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CREATE TABLE team_kingkong.offus_monthly_base_data2 AS
SELECT
  a.mt,
  a.mid_type,
  a.isindian,
  a.merchantcategory,
  a.paymethod,
  a.mcc,
  a.entity_id,
  success_users,
  refunded_success_users,
  rejected_users,
  failed_users,
  total_unique_users,
  success_merchants,
  refunded_success_merchants,
  rejected_merchants,
  failed_merchants,
  total_unique_merchants,
  success_txns,
  refunded_success_txns,
  rejected_txns,
  failed_txns,
  success_gmv,
  refunded_success_gmv,
  rejected_gmv,
  failed_gmv,
  fraud_merchants,
  refunded_fraud_merchants,
  fraud_txns,
  refunded_fraud_txns,
  fraud_gmv,
  refunded_fraud_gmv,
  CAST((fraud_gmv / success_gmv) * 10000 AS DECIMAL(18, 2)) AS gross_fts,
  CAST(
    (
      (fraud_gmv - refunded_fraud_gmv) / (success_gmv - refunded_success_gmv)
    ) * 10000 AS DECIMAL(18, 2)
  ) AS net_fts,
  cb_merchants,
  cb_txns,
  cb_gmv,
  CAST((cb_gmv / success_gmv) * 10000 AS DECIMAL(18, 2)) AS cts,
  accepted_cb_merchants,
  accepted_cb_txns,
  accepted_cb_gmv,
  defended_cb_merchants,
  defended_cb_txns,
  defended_cb_gmv,
  open_cb_merchants,
  open_cb_txns,
  open_cb_gmv,
  rec_pend_cb_merchants,
  rec_pend_cb_txns,
  rec_pend_cb_gmv
FROM
  (
    SELECT
      DISTINCT IF(
        mt < 10,
        CONCAT('0', CAST(mt AS VARCHAR)),
        CAST(mt AS VARCHAR)
      ) AS mt,
      mid_type,
      isindian,
      merchantcategory,
      paymethod,
      mcc,
      entity_id,
      COUNT(DISTINCT users) AS total_unique_users,
      COUNT(DISTINCT paytmmerchantid) AS total_unique_merchants
    FROM
      team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec2_corrected
    WHERE
      mt <> MONTH(CURRENT_DATE)
    GROUP BY
      1,
      2,
      3,
      4,
      5,
      6,
      7
  ) AS x
  LEFT JOIN (
    SELECT
      DISTINCT IF(
        mt < 10,
        CONCAT('0', CAST(mt AS VARCHAR)),
        CAST(mt AS VARCHAR)
      ) AS mt,
      mid_type,
      isindian,
      merchantcategory,
      paymethod,
      mcc,
      entity_id,
      COUNT(DISTINCT users) AS success_users,
      COUNT(DISTINCT paytmmerchantid) AS success_merchants,
      COUNT(transactionid) AS success_txns,
      SUM(txn_amount) AS success_gmv,
      COUNT(DISTINCT cb_mid) AS cb_merchants,
      COUNT(cb_txnid) AS cb_txns,
      SUM(cb_amount) AS cb_gmv,
      COUNT(DISTINCT fraud_mid) AS fraud_merchants,
      COUNT(fraud_txnid) AS fraud_txns,
      SUM(fraud_amount) AS fraud_gmv
    FROM
      team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec2_corrected
    WHERE
      actionrecommended = 'PASS'
      AND txn_status = 'SUCCESS'
      AND mt <> MONTH(CURRENT_DATE)
    GROUP BY
      1,
      2,
      3,
      4,
      5,
      6,
      7
  ) AS a ON x.mt = a.mt
  AND x.mid_type = a.mid_type
  AND a.isindian = x.isindian
  AND a.merchantcategory = x.merchantcategory
  AND a.paymethod = x.paymethod
  AND a.mcc = x.mcc
  AND a.entity_id = x.entity_id
  LEFT JOIN (
    SELECT
      DISTINCT IF(
        mt < 10,
        CONCAT('0', CAST(mt AS VARCHAR)),
        CAST(mt AS VARCHAR)
      ) AS mt,
      mid_type,
      isindian,
      merchantcategory,
      paymethod,
      mcc,
      entity_id,
      COUNT(DISTINCT users) AS failed_users,
      COUNT(DISTINCT paytmmerchantid) AS failed_merchants,
      COUNT(transactionid) AS failed_txns,
      SUM(txn_amount) AS failed_gmv
    FROM
      team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec2_corrected
    WHERE
      actionrecommended = 'PASS'
      AND txn_status = 'CLOSED'
      AND mt <> MONTH(CURRENT_DATE)
    GROUP BY
      1,
      2,
      3,
      4,
      5,
      6,
      7
  ) AS b ON a.mt = b.mt
  AND a.mid_type = b.mid_type
  AND a.isindian = b.isindian
  AND a.merchantcategory = b.merchantcategory
  AND a.paymethod = b.paymethod
  AND a.mcc = b.mcc
  AND a.entity_id = b.entity_id
  LEFT JOIN (
    SELECT
      DISTINCT IF(
        mt < 10,
        CONCAT('0', CAST(mt AS VARCHAR)),
        CAST(mt AS VARCHAR)
      ) AS mt,
      mid_type,
      isindian,
      merchantcategory,
      paymethod,
      mcc,
      entity_id,
      COUNT(DISTINCT users) AS rejected_users,
      COUNT(DISTINCT paytmmerchantid) AS rejected_merchants,
      COUNT(transactionid) AS rejected_txns,
      SUM(txn_amount) AS rejected_gmv
    FROM
      team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec2_corrected
    WHERE
      actionrecommended = 'BLOCK'
      AND mt <> MONTH(CURRENT_DATE)
    GROUP BY
      1,
      2,
      3,
      4,
      5,
      6,
      7
  ) AS c ON a.mt = c.mt
  AND a.mid_type = c.mid_type
  AND a.isindian = c.isindian
  AND a.merchantcategory = c.merchantcategory
  AND a.paymethod = c.paymethod
  AND a.mcc = c.mcc
  AND a.entity_id = c.entity_id
  LEFT JOIN (
    SELECT
      DISTINCT IF(
        mt < 10,
        CONCAT('0', CAST(mt AS VARCHAR)),
        CAST(mt AS VARCHAR)
      ) AS mt,
      mid_type,
      isindian,
      merchantcategory,
      paymethod,
      mcc,
      entity_id,
      COUNT(DISTINCT users) AS refunded_success_users,
      COUNT(DISTINCT paytmmerchantid) AS refunded_success_merchants,
      COUNT(transactionid) AS refunded_success_txns,
      SUM(txn_amount) AS refunded_success_gmv,
      COUNT(DISTINCT fraud_mid) AS refunded_fraud_merchants,
      COUNT(fraud_txnid) AS refunded_fraud_txns,
      SUM(fraud_amount) AS refunded_fraud_gmv
    FROM
      team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec2_corrected
    WHERE
      actionrecommended = 'PASS'
      AND txn_status = 'SUCCESS'
      AND refund_amount > 0
      AND mt <> MONTH(CURRENT_DATE)
    GROUP BY
      1,
      2,
      3,
      4,
      5,
      6,
      7
  ) AS d ON a.mt = d.mt
  AND a.mid_type = d.mid_type
  AND a.isindian = d.isindian
  AND a.merchantcategory = d.merchantcategory
  AND a.paymethod = d.paymethod
  AND a.mcc = d.mcc
  AND a.entity_id = d.entity_id
  LEFT JOIN (
    SELECT
      DISTINCT IF(
        mt < 10,
        CONCAT('0', CAST(mt AS VARCHAR)),
        CAST(mt AS VARCHAR)
      ) AS mt,
      mid_type,
      isindian,
      merchantcategory,
      paymethod,
      mcc,
      entity_id,
      COUNT(DISTINCT cb_mid) AS accepted_cb_merchants,
      COUNT(cb_txnid) AS accepted_cb_txns,
      SUM(cb_amount) AS accepted_cb_gmv
    FROM
      team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec2_corrected
    WHERE
      actionrecommended = 'PASS'
      AND txn_status = 'SUCCESS'
      AND final_cb_status = 'ACCEPTED'
      AND mt <> MONTH(CURRENT_DATE)
    GROUP BY
      1,
      2,
      3,
      4,
      5,
      6,
      7
  ) AS f ON a.mt = f.mt
  AND a.mid_type = f.mid_type
  AND a.isindian = f.isindian
  AND a.merchantcategory = f.merchantcategory
  AND a.paymethod = f.paymethod
  AND a.mcc = f.mcc
  AND a.entity_id = f.entity_id
  LEFT JOIN (
    SELECT
      DISTINCT IF(
        mt < 10,
        CONCAT('0', CAST(mt AS VARCHAR)),
        CAST(mt AS VARCHAR)
      ) AS mt,
      mid_type,
      isindian,
      merchantcategory,
      paymethod,
      mcc,
      entity_id,
      COUNT(DISTINCT cb_mid) AS defended_cb_merchants,
      COUNT(cb_txnid) AS defended_cb_txns,
      SUM(cb_amount) AS defended_cb_gmv
    FROM
      team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec2_corrected
    WHERE
      actionrecommended = 'PASS'
      AND txn_status = 'SUCCESS'
      AND final_cb_status = 'DEFENDED'
      AND mt <> MONTH(CURRENT_DATE)
    GROUP BY
      1,
      2,
      3,
      4,
      5,
      6,
      7
  ) AS g ON a.mt = g.mt
  AND a.mid_type = g.mid_type
  AND a.isindian = g.isindian
  AND a.merchantcategory = g.merchantcategory
  AND a.paymethod = g.paymethod
  AND a.mcc = g.mcc
  AND a.entity_id = g.entity_id
  LEFT JOIN (
    SELECT
      DISTINCT IF(
        mt < 10,
        CONCAT('0', CAST(mt AS VARCHAR)),
        CAST(mt AS VARCHAR)
      ) AS mt,
      mid_type,
      isindian,
      merchantcategory,
      paymethod,
      mcc,
      entity_id,
      COUNT(DISTINCT cb_mid) AS open_cb_merchants,
      COUNT(cb_txnid) AS open_cb_txns,
      SUM(cb_amount) AS open_cb_gmv
    FROM
      team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec2_corrected
    WHERE
      actionrecommended = 'PASS'
      AND txn_status = 'SUCCESS'
      AND final_cb_status = 'OPEN'
      AND mt <> MONTH(CURRENT_DATE)
    GROUP BY
      1,
      2,
      3,
      4,
      5,
      6,
      7
  ) AS h ON a.mt = h.mt
  AND a.mid_type = h.mid_type
  AND a.isindian = h.isindian
  AND a.merchantcategory = h.merchantcategory
  AND a.paymethod = h.paymethod
  AND a.mcc = h.mcc
  AND a.entity_id = h.entity_id
  LEFT JOIN (
    SELECT
      DISTINCT IF(
        mt < 10,
        CONCAT('0', CAST(mt AS VARCHAR)),
        CAST(mt AS VARCHAR)
      ) AS mt,
      mid_type,
      isindian,
      merchantcategory,
      paymethod,
      mcc,
      entity_id,
      COUNT(DISTINCT cb_mid) AS rec_pend_cb_merchants,
      COUNT(cb_txnid) AS rec_pend_cb_txns,
      SUM(cb_amount - cb_RecoveredAmount) AS rec_pend_cb_gmv
    FROM
      team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec2_corrected
    WHERE
      actionrecommended = 'PASS'
      AND txn_status = 'SUCCESS'
      AND final_cb_status = 'ACCEPTED'
      AND (
        cb_RecoveredAmount IS NULL
        OR cb_RecoveredAmount < cb_amount
      )
      AND mt <> MONTH(CURRENT_DATE)
    GROUP BY
      1,
      2,
      3,
      4,
      5,
      6,
      7
  ) AS i ON a.mt = i.mt
  AND a.mid_type = i.mid_type
  AND a.isindian = i.isindian
  AND a.merchantcategory = i.merchantcategory
  AND a.paymethod = i.paymethod
  AND a.mcc = i.mcc
  AND a.entity_id = i.entity_id;

team_kingkong.offus_lmtd_mtd_base_data2

#kucoinclonescript #cryptoexchangedevelopment #cryptoentrepreneurtips #blockchaindevelopment #cryptocurrencyexchange

