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"Daily Change Log – Provides IDs and timestamps for teams, players, game statistics, schedules, and standings that have been modified on a given date. To receive the data updates, use these unique IDs to pull relevant API feeds." 20 Twice a Day 11AM and 11PM to add the new items. New items will cause need for Game Stat, PlayerGameStat API to need to re-trigger based on values returned Ad-Hoc #49
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Potential solutionThe task involves integrating a change log system that captures modifications to teams, players, game statistics, schedules, and standings, and then using this information to trigger updates in various APIs and display the change log in the frontend dashboard. The solution will require changes across multiple files to ensure that the system correctly logs changes, triggers updates, and displays the information to the users. CodeFor # No specific code changes are proposed here since the ChangelogEntry model already contains the necessary fields.
# However, if additional details are needed, the model can be extended as described in the proposal. For # Add the following method to the PlayerFeeds class
def update_player_profiles(self, changelog_model, api_key):
new_changes = changelog_model.get_new_changes(entity_type='player')
for change in new_changes:
player_id = change['entity_id']
try:
self.get_player_profile(
access_level='...',
version='...',
language_code='...',
player_id=player_id,
file_format='...',
api_key=api_key
)
logger.info(f"Updated player profile for player ID: {player_id}")
except Exception as e:
logger.error(f"Failed to update player profile for player ID: {player_id}: {e}") For # Add the following code to schedule the task
from apscheduler.schedulers.background import BackgroundScheduler
from changelog import generate_change_log_entries
def scheduled_task():
print(f"Generating change log entries at {datetime.now()}")
generate_change_log_entries()
print("Change log entries generated successfully.")
scheduler = BackgroundScheduler()
scheduler.add_job(scheduled_task, 'cron', hour='11,23')
scheduler.start() For # Add the following methods to the GameFeeds class
def check_for_updates(self, game_id):
# Implement the logic to check for updates in the change log
pass
def update_game_data(self, game_id):
if self.check_for_updates(game_id):
boxscore = self.get_game_boxscore(...)
roster = self.get_game_roster(...)
statistics = self.get_game_statistics(...)
pbp = self.get_game_pbp(...)
# Process and store the fetched data
pass
else:
logger.info(f"No update needed for game ID {game_id}.") For // Import the new ChangeLog component
import ChangeLog from "./ChangeLog";
// Add the ChangeLog component to the dashboard layout
const Default = () => (
// ... existing code ...
<Row>
<Col className="d-flex">
<ChangeLog /> {/* Add the ChangeLog component to the dashboard */}
</Col>
</Row>
// ... existing code ...
); For from src.models.changelog import ChangeLog
def save_to_database(mapped_seasons, mapped_players, opponenetseasondata, teamseasondata, playerseasondata, team_info_dict):
for entry_id, mapped_entry in mapped_data.items():
last_change = ChangeLog.objects(entity_id=entry_id).order_by('-timestamp').first()
if last_change and last_change.timestamp > existing_entry.last_updated:
# Update or add records
else:
logging.info(f"No changes found for {collection_name} with id {entry_id}. Skipping update.") These code snippets provide a high-level overview of the changes needed to implement the solution. Each snippet should be adapted to fit the specific details of the application, such as the actual parameters for API calls, the logic for checking the change log, and the integration with the frontend component. Additionally, thorough testing is required to ensure that the system behaves as expected after these changes are made. Changes on backend-container/src/models/changelog.pyThe Here is a practical proposal to ensure the
Since the current model already includes the necessary fields, there may be no need for immediate changes unless further details are required by the application's logic. If the current fields are sufficient, you can proceed with implementing the other parts of the task that interact with the Changes on backend-container/src/sportsradar/extract/playerfeeds.pyTo modify the
Here is a code snippet that outlines the new method: class PlayerFeeds:
# ... existing code ...
def update_player_profiles(self, changelog_model, api_key):
"""
Check for new change log entries and update player profiles if necessary.
:param changelog_model: The model used to interact with the change log.
:param api_key: The API key for authentication.
"""
# Fetch new change log entries for players
new_changes = changelog_model.get_new_changes(entity_type='player')
# Iterate over new changes and update player profiles
for change in new_changes:
player_id = change['entity_id']
try:
self.get_player_profile(
access_level='...', # specify the access level
version='...', # specify the version
language_code='...', # specify the language code
player_id=player_id,
file_format='...', # specify the file format
api_key=api_key
)
logger.info(f"Updated player profile for player ID: {player_id}")
except Exception as e:
logger.error(f"Failed to update player profile for player ID: {player_id}: {e}")
# Note: Replace '...' with the actual parameters required for the API call. In this snippet, Remember to replace the placeholder values for This code assumes that the change log model and its methods are already implemented and available for use. If they are not, you will need to implement them as part of the overall task. Changes on backend-container/src/bpscheduler/bpschedule.pyTo create a scheduled task that runs twice daily at 11AM and 11PM to generate and store new change log entries, we need to use a scheduling library such as
Here's how the code could look after the changes: import sys
import os
from apscheduler.schedulers.background import BackgroundScheduler
from datetime import datetime
# Other imports remain the same
# Assuming there's a function to generate and store change log entries
# This function should be implemented in the appropriate module
from changelog import generate_change_log_entries
def scheduled_task():
"""
This function is called by the scheduler to generate and store change log entries.
