1. Convert xls files to db table. For this goal need to create php script, which will do it automatically (if needed) in case if all xls files will be in the same format.
2. Create laravel script with CRUD (create, read, update, delete) and mail operations. It will include list with operations (like to send email, to send emails to all, to send email to selected, select all, etc).
3. Add sparkpost API integration to be able to send emails
4. Create additional features, like email sending schedule, CRUD operation for email templates (like to add new email template, apply it as default, etc.) if needed.
5. Testing and bugfix
Budget: 20000 UAH Deadline: 20 days
Hi. I have experience with sparkpost and some of the functions are completed already.
Lets discuss.
Thanks.
Skype dubok1195
Email [email protected]
Budget: 111 UAH Deadline: 10 days
Здравствуйте я по поводу вашего репоста чем могу помочь
Готов обсудить детали проекта и показать своё портфолио.
я Full Stack Php -разработчик.
Я занимаюсь версткой сайтов (front-end,back-end).
Для вас мои предложения:
- Адаптивная верстку (это когда ваш сайт одинаково и хорошо смотрится на раздных устройствах).
- Пишу валидный и чистый код без ошибок, это помогает поисковым машинам быстрее считывать код сайта, и загружать его быстрее.
- Pixel perfect (сайт выглядит точь в точь как на дизайн-макете).
- Делаю все качественно и в установленные сроки.
Использую знания:
- HTML5,
- CSS3,
-Sass
- Адаптивная, кроссбраузерная верстка,
- JavaScript/jQuery,
- WordPress
- Opencart
-PHP
-Laravel
Vue Js
JAVA
MYSql
Разработка парсеров
буду рад всё с Вами обсудить и сотрудничать
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Budget: 376 UAH Deadline: 1 day
Expert Full Stack Web developer with more than 10 years of expertise.
In review of your requirements, I am confident to provide you top line of support and services for your projects as I have immense expertise with developing from small scale to large complex web applications. I am experienced in PHP/Laravel, API and Database development.
Programming Languages:
-PHP
Frameworks:
-Laravel
Databases:
-MYSQL
Operating Systems:
- Windows, Linux, Mac OSx
Scripting languages:
- Bash, Tcl, Javasqript, JQuery, HTML, CSS
In the case of questions, please, don't hesitate to contact with me. Additionally, I am fluent both in English and Russian.
Regards,
Aghasi.
Budget: 10000 UAH Deadline: 10 days
Hi Jens, I can do it with laravel + laravel-admin technologies
Budget: 40000 RUB Deadline: 30 days
Hi Jens! I'm SM of the company ITResources. Our company has a team of specialized web and mobile app developers with 8+ years of experience. We're interested in your offer and would like to deal with it and cooperate with you.
Best regards,
ITResources team
Budget: 11180 UAH Deadline: 7 days
Hi, Jens
We are team of Laravel devs, want to cooperate with you for this project. Can we see example\structure of xls files?
Budget: 10000 UAH Deadline: 7 days
Hi
I’m ready to realize your tasks at the right time after verification of all details. Operational experience is more than 3d years in the web development
(online stores, web applications , online portals and services, bitcoin exchanges and accounting systems).
Technology stack: (PHP, Laravel, Vue.js, React, JS, HTML, CSS, API).
Budget: 2500 UAH Deadline: 5 days
Hello. I would need an example of the xls file in order to start working. I have 1.5 years of experience working with Laravel. Also please send me more technical details of the project.
Budget: 300 UAH Deadline: 1 day
Hi, Jens. I am a PHP dev with 3 years experience, 2 years as I develop web apps on Laravel. You can find some of my works in my portfolio, or on my personal site https://alanvb.pro.
Send me please technical specifications of the project so I can calculate needed time and price.
Budget: 9000 RUB Deadline: 5 days
Hello. I'm working with Laravel CRUD for the long time, Recently i have moved to new version of laravel 6.
