, add a graph-building layer, and a module that highlights key addresses and top recipients. I can start implementation right after agreeing on the details.

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Hello! I can do your project. I have experience. Write to me, and we will agree.

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Good day, I can create a tool according to your specifications: obtaining USDT TRC-20 transactions via API, building a graph with 1-3 hops, identifying main flows and top addresses, plus output in JSON/CSV.
Feel free to contact me, I would be happy to collaborate.

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Hello! 👋

I can develop a tool for analyzing the movement of USDT TRC-20 in the TRON network with graph construction and exporting results in JSON/CSV.

What I will implement:

1. Obtaining all USDT TRC-20 transactions for a given address
– via the TronGrid / Tronscan / OKLink API (we will agree on the optimal option).

… 2. Constructing a graph of fund movement (1–3 "hops" from the address)
– nodes = addresses, edges = transactions;
– ability to customize the depth of analysis.

3. Identifying main directions of movement
– aggregation of flows;
– highlighting key addresses and final recipients.

4. Supporting public tags
– tagging exchanges / services / known addresses (where public tags exist);
– displaying tags in the results.

5. Exporting results
– JSON/CSV with:

graph structure,

main flows,

list of top recipients.

Technologies:

Python 3.x, requests / httpx;

networkx or custom graph model (if needed – extension for Neo4j);
separate README with instructions for running;
example of operation on a test TRON address.

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Here and there, masters of all trades, a team of specialists is ready to fulfill your wishes, write in private messages, discounts are available for new clients.

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Hello! 👋
I am ready to develop a full-fledged tool for analyzing the movement of funds in the TRON blockchain for USDT TRC-20 — with graph construction, key address search, and data export.

🔥 Why I am perfectly suited for the task

I have already implemented a similar 1-to-1 service for analyzing fund flows in Solana, and I am currently leading a large project for monitoring transactions in BSC (BNB Chain) — with webhooks, token analysis, tracking millions of events, and optimizing graph structures.
📌 What I will implement within the project
1. Obtaining all USDT TRC-20 transactions

… API support:

TronGrid

Tronscan

OKLink (more structured data)

With normalization, pagination, and protection against omissions.

2. Constructing a graph of fund movement (1–3 "hops")

I will use:

networkx or a custom graph (faster on large data)

Optimized storage of nodes and edges

Filtering of unique flows

Merging transactions into aggregated connections

3. Analyzing movement directions

Determining:

key nodes (in/out degree, centrality)

main flows (top directions)

final recipients after several “hops”

suspicious clusters

4. Supporting public tags

Automatic identification of exchanges/services:

Binance

OKX

Huobi

KuCoin

Bitget

TronStake / staking

OTC pools

Tags are added to JSON/CSV and the graph.

5. Exporting results

Formats:

JSON — complete graph, nodes, edges, metadata

CSV — main flows, list of recipients, transaction table

📂 You will receive as a result

Complete working code (repository or archive)

README with instructions for launching

Example analysis on a test TRON address

Structured output of results in JSON and CSV

Ability to scale for greater search depths

🧭 I can additionally implement

REST API for external requests

Web interface for graph visualization (D3.js / Cytoscape)

Automatic search for “phantom” routes

Deduplication of exchange warehouse addresses

Dynamic real-time analysis (as in my BSC project)

I am ready to start immediately.

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