Python library to parse XML data directly from HTTP, HTTPS, or FTP sources without loading the entire file into memory, supporting decompression, encoding detection, tag-based itemization, and optional filtering.
Project description
xmlstreamer
xmlstreamer is a Python library designed for efficient, memory-friendly streaming and parsing of large XML feeds from various sources, including compressed formats. It supports decompression, character encoding detection, tag-based itemization, and optional item filtering, making it ideal for handling real-time XML data feeds, large datasets, and complex structured content.
Features
- Streamed Data Parsing: Parses XML data directly from HTTP, HTTPS, or FTP sources without loading the entire file into memory.
- GZIP Decompression Support: Seamlessly handles GZIP-compressed XML feeds for bandwidth efficiency.
- Encoding Detection: Automatically detects and decodes character encodings, ensuring compatibility with varied XML data formats.
- Customizable Item Tokenization: Uses SAX-based parsing with user-defined tags to parse only relevant items from XML streams, reducing parsing overhead.
- Configurable Runtime and Buffering: Includes configurable buffer sizes and runtime limits, allowing you to tailor performance to your application’s needs.
- Flexible Filtering: Supports custom item filtering based on tag attributes and content, ideal for targeted data extraction.
Example Use Cases
- Parsing large RSS/Atom feeds in real-time, with item-by-item streaming and filtering.
- Handling compressed XML datasets for applications in web scraping, data aggregation, and news syndication.
- Memory-efficient parsing of large or continuous XML data streams without requiring the entire document in memory.
Installation
To install xmlstreamer
, use pip:
pip install xmlstreamer
Usage
from xmlstreamer import StreamInterpreter
import pprint
url = "https://example.com/large-feed.xml"
separator_tag = "item"
interpreter = StreamInterpreter(
url=url,
separator_tag=separator_tag,
buffer_size=1024 * 128,
max_running_time=600 # 10 minutes
)
for item in interpreter:
pprint.pprint(item) # Process each parsed item as a dictionary
Define custom filters, encoding mappings, or buffer sizes as needed for optimal performance.
Filtering Usage
To enable item filtering and alerts, create a subclass of xmlstreamer.StreamInterpreter
with custom methods for filtering and alerting. Below is an example of setting up an item filter based on date and creating a zero-items alert.
Step 1: Define an ItemFilter
The ItemFilter
class specifies which items to keep based on date filtering criteria:
import attrs
from attrs_strict import type_validator
from typing import Optional
@attrs.define
class ItemFilter:
attrib: str = attrs.field(
kw_only=True,
validator=type_validator()
)
fmt: Optional[str] = attrs.field(
validator=type_validator(),
default=None
)
max_item_age_in_days: int = attrs.field(
kw_only=True,
validator=type_validator()
)
- attrib: The XML tag or attribute to filter by.
- fmt: Optional date format for parsing dates within the attribute. If not provided, dateparser will be used for parsing.
- max_item_age_in_days: The maximum allowable age of items in days.
Step 2: Define Helper Functions for Parsing and Filtering Dates
Functions to parse dates and evaluate if an item should be kept based on the specified date limit:
from datetime import datetime, timedelta
from typing import Optional
import dateparser
def parse_date(string: str, fmt: str) -> Optional[datetime]:
try:
return datetime.strptime(string, fmt)
except ValueError:
return None
def eval_keep_date_item(string: str, fmt: str, limit_date: datetime) -> Optional[bool]:
string = string.strip()
parsed_date = parse_date(string, fmt) if fmt else dateparser.parse(string)
return parsed_date.timestamp() > limit_date.timestamp() if parsed_date else None
- parse_date: Parses the date string with the specified format.
- eval_keep_date_item: Checks if the item’s date is within the allowable age limit.
Step 3: Define the Filtering Function
The filter_parsed_item function applies the date filter to each parsed item:
from typing import Optional, Dict, Any
def filter_parsed_item(ITEM_FILTER: ItemFilter, parsed_item: ParsedItem) -> Optional[ParsedItem]:
attrib = ITEM_FILTER.attrib
fmt = ITEM_FILTER.fmt
max_item_age_in_days = ITEM_FILTER.max_item_age_in_days
limit_date = datetime.now() - timedelta(days=max_item_age_in_days)
item_content: Dict[str, Any] = parsed_item.parsed_content
if attrib in item_content:
dt = item_content[attrib]
keep_item = eval_keep_date_item(dt, fmt, limit_date) if isinstance(dt, str) else None
if keep_item is None:
item_content[attrib] = None
return parsed_item
elif keep_item:
return parsed_item
return None
Step 4: Extend StreamInterpreter for Filtering and Alerts
Create a subclass that enables filtering with filter_parsed_item and alerts if no items are parsed.
from xmlstreamer import StreamInterpreter
from datetime import datetime
from pathlib import Path
import inspect
class CustomStreamInterpreter(StreamInterpreter):
def __init__(self, **kwargs):
kwargs["max_running_time"] = 3600 # Set max runtime to 1 hour
super().__init__(**kwargs)
stack = inspect.stack()
fname = stack[1].filename
fname_path = Path(fname)
self.called_from = fname_path.stem
self.alerts_enabled = True
self.filter_parsed_item_func = filter_parsed_item
def raise_stop_iteration(self):
print(f"XMLSTREAMER STATS ITEMS PARSED: {self.stats_parsed_items}")
if self.stats_parsed_items == 0:
self.raise_zero_items_alert()
raise StopIteration
def raise_zero_items_alert(self):
print("--- ZERO ITEMS ALERT ---")
actual_date = datetime.now()
running_time = actual_date - self.start_date
print(f"Running time exceeded with no items parsed: {running_time}")
- CustomStreamInterpreter: Initializes with filter_parsed_item_func for item filtering.
- raise_zero_items_alert: Triggered if no items are parsed, printing a warning.
Step 5: Run with Custom Filtering
To use filtering and alerting with your subclass:
url = "https://example.com/large-feed.xml"
separator_tag = "item"
item_filter = ItemFilter(
attrib="pubDate",
fmt="%a, %d %b %Y %H:%M:%S %z",
max_item_age_in_days=7
)
interpreter = CustomStreamInterpreter(
url=url,
separator_tag=separator_tag,
item_filter=item_filter,
buffer_size=1024 * 128,
)
for item in interpreter:
print(item) # Process each filtered item as a dictionary
This example demonstrates setting a pubDate filter that removes items older than 7 days. The CustomStreamInterpreter will also trigger an alert if no items are parsed within the set runtime.
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