Freelancers using TradingView in IndiaFreelancers using TradingView in India
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Raj Kumar's avatar
Raj Kumar
Chennai, India
Algo Trading Developer - Pine Script,MQL5 &Python Automation
43
Followers
Algo Trading Developer - Pine Script,MQL5 &Python Automation
Cover image for Designed and implemented a robust
Designed and implemented a robust webhook-based trading automation system that connects TradingView signals to real-time trade execution via the Tradovate API. The system is built using Python and handles signal reception, validation, and order execution in a seamless automated pipeline. The architecture ensures low-latency communication, secure data handling, and reliable execution of trades without manual intervention. It processes incoming webhook alerts, applies validation logic, and triggers precise API-based trade execution. Key features include: • Real-time webhook signal processing (TradingView alerts) • Python-based signal receiver and validation engine • Secure and reliable API integration (Tradovate) • Low-latency execution pipeline • Fully automated trade workflow (zero manual input) • Scalable design for multi-strategy integration This solution is ideal for traders and firms looking to automate their strategies using webhook-driven architecture, enabling faster execution, reduced human error, and consistent performance in live trading environments.
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Cover image for Developed a fully automated trading
Developed a fully automated trading system for MetaTrader 5 (MT5) that executes trades based on validated multi-indicator signals. The system integrates TradingView-generated signals with a Python-based processing engine, which evaluates multiple technical conditions before triggering precise trade execution. The Expert Advisor (EA) is designed with advanced trade logic, risk management, and real-time execution capabilities. It ensures consistent performance by removing emotional decision-making and strictly following predefined rules. Key features include: • Automated trade execution on MT5 (buy/sell orders) • Integration with external signal sources (TradingView via webhook) • Multi-indicator validation (RSI, EMA, ADX, Volume, etc.) • Built-in risk management (lot sizing, SL/TP control) • Real-time processing with minimal latency • Fully customizable strategy logic This system enables traders to automate their strategies end-to-end — from signal generation to execution — ensuring speed, accuracy, and consistency in live market conditions.
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Cover image for Engineered a high-performance Python-based trading
Engineered a high-performance Python-based trading signal engine designed to generate precise and reliable trade signals using multi-indicator confluence logic. The system evaluates over 12 technical indicators including RSI, EMA, ADX, Volume, and trend-based conditions to identify strong market opportunities while effectively filtering out noise and false signals. The architecture is built to process real-time market data, validate multiple conditions simultaneously, and trigger only high-probability trade setups. This significantly improves signal accuracy and reduces unnecessary trades. Key capabilities include: • Multi-indicator confluence engine (12+ conditions) • Real-time signal processing and validation • False signal reduction using layered logic • Scalable architecture for integration with trading APIs • Seamless compatibility with automated execution systems (webhooks, APIs) This system can be integrated with platforms like TradingView, Tradovate, or custom trading environments to enable fully automated trading workflows — from signal generation to execution. Designed for traders and firms looking to achieve consistent, rule-based, and emotion-free trading through intelligent automation.
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Cover image for Built a complete end-to-end automated
Built a complete end-to-end automated trading system that captures alerts from TradingView, processes them through a Python-based webhook engine, validates multi-condition logic, and executes trades directly via the Tradovate API — eliminating manual intervention and improving execution speed and accuracy.
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TradingView(4)
Prem Patel's avatar
Prem Patel
proIndia
Make.com Level 5 & Zapier Expert: AI and Ops Automation
10
Followers
Make.com Level 5 & Zapier Expert: AI and Ops Automation
Cover image for How do you get TradingView
How do you get TradingView alerts into Telegram in under 2 seconds, 24/7, without losing or doubling a signal? The pipeline is easy to describe and hard to keep alive. Four traps decide it. The shape: TradingView fires a webhook, Make.com catches it, formats the message the way the channel wants it, and posts it. Capture to post in under 2 seconds, around the clock, no human in the loop. That is the scenario in the image, running for a registered research analyst since 2025. 1. The 3-second window. TradingView gives a webhook receiver about 3 seconds to respond. A slow receiver loses the alert and nothing anywhere tells you. Fix: acknowledge instantly, process afterwards, never inline. 2. Telegram's rate cap. A channel takes roughly 20 messages a minute. One volatile candle across several symbols can fire more than that, and the extras vanish silently. Fix: a per-channel queue that preserves order and releases under the cap. 3. Duplicates. Retries and repeated triggers post the same signal twice unless every alert carries a dedupe key. Two identical entries in a row is how a channel loses trust in one afternoon. Fix: a key built from symbol, signal and bar time, checked before every send. 4. Silent death. The worst failure is the pipeline stopping while you assume it is posting. Fix: every run logged, every failure alerting you on a separate channel within seconds, and a heartbeat so silence itself raises an alarm. One more for Indian channels: if the channel belongs to a SEBI-registered adviser, promotional messages need the registration number leading the message and you need retrievable send records. That is a formatting and logging problem, so the pipeline handles it. Branded alert images instead of plain text are the same pipeline with one extra step: an image engine lays the signal over a base card by URL, so every alert ships as a picture. That build is its own case study on my profile. The full case study is on my profile, and the delivered version (I install it on your Make.com account, with your templates, queue, dedupe, alerting and a send log) is the TradingView product on my services page. Prem Patel, Nex Automations. Make.com Level 5 certified, official Make partner, Zapier Certified Expert.
