apiphany 0.1.0

Apiphany is a high-performance API orchestration engine. It transforms the chaotic process of extracting data from complex REST and GraphQL APIs into a clean, strictly-typed, and fully declarative workflow. Powered by `httpx` and `asyncio`, Apiphany tears through deeply chained API requests concurrently without ever triggering rate limits, handles massive multi-page payloads automatically, and seamlessly unpacks deeply nested JSON blobs into pristine Pandas DataFrames or SQL tables.

Apiphany

Apiphany is a high-performance API orchestration engine. It transforms the chaotic process of extracting data from complex REST and GraphQL APIs into a clean, strictly-typed, and fully declarative workflow. Powered by httpx and asyncio, Apiphany tears through deeply chained API requests concurrently without ever triggering rate limits, handles massive multi-page payloads automatically, and seamlessly unpacks deeply nested JSON blobs into pristine Pandas DataFrames or SQL tables.

Features

• Asynchronous Concurrency: Built entirely on httpx and asyncio, the engine fires hundreds of concurrent requests simultaneously with near-zero memory footprint.
• Enterprise Rate Limiting: Built-in aiolimiter ensures you never get IP banned. Strictly limits execution to requests_per_second.
• Chained Requests: Feed the extracted outputs of one API call as parameters into another dynamically (e.g., fetch Users -> Posts -> Comments).
• Deep Extraction: Native integration with json_extract_pandas to extract, unpack, and normalize nested JSON responses into clean DataFrames.
• Incremental State Tracking: Native state.json watermarking. Works locally or via S3 (s3://bucket/state.json) to persist the latest timestamps or IDs fetched.
• Secrets Management: Dynamically fetch client credentials or API keys directly from AWS Secrets Manager using ARNs.
• Robust Failure Handling: Automatic exponential backoff for server errors (500, 502, 503, 504).
• Cloud-Agnostic Logging: Emits pure JSON logs using python-json-logger natively compatible with AWS CloudWatch and Datadog.

Requirements

• Python 3.8+
• httpx
• aiolimiter
• pydantic
• python-json-logger

(Optional based on cloud providers)

• boto3 (for S3 exports, state management, and AWS Secrets Manager)
• pandas & sqlalchemy (for SQL database exports)

---

Installation & Usage

Install the core package:

pip install apiphany

To install with AWS capabilities (S3 exports and AWS Secrets Manager) or SQL export capabilities:

pip install apiphany[aws]
pip install apiphany[sql]

Python API

Import APIOrchestrator directly into your data pipeline, Lambda function, or test suite:

import asyncio
from apiphany import APIOrchestrator

# 1. Initialize the Client
client = APIOrchestrator(
    config_file="apiphany_config.json", 
    entity_name="jsonplaceholder"
)

# 2. Execute an API asynchronously!
# output_format can be "raw" (list of JSON dicts) or "flattened" (Pandas DataFrame)
df = asyncio.run(client.execute(
    api_identifier="get_users", 
    output_format="flattened"
))

print(df.head())

---

Configuration Schema Details

Apiphany operates entirely off a declarative JSON configuration file (apiphany_config.json). Every attribute is strictly validated at runtime by pydantic.

1. Root Entity Structure

The top level defines logical groups of APIs (Entities), global credentials, and rate limit rules.

• entity_name (string): The logical name of the API provider (e.g., "stripe", "salesforce").
• post_process (string): (Optional) Filepath to a custom Python script to mutate raw JSON before extraction.
• certificates (dict): (Optional) Must contain "cert" and "key" paths. Supports local or s3:// URIs for mTLS.
• client_credentials (dict): Global dictionary for Secrets. Supports templating ({{variable}}). If you provide "secrets_manager_arn", Apiphany resolves it directly from AWS Secrets Manager.
• retry_config (dict): Contains total_retries (default: 3) and requests_per_second (default: 10).
• api_list (list): The core array of APISchema endpoint objects.

Example:

{
    "api_config": [
        {
            "entity_name": "stripe",
            "client_credentials": {
                "secrets_manager_arn": "arn:aws:secretsmanager:us-east-1:123:secret:stripe-keys"
            },
            "retry_config": {
                "total_retries": 5,
                "requests_per_second": 20
            },
            "api_list": [ ... ]
        }
    ]
}

---

2. API Object (api_list)

Each object inside api_list defines a single executable endpoint.

• api_identifier (string): Unique ID used to execute the endpoint via .execute(api_identifier="my_api").
• api_name (string): Human-readable description.
• method (string): HTTP Method ("GET", "POST", "PUT", etc.).
• url (string): The URL. Supports templating from parent outputs (e.g., https://api.com/users/{{id}}).
• auth_type (string): Authentication type: "None", "Bearer", "Basic", or "APIKey".
• api_key_name (string): If auth_type is "APIKey", the header key name (default: "x-api-key").
• headers (dict): Static HTTP headers to inject.
• query_params (dict): Static URL parameters to inject. Supports templating.
• payload (dict): JSON body payload for POST/PUT requests.
• graphql_query (string): If supplied, forces a POST request and wraps the string as {"query": "..."}. Supports templating.

Example:

{
    "api_identifier": "create_user",
    "api_name": "Create a new User",
    "method": "POST",
    "url": "https://api.example.com/users",
    "auth_type": "Bearer",
    "headers": {
        "Content-Type": "application/json"
    },
    "payload": {
        "name": "Jane",
        "role": "admin"
    }
}

---

3. Pagination Configuration

Apiphany automatically scrolls through pages until the payload is empty.

