### Setup Local Environment with Venv

Source: https://github.com/diliprk/vedicastro/blob/main/README.md

Set up a Python virtual environment using venv, activate it, and install project dependencies from requirements.txt.

```bash
python -m venv astrovenv
source astrovenv/bin/activate
pip install --upgrade  pip
pip install -r requirements.txt
```

--------------------------------

### Example Usage and Output

Source: https://github.com/diliprk/vedicastro/blob/main/StudyNotebooks/AscMotionStudy.ipynb

Demonstrates how to use the calculate_daily_asc_speed function with example parameters and prints the ascendant speed for the first day.

```python
# Example usage parameters
year = 2024
lat = 11.020085773931049 # Example latitude
lon = 76.98319647719487  # Example longitude
utc = "+05:30"
ayan = "Krishnamurti" 
house_system = "Placidus"

dates, asc_speeds = calculate_daily_asc_speed(year, lat, lon, utc, ayan, house_system)
print(f"Asc Speed on {dates[0]}: {asc_speeds[0]:.5f} ° per second")
```

--------------------------------

### Install flatlib from GitHub

Source: https://github.com/diliprk/vedicastro/blob/main/README.md

After installing VedicAstro from PyPI, install the required flatlib package from its sidereal branch on GitHub using pip.

```bash
pip install git+https://github.com/diliprk/flatlib.git@sidereal#egg=flatlib
```

--------------------------------

### Install VedicAstro from PyPi

Source: https://github.com/diliprk/vedicastro/blob/main/README.md

Install the VedicAstro package using pip. This is the primary method for obtaining the library.

```bash
pip install vedicastro
```

--------------------------------

### Install Required Packages

Source: https://github.com/diliprk/vedicastro/blob/main/StudyNotebooks/AscMotionStudy.ipynb

Installs plotly and nbformat. Run these commands in your virtual environment before executing the notebook.

```bash
pip install plotly
pip install --upgrade nbformat
```

--------------------------------

### Setup Local Environment with Conda

Source: https://github.com/diliprk/vedicastro/blob/main/README.md

Set up a Python virtual environment using Conda with a specific Python version and install project dependencies.

```bash
conda create -n astrovenv python=3.11
conda activate astrovenv
pip install -r requirements.txt
```

--------------------------------

### Compute Vimshottari Dasa Example

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/README.md

Example of computing the Vimshottari Dasa periods for a given chart. The output includes start and end dates for major periods and their sub-periods (Bhuktis).

```python
dasa = horoscope.compute_vimshottari_dasa(chart)
# Returns: {
#     "Ketu": {
#         "start": "15-06-1990",
#         "end": "01-06-1998",
#         "bhuktis": {
#             "Ketu": {"start": "...", "end": "..."},
#             "Venus": {"start": "...", "end": "..."},
#             ...
#         }
#     },
#     ...
# }
```

--------------------------------

### Get Planet Significators Example

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/README.md

Example of how to retrieve planet significators using the get_planet_wise_significators function. This function requires pre-fetched planet and house data.

```python
significators = horoscope.get_planet_wise_significators(planets_data, houses_data)
# Returns: [
#   {"Planet": "Sun", "A": 10, "B": 5, "C": [2, 9], "D": [3, 10]},
#   ...
# ]
```

--------------------------------

### GET /

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/endpoints.md

Root endpoint that returns service information and a welcome message.

```APIDOC
## GET /

### Description
Root endpoint that returns service information.

### Method
GET

### Endpoint
/

### Response
#### Success Response (200)
- **message** (string) - Welcome message from the service.
- **info** (string) - Link to the interactive API documentation.

#### Response Example
```json
{
  "message": "Welcome to VedicAstro FastAPI Service!",
  "info": "Visit http://127.0.0.1:8088/docs to test the API functions"
}
```
```

--------------------------------

### Working with Nakshatras Example

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/constants.md

Illustrates how to approximate the nakshatra index from a given degree and retrieve the nakshatra name.

```python
from vedicastro.VedicAstro import NAKSHATRAS

# Find which nakshatra based on degree
degree = 45.5
nak_index = int(degree / 13.333)  # Approximate
nakshatra = NAKSHATRAS[nak_index % 27]
```