CREATE TABLE team_kingkong.offus_lmtd_mtd_base_data2 AS
SELECT
  a.mt,
  a.mid_type,
  a.isindian,
  a.merchantcategory,
  a.paymethod,
  a.mcc,
  a.entity_id,
  success_users,
  refunded_success_users,
  rejected_users,
  failed_users,
  total_unique_users,
  success_merchants,
  refunded_success_merchants,
  rejected_merchants,
  failed_merchants,
  total_unique_merchants,
  success_txns,
  refunded_success_txns,
  rejected_txns,
  failed_txns,
  success_gmv,
  refunded_success_gmv,
  rejected_gmv,
  failed_gmv,
  fraud_merchants,
  refunded_fraud_merchants,
  fraud_txns,
  refunded_fraud_txns,
  fraud_gmv,
  refunded_fraud_gmv,
  CAST((fraud_gmv / success_gmv) * 10000 AS DECIMAL(18, 2)) AS gross_fts,
  CAST(
    (
      (fraud_gmv - refunded_fraud_gmv) / (success_gmv - refunded_success_gmv)
    ) * 10000 AS DECIMAL(18, 2)
  ) AS net_fts,
  cb_merchants,
  cb_txns,
  cb_gmv,
  CAST((cb_gmv / success_gmv) * 10000 AS DECIMAL(18, 2)) AS cts,
  accepted_cb_merchants,
  accepted_cb_txns,
  accepted_cb_gmv,
  defended_cb_merchants,
  defended_cb_txns,
  defended_cb_gmv,
  open_cb_merchants,
  open_cb_txns,
  open_cb_gmv,
  rec_pend_cb_merchants,
  rec_pend_cb_txns,
  rec_pend_cb_gmv
FROM
  (
    SELECT
      mt,
      mid_type,
      isindian,
      merchantcategory,
      paymethod,
      mcc,
      entity_id,
      COUNT(DISTINCT users) AS total_unique_users,
      COUNT(DISTINCT paytmmerchantid) AS total_unique_merchants
    FROM
      (
        SELECT
          DISTINCT IF(
            DATE(dateinserted) BETWEEN DATE'2025-02-01'
            AND DATE'2025-02-23',
            'LMTD',
            IF(
              (
                DATE(dateinserted) BETWEEN DATE'2025-03-01'
                AND DATE'2025-03-23'
              ),
              'MTD',
              'NA'
            )
          ) AS mt,
          transactionid,
          mid_type,
          isindian,
          merchantcategory,
          paymethod,
          mcc,
          entity_id,
          users,
          paytmmerchantid
        FROM
          team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec2_corrected
        WHERE
          DATE(dateinserted) >= CAST('2025-02-01' AS DATE)
      )
    GROUP BY
      1,
      2,
      3,
      4,
      5,
      6,
      7
  ) AS x
  LEFT JOIN (
    SELECT
      mt,
      mid_type,
      isindian,
      merchantcategory,
      paymethod,
      mcc,
      entity_id,
      COUNT(DISTINCT users) AS success_users,
      COUNT(DISTINCT paytmmerchantid) AS success_merchants,
      COUNT(transactionid) AS success_txns,
      SUM(txn_amount) AS success_gmv,
      COUNT(DISTINCT cb_mid) AS cb_merchants,
      COUNT(cb_txnid) AS cb_txns,
      SUM(cb_amount) AS cb_gmv,
      COUNT(DISTINCT fraud_mid) AS fraud_merchants,
      COUNT(fraud_txnid) AS fraud_txns,
      SUM(fraud_amount) AS fraud_gmv
    FROM
      (
        SELECT
          DISTINCT IF(
            DATE(dateinserted) BETWEEN DATE'2025-02-01'
            AND DATE'2025-02-23',
            'LMTD',
            IF(
              (
                DATE(dateinserted) BETWEEN DATE'2025-03-01'
                AND DATE'2025-03-23'
              ),
              'MTD',
              'NA'
            )
          ) AS mt,
          transactionid,
          mid_type,
          isindian,
          merchantcategory,
          paymethod,
          mcc,
          entity_id,
          users,
          paytmmerchantid,
          txn_amount,
          cb_mid,
          cb_txnid,
          cb_amount,
          fraud_mid,
          fraud_txnid,
          fraud_amount
        FROM
          team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec2_corrected
        WHERE
          actionrecommended = 'PASS'
          AND txn_status = 'SUCCESS'
          AND DATE(dateinserted) >= CAST('2025-02-01' AS DATE)
      )
    GROUP BY
      1,
      2,
      3,
      4,
      5,
      6,
      7
  ) AS a ON x.mt = a.mt
  AND x.mid_type = a.mid_type
  AND a.isindian = x.isindian
  AND a.merchantcategory = x.merchantcategory
  AND a.paymethod = x.paymethod
  AND a.mcc = x.mcc
  AND a.entity_id = x.entity_id
  LEFT JOIN (
    SELECT
      mt,
      mid_type,
      isindian,
      merchantcategory,
      paymethod,
      mcc,
      entity_id,
      COUNT(DISTINCT users) AS failed_users,
      COUNT(DISTINCT paytmmerchantid) AS failed_merchants,
      COUNT(transactionid) AS failed_txns,
      SUM(txn_amount) AS failed_gmv
    FROM
      (
        SELECT
          DISTINCT IF(
            DATE(dateinserted) BETWEEN DATE'2025-02-01'
            AND DATE'2025-02-23',
            'LMTD',
            IF(
              (
                DATE(dateinserted) BETWEEN DATE'2025-03-01'
                AND DATE'2025-03-23'
              ),
              'MTD',
              'NA'
            )
          ) AS mt,
          transactionid,
          mid_type,
          isindian,
          merchantcategory,
          paymethod,
          mcc,
          entity_id,
          users,
          paytmmerchantid,
          txn_amount
        FROM
          team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec2_corrected
        WHERE
          actionrecommended = 'PASS'
          AND txn_status = 'CLOSED'
          AND DATE(dateinserted) >= CAST('2025-02-01' AS DATE)
      )
    GROUP BY
      1,
      2,
      3,
      4,
      5,
      6,
      7
  ) AS b ON a.mt = b.mt
  AND a.mid_type = b.mid_type
  AND a.isindian = b.isindian
  AND a.merchantcategory = b.merchantcategory
  AND a.paymethod = b.paymethod
  AND a.mcc = b.mcc
  AND a.entity_id = b.entity_id
  LEFT JOIN (
    SELECT
      mt,
      mid_type,
      isindian,
      merchantcategory,
      paymethod,
      mcc,
      entity_id,
      COUNT(DISTINCT users) AS rejected_users,
      COUNT(DISTINCT paytmmerchantid) AS rejected_merchants,
      COUNT(transactionid) AS rejected_txns,
      SUM(txn_amount) AS rejected_gmv
    FROM
      (
        SELECT
          DISTINCT IF(
            DATE(dateinserted) BETWEEN DATE'2025-02-01'
            AND DATE'2025-02-23',
            'LMTD',
            IF(
              (
                DATE(dateinserted) BETWEEN DATE'2025-03-01'
                AND DATE'2025-03-23'
              ),
              'MTD',
              'NA'
            )
          ) AS mt,
          transactionid,
          mid_type,
          isindian,
          merchantcategory,
          paymethod,
          mcc,
          entity_id,
          users,
          paytmmerchantid,
          txn_amount
        FROM
          team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec2_corrected
        WHERE
          actionrecommended = 'BLOCK'
          AND DATE(dateinserted) >= CAST('2025-02-01' AS DATE)
      )
    GROUP BY
      1,
      2,
      3,
      4,
      5,
      6,
      7
  ) AS c ON a.mt = c.mt
  AND a.mid_type = c.mid_type
  AND a.isindian = c.isindian
  AND a.merchantcategory = c.merchantcategory
  AND a.paymethod = c.paymethod
  AND a.mcc = c.mcc
  AND a.entity_id = c.entity_id
  LEFT JOIN (
    SELECT
      mt,
      mid_type,
      isindian,
      merchantcategory,
      paymethod,
      mcc,
      entity_id,
      COUNT(DISTINCT users) AS refunded_success_users,
      COUNT(DISTINCT paytmmerchantid) AS refunded_success_merchants,
      COUNT(transactionid) AS refunded_success_txns,
      SUM(txn_amount) AS refunded_success_gmv,
      COUNT(DISTINCT fraud_mid) AS refunded_fraud_merchants,
      COUNT(fraud_txnid) AS refunded_fraud_txns,
      SUM(fraud_amount) AS refunded_fraud_gmv
    FROM
      (
        SELECT
          DISTINCT IF(
            DATE(dateinserted) BETWEEN DATE'2025-02-01'
            AND DATE'2025-02-23',
            'LMTD',
            IF(
              (
                DATE(dateinserted) BETWEEN DATE'2025-03-01'
                AND DATE'2025-03-23'
              ),
              'MTD',
              'NA'
            )
          ) AS mt,
          transactionid,
          mid_type,
          isindian,
          merchantcategory,
          paymethod,
          mcc,
          entity_id,
          users,
          paytmmerchantid,
          txn_amount,
          fraud_mid,
          fraud_txnid,
          fraud_amount
        FROM
          team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec2_corrected
        WHERE
          actionrecommended = 'PASS'
          AND txn_status = 'SUCCESS'
          AND refund_amount > 0
          AND DATE(dateinserted) >= CAST('2025-02-01' AS DATE)
      )
    GROUP BY
      1,
      2,
      3,
      4,
      5,
      6,
      7
  ) AS d ON a.mt = d.mt
  AND a.mid_type = d.mid_type
  AND a.isindian = d.isindian
  AND a.merchantcategory = d.merchantcategory
  AND a.paymethod = d.paymethod
  AND a.mcc = d.mcc
  AND a.entity_id = d.entity_id
  LEFT JOIN (
    SELECT
      mt,
      mid_type,
      isindian,
      merchantcategory,
      paymethod,
      mcc,
      entity_id,
      COUNT(DISTINCT cb_mid) AS accepted_cb_merchants,
      COUNT(cb_txnid) AS accepted_cb_txns,
      SUM(cb_amount) AS accepted_cb_gmv
    FROM
      (
        SELECT
          DISTINCT IF(
            DATE(dateinserted) BETWEEN DATE'2025-02-01'
            AND DATE'2025-02-23',
            'LMTD',
            IF(
              (
                DATE(dateinserted) BETWEEN DATE'2025-03-01'
                AND DATE'2025-03-23'
              ),
              'MTD',
              'NA'
            )
          ) AS mt,
          transactionid,
          mid_type,
          isindian,
          merchantcategory,
          paymethod,
          mcc,
          entity_id,
          cb_mid,
          cb_txnid,
          cb_amount
        FROM
          team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec2_corrected
        WHERE
          actionrecommended = 'PASS'
          AND txn_status = 'SUCCESS'
          AND final_cb_status = 'ACCEPTED'
          AND (
            (
              DATE(dateinserted) BETWEEN DATE'2025-02-01'
              AND DATE'2025-02-23'
            )
            OR (
              DATE(dateinserted) BETWEEN DATE'2025-03-01'
              AND DATE'2025-03-23'
            )
          )
      )
    GROUP BY
      1,
      2,
      3,
      4,
      5,
      6,
      7
  ) AS f ON a.mt = f.mt
  AND a.mid_type = f.mid_type
  AND a.isindian = f.isindian
  AND a.merchantcategory = f.merchantcategory
  AND a.paymethod = f.paymethod
  AND a.mcc = f.mcc
  AND a.entity_id = f.entity_id
  LEFT JOIN (
    SELECT
      mt,
      mid_type,
      isindian,
      merchantcategory,
      paymethod,
      mcc,
      entity_id,
      COUNT(DISTINCT cb_mid) AS defended_cb_merchants,
      COUNT(cb_txnid) AS defended_cb_txns,
      SUM(cb_amount) AS defended_cb_gmv
    FROM
      (
        SELECT
          DISTINCT IF(
            DATE(dateinserted) BETWEEN DATE'2025-02-01'
            AND DATE'2025-02-23',
            'LMTD',
            IF(
              (
                DATE(dateinserted) BETWEEN DATE'2025-03-01'
                AND DATE'2025-03-23'
              ),
              'MTD',
              'NA'
            )
          ) AS mt,
          transactionid,
          mid_type,
          isindian,
          merchantcategory,
          paymethod,
          mcc,
          entity_id,
          cb_mid,
          cb_txnid,
          cb_amount
        FROM
          team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec2_corrected
        WHERE
          actionrecommended = 'PASS'
          AND txn_status = 'SUCCESS'
          AND final_cb_status = 'DEFENDED'
          AND DATE(dateinserted) >= CAST('2025-02-01' AS DATE)
      )
    GROUP BY
      1,
      2,
      3,
      4,
      5,
      6,
      7
  ) AS g ON a.mt = g.mt
  AND a.mid_type = g.mid_type
  AND a.isindian = g.isindian
  AND a.merchantcategory = g.merchantcategory
  AND a.paymethod = g.paymethod
  AND a.mcc = g.mcc
  AND a.entity_id = g.entity_id
  LEFT JOIN (
    SELECT
      mt,
      mid_type,
      isindian,
      merchantcategory,
      paymethod,
      mcc,
      entity_id,
      COUNT(DISTINCT cb_mid) AS open_cb_merchants,
      COUNT(cb_txnid) AS open_cb_txns,
      SUM(cb_amount) AS open_cb_gmv
    FROM
      (
        SELECT
          DISTINCT IF(
            DATE(dateinserted) BETWEEN DATE'2025-02-01'
            AND DATE'2025-02-23',
            'LMTD',
            IF(
              (
                DATE(dateinserted) BETWEEN DATE'2025-03-01'
                AND DATE'2025-03-23'
              ),
              'MTD',
              'NA'
            )
          ) AS mt,
          transactionid,
          mid_type,
          isindian,
          merchantcategory,
          paymethod,
          mcc,
          entity_id,
          cb_mid,
          cb_txnid,
          cb_amount
        FROM
          team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec2_corrected
        WHERE
          actionrecommended = 'PASS'
          AND txn_status = 'SUCCESS'
          AND final_cb_status = 'OPEN'
          AND DATE(dateinserted) >= CAST('2025-02-01' AS DATE)
      )
    GROUP BY
      1,
      2,
      3,
      4,
      5,
      6,
      7
  ) AS h ON a.mt = h.mt
  AND a.mid_type = h.mid_type
  AND a.isindian = h.isindian
  AND a.merchantcategory = h.merchantcategory
  AND a.paymethod = h.paymethod
  AND a.mcc = h.mcc
  AND a.entity_id = h.entity_id
  LEFT JOIN (
    SELECT
      mt,
      mid_type,
      isindian,
      merchantcategory,
      paymethod,
      mcc,
      entity_id,
      COUNT(DISTINCT cb_mid) AS rec_pend_cb_merchants,
      COUNT(cb_txnid) AS rec_pend_cb_txns,
      SUM(cb_amount - cb_RecoveredAmount) AS rec_pend_cb_gmv
    FROM
      (
        SELECT
          DISTINCT IF(
            DATE(dateinserted) BETWEEN DATE'2025-02-01'
            AND DATE'2025-02-23',
            'LMTD',
            IF(
              (
                DATE(dateinserted) BETWEEN DATE'2025-03-01'
                AND DATE'2025-03-23'
              ),
              'MTD',
              'NA'
            )
          ) AS mt,
          transactionid,
          mid_type,
          isindian,
          merchantcategory,
          paymethod,
          mcc,
          entity_id,
          cb_mid,
          cb_txnid,
          cb_amount,
          cb_RecoveredAmount
        FROM
          team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec2_corrected
        WHERE
          actionrecommended = 'PASS'
          AND txn_status = 'SUCCESS'
          AND final_cb_status = 'ACCEPTED'
          AND (
            cb_RecoveredAmount IS NULL
            OR cb_RecoveredAmount < cb_amount
          )
          AND DATE(dateinserted) >= CAST('2025-02-01' AS DATE)
      )
    GROUP BY
      1,
      2,
      3,
      4,
      5,
      6,
      7
  ) AS i ON a.mt = i.mt
  AND a.mid_type = i.mid_type
  AND a.isindian = i.isindian
  AND a.merchantcategory = i.merchantcategory
  AND a.paymethod = i.paymethod
  AND a.mcc = i.mcc
  AND a.entity_id = i.entity_id;

