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TikTok took years and thousands of engineers. You’ve got a week and Python.
And yet… you can still build a real short video platform, fast uploads, instant playback, automatic thumbnails, adaptive delivery, without touching a media server.
Because video infrastructure has changed.
FastPix gives you the same backend primitives big platforms use, but wrapped in clean SDKs you can drop into your Python project. Upload APIs that handle chunking and retries. Processing that just works. HLS playback out of the box. And all of it scales when your app goes viral.
In this guide, we’ll show you how to build the core of a short video platform using the FastPix Python SDK, the kind that looks like it took a year, but only took a week.
Let’s go.
Building a short video app isn’t just about uploading files. It’s about solving hard infrastructure problems, uploads that don’t fail, videos that process fast, and playback that just works across all devices and network conditions.
If you try to build that from scratch, you’ll quickly run into…
They abstract the messy parts, giving you clean, ready-to-use functions that map to complex video workflows behind the scenes.
FastPix offers SDKs in multiple languages, including Python, Node.js, Go, PHP, and more, so you can use it in whatever stack you’re working with.
But for this guide, we’ll focus on Python.
What you’ll need before we start
Before we jump into the code, make sure you’ve got a few things ready:
Once you’ve got that, we’re good to go.
To get started, install the FastPix Python SDK:
pip install fastpix
Then import the client and authenticate using your API credentials:
from fastpix import FastPixClient
client = FastPixClient(
api_key="YOUR_API_KEY",
api_secret="YOUR_API_SECRET",
region="us-west" # Replace with your FastPix region
)
Once the client is initialized, you're ready to upload and process videos with just a few lines of code.
Let’s put it to work.
Short video platforms are all about user-generated clips, usually 15 to 60 seconds long. On the backend, your jobis to handle those uploads reliably and attach the right metadata (like who uploaded it and what it’s about).
Here’s a simple function to upload a video using the FastPix Python SDK:
def upload_video(file_path, user_id, title=""):
video = client.videos.upload(
file_path=file_path,
metadata={"user_id": user_id, "title": title}
)
print(f"Video uploaded with ID: {video.id}")
return video.id
You can now call:
upload_video("clip.mp4", "user_456", "My Travel Reel")
This uploads the video and stores user-specific metadata alongside it. Once uploaded, FastPix will automatically handle processing and transcoding in the background.
Once a video is uploaded, it needs to be processed before playback. That usually means two things:
With FastPix, you can kick off both steps in one go using a background job:
def process_video(video_id):
job = client.jobs.create(
operation="transcode_thumbnail",
input={"video_id": video_id},
output={
"formats": ["mp4", "webm"],
"thumbnail_times": [1, 3, 5]
}
)
client.jobs.wait_until_complete(job.id)
print(f"Processing complete for video ID: {video_id}")
This triggers a processing pipeline that converts the video into multiple formats and captures thumbnails at the 1st, 3rd, and 5th second marks.
Once the job completes, your video is fully prepped and ready to stream.
Once the video has been processed, you’ll want to fetch the output, like the final playback URLs and thumbnail images, and store them in your database. This will power your video feed and playback screens.
Here’s how to retrieve the assets for a given video:
def get_video_assets(video_id):
video = client.videos.get(video_id)
jobs = client.jobs.list(video_id=video_id)
assets = {"formats": [], "thumbnails": []}
for job in jobs:
if job.status == "completed":
assets["formats"].extend(job.output.get("urls", []))
assets["thumbnails"].extend(job.output.get("thumbnails", []))
return {
"id": video.id,
"title": video.metadata.get("title"),
"formats": assets["formats"],
"thumbnails": assets["thumbnails"]
}
This will return all the processed formats and thumbnails for that video. You can store these in your database or mock it in memory for now — and use them to power your video feed, preview tiles, or player URLs.
Let’s bring everything together.
Using Flask, you can wire up a lightweight API that handles uploads and serves a paginated feed, just like the backend for a short video app. Here’s a minimal example:
from flask import Flask, request, jsonify
import os
app = Flask(__name__)
VIDEO_FEED = []
@app.route("/upload", methods=["POST"])
def upload():
file = request.files["file"]
title = request.form.get("title", "")
user_id = request.form.get("user_id")
file_path = f"/tmp/{file.filename}"
file.save(file_path)
video_id = upload_video(file_path, user_id, title)
process_video(video_id)
video_data = get_video_assets(video_id)
VIDEO_FEED.append(video_data)
return jsonify(video_data), 201
@app.route("/feed", methods=["GET"])
def feed():
page = int(request.args.get("page", 1))
per_page = 10
start = (page - 1) * per_page
end = start + per_page
return jsonify(VIDEO_FEED[start:end])
if __name__ == "__main__":
app.run(debug=True, port=5000)
This gives you two working routes:
You now have the foundation of a backend for a TikTok-style video app, all powered by FastPix and Python.
You’ve got a working backend. Uploads work.Processing runs. Playback is smooth.
But if you’re planning to launch, even to a small beta, this needs to evolve from “cool Flask demo” to “real, battle-tested infrastructure.”
Here’s what that looks like:
Security isn’t optional
When users upload content, you're on the hook for what happens next. Protect your platform before it scales:
Build for real-world scale
The difference between a prototype and a product? Whether it falls over when 50users hit it at once.
Frontend is where it all comes together
Your backend only matters if playback feels instant and smooth.
The FastPix Python SDK gives you everything you need to build and scale a video platform, upload, transcode, stream, generate thumbnails, and serve adaptive playback, all from your backend, with clean, production-ready APIs. No custom pipelines. No DevOps overhead. Just one SDK built for developers who want to move fast.
FastPix offers SDKs in Node.js, Go, PHP, and C#, so you can build in the language that fits your stack.
Sign up to get $25 in free credits. Have questions? Our team’s always happy to help.
Yes, the FastPix Python SDK is ideal for building TikTok-style or Reels-like applications. It abstracts away the hardest parts, video uploads, encoding, thumbnail generation, and adaptive playback, so you can focus on user flows, content feeds, and interactivity without worrying about video infrastructure.
The SDK supports direct file uploads and cloud imports, including large files via chunked transfers. Once uploaded, FastPix automatically encodes your videos into adaptive formats like HLS and MP4, generates thumbnails, and prepares everything for instant playback, no media pipeline setup required on your end.
No, you don’t need to build a custom video player. FastPix provides playback URLs that work across browsers and devices, and also offers SDKs for mobile and web. This ensures smooth playback with adaptive bitrate streaming, optimized for network conditions and device types.
Yes, FastPix offers built-in playback analytics that you can access directly through the Python SDK. You’ll be able to track views, watch time, playback quality, errors, and engagement data, broken down by device, location, or network, making it easy to optimize content performance.
Absolutely. The SDK is built to handle production workloads, from startups to enterprise use cases. It supports async and sync workflows, integrates with any Python-based backend, and provides full access to FastPix’s APIs for uploading, tagging, transforming, and monitoring video—all with developer-friendly abstractions.
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