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Cover image for TradingView alerts to Telegram in under 2 seconds on Make.com
TradingView alerts to Telegram in under 2 seconds on Make.com
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Cover image for Does someone on your team
Does someone on your team lose a day or two building the sales report every week or month? That was the starting point at Mokobara, the premium travel brand. Pulling sales across all their stores, checking returns, reconciling the numbers and emailing each manager took 1 to 2 days every cycle, with 8+ hours of that spent just reconciling. I built them an automation on Make.com (http://Make.com) a few months ago. It has run on its own ever since, weekly and monthly: Make pulls every sales record from BigQuery, 100K to 250K per cycle. That is too many for one request, so it reads them page by page and stitches them back together. It calculates the numbers the team actually uses: net sales per store after returns and discounts, return rates and the change against the last period. It builds a CSV with the full breakdown and a short email summary you can read in 60 seconds. It reads a Google Sheet of store representatives and emails every one of them the report for their own store. The result: the reporting problem is gone. The report went from 1 to 2 days of manual work to fully automatic, and the 8+ hours of reconciliation dropped to zero. Two things I would do the same way again: Calculate "net sales" in the automation, not in the warehouse. The business rule for what counts as a net sale is not what the raw data stores. Send people their slice, not the whole report. One report for everyone gets skimmed by everyone. The figures in the image are placeholders, the real ones stay with the client. What report is your team still building by hand? Tell me where the data lives and I will tell you how I would automate it.
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Cover image for Is your Contra discovery score
Is your Contra discovery score stuck? Mine went from top 45% to top 20% in 13 days, and posting more is not what moved it. And i need real Project On Contra😅 I log my score on every tag with a small script that reads all 48 options on the discovery page, so this is what actually changed between 27 August and 9 September 2026, and what did not. What moved it: Case studies. From 0 passing Contra's quality check to 15. Contra's checklist is short: a custom cover, a clear descriptive title, an engaging description, in-depth content and real media. My first two projects failed it, one on the description and one on the media. Services. From 1 passing service to 9, each with its own cover, a descriptive title, a rate and a real summary. Every tag a service carries gets the lift, so tag the tools you actually used. Profile quality, 66% to 100% after the profile rewrite. Replying to the first inquiry quickly. Response time was blank until then. It now reads 2 hours. The result: Overall top 45% to top 20%. Automation Engineer top 25% to top 10%. Make top 35% to top 20%. What did not move it: the four days after. From 9 to 13 September every tag gained exactly 1 point. Nothing new on the profile, nothing moves. And the three biggest levers on my board are still at zero: earnings, reviews and verified projects. All three come from the same move, one paid project routed through Contra, so that is where my next week goes. One thing if you compare yourself with others: Contra's point scale changed between my runs, so compare your rank band (top X%) rather than the raw points. What moved yours? If yours is stuck, reply with your score and the tag, and I will tell you which lever I would pull first.
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TradingView(2)
Jaskaran Singh's avatar
Jaskaran Singh
Sahibzada Ajit Singh Nagar, India
Full-Stack Developer | APIs, Dashboards & AI-Powered Apps
New to Contra
Full-Stack Developer | APIs, Dashboards & AI-Powered Apps
Cover image for Built an AI trading indicator
Built an AI trading indicator for NSE options traders 🇮🇳
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Cover image for 🚚 Case Study: Built a
🚚 Case Study: Built a live driver-ops platform for a UK logistics company Just shipped a project I'm genuinely proud of a driver mobile app + admin dashboard for EC Logistics, a UK-based logistics operator. The problem: their drivers were tracking shifts, expenses, and delays manually no live visibility for the office, slow expense approvals, and no single source of truth. What we built: 📱 Driver App (iOS + Android, live on both stores) • Start/end shift with live GPS tracking (even in background) • Snap & submit expense receipts and delay evidence on the spot • Real-time chat with the office • Push notifications for approvals and updates 🖥️ Admin Console • Live driver map with route history • Expense approval queue with an AI layer that flags invalid/suspicious receipts automatically • Configurable auto-approval rules by category, time window, and spend limit • Xero integration for accounting sync • Audit logs, broadcast messaging, and per-driver chat • Delay and shift history reporting Stack: mobile app + backend services, real-time location pipeline, AI-assisted receipt review, and a full admin web console. The result: the office now approves expenses in minutes instead of days, gets live visibility into every driver on shift, and has an audit trail for everything. 📲 App Store: https://apps.apple.com/us/app/ecl-driver/id6793643563 I run an agency building production-grade mobile apps, dashboards, and backend systems for logistics, fintech, and SaaS teams. If you need something similar an ops dashboard, a driver/field-worker app, or backend systems that actually hold up in production let's talk. 👉 Hire me on Fiverr: https://www.fiverr.com/s/jyjLeWm (https://www.fiverr.com/s/jyjLeWm)Or message me here on Contra happy to scope your project.
