• Started uni in 2007.
• I have a £32,000 student loan from the UK (Plan 1)
• Been living abroad since 2014 (US).
• I've always made my repayments on time until recently. I also had a Plan 2 but paid it off during less hard times money-wise.
• Due to financial obligations (child support) and medical bills, I can no longer afford the monthly payments.

1. I not acknowledge SLC communications.
   1. Receive letters and emails reminding me about my noncompliance.
   2. Arrears delegated to transcom to collect. I don't acknowledge the debt to transcom.
   3. Transcom runs into someone in the legal field who makes sure they're following every relevant local statute on debt collection practices, while avoiding acknowledging the loan. If they don't meet the (honestly pretty onerous) requirements, there are quite a lot of remedies available in local court.
   4. Transcom gets bored, fails to collect, I start hearing from SLC again with pestering letters.

1. Either as a means of me finding out about foreclosure or after me finding out, I am presumably served with either the complaint if direct filed to local court or a UK summons if they go foreign judgment enforcement as a route.
   
2. If it's a UK judgment they seek, I'd be in a bind as I've never studied British contract law. So my instinct would be to try to seek affordable local counsel or put up a pretty basic pro-se response just articulating my objections. There are a number of objections I understand that could be made under UK law that might not be applicable in the US. I know there's been legal debate about court enforceability from the UK legal community, but it's all untested.
   
3. If they sue me in the US and/or try to enforce the UK judgment in US court, I'm much more confident about what I'd do. Essentially, try to settle, then commence legal scorched earth. Every possible and defensible motion, brief, appellate process etc is utilized. Consistently offer a settlement throughout. There's a fair bit of "there" in terms of debtor protection statutes, their whole mess of constant ex-post-facto term and conditions modifications, etc etc. Suffice to say, I believe I could make it cost (even with their lawyer being the cheapest bargain basement guy, a lot more than the value of my debt).
   
4. If despite this, they don't settle and I lose and have a local judgment against me options are - I declare bankruptcy. I don't borrow at all since my student loan, so it'd trash my redundant good credit but that's about it. SLC gets $0 - I allow SLC to garnish my salary.
   

• How would you describe homebuying in Des Moines these days, considering that they have risen by more than 36% since the pandemic?
• Have you given up on homebuying until mortgage rates fall, or even given up on buying altogether?
• If you already own, do you have an adjustable rate mortgage that’s renewing?