--------------------------------

### Example Usage of Aspect Mapping

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/constants.md

Demonstrates how to retrieve an aspect name using the ASPECT_MAPPING dictionary and flatlib constants.

```python
from vedicastro.VedicAstro import ASPECT_MAPPING
from flatlib import const

aspect_name = ASPECT_MAPPING[const.TRINE]  # Returns "Trine"
```

--------------------------------

### CORS Configuration

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/endpoints.md

Example CORS configuration allowing all origins, credentials, methods, and headers. This is a permissive setting.

```json
{
  "allow_origins": ["*"],
  "allow_credentials": true,
  "allow_methods": ["*"],
  "allow_headers": ["*"]
}
```

--------------------------------

### Converting Aspects Example

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/constants.md

Shows how to get an aspect between two objects, check if it exists, and then map its type to a human-readable name.

```python
from vedicastro.VedicAstro import ASPECT_MAPPING
from flatlib import aspects

aspect = aspects.getAspect(obj1, obj2, const.ALL_ASPECTS)
if aspect.exists():
    aspect_name = ASPECT_MAPPING[int(aspect.type)]
    print(f"Aspect: {aspect_name}")
```

--------------------------------

### HoraryChartInput Example JSON

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/types.md

An example of a JSON payload for the HoraryChartInput model, illustrating the fields needed for KP Horary chart generation.

```json
{
  "horary_number": 34,
  "year": 2024,
  "month": 2,
  "day": 5,
  "hour": 12,
  "minute": 0,
  "second": 0,
  "utc": "+5:30",
  "latitude": 11.02,
  "longitude": 76.98,
  "ayanamsa": "Krishnamurti",
  "house_system": "Placidus",
  "return_style": null
}
```

--------------------------------

### ChartInput Example JSON

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/types.md

An example of a JSON payload for the ChartInput model, demonstrating the required and optional fields for generating a horoscope chart.

```json
{
  "year": 1990,
  "month": 6,
  "day": 15,
  "hour": 14,
  "minute": 30,
  "second": 0,
  "utc": "+5:30",
  "latitude": 40.7128,
  "longitude": -74.0060,
  "ayanamsa": "Krishnamurti",
  "house_system": "Placidus",
  "return_style": null
}
```

--------------------------------

### Run VedicAstro API with FastAPI

Source: https://github.com/diliprk/vedicastro/blob/main/README.md

Deploy the VedicAstro package as an API service using FastAPI. This command starts the Uvicorn server.

```bash
uvicorn VedicAstroAPI:app --reload --port 8088
```

--------------------------------

### Accessing Planet Ruler Example

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/constants.md

Demonstrates how to find the ruling planet of a zodiac sign using predefined lists for signs and their lords.

```python
from vedicastro.VedicAstro import RASHIS, SIGN_LORDS

# Get the ruler of Leo
sign_idx = RASHIS.index("Leo")
ruler = SIGN_LORDS[sign_idx]  # "Sun"
```

--------------------------------

### Mapping Ayanamsa Values Example

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/constants.md

Demonstrates creating a VedicHoroscopeData object with a specified ayanamsa and retrieving its corresponding constant.

```python
from vedicastro.VedicAstro import VedicHoroscopeData, AYANAMSA_MAPPING

horoscope = VedicHoroscopeData(
    1990, 6, 15, 14, 30, 0,
    40.7128, -74.0060,
    ayanamsa="Krishnamurti"
)
ayanamsa_const = AYANAMSA_MAPPING[horoscope.ayanamsa]
```

--------------------------------

### Example: Using Different House Systems

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/configuration.md

Shows how to initialize VedicHoroscopeData with different house systems. Different house systems will lead to variations in house cusps and planetary positions.

```python
# Using different house systems
horoscope_placidus = VedicAstro.VedicHoroscopeData(
    year=1990, month=6, day=15, hour=14, minute=30, second=0,
    latitude=40.7128, longitude=-74.0060,
    house_system="Placidus"
)

horoscope_equal = VedicAstro.VedicHoroscopeData(
    year=1990, month=6, day=15, hour=14, minute=30, second=0,
    latitude=40.7128, longitude=-74.0060,
    house_system="Equal"
)

# Different house systems produce different house cusps and planet placements
```

--------------------------------

### VedicHoroscopeData with Auto-Detected Timezone (Example)

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/configuration.md

Demonstrates horoscope data creation where the timezone is automatically detected from the provided latitude and longitude.

```python
# Auto-detected timezone
horoscope_auto = VedicAstro.VedicHoroscopeData(
    year=1990, month=6, day=15, hour=14, minute=30, second=0,
    latitude=40.7128, longitude=-74.0060
    # Automatically becomes "America/New_York"
)
```