Brisbane - What's On Comms - 31st March 2025

@FOHWellington

{
	"blocks": [
		{
			"type": "header",
			"text": {
				"type": "plain_text",
				"text": ":xerovision: :x-connect: Boost Days: What's on this week :x-connect: :xerovision:"
			}
		},
		{
			"type": "section",
			"text": {
				"type": "mrkdwn",
				"text": "Good morning Brisbane, \n\n See below for what's on this week! \n\n _*Please note that due to Xerovision this week, our Boost day has changed from Wednesday to Thursday!*_"
			}
		},
		{
			"type": "divider"
		},
		{
			"type": "header",
			"text": {
				"type": "plain_text",
				"text": ":calendar-date-31: Monday, 31st March",
				"emoji": true
			}
		},
		{
			"type": "section",
			"text": {
				"type": "mrkdwn",
				"text": "\n :meow-coffee: *Café Partnership*: Enjoy free coffee and café-style beverages from our Cafe partner *Edwards*.\n\n :Lunch: *Lunch*: provided by _Pita Pit Green Square_ from *12pm* in the kitchen.\n\n:massage:*Wellbeing*: Pilates at *SP Brisbane City* is bookable every Monday!"
			}
		},
		{
			"type": "header",
			"text": {
				"type": "plain_text",
				"text": ":calendar-date-3: Thursday, 3rd April",
				"emoji": true
			}
		},
		{
			"type": "section",
			"text": {
				"type": "mrkdwn",
				"text": "\n\n :meow-coffee: *Café Partnership*: Enjoy free coffee and café-style beverages from our Cafe partner *Edwards*. \n\n:lunch: *Morning Tea*: provided by _Say Cheese_ from *9am* in the kitchen! \n\n :xerovision: *Xerovision Streaming Party:* in the Breakout Space from *10am - 1pm* \n\n :cheers-9743: *Xerovision Social:* 3pm - 4pm in the kitchen!"
			}
		},
		{
			"type": "divider"
		},
		{
			"type": "section",
			"text": {
				"type": "mrkdwn",
				"text": "Stay tuned to this channel for more details, check out the <https://calendar.google.com/calendar/u/0?cid=Y19uY2M4cDN1NDRsdTdhczE0MDhvYjZhNnRjb0Bncm91cC5jYWxlbmRhci5nb29nbGUuY29t|*Brisbane Social Calendar*>, and get ready to Boost your workdays!\n\nLove,\nWX Team :party-wx:"
			}
		}
	]
}

#bash

Remove files not starting with...

@dphillips

rm !(.*)

// matches everything except files starting with a .

xasfdasf

@Ajay1212

https://limewire.com/?referrer=48k1433kko

#bash

Copy files through sftp/ftp via wget

@dphillips

wget -r -l 0 <ftp|sftp>://<user>:<password>@<host>/<path>/*


// -r means recursive.
// -l 0 for infinite recursion, because -r by default have recursion depth of 5.

// If the host is 'example.com' and the path is 'foo/bar' with the file 'baz.txt',
// the result will be './example.com/foo/bar/baz.txt'.

#jquery

jquery, set focus on the first enabled input or select or textarea on the page - Stack Overflow

@agungnb

$('form :input:text:visible:not(input[class*=filter]):first').focus();

#mysql

MySQL Removing Some Foreign keys - Stack Overflow

@agungnb

ALTER TABLE footable DROP FOREIGN KEY fooconstraint;

#jquery

To set the focus to the first input field

@agungnb

$(this).parent().siblings('div.bottom').find("input.post").focus();

Create a high-performance crypto exchange with the OKX clone script

@zaramarley

The OKX Clone Script is a groundbreaking solution for entrepreneurs eager to venture into cryptocurrency exchange development. With this innovative script, you can launch your own exchange platform, modeled after OKX, one of the most reliable and widely trusted platforms in the industry. The OKX Clone Script is equipped with advanced features and an intuitive user interface, ensuring that you can deliver a seamless and engaging trading experience to your users right from day one. What truly sets the OKX Clone Script apart is its flexibility and customizability. You can tailor it to meet your specific business needs and easily add new features as your platform grows. By utilizing the OKX Clone Script, you're not merely launching an exchange—you're entering a thriving industry with a ready-made, scalable solution that can evolve with your vision. Start with a proven, high-performance platform that ensures both growth and success. Don’t just follow the trend—create your own cryptocurrency exchange and position yourself as a leader in the digital asset market today! For more details, >>>

Education – Unlocking Success with the Right Support

@jeteler138

https://myassignmenthelp.expert/assignment-help-sydney.html

Education – Unlocking Success with the Right Support

@jeteler138

Education is the foundation upon which a person's future is built. It not only imparts knowledge but also shapes character, critical thinking, and problem-solving skills. A well-rounded education is crucial in preparing students for the challenges of the world and empowering them to achieve their goals. However, academic journeys often come with their own set of hurdles, from complex assignments to time management struggles. This is where support becomes invaluable.
For students in Sydney, <a href="https://myassignmenthelp.expert/assignment-help-sydney.html" target="_blank">assignment help Sydney</a> offers an essential resource. With the guidance of expert tutors and academic professionals, students can tackle assignments with greater confidence and clarity. Whether it's understanding difficult concepts or refining writing skills, assignment help services provide personalized assistance tailored to individual needs. These services also ensure that students meet deadlines and submit high-quality work, leading to better grades and academic performance.
In today&rsquo;s competitive academic environment, seeking the right help can make a significant difference. Assignment help Sydney provides not just academic support but also mentorship that nurtures a student's overall growth. By leveraging such resources, students can make the most out of their education and set themselves up for future success, whether in higher studies or the professional world. Education, when paired with the right tools and guidance, unlocks the door to endless possibilities.

Unlocking Opportunities: The Power of Online Education in the UK

@jannalopez

https://www.uniccm.com

Sports Betting App Development Company

@Olivecarter

https://innosoft.ae/sports-betting-app-development-company/

A Guide to Effortless Crypto Platform Development

@janetbrownjb

https://www.coinsclone.com/kucoin-clone-script/

#metamaskwallet clone script #metamaskclone script #metamaskclone software #metamask clone app #metamaskclone development #white-labelmetamask clone solutions

Metamask Wallet Clone Script - Addus Technologies

@Seraphina

Using our trustworthy Metamask Wallet Clone Script, you can create your own cryptocurrency wallet similar to Metamask. With this ready-made solution, you can easily build a secure and feature-rich crypto wallet. Whether you're an entrepreneur or an investor, now is your moment to enter the cryptocurrency market. Learn more about our Metamask Wallet Clone Script and get started now!

#php #javascript #mysql #css

Upwork Clone Website – Launch Your Own Freelance Marketplace

@freelancerclone

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OFFUS Dec onwards txn query for KPI base

create table team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec_Feb2 as
select g.*, h.final_status as final_cb_status, h.MID as cb_mid, h.txn_id as cb_txnid,
h.amount as cb_amount, h.RecoveredAmount as cb_RecoveredAmount, k.mid as fraud_mid,
k.txn_id as fraud_txnid, k.txn_amount as fraud_amount, k.refund_amount as refunded_fraud_gmv
from
--- creating olap from pgolap and M* flattened ---
(select distinct c., d. from
    (select a.*, f.channel, case when edc_mid is not null then 'EDC' else 'QR' end as mid_type from
        (SELECT DISTINCT pg_mid, channel from cdo.total_offline_merchant_base_snapshot_v3) f
    join
        (select distinct actionrecommended, cardtype,   corporatecard, dateinserted,
        isindian, isupicc, merchantcategory, merchantid, merchantsubcategory, paymethod,
        paytmmerchantid, prepaidcard, transactionid, userid, vpa,
        month(dateinserted) as mt, case when paymethod = 'UPI' then vpa
        when paymethod in ('CREDIT_CARD', 'DEBIT_CARD','EMI','EMI_DC') then globalcardindex end as users,
        cast(eventamount as double)/100 as txn_amount
        from cdp_risk_transform.maquette_flattened_offus_snapshot_v3
        where dl_last_updated >= date '2024-12-01'
        and paymethod in ('UPI','CREDIT_CARD','DEBIT_CARD','EMI','EMI_DC')) a
    on a.paytmmerchantid = f.pg_mid
    LEFT JOIN
        -- LIST OF EDC MX
        (SELECT DISTINCT mid AS edc_mid FROM paytmpgdb.entity_edc_info_snapshot_v3
        WHERE terminal_status = 'ACTIVE' AND dl_last_updated >= DATE '2010-01-01') b
    ON a.paytmmerchantid = b.edc_mid)c
left join
    -- TABLE TO GET STATUS OF TXN
    (select distinct refund_amount, txn_id, txn_started_at, txn_status
    from dwh.pg_olap
    where ingest_date >= date '2024-12-01'
    and txn_started_at >= date '2024-12-01'
    and txn_status in ('SUCCESS','CLOSED'))d
on c.transactionid = d.txn_id) g
left join
    --- mapping data with CB Data ---
    (select * from
    (select distinct a.*, ROW_NUMBER() OVER (PARTITION BY txn_id ORDER BY
    CASE WHEN final_status = 'ACCEPTED' THEN 1
    WHEN final_status IN ('OPEN', 'DEFENDED') THEN 2 ELSE 3 END,
    Intimation_Date DESC) AS row_num
    from
(SELECT distinct a.dispute_id, a.transaction_date AS Txn_Date, a.transaction_id as txn_id,
CASE WHEN a.from_status='ACCEPT' AND a.to_status='CLOSED' THEN 'ACCEPTED'
WHEN a.from_status='DEFEND' AND a.to_status='CLOSED' THEN 'DEFENDED'
WHEN a.from_status='PROCESSING' AND a.to_status='ACCEPT' THEN 'ACCEPTED'
WHEN a.from_status='POD_UPLOAD' AND a.to_status='DEFEND' THEN 'DEFENDED'
WHEN a.from_status='POD_UPLOAD' AND a.to_status='ACCEPT' THEN 'ACCEPTED'
WHEN a.from_status='POD_REJECT' AND a.to_status='ACCEPT' THEN 'ACCEPTED'
WHEN a.from_status='INIT' AND a.to_status='PROCESSING' THEN 'OPEN'
ELSE 'OPEN' END AS final_status, a.created_on as Intimation_Date,
CAST(b.original_amount AS DECIMAL (18,2)) / 100 as amount,
b.payer_id as MID, CAST(b.recovered_amount AS DECIMAL (18,2)) / 100 as RecoveredAmount,
b.merchant_trans_id as Order_ID
FROM pgplusbo.chargeback_details_snapshot_v3 a
JOIN
pgaws_datalake_prod2.ded_order_snapshot_v3 b
ON a.dispute_id = b.bill_id
WHERE a.dl_last_updated >= date '2024-12-01'
AND b.dl_last_updated >= date '2024-12-01'
and date(transaction_date) >= date '2024-12-01') a
)x where row_num = 1) h
on g.transactionid = h.txn_id
left join
--- mapping data with Fraud Data ---
(select * from
(select distinct old_pg_txn_id as txn_id, cast(old_pg_txn_amount as double) as txn_amount,
date(old_pg_txn_started_at) as txn_date, old_pg_mid as mid,
min(reporting_date) as reporting_date
from frauds.fraud_combined_snapshot_v3
where old_pg_ingest_date >= date'2024-12-01'
and dl_last_updated >= date'2024-12-01'
and date(old_pg_txn_started_at) >= date'2024-12-01'
and ((table_name in ('ppsl_cybercell','ro_panel_cybmerchant_details_with_pg_olap',
'lending_fraud','efrm','ppsl_bank_escalations','ro_panel_minifmr_l2_PPI',
'ro_panel_minifmr_l2_BNK')) or
(sources_concatenated like '%ppsl_cybercell%'
or sources_concatenated like '%ro_panel_cybmerchant_details_with_pg_olap%'
or sources_concatenated like '%lending_fraud%'
or sources_concatenated like '%efrm%'
or sources_concatenated like '%ppsl_bank_escalations%'
or sources_concatenated like '%ro_panel_minifmr_l2_PPI%'
or sources_concatenated like '%ro_panel_minifmr_l2_BNK%'))
and old_pg_txn_status = 'SUCCESS' AND cast(old_pg_txn_amount as double) > 0
AND old_pg_txn_id IS NOT NULL
group by 1,2,3,4) i
left join
(SELECT distinct acq_id, CAST(refund_amount AS DOUBLE) / 100 AS refund_amount
FROM pgaws_datalake_prod.acq_refund_snapshot_v3
WHERE dl_last_updated >= date'2024-12-01' AND refund_status = 'SUCCESS') j
ON i.txn_id = j.acq_id) k
on g.transactionid = k.txn_id;



