Budget: 450 UAH Deadline: 2 days
Good day . I am pleased to fulfill your task. The price is 450 UAH for 250 companies. turn to
Budget: 480 UAH Deadline: 2 days
Good day !
Ready to implement your project!
I have experience working in such projects, so I am sure you will be fully satisfied with the quality of work!
I will respect any of your wishes.
I will be happy to cooperate,
with UW. Romance
+38 099 744 35 25
Budget: 400 UAH Deadline: 1 day
Good day ! Ready to fulfill your order, have experience of such information collection, I can provide examples.
Cost of work: 2 UAH. For 1 company, a day ready to work for 10-12 hours, the number of work contact per day: 400-500 meals. Go to turn.
Contact: mail: [email protected] telegram @andrey160.
Budget: 400 RUB Deadline: 1 day
Hello to you! Experience with Excel. I’m ready to make a price of 400 rubles for 250 companies, as on the exchange recently and I want to earn positive reviews.
Quality and delivery in time guaranteed!
Budget: 750 UAH Deadline: 2 days
Hello to you,
If it is still relevant, I can fill the table according to your requirements.
There is experience of collecting such information, time and effort, the monotony of work is not scary at all.
The costs and deadlines are indicated for all 500 companies.
Please contact me, I will be happy to work with you!
Budget: 300 UAH Deadline: 1 day
I will do my work quickly and quality. Call to
Budget: 500 UAH Deadline: 1 day
Good day . Ready to implement your project. Experience in work is great. Details in private.
Budget: 625 UAH Deadline: 2 days
Good day . I get acquainted with the tables, I have skills in collecting information and knowledge of English. I can help you fill out the information you need. 1 company- 2.5 rubles, as you are offered a large amount, I will review your offer in terms of cost, in the direction of reduction. thank you.
- Projects -
- Rating -
- Rating 130
Budget: 300 UAH Deadline: 2 days
Good morning, ready to get to work. All the details are presented in the face. by [email protected]
With respect to Jaroslav
Budget: 300 UAH Deadline: 1 day
Good time of day. Ready to accomplish your task.
Anastasiia Rybalchenko
Winning proposal- Projects 129
- Rating 5.0
- Rating 2 521
Budget: 400 UAH Deadline: 1 day
Good day . I am ready to take your project, I have a lot of experience in this work. It indicates the actual cost and time of execution.
Budget: 400 RUB Deadline: 1 day
I will do quality work until the end of the day, ready to accept work immediately after the conclusion of the contract.
- Projects 8
- Rating -
- Rating 118
Budget: 350 UAH Deadline: 1 day
Hello, I will do it quickly and quality. Price and deadlines indicated for 250 companies!
Budget: 250 UAH Deadline: 1 day
Good day .
Ready to make your order.
I have a lot of experience working with Excel. I have recently done such a project.
250 UAH – 250 companies.
With respect, Vasily.
Budget: 400 UAH Deadline: 2 days
Good day .
Take for work. 400 UAH for 250 companies. During the period - 1-2 days.
With respect, Darja
Proposals are currently absent
Proposals concealed
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Marya Yota 7 April 2019Напишу скрипт обхода этих вебсайтов (по сути он уже есть).
Сформирую XLS.
Дайте все 30 заданий.
Только тогда смогу оценить стоимость.
На вскидку 1000 рублей. За все.
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Ivan Ivanov 7 April 2019Здравствуйте. А написание простенького скрипта, автоматически заполняющего таблицу, не рассматриваете? Задача не сложная, можно реализовать даже на Curl
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Ivan Ivanov 7 April 2019Ну Curl быстрее выполнит запросы и соберет данные, а при сборе больших объемов данных - скорость работы критична. К тому же будет работать везде: и на Windows и на Linux. Да и выводить он сможет не только в *.xlsx или в *.xls, но и в *.csv или в *.txt
Ну, в прочем, как заказчику будет удобнее - так и сделаем.
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Marya Yota 7 April 2019Кто вам сказал, что cURL (так правильно пишется) работает быстрее, чем HttpRequest?
Курл - это обертка серверного варианта запроса с сервера. Например php или python на unix, linux.
А локальные запросы обрабатываются всегда быстрее, даже если через список прокси. На порядок. Тайминг х 10 степени. Даже если с локального unix, linux.
Чота вы тут воду мутите )))
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Ivan Ivanov 7 April 2019А вы где прочитали, что HttpRequest VBA быстрее чем HttpRequest curl? Если я чего-то не знаю, можно мне ссылочку? Я почитаю.
Кроме того, я знаю как можно эмулировать многопоточность в curl. А VBA многопоточность точно не поддерживает. Может быть Вы и знаете какую-либо хитрость?
Мне нет принципиальной разницы на чем писать этот небольшой скриптик. И я бы не хотел разводить тут больших дискуссий и заниматься расчетами что будет быстрее. Если Вам понравилось это задание - я могу уступить.
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Marya Yota 7 April 2019Если вы про cURL c использованием пхп, то про многозадачность забудьте )))
ПХП - это интерпретатор. Причем написан он на Си.
Поэтому только эмуляция многопоточности.
И curl это библиотека, такая же как например mail (это я про скорость нативного кода и кода скомпилированного в библиотеке). Панимаете?
Ладно, проехали. Молодой видимо, неопытный.
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Ivan Ivanov 7 April 2019Как раз-таки именно в curl php - можно только эмулировать многопоточность.
В curl на Питоне - вы работаете с потоками так же, как и обычно, на чистом Python.
Спасибо за столь подробную лекцию про php.
А по поводу библиотеки - Вы же сами меня, вроде поправляли в правильном написании? Вы же знаете что libcurl, Curl, cUrl и PycURL - это 4 разные вещи?
И Вы серьезно хотите сказать, что VBA быстрее компилируется? Хотя нет, может быть, но не сразу а при включении условной компиляции.
Да, все верно - вечно молодой, вечно пьяный.
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Marya Yota 7 April 2019Вот в догонку.
Сейчас парсю bbb.org
Там примерно 3 000 000 компаний.
Скорость парсинга сейчас около 8000 карточек в час при 4 потоках (больше не надо - установлено экспериментальным путем).
Через курл - около 1200 карточек в час. Тоже в 4 потока. На стандартном дедикате.
Попробуйте и посмотрите )))
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Ivan Ivanov 7 April 2019Поздравляю. Если Вам необходимо это задание для еще большей отточки навыков работы с VBA - я Вам уступлю, как уже писал.
У Вас свои методы реализации, у меня - свои. Скорость работы программ, тоже думаю, будет отличаться.
Если данная задача Вам настолько - хоть асинхронность реализуйте, кто же Вам мешает.
Current freelance projects in the category Databases & SQL
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)