With converting xls to db is clear, I've just looked through sparkpost api and if you hire me i can start from now
My contacts
Telegram: @lazerg
Skype: live:lazerg2
Instagram: instagram.com/lazerg2
my recent works
https://medianar.ru/
http://www.school-id.uz
https://yo-yo.eu/
http://relaxzone.club
There is an active production platform with a catalog and automatic updates of external offers and prices. Stack: — Node.js / TypeScript; — PostgreSQL; — existing price refresh service and cron; — separate ready Python module for validation and selection of offers; — staging and production. It is necessary to make targeted improvements to the existing price refresh pipeline without completely rewriting the backend. MANDATORY SCOPE 1. Integration of the Python module — The Python module remains a separate component; — returns a structured result: offers, selected offer, statuses, and risk flags; — Node.js validates the result and performs a write to the database; — provide for error handling and partial/failed runs; — the legacy pipeline is not turned off until QA is completed. 2. Launch refresh by list Add launch: — by one slug/id; — by the provided list of slug/id. Assume CLI or existing service API. A new user interface is not required. 3. Shadow Mode New results must be recorded separately and not affect production until QA. Shadow fields required: — price; — selected offer ID; — direct URL; — offer status; — risk/QA flags; — checkedAt; — engineVersion. 4. Expanding the existing offers table Add: — source; — external_offer_id; — last_seen_at; — last_checked_at; — engine_version; — risk flags or storage in existing JSON; — unique constraint to protect against duplicates. It is not required to create a new parallel offer system if the existing table can be safely expanded. 5. UPSERT, STALE, and DB transaction Replace the current DELETE → CREATE scheme: — UPSERT existing and new offers; — offers missing in the full successful snapshot are translated to STALE; — in case of API error, partial result, or incomplete snapshot, active offers should not become STALE; — updating offers, selected offer metadata, and shadow fields for one model is performed within one DB transaction; — in case of an error, a full rollback is performed. 6. Canonical-safe refresh Price refresh should not change: — brand; — reference; — model; — collection; — name/title; — slug; — descriptions; — images; — SEO fields. Only offer, price, and shadow data are updated. 7. Preserving current cron logic Preserve: — existing cron; — rolling batches; — cooldown; — checking PRICE_REFRESH_MIN_DAYS before calling the external API; — legacy production pipeline until Shadow QA is completed. 8. Audit output One option is sufficient: — shadow columns in the existing admin table; or — CSV export. Minimum data: — model/reference; — production price; — shadow price; — delta; — production/shadow URL; — status; — risk flags; — checkedAt; — engineVersion. A new complex dashboard is not required. 9. Staging and QA — DB migrations; — staging deployment; — smoke test on 5 provided models; — then Shadow Mode on approximately 50 models; — fixing technical errors identified during these runs; — brief documentation of the Python → Node.js contract and rollback procedure. OPTIONALLY ASSESS SEPARATELY Simple technical promotion without a new UI: — promotion of one model by slug; — promotion of a list of slugs; — transferring confirmed shadow values to production; — technical check after rollout. RESULT — Pull Request; — DB migrations; — working integration Python → Node.js; — Shadow Mode; — UPSERT, STALE, and transactional update; — launch by slug/id; — staging deployment; — smoke-test results; — brief documentation; — at least 7 days of bug fixes for the implemented scope after acceptance. IN RESPONSE, INDICATE 1. Fixed price for the mandatory scope. 2. Separate cost for the promotion mechanism. 3. Timeline. 4. Hourly estimate. 5. When you are ready to start. 6. Experience with PostgreSQL transactions, migrations, and ingestion pipelines. 7. What questions need to be clarified before starting. 8. Whether staging, QA, migrations, and bug-fix period are included. Template responses without specific estimates will not be considered. Access to production is not provided at the first stage. Work begins with limited code review and staging.
A centralized server system for collecting and storing data from Planfix, 1C, Meta Ads, and Google Ads is needed, as well as a web dashboard for displaying and analyzing this data. All data, change history, calculations, and aggregated metrics must be stored exclusively in the server database. The dashboard should not store or duplicate business data. It must retrieve the necessary information from the server database via API according to user requests and display it in the form of KPIs, charts, tables, and detailed reports.
We are looking for support for a project based on Yii , we need to make edits and improvements to the database, there is partially a connection with the previous contractor .....................
It is necessary to migrate the database from CRM G-PLUS to MyChatBot Database volume - 26 thousand leads 2 funnels - Call center and Sales department with their own funnels Lead cards (besides name and number) have many different fields Leads also have voice recordings of calls. These also need to be transferred I expect an approximate amount and implementation timeline from the candidate
Create a dashboard for monitoring and analyzing the performance of the company's location network (branches) in Google Business Profile (GBP) through the official Google Business Profile API. Process via a script based on Google Apps Script (link to Google Sheets). Record data in Google Sheets (which serves as a database for Looker Studio). Update: Daily (with an indication of the last update date). Create a Google Cloud service account. The script runs once a day (trigger at 03:00 AM) and sends a request to the GBP API. It retrieves metrics for the previous day for each location (locationId). Records data in a flat format (row = unique combination of Date + Branch ID + Metrics). Key Performance Indicator CardsCard NameGBP MetricDynamic FormatProfile ViewsImpressions (Search + Maps)Percentage %, Sparkline (blue)CallsLocal Services Phone CallsPercentage %, Sparkline (green)Website ClicksWebsite ClicksPercentage %, Sparkline (purple)Direction RequestsDirection RequestsPercentage %, Sparkline (orange)Average RatingAverage Review RatingAbsolute change (e.g., +0.1), Sparkline (yellow)New ReviewsNew Reviews CountPercentage %, Sparkline (turquoise)