--------------------------------

### Horary Chart Input - Example 1

Source: https://github.com/diliprk/vedicastro/blob/main/StudyNotebooks/HoraryChartStudy.ipynb

Defines the parameters for the first horary chart, including date, time, and horary number.

```python
## Chart Input - 1
# year = 2024
# month = 2
# day = 5
# hour = 9
# minute = 14
# secs = 0
# horary_number = 168
```

--------------------------------

### Example: Using Different Ayanamsa Systems

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/configuration.md

Demonstrates initializing VedicHoroscopeData with different ayanamsa systems. Note that the same birth data with different ayanamsa values will result in different sign and house placements.

```python
# Using different ayanamsa systems
horoscope_lahiri = VedicAstro.VedicHoroscopeData(
    year=1990, month=6, day=15, hour=14, minute=30, second=0,
    latitude=40.7128, longitude=-74.0060,
    ayanamsa="Lahiri"
)

horoscope_kp = VedicAstro.VedicHoroscopeData(
    year=1990, month=6, day=15, hour=14, minute=30, second=0,
    latitude=40.7128, longitude=-74.0060,
    ayanamsa="Krishnamurti"
)

# Note: Same birth data, different ayanamsa produces different sign/house placements
```

--------------------------------

### Horary Chart Input - Example 2

Source: https://github.com/diliprk/vedicastro/blob/main/StudyNotebooks/HoraryChartStudy.ipynb

Defines the parameters for the second horary chart, including date, time, and horary number.

```python
## Chart Input - 2
year = 2024
month = 2
day = 5
hour = 15
minute = 51
secs = 0
horary_number = 140
```

--------------------------------

### Get Swisseph Version

Source: https://github.com/diliprk/vedicastro/blob/main/test_suite/deg_var_check_houses.ipynb

Retrieves and prints the major, minor, and patch versions of the swisseph library.

```python
se_version_major, se_version_minor, se_version_patch = swe.version.split('.')
print(se_version_major,'.',se_version_minor,'.',se_version_patch)
```

--------------------------------

### VedicHoroscopeData with Lahiri Ayanamsa and Equal Houses

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/configuration.md

Example of configuring `VedicHoroscopeData` to use the Lahiri ayanamsa and the Equal house system.

```python
horoscope = VedicAstro.VedicHoroscopeData(
    year=1990, month=6, day=15, hour=14, minute=30, second=0,
    latitude=40.7128, longitude=-74.0060,
    tz="America/New_York",
    ayanamsa="Lahiri",
    house_system="Equal"
)
```

--------------------------------

### KP SubLord Divisions Usage Example

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/constants.md

Shows how to retrieve horary chart data, including sign and ruling planet, for a given division number.

```python
from vedicastro import horary_chart

horary_data = horary_chart.get_horary_ascendant_degree(34)
print(horary_data['Sign'])      # Zodiac sign
print(horary_data['SubLord'])   # Ruling planet
print(horary_data['ZodiacDegreeLocation'])  # Absolute degree (0-360)
```

--------------------------------

### Get Planet in House Mapping

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/api-reference/VedicHoroscopeData.md

Determines which house (1-12) each planet is located in. Requires chart objects for houses and planets.

```python
planet_houses = horoscope.get_planet_in_house(chart, chart)
print(planet_houses)  # {'Sun': 1, 'Moon': 3, ...}
```

--------------------------------

### Test Horoscope Data Endpoint with Curl

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/endpoints.md

Example curl command to send a POST request to the /get_all_horoscope_data endpoint with a JSON payload.

```bash
curl -X POST http://127.0.0.1:8088/get_all_horoscope_data \
  -H "Content-Type: application/json" \
  -d '{
    "year": 1990,
    "month": 6,
    "day": 15,
    "hour": 14,
    "minute": 30,
    "second": 0,
    "utc": "+5:30",
    "latitude": 40.7128,
    "longitude": -74.0060,
    "ayanamsa": "Krishnamurti",
    "house_system": "Placidus"
  }'
```

--------------------------------

### Get Transit Details

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/api-reference/VedicHoroscopeData.md