• type (string): "page_based" or "offset_based".
• page_key (string): Parameter name for page number (default: "page").
• size_key (string): Parameter name for page size (default: "limit").
• page_size (int): Number of records to request per page (default: 100).
• offset_key (string): Parameter name for offset (default: "offset").
• limit_key (string): Parameter name for limit (default: "limit").
• limit_value (int): Offset increment amount (default: 100).
• stop_condition (string): Defines when to stop. "no_data" stops when returned array length < limit.

Example (Offset Based):

"pagination": {
    "type": "offset_based",
    "offset_key": "start",
    "limit_key": "limit",
    "limit_value": 500
}

---

4. Chained Requests

Dynamically feeds the output of this API into another child API.

• child_api_identifier (string): The api_identifier of the next endpoint to trigger.
• key_mapping (dict): Maps parent JSON keys to child URL template parameters (e.g., {"id": "userId"}).
• max_concurrent_requests (int): Maximum parallel threads hitting the child API (default: 5).
• batch_size (int): If > 1, combines parent values into comma-separated lists (e.g. 1,2,3,4,5).

Example (Batched Child Resolution):

"chained_request": {
    "child_api_identifier": "get_user_posts",
    "key_mapping": {
        "id": "userIds"
    },
    "max_concurrent_requests": 10,
    "batch_size": 20
}

If 100 IDs are fetched, it will group them into 5 concurrent requests, injecting ?userIds=1,2,3...20 into the child URL.

---

5. Extractor Configuration

Defines how deeply nested API JSON is parsed and flattened into Pandas DataFrames. Powered by json_extract_pandas.

• response_data_extractor (string): Target JSON path to pluck the core array from the root response (e.g. "data.results").
• json_extract_config.record_path (list): Path to the nested array within the row to explode into multiple rows (e.g., ["line_items"]).
• json_extract_config.meta (list): Fields to duplicate across every exploded row (e.g., ["transaction_id", ["user", "name"]]).
• json_extract_config.errors (string): How to handle missing keys ("raise" or "ignore").

Example:

"extractor_config": {
    "response_data_extractor": "data.results",
    "json_extract_config": {
        "record_path": [
            "line_items"
        ],
        "meta": [
            "transaction_id",
            "timestamp",
            ["user", "name"]
        ]
    }
}

The above will flatten an array of line_items while ensuring transaction_id, timestamp, and user.name are attached as columns to every item's row.

---

6. Export Configuration

Defines where Apiphany automatically saves the final dataset when execution finishes.

• save_output (bool): Master toggle to enable saving (default: true).
• output_type (string): "flattened" (Pandas CSV/JSON/SQL) or "raw" (Pure JSON dicts).
• target.type (string): Destination: "file" or "sql".
• target.location (string): Local filepath ("out.csv"), S3 URI ("s3://bucket/out.csv"), or SQL URI ("sqlite:///db.sqlite").
• target.table_name (string): (SQL Only) Name of the target database table.
• target.if_exists (string): (SQL Only) Behavior if table exists ("append", "replace", "fail").

Example (Export to SQL):

"export_config": {
    "save_output": true,
    "output_type": "flattened",
    "target": {
        "type": "sql",
        "location": "sqlite:///my_db.db",
        "table_name": "transactions",
        "if_exists": "append"
    }
}

---

7. State Tracking (Incremental Syncs)

Saves the highest watermark detected in a payload to skip historical downloads on the next run.

• incremental_key (string): The column to evaluate for the highest watermark (e.g., "updated_at", "id").

Example:

"state_tracking": {
    "incremental_key": "updated_at"
}

When you run Apiphany, it scans the DataFrame for the highest updated_at and saves it. On your next run, you can inject it directly into the URL by putting {{state_updated_at}} in your query_params.

---

Full End-to-End Example Config

Here is a complete example demonstrating how Apiphany can fetch a list of Users, automatically extract the id from each user, and concurrently fetch all the Posts authored by those users using batched Chained Requests.

{
    "api_config": [
        {
            "entity_name": "jsonplaceholder",
            "client_credentials": {},
            "retry_config": {
                "total_retries": 3,
                "requests_per_second": 10
            },
            "api_list": [
                {
                    "api_identifier": "get_users",
                    "api_name": "Fetch Users",
                    "method": "GET",
                    "url": "https://jsonplaceholder.typicode.com/users",
                    "auth_type": "None",
                    "chained_request": {
                        "child_api_identifier": "get_user_posts",
                        "key_mapping": {
                            "id": "userId"
                        },
                        "batch_size": 5,
                        "max_concurrent_requests": 10
                    },
                    "export_config": {
                        "save_output": true,
                        "output_type": "flattened",
                        "target": {
                            "type": "file",
                            "location": "users.csv"
                        }
                    }
                },
                {
                    "api_identifier": "get_user_posts",
                    "api_name": "Fetch Posts for User",
                    "method": "GET",
                    "url": "https://jsonplaceholder.typicode.com/posts",
                    "query_params": {
                        "userId": "{{userId}}"
                    },
                    "auth_type": "None",
                    "export_config": {
                        "save_output": true,
                        "output_type": "flattened",
                        "target": {
                            "type": "file",
                            "location": "posts.csv"
                        }
                    }
                }
            ]
        }
    ]
}