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


create table team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec2 as
select DISTINCT g.*, h.final_status as final_cb_status, h.MID as cb_mid, h.txn_id as cb_txnid,
h.amount as cb_amount, h.RecoveredAmount as cb_RecoveredAmount, k.mid as fraud_mid,
k.txn_id as fraud_txnid, k.txn_amount as fraud_amount, k.refund_amount as refunded_fraud_gmv
from
--- creating olap from pgolap and M* flattened ---
(select distinct c.*, d.* from
(select a.*, f.channel, case when edc_mid is not null then 'EDC' else 'QR' end as mid_type
from
(SELECT DISTINCT pg_mid, channel from cdo.total_offline_merchant_base_snapshot_v3) f
join
(select distinct actionrecommended, dateinserted, merchantcategory, isindian,
merchantsubcategory, paymethod, paytmmerchantid, transactionid,
month(dateinserted) as mt, case when paymethod = 'UPI' then vpa
when paymethod in ('CREDIT_CARD', 'DEBIT_CARD','EMI','EMI_DC') then globalcardindex end as users,
cast(eventamount as double)/100 as txn_amount
from cdp_risk_transform.maquette_flattened_offus_snapshot_v3
where dl_last_updated BETWEEN date '2024-12-01' AND date '2024-12-31'
and paymethod in ('UPI','CREDIT_CARD','DEBIT_CARD','EMI','EMI_DC')
group by 1,2,3,4,5,6,7,8,9,10, 11) a
on a.paytmmerchantid = f.pg_mid
LEFT JOIN
(SELECT DISTINCT mid AS edc_mid FROM paytmpgdb.entity_edc_info_snapshot_v3
WHERE terminal_status = 'ACTIVE' AND dl_last_updated >= DATE '2010-01-01') b
ON a.paytmmerchantid = b.edc_mid
)c
left join
(select distinct refund_amount, txn_id, txn_status, mcc, entity_id
from dwh.pg_olap
where ingest_date BETWEEN date '2024-12-01' AND date '2024-12-31'
and txn_started_at BETWEEN date '2024-12-01' AND date '2024-12-31'
and txn_status in ('SUCCESS','CLOSED'))d
on c.transactionid = d.txn_id) g


left join
--- mapping data with CB Data ---
(select * from
(select distinct a.*, ROW_NUMBER() OVER (PARTITION BY txn_id ORDER BY
CASE WHEN final_status = 'ACCEPTED' THEN 1
WHEN final_status IN ('OPEN', 'DEFENDED') THEN 2 ELSE 3 END,
Intimation_Date DESC) AS row_num
from
(SELECT distinct a.dispute_id, a.transaction_date AS Txn_Date, a.transaction_id as txn_id,
CASE WHEN a.from_status='ACCEPT' AND a.to_status='CLOSED' THEN 'ACCEPTED'
WHEN a.from_status='DEFEND' AND a.to_status='CLOSED' THEN 'DEFENDED'
WHEN a.from_status='PROCESSING' AND a.to_status='ACCEPT' THEN 'ACCEPTED'
WHEN a.from_status='POD_UPLOAD' AND a.to_status='DEFEND' THEN 'DEFENDED'
WHEN a.from_status='POD_UPLOAD' AND a.to_status='ACCEPT' THEN 'ACCEPTED'
WHEN a.from_status='POD_REJECT' AND a.to_status='ACCEPT' THEN 'ACCEPTED'
WHEN a.from_status='INIT' AND a.to_status='PROCESSING' THEN 'OPEN'
ELSE 'OPEN' END AS final_status, a.created_on as Intimation_Date,
CAST(b.original_amount AS DECIMAL (18,2)) / 100 as amount,
b.payer_id as MID, CAST(b.recovered_amount AS DECIMAL (18,2)) / 100 as RecoveredAmount,
b.merchant_trans_id as Order_ID
FROM pgplusbo.chargeback_details_snapshot_v3 a
JOIN
pgaws_datalake_prod2.ded_order_snapshot_v3 b
ON a.dispute_id = b.bill_id
WHERE a.dl_last_updated BETWEEN date '2024-12-01' AND date '2024-12-31'
and date(transaction_date) BETWEEN date '2024-12-01' AND date '2024-12-31'
AND b.dl_last_updated >= date '2024-12-01') a
)x where row_num = 1) h
on g.transactionid = h.txn_id


left join
--- mapping data with Fraud Data ---
(select * from
(select distinct old_pg_txn_id as txn_id, cast(old_pg_txn_amount as double) as txn_amount,
date(old_pg_txn_started_at) as txn_date, old_pg_mid as mid,
min(reporting_date) as reporting_date
from frauds.fraud_combined_snapshot_v3
where old_pg_ingest_date >= date'2024-12-01'
and dl_last_updated >= date'2024-12-01'
and date(old_pg_txn_started_at) >= date'2024-12-01'
and ((table_name in ('ppsl_cybercell','ro_panel_cybmerchant_details_with_pg_olap',
'lending_fraud','efrm','ppsl_bank_escalations','ro_panel_minifmr_l2_PPI',
'ro_panel_minifmr_l2_BNK')) or
(sources_concatenated like '%ppsl_cybercell%'
or sources_concatenated like '%ro_panel_cybmerchant_details_with_pg_olap%'
or sources_concatenated like '%lending_fraud%'
or sources_concatenated like '%efrm%'
or sources_concatenated like '%ppsl_bank_escalations%'
or sources_concatenated like '%ro_panel_minifmr_l2_PPI%'
or sources_concatenated like '%ro_panel_minifmr_l2_BNK%'))
and old_pg_txn_status = 'SUCCESS' AND cast(old_pg_txn_amount as double) > 0
AND old_pg_txn_id IS NOT NULL
group by 1,2,3,4) i
left join
(SELECT distinct acq_id, CAST(refund_amount AS DOUBLE) / 100 AS refund_amount
FROM pgaws_datalake_prod.acq_refund_snapshot_v3
WHERE dl_last_updated >= date'2024-12-01' AND refund_status = 'SUCCESS') j
ON i.txn_id = j.acq_id) k
on g.transactionid = k.txn_id ;

OFFUS lmtd mtd base query corrected

SELECT
  a.mt,
  a.mid_type,
  success_users,
  refunded_success_users,
  rejected_users,
  failed_users,
  total_unique_users,
  success_merchants,
  refunded_success_merchants,
  rejected_merchants,
  failed_merchants,
  total_unique_merchants,
  success_txns,
  refunded_success_txns,
  rejected_txns,
  failed_txns,
  success_gmv,
  refunded_success_gmv,
  rejected_gmv,
  failed_gmv,
  fraud_merchants,
  refunded_fraud_merchants,
  fraud_txns,
  refunded_fraud_txns,
  fraud_gmv,
  refunded_fraud_gmv,
  CAST((fraud_gmv / success_gmv) * 10000 AS DECIMAL(18, 2)) AS gross_fts,
  CAST(
    (
      (fraud_gmv - refunded_fraud_gmv) / (success_gmv - refunded_success_gmv)
    ) * 10000 AS DECIMAL(18, 2)
  ) AS net_fts,
  cb_merchants,
  cb_txns,
  cb_gmv,
  CAST((cb_gmv / success_gmv) * 10000 AS DECIMAL(18, 2)) AS cts,
  accepted_cb_merchants,
  accepted_cb_txns,
  accepted_cb_gmv,
  defended_cb_merchants,
  defended_cb_txns,
  defended_cb_gmv,
  open_cb_merchants,
  open_cb_txns,
  open_cb_gmv,
  rec_pend_cb_merchants,
  rec_pend_cb_txns,
  rec_pend_cb_gmv
FROM
  (
    SELECT
      mt,
      mid_type,
      COUNT(DISTINCT users) AS total_unique_users,
      COUNT(DISTINCT paytmmerchantid) AS total_unique_merchants
    FROM
      (
        SELECT
          DISTINCT IF(
            dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', ADD_MONTHS(CURRENT_DATE, -1)))
            AND ADD_MONTHS(CURRENT_DATE - INTERVAL '1' DAY, -1),
            'LMTD',
            IF(
              (
                dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', CURRENT_DATE))
                AND DATE(CURRENT_DATE - INTERVAL '1' DAY)
              ),
              'MTD',
              'NA'
            )
          ) AS mt,
          mid_type,
          users,
          paytmmerchantid
        FROM
          team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec
        WHERE
          (
            (
              dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', ADD_MONTHS(CURRENT_DATE, -1)))
              AND ADD_MONTHS(CURRENT_DATE - INTERVAL '1' DAY, -1)
            )
            OR (
              dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', CURRENT_DATE))
              AND DATE(CURRENT_DATE - INTERVAL '1' DAY)
            )
          )
      )
    GROUP BY
      1,
      2
  ) AS x
  LEFT JOIN (
    SELECT
      mt,
      mid_type,
      COUNT(DISTINCT users) AS success_users,
      COUNT(DISTINCT paytmmerchantid) AS success_merchants,
      COUNT(transactionid) AS success_txns,
      SUM(txn_amount) AS success_gmv,
      COUNT(DISTINCT cb_mid) AS cb_merchants,
      COUNT(cb_txnid) AS cb_txns,
      SUM(cb_amount) AS cb_gmv,
      COUNT(DISTINCT fraud_mid) AS fraud_merchants,
      COUNT(fraud_txnid) AS fraud_txns,
      SUM(fraud_amount) AS fraud_gmv
    FROM
      (
        SELECT
          DISTINCT IF(
            dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', ADD_MONTHS(CURRENT_DATE, -1)))
            AND ADD_MONTHS(CURRENT_DATE - INTERVAL '1' DAY, -1),
            'LMTD',
            IF(
              (
                dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', CURRENT_DATE))
                AND DATE(CURRENT_DATE - INTERVAL '1' DAY)
              ),
              'MTD',
              'NA'
            )
          ) AS mt,
          mid_type,
          users,
          paytmmerchantid,
          transactionid,
          txn_amount,
          cb_mid,
          cb_txnid,
          cb_amount,
          fraud_mid,
          fraud_txnid,
          fraud_amount
        FROM
          team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec
        WHERE
          actionrecommended = 'PASS'
          AND txn_status = 'SUCCESS'
          AND (
            (
              dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', ADD_MONTHS(CURRENT_DATE, -1)))
              AND ADD_MONTHS(CURRENT_DATE - INTERVAL '1' DAY, -1)
            )
            OR (
              dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', CURRENT_DATE))
              AND DATE(CURRENT_DATE - INTERVAL '1' DAY)
            )
          )
      )
    GROUP BY
      1,
      2
  ) AS a ON x.mt = a.mt
  AND x.mid_type = a.mid_type
  LEFT JOIN (
    SELECT
      mt,
      mid_type,
      COUNT(DISTINCT users) AS failed_users,
      COUNT(DISTINCT paytmmerchantid) AS failed_merchants,
      COUNT(transactionid) AS failed_txns,
      SUM(txn_amount) AS failed_gmv
    FROM
      (
        SELECT
          DISTINCT IF(
            dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', ADD_MONTHS(CURRENT_DATE, -1)))
            AND ADD_MONTHS(CURRENT_DATE - INTERVAL '1' DAY, -1),
            'LMTD',
            IF(
              (
                dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', CURRENT_DATE))
                AND DATE(CURRENT_DATE - INTERVAL '1' DAY)
              ),
              'MTD',
              'NA'
            )
          ) AS mt,
          mid_type,
          users,
          paytmmerchantid,
          transactionid,
          txn_amount
        FROM
          team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec
        WHERE
          actionrecommended = 'PASS'
          AND txn_status = 'CLOSED'
          AND (
            (
              dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', ADD_MONTHS(CURRENT_DATE, -1)))
              AND ADD_MONTHS(CURRENT_DATE - INTERVAL '1' DAY, -1)
            )
            OR (
              dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', CURRENT_DATE))
              AND DATE(CURRENT_DATE - INTERVAL '1' DAY)
            )
          )
      )
    GROUP BY
      1,
      2
  ) AS b ON a.mt = b.mt
  AND a.mid_type = b.mid_type
  LEFT JOIN (
    SELECT
      mt,
      mid_type,
      COUNT(DISTINCT users) AS rejected_users,
      COUNT(DISTINCT paytmmerchantid) AS rejected_merchants,
      COUNT(transactionid) AS rejected_txns,
      SUM(txn_amount) AS rejected_gmv
    FROM
      (
        SELECT
          DISTINCT IF(
            dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', ADD_MONTHS(CURRENT_DATE, -1)))
            AND ADD_MONTHS(CURRENT_DATE - INTERVAL '1' DAY, -1),
            'LMTD',
            IF(
              (
                dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', CURRENT_DATE))
                AND DATE(CURRENT_DATE - INTERVAL '1' DAY)
              ),
              'MTD',
              'NA'
            )
          ) AS mt,
          mid_type,
          users,
          paytmmerchantid,
          transactionid,
          txn_amount
        FROM
          team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec
        WHERE
          actionrecommended = 'BLOCK'
          AND (
            (
              dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', ADD_MONTHS(CURRENT_DATE, -1)))
              AND ADD_MONTHS(CURRENT_DATE - INTERVAL '1' DAY, -1)
            )
            OR (
              dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', CURRENT_DATE))
              AND DATE(CURRENT_DATE - INTERVAL '1' DAY)
            )
          )
      )
    GROUP BY
      1,
      2
  ) AS c ON a.mt = c.mt
  AND a.mid_type = c.mid_type
  LEFT JOIN (
    SELECT
      mt,
      mid_type,
      COUNT(DISTINCT users) AS refunded_success_users,
      COUNT(DISTINCT paytmmerchantid) AS refunded_success_merchants,
      COUNT(transactionid) AS refunded_success_txns,
      SUM(txn_amount) AS refunded_success_gmv,
      COUNT(DISTINCT fraud_mid) AS refunded_fraud_merchants,
      COUNT(fraud_txnid) AS refunded_fraud_txns,
      SUM(fraud_amount) AS refunded_fraud_gmv
    FROM
      (
        SELECT
          DISTINCT IF(
            dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', ADD_MONTHS(CURRENT_DATE, -1)))
            AND ADD_MONTHS(CURRENT_DATE - INTERVAL '1' DAY, -1),
            'LMTD',
            IF(
              (
                dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', CURRENT_DATE))
                AND DATE(CURRENT_DATE - INTERVAL '1' DAY)
              ),
              'MTD',
              'NA'
            )
          ) AS mt,
          mid_type,
          users,
          paytmmerchantid,
          transactionid,
          txn_amount,
          fraud_mid,
          fraud_txnid,
          fraud_amount
        FROM
          team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec
        WHERE
          actionrecommended = 'PASS'
          AND txn_status = 'SUCCESS'
          AND refund_amount > 0
          AND (
            (
              dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', ADD_MONTHS(CURRENT_DATE, -1)))
              AND ADD_MONTHS(CURRENT_DATE - INTERVAL '1' DAY, -1)
            )
            OR (
              dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', CURRENT_DATE))
              AND DATE(CURRENT_DATE - INTERVAL '1' DAY)
            )
          )
      )
    GROUP BY
      1,
      2
  ) AS d ON a.mt = d.mt
  AND a.mid_type = d.mid_type
  LEFT JOIN (
    SELECT
      mt,
      mid_type,
      COUNT(DISTINCT cb_mid) AS accepted_cb_merchants,
      COUNT(cb_txnid) AS accepted_cb_txns,
      SUM(cb_amount) AS accepted_cb_gmv
    FROM
      (
        SELECT
          DISTINCT IF(
            dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', ADD_MONTHS(CURRENT_DATE, -1)))
            AND ADD_MONTHS(CURRENT_DATE - INTERVAL '1' DAY, -1),
            'LMTD',
            IF(
              (
                dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', CURRENT_DATE))
                AND DATE(CURRENT_DATE - INTERVAL '1' DAY)
              ),
              'MTD',
              'NA'
            )
          ) AS mt,
          mid_type,
          cb_mid,
          cb_txnid,
          cb_amount
        FROM
          team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec
        WHERE
          actionrecommended = 'PASS'
          AND txn_status = 'SUCCESS'
          AND final_cb_status = 'ACCEPTED'
          AND (
            (
              dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', ADD_MONTHS(CURRENT_DATE, -1)))
              AND ADD_MONTHS(CURRENT_DATE - INTERVAL '1' DAY, -1)
            )
            OR (
              dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', CURRENT_DATE))
              AND DATE(CURRENT_DATE - INTERVAL '1' DAY)
            )
          )
      )
    GROUP BY
      1,
      2
  ) AS f ON a.mt = f.mt
  AND a.mid_type = f.mid_type
  LEFT JOIN (
    SELECT
      mt,
      mid_type,
      COUNT(DISTINCT cb_mid) AS defended_cb_merchants,
      COUNT(cb_txnid) AS defended_cb_txns,
      SUM(cb_amount) AS defended_cb_gmv
    FROM
      (
        SELECT
          DISTINCT IF(
            dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', ADD_MONTHS(CURRENT_DATE, -1)))
            AND ADD_MONTHS(CURRENT_DATE - INTERVAL '1' DAY, -1),
            'LMTD',
            IF(
              (
                dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', CURRENT_DATE))
                AND DATE(CURRENT_DATE - INTERVAL '1' DAY)
              ),
              'MTD',
              'NA'
            )
          ) AS mt,
          mid_type,
          cb_mid,
          cb_txnid,
          cb_amount
        FROM
          team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec
        WHERE
          actionrecommended = 'PASS'
          AND txn_status = 'SUCCESS'
          AND final_cb_status = 'DEFENDED'
          AND (
            (
              dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', ADD_MONTHS(CURRENT_DATE, -1)))
              AND ADD_MONTHS(CURRENT_DATE - INTERVAL '1' DAY, -1)
            )
            OR (
              dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', CURRENT_DATE))
              AND DATE(CURRENT_DATE - INTERVAL '1' DAY)
            )
          )
      )
    GROUP BY
      1,
      2
  ) AS g ON a.mt = g.mt
  AND a.mid_type = g.mid_type
  LEFT JOIN (
    SELECT
      mt,
      mid_type,
      COUNT(DISTINCT cb_mid) AS open_cb_merchants,
      COUNT(cb_txnid) AS open_cb_txns,
      SUM(cb_amount) AS open_cb_gmv
    FROM
      (
        SELECT
          DISTINCT IF(
            dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', ADD_MONTHS(CURRENT_DATE, -1)))
            AND ADD_MONTHS(CURRENT_DATE - INTERVAL '1' DAY, -1),
            'LMTD',
            IF(
              (
                dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', CURRENT_DATE))
                AND DATE(CURRENT_DATE - INTERVAL '1' DAY)
              ),
              'MTD',
              'NA'
            )
          ) AS mt,
          mid_type,
          cb_mid,
          cb_txnid,
          cb_amount
        FROM
          team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec
        WHERE
          actionrecommended = 'PASS'
          AND txn_status = 'SUCCESS'
          AND final_cb_status = 'OPEN'
          AND (
            (
              dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', ADD_MONTHS(CURRENT_DATE, -1)))
              AND ADD_MONTHS(CURRENT_DATE - INTERVAL '1' DAY, -1)
            )
            OR (
              dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', CURRENT_DATE))
              AND DATE(CURRENT_DATE - INTERVAL '1' DAY)
            )
          )
      )
    GROUP BY
      1,
      2
  ) AS h ON a.mt = h.mt
  AND a.mid_type = h.mid_type
  LEFT JOIN (
    SELECT
      mt,
      mid_type,
      COUNT(DISTINCT cb_mid) AS rec_pend_cb_merchants,
      COUNT(cb_txnid) AS rec_pend_cb_txns,
      SUM(cb_amount - cb_RecoveredAmount) AS rec_pend_cb_gmv
    FROM
      (
        SELECT
          DISTINCT IF(
            dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', ADD_MONTHS(CURRENT_DATE, -1)))
            AND ADD_MONTHS(CURRENT_DATE - INTERVAL '1' DAY, -1),
            'LMTD',
            IF(
              (
                dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', CURRENT_DATE))
                AND DATE(CURRENT_DATE - INTERVAL '1' DAY)
              ),
              'MTD',
              'NA'
            )
          ) AS mt,
          mid_type,
          cb_mid,
          cb_txnid,
          cb_amount,
          cb_RecoveredAmount
        FROM
          team_kingkong.rohit_edc_qr_users_wCB_wFraud_Dec
        WHERE
          actionrecommended = 'PASS'
          AND txn_status = 'SUCCESS'
          AND final_cb_status = 'ACCEPTED'
          AND (
            cb_RecoveredAmount IS NULL
            OR cb_RecoveredAmount < cb_amount
          )
          AND (
            (
              dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', ADD_MONTHS(CURRENT_DATE, -1)))
              AND ADD_MONTHS(CURRENT_DATE - INTERVAL '1' DAY, -1)
            )
            OR (
              dateinserted BETWEEN DATE(DATE_TRUNC('MONTH', CURRENT_DATE))
              AND DATE(CURRENT_DATE - INTERVAL '1' DAY)
            )
          )
      )
    GROUP BY
      1,
      2
  ) AS i ON a.mt = i.mt
  AND a.mid_type = i.mid_type

