Your Team Copies Information Page by Page
Staff repeatedly open websites, collect details and organize them in a spreadsheet.
We can assess whether a custom collection script would make that process more practical.
Available worldwideAvailable for Projects · Worldwide
Web Scraping & Data Solutions
Turn Website Information Into Data You Can Use
When useful information is spread across pages, collecting it manually can become slow and difficult to maintain.
I’m Mohid Imran, a developer working with Python web scraping and automated data collection. I build scoped solutions around agreed sources, required fields and the way you need to use the results.
Custom Python scrapers · Website data extraction · Data preparation · Repeat collection
The Information Changes Regularly
A one-time dataset becomes outdated, but manually checking every record takes too much time.
We can define the required collection frequency and assess how updates should be handled.
Different Sources Use Different Formats
The same type of information appears under different labels or structures, making comparison difficult.
A data-preparation step can organize agreed fields into a more consistent format.
Your Current Scraper Stops Working
A website change affects the extraction, records are missing or the output no longer matches what your workflow needs.
I can review the script and source behavior before confirming the work.
You Have Collected Data but Cannot Use It Easily
The output contains inconsistent fields, duplicates or values that need preparation before they can be imported elsewhere.
We can define the checks and transformations needed for the intended use.
/ Data Services
Choose the Work Your Project Needs
Custom Web Scraper Development
A Python script developed around agreed websites, page types and required information.
Suitable for: A collection requirement that available exports or existing tools do not adequately support.
Website Data Extraction
Collect defined fields from reviewed sources and deliver them in an agreed structure.
Suitable for: A one-time dataset with clear source and field requirements.
Repeat Data Collection
Develop a collection process that can run again as information changes.
Suitable for: Recurring research, catalog checks or other requirements where the dataset needs updating.
Data Cleaning & Preparation
Apply agreed rules to organize extracted information, handle duplicates and prepare output for its intended use.
Suitable for: Data that needs a more consistent structure before reporting or import.
Existing Scraper Review
Investigate a script that produces errors, incomplete records or an unsuitable output.
Suitable for: An existing collection workflow that needs repair or further development.
/ Project Scope
Define the Dataset Before Building the Scraper
A useful collection brief explains more than which website to visit.
We agree on the information required and how it will be used. That helps identify which pages matter and what the output should contain.
Planning covers:
- The website sources and relevant page types.
- The fields required for each record.
- How records should be identified.
- Whether collection is one-time or recurring.
- What should happen when a value is missing.
- The required output format.
- The checks used to assess the result.
These details make the work easier to estimate and the output easier to review.
/ Source Review
Check Whether the Proposed Collection Is Practical
Websites differ in how information is presented and accessed.
Before confirming the implementation, I review representative pages and the available collection options. If a suitable export or API already provides the required information, that may be a better starting point.
The review also establishes access requirements and relevant source restrictions. Collection methods and any required permissions are agreed before development.
/ Data Structure
Organize the Output Around Its Next Use
The dataset should fit the task it supports.
A product-data import, research spreadsheet and application feed may require different fields and structures. We define that output before building the collection process.
Depending on the scope, preparation can include:
Field Mapping
Connect source information with the agreed output columns or properties.
Consistent Formatting
Apply defined rules for text, dates, units or other relevant values.
Duplicate Handling
Identify repeated records using an agreed matching rule.
Missing-Value Handling
Distinguish unavailable information from values that genuinely represent zero or an empty field.
Record Validation
Check required fields and representative records against the source.
The output reflects the agreed rules. Missing source information is not filled with invented values.
/ Recurring Collection
Plan for What Changes Between Runs
A recurring workflow needs decisions about updates.
We define whether each run produces a fresh dataset, updates existing records or captures changes. We also consider how to identify records and recognize information that is no longer available.
Scheduling, hosting and the response to unsuccessful runs are included only where agreed.
Website changes can affect extraction, so recurring collection also needs a maintenance arrangement.
/ Quality Checks
Review the Data Alongside the Source
A script completing successfully does not establish that every record is correct.
Testing follows the agreed dataset and can include:
- Comparing representative output records with source pages.
