DEV Community: Rabia42

Building with HikerAPI: A Practical Alternative to Instagram Scraping

Rabia42 — Thu, 03 Sep 2026 18:36:57 +0000

When I started working on , I needed a reliable way to retrieve Instagram data programmatically.

My first thought was to interact with Instagram directly using .

That approach can work for experimentation, but as soon as the application starts making repeated requests, things become more complicated.

Rate limits, blocks, authentication/session handling, changing responses, and maintenance can quickly become part of the project itself.

Eventually, I decided to move the Instagram data layer to HikerAPI.

HikerAPI provides a REST API for accessing public Instagram data, including profiles, posts, reels, stories, followers, comments, hashtags, locations, and other data through API endpoints.

The Use Case

The problem I was trying to solve was:

«»

For example, my workflow needed to:

Start with an Instagram username.
Retrieve the user's profile information.
Get the user's media.
Process the returned data inside my application.

The important part was that I didn't want the Instagram request layer to become the main thing I had to maintain.

I wanted something closer to a normal API integration.

Why Scraping Became Difficult

Direct scraping sounds simple:

import requests

url = "https://www.instagram.com//"
response = requests.get(url)

print(response.status_code)

The problem is that a production workflow isn't just about making one successful request.

You also have to think about things like:

Rate limits
Blocks
Request failures
Session management
Authentication
Changes to Instagram's responses
Parsing HTML or internal responses
Retries
Proxies and infrastructure
Maintaining the scraper when things change

For , this created more engineering overhead than I wanted.

The question became less about "Can I scrape this?" and more about:

"Do I want to maintain an Instagram scraping system?"

My answer was no.

What About instagrapi?

I also considered "instagrapi".

It's a useful option when you want Python-level control and are comfortable managing the Instagram client yourself.

For example, a typical workflow can look conceptually like:

from instagrapi import Client

cl = Client()
cl.login("USERNAME", "PASSWORD")

user = cl.user_info_by_username("")
medias = cl.user_medias(user.pk, amount=10)

print(medias)

The advantage is control.

Your application communicates through a Python client, and you can build your own logic around it.

The downside is that you also inherit more of the operational complexity.

You may need to deal with sessions, authentication, rate limiting, account health, retries, and changes in Instagram behavior.

For some projects, that tradeoff is completely reasonable.

For mine, I preferred moving that complexity behind an API.

Moving to a REST API

This is where HikerAPI fit my workflow better.

Instead of having my Python application communicate with Instagram directly, I could make normal HTTP requests to an API.

The authentication model is simple: the API key is sent through the "x-access-key" header.

The basic flow becomes:

My Python application
↓
HikerAPI REST endpoint
↓
JSON response
↓
My application processes the data

That is a much simpler boundary for my application.

Making the First Request

The request itself is straightforward.

Here is the complete example:

import requests

headers = {"x-access-key": "YOUR_KEY"}

user = requests.get(
"https://api.hikerapi.com/v2/user/by/username?username=nike",
headers=headers
).json()

resp = requests.get(
"https://api.hikerapi.com/v2/user/medias",
params={"user_id": user["pk"]},
headers=headers
)

print(resp.json())

The first request finds the user by username.

The response contains the user's "pk", which I can then pass to the media endpoint.

The second request retrieves the user's media.

The nice part is that the application doesn't need to understand Instagram's internal page structure. It just needs to understand the API response.

Keeping the API Key Safe

One thing I wouldn't recommend is hardcoding the real API key into production code.

Instead, I would keep it in an environment variable:

import os
import requests

API_KEY = os.environ["HIKERAPI_KEY"]

headers = {
"x-access-key": API_KEY
}

Then set the key outside the source code.

For example:

export HIKERAPI_KEY="your-real-key"

This makes it much easier to keep secrets out of Git repositories and shared code.

Handling API Errors

One mistake I've learned to avoid with API integrations is assuming every request will succeed.

Instead of immediately calling ".json()", I can inspect the response:

import requests

headers = {"x-access-key": "YOUR_KEY"}

response = requests.get(
"https://api.hikerapi.com/v2/user/by/username",
params={"username": "nike"},
headers=headers,
timeout=30
)

if response.ok:
user = response.json()
print(user)
else:
print("Request failed:", response.status_code)
print(response.text)

This gives my application a chance to handle failures gracefully.