SDK

@Taimoor

1. Clone the Repository
git clone https://github.com/fananimi/pyzk.git
cd pyzk
pip install .

OR, if you want to install directly from GitHub without cloning:

pip install git+https://github.com/fananimi/pyzk.git

Expert Mold Removal and Remediation Services in Florida: Protect Your Home and Health

@themoldguys

Professional mold removal & remediation in Florida. Keep your home safe & healthy with expert inspection and treatment. Reliable & thorough service!

Mold Removal in Florida: Why You Need Professional Help
Florida’s warm and humid climate is a perfect breeding ground for mold, making it a common problem in many homes and businesses across the state. Whether it’s a small patch in the bathroom or a more significant issue in your crawl spaces, mold can quickly become a serious concern if left untreated. At The Mold Guys, we specialize in professional mold removal and remediation services, helping residents and business owners protect their properties from the dangers of mold growth.
What is Mold Remediation?
Mold remediation, also known as mold removal or mold abatement, is the process of identifying, containing, and eliminating mold from affected areas. It’s a critical step to prevent further growth and to protect the health of the people living or working in the space. Mold thrives in damp, humid environments, often invading areas like bathrooms, kitchens, crawl spaces, basements, and places with water leaks.
While mold may start as a minor inconvenience, it can lead to significant damage if not addressed in a timely manner. The Mold Guys are your trusted mold removal experts in Florida, equipped to handle mold issues of all sizes quickly and professionally.
Is Mold Dangerous?
Mold isn’t just an eyesore—it can be a health hazard. While some types of mold are relatively harmless, others, particularly black mold, can be extremely toxic. Black mold produces mycotoxins that can enter the air, posing significant risks to anyone who comes into contact with it. These toxins can cause a variety of health problems, including:
Chronic sinus infections
Breathing difficulties
Fatigue
Headaches
Asthma flare-ups
Aggravation of respiratory conditions like COPD
The health risks associated with mold make it imperative to address the issue as soon as possible. Even if you don't see black mold, other types of mold can still lead to respiratory problems, skin irritation, and other health concerns.
Why Should You Hire Professionals for Mold Removal?
While it might be tempting to tackle mold removal on your own, DIY mold removal can be risky. Inadequate cleaning methods can spread spores, making the problem worse. Mold can also hide in places that are difficult to reach or notice, such as behind walls or under floors. At The Mold Guys, our experienced team uses industry-standard equipment and techniques to ensure mold is properly removed and prevented from returning.
By hiring professionals, you’ll not only eliminate the mold but also ensure the affected areas are thoroughly cleaned and treated. We also use advanced tools to identify hidden mold that might not be visible to the naked eye. This comprehensive approach helps us create a safe, mold-free environment for you and your family or employees.
How to Spot Mold in Your Home or Business
Mold often grows in areas with high moisture levels, so it's essential to stay vigilant for any signs that mold may be developing. Common places where mold is found include:
Bathrooms: Due to high humidity levels and frequent water use, bathrooms are prime spots for mold growth.
Kitchens: Leaky pipes, wet dish towels, and standing water can provide a perfect environment for mold.
Crawl Spaces and Basements: These areas are often poorly ventilated and prone to moisture buildup, making them ideal breeding grounds for mold.
Floorboards and Walls: Water leaks from windows, roofs, or plumbing can lead to mold growth in walls and under flooring.
If you notice musty odors, visible mold spots, or an increase in respiratory issues, it’s time to call the experts at The Mold Guys for a professional assessment.
Preventing Mold Growth
Once mold has been removed, it’s important to take steps to prevent future growth. Moisture control is the key to keeping your home or business safe. Some preventative measures include:
Fixing leaks promptly to prevent water from seeping into walls and floors.
Improving ventilation in high-moisture areas like bathrooms and kitchens.
Using dehumidifiers to control indoor humidity, especially in areas with poor airflow.
Regular inspections of crawl spaces, basements, and other high-risk areas.
These steps, combined with professional mold removal services, will help ensure your property stays mold-free for the long term.
Get Professional Mold Removal with The Mold Guys
If you suspect that mold is affecting your home or business, don’t wait until it becomes a bigger problem. The Mold Guys are ready to help with quick and effective mold removal services in Florida. With hundreds of satisfied customers and a reputation for professionalism, we’re the team you can trust to restore your property to a safe, healthy condition.
Call us today.
Let us help you eliminate mold and bring peace of mind back to your property.

Expert Mold Removal and Remediation Services in Florida: Protect Your Home and Health

@themoldguys

Professional mold removal & remediation in Florida. Keep your home safe & healthy with expert inspection and treatment. Reliable & thorough service!

Mold Removal in Florida: Why You Need Professional Help
Florida’s warm and humid climate is a perfect breeding ground for mold, making it a common problem in many homes and businesses across the state. Whether it’s a small patch in the bathroom or a more significant issue in your crawl spaces, mold can quickly become a serious concern if left untreated. At The Mold Guys, we specialize in professional mold removal and remediation services, helping residents and business owners protect their properties from the dangers of mold growth.
What is Mold Remediation?
Mold remediation, also known as mold removal or mold abatement, is the process of identifying, containing, and eliminating mold from affected areas. It’s a critical step to prevent further growth and to protect the health of the people living or working in the space. Mold thrives in damp, humid environments, often invading areas like bathrooms, kitchens, crawl spaces, basements, and places with water leaks.
While mold may start as a minor inconvenience, it can lead to significant damage if not addressed in a timely manner. The Mold Guys are your trusted mold removal experts in Florida, equipped to handle mold issues of all sizes quickly and professionally.
Is Mold Dangerous?
Mold isn’t just an eyesore—it can be a health hazard. While some types of mold are relatively harmless, others, particularly black mold, can be extremely toxic. Black mold produces mycotoxins that can enter the air, posing significant risks to anyone who comes into contact with it. These toxins can cause a variety of health problems, including:
Chronic sinus infections
Breathing difficulties
Fatigue
Headaches
Asthma flare-ups
Aggravation of respiratory conditions like COPD
The health risks associated with mold make it imperative to address the issue as soon as possible. Even if you don't see black mold, other types of mold can still lead to respiratory problems, skin irritation, and other health concerns.
Why Should You Hire Professionals for Mold Removal?
While it might be tempting to tackle mold removal on your own, DIY mold removal can be risky. Inadequate cleaning methods can spread spores, making the problem worse. Mold can also hide in places that are difficult to reach or notice, such as behind walls or under floors. At The Mold Guys, our experienced team uses industry-standard equipment and techniques to ensure mold is properly removed and prevented from returning.
By hiring professionals, you’ll not only eliminate the mold but also ensure the affected areas are thoroughly cleaned and treated. We also use advanced tools to identify hidden mold that might not be visible to the naked eye. This comprehensive approach helps us create a safe, mold-free environment for you and your family or employees.
How to Spot Mold in Your Home or Business
Mold often grows in areas with high moisture levels, so it's essential to stay vigilant for any signs that mold may be developing. Common places where mold is found include:
Bathrooms: Due to high humidity levels and frequent water use, bathrooms are prime spots for mold growth.
Kitchens: Leaky pipes, wet dish towels, and standing water can provide a perfect environment for mold.
Crawl Spaces and Basements: These areas are often poorly ventilated and prone to moisture buildup, making them ideal breeding grounds for mold.
Floorboards and Walls: Water leaks from windows, roofs, or plumbing can lead to mold growth in walls and under flooring.
If you notice musty odors, visible mold spots, or an increase in respiratory issues, it’s time to call the experts at The Mold Guys for a professional assessment.
Preventing Mold Growth
Once mold has been removed, it’s important to take steps to prevent future growth. Moisture control is the key to keeping your home or business safe. Some preventative measures include:
Fixing leaks promptly to prevent water from seeping into walls and floors.
Improving ventilation in high-moisture areas like bathrooms and kitchens.
Using dehumidifiers to control indoor humidity, especially in areas with poor airflow.
Regular inspections of crawl spaces, basements, and other high-risk areas.
These steps, combined with professional mold removal services, will help ensure your property stays mold-free for the long term.
Get Professional Mold Removal with The Mold Guys
If you suspect that mold is affecting your home or business, don’t wait until it becomes a bigger problem. The Mold Guys are ready to help with quick and effective mold removal services in Florida. With hundreds of satisfied customers and a reputation for professionalism, we’re the team you can trust to restore your property to a safe, healthy condition.
Call us today.
Let us help you eliminate mold and bring peace of mind back to your property.