from datetime import datetime, timedelta import pandas as pd import requests import time import numpy as np class AircallAPI: def __init__(self, api_id, api_token): self.base_url = "https://api.aircall.io/v1" self.auth = (api_id, api_token) def get_calls(self, from_date=None, to_date=None): """Fetch a list of calls within a specified date range, handles various HTTP response codes.""" endpoint = f"{self.base_url}/calls" params = {} if from_date: params['from'] = from_date if to_date: params['to'] = to_date response = requests.get(endpoint, auth=self.auth, params=params) # Check for various HTTP response codes and handle them if response.status_code == 200: # Request was successful return response.status_code, response.json() elif response.status_code == 401: # Unauthorized access return response.status_code, "Unauthorized: Check your API ID and Token." elif response.status_code == 404: # Endpoint not found return response.status_code, "Not Found: The requested endpoint is incorrect." elif response.status_code == 429: # Too many requests return response.status_code, "Too Many Requests: Rate limit exceeded." elif response.status_code >= 500: # Server error return response.status_code, "Server Error: The server encountered an error." else: # Other errors return response.status_code, response.text def get_calls_detailed(self, from_date, to_date, page_number=1, order='desc', fetch_contact=True): """Fetch detailed call data including contact details for each call for the specified date range and page.""" # Convert the provided dates into UNIX timestamps from_date_timestamp = int(datetime.strptime(from_date, "%Y-%m-%d").timestamp()) to_date_timestamp = int(datetime.strptime(to_date, "%Y-%m-%d").timestamp()) # Construct the API endpoint URL with query parameters url = f"{self.base_url}/calls" params = { "from": from_date_timestamp, "to": to_date_timestamp, "page": page_number, "order": order, # Include the order parameter "per_page": 50, # Fetch 50 calls per page "fetch_contact": fetch_contact # Include contact details in the response } # Make the HTTP GET request response = requests.get(url, params=params, auth=self.auth) formatted_calls = [] # Check if the request was successful if response.status_code == 200: calls_data = response.json().get('calls', []) for call in calls_data: formatted_call = { "CallId": call.get('id'), "CallLink": call.get('direct_link'), "CallStartedAt": datetime.utcfromtimestamp(call.get('started_at')).strftime('%Y-%m-%d %H:%M:%S') if call.get('started_at') else None, "CallAnsweredAt": datetime.utcfromtimestamp(call.get('answered_at')).strftime('%Y-%m-%d %H:%M:%S') if call.get('answered_at') else None, "CallEndedAt": datetime.utcfromtimestamp(call.get('ended_at')).strftime('%Y-%m-%d %H:%M:%S') if call.get('ended_at') else None, "Duration": call.get('duration'), "CallStatus": call.get('status'), "CallDirection": call.get('direction'), "FromNumber": call.get('raw_digits'), #"Asset": call.get('asset'), #"Recording": call.get('recording'), #"Voicemail": call.get('voicemail'), "Archived": call.get('archived'), "MissedReason": call.get('missed_call_reason'), #"Cost": call.get('cost'), "Number": call.get('number', {}), "User": call.get('user', {}), "Contact": call.get('contact', {}), #"AssignedTo": call.get('assigned_to', {}), "AssignedTeam": call.get('teams', {}), #"TransferredBy": call.get('transferred_by', {}), #"TransferredTo": call.get('transferred_to', {}), "Comments": call.get('comments', []), "Tags": call.get('tags', [{}]), "Participants": call.get('participants', {}), "IVROptions": call.get('ivr_options', {}) } formatted_calls.append(formatted_call) return formatted_calls else: print(f"Failed to fetch detailed call data: {response.status_code}") return [] # Replace 'your_api_id' and 'your_api_token' with your actual Aircall API ID and Token api_id = 'XXX' api_token = 'XXX' aircall = AircallAPI(api_id, api_token) # Start time of fetching data for rate limit calculation from_date = datetime.now() - timedelta(days=7) #from_date = from_date.replace(hour=0, minute=0, second=0) from_date = from_date.strftime("%Y-%m-%d") to_date = datetime.now() #to_date = to_date.replace(hour=23, minute=59, second=59) to_date = to_date.strftime("%Y-%m-%d") all_calls = [] page_number = 1 calls_per_minute_limit = 7000 # Assuming a maximum of 3000 calls can be fetched per minute calls_fetched = 0 start_time = datetime.now() # Initialize start time # Fetch all calls info from Aircall for the specified date range while True: current_calls = aircall.get_calls_detailed(from_date, to_date, page_number) if not current_calls: break # No more calls available, exit loop all_calls.extend(current_calls) calls_fetched += len(current_calls) page_number += 1 # Check if the rate limit is reached, if so, pause the fetching if calls_fetched >= calls_per_minute_limit: end_time = datetime.now() elapsed_time = (end_time - start_time).total_seconds() if elapsed_time < 60: time.sleep(60 - elapsed_time) # Pause to respect the rate limit # Reset counting calls_fetched = 0 start_time = datetime.now() # Convert the list of calls to a pandas DataFrame df_calls = pd.DataFrame(all_calls) # Print the DataFrame print(f"Total Pages Fetched: {page_number - 1}") #print(df_calls.columns) #print(df_calls) # Define a function to extract the required columns from the 'Number' dictionary def extract_number_info(number_dict): if number_dict: return { "ToNumberId": number_dict.get('id'), "OptionDialled": number_dict.get('name'), "ToNumber": number_dict.get('digits') } else: return None # Apply the function to create a new DataFrame with the extracted 'Number' information df_number_info = df_calls['Number'].apply(extract_number_info).apply(pd.Series) # Define a function to extract the required columns from the 'User' dictionary def extract_user_info(user_dict): if user_dict: return { "UserId": user_dict.get('id'), "UserName": user_dict.get('name'), "UserEmail": user_dict.get('email') } else: return None # Apply the function to create a new DataFrame with the extracted 'User' information df_user_info = df_calls['User'].apply(extract_user_info).apply(pd.Series) # Define a function to extract the required columns from the 'AssignedTeam' list def extract_assigned_team_info(team_list): if team_list: team_info = team_list[0] # Assuming there's only one team in the list return { "AssignedTeamId": team_info.get('id'), "AssignedTeamName": team_info.get('name') } else: return None # Apply the function to create a new DataFrame with the extracted 'AssignedTeam' information df_assigned_team_info = df_calls['AssignedTeam'].apply(extract_assigned_team_info).apply(pd.Series) # Concatenate the extracted information DataFrames with the original DataFrame df_calls_info = pd.concat([df_calls, df_number_info, df_user_info,df_assigned_team_info], axis=1) # Print the DataFrame with the extracted information print(df_calls_info['Comments']) 

Thursday, May 2nd:

• Glow & Flow: Bring your favorite props to spin, flow, and juggle (practice/ LED/ covered fire props). A great space to vibe, dance and get into the Flow state. Surprise DJ sets on some nights. 7pm-9:30pm.
• Trivia: at Second Summit Cider. Free to play Trivia hosted by Game Night Live. There is two rounds of trivia each night, starting at 7pm and 8pm.
• This Is Your Band Live Karaoke: at Club 90 in Sandy. 8pm-11pm.
• Thursday Tunes: at Prohibition. Live jazz and blues from 8pm-10pm.