For a real application, I would also consider retry logic, logging, timeouts, and validation of the returned JSON.

Why I Preferred This Architecture

The biggest benefit wasn't that the Python code was shorter.

It was that I could separate responsibilities.

My application is responsible for:

Business logic
Data processing
Storage
Authentication for my own users
Scheduling
Analytics

The API handles the Instagram-specific communication layer.

That separation makes the architecture easier for me to reason about.

The Cost

Of course, a hosted API isn't free.

HikerAPI uses pay-per-request pricing. Its current pricing starts at $0.001 per request on the Standard tier, with higher-volume tiers offering lower per-request rates, and new accounts receive 100 free requests for testing.

That means I need to consider request volume.

If my application makes 100 requests, the cost is very different from an application making millions of requests.

So before choosing a hosted API, I would calculate:

Expected requests per day
×
Cost per request
×

Days per month

Estimated monthly API cost

For small projects and prototypes, the cost can be easier to justify because I'm also saving development and maintenance time.

For very large workloads, I'd definitely benchmark the economics against running my own infrastructure.

Hosted API vs Scraping

There isn't one answer that's best for everyone.

Direct scraping

Pros:

More control
No third-party API markup
Potentially lower direct API costs
Full control over infrastructure

Cons:

More maintenance
Rate-limit handling
Blocks
Proxy/infrastructure considerations
Parsing and response changes
More Instagram-specific code

instagrapi

Pros:

Python-friendly
More direct control
Useful for developers who want to manage the client themselves
Can be integrated deeply into a Python application

Cons:

You still own much of the operational complexity
Sessions and authentication need attention
Instagram changes can require maintenance
Scaling requires more infrastructure planning

HikerAPI

Pros:

Simple REST interface
API-key authentication
JSON responses
Many Instagram-specific endpoints
Pay-per-request model
100 free requests for testing

Cons:

Adds a third-party dependency
Costs money once usage exceeds the free requests
Less control over the underlying Instagram communication
API availability and endpoint changes become another dependency to monitor

For , the reduction in maintenance was worth the tradeoff.

What I Would Do Before Building Around It

I wouldn't immediately rewrite an entire application around any API.

I'd test the exact endpoints I need first.

For example:

import requests

headers = {"x-access-key": "YOUR_KEY"}

response = requests.get(
"https://api.hikerapi.com/v2/user/by/username",
params={"username": "nike"},
headers=headers,
timeout=30
)

print(response.status_code)
print(response.json())

Then I'd test:

Expected users
Invalid usernames
Large accounts
Different response cases
API failures
Request volume
Response speed
Data completeness

The 100 free requests make this initial evaluation relatively easy.

The Biggest Lesson

The biggest lesson I took from this wasn't simply "use an API instead of scraping."

It was that engineering time is also a cost.

I can spend days building and maintaining infrastructure around .

Or I can pay for a service that gives my application a cleaner interface and spend that engineering time on the actual product.

Neither option is universally better.

If you have low volume, need maximum control, or already have a stable scraping infrastructure, managing the stack yourself may make sense.

If you want a simpler integration and don't want Instagram-specific infrastructure to become a major part of your application, a hosted API can be a much more attractive option.

For me, HikerAPI gave me a straightforward REST layer between my application and Instagram data.

And sometimes, simplifying the architecture is more valuable than having complete control over every layer.

python #api #webscraping

Lessons Learned: Dealing With Instagram Rate Limits and Blocks

Rabia42 — Thu, 03 Sep 2026 18:31:05 +0000

When I started building , one of the first approaches I tried was interacting with Instagram directly.

It seemed straightforward: make requests, collect the public data I needed, process it, and move on.

It worked at first.

Then the rate limits and blocks started becoming a problem.

What Went Wrong

My initial approach looked roughly like this:

import requests

response = requests.get(
"https://www.instagram.com//",
headers={"User-Agent": "Mozilla/5.0"}
)

print(response.status_code)

For , this approach became unreliable.

Requests that worked previously could start returning errors, responses could change, and repeated requests made the workflow increasingly difficult to maintain.