Captures real-time transit data for all planets at the current chart time. Returns nakshatra, lords, and retrograde status for each planet.

```python
transits = horoscope.get_transit_details()
for transit in transits:
    print(f"{transit.PlanetName}: {transit.Nakshatra}, Retrograde: {transit.isRetrograde}")
```

--------------------------------

### cURL Example for Horary Chart Request

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/endpoints.md

Demonstrates how to make a POST request to the horary data endpoint using cURL. Includes setting the Content-Type header and providing the JSON request body.

```bash
curl -X POST http://127.0.0.1:8088/get_all_horary_data \
  -H "Content-Type: application/json" \
  -d '{
    "horary_number": 34,
    "year": 2024,
    "month": 2,
    "day": 5,
    "hour": 12,
    "minute": 0,
    "second": 0,
    "utc": "+5:30",
    "latitude": 11.02,
    "longitude": 76.98,
    "ayanamsa": "Krishnamurti",
    "house_system": "Placidus"
  }'
```

--------------------------------

### Handle Missing Ephemeris Data

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/errors.md

Use a try-except block to catch errors when setting the ephemeris path and ensure Swiss Ephemeris files are installed.

```python
import swisseph as swe

try:
    swe.set_ephe_path('./swisseph')  # Ensure path is set
    chart = horoscope.generate_chart()
except Exception as e:
    print(f"Ephemeris error: {e}")
    print("Ensure Swiss Ephemeris files are installed")
```

--------------------------------

### Get Consolidated Chart Data

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/api-reference/VedicHoroscopeData.md

Creates consolidated data organized by rasi (zodiac sign), combining planets and houses. Can return data grouped by rasi or as a list of dictionaries.

```python
consolidated = horoscope.get_consolidated_chart_data(planets_data, houses_data)
for rasi, objects in consolidated.items():
    print(f"{rasi}: {list(objects.keys())}")
```

--------------------------------

### Get Consolidated Chart Data (DataFrame Records Style)

Source: https://github.com/diliprk/vedicastro/blob/main/StudyNotebooks/VedicAstroStudy.ipynb

Retrieves consolidated astrological chart data and formats it as a list of dictionaries, similar to pandas' `to_dict(orient='records')`. This is useful for direct display or further processing.

```python
consolidated_chart_data_style1 = vhd.get_consolidated_chart_data(planets_data=planets_data, houses_data=houses_data, return_style = "dataframe_records")
pprint(consolidated_chart_data_style1[:3])
```

--------------------------------

### Initialize Birth Details for Chart Generation

Source: https://github.com/diliprk/vedicastro/blob/main/StudyNotebooks/VedicAstroStudy.ipynb

Set up the necessary variables for year, month, day, hour, minute, second, timezone, latitude, longitude, ayanamsa, and house system.

```python
year = 2024
month = 1
day = 1
hour = 9
minute = 15
secs = 0
latitude, longitude, utc = 40.707013856558156, -74.01123260406254, "-5:00" ## New York
ayan = "Lahiri"
house_system = "Placidus" # Default House system for Krishnamurti Paddhati system
```

--------------------------------

### compute_new_date

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/api-reference/utils.md

Calculates a new date by adding or subtracting a specified duration from a starting date.

```APIDOC
## Function: `compute_new_date`

### Description
Compute a new date by adding or subtracting a specified duration (in years) from a starting date tuple.

### Parameters
#### Path Parameters
- **start_date_tuple** (tuple) - Required - The starting date as a tuple (year, month, day, hour, minute)
- **duration_years** (float) - Required - The duration in years to add or subtract.
- **direction** (str) - Required - 'forward' to add duration, 'backward' to subtract.

### Return Type
`tuple` — The new date as a tuple (year, month, day, hour, minute).

### Example
```python
from vedicastro.utils import compute_new_date

start = (2024, 1, 1, 0, 0)
end_date = compute_new_date(start, 1.5, "forward") # Computes date 1.5 years from start
# end_date will be (2025, 7, 1, 0, 0)
```
```

--------------------------------

### Import necessary libraries

Source: https://github.com/diliprk/vedicastro/blob/main/test_suite/different_eph_files.ipynb

Imports pandas, swisseph, and utility functions from vedicastro.

```python
import pandas as pd
import swisseph as swe
from vedicastro.utils import *
from vedicastro import VedicAstro as va
```