Friday, May 3rd:

• Thanksgiving Point Tulip Festival: live music, food trucks, vendors, and activities for the whole family. Runs all of April and May. Tickets are $24.
• Salt Lake Home Expo: at the Mountain America Expo Center. Runs all weekend. Admission is free.
• Fast CAT Speed Trial: at USU Bastian Agricultural Center. Fast CAT – is a timed 100-yard dash where dogs run one at a time, chasing a lure. Runs all weekend.
• The Pickpockets: at Second Summit Cider. Starts at 7pm. Entry is $10.
• First Friday Concerts: live music by talented local artists every first Friday of the month. Arrive early for family-friendly activities courtesy of the city of West Jordan and food truck fare. At the Viridian Event Center. Starts at 7:30pm.
• [Angel City FC at Utah Royals FC](seatgeek.pxf.io/eKzN6D): Women’s Soccer at America’s First Field. 7:30pm. Tickets are $5.

Saturday, May 4th:

• Spring Plant Sale: at Liberty Heights Fresh. From 8:30am-11am.
• Wasatch Reptile Expo: Thousands of reptiles, amphibians, arachnids, insects, feeders, enclosures and much more on display and for sale. At Utah State Fairpark. 10am-6pm. Tickets are $10.
• Free Comic Book Day: at the Main Library. Comics in all sorts of genres and for all ages. From 10am–1pm.
• Vintage Signs of Sugar House: Join local author Lisa Michele Church as she discusses the lost art of sign-making. This combination of lecture and tour provides an entertaining, informative walking tour of Sugar House. Meet at Fiddler’s Elbow at 10am. Tickets are $30.
• Salt Lake Mural Fest: Download the map, follow the balloons, and meet the artists along the way. 4pm-8pm.
• Monster Jam: at Rice Eccles Stadium. Starts at 7pm. Tickets are $35.
• Real Salt Lake vs Sporting Kansas City: at America First Field. Starts at 7:30pm. Tickets are $17.
• Salt Lake Mural Fest: Download the map, follow the balloons, and meet the artists along the way. 4pm-8pm.
• Houston SaberCats at Utah Warriors: Rugby at Zions Bank Stadium. 7pm. Tickets are $13.
• Utah Food Festival: at NHMU. Sample and shop an array of flavors from local food artisans, workshops led by culinary experts, and enrich knowledge of food history. Tickets are $22.
• Retro Riot's 80's & 90's Star Wars Dance Party: at Leatherhead's in Draper. Starts at 9pm. $10 cover.

Sunday, May 5th:

• Show & Shine: at Les Schwab in Murray. Car, Truck, and bike show. Maracas coloring contest and pinata for the kids, vendors and more. 11am-5pm.
• Cinco de Mayo: at Scion Cider Bar. Loteria, dominoes, food, music and more. 12pm-6pm.
• Cinco de Mayo Fiesta: at Millcreek Common. 4pm-11pm.
• Patio Tiki Party: at Lucky 13 Bar and Grill. Starts at 5pm.
• Sunday Night Comedy Show: Sunday nights Crowdsourced Comedy takes over the Why Kiki stage! Scenes, characters, and jokes are made up on the spot, all based off audience suggestions. 'Who's Line is it Anyway?' style! 7pm. Tickets are $5.

• How to work with fear.
• The secret of success of all great achievers.
• The best way to learn how to trade.
• How to overcome all negative emotions.
• Almost guaranteed ways to failure: 8 most dangerous issues beginners are facing today.
• Lessons learned from 2 traders who lost over $1 million.
• Powerful sources of self discipline.
• Contrarian’s opinion: Why „systems approach” to the market simply doesn’t work.
• How to learn to forgive yourself: an example of $45 thousand loss in 20 minutes.
• Powerful mental preparation before trading.
• Four pillars of trading success.
• What is the best way to learn discipline fast?
• The best systems for beginners. 10 laws of trading never seen before.
• The most critical beginners’ mistakes.
• Smart way of using equity curve to increase amount of winning trades.

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