"""
print(f"Generating change log entries at {datetime.now()}")
generate_change_log_entries()
print("Change log entries generated successfully.")
# Initialize the scheduler
scheduler = BackgroundScheduler()
# Schedule the task to run twice daily at 11AM and 11PM
scheduler.add_job(scheduled_task, 'cron', hour='11,23')
# Start the scheduler
scheduler.start()
# Rest of the existing code... In this code snippet, we've added the Please note that the Make sure to add the necessary error handling and logging to the Changes on backend-container/src/sportsradar/extract/gamefeeds.pyTo address the task of modifying the
Here is a conceptual implementation outline for the from datetime import datetime
class GameFeeds:
# Existing methods...
def check_for_updates(self, game_id):
"""
Check the change log for updates related to the given game_id.
:param game_id: The ID of the game to check for updates.
:return: Boolean indicating whether an update is needed.
"""
# This is a placeholder for the actual change log checking logic.
# You would need to implement the logic to interact with the change log system.
# For example, you could query a database or an API to get the latest change log entries.
# Then, compare the timestamps to determine if there's a newer update since the last check.
# Return True if an update is needed, False otherwise.
pass
def update_game_data(self, game_id):
"""
Update the game data by fetching the latest information from the API.
:param game_id: The ID of the game to update.
"""
# Check if updates are needed for the game.
if self.check_for_updates(game_id):
# Fetch the latest data from the API.
boxscore = self.get_game_boxscore(...) # Add the required parameters
roster = self.get_game_roster(...)
statistics = self.get_game_statistics(...)
pbp = self.get_game_pbp(...)
# Process and store the fetched data as needed.
# This could involve updating a database or sending data to another service.
# You would implement the specific logic based on your application's requirements.
pass
else:
# Log that no update is needed.
logger.info(f"No update needed for game ID {game_id}.")
# Existing methods would remain unchanged... In this outline, the Please note that this is a high-level proposal and the actual implementation would require more details about how the change log system works, how updates should be processed, and how the data should be stored or cached. Changes on frontend-container/src/pages/dashboards/Default/index.jsxTo solve the task for the
Here's an example of how you might modify the import React from "react";
import { Helmet } from "react-helmet-async";
import { Container, Row, Col } from "react-bootstrap";
import Header from "./Header";
import Appointments from "./Appointments";
import BarChart from "./BarChart";
import Calendar from "./Calendar";
import Feed from "./Feed";
import PieChart from "./PieChart";
import Projects from "./Projects";
import Statistics from "./Statistics";
import ChangeLog from "./ChangeLog"; // Import the new ChangeLog component
const Default = () => (
<React.Fragment>
<Helmet title="Default Dashboard" />
<Container fluid className="p-0">
<Header />
<Statistics />
<Row>
<Col lg="8" className="d-flex">
<BarChart />
</Col>
<Col lg="4" className="d-flex">
<Feed />
</Col>
</Row>
<Row>
<Col lg="6" xl="4" className="d-flex">
<Calendar />
</Col>
<Col lg="6" xl="4" className="d-flex">
<PieChart />
</Col>
<Col lg="6" xl="4" className="d-flex">
<Appointments />
</Col>
</Row>
<Projects />
<Row>
<Col className="d-flex">
<ChangeLog /> {/* Add the ChangeLog component to the dashboard */}
</Col>
</Row>
</Container>
</React.Fragment>
);
export default Default; Remember to style the ChangeLog component to match the dashboard's design and ensure that it is user-friendly and accessible. Changes on backend-container/src/apimappings/SeasonalStats.pyThe To address this task, we need to modify the
Here is a pseudo-code snippet to illustrate how the change log check might be integrated into the from src.models.changelog import ChangeLog
def save_to_database(mapped_seasons, mapped_players, opponenetseasondata, teamseasondata, playerseasondata, team_info_dict):
# ... existing code ...
for entry_id, mapped_entry in mapped_data.items():
# ... existing code ...
# Check for changes in the ChangeLog
last_change = ChangeLog.objects(entity_id=entry_id).order_by('-timestamp').first()
if last_change and last_change.timestamp > existing_entry.last_updated:
# Proceed with update or addition
# ... existing code for updating or adding records ...
else:
# Skip update as there are no new changes
logging.info(f"No changes found for {collection_name} with id {entry_id}. Skipping update.")
# ... existing code ... By following these steps, the Disclaimer: This comment was entirely generated using AI. Be aware that the information provided may be incorrect. Current plan usage: 121.62% Have feedback or need help? |
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