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Cover image for Built my first Web3 desktop
Built my first Web3 desktop trading bot this week and it's running . 🟢 Here's what I actually shipped: → Connected to Ethereum mainnet via RPC using Ethers.js → Reads live wallet balances and token data from the chain → Integrated Uniswap V2/V3 router calling swapExactTokensForTokens() to execute real swaps → Understands gas estimation, transaction signing, and contract ABIs → Wrapped the whole thing in a desktop app using Electron.js This isn't a tutorial follow-along. I went through the actual Ethers.js docs, dug into Uniswap's router contracts, and debugged real on-chain calls until it worked. Next step: add multi-chain support (BSC + Arbitrum) and DCA strategy automation. If you need a Web3 developer who builds things instead of just talking about them I'm available for projects.
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Cover image for AI Outbound Lead Generation
AI Outbound Lead Generation
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TradingView(1)
Mohd Anas Ansari's avatar
Mohd Anas Ansari
Bengaluru, India
AI automation/backend solution provider
New to Contra
AI automation/backend solution provider
Cover image for AlgoTrade Sentinel — Helps users
AlgoTrade Sentinel — Helps users decide whether to buy, sell, or hold company stocks by using various machine learning algorithms. It instantly analyzes and trains on historical data to generate the best possible outcomes and support smarter wealth-building decisions.
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Cover image for Agent Orchestrator
Agent Orchestrator
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Cover image for Estate Vault EstateVault is a
Estate Vault EstateVault is a privacy-first trophy real estate platform for high-value property discovery, verification, and deal execution. The repository contains the full product surface across web, mobile, shared domain packages, a legacy full-stack API, and a newer microservices deployment architecture. The platform is built around one core idea: buyers, sellers, agents, and admins should be able to discover premium assets, complete compliance checks, collaborate in private deal rooms, and move from interest to offer inside a secure, auditable workflow.
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Cover image for Enhance Sales with Voqal: AI Voice Agent + Lead Automation
Voqal- AI voice agent with lead qualification automation.
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TradingView(1)
VISHNU GHOSH's avatar
VISHNU GHOSH
Gurugram, India
Full Stack Developer specializing in Python, Django, FastAPI
New to Contra
Full Stack Developer specializing in Python, Django, FastAPI
Cover image for Algorithmic Trading & Automation Platform A
Algorithmic Trading & Automation Platform A full-stack algorithmic trading platform with strategy management, order and position tracking, portfolio analytics, risk management, broker connectivity, and an admin portal for monitoring trading operations. Role Full Stack Developer
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Cover image for Fintech Payment & Business Management
Fintech Payment & Business Management Platform A full-stack fintech management platform for handling recharge, BBPS, AEPS, DMT, wallet operations, settlements, commissions, KYC, users, roles, API management, audit logs, reports, and transaction workflows. Full Stack Developer
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Cover image for Risk & Case Management System A
Risk & Case Management System A full-stack risk and case management platform designed to manage client cases, field verification, employees, team leads, quality checks, case transfers, reporting, and operational workflows through a centralized admin dashboard. Role- Full Stack Developer
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Cover image for Dynamic Community & Cultural Management
Dynamic Community & Cultural Management Website A fully dynamic community platform with an admin panel for managing events, galleries, family trees, resources, members, donations, and website content. Fully Dynamic Admin Panel content, events, gallery, resources and other modules can be managed without changing the code.
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TradingView(1)
Nandita N's avatar
Nandita N
India
Stock Market & Finance Article Writer
Stock Market & Finance Article Writer
Cover image for Turning Market Movements into Meaningful Insights.
Turning Market Movements into Meaningful Insights.
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Cover image for Creating Compelling Stock Market Articles
Creating Compelling Stock Market Articles
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Cover image for I catch typos, before your readers do.
I catch typos, before your readers do.
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TradingView(2)