- Checking required fields.
- Reviewing duplicate handling.
- Examining missing or unexpected values.
- Confirming the output structure.
- Reviewing coverage against the agreed sources.
Any limits in source access or collection coverage are recorded with the findings.
/ Delivery
Choose a Format Your Team Can Work With
The delivery format is agreed around your next step.
This may be a structured file for review, an import-ready dataset or a connection with another application, subject to the project requirements.
Common format requirements can include CSV, Excel or JSON. API or database delivery needs its own defined implementation scope.
If you need the script as well as the output, ownership, dependencies and handover requirements are agreed before development.
/ Existing Scrapers
Investigate the Failure Before Rebuilding
A scraper may fail because the source structure changed, a field moved or the original assumptions no longer hold.
I review the available code, examples of the problem and the intended output. The scope may involve a focused repair, updated extraction rules or a wider change.
Where the source no longer supports a reliable collection method, that limitation needs to be established before further work.
/ Relevant Experience
Python Development for Automated Data Collection
My experience includes developing Python scripts for web scraping and automated data collection during research and development work.
My broader background includes Django REST APIs and custom web development. That helps when collected information needs to support another application or business workflow.
We can review your sources and identify what needs to be demonstrated before committing to the full dataset.
/ Deliverables
Agree on the Sources, Fields and Output
Depending on the engagement, deliverables can include:
- A defined source and field specification.
- A source-feasibility assessment.
- An agreed collection script or workflow.
- A sample dataset for review.
- Selected cleaning and validation rules.
- The agreed final output.
- Setup and handover documentation.
- Known limitations and maintenance requirements.
Hosting, recurring runs, third-party costs, integrations and ongoing maintenance are included only where arranged.
/ Working Process
From Source Review to Data Delivery
Define the Requirement
You share the sources, required fields and intended use.
Review Feasibility
I inspect representative pages and assess the collection approach.
Agree on a Sample
We confirm a small representative output and the rules it should follow.
Develop and Collect
I implement the agreed workflow and process the defined scope.
Validate the Results
We review representative records, structure and relevant coverage checks.
Deliver and Hand Over
You receive the agreed output and documentation. Recurring collection or maintenance can be arranged separately.
/ Related Services
Does the Data Need to Support a Wider Workflow?
AI & Workflow Automation
For processes that move, prepare or act on information across business systems.
Custom Web Application Development
For an application that lets users manage and work with the collected information.
Dashboards, Portals & Internal Tools
For interfaces that present the relevant data and support operational tasks.
Shopify App Development & Integrations
For defined connections and application functionality within a Shopify project.
/ Frequently Asked Questions
Frequently Asked Questions
Can you collect data from any website?
That cannot be confirmed without reviewing the source. Access, structure, restrictions and the required information affect feasibility.
Can you collect information from several websites?
Yes, where the reviewed sources support the agreed approach. Each source may require separate extraction and field-mapping work.
Can the collection run regularly?
Recurring runs can be scoped. We define the schedule, hosting, update behavior and maintenance responsibilities.
Can you clean data after extracting it?
Yes. Cleaning rules need to be agreed, including formatting, duplicates and missing-value handling.
Will every field always contain a value?
Not necessarily. The source may omit information or present it inconsistently. We define how missing values should appear in the output.
Can you repair a scraper another developer built?
Potentially. I first review the available code, source behavior and intended output before confirming the work.
Can I review a sample before the full collection?
A representative sample can be included in the engagement to confirm the fields and structure before processing the wider scope.
Can you deliver data for import into another system?
That can be assessed. The receiving system’s field requirements and import rules need to be included in the specification.
What happens if the website changes later?
The extraction may need updating. Ongoing maintenance is agreed separately, including responsibility for investigating unsuccessful runs.
What determines the price and timeline?
The number and complexity of sources, required fields, collection volume, preparation rules and delivery requirements affect the estimate.
/ Next
Show Me the Information You Need to Collect
Send example source pages, list the required fields and explain how you plan to use the results.
We can assess the sources and define a practical collection and delivery scope.