--------------------------------

### VedicHoroscopeData with Explicit Timezone

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/configuration.md

Explicitly set the timezone for horoscope calculations. This example specifies 'America/New_York'.

```python
# Explicit timezone
horoscope_ny = VedicAstro.VedicHoroscopeData(
    year=1990, month=6, day=15, hour=14, minute=30, second=0,
    latitude=40.7128, longitude=-74.0060,
    tz="America/New_York"
)
```

--------------------------------

### Initialize VedicHoroscopeData Instance

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/api-reference/VedicHoroscopeData.md

Create an instance of VedicHoroscopeData with birth details, location, and astrological system configurations. Ensure all required parameters like year, month, day, hour, minute, second, latitude, and longitude are provided.

```python
from vedicastro import VedicAstro

# Create a horoscope for a birth time and location
horoscope = VedicAstro.VedicHoroscopeData(
    year=1990,
    month=6,
    day=15,
    hour=14,
    minute=30,
    second=0,
    latitude=40.7128,
    longitude=-74.0060,
    tz="America/New_York",
    ayanamsa="Krishnamurti",
    house_system="Placidus"
)
```

--------------------------------

### Complete Horary Chart Analysis Example

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/api-reference/horary_chart.md

This snippet demonstrates the complete workflow for horary chart analysis. It first finds the ascendant degree for a given horary number and then uses that time to generate a full horary chart, including planet data, significators, and Vimshottari Dasa.

```python
from vedicastro import VedicAstro, horary_chart

# Step 1: Find when ascendant matches horary number
horary_number = 34
matched_time, houses_chart, houses_data = horary_chart.find_exact_ascendant_time(
    year=2024, month=2, day=5,
    utc_offset="+5:30",
    lat=11.02, lon=76.98,
    horary_number=horary_number,
    ayanamsa="Krishnamurti"
)

if matched_time:
    # Step 2: Generate full horary chart data
    vhd = VedicAstro.VedicHoroscopeData(
        year=2024, month=2, day=5,
        hour=matched_time.hour,
        minute=matched_time.minute,
        second=matched_time.second,
        latitude=11.02,
        longitude=76.98,
        tz="+5:30",
        ayanamsa="Krishnamurti"
    )
    
    planets_chart = vhd.generate_chart()
    planets_data = vhd.get_planets_data_from_chart(planets_chart, houses_chart)
    
    # Step 3: Analyze significators and dasa
    significators = vhd.get_planet_wise_significators(planets_data, houses_data)
    dasa = vhd.compute_vimshottari_dasa(planets_chart)
```

--------------------------------

### Get Planet Positions within Houses

Source: https://github.com/diliprk/vedicastro/blob/main/StudyNotebooks/VedicAstroStudy.ipynb

Retrieve and print a dictionary showing which house each planet is located in.

```python
planet_in_house = vhd.get_planet_in_house(houses_chart = chart, planets_chart = chart)
pprint(planet_in_house)
```

--------------------------------

### Clone VedicAstro Repository

Source: https://github.com/diliprk/vedicastro/blob/main/README.md

Clone the VedicAstro repository from GitHub to set up the project locally.

```bash
https://github.com/diliprk/VedicAstro.git
```

--------------------------------

### Calculate Julian Day from UTC Time

Source: https://github.com/diliprk/vedicastro/blob/main/test_suite/deg_var_check_houses.ipynb

Calculates the Julian day starting from a given UTC time, including the offset.

```python
utc = swe.utc_time_zone(year, month, day, hour = hour, minutes = minute, seconds = secs, offset = utc_float)
_ , jd_start = swe.utc_to_jd(*utc) ## Unpacks utc tuple
current_time = jd_start
```

--------------------------------

### Prepare DataFrames for Side-by-Side Comparison

Source: https://github.com/diliprk/vedicastro/blob/main/test_suite/deg_var_check_planets.ipynb

Selects specific columns from both Swisseph and Flatlib DataFrames and converts them to HTML for display. This is a preparatory step for visual comparison.

```python
final_cols = ["Object","Rasi","LonDecDeg","SignLonDMS"]
df1_html = df_swe_planets[final_cols].to_html()
df2_html = df_flatlib_planets[final_cols].to_html()
```

--------------------------------

### 422 Unprocessable Entity Error Response

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/endpoints.md

Example JSON response for a validation error. The 'detail' field indicates which fields are missing or invalid.

```json
{
  "detail": [
    {
      "loc": ["body", "year"],
      "msg": "field required",
      "type": "value_error.missing"
    }
  ]
}
```

