Data API

Для получения данных из системы FraudScore вы можете использовать наш Data API.

Data API позволяет получить все срезы данных, которые можно настроить в отчётах через веб-интерфейс, и даже больше.

Спецификации

В левой боковой панели в подменю каждой интеграции вам доступен раздел API Documentation.

В этом разделе вы можете узнать CHANNEL_ID вашей интеграции и персональный USER_KEY. Также в этом разделе можно найти ссылку на интерактивную документацию по Data API, где можно изучить его возможности и выполнить тестовые запросы.

Формат ссылки на интерактивную документацию:

https://api.fraudscore.ai/<CHANNEL_ID>/help?key=<USER_KEY>

Просто подставьте ваши CHANNEL_ID и USER_KEY.

Примеры запросов

Events ListEvents Grouping

Скачайте файл events_list.py или изучите код ниже:

events_list.py

#!/usr/bin/env python3
# coding: utf8

# Events List Request Example

import json
import requests

# Your channel id.

CHANNEL = 'channel_id'

# Your user key.

USER_KEY = 'user_key'

# Event type.
# Possible values:
# install, click, impression, custom.

EVENT = 'install'

# This is how URL looks like.

url = f'https://get.fraudscore.ai/{CHANNEL}/{EVENT}'

# Initialize request parameters.
# User key required.

params = dict(key = USER_KEY)

# List of fields we need.
# String or list of strings.

params['field'] = ['datetime', 'offer_id', 'affiliate_id', 'ipv4_str', 'ua']

# Optional filter expression.
# String (JSON).
# Expression format: ["operator", operand, operand, ...]
# Operand format: ["field", "value"]
# Nested expressions are supported. Example:
# `date >= "2024-01-01" AND date <= "2024-06-01" AND (offer_id = "id1" OR offer_id = "id2")`

params['filter'] = json.dumps([
    "AND",
    ["date_ge", "2024-01-01"],
    ["date_le", "2024-06-01"],
    [ # Nested expression.
        "OR",
        ["offer_id", "id1"],
        ["offer_id", "id2"],
        # More operands here...
    ],
    # More operands here...
])

# Optional sorting.
# String or list of strings.

params['sort'] = [
    'offer_id_asc',  # sort by id ascending
    'datetime_desc', # then by datetime descending
]

# Optional page number.
# Default 1.

params['page'] = 1

# Optional page size.
# Maximum 1000000.
# Default 100.

params['page_size'] = 100

# Optional timezone.
# Default `UTC`.
# Your value is here https://report.fraudscore.ai/account_settings
# Example: `Timezone settings` `Europe/Moscow (UTC+3)`
# Usage: `params['tz'] = 'Europe/Moscow'`

params['tz'] = 'UTC'

r = requests.get(url, params, stream=True)

print('Request URL', r.url)
# `https://get.fraudscore.ai/channel_id/install?key=user_key&field=datetime&field=offer_id&field=affiliate_id&field=ipv4_str&field=ua&filter=%5B%22AND%22%2C+%5B%22date_ge%22%2C+%222024-01-01%22%5D%2C+%5B%22date_le%22%2C+%222024-06-01%22%5D%2C+%5B%22OR%22%2C+%5B%22offer_id%22%2C+%22id1%22%5D%2C+%5B%22offer_id%22%2C+%22id2%22%5D%5D%5D&sort=offer_id_asc&sort=datetime_desc&page=1&page_size=100&tz=UTC`

# Response format is JSON lines. Read it line by line.
# That's why we passed `stream=True` above.

for line in r.iter_lines():
    # Each line is JSON.
    # Decode it and have fun!

    data = json.loads(line)

Скачайте файл events_grouping.py или изучите код ниже:

events_grouping.py

#!/usr/bin/env python3
# coding: utf8

# Events Grouping Request Example

import json
import requests

# Your channel id.

CHANNEL = 'channel_id'

# Your user key.

USER_KEY = 'user_key'

# Event type.
# Possible values:
# install, click, impression, custom.

EVENT = 'install'

# This is how URL looks like.

url = f'https://get.fraudscore.ai/{CHANNEL}/{EVENT}/groups'

# Initialize request parameters.
# User key required.

params = dict(key = USER_KEY)

# List of fields to group.
# String or list of strings.

params['group'] = [
    'date',
    'ipv4_str',
]

# List of special group fields we need.
# String or list of strings.

params['field'] = [
    'any_offer_name',
    'any_affiliate_name',
]

# Optional filter expression.
# String (JSON).
# Expression format: ["operator", operand, operand, ...]
# Operand format: ["field", "value"]
# Nested expressions are supported. Example:
# `date >= "2024-01-01" AND date <= "2024-06-01" AND (offer_id = "id1" OR offer_id = "id2")`

params['filter'] = json.dumps([
    "AND",
    ["date_ge", "2024-01-01"],
    ["date_le", "2024-06-01"],
    [ # Nested expression.
        "OR",
        ["offer_id", "id1"],
        ["offer_id", "id2"],
        # More operands here...
    ],
    # More operands here...
])

# Optional filter after grouping.
# Works the same way as `filter` param.
# Example: return groups where count >= 10

params['having'] = json.dumps(
    ["count_ge", "10"]
)

# Optional sorting.
# String or list of strings.

params['sort'] = [
    'any_offer_name_asc', # sort by offer_name ascending
    'any_affiliate_name_desc', # then by affiliate_name descending
]

# Optional page number.
# Default 1.

params['page'] = 1

# Optional page size.
# Maximum 1000000.
# Default 100.

params['page_size'] = 100

# Optional timezone.
# Default `UTC`.
# Your value is here https://report.fraudscore.ai/account_settings
# Example: `Timezone settings` `Europe/Moscow (UTC+3)`
# Usage: `params['tz'] = 'Europe/Moscow'`

params['tz'] = 'UTC'

# Perform GET request.
# Stream mode recommended.

r = requests.get(url, params, stream=True)

print('Request URL', r.url)
# `https://get.fraudscore.ai/channel_id/install/groups?key=user_key&group=date&group=ipv4_str&field=any_offer_name&field=any_affiliate_name&filter=%5B%22AND%22%2C+%5B%22date_ge%22%2C+%222024-01-01%22%5D%2C+%5B%22date_le%22%2C+%222024-06-01%22%5D%2C+%5B%22OR%22%2C+%5B%22offer_id%22%2C+%22id1%22%5D%2C+%5B%22offer_id%22%2C+%22id2%22%5D%5D%5D&having=%5B%22count_ge%22%2C+%2210%22%5D&sort=any_offer_name_asc&sort=any_affiliate_name_desc&page=1&page_size=100&tz=UTC`

# Response format is JSON lines. Read it line by line.
# That's why we passed `stream=True` above.

for line in r.iter_lines():
    # Each line is JSON.
    # Decode it and have fun!

    data = json.loads(line)