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##
## name: Dimension Tags from Campaign Name
## description:
##  
## 
## author: 
## created: 2023-12-04
## 

today = datetime.datetime.now().date()

# Sample DataFrame creation (replace this with your data loading logic)
data = {
    'Client': [np.nan],
    'Campaign': ['10/2/2023-12/31/2023_CPM_1300_Target1_Budget10000_Impression50000'],
    'Pacing - Start Date': [np.nan],  # Add this line
    'Pacing - End Date': [np.nan],  # Add this line
    'Account': [np.nan],  # Add this line
    'Goal': [np.nan],  # Add this line
    'Target (Impr/Spend/Views)': [np.nan],  # Add this line
    'CPM Imp Target': [np.nan],  # Add this line
}
df = pd.DataFrame(data)

RPT_COL_CLIENT = 'Client'
RPT_COL_CAMPAIGN = 'Campaign'
RPT_COL_ACCOUNT = 'Account'
RPT_COL_PACING_START_DATE = 'Pacing - Start Date'
RPT_COL_PACING_END_DATE = 'Pacing - End Date'
RPT_COL_GOAL = 'Goal'
RPT_COL_TARGET_IMPR_PER_SPENDVIEWS = 'Target (Impr/Spend/Views)'
RPT_COL_CPM_IMP_TARGET = 'CPM Imp Target'
BULK_COL_CLIENT = 'Client'
BULK_COL_ACCOUNT = 'Account'
BULK_COL_CAMPAIGN = 'Campaign'
BULK_COL_PACING_START_DATE = 'Pacing - Start Date'
BULK_COL_PACING_END_DATE = 'Pacing - End Date'
BULK_COL_GOAL = 'Goal'
BULK_COL_TARGET_IMPR_PER_SPENDVIEWS = 'Target (Impr/Spend/Views)'
BULK_COL_CPM_IMP_TARGET = 'CPM Imp Target'

outputDf = pd.DataFrame(columns=[
    BULK_COL_PACING_START_DATE,
    BULK_COL_PACING_END_DATE,
    BULK_COL_GOAL,
    BULK_COL_TARGET_IMPR_PER_SPENDVIEWS,
    BULK_COL_CPM_IMP_TARGET
])

# create temp columns to store new dim tags and default to empty
TMP_START_DATE = RPT_COL_PACING_START_DATE + '_'
TMP_END_DATE = RPT_COL_PACING_END_DATE + '_'
TMP_GOAL = RPT_COL_GOAL + '_'
TMP_TARGET_IMPR_PER_SPENDVIEWS = RPT_COL_TARGET_IMPR_PER_SPENDVIEWS + '_'
TMP_CPM_IMP_TARGET = RPT_COL_CPM_IMP_TARGET + '_'

df[TMP_START_DATE] = np.nan
df[TMP_END_DATE] = np.nan
df[TMP_GOAL] = np.nan
df[TMP_TARGET_IMPR_PER_SPENDVIEWS] = np.nan
df[TMP_CPM_IMP_TARGET] = np.nan

def get_dates_and_tags_from_campaign_name(row):
    campaign_name = row[RPT_COL_CAMPAIGN]
    # Adjusted pattern to match the campaign name format
    pattern = r'(\d{1,2}/\d{1,2}/\d{4})-(\d{1,2}/\d{1,2}/\d{4})_([^_]+)_([^_]+)_Budget(\d+)_Impression(\d+)'
    match = re.search(pattern, campaign_name)
    if match:
        start_date, end_date, goal, target_impr_spend_views, cpm_imp_target = match.groups()
        return start_date, end_date, goal, target_impr_spend_views, cpm_imp_target
    else:
        return np.nan, np.nan, np.nan, np.nan, np.nan

# parse out Start/End Date, Goal, Target (Impr/Spend/Views), and CPM Imp Target from Campaign name
for index, row in df.iterrows():
    start_date, end_date, goal, target_impr_spend_views, cpm_imp_target = get_dates_and_tags_from_campaign_name(row)
    df.at[index, TMP_START_DATE] = start_date
    df.at[index, TMP_END_DATE] = end_date
    df.at[index, TMP_GOAL] = goal
    df.at[index, TMP_TARGET_IMPR_PER_SPENDVIEWS] = target_impr_spend_views
    df.at[index, TMP_CPM_IMP_TARGET] = cpm_imp_target

# find changed campaigns
changed = (
    (df[TMP_START_DATE].notnull() & (df[RPT_COL_PACING_START_DATE] != df[TMP_START_DATE])) |
    (df[TMP_END_DATE].notnull() & (df[RPT_COL_PACING_END_DATE] != df[TMP_END_DATE])) |
    (df[TMP_GOAL].notnull() & (df[BULK_COL_GOAL] != df[TMP_GOAL])) |
    (df[TMP_TARGET_IMPR_PER_SPENDVIEWS].notnull() & (df[BULK_COL_TARGET_IMPR_PER_SPENDVIEWS] != df[TMP_TARGET_IMPR_PER_SPENDVIEWS])) |
    (df[TMP_CPM_IMP_TARGET].notnull() & (df[BULK_COL_CPM_IMP_TARGET] != df[TMP_CPM_IMP_TARGET]))
)

# only select changed rows
cols = [
    RPT_COL_CLIENT, RPT_COL_ACCOUNT, RPT_COL_CAMPAIGN,
    TMP_START_DATE, TMP_END_DATE,
    TMP_GOAL, TMP_TARGET_IMPR_PER_SPENDVIEWS, TMP_CPM_IMP_TARGET
]
outputDf = df.loc[changed, cols].copy() \
    .rename(columns={
        TMP_START_DATE: BULK_COL_PACING_START_DATE,
        TMP_END_DATE: BULK_COL_PACING_END_DATE,
        TMP_GOAL: BULK_COL_GOAL,
        TMP_TARGET_IMPR_PER_SPENDVIEWS: BULK_COL_TARGET_IMPR_PER_SPENDVIEWS,
        TMP_CPM_IMP_TARGET: BULK_COL_CPM_IMP_TARGET
    })

print("inputDf with parsed tags", df)
print("== Campaigns with Changed Tag ==", outputDf)