--------------------------------

### Initialize VedicHoroscopeData and Generate Chart

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/README.md

Instantiate the main VedicAstro class with birth details and location, then generate a horoscope chart. This is the primary entry point for astrological calculations.

```python
from vedicastro import VedicAstro

horoscope = VedicAstro.VedicHoroscopeData(
    year=1990, month=6, day=15,
    hour=14, minute=30, second=0,
    latitude=40.7128, longitude=-74.0060,
    tz="America/New_York",
    ayanamsa="Krishnamurti",
    house_system="Placidus"
)

chart = horoscope.generate_chart()
planets_data = horoscope.get_planets_data_from_chart(chart)
houses_data = horoscope.get_houses_data_from_chart(chart)
significators = horoscope.get_planet_wise_significators(planets_data, houses_data)
dasa = horoscope.compute_vimshottari_dasa(chart)
aspects = horoscope.get_planetary_aspects(chart)
```

--------------------------------

### Display help for VedicHoroscopeData

Source: https://github.com/diliprk/vedicastro/blob/main/StudyNotebooks/VedicAstroStudy.ipynb

Shows the documentation and available methods for the VedicHoroscopeData class.

```python
help(VedicHoroscopeData)
```

--------------------------------

### Get House-wise Significators

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/api-reference/VedicHoroscopeData.md

Computes house-wise significators according to KP Astrology rules. This is useful for analyzing the significations for each house in a horoscope.

```python
significators = horoscope.get_house_wise_significators(planets_data, houses_data)
for sig in significators:
    print(f"House {sig.House}: A={sig.A}, B={sig.B}, C={sig.C}, D={sig.D}")
```

--------------------------------

### Set Case 2 Date and Time Variables

Source: https://github.com/diliprk/vedicastro/blob/main/test_suite/deg_var_check_planets.ipynb

Initializes variables for year, month, day, hour, minute, and seconds for a specific date and time. Also sets latitude, longitude, and UTC offset for Delhi.

```python
## Case 2
year = 2000
month = 12
day = 30
hour = 22
minute = 31
secs = 59
latitude, longitude, utc_offset = 28.6334, 77.2834, "+5:30" ## Delhi
```

--------------------------------

### Handle Missing Ephemeris Data

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/errors.md

Catches exceptions that occur when Swiss Ephemeris files are not available. This typically indicates an issue with the pyswisseph installation.

```python
try:
    horoscope = VedicAstro.VedicHoroscopeData(
        year=1900, month=1, day=1, hour=0, minute=0, second=0,
        latitude=0, longitude=0
    )
    chart = horoscope.generate_chart()
except Exception as e:
    print(f"Ephemeris error: {e}")
```

--------------------------------

### Handle Invalid Ayanamsa Error

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/README.md

Example of using a try-except block to catch a TypeError when an invalid ayanamsa is provided during horoscope data initialization.

```python
try:
    horoscope = VedicAstro.VedicHoroscopeData(
        1990, 6, 15, 14, 30, 0,
        40.7128, -74.0060,
        ayanamsa="InvalidAyanamsa"
    )
    chart = horoscope.generate_chart()
except TypeError as e:
    print(f"Invalid ayanamsa: {e}")
```

--------------------------------

### Root Endpoint Information

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/endpoints.md

Retrieves basic service information from the root endpoint. Use this to confirm the service is running.

```json
{
  "message": "Welcome to VedicAstro FastAPI Service!",
  "info": "Visit http://127.0.0.1:8088/docs to test the API functions"
}
```

--------------------------------

### Get House-wise Significators

Source: https://github.com/diliprk/vedicastro/blob/main/StudyNotebooks/VedicAstroStudy.ipynb

Calculates and displays house-wise significators from planetary and house data. The output is a Polars DataFrame showing significators for each house.

```python
house_significators_table = vhd.get_house_wise_significators(planets_data, houses_data)
pl.DataFrame(house_significators_table)
```

--------------------------------

### Get Planet-wise Significators

Source: https://github.com/diliprk/vedicastro/blob/main/StudyNotebooks/VedicAstroStudy.ipynb

Calculates and displays planet-wise significators from planetary and house data. The output is a Polars DataFrame showing significators for each planet.

```python
planets_significators_table = vhd.get_planet_wise_significators(planets_data, houses_data)
pl.DataFrame(planets_significators_table)
```