The biggest lesson for me was:

Getting a request to work once is very different from building a reliable data pipeline.

I could keep adding delays, retries, different headers, and other workarounds, but that also meant more code to maintain and more things that could break.

The Problem With Handling Everything Myself

I considered several ways to deal with the situation:

Adding delays between requests
Implementing retry logic
Managing sessions
Handling different response formats
Trying to reduce request frequency

Some of these techniques helped temporarily, but they didn't solve the underlying problem.

I didn't really want my application to become a project for managing Instagram's request behavior.

I wanted it to focus on .

That was the point where I started looking at hosted APIs instead.

Why I Moved to HikerAPI

I eventually moved the Instagram data requests to HikerAPI.

"HikerAPI" (https://reference-url-citation.invalid/1)

The main attraction was simplicity.

Instead of my application having to handle the Instagram communication directly, I could make a normal HTTP request and work with the JSON response.

HikerAPI provides REST endpoints for things such as user profiles, posts, reels, stories, followers, following, hashtags, and locations. It also uses API-key authentication rather than requiring me to build my own Instagram session-management layer.

The pricing is pay-per-request. The current pricing page lists plans starting at $0.60 per 1,000 requests, while the popular Standard tier is $1 per 1,000 requests, and new accounts receive 100 free requests.

For my use case, predictable per-request costs were easier to reason about than spending time maintaining a custom scraping setup.

A Simple Request

One thing I liked was that I could use a standard Python HTTP client.

For example:

import requests

headers = {"x-access-key": "YOUR_KEY"}

user = requests.get(
"https://api.hikerapi.com/v2/user/by/username?username=nasa",
headers=headers
).json()

r = requests.get(
"https://api.hikerapi.com/v2/user/followers",
params={"user_id": user["pk"]},
headers=headers
)

print(r.json())

There is no special networking layer here.

It's just an HTTP request, an API key, and JSON.

That makes it easy to integrate into an existing Python project.

What Changed in My Architecture

Before:

My application
↓
Instagram
↓
Rate limits / blocks / changing behavior
↓
My application handles failures

After:

My application
↓
HikerAPI REST API
↓
JSON response
↓
My application

This doesn't magically eliminate every possible failure. An external API is still another dependency, and its availability, endpoint behavior, pricing, and limits need to be considered.

But it moved a lot of Instagram-specific complexity away from my application.

The Tradeoffs

Moving to a hosted API isn't automatically the right choice for every project.

There are some clear tradeoffs.

You Pay for Usage

Direct requests might appear cheaper because there isn't an API bill.

With a hosted API, every request can have a cost.

For a small project, this may be negligible. At large scale, you need to calculate the cost carefully.

You Add a Dependency

Your application now depends on another service.

If the API has an outage or an endpoint changes, your application needs to handle it.

You Have Less Control

With your own implementation, you control the entire request and processing pipeline.

With a hosted API, part of that infrastructure is outside your control.

But You Save Development Time

This was the biggest benefit for me.

Instead of spending more time dealing with , I could spend that time working on .

For me, that tradeoff made sense.

What I Would Do Differently

If I were starting again, I would evaluate the API layer much earlier.

I'd first define:

What Instagram data I actually need
How many requests I expect to make
Whether the data needs to be real-time
How much failure/retry handling my application needs
What the monthly API cost would look like
Whether the data source and use case comply with the relevant platform rules

Then I'd test the API with a small number of requests before designing the entire application around it.

The 100 free requests available with HikerAPI are useful for this kind of initial evaluation.

Final Takeaway

The main lesson wasn't simply "use HikerAPI."

It was that reliability has a cost, and developer time is part of that cost.

Trying to handle every Instagram-specific problem myself initially seemed like the cheaper option.

Eventually, I realized that maintaining was taking attention away from the actual application.

Moving that responsibility behind a hosted REST API gave me a much simpler interface:

Send a request → receive JSON → build the feature.

For , that was a much better tradeoff.

DEV Community: Rabia42

Building with HikerAPI: A Practical Alternative to Instagram Scraping

Days per month

python #api #webscraping

Lessons Learned: Dealing With Instagram Rate Limits and Blocks

python #webscraping #api