Laminate Flooring: The Perfect Blend of Durability, Style, and Affordability

@parmafloors

Laminate Flooring: Real Wood Appeal with Scratch-Resistant Strength
When it comes to choosing the right flooring for your home or office, laminate flooring stands out as one of the most versatile and practical options available today. Offering a stunning appearance that mimics real wood or stone, laminate provides the best of both worlds—style and durability—at a fraction of the price of traditional materials.
What Makes Laminate Flooring a Top Choice?
Laminate flooring features a multi-layer construction designed to bring together strength, beauty, and performance. The top wear layer is engineered to resist scratches, stains, and fading, making it perfect for high-traffic areas like living rooms, hallways, and kitchens. This protective layer ensures your floors look fresh and vibrant even after years of use.
Underneath the wear layer, a high-resolution design layer gives laminate its realistic wood or stone appearance, offering a sophisticated aesthetic without the maintenance. This layer allows homeowners to enjoy the beauty of natural materials, such as oak, walnut, or marble, at a more affordable price point.
The core of laminate floors is made from a durable, moisture-resistant material, providing enhanced stability and longevity. This core is often made of high-density fiberboard (HDF) or medium-density fiberboard (MDF), which helps absorb impacts and prevents warping. Additionally, many laminate floors feature a moisture-resistant backing that protects against spills and humidity, making them ideal for kitchens, bathrooms, and basements.
Why Laminate Floors Are Perfect for Busy Homes
One of the biggest advantages of laminate flooring is its ability to withstand the demands of busy households. For families with pets, young children, or heavy foot traffic, laminate floors are the perfect solution. Their resistance to scratches, dents, and stains ensures that they continue to look great, even in high-activity areas.
Another key benefit is laminate's low maintenance requirements. Unlike hardwood floors that require refinishing over time, laminate floors only need occasional cleaning with a damp mop or cloth. The surface resists dirt and grime buildup, making it an ideal choice for households with active lifestyles.
The Affordability of Laminate Flooring
When looking for the best laminate flooring, many homeowners are drawn to its affordability without sacrificing quality. Laminate floors offer a premium look—often indistinguishable from real hardwood or stone—at a fraction of the price. Whether you are renovating a single room or outfitting an entire home, laminate provides a cost-effective way to achieve the desired aesthetic.
Additionally, laminate flooring is easy to install, which can further save on installation costs. With click-lock installation systems, many laminate options can be installed by DIY enthusiasts, eliminating the need for professional help.
Ideal for Modern Living
Whether you’re upgrading your living room, bedroom, or kitchen, premium laminate floors offer the perfect combination of style and practicality. They fit seamlessly into any interior design scheme, from traditional to modern, and can be easily customized to suit your unique taste. Moreover, laminate flooring is available in a wide range of styles, colors, and finishes, giving you plenty of options to choose from.
Conclusion: Laminate Flooring as the Smart Choice
In conclusion, laminate flooring offers exceptional durability, beautiful designs, and affordable pricing, making it a smart choice for both residential and commercial spaces. Whether you're upgrading your home or outfitting a high-traffic premium office, laminate provides a reliable, cost-effective solution that combines the best of form and function. For laminate floors that perform in any environment, laminate flooring is truly an excellent investment for modern living.

HB Boost Day Comms 24 March

@FOHWellington

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			"type": "header",
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				"text": ":xeros-connect: Boost Days - What's on this week! :xeros-connect:"
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			"text": {
				"type": "mrkdwn",
				"text": "Morning Ahuriri :wave: Happy Monday, let's get ready to dive into another week with our Xeros Connect Boost Day programme! See below for what's in store :eyes:"
			}
		},
		{
			"type": "divider"
		},
		{
			"type": "header",
			"text": {
				"type": "plain_text",
				"text": ":calendar-date-26: Wednesday, 26th March :camel:",
				"emoji": true
			}
		},
		{
			"type": "section",
			"text": {
				"type": "mrkdwn",
				"text": "\n:coffee: *Café Partnership*: Enjoy coffee and café-style beverages from our cafe partner, *Adoro*, located in our office building *8:00AM - 11:30AM*.\n:wrap: *Lunch*: Provided by *Design Cuisine* from *12:30PM-1:30PM* in the Kitchen."
			}
		},
		{
			"type": "header",
			"text": {
				"type": "plain_text",
				"text": ":calendar-date-27: Thursday, 27th March",
				"emoji": true
			}
		},
		{
			"type": "section",
			"text": {
				"type": "mrkdwn",
				"text": "\n:coffee: *Café Partnership*: Enjoy coffee and café-style beverages from our cafe partner, *Adoro*, located in our office building *8:00AM - 11:30AM*.\n:breakfast: *Breakfast*: Provided by *Roam* from *9:30AM-10:30AM* in the Kitchen.\n:beers: *Social Happy Hour*: Enjoy some drinks and nibbles from *4:00PM-5:30PM* in Clearview."
			}
		},
		{
			"type": "divider"
		},
		{
			"type": "section",
			"text": {
				"type": "mrkdwn",
				"text": "*What else?* Stay tuned to this channel for more details, check out the <https://calendar.google.com/calendar/u/0?cid=eGVyby5jb21fbXRhc2ZucThjaTl1b3BpY284dXN0OWlhdDRAZ3JvdXAuY2FsZW5kYXIuZ29vZ2xlLmNvbQ|*Hawkes Bay Social Calendar*>, and get ready to Boost your workdays!\n\nWX Team :party-wx:"
			}
		}
	]
}

ERPNext Connect with MS-Sql Server on Ubuntu 22.04.5 LTS with Window

@Taimoor

Step:-1. //Create Virtual Environment and Install Dependencies

sudo apt update
sudo apt install python3.10-venv
python3 -m venv venv
source venv/bin/activate

pip install pyodbc requests

Step:-2. //Install ODBC Driver for Microsoft SQL Server

curl https://packages.microsoft.com/keys/microsoft.asc | sudo apt-key add -
curl https://packages.microsoft.com/config/ubuntu/$(lsb_release -rs)/prod.list | sudo tee /etc/apt/sources.list.d/mssql-release.list

sudo apt-get update
sudo ACCEPT_EULA=Y apt-get install -y msodbcsql17 unixodbc-dev
odbcinst -q -d -n "ODBC Driver 17 for SQL Server"

Step:-3. //Configure SQL Server
--Ensure that your SQL Server allows remote connections and
--you can access it from your Ubuntu environment.

// Install ODBC Driver for SQL Server:
sudo apt-get install unixodbc-dev msodbcsql17

Step:-4. //Generate API Key and API Secret for ERPNext
1-Log in to ERPNext as an Administrator.
2-Generate an API Key and Secret by going to User Settings and creating an API key.
3-Save these credentials securely, as you will use them to authenticate the API requests in the script.

Step:-5. //Create a python file and Write the Python Script
Create a Python file called erpnext_sql.py in your desired directory.
You can download or copy the provided code from the Bellow link.
https://www.thiscodeworks.com/embed/66f3fc60f4dcb900149d8681

5.1. //Using nano to Create and Edit the File:
nano erpnext_sql.py
//Copy data from the above link and Configure your API, SQL Setting, and Save it
To save and exit:
Press CTRL + O to save the file.
Press Enter to confirm the filename.
Press CTRL + X to exit nano.

Customize the Python script as necessary to suit your SQL Server data import logic and ERPNext API interactions.

Step:-6. Create a file "last_imported_timestamp.txt"
# Define path to the timestamp file
timestamp_file_path = '/home/erpnext/last_imported_timestamp.txt'
# Default timestamp value
default_timestamp = '2000-01-01 00:00:00'

Step:-7. Run the Python Script Manually
//"python3 file_name"
python3 erpnext_sql.py
-----------------------------

source venv/bin/activate
python3 erpnext_sql.py

to create an abstract class named shape that contains two integers and an empty method named printArea(). Provide three classes named Rectangle, Triangle and Circle such that each one of the classes extends the class Shape. Each one of the classes contains only the method printArea() that prints the area of the given shape

abstract class Shape 
{
 int dimension1;
 int dimension2;
 abstract void printArea();
}
class Rectangle extends Shape 
{
 void printArea() 
 {
 System.out.println("Area of Rectangle: " + (dimension1 * dimension2));
 }
}
class Triangle extends Shape 
{
 void printArea() 
 {
 System.out.println("Area of Triangle: " + (0.5 * dimension1 * dimension2));
 }
}
class Circle extends Shape 
{
 void printArea() 
 {
 System.out.println("Area of Circle: " + (Math.PI * dimension1 * dimension1));
 }
}
class ShapeArea 
{
 public static void main(String[] args) 
 {
 Rectangle rectangle = new Rectangle();
 rectangle.dimension1 = 5;
 rectangle.dimension2 = 4;
 Triangle triangle = new Triangle();
 triangle.dimension1 = 8;
   triangle.dimension2 = 6;

 Circle circle = new Circle();

 circle.dimension1 = 10;

 rectangle.printArea();

 triangle.printArea();

 circle.printArea();

 }

}

to import multiple classes in a user defined package

Addition.java

package mypack1;

public class Addition 

{

 public int add(int a, int b) 

 {

 System.out.println(a + b);

 }

}

Multiplication.java

package mypack1;

public class Multiplication 

{

 public int multiply(int a, int b) 

 {

 System.out.println(a * b);

 }

}

Main Class

import mypack1.Addition;

import mypack1.Multiplication;

public class Demo24

{

public static void main(String[] args) 

{

 Addition obj1 = new Addition();

obj1.add(50,100);

 Multiplication obj2 = new Multiplication();

obj2.multiply(5,6);

 

}

}

Multiple Inheritance with interfaces

interface I1

{ 

void print( ); 

} 

interface I2

{ 

void show( ); 

} 

class A implements I1,I2

{ 

public void print( )

{ 

System.out.println("Hello"); 

} 

public void show( )

{ 

System.out.println("Welcome"); 

} 

}

class Demo12

{

public static void main(String args[ ]) 

{ 

A obj = new A( ); 

obj.print( ); 

obj.show( );

} 

}

Java program to allow method overriding using super.

class Base

{ 

void display( )

{ 

System.out.println("Base Class Method"); 

} 

} 

class Derived extends Base

{ 

void display( )

{ 

System.out.println("Derived Class Method"); 

} 

void show( )

{ 

display( ); 

super.display( ); 

} 

} 

class TestSuper2

{ 

public static void main(String args[ ]) 

{ 

Derived d=new Derived( ); 

d.show( ); 

} 

}

Hierarchical inheritance

class Base

{

 int a=10, b=5, c;

 void add()

 {

 c=a+b;

 System.out.println("c="+c);

 }

}

class Derived1 extends Base

{

 void sub()

 {

 c=a-b;

 System.out.println("c="+c);

 }

}

class Derived2 extends Base

{

 void multiply()

 {

 c=a*b;

 System.out.println("c="+c);

 }

}

class HI

{

 public static void main(String args[])

 {

 Derived1 obj1=new Derived1();

 obj1.add();

 obj1.sub();

 Derived2 obj2=new Derived2();

 obj2.add();

 obj2.multiply();

 }

}

Constructor overloading

public class Person

{

Person ( )

{

System.out.println("Introduction:");

}

Person(String name)

{

System.out.println("Name: " +name);

}

Person(String dept, int rollNo)

{

System.out.println("Department: "+dept+ ", "+"Roll no:"+rollNo);

}

public static void main(String[ ] args)

{

Person p1 = new Person( ); 

Person p2 = new Person("Ravi");

Person p3 = new Person("CSE", 123);

}

}

ARMASTRONG NUMBER Create a Java project using variables, methods and classes. Try debug with a small program of about 10 to 15 lines which consist at least one if else condition and a for loop

public class Demo

{

 public static void main(String[] args) 

 {

 int num = 153, num1, sum = 0;

 num1 = num;

 while (num != 0) 

 {

 int digit = num % 10;

 sum = sum + (digit * digit * digit); 

 num = num/10;

 }

 if (sum == num1) 