--------------------------------

### Import Vedic Astro Libraries

Source: https://github.com/diliprk/vedicastro/blob/main/test_suite/deg_var_check_planets.ipynb

Imports necessary libraries for astrological calculations, including swisseph for ephemeris data and vedicastro for astrological functions.

```python
import os
import pandas as pd
import swisseph as swe
from swe_const import *
from vedicastro import VedicAstro as va
```

--------------------------------

### Get Planet-wise Significators

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/api-reference/VedicHoroscopeData.md

Retrieves planet-wise significators based on planet and house data. Use this to understand the significations of each planet within a horoscope.

```python
chart = horoscope.generate_chart()
planets_data = horoscope.get_planets_data_from_chart(chart)
houses_data = horoscope.get_houses_data_from_chart(chart)

significators = horoscope.get_planet_wise_significators(planets_data, houses_data)
for sig in significators:
    print(f"{sig.Planet}: A={sig.A}, B={sig.B}, C={sig.C}, D={sig.D}")
```

--------------------------------

### House System Name to Constant Mapping

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/constants.md

Maps string names of house systems (e.g., 'Placidus', 'Equal') to their corresponding constants from the flatlib library. This facilitates the selection of different house calculation methods.

```python
HOUSE_SYSTEM_MAPPING = {
    "Placidus": const.HOUSES_PLACIDUS,
    "Equal": const.HOUSES_EQUAL,
    "Equal 2": const.HOUSES_EQUAL_2,
    "Whole Sign": const.HOUSES_WHOLE_SIGN,
}
```

```python
from vedicastro.VedicAstro import HOUSE_SYSTEM_MAPPING

system_const = HOUSE_SYSTEM_MAPPING.get("Placidus")
# Returns flatlib constant for Placidus houses
```

--------------------------------

### Get Horary Ascendant Details

Source: https://github.com/diliprk/vedicastro/blob/main/StudyNotebooks/HoraryChartStudy.ipynb

Retrieves the ascendant degree and sublord for a given horary number. This is a foundational step for horary chart calculations.

```python
horary_asc = horary_chart.get_horary_ascendant_degree(horary_number)
desired_asc = horary_asc["ZodiacDegreeLocation"]
sublord =  horary_asc["SubLord"]
```

--------------------------------

### Import necessary libraries

Source: https://github.com/diliprk/vedicastro/blob/main/StudyNotebooks/VedicAstroStudy.ipynb

Imports the required modules for Vedic astrology calculations and data handling.

```python
from vedicastro.VedicAstro import VedicHoroscopeData
from vedicastro.utils import pretty_data_table
from pprint import pprint
import polars as pl
```

--------------------------------

### Get UTC Offset with DST

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/api-reference/utils.md

Retrieves the UTC offset string and timedelta for a given timezone and date, accounting for daylight saving time.

```python
from vedicastro.utils import get_utc_offset
from datetime import datetime

tz_str, tz_delta = get_utc_offset("Asia/Kolkata", datetime(2024, 1, 1, 12, 0))
print(tz_str)  # "+05:30"
print(tz_delta)  # 5:30:00

ny_str, ny_delta = get_utc_offset("America/New_York", datetime(2024, 7, 1, 12, 0))
print(ny_str)  # "-04:00" (EDT during summer)
```

--------------------------------

### Initialize VedicHoroscopeData and Generate Chart

Source: https://github.com/diliprk/vedicastro/blob/main/test_suite/deg_var_check_planets.ipynb

This snippet shows how to initialize the VedicHoroscopeData class with specific date, time, location, and ayanamsa details. It then generates the horoscope chart and retrieves planetary data from it.

```python
vhd = va.VedicHoroscopeData(year = year, month = month, day = day, hour = hour, minute = minute, second = secs, utc = utc_offset, 
                        latitude = latitude, longitude = longitude, ayanamsa = "Krishnamurti_Senthilathiban", house_system = "Placidus")

chart = vhd.generate_chart()
planets_data = vhd.get_planets_data_from_chart(chart)
```

--------------------------------

### Print Ayanamsa Flags and Values

Source: https://github.com/diliprk/vedicastro/blob/main/test_suite/deg_var_check_planets.ipynb