 System.out.println(num1 + " is an Armstrong number");

 else

 System.out.println(num1 + " is not an Armstrong number");
   }
}

amaing terminal text edit

@v1ral_ITS

this is a test
#!/bin/bash
dialog --inputbox "What is your username?" 0 0 2> ~/tmp/inputbox.tmp.$$
retval=$?
input=`cat ~/tmp/inputbox.tmp.$$`
rm -f ~/tmp/inputbox.tmp.$$
case $retval in
0)
echo "Your username is '$input'";;
1)
echo "Cancel pressed.";;
esac
############################################################## 
#						             #
# Termux terminal dialog script for downloading music/videos #
#							     #
##############################################################
#!/bin/bash
dialog --inputbox "Type In Folder Destination In SDCARD" 0 0 2> ~/tmp/inputbox.tmp.$$
retval=$?
DST=`cat ~/tmp/inputbox.tmp.$$`
rm -f ~/tmp/inputbox.tmp.$$
dialog --inputbox "URL/mp3-mp4: " 0 0 2> ~/tmp/inputbox.tmp.$$
retval=$?
LRU=`cat ~/tmp/inputbox.tmp.$$`
rm -f ~/tmp/inputbox.tmp.$$
case $retval in
0)
youtube-dl  -i -c --yes-playlist "$LRU" -o "/sdcard/$DST/%(title)s.%(ext)s";;
1)
echo -e "\nv1ral_ITS\nwww.pastebin.com/u/v1ral_ITS\n";;
esac

Scode.html

@Praise

<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <title>Submit a Question</title>
  <link rel="stylesheet" href="Scode.css">
</head>
<body>
  <div class="form-container">
    <h1>Submit a New Question</h1>
    <form id="questionForm">
      <div class="form-group">
        <label for="question">Question:</label>
        <input type="text" id="question" name="question" required>
      </div>
      
      <div class="form-group">
        <label>Answers:</label>
        <div>
          <input type="radio" name="correctAnswer" value="0" required>
          <input type="text" id="answer1" name="answer1" required placeholder="Correct Answer">
        </div>
        <div>
          <input type="radio" name="correctAnswer" value="1">
          <input type="text" id="answer2" name="answer2" required>
        </div>
        <div>
          <input type="radio" name="correctAnswer" value="2">
          <input type="text" id="answer3" name="answer3" required>
        </div>
        <div>
          <input type="radio" name="correctAnswer" value="3">
          <input type="text" id="answer4" name="answer4" required>
        </div>
      </div>
      
      <div class="form-group">
        <label for="category">Category:</label>
        <select id="category" name="category">
          <option value="" disabled selected>Select Category</option>
        </select>
      </div>
      <div class="form-group">
        <label for="newCategory">Or Add New Category:</label>
        <input type="text" id="newCategory" name="newCategory">
      </div>
      <button type="submit">Submit Question</button>
    </form>
  </div>
  <script src="Scode.js"></script>
</body>
</html>

Fiber and Probiotics: Better Together?

@omnibioticlife

Probiotics and fiber are both critical for digestion and can improve common digestive ailments. Dietary fiber comes from plant foods and promotes digestive regularity. Some specialized types of fiber, called prebiotics, provide a food source for gut bacteria and may enhance the effects of probiotics.

Probiotics are beneficial bacteria found in dietary supplements and some foods. Fiber and probiotics can work together to support a healthy, balanced gut microbiome, which is critical for digestive and overall health.

If you suffer from common digestive issues like constipation, gas and bloating, or diarrhea, you may have heard the advice to increase your fiber intake. Consuming adequate dietary fiber can improve your digestion and help with common gastrointestinal ailments.

You may have also heard of using probiotics, live good bacteria, to improve gut health. But what about taking probiotics and fiber together? Certain types of fiber can work in tandem with probiotics to benefit digestive health, and this combination can be a key element of a probiotic and fiber diet.
How Fiber and Probiotics Support One Another
Eating more fiber has been linked to improved digestive and overall health. High-fiber diets can prevent or relieve constipation and also reduce the risk of several chronic diseases. Unfortunately, many of our diets are too low in fiber due to a lack of whole plant foods and an over-reliance on animal products and highly processed foods.

Estimates indicate that 95% of Americans don’t meet the recommended dietary fiber intake of 19-38 grams daily. Western-style diets, including the typical U.S. diet, are also associated with lower diversity of beneficial gut microbes compared to diets higher in fiber from plant foods.

Dietary fiber is typically categorized into soluble and insoluble forms. Both are important for digestive health. Soluble fiber can dissolve in water to form a gel and helps to soften the stool. It also slows nutrient absorption and increases satiety. Insoluble fiber provides bulk for easier passage of stool. Most foods provide a mix of fiber types.
Common types of fiber include:

Insoluble sources: Cellulose, hemicellulose, and lignin, found mainly in vegetables and whole grains.

Soluble sources: Pectin, gums, and mucilages; pectins are found primarily in fruits and vegetables, whereas gums and mucilages are mainly extracted from plants for use in processed foods.
Prebiotics are specific types of soluble fiber that pass undigested through the upper gastrointestinal tract and go on to provide nourishment for the beneficial bacteria in the colon. They can work together with probiotics, a direct source of live beneficial bacteria. Prebiotics act as the food source for our gut bacteria, whereas probiotic supplements deliver live, beneficial bacteria to the gut to support balanced and diverse gut flora.

What are the Benefits of Combining Fiber with Probiotics?

Both probiotics and dietary fiber can be beneficial for digestive health. But what happens when you combine them?
The Role of Probiotics
Probiotics offer many benefits for digestive health, including enhanced digestion, protection against bad bacteria, and a reduction in digestive symptoms like diarrhea and constipation.

Although some foods, such as yogurt, kefir, sauerkraut, kimchi, and kombucha, are cultured with or have added probiotics, not all probiotic foods have enough live bacteria to survive the digestive system to provide health benefits. They may also not have the right combination of strains to have a lasting impact on your gut health.

On the other hand, probiotic supplements typically provide information on the CFU (colony-forming units) per gram of live active microorganisms, which ideally will be 107 to 1011.

Finding a product with multiple strains of beneficial bacteria may be preferable since much of the research on common digestive issues, such as antibiotic-associated diarrhea and symptoms of irritable bowel syndrome, has used multi-strain products.
The Role of Fiber
Adequate fiber intake is critical for digestive health; it keeps your gastrointestinal tract moving and your bowel movements regular and helps prevent chronic conditions.

Increasing your intake of whole plant foods high in fiber, including whole grains, fruits, vegetables, legumes, nuts, and seeds, will provide a variety of insoluble and soluble dietary fibers, along with other crucial nutrients and beneficial plant compounds.

Fiber supplements can be helpful if you’re looking to add a specific fiber source. Some varieties of fiber offer more benefits than others, depending on your health goals.
Combining Probiotics and Fiber
If you’re supplementing both probiotics and additional fiber, it’s typically best to take them separately since some of the beneficial bacteria can adhere to the fiber and be eliminated rather than absorbed.

Prebiotic fibers work with the good bacteria in the digestive system by increasing their numbers and activity, including their ability to support immunity and maintain the gut barrier against harmful pathogens. Prebiotics can also enhance the benefits of probiotics.

It’s preferable not to take probiotics and prebiotic fiber simultaneously because if the probiotics ferment the prebiotics too soon, this can cause bothersome symptoms like abdominal pain and bloating.

Synbiotics designed to be combined are the exception.
Synbiotics are combination products that typically contain probiotics with a prebiotic, most commonly inulin, GOS, or FOS, that supports its beneficial health effects. Research has found that synbiotics can enhance the microbiota, increasing beneficial Bifidobacteria and Lactobacilli.

The goal of a synbiotic is to maximize the health impact of both the good bacteria and the prebiotic fiber by providing them together. The amount of fiber in synbiotics varies, from very small quantities to larger amounts. Look for products that provide an optimal blend of probiotics with prebiotics.

Omni-Biotics’ probiotic products are all synbiotics. Each Omni-Biotic probiotic contains prebiotic nutrients specifically selected for the probiotic strains in the formulation. These prebiotic fibers act as the food source for the specific probiotic bacteria in the Omni-Biotic powder. When Omni-Biotic probiotics are dissolved in water prior to intake, the probiotic bacteria rehydrate and consume these prebiotic fibers. This makes them strong for their passage through the GI tract, ensuring they arrive in the intestine alive and metabolically active.
Is it Better to Take Prebiotics or Another Kind of Fiber?
Although all prebiotics are considered fiber, not all dietary fibers have prebiotic effects.
The benefits of prebiotics for digestion go beyond those of standard fiber since they nourish beneficial bacteria, leading to a healthier, more balanced gut microbiome.

Though humans have been consuming prebiotics in food since prehistoric times, research has uncovered their health benefits much more recently. Well-studied prebiotics include inulin, galactooligosaccharides (GOS), fructooligosaccharides (FOS), and resistant starch.

Prebiotics are found naturally in some plant foods like chicory, artichokes, asparagus, onions, garlic, whole wheat, oats, and barley, as well as in some processed foods with added prebiotics. They are also available as supplements.
Prebiotics target good bacteria in the colon, particularly Bifidobacteria. Research has found that consumption of the prebiotics inulin, FOS, resistant starch, and GOS significantly increased levels of Bifidobacteria and other beneficial gut bacteria.

The benefits to gut flora are specific to fiber with prebiotic effects. A recent analysis of randomized controlled trials found that prebiotic fiber supplements lead to significantly higher counts of Bifidobacteria and Lactobacilli than non-prebiotic fiber supplements.

In addition to enhancing their diversity and activity, prebiotics can increase the gut bacteria’s production of short-chain fatty acids. These acids are critical in supporting the gut barrier and lowering colon pH. In turn, this promotes the growth of beneficial bacteria and inhibits gut pathogens. Enhanced production of short-chain fatty acids ensures adequate absorption of fluids and electrolytes in the colon and promotes intestinal motility.

Some prebiotics are more easily digested than others. Some, such as inulin and fructooligosaccharides, may not be well tolerated in larger doses and can cause digestive side effects such as gas, bloating, and diarrhea.

These symptoms may be temporary as your digestive tract adapts. To limit digestive upset, increase new fiber sources slowly and drink plenty of water to help move the fiber through your system.

There are various prebiotic supplements available. Since different prebiotics affect different strains of good bacteria, it’s optimal to take in a variety of prebiotics. A mixture of prebiotics may also most effectively support the beneficial actions of gut bacteria, like the production of short-chain fatty acids.

Omni-Biotic offers two different prebiotic options containing various beneficial fiber sources to meet your individual needs.
Fiber vs. Probiotics for Constipation

Constipation, infrequent or difficult bowel movements, often of small, hard stools, is a common problem affecting both adults and children.

A lack of fiber and fluids can lead to constipation. Increasing fiber intake adds bulk and fluids to stool, making them softer and leading to easier passage and improved regularity.

Insoluble fibers, such as those found in whole grains, vegetables, beans, nuts, and fruits, are most effective for adding bulk to stool. For fiber supplements, however, experts frequently recommend soluble fibers such as psyllium for constipation and irritable bowel syndrome due to their ability to hold fluid and lead to softer stools.

Patients with constipation have been found in some studies to have lower levels of beneficial Bifidobacteria and Lactobacilli. Several studies providing various species of Bifidobacteria probiotics found that they improved subjects’ constipation.

Prebiotic inulin has also been found to relieve constipation in some studies with adults and children. Additionally, several synbiotics with various combinations of Bifidobacteria, Lactobacilli, and the prebiotic fibers FOS, GOS, and inulin have also been found to improve constipation.

Omni-Biotic Balance is a synbiotic with multiple strains of beneficial bacteria selected to optimize digestion and reduce constipation. It includes species found to support the protective gut barrier, enhancing its mucus production and improving gut motility. It also provides small amounts of the prebiotics FOS and inulin to enhance its effects.
Fiber vs. Probiotics for Diarrhea

Diarrhea can have many causes, some acute such as infections, food poisoning, or traveler’s diarrhea, and some chronic, including food intolerances or chronic gastrointestinal conditions.

Probiotics, particularly Bifidobacteria and Lactobacilli species, have been found to improve infectious diarrhea, possibly due to their ability to fight off gastrointestinal pathogens by maintaining the gut barrier and enhancing immunity.

In addition, some probiotic strains have been associated with a reduced risk of antibiotic-associated diarrhea. Containing 10 species of Lactobacilli and Bifidobacteria, Omni-Biotic AB 10 significantly reduced the risk of antibiotic-associated diarrhea in two separate studies in surgical patients and nursing home residents.

Some prebiotics can also help ward off diarrhea due to GI pathogens. Research has found that supplements of the prebiotic fibers GOS and inulin significantly reduced the risk of diarrhea in travelers to high-risk areas.

Combining probiotics and beneficial prebiotics may be especially effective for combatting certain types of diarrhea. In one study, adding prebiotic inulin to a strain of Bifidobacteria improved the resolution of infectious diarrhea in children. Research has also found that synbiotics prevented traveler’s diarrhea.
Fiber vs. Probiotics for Optimized Digestion
Gas and bloating
are common symptoms of several common gastrointestinal conditions, including
irritable bowel syndrome (IBS)
, small intestinal bacterial overgrowth (SIBO), constipation, and dietary intolerance. They can indicate an imbalance in the gut microbiome.

A
lack of regularity
resulting in constipation, diarrhea, or both, as can sometimes occur with IBS, can also indicate that your gut health is out of balance.

Probiotics and fiber can both play a part in reducing common gastrointestinal ailments and supporting a healthy gut.

Probiotics for Digestion
Various strains of both Bifidobacteria and Lactobacilli have been associated with improved microbial balance and better digestive health, including better regularity and a reduction in constipation, bloating, and other symptoms of irritable bowel syndrome.

A synbiotic composed of Lactobacillus, Bifidobacterium, and FOS was found to reduce digestive symptoms of lactose intolerance in one small study.
Prebiotics for Digestion
Research indicates that the prebiotics inulin and FOS can improve bowel regularity and gut barrier function. In some studies, prebiotic GOS supplements reduced some of the symptoms of patients with IBS.

Research has found that acacia fiber, a soluble fiber also known as gum arabic, may have prebiotic properties and can increase beneficial Lactobacilli and Bifidobacteria and their production of short-chain fatty acids. One study of patients with irritable bowel syndrome found that yogurt with acacia fiber and a strain of Bifidobacteria reduced their symptoms.

Omni-Biotic offers two prebiotic product options; Omni-Logic Immune provides acacia fiber and resistant starch, while Omni-Logic Plus provides FOS, GOS, and glucomannan.

The non-digestible fibers in prebiotics can cause side effects in sensitive individuals, including those with irritable bowel syndrome or other gastrointestinal conditions. If you have a chronic digestive condition, consult your healthcare provider or registered dietitian before trying new fiber sources or probiotics.

Sjf

@ccc

#include<stdio.h>
int main()
{
int max[10][10],need[10][10],alloc[10][10],avail[10],work[10];
int p,r,i,j,process,flag,executed=0,canExecute;
char finish[10];
printf("\nEnter the no. of processes and resources:");
scanf("%d%d",&p,&r);

 //Input Max matrix
printf("\nEnter the Max Matrix for each process:");
for(i=0;i<p;i++)
{
for(j=0;j<r;j++)
scanf("%d",&max[i][j]);
}
// Input Allocation Matrix
printf("\nEnter the allocation for each process:");
for(i=0;i<p;i++)
{
for(j=0;j<r;j++)
scanf("%d",&alloc[i][j]);
}
// Input Available Resources after allocation
printf("\n\n Enter the Available Resources:");
for(i=0;i<r;i++)
scanf("%d",&avail[i]);
// Calculation of Need Matrix
for(i=0;i<p;i++)
{
printf("\n");
for(j=0;j<r;j++)
{
need[i][j]=max[i][j]-alloc[i][j];
printf("%d",need[i][j]);
}
printf("\t\t");
}
for(i=0;i<p;i++)
finish[i]='F';
for(j=0;j<r;j++)
work[j]=avail[j];
printf("\nSafe Sequence: ");
   while (executed < p) {
       flag = 0;
 
       for (i = 0; i < p; i++) {
           if (finish[i] == 'F') {
                canExecute = 1;
               
               // Check if need can be satisfied
               for (j = 0; j < r; j++) {
                   if (need[i][j] > work[j]) {
                       canExecute = 0;
                       break;
                   }
               }
 
               if (canExecute) {
                   // Process can execute
                   printf("P%d ", i);
                   for (j = 0; j < r; j++)
                       work[j] += alloc[i][j];
 
                   finish[i] = 'T';
                   executed++;
                   flag = 1;
               }
           }
       }
 
       // If no process is executed in an iteration, break (unsafe state)
       if (flag == 0) {
           printf("\nSystem is in an unsafe state!");
           return 1;
       }
   }
 
   printf("\nSystem is in a safe state.");
   return 0;
}

Round robin

#include<stdio.h>

int main()

{

int i,n,count=0,time_quantum,t,at[10],bt[10],rem_bt[10],wt[10],tat[10],flag=0,t=0;

floattotal_wt=0 , total_tat=0

printf("Enter Total Process:\t ");

scanf("%d",&n);

for(i=0;i<n;i++)

{

printf("Enter Burst Time for Process %d :",i+1);

scanf("%d",&bt[i]);

}

printf("Enter Time Quantum:\t");

scanf("%d",&time_quantum);

for (i = 0 ; i < n ; i++) 

        rem_bt[i] =  bt[i]; 

// Keep traversing processes in round robin manner  until all of them are not done. 

while (1) 

{ 

flag=1; 

// Traverse all processes one by one repeatedly 

for (i = 0 ; i < n; i++) 

{ 

// If burst time of a process is greater than 0 then only need to process further 

if (rem_bt[i] > 0) 

{ 

flag=0; // There is a pending process 

		if (rem_bt[i] > time_quantum) 

		{ 

	// Increase the value of t i.e. shows how much time a process has been processed 

	t += time_quantum; 

		// Decrease the burst_time of current process by quantum 

		rem_bt[i] -= time_quantum;

		} 

// If burst time is smaller than or equal to quantum. Last cycle for this process 

else

{ 

// Increase the value of t i.e. shows how much time a process has been processed 

		t = t + rem_bt[i]; 

		 // Waiting time is current time minus time used by this process 

		wt[i] = t - bt[i]; 

		// As the process gets fully executed make its remaining burst time = 0

		 rem_bt[i] = 0;

}

}

}

if (flag==1)

break;

} 

for (i = 0; i < n ; i++)

	tat[i] = bt[i] + wt[i];

printf("\n Process BT\t WT\t TAT \n");

for(i=0;i<n;i++)

printf("\n %d \t %d \t %d \t %d \t",i+1,bt[i],wt[i],tat[i]);

for (i = 0; i < n ; i++)

{

total_wt= total_wt+wt[i];

total_tat= total_tat+tat[i];

}

printf("\nAverage waiting time = %f", total_wt/n);

printf ("\nAverage turn around time = %f",total_tat/n);

}

Sjf

#include<stdio.h>

#include<conio.h>

#define max 30

void main()

{

Int i,j,n,t,p[max],bt[max],wt[max],tat[max],Total_wt=0,Total_tat=0;

float awt=0,atat=0;

printf("Enter the number of processes\n");

scanf("%d",&n);

//Enter the processes according to their arrival times

for(i=0;i<n;i++)

{

printf("Enter the process number\n");

scanf("%d",&p[i]);

printf("Enter the burst time of the process\n");

scanf("%d",&bt[i]);

}

//Apply the bubble sort technique to sort the processes according to their burst times

for(i=0;i<n;i++)

{

	for(j=0;j<n-i-1;j++)

	{

		if(bt[j]>bt[j+1])

		{

// Sort according to the burst times

		t=bt[j];

		bt[j]=bt[j+1];

		bt[j+1]=t;

		//Sorting Process Numbers

		t=p[j];

		p[j]=p[j+1];

		p[j+1]=t;

		}

	}

}

printf("Process\t Burst Time\t Waiting Time\t Turn Around Time\n");

for(i=0;i<n;i++)

{

	wt[i]=0;

	tat[i]=0;

	for(j=0;j<i;j++)

		wt[i]=wt[i]+bt[j];

	tat[i]=wt[i]+bt[i];

	Total_wt=Total_wt +wt[i];

	Total_tat=Total_tat+tat[i];

	printf("%d\t %d\t\t %d\t\t %d\n",p[i],bt[i],wt[i],tat[i]);

}

awt=(float)Total_wt /n;

atat=(float)Total_tat /n;

printf("The average waiting time =  %f\n",awt);

printf("The average turn aroud time = %f\n",atat);

}

Round robin

#include<stdio.h>

int main()

{

int i,n,count=0,time_quantum,t,at[10],bt[10],rem_bt[10],wt[10],tat[10],flag=0,t=0;

floattotal_wt=0 , total_tat=0

printf("Enter Total Process:\t ");

scanf("%d",&n);

for(i=0;i<n;i++)

{

printf("Enter Burst Time for Process %d :",i+1);

scanf("%d",&bt[i]);

}

printf("Enter Time Quantum:\t");

scanf("%d",&time_quantum);

for (i = 0 ; i < n ; i++) 

        rem_bt[i] =  bt[i]; 

// Keep traversing processes in round robin manner  until all of them are not done. 

while (1) 

{ 

flag=1; 

// Traverse all processes one by one repeatedly 

for (i = 0 ; i < n; i++) 

{ 

// If burst time of a process is greater than 0 then only need to process further 

if (rem_bt[i] > 0) 

{ 

flag=0; // There is a pending process 

		if (rem_bt[i] > time_quantum) 

		{ 

	// Increase the value of t i.e. shows how much time a process has been processed 

	t += time_quantum; 

		// Decrease the burst_time of current process by quantum 

		rem_bt[i] -= time_quantum;

		} 

// If burst time is smaller than or equal to quantum. Last cycle for this process 

else

{ 

// Increase the value of t i.e. shows how much time a process has been processed 

		t = t + rem_bt[i]; 

		 // Waiting time is current time minus time used by this process 

		wt[i] = t - bt[i]; 

		// As the process gets fully executed make its remaining burst time = 0

		 rem_bt[i] = 0;

}

}

}

if (flag==1)

break;

} 

for (i = 0; i < n ; i++)

	tat[i] = bt[i] + wt[i];

printf("\n Process BT\t WT\t TAT \n");

for(i=0;i<n;i++)

printf("\n %d \t %d \t %d \t %d \t",i+1,bt[i],wt[i],tat[i]);

for (i = 0; i < n ; i++)

{

total_wt= total_wt+wt[i];

total_tat= total_tat+tat[i];

}

printf("\nAverage waiting time = %f", total_wt/n);

printf ("\nAverage turn around time = %f",total_tat/n);

}

Producer cons

#include <stdio.h>
#include <stdlib.h>

int full = 0, empty = 3, x = 0;

void producer();
void consumer();
int wait(int);
int signal(int);

int main() {
    int n;
    
    printf("1. PRODUCER\n2. CONSUMER\n3. EXIT\n");
    
    while (1) {
        printf("ENTER YOUR CHOICE\n");
        scanf("%d", &n);
        
        switch (n) {
            case 1:
                if (empty != 0)
                    producer();
                else
                    printf("BUFFER IS FULL\n");
                break;
                
            case 2:
                if (full != 0)
                    consumer();
                else
                    printf("BUFFER IS EMPTY\n");
                break;
                
            case 3:
                exit(0);
                break;
        }
    }
}

int wait(int s) {
    return (--s);
}

int signal(int s) {
    return (++s);
}

void producer() {
    full = signal(full);
    empty = wait(empty);
    x++;
    printf("In Producer: Produces the item %d\n", x);
}

void consumer() {
    full = wait(full);
    empty = signal(empty);
    printf("In Consumer: Consumes item %d\n", x);
    x--;
}

SJF

#include<stdio.h>

#include<conio.h>

#define max 30

void main()

{

Int i,j,n,t,p[max],bt[max],wt[max],tat[max],Total_wt=0,Total_tat=0;

float awt=0,atat=0;

printf("Enter the number of processes\n");

scanf("%d",&n);

//Enter the processes according to their arrival times

for(i=0;i<n;i++)

{

printf("Enter the process number\n");

scanf("%d",&p[i]);

printf("Enter the burst time of the process\n");

scanf("%d",&bt[i]);

}

//Apply the bubble sort technique to sort the processes according to their burst times

for(i=0;i<n;i++)

{

	for(j=0;j<n-i-1;j++)

	{

		if(bt[j]>bt[j+1])

		{

// Sort according to the burst times

		t=bt[j];

		bt[j]=bt[j+1];

		bt[j+1]=t;

		//Sorting Process Numbers

		t=p[j];

		p[j]=p[j+1];

		p[j+1]=t;

		}

	}

}

printf("Process\t Burst Time\t Waiting Time\t Turn Around Time\n");

for(i=0;i<n;i++)

{

	wt[i]=0;

	tat[i]=0;

	for(j=0;j<i;j++)

		wt[i]=wt[i]+bt[j];

	tat[i]=wt[i]+bt[i];

	Total_wt=Total_wt +wt[i];

	Total_tat=Total_tat+tat[i];

	printf("%d\t %d\t\t %d\t\t %d\n",p[i],bt[i],wt[i],tat[i]);

}

awt=(float)Total_wt /n;

atat=(float)Total_tat /n;

printf("The average waiting time =  %f\n",awt);

printf("The average turn aroud time = %f\n",atat);

}

Producer consumer

#include <stdio.h>

#include <stdlib.h>

int full = 0, empty = 3, x = 0;

void producer();

void consumer();

int wait(int);

int signal(int);

int main() {

    int n;

    

    printf("1. PRODUCER\n2. CONSUMER\n3. EXIT\n");

    

    while (1) {

        printf("ENTER YOUR CHOICE\n");

        scanf("%d", &n);

        

        switch (n) {

            case 1:

                if (empty != 0)

                    producer();

                else

                    printf("BUFFER IS FULL\n");

                break;

                

            case 2:

                if (full != 0)

                    consumer();

                else

                    printf("BUFFER IS EMPTY\n");

                break;

                

            case 3:

                exit(0);

                break;

        }

    }

}

int wait(int s) {

    return (--s);

}

int signal(int s) {

    return (++s);

}

void producer() {

    full = signal(full);

    empty = wait(empty);

    x++;

    printf("In Producer: Produces the item %d\n", x);

}

void consumer() {

    full = wait(full);

    empty = signal(empty);

    printf("In Consumer: Consumes item %d\n", x);

    x--;

}

Producer consumer

#include <stdio.h>

#include <stdlib.h>

int full = 0, empty = 3, x = 0;

void producer();

void consumer();

int wait(int);

int signal(int);

int main() {

    int n;

    

    printf("1. PRODUCER\n2. CONSUMER\n3. EXIT\n");

    

    while (1) {

        printf("ENTER YOUR CHOICE\n");

        scanf("%d", &n);

        

        switch (n) {

            case 1:

                if (empty != 0)

                    producer();

                else

                    printf("BUFFER IS FULL\n");

                break;

                

            case 2:

                if (full != 0)

                    consumer();

                else

                    printf("BUFFER IS EMPTY\n");

                break;

                

            case 3:

                exit(0);

                break;

        }

    }

}

int wait(int s) {

    return (--s);

}

int signal(int s) {

    return (++s);

}

void producer() {

    full = signal(full);

    empty = wait(empty);

    x++;

    printf("In Producer: Produces the item %d\n", x);

}

void consumer() {

    full = wait(full);

    empty = signal(empty);

    printf("In Consumer: Consumes item %d\n", x);

    x--;

}

Fcfs