Demonstrates the use of different flags with the `swe.get_ayanamsa_ex_ut` function to retrieve ayanamsa values. It prints the raw flag values and the results of ayanamsa calculations with various flag combinations.

```python
print(swe.FLG_SWIEPH)
print(swe.FLG_SIDEREAL)
print(swe.get_ayanamsa_ut(current_time))
print(swe.get_ayanamsa_ex_ut(current_time, flags = swe.FLG_SWIEPH))
print(swe.get_ayanamsa_ex_ut(current_time, flags = swe.FLG_SIDEREAL | swe.FLG_SPEED))
print(swe.get_ayanamsa_ex_ut(current_time, flags = swe.FLG_SIDEREAL + swe.FLG_SWIEPH ))
print(swe.get_ayanamsa_ex_ut(current_time, flags = swe.FLG_SWIEPH | swe.FLG_SIDEREAL)[1])
```

--------------------------------

### Compare All Ayanamshas: SwissEPH vs Flatlib

Source: https://github.com/diliprk/vedicastro/blob/main/test_suite/deg_var_check_houses.ipynb

Compares all concatenated SwissEPH data with all flatlib results. Converts DataFrames to HTML and displays them side-by-side for a comprehensive overview.

```python
# Convert DataFrames to HTML and concatenate them with some space in between
df1_html = df_swisseph.to_html()
df2_html = df_flatlib.to_html()
display_side_by_side(df1_html, df2_html, localized_time, latitude, longitude, ayan = "For All")
```

--------------------------------

### VedicHoroscopeData with Auto-Detected Timezone

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/configuration.md

When `tz` is not specified, the timezone is automatically detected using TimezoneFinder based on latitude and longitude. This example uses default settings.

```python
horoscope = VedicAstro.VedicHoroscopeData(
    year=1990, month=6, day=15, hour=14, minute=30, second=0,
    latitude=40.7128, longitude=-74.0060
    # tz=None triggers auto-detection -> "America/New_York"
)
```

--------------------------------

### Verify Ayanamsa and House System Settings

Source: https://github.com/diliprk/vedicastro/blob/main/StudyNotebooks/VedicAstroStudy.ipynb

Check the ayanamsa and house system attributes of the created VedicHoroscopeData object to confirm they were set correctly.

```python
vhd.ayanamsa, vhd.house_system
```

--------------------------------

### Get Vedic Planetary Aspects

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/api-reference/VedicHoroscopeData.md

Retrieves Vedic planetary aspects and descriptive strings from planet data. Use this to analyze relationships between planets in a horoscope.

```python
planets_data = horoscope.get_planets_data_from_chart(chart)
vedic_aspects, descriptions = horoscope.get_planetary_aspects_vedic(planets_data)

for aspect in vedic_aspects:
    print(f"{aspect['P1']} and {aspect['P2']} are in {aspect['Aspect']}")
```

--------------------------------

### Import Libraries

Source: https://github.com/diliprk/vedicastro/blob/main/StudyNotebooks/AscMotionStudy.ipynb

Imports necessary libraries for calculations and plotting, including flatlib, plotly, datetime, and VedicAstro.

```python
from flatlib import const
import plotly.graph_objects as go
from datetime import datetime, timedelta
from vedicastro.VedicAstro import VedicHoroscopeData
```

--------------------------------

### Get House Data from Chart

Source: https://github.com/diliprk/vedicastro/blob/main/StudyNotebooks/VedicAstroStudy.ipynb

Retrieves house data for a given astrological chart and converts it into a Polars DataFrame. This is useful for analyzing the astrological houses.

```python
houses_data = vhd.get_houses_data_from_chart(chart)
houses_df = pl.DataFrame(houses_data)
houses_df
```

--------------------------------

### Handle Horary Charting Error

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/README.md

Example of using a try-except block to catch general exceptions during horary chart analysis, such as when no matching ascendant time is found.

```python
try:
    matched = horary_chart.find_exact_ascendant_time(...)
    if matched is None:
        print("No matching ascendant time found")
except Exception as e:
    print(f"Horary error: {e}")
```

--------------------------------

### Get Ayanamsa Constant

Source: https://github.com/diliprk/vedicastro/blob/main/_autodocs/api-reference/VedicHoroscopeData.md

Returns the ayanamsa constant from flatlib based on the configured ayanamsa string. This is useful for astrological calculations requiring specific ayanamsa systems.

```python
ayanamsa_const = horoscope.get_ayanamsa()
```